Page 1 of 244 Project Number: 318023 Project acronym

Transcription

Project Number:
318023
Project acronym:
SmartC2Net
Project title:
Contract type:
Smart Control of Energy Distribution Grids over Heterogeneous
Communication Networks
Collaborative project (STREP)
Deliverable number:
D1.1 - version 2
Deliverable title:
Work package:
SmartC2Net Use Cases, Preliminary Architecture and Business
Drivers
WP1 -Use Cases and Architecture
Due date of deliverable:
M22 – September 2014
Actual submission date:
30/09/2014
Start date of project:
01/12/2012
Duration:
36 months
Editor(s):
Giovanna Dondossola, Roberta Terruggia (RSE)
Authors:
Giovanna Dondossola (RSE), Roberta Terruggia (RSE)
S. Bessler (FTW), J. Grønbæk (FTW), P. Zwickl (FTW), R. Løvenstein
Olsen (AAU), F. Iov (AAU), Ch. Haegerling (TUDO), F. Kurtz (TUDO), D.
Iacono (RT), A. Bovenzi (RT), S. Marzorati (VO), A. Carrapatoso
(EFACEC)
FTW Forschungszentrum Telekommunikation Wien (FTW), Aalborg
University (AAU), Technische Universität Dortmund / Communications
Networks Institute (TUDO), ResilTech S.R.L. (RT), Ricerca Sul Sistema
Energetico (RSE), Vodafone Omnitel N.V. (VO), Efacec Engenharia e
Sistemas SA (EFACEC)
Contributing partners:
Dissemination Level of this Deliverable:
PU
Public
Restricted to other programme participants (including the Commission Services)
Restricted to a group specified by the consortium (including the Commission Services)
Confidential, only for members of the consortium (including the Commission Services)
PU
PP
RE
C0
This project has received funding from the European Union’s Seventh Framework Programme for
research, technological development and demonstration under grant agreement no 318023. Further
information is available at www.SmartC2Net.eu.
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FP7-ICT-318023/ D1.1 ver 2
Introductory note:
Following the first review meeting and the comments received, changes within the updated version 2
have been made in the following sections (notwithstanding the correction of a few minor details in
other places):






Section Executive Summary
Section 1
Introduction: from SmartC2Net UC to the overall architecture
Section 2
The Use Cases and their key elements (Intro)
Section 5
UC ICT requirements & success KPI (All subsections)
Section 11
Annex C - Table of Requirements (All subsections)
Section 12
Annex D - Table of KPIs (All subsections)
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FP7-ICT-318023/ D1.1 ver 2
Executive Summary
The SmartC2Net project addresses different control scenarios related to the evolution of the
distribution grids. In order to provide a good coverage of the control applications characterizing the
evolution of European smart grids in the next future, the following four use cases are analyzed in
detail:
• Voltage Control in Medium Voltage Grids
• External Generation Site
• Automated Meter Reading and Customer Energy Management Systems
• Electrical Vehicle Charging in Low Voltage Grids.
Starting from the analysis of these use cases a preliminary global high level architecture is derived at
the aim of highlighting the interactions among the respective control components and ICT networks.
An economic analysis of the use case scenarios is performed for getting the specific business drivers
and business requirements of the envisaged smart grid evolution.
Most outcome from the UC analysis and the overall architecture have provided inputs to the
monitoring, communication, control, evaluation and test bed activities undertaken by the other
project work packages.
The requirements and the Key Performance Indicators (KPIs), initially determined from the use case
analysis, will be used along the whole project running for the evaluation of the SmartC2Net
achievements.
This second version of the deliverable addresses the comments coming from the first review in
Brussels.
First of all the motivations for the four use case selection are better highlighted in the introduction
and in the Use Case chapter (Chapter 2).
The Requirements and KPIs definition and analysis have been improved with the quantitative values
and the mapping with related WPs. The aim is to point out which of the Requirements and KPIs are
addressed by the project developments and how they are evaluated.
As a means to highlight the more relevant elements for the project developments, the priority field
of the requirement template is used and a reduced number of requirements and KPIs has been
focused. This work is reflected in Chapter 11 Annex C and Chapter 12 Annex D, that now provide the
list of enhanced requirements and KPIs presented in a more readable way, and in their enriched
analysis reported in Chapter 5.
Given its relevance to the SmartC2Net exploitation plan, the business analysis have been elaborated
further in deliverable D7.2 where the business drivers and benefits have been linked to the use case
KPIs from SmartC2Net.
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Table of Contents
List of Figures........................................................................................................................................... 7
List of Tables .......................................................................................................................................... 10
Glossary ................................................................................................................................................. 11
1 Introduction: from SmartC2Net UC to the overall architecture ................................................... 13
2 The Use Cases and their key elements .......................................................................................... 15
2.1
Voltage Control in Medium Voltage Grid............................................... 16
2.2
External Generation Site ........................................................................ 17
2.3
Automated Meter Reading (AMR) and Customer Energy Management
Systems (CEMS)
19
2.4
Electrical Vehicle Charging in Low Voltage Grids ................................... 21
3 The business drivers ...................................................................................................................... 24
3.1
Business Drivers ..................................................................................... 24
3.1.1
Telco Sector ............................................................................................ 24
3.1.2
Categories .............................................................................................. 27
3.1.3
Use cases ................................................................................................ 32
3.2
Business Requirements .......................................................................... 38
3.2.1
Telco and energy sector interplay.......................................................... 39
3.2.2
Template ................................................................................................ 39
3.2.3
Use cases ................................................................................................ 43
4 UC details....................................................................................................................................... 49
4.1
Voltage Control in Medium Voltage Grid............................................... 49
4.1.1
Objective ................................................................................................ 49
4.1.2
Architecture and Sequence Diagrams.................................................... 51
4.1.3
Fault/threat analysis/scenarios.............................................................. 53
4.2
External generation site ......................................................................... 56
4.2.1
Objective ................................................................................................ 56
4.2.2
Control of assets .................................................................................... 59
4.2.3
Network adaptive data transport (AN/WAN) ........................................ 59
4.2.4
4.3
Systems (CEMS)
63
4.3.1
Objective ................................................................................................ 63
4.3.2
4.3.3
4.4
Electrical Vehicle Charging in Low Voltage Grids ................................... 70
4.4.1
Objective ................................................................................................ 70
4.4.2
4.4.3
5 UC ICT requirements & success KPI............................................................................................... 78
5.1
Requirement Template .......................................................................... 78
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5.2
Requirements ......................................................................................... 80
5.3
KPIs Template......................................................................................... 84
5.4
Key Performance Indicators (KPIs) ......................................................... 85
6 Preliminary overall architecture .................................................................................................... 88
6.1
Global architecture ................................................................................ 89
6.1.1
Layered architecture .............................................................................. 89
6.1.2
Distribution of functions ........................................................................ 90
6.2
Use Case mapping .................................................................................. 91
7 Conclusions and Outlook ............................................................................................................... 95
8 Bibliography................................................................................................................................... 96
9 Annex A - Value Networks ............................................................................................................. 98
9.1
Electrical Grid Value Network ................................................................ 98
9.1.1
Entities ................................................................................................. 100
9.1.2
Main Value Flows ................................................................................. 101
9.2
SmartC2Net Value Network ................................................................. 102
9.2.1
Entities (Revised).................................................................................. 104
9.2.2
Main Value Flows (Revised) ................................................................. 107
10
Annex B - UC templates ....................................................................... 109
10.1
USE CASE NAME: Medium Voltage Control ......................................... 109
10.1.1
Description of the Use Case ................................................................. 109
10.1.2
Diagrams of Use Case........................................................................... 112
10.1.3
Technical Details .................................................................................. 120
10.1.4
Step by Step Analysis of Use Case ........................................................ 125
10.1.5
Information Exchanged ........................................................................ 133
10.1.6
Common Terms and Definitions .......................................................... 134
10.2
USE CASE NAME: Electrical Vehicle Charging in Low Voltage Grids .... 135
10.2.1
10.2.2
10.2.3
10.2.4
10.2.5
10.2.6
10.3
USE CASE NAME: External generation site .......................................... 160
10.3.1
10.3.2
10.3.3
10.3.4
10.3.5
10.3.6
10.4
USE CASE NAME: Automated Meter Reading (AMR) and Customer
Energy Management Systems (CEMS) ............................................................................................ 178
10.4.1
10.4.2
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10.4.3
10.4.4
10.4.5
10.4.6
11
11.1
11.2
11.3
11.4
12
12.1
12.2
12.3
12.4
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Annex C - Table of Requirements......................................................... 217
Requirements for Medium Voltage Control Use Case ......................... 217
Requirements for EV Charging Use Case ............................................. 223
Requirements for External Generation Use Case ................................ 226
Requirements for AMR and CEMS Use Case ........................................ 231
Annex D - Table of KPIs ........................................................................ 237
Key Performance Indicators for Medium Voltage Control Use Case ... 237
Key Performance Indicators for EV charging Use Case ........................ 240
Key Performance Indicators for External Generation Use Case .......... 242
Key Performance Indicators for AMR and CEMS Use Case .................. 243
FP7-ICT-318023/ D1.1 ver 2
List of Figures
Figure 1 Overview of Medium Voltage Control Use Case ..................................................................... 16
Figure 2 Overview of External Generation Site Use Case ..................................................................... 18
Figure 3: Advanced Smart Meter Reading and Customer Energy Management System Scenario ....... 20
Figure 4 Overview of the EV Use Case .................................................................................................. 23
Figure 5 M2M device connections, energy and utility sector, worldwide, 2011–2021 [ANME12] ...... 25
Figure 6 – A categorisation of generic business drivers ........................................................................ 28
Figure 7 – A categorisation of business requirements .......................................................................... 39
Figure 8 - The Medium Voltage Control Function ................................................................................. 50
Figure 9 The UC Architecture ................................................................................................................ 51
Figure 10 Voltage Control – Communications ...................................................................................... 52
Figure 11 Medium Voltage Control Sequence Diagram ....................................................................... 53
Figure 12 Possible attack scenarios to the Voltage Control function ................................................... 54
Figure 13 Estimated RES Power per Substation (2020)......................................................................... 55
Figure 14: Overview of external generation site use case .................................................................... 57
Figure 15: Overview of use cases – and fault/error cases. ................................................................... 58
Figure 16 Components distributed in the external grid operation case ............................................... 60
Figure 17 Functionalities in the external grid operation case ............................................................... 61
Figure 18 Overview of the sequence diagram for normal operation mode, capturing Control of Assets
and Data Transport. The specific fault/error cases can be seen in Annex B. ....................................... 62
Figure 19 Physical components of the use case and their locations in the Smart Grid setup .............. 64
Figure 20 Detailed use case clustering structure .................................................................................. 65
Figure 21 Mis-use diagrams for the considered CEMS functionalities.................................................. 67
Figure 22: Mis-sequence diagram for the MIM attack.......................................................................... 69
Figure 23 Networks of the EV use case ................................................................................................. 72
Figure 24 Overview of the interactions between components ............................................................ 73
Figure 37 Requirements: Project WP mapping ..................................................................................... 80
Figure 38 Requirements: WP2, WP3 and WP4 mapping
Figure 39 Requirements: WP5 and WP6
mapping................................................................................................................................................. 81
Figure 25 Requirements: Use Case........................................................................................................ 81
Figure 26 Requirements: Category ........................................................................................................ 82
Figure 27 Requirements: Level .............................................................................................................. 82
Figure 28 Requirements: Priority .......................................................................................................... 82
Figure 29 MVC UC Requirements: Category
Figure 30 MVC UC Requirements: Level ........... 83
Figure 31 EV UC Requirements: Category
Figure 32 EV UC Requirements: Level ........... 83
Figure 33 EGS UC Requirements: Category
Figure 34 EGS UC Requirements: Level .......... 83
Figure 35 CEMS AMR UC Requirements: Category Figure 36 CEMS AMR UC Requirements: Level . 84
Figure 40 KPIs: Project WP mapping ..................................................................................................... 85
Figure 41 WP2, WP3 and WP4 mapping
Figure 42 WP5 and WP6 mapping.......... 86
Figure 43 KPIs: Use Case........................................................................................................................ 86
Figure 44 KPIs: Scope............................................................................................................................ 87
Figure 45 KPIs: Category ........................................................................................................................ 87
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FP7-ICT-318023/ D1.1 ver 2
Figure 46 MVC UC KPIs: Category
Figure 47 MVC UC KPIs: Scope ...................... 87
Figure 48 EV UC KPIs: Scope
Figure 49 EV UC KPIs: Category ..................... 88
Figure 50 EGS UC KPIs: Scope
Figure 51 EGS UC KPIs: Category ............. 88
Figure 52 CEMS AMR UC KPIs: Scope
Figure 53 CEMS AMR UC KPIs: Category ... 88
Figure 54 Overview of the SG architecture ........................................................................................... 90
Figure 55 Overview of Use Cases mapping ........................................................................................... 92
Figure 56 Detailed view of Use Cases mapping..................................................................................... 93
Figure 57: “Classical” Electrical Grid Value Network............................................................................. 99
Figure 58 – SmartC2Net Value Network (with special consideration of chosen use cases) ............... 103
Figure 59 - Voltage Control ................................................................................................................. 113
Figure 60 - Voltage Control - Actors Interactions ................................................................................ 113
Figure 61 - Voltage Control - Use Case Diagram ................................................................................. 114
Figure 62 - Voltage Control - Use Case Diagram - attack scenarios .................................................... 114
Figure 63 - Voltage Control – Mapping on SGAM ............................................................................... 115
Figure 64 - Voltage Control - Overview of involved communications ................................................ 115
Figure 65 – Voltage Control – Communications.................................................................................. 116
Figure 66 – Voltage Control - Component Layer ................................................................................. 116
Figure 67 - Generation Forecast .......................................................................................................... 117
Figure 68 - Generation Forecast - Sequence Diagram ........................................................................ 117
Figure 69 – Voltage Control - Sequence Diagram ............................................................................... 118
Figure 70 - Voltage Control - DoS Attack to DER ................................................................................. 118
Figure 71 - Voltage Control - DoS Attack to MVGC ............................................................................. 119
Figure 72 - Voltage Control - Fake DER Set point ................................................................................ 119
Figure 73 - Voltage Control - Fake DER Set point (Man in the Middle)............................................... 120
Figure 74 - Voltage Control - Fake TSO signal ..................................................................................... 120
Figure 75 Use case components and Networking Connectivity Options ............................................ 139
Figure 76 - Use Case Diagram for EV charging scenario ...................................................................... 140
Figure 77 - Message Sequence Diagram for EV charging scenario ..................................................... 141
Figure 78 - Use Case Diagram for energy and power management scenario ..................................... 142
Figure 79 - Message Sequence Diagram for energy and power management scenario .................... 143
Figure 80 - Use Case Diagram for Energy Market scenario ................................................................. 144
Figure 81 - Message Sequence Diagram for Energy Market Scenario ................................................ 145
Figure 82 - SGAM Function Layer ........................................................................................................ 146
Figure 83 – AS3 Metering information interrupted ............................................................................ 146
Figure 84 – AS2 LVGC-CSO connection interrupted ............................................................................ 147
Figure 85: Diagram of the Interactions described in section 4.1 ........................................................ 148
Figure 86 Overview of Use Case .......................................................................................................... 162
Figure 87 Overview of use cases ......................................................................................................... 164
Figure 88 Set of physical components and their locations in the smart grid setup ............................ 165
Figure 89 Different communication means used for the various components to interact with each
other .................................................................................................................................................... 166
Figure 90 Different functionalities used in the system in order to be able to execute the use cases
over the network on the different physical components ................................................................... 167
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Figure 91: Advanced Smart Meter Reading and Customer Energy Management System Scenario ... 186
Figure 92: Physical components of the use case and their locations in the Smart Grid setup ........... 187
Figure 93: Detailed use case clustering structure ............................................................................... 188
Figure 94: MM.01 Obtain meter reading on demand (refer to [4]) .................................................... 189
Figure 95: Sequence diagram MM.01.01 - Obtain remote meter reading on demand (refer to [4]) . 189
Figure 96: Sequence diagram MM.01.02 - Obtain walk-by meter reading on demand (refer to [4]) 190
Figure 97: MM.02 Obtain scheduled meter reading (refer to [5]) ...................................................... 190
Figure 98: Sequence diagram MM.02.01 - Obtain scheduled meter reading (refer to [5]) ................ 190
Figure 99: Sequence diagram MM.02.02 - Configure reading schedule (refer to [5]) ........................ 191
Figure 100: MM.03 Set tariff parameters (refer to [6]) ...................................................................... 191
Figure 101: Sequence diagram MM.03.01 - Set tariff parameter in the smart meter (refer to [6])... 191
Figure 102: Sequence diagram MM.03.02 - Set tariff parameter in the LNAP/NNAP(refer to [6]) .... 192
Figure 103: CI.01. customer information provision (refer to [8]) ....................................................... 192
Figure 104: Sequence diagram CI.01.01 - Send information to meter display (refer to [8]) .............. 193
Figure 105: Sequence diagram CI.01.02 - Send information to simple external consumer display (refer
to [8]) ................................................................................................................................................... 193
Figure 106: Sequence diagram CI.01.03 -– Smart Meter publishes information on simple external
consumer display (refer to [8])............................................................................................................ 193
Figure 107: ES.02 - Manage supply quality (refer to [7]) .................................................................... 194
Figure 108: Sequence diagram ES.02.01 - Configure power quality parameters to be monitored (ref.
[7]) ....................................................................................................................................................... 194
Figure 109: Sequence diagram ES.02.02 - Smart meter sends information on power quality to display
(refer to [7]) ......................................................................................................................................... 194
Figure 110: DG.01.01 - Direct load / generation demand – appliance has end-decision about its load
adjustment (refer to [14]) ................................................................................................................... 195
Figure 111: DG.01.02 - Direct load / generation demand - appliance has no control over its own load
adjustment (refer to [14]) ................................................................................................................... 196
Figure 112: Sequence diagram DG.03.01 - Information regarding power consumption / generation of
individual appliances (refer to [16]) .................................................................................................... 196
Figure 113: Sequence diagram DG.03.02 - Information regarding total power consumption (refer to
[16]) ..................................................................................................................................................... 197
Figure 114: Sequence diagram DG.03.03 - Price & environmental information (refer to [16]) ......... 197
Figure 115: Sequence diagram DG.03.04 - Warning signals based individual appliances consumption
(refer to [16]) ....................................................................................................................................... 197
Figure 116: External Actors (refer to [1]) ............................................................................................ 198
Figure 117:Mis-use diagrams for the considered CEMS functionalities ............................................. 208
Figure 118 Mis-sequence diagram for the MIM attack....................................................................... 210
Figure 119: Mis-sequence diagram for the Masquerade attack ......................................................... 212
Figure 120 Mis-sequence diagram for the DoS attack ........................................................................ 213
Figure 121: Mis-sequence diagram for the Disclosure of message attack.......................................... 214
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List of Tables
Table 1 Overview of the CEN-CENELEC-ETSI AMR / CEMS sequence diagrams of Annex B - UC
templates............................................................................................................................................... 66
Table 2: Overview of the mis- sequence diagrams of Annex B - UC templates .................................... 70
Table 3 Requirements Template Description ........................................................................................ 79
Table 4 KPIs Template Description ........................................................................................................ 84
Table 5 Requirements for Medium Voltage Control Use Case ........................................................... 223
Table 6 Requirements for EV Charging Use Case ................................................................................ 226
Table 7 Requirements for External Generation Use Case ................................................................... 231
Table 8 Requirements of the AMR / CEMS Use Case .......................................................................... 236
Table 9 Key Performance Indicators for Medium Voltage Control Use Case ..................................... 240
Table 10 Key Performance Indicators for EV charging Use Case........................................................ 241
Table 11 Key Performance Indicators for External Generation Use Case ........................................... 242
Table 12 Key Performance Indicators of the AMR / CEMS Use Case .................................................. 244
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Glossary
Acronym
AC
AMI
AMR
AVR
CAM
CEMS
CHP
CI
CLS
CPE
CS
CSO
CSP
DER
DG
DMS
DNO
DoS
DSM
DSO
EMG
ESP
EV
FLIR
GIS
HAN
HES
HV
IP
KPI
LAN
LNAP
LV
LVGC
M2M
MDA
MDMS
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Definition
Air Conditioning Unit
Advanced Monitoring Infrastructure
Automated Meter Reading
Automatic Voltage Regulator
Control Area Manager
Customer Energy Management System
Combined Heat and Power
Customer Information
Controllable Load System
Customer Premises Equipment
Charging Spot
Charging Station Operator
Connectivity Service Provider
Distributed Energy Resource
Distributed Generation
Distribution Management System
Distribution Network Operator
Denial of Service
Demand Side Management
Distribution System Operator
Energy Management Gateway
Energy Service Provider
Electric Vehicle
Fault Location, Isolation and Restoration
Geographic Information System
Home Area Network
Head End System
High Voltage
Internet Protocol
Key Performance Indicator
Local Area Network
Local Network Access Point
Low Voltage
Low Voltage Grid Controller
Machine-to-Machine
Metering Data Aggregator
Meter Data Management System
FP7-ICT-318023/ D1.1 ver 2
MIM
MO
MPLS
MV
MVGC
MVNO
NAN
NNAP
OLTC
OMS
P
PEV
PG
Q
RES
SAS
SGAM
SM
SSM
TSO
UC
UI
V
VC
VPP
WAN
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Man In the Middle
Meter Operator
Multiprotocol Label Switching
Medium Voltage
Medium Voltage Grid Controller
Mobile Virtual Network Operator
Neighbourhood Area Network
Neighbourhood Network Access Point
On Load Tap Changer
Outage Management System
Active power
Plug-in Electric Vehicle
Power Grid
Reactive power
Renewable Energy Sources
Substation Automation System
Smart Grid Architecture Model
Smart Metering
Supply Side Management
Transmission System Operator
Use Case
User Interface
Voltage
Voltage Control
Virtual Power Plant
Wide Area Network
FP7-ICT-318023/ D1.1 ver 2
1 Introduction: from SmartC2Net UC to the overall architecture
The expected growth in Distributed Generation (DG) will significantly affect the operation and the
control of today’s distribution systems. Being confronted with short time power variations of DGs,
the assurance of a reliable service (grid stability, avoidance of energy losses) and the quality of the
power may become costly. In this light, Smart Grids may provide an answer towards a more active
and efficient electrical network.
The SmartC2Net project addresses different control scenarios related to the evolution of the
European distribution grids. In particular this deliverable addresses the WP1 activity consisting in the
description of selected use cases with the identification of the requirements and details needed by
the others WPs. A first sketch of the overall architecture is presented and the specific economical
business driver derived.
Decision criteria for the selection of the use-cases are the following:
(1) architectural coverage of the smart grid domains and control layers;
(2) coverage of the time horizon from use-cases that are about to be implemented until future
smart grid control scenarios with deployment in 5-10 years;
(3) relevance/contribution to efficient LV/MV grid operation;
(4) challenges of the use-cases with respect to communication load, communication network
performance and control robustness.
Following the guidelines on the harmonized specification of smart grid use cases provided by the
committee Sustainable Processes of the Smart Grid Coordination Group by CEN/CENELEC/ETSI [UCC],
the following four use cases are analyzed:
 Voltage Control in Medium Voltage Grids
 External Generation Site
 Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS).
 Electrical Vehicle Charging in Low Voltage Grids.
Addressing different actors and control layers of the distribution grid, these use-cases provide a good
coverage of the applications characterizing the evolution of European smart grid in the next future:
from the medium voltage grids of the “Voltage Control in Medium Voltage Grid” use case, towards
the low voltage grids and customers involved in “Automated Meter Reading (AMR) and Customer
Energy Management Systems (CEMS)” use case. Some use cases, as Voltage Control in Medium
Voltage Grids and Automated Meter Reading (AMR) and Customer Energy Management Systems
(CEMS) deepen the ICT aspects starting from UC descriptions taken from CEN/CENELEC/ETSI
Coordination Groups on Smart Grid and Smart Meter, respectively. Others, as Electrical Vehicle
Charging in Low Voltage Grids and External Generation Site, are fully new control cases. In all cases
the goal of the analysis is to provide detailed views of the information, communication and
component layers of their control architectures.
Starting from the analysis of these use cases a preliminary global high level architecture is derived at
the aim of highlighting the interactions among the respective control components and ICT networks.
As planned in the project Annex I [DoW] in the next phase of the Task 1.2 this preliminary
architecture will be updated and integrated with the results obtained from the monitoring (WP2),
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communication (WP3) and control (WP4) architecture developments, and a more detailed version of
the SmartC2Net overall architecture will be provided in D1.2.
An economic analysis of the use case scenarios is performed for getting the specific business drivers
and business requirements of the envisaged smart grid evolution. More updated analysis of business
drivers and business requirements will be presented in Deliverable D.7.2.
The requirements and the Key Performance Indicator (KPI) for the evaluation of the SmartC2Net
achievements are determined from the use case analysis and they are studied under several
perspective in order to identify the most important ones. The mapping with the different
SmartC2Net WPs allows understanding how the project results will be addressed and evaluated.
In order to increase the readability of the document, the deliverable is organized into core chapters
presenting the basic methods and most relevant aspects, and a set of annexes providing further
details.
The core part is structured into seven chapters, as follows: chapter 2 introduces the key elements of
the four use cases, then chapter 3 presents the business drivers and the business requirements
related to the use cases. More details regarding the use cases are described in chapter 4 where the
fault/threat scenarios are introduced, and an extended requirement and KPI analysis is presented in
chapter 5. Chapter 6 presents a first high level sketch of the SmartC2Net architecture. Finally,
chapter 7 concludes the deliverable.
Annex A presents the SmartC2Net Value Network used for the analysis of the business drivers; Annex
B includes the full templates of the four UCs by adopting the standard template proposed by IEC TC8
AHG 4 [IEC TC8], Annexes C and D include the refined UC requirements and KPIs lists, respectively.
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2 The Use Cases and their key elements
This Chapter introduces a general vision of the four Use Cases that will be described with more
details in Chapter 4. Following the guidelines on the harmonized specification of smart grid use cases
provided by the committee Sustainable Processes of the Smart Grid Coordination Group by
CEN/CENELEC/ETSI [UCC], the following four use cases are analyzed:
 Voltage Control in Medium Voltage Grid
 External Generation Site
 Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS)
 Electrical Vehicle Charging in Low Voltage Grids.
The selected Use Cases provide a good coverage of the applications characterizing the evolution of
European smart grid in the next future and address the major actors and control layers of the power
grid.
In particular the Voltage Control in Medium Voltage Grids use case addresses a key functionality in
the operation of DER connecting grids, and considers the ICT aspects and related cyber security
challenges. The connection of DERs to medium voltage grids can perturb the status of the whole
power grid: the non-deterministic behavior of DERs should be managed using ICT components in
order to avoid effects on the contracted terms of the DSO (Distribution System Operator) with the
TSO (Transmission System Operator) and on the quality of service of the neighbor grids.
The external generation site resembles a small town with some local industry, covering both low
voltage and medium voltage quality control. The scenario setup is a quite typical setup in many
places in Europe and therefore has a significant relevance.
The Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS) describes
two basic functionalities for enabling future distribution grids for load balancing and integration of
decentralized and distributed (renewable) energy resources. Different European utilities are moving
on the introduction of these functionalities on their grids. According to the European Mandate
M/441, a monthly billing for the customer and a roll-out of smart meters in 80% of all European
households until 2020 is targeted, which requires cost-efficient, modular concepts for the
comprehensive deployment of smart metering devices enabling a variety of flexibility management
scenarios. New customer programs to make the home power consumptions more “intelligent” are
emerging.
A specific flexibility management use case is represented by the Electrical Vehicle Charging in Low
Voltage Grids. In order to reach the European 2020 climate and energy package, in particular the 20%
reduction of CO2, new energy strategies are evaluated. The transition from fuel-powered cars to
Electrical Vehicles represents a challenging goal that need to be addressed by the power utilities in
order to avoid problems on the electrical grid due to the recharging operation and to make this
transition attractive for customers.
The functionalities addressed by the selected use cases represent interesting and relevant aspects for
the External Advisory Board members composed by DSO from different countries. The discussion and
the iteration performed during the first meeting and continuing in the next ones allow obtaining an
aligned vision with the real needs of the utilities for the future European distribution grids.
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The focus of the analysis is given to the ICT aspects and to the communication needs of the control
scenarios. Both normal and abnormal behaviors are addressed by each Use Case, describing the
effect of malicious attacks or accidental faults. The interactions among the Use Cases, participating to
the control of the whole grid system, are shown in Chapter 6.
2.1
Voltage Control in Medium Voltage Grid
The primary aim of this use case is to address the communication needs of a Voltage Control function
for medium voltage grids connecting Distributed Energy Resources (DERs). The actions derived from
the Voltage Control function are considered with the specific aim of defining an ICT architecture
suitable for the security analysis. The Medium Voltage Control is a didactic case for illustrating the
need of cyber security in smart grid applications, first because its behaviour influences both the
system operation and economy, secondly for the high level of inter-networking of its ICT
architecture. The evaluation of attack processes to the Voltage Control function is aimed at
identifying security controls to counter act those attacks having the capability of compromising the
voltage profile [DGPT12].
The connection of DERs to medium voltage grids can influence the status of the whole power grid:
the behaviour of DERs can affects the capacity of the DSO (Distribution System Operator) to comply
with the contracted terms with the TSO (Transmission System Operator) and directly the quality of
service of their neighbour grids.
The main functionality of the medium voltage control function is to monitor the active distribution
grid status from field measurements and to compute optimized set points for DERs, flexible loads and
power equipment deployed in HV/MV substations.
Figure 1 Overview of Medium Voltage Control Use Case
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The optimization function is performed by a Medium Voltage Controller of a HV/MV substation
control network. In order to pursue the previously defined objective, the Controller calculates in a
coordinated manner the optimal states of the controllable devices across the substation area.
The control strategy requires information originating externally to the DSO domain. From the
operation stand point, the optimization function has to receive voltage regulation requests by the
TSO whenever a transmission grid contingency needs to apply preventive measure to voltage
collapse. Load and generation forecasts are used to optimize the operation of distributed devices,
while the economic optimization is based on market prices and DER operation costs.
A first major design assumption underlying the use case ICT architecture (see Chapter 6) is that
communications from the DMS (Distribution Management System) application in the DSO centre
provide to the Controller the information related to DER features, changes in the grid topology,
requests by TSO, load/generation forecasts and market data. This design choice preserves the
integrity of the distribution grid operation by limiting the communication channels at the substation
level and concentrating the communications with those external actors at the DSO centre level.
The control loop is triggered by critical events (e.g. under/over voltage event, TSO request, grid
topology change). In absence of criticalities, the VC function is executed on a periodic base (e.g.
every 15 minutes) for optimization purposes. The total response time of its closed control loop, from
the start of the elaboration to the end of the set point actuation, depends on actuation time
constants of OLTC and DER power electronics.
The architectural layout deployed for implementing the VC function depends on the responsibilities
attributed to the use case roles and on country-based regulations. According to the architectural
layout in Figure 1, the data supply chain of the VC function depends on several communication links
enabling remote accesses from systems outside the perimeter of the DSO operation. The DMS
application in the DSO centre has permanent links (the green WAN in Figure 1) with four actors (TSO,
Aggregator, Generation Forecaster and Load Forecast); the Controller in the DSO substation has
permanent communication links (the red WAN in Figure 1) with third party DERs, possibly deploying
heterogeneous communication technologies available in different geographical areas;
communications between DMS and substation automation and control systems pass through the
DSO SCADA links (the blue WAN), possibly based on telco services. By focusing on the core of the VC
scheme, it results evident that the correct elaboration of the optimal set points depends on the
provision of correct operation and economic data from the above communication channels. A
malicious attack to one of the above communication links may cause either the loss of input data
(generation forecasts, economic data from the Aggregator, TSO requests, topological changes), or
the introduction of faked input values or output set points. The effects of such communication
attacks may lead the control function either to diverge from optimum set points or, even worst, to
produce inadequate set points with cascading effects on connected generators. The global impact of
cyber attacks to the Voltage Control functions on the supplied power depends on the grid size, the
amount of distributed generation, the control network topology on the top of the power grid
structure and the extension of the attack.
2.2
External Generation Site
With the anticipated increase in small decentralized energy resources from primary wind and
photovoltaic (PV), the low voltage (LV) grids are exposed to new load scenarios than originally
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designed for. Further, new high consumer demands from Electrical Vehicle (EV) mobility and heat
pumps challenge existing LV grid infrastructures additionally. As a result, there is an increased
interest in technologies to improve the LV grid operation. These mainly entail: local energy storage,
active control of energy fed in electrical grid, flexible demand control (entailing both end-user
managed demand response and autonomic demand control) for house-holds and EVs. This use case
covers the automation and control techniques required for future LV grids and enables the DSO to
utilize the flexibility of the LV grid assets. All this happens over an imperfect communication network
which poses challenges to the operation of the grid. Therefore, the objective of this use case is to
demonstrate the feasibility of controlling flexible, distributed loads and renewable energy resources
in LV grids over an imperfect communication network. Flexibility of LV grids for upper hierarchical
control levels is also investigated.
WAN
HV Grid
Markets
Forecast
Providers
HV
Primary Substation
Automation&Control
MVGC
TSO
Retailers
MV
DMS
Prosumer
Large DER
Large DER
Prosumer
WAN
Provider(s)
MV
Aggregators
MV/LV
Secondary Substation
Automation & Control
LVGC
LV
MV
MV
Secondary
Substation
Automation
&Control
Secondary
Substation
Automation
&Control
LV
Prosumer
SME
Consumer
Farm
Interm.
DER
SME
...
Consumer
Energy
Storage
...
MicroDER
…
...
LV
...
AN Provider(s)
AN Provider(s)
AN
Commercial
Feasibility
& Flexibility
Technical
Flexibility
&Performance
Use Case
2.3
Figure 2 Overview of External Generation Site Use Case
The reference scenario for this use case consists of a MV and LV grid shown in Figure 2, contains: 1)
fixed and shift-able energy consumption from households, small enterprises and EVs, 2) production
from PVs and wind turbines, 3) Energy storage. Hierarchical controller architecture is utilized, where
a distribution management system (DMS) is at the upper most level. This provides commands to the
MV grid controller, which sends commands to the LV grid controllers as well as flexible generation
and consumption in the MV grid. Finally, the LV grid controller sends commands to flexible assets in
the LV grid. The LV grids are connected to the MV grid via a controllable transformer station with an
online tap changer (OLTC).
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It is considered that all components in the architecture are connected with a communication
network providing monitoring data from and control of the individual components. The LV grid
implements its own control mechanisms which are responsible for: a) maintaining an acceptable
voltage profile, security and safety, b) balancing available power resources (energy storage and
generation) with the (flexible) demand, and c) handling the interactions between a) and b). The
control infrastructure is managed by one or more dedicated LV grid controllers which provide
functionality to support the sub-use cases introduced in the following sections. This Use Case is
considering only faults and performance degradation within the public communication network, and
the system’s overall ability to perform normal grid operation even during network faults and
performance degradation.
With the introduction of significant decentralized energy production from wind and photovoltaic
plants in the LV grid along with energy storage as illustrated in Figure 2, new problems arise. In this
setting the low voltage grid control should preferably be able to: 1) control the voltage profile along
the low voltage feeders, 2) optimize MV grid losses; 3) optimize energy cost; 4) aggregate the
flexibility of LV and MV assets that can be used as an input to the MV control and distribution
management system (DMS). The grid operation should in this matter be resilient to faults and
performance degradation in the public communication lines between the low voltage grid controller
and the assets in the electrical grid with special focus on the low voltage side, hereby limiting the
effect of changing network conditions on the electrical grid performance. This means that the use
case also includes mechanisms for adapting the communication to events in the network that
challenge the communication and the quality of the data exchanged between the controlled and
controlling entities.
Under these settings, two focus points are defined as to show the above characteristics:
- Technical flexibility and performance: Resilience of control towards faults and congestions in
communication networks.
- Commercial feasibility and flexibility: Aggregation of generation and demand (abstraction of
models).
2.3
Automated Meter Reading (AMR) and Customer Energy Management Systems
(CEMS)
This use case describes two basic functionalities for enabling future distribution grids for load
balancing and integration of decentralized and distributed (renewable) energy resources (Figure 3).
Therefore, Automated Meter Reading (AMR) is an enabling technology, which is capable of
generating precise multi-sector metering data and aggregate them on local grid operator side for
large-area and in-house analysis of current energy consumptions as well as grid load conditions.
Additionally, current efforts in the context of the Internet of Things aim to connect more devices in
the household to create a more intelligent home area network (HAN), including components of
customer energy management systems (CEMS) like distributed energy resources (DER) and storages,
demand side management, private electric vehicle charging and user interaction. In the context of
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AMR, this adds an additional way of home building automation by combining the energy
consumption of accordant components with the current status of the energy grid to improve its
stability by shifting loads balanced with the neighborhood area network.
To MV grid
Power
Communication
Metering
Control
Energy grid
In house applications
Power predictor
User
interface
Data aggregator
Fixed or cellular
Communication
hub
Fixed
Aggregated
metering data
Control
network
network
Communication network
Smart
Metering
Air
conditioning
units
Household
appliance
Shiftable
loads
Smart
Metering
EMG
Cellular
network
Photovoltaic
Neighbourhood area
network
Local CHP
Decentralized
power production
Cellular
network
Wind turbines
Cellular
network
Home area network with AMR / CEMS
Figure 3: Advanced Smart Meter Reading and Customer Energy Management System Scenario
AMR is often referred as the key application for enabling a Smart Grid. Basically, AMR represent
different approaches for automatically collecting energy consumption data from electric, gas, water
and heating metering devices and transmitting these data to the meter reading operator for billing
and accounting. This information enables the energy utilities for an accurate meter reading and a
detailed forecast of the predicted energy consumption. Since several years AMR systems are already
deployed mainly for industrial and commercial customers, based upon an integrative approach by
combing the actual metering components and a WAN interface for remote meter reading. Due to the
European Mandate M/441, a monthly billing for the customer and a roll-out of Smart Meters in 80%
of all European households until 2020 is targeted, which requires cost-efficient, modular concepts for
the comprehensive deployment of Smart Metering devices considering a variety of application
scenarios. Due to different technology life cycles for energy components and ICT components a
modular system is targeted in most of the approaches. Usually a Metering HAN Gateway collects and
stores metering data from several metering devices, like electricity, gas, water and heating meters
connected by short range radio, e.g. ZigBee or Wireless M-Bus. The collected data is bundled and
securely transmitted to the meter reading operator by different access technologies, based on
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wireless, wired or PLC technologies. Moreover, a local feedback system gives the prosumer
transparent insight into his current energy consumption. In conjunction with available tariff
information, motivation for reducing overall power consumption can be achieved.
Additionally to the basic functionality of the AMR deployment, a more balanced usage of volatile
renewable energy sources (RES) and shift-able and controllable load system (CLS) in the distribution
grids is achievable by an active integration of the components on the customer side. In this context,
several customer energy management systems (CEMS) are presented, like locally managed and selfsustaining Micro Grids, virtual power plants and centralized load coordination like DSM or DER based
on dynamic energy prices. All approaches focus on the bidirectional integration of DER and
prosumers (producers and consumers) from both power and communication engineering's point of
view. This includes volatile RES such as wind farms and photovoltaic systems, as well as energy-aware
households, which are enabled by AMR to get a detailed forecast of the energy demand and
additional transparency in energy consumption on the customer side. Moreover, based on CLS and
DG through Combined Heat and Power (CHP) generation, micro-turbines and intelligent photovoltaic
(PV) panels, the ability to balance load peaks and valleys is given. These approaches require, because
of the distributed installations and small shift-able load potential, an aggregation of multiple DER.
Through concepts such as VPP, microgrids and energy hubs, different components are combined
using various networking concepts into a logical, partly independent group (e.g. isolated networks).
At this point, the seamless integration, reliable and near real-time connectivity within the households
by an Energy Management Gateway (EMG) and a CEMS, which is required for DER and DSM at the
customers side, are key capabilities of reliable power distribution grids.
All in-house components assume to be connected via a CEMS, which can be realized by a dedicated
wired or wireless home automation system (e.g. narrowband PLC, broadband PLC, BUS systems,
ZigBee, W-MBus, etc.) or a shared medium provided by the customers in-house networks (e.g.
wireless LAN, broadband PLC, etc.). At least one access technology (at least cellular networks), but
potentially more communication means, depending on the existing possibilities, e.g. power line, 3G
or fiber (if already installed in the household) and operators, may differ between households. Faults,
of different varieties, that might occur in context of this Use Case are addressed by Chapter 4.3 of
this deliverable.
2.4
Electrical Vehicle Charging in Low Voltage Grids
This use case describes the charging of electrical vehicles in a low voltage grid considering both public
as well as private charging (Figure 4). The overall objectives of the use case are to provide EV
charging service by:
• Satisfying the charging demands of arriving EVs in such a way that the charging load is distributed
according to the resource capacities in time and space (geographical routing for public charging).
• Enabling electrical vehicle to charge flexibly, a feature that can be used by the local DSO to manage
power quality control in the LV grid along with decentralized PV production as well as other loads
(e.g. households), and by the EV aggregator to handle on the energy market.
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• Providing a system architecture that enables interoperation between new actors such as charging
station operator, the EV routing service provider, the EV aggregator, and existing actors such as DSOs
and energy market.
• Enabling the DSOs to monitor the state of low voltage grid under EV load conditions.
The EV charging scenarios described in this document cover the pre-charging scenario (not in detail)
and the smart charging scenario (similar to CG-CG/M490 document, scenario WGSP-1300). The precharging interactions occur before arrival at the charging spot. The interaction of the EV with the
Charging Station Operator (CSO) (mediated by a routing service) leads to a reservation and the
allocation of a charging spot (CS), as well as the communication of desired charging demand, arrival
time, leave time, etc. from the EV to the CSO. The CSO can already create a plan. Also without the
pre-charge phase, the smart charging scenario is possible: the EV arrives at a free CS and requests
the CSO to charge, while providing following data: arrival time (now), estimated departure time,
minimum required amount of energy, maximum required amount of energy (to fill the battery),
preferred charging speed (sub-scenario PS2). The CSO creates a schedule, based on up-to-date
information: a) from the DSO about the charging capacity at that certain grid bus (available power),
b) energy bought optimally on the market, following the offered (flexible) demand.
The use case also considers how the DSO can supervise the Low Voltage grid to observe potential
power quality issues. The tool for the DSO to ensure power quality is a low voltage grid controller at
the secondary sub-station providing the available power limitations and flexibility demands to the
charging services. The low voltage grid controller utilizes the flexibility in conjunction with local
power resources (battery and production) to actively control power quality.
A regional EV aggregator (or energy supplier) interacts with the market (retail and spot) and buys the
EV charging energy according to the demand predicted by the charging stations. This demand is
expressed specifying also the flexibility of the consumption, for which the charging station is
rewarded. The aggregated requested EV demand cannot exceed the LV grid capacity (expressed by
the available power).
Specific for SmartC2Net are the following communication failure sub-scenarios: in the first the
communication channel from DSO to CSO for updating the available power is interrupted, implying a
reduction of the charging duration or the intensity of all current operations, and in latter the
metering data flow used for estimating the available power from the consumption and generation
forecasts is disrupted. Due to this uncertainty, the calculated available power could be reduced for
safe operation.
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buy energy
EV
Aggregator
Market
MVGrid
Controller
Sell
buy energy
Flexibility
Charging
station
Routing
Network
availability
Meter
Aggregation
LVGrid
Controller
Load
prediction
query & reserve
LV
Network
reservations
Available
power
control
Battery
PV
Inverter
Meter
Meter
Charging
station
Operator
(Controller)
internet
Control
plugin/ leave
Charging
Spot
Figure 4 Overview of the EV Use Case
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3
The business drivers
Drawing the attention towards economic and business drivers motivating a transition towards smart
grids, the present Section will investigate drivers facilitating the decision towards investments over
classical grids, and will further highlight business requirements providing useful feedback to the
technical realization, e.g. in respect to mitigating complexity or security threat disbenefits.
Originating from a value network representation (representing inter-firm business relationships) of
classical grids, the new value streams (in terms of monetary, resource, or other value exchanges) of
smart grids may substantially be different. Thus, creating a sufficient understanding of the business
change from “classical” electrical grids to smarter grids is necessary in order to examine business
advantages, i.e. drivers, arguing for the required transition. The necessity for investigating business
requirements may in addition be argued twofold: on the one hand the full exploitation of business
drivers may deserve the satisfaction of certain technical conditions (i.e. hygiene factors). On the
other hand, opposed to benefits of smart grids (business drivers), there may also arise costs (OPEX
and CAPEX) to be mitigated in order to render an attractive business environment.
The remainder of this section is structured as follows: Building on a common Value Network basis for
“classical” electrical grids and smart grids annexed in Section 9 (including entity (actor role) and
important value stream descriptions), business drivers are formed in Section 3.1. These business
drivers analyses will be conducted on a use case basis following a template proposal.
Correspondingly in Section 3.1.3.4 business requirements are collected and described from a
business driver point of view.
3.1
Business Drivers
This section aims at providing an analysis template for business drivers being applied to each of the
scenarios. We will first introduce a series of relevant business driver categories, which will be
instantiated for individual use cases.
3.1.1 Telco Sector
Before defining an appropriate template for the analysis of business drivers, we briefly discuss the
telco sector role in the smart grid context in order to capture business motivators in the energy
sector. The telco sector is of special interest for this investigation, as it complements the classical
energy sector roles in new smart grid business models and has not yet settled. The outcome will later
on be considered in the definition and application of the template.
There are several definitions of smart grid, but regardless of these definitions, the main characteristic
of the smart grids is the introduction and application of communications and information technology
in power grids. This will lead also to an increased usage of communication services, provided by Telco
operator, to cover the needs of the utility companies. Suitable communication technologies provided
by telco can be wireless or wireline, the first one mainly used in neighbourhood area network for
smart meter communication infrastructure because of easier and less expensive deployment, while
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the backhaul network to connect the smart meter head-end and the data aggregation points can
either be wireless or wired. Hereafter, we will focus on scenarios where connectivity is provided by
cellular technologies through M2M services because, although this technology introduces some
drawbacks, w.r.t. other wireless technologies it appears to provides the best answer in terms of
technical characteristics (coverage range, latency and reliability) at the lower cost and ease of
deployment [EEE12ZZ]. Regarding wired network and its adoption opportunities for smart grid, while
it has and will continue to have a place in utility market applications, several reports [NTS12 and
INT12] indicate a shift towards wireless technologies mainly driven by costs, difficult installations and
copper theft.
These scenarios foresee that the number of M2M device connections in the energy/utility sector will
grow from 22.1 million worldwide in 2011 to 1.3 billion in 2021. The CAGR (Compound Annual
Growth Rate) will be 50% during the 11-year period. Smart metering will be one of the fastestgrowing segments of the M2M ecosystem in terms of device connections during the next 8 years
[ANME12].
Figure 5 M2M device connections, energy and utility sector, worldwide, 2011–2021 [ANME12]
According to [ANME12], the growth in the sector is spurred by energy/utility companies’ need to:
 respond to regulatory and legislative changes

access more granular demand- and supply-side data in near real time

constrain capital and operating costs

increase service offerings.
Limiting analysis to smart metering, [ANME12] list the following factors driving the adoption of M2M
based services within the energy/utility sector:

Reducing operating costs and increasing margins. Operators in the energy sector, including
energy producers and distributors, are looking at ways to reduce costs. M2M devices help
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these businesses to improve processes such as meter reading, supply management and fraud
prevention. As an example, better near-real-time management of electricity supplies can
significantly reduce the cost of total energy production.

Providing accurate and timely data. M2M solutions are a way to remove human intervention
from collecting data and making decisions, which will reduce costs [ANME12] and will help
enterprises make better decisions more quickly by providing employees access to relevant
business data in real time or near real time.

New revenue streams or product differentiation. M2M solutions allow energy companies to
offer new services to consumers and other businesses. These new services might result in
additional revenue streams or increased differentiation for manufacturers. Examples include
home energy management, and residential and commercial security/surveillance solutions.

Renewed interest in connectivity due to Regulatory action and need to constrain costs.
Building new-generation facilities is extremely complex and often politically difficult.
Connectivity embedded in smart meters, homes and businesses helps the energy/utility
sector minimise the need to build new-generation facilities and maximise customer
satisfaction.
On the other hand the complexity of the M2M supply chain can inhibit the adoption of M2M
solutions in the energy sector. With M2M implementations frequently custom-designed, the overall
return on investment (RoI) of the solution is generally lower than that of other IT solutions.
Moreover government policy and regulation could have a deep impact on M2M adoption in energy
sector, depending on the commitment shown by governments and regulatory bodies for keeping
utility prices affordable, matching supply and demand, and encouraging energy conservation.
Connectivity represents almost 90% of M2M for CSP (role details see Section 9) revenue in the
current market, but most of reports indicate that within three years M2M connectivity revenues will
continue to grow, but new revenue streams will increase their importance for a sustainable
profitability [INFO12]:
 Connectivity (Communications services, associated communications hardware)
 Professional services (Consulting, integration, software development)
 Service level management (Security, demand response, performance management)
 Business intelligence (Decision support, reports and alerts, analytics)
The same shift will apply also to business models and role that CSPs will play:
 Today most CSPs function as M2M data wholesalers,
 only one in every 10 CSPs actively runs revenue-sharing models with partners.
 Fewer than one in 10 routinely offers service-level or application-based pricing for M2M.
M2M stakeholders can agree that table stakes for market success are end-to-end service
management and flexible billing for varied M2M applications and traffic profiles.
Beyond these two priorities, however, for smart grids scenarios security and securing data delivery
according to end customers’ service-level requirements is another priority to ensure.
Conflicts
Besides, the market data anticipating the raise of the M2M market and the interleaving of telco and
energy sectors, the particular roles have not been settled. Energy companies may cooperate with
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telcos as “friends”/”partners” or may on the other hand exclude them from the smart grid business
[ADL12], i.e., competitors.
Generally, different entities may have different visions, expectations, and driving interests in the
raise of smart grids [ScTa12]. Communication services may in practice be provided by telcos, but also
by DSOs themselves. Fearing the disadvantages of being locked in by one or more telcos (high or
rising prices, know-how transfer [ADL12]), the classical top-down energy sector approach with full
control over the whole value chain may be preferred by DSOs. However, cost advantages through
synergies (“joint customer base and sales channels”, shared investment costs, etc. [ADL12]) for both
DSOs and telcos thus could not be utilized. [ADL12] recommends that energy providers carefully
consider their strategic positioning with respect to cooperation and competition alternatives for
communication services. Besides that, even telcos could become a competitor in the energy sector,
which may assist the finding of a cooperative equilibrium at the end.
Thus, we argue that conflicting business drivers may only be resolved at mutually beneficial
configurations, i.e. a stable equilibrium. We suggest designing scenarios facilitating high control for
DSOs, high cost synergies for DSOs and telcos, and adequate business involvement of dedicated
CSPs. This could for example be realized on top of full-Mobile Virtual Network Operator (MVNO)1
agreements between a trusted CSP and a DSO, which provides the following flexibilities to DSOs:
Possibility to replace telco provider by a competitor (some contractual limitations), if service or price
levels do not meet expectations
 Complementation with own telco equipment possible (i.e., control over critical elements
could be established)
 Dedicated resources could be assigned to DSOs, which could substantially increase the
control over the communication network (if technically enabled)
 Besides synergies with the CSP, own investments could be made up by selling remaining
resources to external customers, i.e., entering the “classical” telco business as MVNO
Besides that scenario, also regulatory measures could enforce a more direct cooperation, e.g. by
increasing the cost pressure on DSOs and CSPs, thus requiring the consideration of more synergies in
smart grids investment and operation.
3.1.2 Categories
Each listed category represents a specific area of concern that can be extended individually. These
categories extend the considerations of [EPRI10] and are presented here with a short description
listing high-level examples of more specific concerns. Not all categories may apply to each scenario.
1
http://www.nereoconsulting.com/pdf/SmartGridandMVNOs.pdf
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Figure 6 – A categorisation of generic business drivers
As illustrated in Figure 6, two main categories interrelating with most others are cost reductions and
revenue growth. The details are provided in the tables below.
Category
Costs Reductions
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Description & Means of Realization
(Here we describe by which means the area of concern can be addressed)
Cooperation & Incentives: Improved cooperation with customers and suppliers
(business partners) is a significant source of cost reduction. In particular,
incentives for adequate supply/demand patterns may be used in order to
eliminate inefficiencies or even lead to customers/suppliers looking for
alternative business partners.
Entities: DSOs cooperating with energy generators and consumers on
adequate generation & demand levels; Retailers need to be incentivized to
reserve sufficient energy in advance; better integration of heavy users such as
charging stations in the grid stability picture
Increased Reliability: Improving reliability of service may bring a variety of
benefits also affecting cost levels. In the operative business, the compensation
payments (e.g. to business customers/partners) or even loss of customers may
be avoided. Cost advantages may be yielded by reductions of maintenance
costs (e.g. energy loss reduction primarily on MV level). In addition, further
aspects of product satisfaction or product attribute satisfaction like
convenience and quality may also affect customer satisfaction figures.
Entities: DSOs, CAMs (role details see Section 9), and also energy consumers
Wholesale energy trading efficiency: By an increased understanding of arising
supply and demand levels, utilisations can be attempted at the wholesale
market. In particular, unnecessary options deals may be avoided (or
downsized) or replaced by very dedicate futures purchases. This may on the
one hand save option fees and may on the other hand increase the supplies on
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Revenue Growth
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the market.
Entities: Esp. CAMs and DSOs (more efficient trading due to better metering
information and thus forecasting)
Resource usage efficiency: The usage efficiency of invested resources, esp. by
smart control of renewable energy generation/use, may be improved. Thus,
fewer resources are used and less energy needs to be wasted.
Entities: Regulatory (may enforce efficient usage), energy generators
(reduced costs due to fewer raw material inputs), DSOs and CAMs (higher
stability due to reduced danger of shortages), energy consumer (“greener”
energy provisioned)
Claim management: Reduction of claims means a reduction of costs. Claims
could be a perceptually unreasonably/surprisingly highly energy bill (being
provided only on a e.g. yearly basis) or product dissatisfaction (i.e., outages).
Both types of claims may be targeted by smart grids where consumption
figures could be shared more regularly and outages (in increasingly more
difficult environments) are aimed at being further reduced in probability. This
factor also interrelates with customer satisfaction & loyalty, as well as with risk
management subcategories.
Please take note that the introduction of new technologies such as smart
meters may also require some claim handling in the transition phase. Thus,
ease of use for end customers is important – see business requirements.
Entities: Retailers and DSOs
New Sources of Revenue: Newly designed information services may provide
added value to the customers leading to new sources of revenue. On the other
hand, the improved understanding may enable the provisioning of further
flexibility services, i.e., bearing risks of others etc. Finally, new/occasional
service offers could be provided, which could help utilizing fallow energy
resources, e.g., AC in public transport being automatically switched on
whenever there is no supply scarcity. (Please also take note that the utilization
of improved knowledge about customers and their consumption behaviour
may represent very valuable information e.g. for the advertisement industry)
Entities: Com. Service Providers (M2M services), DSOs/Retailers (dynamic
pricing), EV Charging Station Operators (satisfaction of more customer
requests), DERs (more DERs can be integrated in the grid), Vendors (new
equipment sold for metering or communication services)
Differentiation of existing services: Service differentiation, e.g. dynamic pricing
of energy at different times, may also allow energy providers to more
efficiently charge dynamically arising peaks. This may on the one hand
stimulate cooperation with business partners, and on the other hand generate
additional revenues beyond acting on the wholesale markets.
Entities: Retailers but also DSOs (and transitively CAMs)
Customer basis growth (existing resources): Due to a better forecasting of
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demand, as well as the shaping of actual demand and supply, supply levels may
be further exhausted by increasing the demand (new customers), trading of
resources (options, futures), etc.
Entities: Retailers and DSOs
The other categories are listed subsequently:
Category
Risk Management
Efficiency
Marketing &
Societal Benefits
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Risks are generally a considerable threat for business prospects. In smart grids,
this in particular complies with the risk management of energy and ICT
resources. At all the time it has to be ensured that sufficient supply matching
the demand is present.
Hedging: risk of investment (too low demand) hedged against put options or
risk of too low supplies hedged by call options on the wholesale market.
Reduction: Risks may be reduced e.g. by an improved understanding of
demand and supply patterns.
Sharing / Insurance: One may insure against energy (demand/supply)
fluctuations, e.g., by buying insurances. Insurances may cover monetary losses
or more realistically the bearing of the risk of ad-hoc energy demands, i.e.,
options or futures. A better understanding of available risks may lead to a
proper dimensioning insurances / risk sharing mechanisms. Risks may also be
shared among entities besides hedging mechanisms discussed above.
Entities: Mainly CAM, but also retailers and DSOs will have more
responsibilities regarding balancing the grid
The shift towards smart grids may be used for emphasizing the ecological
responsibility of firms (e.g. more renewables can be integrated). Especially in
the relationship with end customers, this may be a very important factor for
motivating such investments.
Smarter energy grids may provide better statistics allowing fine-granular
supply and demand analysis, customer inspection/relationship etc. This may be
seen as platform for doing business intelligence (knowing the customer base
for adjusting advertisements, product offers, etc.) as well as for the generation
of figures being used for PR purposes (e.g., consumption figures, saved energy,
reliability, etc.)
The reduction of greenhouse emissions, i.e. CO2, also poses benefits to the
society, i.e., lowered negative externalities (also see [EPRI10]). Thus, beyond
the direct business utilization, the society profits (also see regulation).
Entities: Retailers and DSOs, society
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Infrastructure
Efficiency
Customer
Satisfaction &
Loyalty
Regulation &
Legislation
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Delaying investments: the better understanding and proper utilisation of
existing infrastructure may allow the delaying of investments in future
upgrades. This may substantially affect the incurred costs, and may thus be
among the central drivers.
Infrastructure efficiency highly depends on the peculiarities of geographical
areas. Frequently most connection requests of renewable generation resources
come from rural areas where the grid hosting capacity and the communication
service availability are lower. On the other hands, the connection of flexible
loads (medium size prosumers and EV charging) is more relevant in urban areas
characterised by more reliable and oversized grid capacity.
(High precision) quality & energy demand/supply statistics: Improved
durability and quality statistics of deployed components may provide even
better selection of future devices
Entities: Mainly DSOs
Loyalty may be increased on two main axes, i.e., whitewashing customer
service, price or quality (reliability or information services), and obligations
(lock-in effects, long-term contracts). Endogenous whitewashing may occur
when intensified relationships with retailers or DSOs may automatically be
blandished by customers. Exogenously, whitewashing may be triggered by
dedicated advertisements & communication with the customers based on high
precision figures.
The customer satisfaction may be subject to economic aspects (is the price too
high? does the pricing scheme fit the needs?), self-control aspects
(consumption metering interrelated with current price), ecological aspects
(saving energy, green energy), (perceived) reliability, new information services
(where can I charge my car?), and trust (in energy grids, services etc.). By
allowing a more transparent communication with the customer a broad
majority of these factors could be addressed. The additionally provided new
capabilities enabling (dynamic) pricing and increasing reliability may further
contribute to suitable customer satisfaction levels.
Beyond that, customers may also profit from lower electricity prices, if smart
grids enable the more cost efficient integration of renewables.
Entities: Mainly retailers, consumers
Smart grid investments and operation may be enforced and regulated by
official bodies or laws. Entities may in particular face the regulatory
enforcement of accommodation for broader scale renewable rollouts paired
with a required maintenance of adequate stability and power quality in the
grid. Thus, the retention of the current business model may require certain
technological and/or business process adaption to changing legal frameworks.
Entities: DSOs, CAMs and partially retailers and larger consumer/resellers like
EV CSOs, society (lowered greenhouse emissions).
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Together with further factors like Risk Management Efficiency and Infrastructure Efficiency the cost
related factors represent an economic dimension comparable to [EPRI10]. Additionally, the Marketing
& Societal Benefits extend the understanding of “Environmental” benefits as captured in [EPRI10].
Customer Satisfaction & Loyalty covers and extends “Reliability” advantages linked to smart grids. On
the other hand, “Security & Safety” aspects are interpreted as business requirements (see later), as
the raising complexity of smart grids require proper countermeasures itself on this axis.
3.1.3 Use cases
Based on the above-presented template, each SmartC2Net use case is analysed on a fine-granular
level. By picking relevant categories from the template, specific business drivers will be discussed,
e.g. smart grids may facilitate charging of more cars a day (revenue opportunity). On the other hand,
less relevant categories for specific use cases are completely omitted in the analysis. We will
additionally address conflicting business driver and related business conflicts per use case, e.g., DAC1
introduces a Business Driver conflict of the AMR/CEMS use case.
All use cases share the following high-level business drivers:
Risk Management Efficiency:
 Due to improved metering, risk management can be further professionalized by receiving
better load forecasts, which lead to improved contractual agreements, i.e., insurances or risk
hedging agreements. These factors are typically immediately revenue-effective.
Marketing Benefits:
 Improved argumentation towards society to better accommodation for renewables in the
grid, and thus probably raising share of “green” sources of energy
On a high-level, [EPRI10] suggests the following general and rather energy-sector-centric benefits per
actor group:
 Energy sector: Reduced operation and maintenance costs, deferred capital costs, etc.
 Consumer: Reduction of electricity costs and disbenefits from power interruptions (or
“power quality events”)2.
 Society: Reduction of negative externalities
These generic drivers are subsequently extended by use-case specific details.
3.1.3.1
Voltage Control in MV grids
Business Driver
Costs
Reductions
2
Instantiation
The Voltage Control use case is mainly driven by cost considerations:
 Improved cooperation between DSO and DER owners is a
significant source of DSO cost reduction
Conflicts
DVC1
These advantages may be seen in direct comparison to cases of extensive renwable rollouts without
smart grid assistance
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

Revenue
Growth
Risk
Management
Efficiency
Marketing
Infrastructure
Efficiency
Customer
Satisfaction &
Loyalty
Regulation &
Legislation
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Minimised technical energy losses
Improving reliability, voltage stability and power quality of the
power supply service may bring cost cost benefits
 Decreased outages means reduction in maintenance and claim
management costs
 Optimised voltage profile reduces OLTC and DER costs of
operation
 Ability to integrate more DERs may reduce pressure to act on
wholesale markets and thus may reduce costs
 SmartC2Net may help DSOs to comply to the contracted terms
with TSOs and thus may be reduce costs inferred due to grid
instabilities (reliability issues) and/or charges (due to TSOs
having to act on the wholesale markets) – see risk
management
Entities: Mainly TSO, DSO cooperating with DER owners (generation
plants and medium size prosumers) on adequate generation &
demand levels
The connection of DERs may enable the satisfaction of higher demand
levels, thus leading to potential electrification of new services. Thus,
this extending the grid business through higher demand levels. It also
requires extended communication services.
Entities: DSOs, CSPs
Related to cost motivations, also risk management becomes of
interest:
 Risks of over/under voltages may be reduced by relying on a
more precise grid monitoring, actors’ communications and
optimized set points
 Specific focus on cyber security as a means of increasing the
efficiency of the cyber-physical risk management
Entities: TSO, DSOs, DER owners
(also see general drivers above)
(see general drivers above)
The connection of DERs will allow to optimise the DSO infrastructure
efficiency in those geographical areas where grid overcapacity is
available – thus helping to delay investments in infrastructure upgrade
through more efficient usage.
Entities: DSOs
The increased acceptance rate of connection requests of DER to the
grid increases the customer satisfaction level, i.e. prosumer acceptance
Entities: DER owners (prosumers)
DER connections to the grid have to guarantee compliance with
country-specific regulations reflecting the adopted business model and
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the grid code. DSO and DER owners need to meet revised regulations
requiring a shift to smarter grids, e.g. according to the new regulation
it is necessary that all active customers are endowed with a
communication system allowing the (real time) data exchange with the
DSO. This will allow the DSO to implement optimization logics and to
send all customers the signals implementing the actions (e.g.
disconnection) needed to guarantee the security of the whole power
system.
Entities: DSOs, DER owners, Regulators
DVC1: DSO operation constraints may decrease DER owners’ revenue.
3.1.3.2
EV Charging
The EV use case in particular targets the advancements over EV charging realisation on top of
classical grids. Explicitly, telecommunications, and as an effect of that, the solutions required in
SmartC2Net, are a result of the distributed character of the EV charging sub-system. Creating
decentralized decision support both at the LV grid, and at the charging station level has the following
advantages:
Business Driver
Costs
Reductions
Revenue
Growth
Instantiation
 No alarms are issued and power line enhancement costs are
deferred.
 Grid operators may profit from overload avoidance in the LV
grid (due to charging station congestion) and in turn deferred
grid enhancements costs
 Better estimates of demand due to smarter reservations may
lead to more efficient wholesale trading (lower overcapacity
and fewer intra-day trades, as well as improved risk
management)
 Smaller dimensioning of charging stations may potentially also
result from load distribution optimizations
Entities: EV CS operators, DSOs, and CAMs (EV users may also profit
from lower prices)


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Due to optimized scheduling, the installed power and the
dynamic calculated available power is maximally utilized
On a high level, new revenue opportunities could be exploited
by e.g. renters/operators of parking lots or store operators that
may further provide charging opportunities in order to
differentiate over competitors or even directly increase their
revenues.
Conflicts
DEV1
DEV3
DEV1
DEV2
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
Risk
Management
Efficiency
Marketing
Infrastructure
Efficiency
Customer
Satisfaction &
Loyalty
Page 35 of 244
Each charging station may also profit from an optimized
utilization of their charging capabilities by an improved
steering of customers to available resources (parking lots and
energy).
 Due to the flexibility of the demand and of energy price
information, charging station operators can increase profits or
increase competitiveness by lowering their service prices
towards the customer
 New information services may be realized on top of a more
capable smart grid platform
Entities: EV CS operators, InfSPs (e.g., E-Mobility Service Operator),
DSOs/retailers (selling all available energy), Com. Network Providers
(M2M services e.g. for charging stations and grid or connectivity in
cars)
In addition, the SmartC2Net grid may enable the broader role out of
EV charging stations and a broader coverage of charging demands due
to optimized balancing the grid. Thus, besides investment cost
reductions, CO2 reduction due to the transition from fuel-powered
cars may provide positive incentives.
Entities: Society, regulators, energy consumers, but also DSOs and
retailers may profit
---------
Transparency by offering to broker between customers and
any supplier of charging services which best satisfies the
requirements of users (near to destination, price, availability of
resources, charging speed, energy mix, discount (loyalty
programs) (communications needed).
 New information services such as the reservation of charging
resources before or during the trip (communication is needed)
while at the same time reserving a parking lot
 No waiting times due optimal steering of customer flows
 Decentralized operation of charging stations makes them less
vulnerable to single point failures of a central charging service,
i.e., higher reliability
Thus, positively attributing to the perceived convenience/quality and
reliability of using the EV charging service. The increased satisfaction
may also help to blandish price figures.
DEV2
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Regulation &
Legislation
Entities: Mainly EV CS operators, DSOs and retailers (transitively also
EV users / energy consumers)
Government incentives seem to expedite the broader usage of EV,
which thus drives the necessity for finding solutions to charge more
cars. Thus, by upgrades to smarter grids proactively regulatory or
legislator intervention may be avoided.
Entities: DSOs and CAMs
DEV3
DEV1: Customers may want to participate in cost reduction prospects, which may mitigate revenue
prospects through new services and more EV charging
DEV2: Customers may be reluctant to switch to other CSs without a monetary incentive or clearly
communicated benefits, otherwise customer satisfaction may not increase or may even be lowered.
DEV3: The political impetus for pushing EVs may entail the requirement for investing in smart grids
or antedating investments in smart grids, which may not be aligned to the plans of the energy sector
entities (in terms of costs etc.).
3.1.3.3
Business Driver
Costs
Reductions
Revenue
Growth
Risk
Management
3
Instantiation
 Reduction of claim management by avoidance of disconnection
of customers, and increased penetration of renewable energy
sources by maintained voltage profile on LV feeders
 Minimize losses in MV grids while increasing the penetration of
renewable energy sources e.g. wind and PV in MV and LV grids
(we also kindly refer to Section 4.2).
 Increase wholesale trading efficiency
 Increase resource usage efficiency
 Increase reliability of MV/LV grids
Entities: DSOs, Retailers, Consumers, Prosumers,
micro/intermediate/large DER, Network Owners/Providers
 New Sources of Revenue for prosumers,
micro/intermediate/large DER by providing ancillary services3
 Service differentiations of existing/new services
 New connectivity for smart grid actors provided by CSPs, e.g.,
by utilizing the network for providing tailored M2M services
and/or QoS-differentiated services
Entities: DSOs, Retailers, Consumers, Prosumers,
micro/intermediate/large DER, Network Owners/Providers
Conflicts
Paid services on top of energy generation such as voltage control or reactive power support, which
form a new type of business (business model) due to decommssing of large power plants. Thus,
such services may gain in importance.
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Efficiency

Marketing
Infrastructure
Efficiency
Customer
Satisfaction &
Loyalty
Regulation &
Legislation
3.1.3.4
Capability to integrate more renewables in MV/LV grids – in
particular the case of renewable energy sources i.e. wind and
PV, is studied in this use case.
Entities: retailers and DSOs, prosumers
 Reduce the need for grid reinforcement by better utilization of
existing grid
Entities: DSOs
 Increase loyalty and satisfaction of end-users by increased
reliable power supply with renewable energy resources
Entities: Consumers, Prosumers, micro/intermediate/large DER
 New regulation and legislation for prosumers and their
interaction with the grid
 Requirements regarding the interfacing between prosumers
and the system
Entities: Consumers, Prosumers, micro/intermediate/large DER
AMR/CEMS
Business Driver
Costs
Reductions
Revenue
Growth
Risk
Management
Efficiency
Marketing
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Instantiation
 Enhance grid status information exchange below substations,
which may raise the reliability of the grid, and thus may reduce
costs
 Peak shaving → Shift of demand at times where energy is
available (reliability and thus cost effective; reduction in
wholesale trading; reduction of required investment costs,
etc.)
 Minimize non-technical energy losses (illegal, unbilled energy
consumption; also see paragraph on revenue)
Entities: Mainly DSO
 Minimize non-technical energy losses (illegal, unbilled energy
consumption) → new fees are received
 Com. Service Providers may profit from selling connectivity
services for AMR/CEMS, while relying on infrastructure
required for CPE connectivity, i.e., connectivity service bundles
providing a new source of revenue with potentially limited
investments required.
Entities: Mainly DSO and Com. Network Providers
Conflicts
DAC1
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Infrastructure
Efficiency

Demand-response may delay infrastructure investments (e.g.
cables)
Customer
Satisfaction &
Loyalty

More frequent / more transparent feedback on consumption
and prices
Supporting customers in order to save energy and/or costs
Feedback mechanisms and home integration may blandish
price disadvantages
Yearly metering models may lead to imbalances of
consumption period and assigned prices, e.g., lower than
expected consumption in winter but higher in summer, as well
as to compensation payments at the end of the year (metering
and payment intervals may not be aligned), which can be
eliminated/mitigated with AMR/CEMS (customer interest &



DAC2
satisfaction due to transparency and self-control capabilities).
Regulation &
Legislation
Entities: Mainly DSO and retailer may profit from increased
satisfaction (besides customers)
Regulators may enforce the deployment of smart meters, as practice in
Germany for example, and may also enforce load-dependent tariffing
schemes in order to promote energy saving behaviours of customers.
DAC1: Customer incentives may conflict with CSP’s revenue prospects, and thus need a proper
alignment.
DAC2: Customer satisfaction increase through improved consumption figures may not compensate
required investments in smart grids and especially smart meters. Thus, this may have to be financed
by other smart grid actors, probably DSOs.
The discussed use case-specific business drivers are viewed as the motivators for the investigation of
subsequent technical solution. Later on these drivers may serve as crosschecking or validation tool
for evaluating how the architectural realization, i.e., the SmartC2Net solutions, support the
realization of listed business drivers. This analysis has also illustrated the requirement for
differentiating in particular smart grid services to be considered, as their driving forces may differ in
their characteristic.
3.2
Business Requirements
Building on the description of business drivers, the present section investigates business
requirements – potentially providing implications on technical requirements – originating from a
business context. Thus, this section correspondingly provides use-case specific investigations on
technical properties that may be required to satisfy business needs. Such needs are caused by
business drivers for smart grids, or are dedicated to mitigate negative side effects (such as high
investment or operation costs of smart grids).
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3.2.1 Telco and energy sector interplay
A central requirement for the transition towards smart grids is the proper alignment of telco and
energy sector business objectives. Thus, this will be briefly discussed in this subsection and finally
provide implications on the business requirements template.
While DSOs may want to keep outmost control over their distribution network (including
communication services), CSPs are looking for a business case and may be able to utilize cost
synergies through the reuse of existing infrastructure. Thus, a fruitful cooperation implies the
following business requirements (also see dedicated business drivers section), which may, amongst
other technical solutions, be targeted by smart MVNO agreements:
 Straightforward replicability of CSPs
 DSOs’ possibility to deploy own communication infrastructure at critical locations
 Cost efficient integration of DSO communication infrastructure with CSP infrastructure
 Quality assurance, e.g., dedicated resources, access control, prioritization or other smart QoS
techniques
 Efficient reuse of existing resources (e.g., MPLS rather than leased lines/own spectrum;
dynamic adaption to energy sector)
3.2.2 Template
The applicable categories for factors triggering business requirements specification are summarized
in Figure 7.
Figure 7 – A categorisation of business requirements
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Category
Information Sharing
(Frequency, data sets
& access,
communication links)
Information Sharing: Requirements of communication links towards external
or internal business partners and/or between internal systems/departments.
Not only the frequency of data exchange is of high relevance, but also the
amount of data being required to be exchanged. Generally, we assume that
only the minimal set of data will be shared with business partners in order to
assure a proper functioning of the smart grid. Different data exchange and
access rules may apply to smart grid entities and (external) Information
Service Providers. Specifically of interest is the exchange between DSOs and
CSPs regarding current/expected performance and capabilities of the
network as well as the information dissemination of the grid status.
Another special case refers to the integration of Information Service
Providers building added value on top of smart grid interfaces. Information
services here refer to internally or externally provided added value services
(partially) utilizing information gathered or circulated in smart grids.

Investment
Efficiency
Efficiency of
Interaction
Data access: While the access of data needs to be restricted mainly
for security reasons (see dedicated category), the defined level of
data utilization may be subject to different degrees of market
openness: in order to allow the access of third party actors –
facilitating competition on information services – segmentation of
exchanged data would be useful (different information sets being
shared with different entities on different levels of aggregation)
 Trust relationship: There must be a trust relationship between
partners accessing the data, data providers, and customers (trusting
in the proper handling of their data). Unreliable partners need to be
removed, and the data access design should limit the required trust
level as much as possible.
Entities: All actors, esp. Information Service Providers, E-Mobility Service
Operators, Com. Service Providers, and DSOs.
Investments in smart grids (and individual systems or components) should be
kept as low as technical feasible. Thus, cost efficiency is required in order to
manage a successful transition towards smarter grids.
Entities: Esp. DSOs but also Com. Service Providers (w.r.t. revenue
prospects)
Market or system interactions or price adjustments may be subject to
different timescales. Thus, economic requirements for maximum timescales
or granularities may exist (in respect to dynamic pricing).
System/Market Interactions: The granularity of interactions between
systems or market places may be subject to service/use case requirements or
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customer demands, which may substantially influence the practical
realization of use cases.
Entities: Retailer (on wholesale market), CAM (on wholesale market and
with retailer), and esp. DSO (with generators, consumers, and CAM w.r.t
metering information exchange)
Possibility of (dynamic) pricing / service differentiation: The requirement of
allowing (dynamic) pricing (or comparable differentiation of existing services)
of particular resources
Entities: DSO (in cooperation with retailers)
Flexibility of
Deployment (e.g.
plug & play)
Environmentally
Sustainability
Improved Metering
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
Limited effort: The transition to smart grids should be accompanied
by limited deployment or behavioural adaption efforts
 Plug & Play: The reduction of deployment complexity in terms of
required know-how is of high importance, i.e., a "plug & play"
paradigm in lieu of required individual adaptions. Also the
complexity for customers should be limited towards the transition to
smart grids in order to keep claim management efforts minimal. New
features/technical capabilities should thus optimally be selfexplanatory.
 Entities: DSOs & Com. Service Providers (limited CAPEX for smart
grid investments), Information Service Providers (easy access to
data), EV Charging Station operator (w.r.t integration in smart
grids)
Energy-aware components, e.g., having the capabilities of shutdowns under
low loads, are required in order to mitigate cost increases as well as in order
to support the ecological argumentation of smart grid role outs towards
customers or the society in general.
Entities: all, but esp. DSO & Com. Service Providers
A key element for gathering information in smart grids is metering (on the
customer side as well as in the grid). Thus, metering information provides a
fundamental basis for business considerations or utilizations of gathered
data.
Control/Validation of business/legal agreements: A more precise validation
of business or legal agreements may be enabled
Entities: CAM, DSO and retailer
Basis for Forecasting: Currently present or historic demand / supply patterns
may be useful for forecasting subsequent deviations (especially regarding
seasonal, daytime, etc. effects)
Entities: CAM and DSO
Localization (of faults): Metering information may provide a good basis for
localizing events like faults, stressed components, deviating demand/supply
patterns etc.
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Incentivizing
Customers
Operational
Efficiency
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Entities: DSO
Basis for Statistics: Gathered information may be utilized for business needs.
In particular, business intelligence (classification of customers, customized
offers, etc.) and PR/Marketing (communicable figures etc.) considerations
may play a big role.
Entities: Retailer (and DSO?)
Basis for Shaping: The metering information will be useful for providing a
basis for shaping demand and supply (demand-response) via automatisms
(i.e., consumer devices adapting their energy consummation),
feedback/suggestions (e.g., alternative charging station suggestions or high
load indications), pricing, etc.
Entities: Mainly DSO
Customer demands regarding the usage of service, e.g., localization of
available charging stations, have to be met in order to successfully realize
SmartC2Net use cases. These factors may be assisted by technical or
monetary incentivization of customers.
Entities: Esp. DSOs
Originating from key business driver, the maintenance as cost factor is a very
import prerequisite towards the transition to smart grid systems. On the one
hand, smart grids should only add limited maintenance effort to existing
grids. On the other hand, smart grids should contribute to lower
maintenance costs of classical grid components, e.g., due to faster recovery.
 Reliability (outages):
o Durability of components (years): The durability of individual
components is in important factor for reducing outages, but
also reducing overall maintenance costs.
o Redundancy & Fault Tolerance: The failure of one
component should be of limited/minor effect to the overall
grid. This may be targeted by suitable degrees of redundancy
or component failure tolerance
o Quality of Network/System: Besides durability constraints,
communication network quality (or quality of other systems)
may decrease the required maintenance effort in terms of
human intervention.
o Alerts:
 Component failure: Automatic and precise (e.g., in
terms of localization) notifications about component
failures should be provided
 Component overload: Automatic and precise
notifications about highly stressed components may
be provided
 Self-healing: Recoverable failures (e.g., software) of
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components/control system/etc. may be assisted by automatic selfhealing processes. This may essential reduce the human effort in
maintenance
 Time to recover: Outages or limited service usages may be very
costly. The time to recover from failures is thus critical.
Entities: DSOs and Com. Service Providers
Information Security

Confidentiality: The business information gathered or circulated in
the smart grid has to be regarded as confidential to external and/or
competing actors. Competitive information needs to be protected
throughout the smart grid.
 Privacy: The customer information collected or circulated in the
smart grid has to be protected. In particular, careful handling of
information exchange with other entities is required: there should be
the capability to blur unavoidable data exchange (e.g., due to
technical or legal reasons), i.e., elimination of identities, meaningful
aggregation of information, segmentation of information sets etc.
Avoidable data exchanges (besides judicial or social restrictions)
should serve a business interest of the information contributing
party.
 Information Integrity and Availability: The requirements to be able
to trust on information gathered through metering and/or
exchanged with partners or other systems, or circulated in the own
network.
Entities: All (as all are using communication services)
3.2.3 Use cases
By picking relevant categories form the above-presented template each use case is specifically and
fine-granularly addressed. Thus, the present section will provide qualitative and use-case specific
feedback towards the analysis of requirements. Additionally, we will again investigate business
conflicts associated to stated business requirements of each use case, e.g. RAC1 introduces a
Business Requirement-related conflict for the AMR/CEMS use case.
Please, note that all use cases of course immanently require cost efficiency for a successful
realization, e.g., typically combination of connectivity services for end customers (Internet access)
may be aligned to the realization of smart grids to keep costs low and/or strengthen revenue figures.
We may also state the following high-level business requirements being shared by all use cases:
Efficiency of Interaction:
 Higher dynamicity of interaction, information exchange and trading:
o Grid resource trading in seconds
o Supply-demand balancing in milliseconds -> thus balancing reserves like batteries
required more intensively
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o Pricing updates in milliseconds in order to provide meaningful behavioural adaption
incentives (mechanisms avoiding oscillations in the system may be required)
 More fine-granular interaction and cooperation
 More fine-granular control over the distribution grid
o Incentives / compensation mechanisms (w.r.t. contracts and information exchange)
for balanced / unbalanced energy demand & supply by retailers
 More systematic integration of DER supply-levels, retailer energy sales, customer behaviour
and actors balancing the grid, i.e., DSO, CAM, TSO.
Improved Metering:
 More fine-granular metering capabilities
o Providing means for require fewer flexibility & reserves
o Better forecasting of demand and supply levels in order to make reservations earlier
(at a cheaper point in time)
3.2.3.1
Voltage Control in MV grids
Business
Requirements
Information
Sharing
Investment
Efficiency
Efficiency of
Interaction
Flexibility of
Deployment
Evniron.
Sustainability
Improved
Metering
Incentivizing
Customers
Operational
Efficiency
Information
Security
3.2.3.2
Instantiation
Conflicts
Communication links between DSO and TSO, Aggregators, InfSP, CSP,
and between DSO systems and networks (e.g. metering, SCADA and ICT
infrastructures)
------------------(see generic business requirement above)
Flexibility in implementing new DER connections is required. The role
of standards is particularly relevant
Environmental sustainability is relevant in view of energy source plans
and global economic strategies
Improved metering capabilities provide more accurate generation and
load forecasts (also see generic business requirement above)
Favourable contractual conditions (e.g., electricity costs) through a
more efficient integration of DERs or tax deductions for installation
costs may support the transition towards smart grids.
The voltage control is tightly coupled with efficiency of operation of the
grid and its components, i.e. advanced voltage control is required
Availability and integrity of grid monitoring and voltage control
information flows is essential
EV Charging
Business
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Instantiation
Conflicts
FP7-ICT-318023/ D1.1 ver 2
Requirements
Information
Sharing
Page 45 of 244
Information Sharing: On a high level competitive data needs to be
protected from competitors, which includes occupancy rates. On the
other hand, the privacy of end customers needs to be protected.
 All involved entities inherently require communication services
for their coordination.
 Direct and convenient interaction between end customers and
CSOs is required in order to find suitable charging stations in
the proximity of most customers. Thus, E-Mobility Service
Operators (or comparable information services) require access
to reliable forecasts whether a CS will be able to meet the
energy demands of a requesting EV in a certain timeframe.
However, the charging station should not directly exploit load
levels allowing a long-term monitoring of financial success.
Thus, we for example envision the following process chain
avoiding iterative requests for data collection purposes:
 Car request (energy demand, area, price constraints) → EMobility Service Operator one-by-one contacts CSs → positive
reply means automatic and compulsory reservation of the
energy slot (i.e., no-show fee seems to be required)
 Moreover, due to the sharing of customer demand levels the
role of an Aggregated EV Charging Infrastructure Management
cannot be played by direct competitors and may only be
shared with trusted partners. We, thus, suggest linking this role
with energy aggregators or creating an Aggregated EV Charging
Infrastructure Management instance for each CS chain.
 CSOs require an on request communication link towards DSOs
and their energy retailers to make sure that sufficient energy
can be distributed in order to satisfy present EV requests.
Whenever minimum loads are guaranteed to users, the DSOs
need to immediately update the information being
communicated to other (requesting) consumers. As there may
still be a certain fluctuations of individual demands, it is
advised that CS request a minimum energy level plus an
epsilon as risk hedging factor for the satisfaction of own
customers’ interests.
 In order to allow pre-planning of both the distribution grid load
levels and the CS utilization, customer requirements should be
characterized by minimal and maximal energy charges
requested
User data – especially personal data, consumption pattern, reservation
details, and payment information – should only be exposed to a limited
REV1
REV2
FP7-ICT-318023/ D1.1 ver 2
Investment
Efficiency
Efficiency of
Interaction
Flexibility of
Deployment
Environ.
Sustainability
Improved
Metering
Incentivizing
Customers
Operational
Efficiency
Information
Security
number of entities or optimally be handled anonymously (optimally up
to a single actor like the CSO or an InfSP). Thus, user data is only
forwarded to entities absolutely requiring this information and may in
the optimal case be anonymised.
---------The charging is currently a slow process with duration between 30
minutes and 3-4 hours. A time accuracy in the schedule in the range of
minutes is therefore sufficient. Therefore the charging capacity
planning will have a granularity in the range of e.g., 5-15 minutes.
Charging stations require the latest price signals (wholesale markets,
aggregators) and available power profiles (calculated by the LV grid
controller; DSO interface) in order to optimize the utilization of
charging slots. In addition, an interaction between the charging station
(CSO) and the aggregator, for reserving/purchasing the energy is
required (also see generic business requirement above).
------------------Related to higher efficiency of interaction, frequent updates of
metering information again in the granularity of 15 minutes are an
essential prerequisite for the effective steering of customers and
efficient reservation of resources (also see generic business
requirement above).
Requests consisting of a minimum and maximum (full battery) amount
of energy have to be considered in order to align energy demand and
price expectations to available resources and wholesale trading prices
in the energy supply. While due to congestions, fluctuating grid
conditions, the maximum request may not be satisfiable, the minimum
charge request should be met in any case.
---------Secure handling of customer reservations (avoidance of manipulation,
and privacy) and wholesale market interactions is essential.
REV1
REV1: Required information sharing may conflict with the protection of user information and
anonymisation especially w.r.t. to the optimal steering of customers.
REV2: Customers may not be aware of their needs, especially hours before the usage. This may be an
immanent EV charging problem, but especially relates to the problem of reservation and preplanning. Thus, certain flexibilities for increased or reduced energy charging may have to be found,
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e.g., by proper integration with information services allowing an updating of plans within certain
bounds.
3.2.3.3
Business
Requirements
Information
Sharing
Investment
Efficiency
Efficiency of
Interaction
Flexibility of
Deployment
Environ.
Sustainability
Improved
Metering
Incentivizing
Customers
Operational
Efficiency
Information
Security
Instantiation
DSOs will collect and process all data from end-users. Specific data will
be provided to relevant actors using different comm. networks. There
will be a need for a legal framework regarding the access and usage of
data.
Entities: All actors, esp. Information Service Providers, E-Mobility
Service Operators, Com. Network Providers, and DSOs.
Software platform allowing efficient deployment and interaction over
communication infrastructure with actors.
Adaptation of communication to fit current network condition without
changing interface for DSO or other entities accessing data from endusers (also see generic business requirement above).
Plug&Play will require demanding connection requirements and
standardization for both grid and networks.
Reduction of power losses due to a more careful handling and control
of assets
Conflicts
REG1

New metering functionalities will be required
o faster update rates for exchanged data
o possibility for delay estimation (network level)
(also see generic business requirement above)
Potential of providing detailed information of energy
consumption/production to individuals, which may allow end users to
for example become aware of own consumption.
----------
REG1
----------
REG1: Access and usage of data may be strong concern for customers, whether end users or
enterprise customers.
3.2.3.4
AMR/CEMS
Business
Requirements
Information
Sharing
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Instantiation
Conflicts
Information sharing between the customer energy management
domain and the service domain (DSO, Supplier, 3rd Party) is essential
business requirement and may additional technical infrastructure (at
RAC1
FP7-ICT-318023/ D1.1 ver 2
Investment
Efficiency
Efficiency of
Interaction
Flexibility of
Deployment
Evniron.
Sustainability
Improved
Metering
Incentivizing
Customers
Operational
Efficiency
Information
Security
gateway) and may require careful additional regulation
---------(see generic business requirement above)
No decline of comfort or reliability of supply for customers (they need
not care about underlying infrastructure), i.e., influence to end users’
usage habits (manual) may be kept as minimal as possible or may be
assisted be compensatory measures such as monetary incentives or
supporting systems/automatisms (it has to be ensured that
automatisms cannot be used to the disadvantage of customers).
Consumption figures (visual indications) should be easy
understandable for end users and required human intervention should
be kept.
---------(also see generic business requirement above)
Access to CPE may require incentives for the customers, e.g., by
receiving cheaper or even free Internet access etc. (provided by telcos
or grid operators themselves), in order to create a mutual interest of all
actors.
----------
RAC2
Especially protection of energy consumer data is essential, i.e., privacy,
in order avoid legal or societal blockage.
RAC1
RAC1: More precise information of customer demand patterns is very valuable information esp. for
DSOs, which may thus be reserved towards actions protecting customer information. Anonymisation
and privacy protecting architectures may be supportive for aligning conflicting interests.
RAC2: CSPs may require to be subsidized for providing such offers, which may not be in line with
other smart grid actors’ intention.
Despite the broad conformity across use cases, a wide range of flavors is represented by the chosen
use cases. Thus, the identified use case-specific business requirements and drivers will serve as basis
for cross-validation dimensions during the formulation of the architecture and evaluation phases in
later stages of the development.
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4 UC details
In Chapter 2 an overview of the four Use Cases is presented. In this chapter a more deep description
is provided in order to highlight the ICT aspects. The communication components and the relevant
networks are hereby reported and the specific anomalous scenarios addressed by each Use Case
identified. In particular we distinguish the accidental faults from the intentional malicious attacks.
The type and the characteristics of the abnormal scenarios depend on the specific information flows
and architectures addressed.
4.1
Voltage Control in Medium Voltage Grid
4.1.1 Objective
The introduction of Distributed Energy Resources (DERs) can influence the status of the power grid.
The behaviour of DERs can affects the capacity of the DSO to comply with the contracted terms with
the TSO and directly the quality of service of their neighbour grids. DSO has to face with units whose
behaviour is both unknown and uncontrollable and investments on conventional reactive power
control devices in substations may become ineffective. Automatic voltage regulations limited to the
OLTC (On Load Tap Changer) of the substation transformers, as usually operated in passive grids, may
be not sufficient to meet the supply requirements established by the norm EN 50160. This difficulty
to meet the contracted terms and the quality of service standards not only could be transferred into
charges to the DSO, but also affects the TSO operation because the scheduled voltages at grid nodes
could not be observed and voltage stability problems cannot be managed properly.
In order to maintain stable voltages in the distribution grid the Voltage Control function is
introduced. This main goal can be extended in order to achieve other important objectives as supply
ancillary services, minimize the cost and the KWh consumption, provide reactive power support for
distribution buses, reduce energy losses and provide compatible combinations of the above
objectives. The specific aim of this UC is to define a ICT architecture for the Voltage Control function
suitable for the security analysis. The main functionality of the medium voltage control function is to
monitor the active distribution grid status from field measurements and to compute optimized set
points for MV DERs, flexible loads and power equipment deployed in HV/MV substations.
The voltage profile optimization is reached by controlling reactive and active power injection by
distributed generators, flexible loads and energy storages, and setting On Load Tap Changers (OLTC),
voltage regulators and switched capacitor banks. Costs of control actions and load/generation
forecasts in the area have to be taken into account to select the appropriate control strategy
[UC200].
Figure 8 schematizes the Voltage Control Function with the inputs and the computation of a Voltage
profile in order to send set points to customer and utility devices.
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Field
measurem
ent
Grid
Topology
Market
prices
Resource
Operation
costs
Generation
Forecast
Load
Forecast
Voltage
Control
Function
TSO
signals
Voltage
Profile
Third party MV DER
Distributor’s device
Figure 8 - The Medium Voltage Control Function
Voltage profile and power flows in active distribution grids are changing dynamically, mainly because
of the stochastic production of renewable sources. The power injected by distributed generators can
overload feeder segments or lead the voltage beyond the limits in some parts of the grid. In order to
guarantee the correct voltage value at each customer site, the voltage profile of the distribution grid
is continuously monitored and optimized using the available grid flexibilities.
The optimization function can be implemented in a delocalized site for the selected area. Considering
the hierarchical architecture of the electric grids, a controlled area is a Medium Voltage (MV) section
of the grid, typically underlying a primary (HV/MV) substation and having points of common coupling
with distribution buses or the upper level grid. In this UC, the optimization function is performed by
the Medium Voltage Grid Controller of HV/MV substations.
At the border of the control zone the function can manage the area as a technical Virtual Power Plant
(VPP) and the main voltage optimization criteria can be extended to supply ancillary services to the
upper level grid, contributing to the stability of the electric power system. The function then
improves the spatial reactive power balance as well as the voltage quality in electric distribution
systems and also the spatial balance of the active power.
In a generic case, the optimization process takes into account combinations of technical/economical
objectives and constraints, including requirements on power exchanges at points of common
coupling with the higher-level grid. The optimization algorithm is not detailed in this generic use case
and it is assumed to be performed by an ICT component within the substation control network. Only
the actions derived from the optimization function are considered in view of their communication
needs.
As part of the coordinated optimization within the substation, suitable devices for control actions are
selected. Depending on the particular grid controlled area where the voltage control is applied and
on the optimization objectives, some generation/load units can be controlled either directly by the
DSO Controller or via the Flexibility Operator (in the following referred with the term Aggregator).
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After any change of an equipment state, either due to a substation request or to a local automatic
action, the substation is notified about the new state or operating point, including the information
on available regulation ranges.
The application includes the controllable power equipment, distributed generators variables and
issue corresponding signals to these variables in the closed-loop control sequences.
If during the execution of the optimal solution, the topology of the grid changes, then the application
is interrupted and the solution is re-optimized. If during the execution some operations are
unsuccessful, then the solution is re-optimized without involving the malfunctioning devices. If some
of the controllable devices are unavailable for the remote control, then the solution does not involve
these devices but takes into account their reaction to changes in operating conditions.
4.1.2 Architecture and Sequence Diagrams
In order to analyze the communication aspects of this use case, we need to highlight the main
interaction between the elements involved. The main control and communication components are
presented in Figure 9.
6
IEC
087
104
0-5-
TSO Control
Network
TSO/EMS
8
IEC 60
70-5-1
DER
04
IEC 61850
DSO Control
Network
IEC 61850-8-1
(MMS, IP GOOSE)
IEC 60870-5-104
DSO Enterprise
Network
P)
C
(IC
-6
0
70 8-10
8
60 96
C C 61
E
I IE
IEC 61850
DSO/DMS
MVGC
P)
(ICC
70-6
608 68-100
C
9
E
I
61
IEC
CP)
(IC
0-6 0
087 68-10
6
IEC EC 619
I
Aggregator
IEC 61850-8-1 (MMS)
Flexible Load
Substation Automation
System
Load Forecast
Generation Forecast
Capacitor Bank
OLTC
Figure 9 The UC Architecture
The Medium Voltage Control Use case involves communications through components inside the DSO
area, but also exchange of information with systems outside the DSO domain.
The TSO Control Center interacts through the TSO Control Network and the DSO Control Network
with the DMS through a permanent link in order to be able to send, if necessary, the signal that
triggers the execution of the voltage control function.
In order to compute an optimized voltage profile the algorithm needs different input data provided
by different actors. The DMS forwards the information from these components to the Medium
Voltage Grid Controller. In this way the control center – primary substation communications are
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reduced. The Aggregator provides the load and generation program and the ancillary cost to DMS via
the DSO Enterprise Network.
Also the Load and Generation forecast interact with the DMS through the DSO Enterprise Network.
The DMS sends /receives information to/from the Medium Voltage Grid Controller through the DSO
Control Network.
The Medium Voltage Grid Controller is connected through the Substation Automation System with
the Capacitor Bank and with the OLTC in the substation LAN. DERs and Flexible loads communicate
with the Medium Voltage Grid Controller via the DER /Flexible loads Control Network, possibly
deploying heterogeneous communication technologies available in different geographical areas.
In particular it is possible to identify the following different networks as depicted in Figure 10 :
 NW1: Wired LAN local to substation, distinguishing different network segments that
corresponds to separate control layers, e.g. station, bay and process layers
 NW2: Wireless/wired WAN that may use commercial cellular or private wireless technology.
This network connects the substation with the DER sites
 NW3: Private wired WAN. This network connects the DSO Operation Center with the
Substation. It may be based on dedicated communication services via wired WAN
 NW4: Wired LAN local to DSO Operation Center, distinguishing different network segments
that corresponds to separate operation layers, e.g. DMS and MDMS
 NW5: Wired WAN. This network connects the TSO Center with the DSO Operation Center. It
may be based on dedicated communication services via wired WAN
 NW6: Public IP. This network connects the Aggregator with the DSO Enterprise Center
 NW7: Wired WAN. This network connects the DSO Operation Center with the DSO Enterprise
Center. Most probably it will be based on dedicated communication services via wired WAN.
Aggregator Site
NW6
TSO Center
DSO Enterprise Center
Enterprise
Systems
NW5
NW7
NW4
DSO Operation Center
DMS
NW3
Flexible load site
DSO/Customer
NW2
DSO Substation
Field
DER Site
DSO/Customer
MVGC
NW1
Substation
Automation
System
Figure 10 Voltage Control – Communications
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Figure 11 Medium Voltage Control Sequence Diagram
The sequence diagram in Figure 11 shows the exchange of messages between the actors. The DMS
collects information from the Generation Forecast, Load Forecast and Aggregator and forwards them
to the Medium Voltage Grid Controllers. The TSO can send signals to the DMS that dispatches them
to the Medium Voltage Grid Controller. The distributed energy resources, flexible loads and
distributor’s devices (OLTCs, Capacitor banks) provide measurements to the Medium Voltage Grid
Controller.
Once obtained all the required information the Medium Voltage Grid Controller, if necessary due to
the estimation of the state of the grid or for optimization purpose, computes the set points. These
values are sent to the field devices in order to stabilize the voltage.
4.1.3 Fault/threat analysis/scenarios
In the analysis of the attack scenarios different networks can be taken in consideration, in this Use
Case the Medium Voltage Control function is taken as central element and the related
communication networks are addressed. In particular the input and output data flows are
considered.
The two main areas of data exchange are the DSO Control Network (connecting the DMS with the
Medium Voltage Grid Controller) and the DER Control Network (connecting the Medium Voltage Grid
Controller with the DERs).
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After the identification of the critical networks that will be addressed, we focus our attention on the
possible effects that the attack can cause to the control function. In general the attack scenarios can
affect the following security properties [IEC 62351]:
 Confidentiality: preventing the unauthorized access to information
 Integrity: preventing the unauthorized modification or theft of information
 Availability: preventing the denial of service and ensuring authorized access to information.
In the Voltage Control Use Case integrity and availability represent the most relevant security legs.
The availability is threatened by the possible loss of data or commands, while the introduction of
possible fake data or the execution of possible fake commands can have effect on the integrity of the
control function.
For each UC network, we can initially consider two macro categories of attack effects: loss of good
messages (effects on availability) or introduction of fake messages (effects on integrity). Moreover it
is possible to identify two types of traffic: periodic and asynchronous. Combining this information the
schema of possible attacks depicted in Figure 12 can be completed where three dimensions can be
observed: type of traffic (Periodic or Asynchronous), network addressed (DSO Control network or
DER Control network) and the security propriety effected (Integrity or Availability).
Availability
Integrity
DSO Control
Network
DER Control
Network
Periodic
traffic
I: Costs,
Generations
Forecast,
Load Forecast
Measurements
(field)
O:Measurements,
states (to DMS)
I: Measurements
P,Q,V
Asynchronous
traffic
I: TSO signal,
Topology
O: Setpoint
O: Setpoint P,Q,V
Figure 12 Possible attack scenarios to the Voltage Control function
In order to reduce the analysis space, a selection criteria based on the evaluation of effect criticality
has to be applied to all the possible attack combinations in Figure 12, resulting in the following attack
cases:
 DoS Attacks to DER (gateways). The traffic between DER and Voltage Controller is perturbed
and some DER measurements are not able to reach the Voltage Controller.
 DoS Attacks to Substation (gateways). The traffic between the Voltage Controller and the
DMS is perturbed; some DER and SCADA measurements are not able to reach the DMS any
more.
 Fake DER setpoints. Either an (additional) fake setpoint is sent to DER, or a legal setpoint is
intercepted and modified with wrong set point values
 Fake TSO signals. A fake TSO signal is sent to the Voltage Controller.
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A (flooding-based) DoS attack performed against DER or Substation gateway may perturb the
periodic traffic. The percentage of lost messages could allow to evaluate the possible effects on the
voltage control. On the other hand the sending of a fake message performed in order to implement a
fake setpoint or a fake signal, or to alter an existing message may cause instability or DER
detachment. The observed effect of the fake setpoints sent to DER is an enabling factor for the
intrusion detection.
In section 10.1.4.2 of the template (see Annex B - UC templates) some anomalous scenarios of the
Voltage Control function are analyzed with focus on the effect of the attack scenarios introduced
above.
The global impact of such cyber attacks to the Voltage Control functions on the supplied power
depends on the grid size and the amount of distributed generation, both these factors varying on a
geographical base.
By focusing on the Italian target of integrating an amount of renewable energy of about 40 GW
within 2020 [Petroni12], the distribution grid development plan will require the building of about
10% new HV/MV substations. The analysis of the attack impact on the supplied power depends on
the control network topology on the top of the power grid structure. By applying an extreme case
approach, the impact value associated to future smart grids endowed with the Voltage Control
function depends on the extension of the attack effect. For example, an attack to the DER network
could cause the disconnection of all the generators connected to the MV feeders of a given
substation (that means more than 100MW in the extreme case of the Center 25 in the Figure 13).
From the same impact analysis it results that an attack to the substation networks could be able to
disconnect one or several substations (e.g. less than 1 GW), while a control centre attack, causing the
disconnection of all the substations in a given control centre, could count 6 GW of unsupplied power.
Figure 13 Estimated RES Power per Substation (2020)
By mapping such impact values on the power scales identified by the SGIS working group [SG-CG/IS
12], it results that the impact of those cyber attacks to the communications of the Voltage Control
functions may be associated, respectively, to the Medium, High and Critical impact levels.
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4.2
External generation site
The Use Case is focusing on demonstrating the feasibility of controlling flexible loads and renewable
energy resources in LV grids over an imperfect communication network. The flexibility provided by LV
grids for upper hierarchical control levels is also investigated. The case is potentially disconnected
from the external MV grid, therefore the external generation site. In the following we elaborate this
use case.
4.2.1 Objective
Under these settings, different sets of actors will interact for the two focus points:
models).
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WAN
HV Grid
Markets
Forecast
Providers
HV
Primary Substation
Automation&Control
MVGC
TSO
Retailers
MV
DMS
Prosumer
Large DER
Large DER
Prosumer
WAN
Provider(s)
MV
Aggregators
MV/LV
LVGC
LV
MV
MV
Secondary
Substation
Automation
&Control
Secondary
Substation
Automation
&Control
LV
Prosumer
SME
Consumer
Farm
Interm.
DER
SME
...
Consumer
Energy
Storage
...
MicroDER
…
...
LV
...
AN Provider(s)
AN Provider(s)
AN
Commercial
Feasibility
& Flexibility
Technical
Flexibility
&Performance
Use Case
2.3
Figure 14: Overview of external generation site use case
Figure 14 also shows the proposed communication network structure imposed on the power grid.
The use case includes control of LV grid components, such as households, farms, PV’s, local wind
turbines, etc. as well as MV grid components such as larger refrigerator systems, wind farms etc. To
achieve this communication is needed to ensure proper transport of measurement and control
signals to assure proper control of the assets in the grid. Thus, the electrical grid includes both LV as
well as MV grid. The communication network is split into three categories: 1) the access network
(shown in orange) connects all actors in the low voltage grid; 2) the dedicated wide area network
(shown in blue) which is a high performance dedicated network for grid control; 3) the wide area
network (shown in red) connects the rest of the middle voltage actors.
The definitions for distributed energy resources used for this Use Case are defined in the table
below. These definitions take into account the voltage and current at the connection point as well as
the power rating of the device.
DER Definition
Voltage Ratings
[kV]
Current Ratings
[A]
Micro DER
<1
<16
Installed
Capacity
[kW]
<5
Intermediate DER
<1
> 16
5 < …< 500
Page 57 of 244
DER Type
DER at Household level e.g.
micro CHP, PV system, wind
turbine, energy storage,
DER connected to low
voltage feeders. Examples:
standalone systems e.g. PV
FP7-ICT-318023/ D1.1 ver 2
Large DER
>1
WAN Provider(s)
> 16
Forecast
Provider(s)
> 500
panels and heat pumps,
single wind turbine, battery
storage, charging spot for
EVs, etc
DER connected to medium
voltage grids. Examples:
wind or PV power plants,
Combined Heat and Power
plants, Supermarkets with
refrigeration systems and
charging stations for EVs,
etc.
Market(s)
Retailer
Large DER
Data Transport
(WAN)
DMS
Network
congestion
TSO
DSO
Network
performance
change
Medium Voltage
Grid Controller
Prosumer
Lost
Network
connectivity
Control of
assets
Micro DER
Prosumer
Aggregator
Technical (MV/LV)
Low Voltage Grid
Controller
AN Provider(s)
Data Transport
(AN)
Lost network
connectivity
Network
performance
change
Intermediate DER
Network
congestion
Consumer
Figure 15: Overview of use cases – and fault/error cases.
The diagram in Figure 15 illustrates the use cases found in the external generation case. The key
functionality is to keep the grid operational in both technical and commercial sense as already
mentioned which is the key focus of Control of Assets use case. To ensure this, data and signals need
to be transported between the different actors which is the focus of Data Transport in both Access
and Wide Area Networks. The main issue with the data transport is that the network used for this
purpose, is not perfect and adds stochastic delays (potentially leads to loss of connectivity) as well as
packet loss to the transport. These undesirable effects are caused by various reasons in the networks
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and lead to different undesirable behaviors causing potential troubles for the control of the system
and therefore affect the Control of Assets case. Therefore it is important to enable the system to
overcome different situations in the communication network. In order to do so, the system must first
be able to detect faults and detect when it is safe to return to normal operational mode. To support
these use cases, there is a range of network activity necessary, first the monitoring of the
communication network is required to keep track of what is going on in the communication network;
second scalable management of data access mechanisms is a necessity to overcome the potential
number of sources and the geographical spread. To support the data access, data quality estimation
is also done. By this estimation process, data collected can be attached quality attribute that are
useful for efficient data access management. This may require reconfiguration of the network or
completely using a different communication network infrastructure. Finally, registration of
communicating entities is needed for the system to be aware of what is interacting with what.
4.2.2 Control of assets
The normal operation defines three sub cases that will be considered in the use case:
 Energy balance – where the operation of MV grids is targeted. LV grids are considered
aggregated and the LVGC is offering flexibility to the MVGC. Thus the MVCG is primarly
controlling the assets such as Large DER, prosumers and LV grid via the LVGC to keep the
energy balance. The primary actor involved here is the WAN Provider
 MV operation – where the focus is to control the voltage profile as well as to optimize losses
and energy costs on MV grids using active and reactive power capabilities offered by Large
DER, MV prosumers and the secondary substations on MV side. The primary actor involved
here is the WAN Provider
 LV control - where the focus is to control the voltage profile on LV grids using reactive power
capabilities offered by Micro and Intermediate DER, flexible consumption and production at
household or small and medium enterprises. The primary actor involved here is the AN
Provider(s)
These subcases may involve only some of the actors while other are neglected as mentioned above.
A detailed description of these scenarios is given in 10 Annex B - UC templates
4.2.3 Network adaptive data transport (AN/WAN)
The data transport covers the communication required to execute normal operations as described in
previous sub section, and generally covers data and signaling between entity A and entity B, and is a
part of the normal operation situation as shown in Figure 18. The use cases for the AN and WAN
focus on adapting the network layer to overcome different performance issues in the network that
affect the operation of the Control of Assets. For the network part, three fault/error cases are
thereafter considered (detailed views on these can be found in Annex B - UC templates):
 Network Performance Changed - This scenario deals with time varying performance in the
network, and the adaptation of access methods to provide reliable data exchange between
entities communicating. This scenario is relevant for both WAN and AN.
 Network Congestion - This scenario deals with more severe network conditions, i.e.
congestions in the network, and the adaptation of access methods to provide reliable data
exchange between entities communicating. This scenario is relevant for both WAN and AN.
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
Lost Network Connectivity - This scenario addresses the case where devices loose
connectivity at the network layer. The case assumes a certain notion of connectivity, e.g. as
in TCP. This scenario is relevant for AN only.
In the following a brief overview of the architecture and functionality of the use case diagram is
provided in component and functional layers as described in [UCC]. This approach describes the
relation between components and functions in terms of electrical grid components (x-axis) and zones
of operation (y-axis) which is helpful also to understand the need for communication between the
various components and functions. Following this, a high level message sequence diagram connects
these components and functions in time.
Component Layer
Private Channel(s)
WAN Channel(s)
AN Channel(s)
Markets
Market
Enterprise
Forecast Provider
Operation
TSO
Station
Retailer
DMS
Technical
Aggregation
(MV)
Technical
Aggregation (LV)
MV grid control
LV grid control
AN Network
Provider(s)
WAN Network
Provider(s)
Field
MV Grid
Components
Process
Transmission
LV Grid
Components
Distribution
Large DER
Prosumer
DER
Smart
Meter
Smart
Meter
Smart
Meter
Smart
Meter
Prosumer
Micro DER
Intermediat
e DER
Consumer
Customer Premises
Figure 16 Components distributed in the external grid operation case
This figure illustrates what components are foreseen to be used in order to effectively execute the
use case Control of Assets shown in Figure 15, and although it appears quite wide, the focus in deed
is to balance the energy in the system which requires both MV and LV operations as well as
interaction with the external world related to the market and TSO. The setup in the scenario requires
several different types of DERs for proper energy balancing, with specific focus on the LV side
considering the technical and commercial aggregation as main points of operation. For completeness
to describe and understand the full operation of the grid, MV and some functionality from the LV/MV
and MV/HV is also needed as well as the parts related to commercial operation, e.g. retailers and
market interfaces. Communication will be focused to the Access Network and to some extend also
the Wide Area Network, which poses challenges due to a continously changing condition and
enviornment. Different traffic patterns, link conditions etc. will change the properties of the network
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over time, which needs to be handles. This will be addressed in the Data Transport use cases, and
the challenges as described in the sub cases.
Functional Layer
Market
Market
prices
Markets
Weather
Enterprise
Operation
information
Forecast
Provider
HV grid management,
GIS system data,
planning
TSOtools,
visualisation
Commercial
Retailer
aggregation
MV/LV grid
management, GIS
system DMS
data, planning
tools,
visualisation
Technical aggregation
GridTechnical
resynch., fault detection and
Technical
Aggregation
isolation,
demand Aggregation
side mngt(LV)
and
response,(MV)
curtailment, ancillery services
Station
Protection and monitoring
LV grid control
Warnings and alarms for
grid failure
MV grid control
AN Network
Provider(s)
WAN Network
Provider(s)
Field
Smart
Meter
MV Grid ActuationLV Grid
Components
Components
Process
Transmission
Distribution
Large DER
Actuation Prosumer
Prosumer
DER
Smart
Smart
Smart
Protection
metering Meter
Meter and Meter
Intermediat
Actuation
Micro DER
e DER
Consumer
Customer Premises
Figure 17 Functionalities in the external grid operation case
The functionalities shown in Figure 17 enable the envisioned operation of the Control of Assets use
case. The subsequent message sequence diagram shows an overview of the most important
operation, using the components and functionalities from Figure 16 and Figure 17. The remaining use
cases are found in the annex. At the lowest part, actuation functionality is used to efficiently
distribute actuation messages to the individual assets in the system. Protection metering and
monitoring functionality is running on top of the actuation for efficient and scalable data collection,
and event observation. On the DER side, this also includes some control functionality. On the MV and
LV side there is grid control functionality for the different voltage levels, and for the DER side
technical aggregation that allows the demand-response and production management. Further on
top, functionality for interaction between HV/MV and MV/LV is done, as well as the commercial
aspects are taken into account via functionalities allowing commercial aggregation, market (price)
interaction and interaction with forecast providers, e.g. on the weather situation. Again here,
communication is critical for these functions to perform properly. The impact of the solutions of the
network adaptation found in the Data Transport use cases to changing network conditions; will be
evaluated by the performance of the functions.
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Forecast Provider
Technical
Aggregation (MV)
TSO
Retailer
Markets
DMS
WAN Network
Provider(s)
MV grid control
Measurements
Technical
Aggregation (LV)
Large DER
Network
Status/
performance
Network
Status/
performance
Measurements
Measurements
AN Network
Provider(s)
LV grid control
Network
Status/
performance
Consumer
Micro DER/
Intermediate
DER/Prosumer
Network
Status/
performance
Measurements
Measurements
Measurements
Measureme
nts
Price signal
Weather
information
Weather information
Aggregated
Flexibility (LV)
Aggregated
flexibility (LV)
Aggregated
Flexibility (MV)
Aggregated flexibility (MV)
Aggregated flexibility (LV)
Network
Status/
performance
Network
Status/
performance
Bids
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Measurements
Accepted bids
Setpoint
Setpoints
Aggregated Setpoint (MV)
Aggregated
setpoint (MV)
Network
Status/
performance
Network
Status/
performance
Individual
setpoints (MV)
Individual
setpoints (MV)
Individual
setpoints (MV)
Aggregated set point
Aggregated set
point
Network
Status/
performance
Network
Status/
performance
Individual
setpoints
Individual
setpoints
Individual
setpoints
Figure 18 Overview of the sequence diagram for normal operation mode, capturing Control of Assets and
Data Transport. The specific fault/error cases can be seen in Annex B.
Figure 18 shows the message exchange in normal operation. Starting from the lowest level (right in
the figure), consumers and DERs send measurements to the LV grid controller and receive setpoints
from the LV grid controller. The measurements from LV assets are aggregated before they are sent to
the MV grid controller. Similarly, the LV grid control receives an aggregated setpoint from the MV
grid controller that must be dispatched to the individual LV assets. The MV grid controller
communicates with Large DERs and LV grid controllers to exchange aggregated flexibility,
measurements, and setpoints. Additionally, the MV grid controller sends the aggregated flexibility to
the DMS, which generates setpoints based on the available flexibility, weather information, and
market conditions.
Basically, the operation mode interacts with the different actors as needed, and in particular, the
commercial part interacts also with the market entities to obtain set points for the grid operation.
These steps are continuously repeated with specific time intervals. It is important to realize that the
network use cases are run in the background and effectively evaluates the performance of the
interactions between the entities shown in Figure 18. That is, the overall functionality of the network
is to ensure that the signals shown in Figure 18 are effectively mediated to the different entities
involved. When faults/errors/performance degradation in the network occurs, the smartC2Net
platform shall adapt the strategies such that the overall operation does not necessarily degrades, or
at least to an acceptable level.
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4.3
Automated Meter Reading (AMR) and Customer Energy Management Systems
(CEMS)
This paragraph provides details on the Automated Meter Reading (AMR) and Customer Energy
Management System (CEMS) Use Case.
4.3.1 Objective
The following goals cover the objectives of the user as well as of the operator.
Automated Meter Reading:
 Collection of energy consumption data from electric, gas, water and heating metering devices
 Transmission of aggregated data from the households to the energy utilities/meter reading
operators for billing and accounting
 Provide (local) feedback system to the customers in order to provide transparent insight on the
current energy consumption and enabling indirect demand side management
 Aggregate information of energy consumption in order to balance the distribution grid by
enabling direct demand side management
Customer Energy Management Systems:
 Improve distribution grid stability by enabling direct demand side management
 Reduce energy costs for consumers by shifting flexible loads to less expensive time slots or
improve utilization of local energy resources
 Optimize the utilization of energy according to supply contracts or other economic targets, e.g. by
shifting flexible loads to less expensive time slots
 Provide added-value services to the customers
 Provide the flexibility information to the Aggregator by gathering customer premises’ data
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Figure 19 helps to get an understanding of the Automated Meter Reading (AMR) and Customer
Energy Management System (CEMS) Use Case (UC) by showing its logical and physical components
(e.g. the physical Network Access Points, not logical information flows) and their locations in the
Smart Grid Setup.
Meter Data
Management System
Customer Energy Management System (CEMS)
Home
automation
end device
Simple
external
consumer
display
Metering Data
Aggregator
Distribution Network
Operator
Related to EV Use Case
Private
Charging Spot
Energy Management
Gateway (EMG)
Local
Network
Access
Point
(LNAP)
Neighborhood
Network Access
Point (NNAP)
Head End
System
(HES)
Aggregator
Flexible Loads
Metering Operator
Related to External Generation
Use Case
Smart
Meter (SM)
Non-Flexible
Loads
Energy Service
Provider
Use Case
Automated Meter Reading (AMR)
Substation Level
Operator Level
Figure 19 Physical components of the use case and their locations in the Smart Grid setup
The figure depicts how the individual physical components are laid out. The Smart Meters (SM) of
the AMR use case measure the amount of energy, gas and water used in the household. Therefore a
connection between the flexible and non-flexible loads and the Smart Meter is necessary. The SM
interfaces with the Local Network Access Point (LNAP), which provides the WAN connection for
upload of the metering data. It is to be considered that, due to legal restrictions out of privacy
concerns, it is possible that a direct connection between SM and Energy Management Gateway
(EMG) might not exist. An EMG has the ability to controls flexible loads, private parking spots and
home automation devices. The state of these devices, along with current tariff and consumption
information, is made available for the consumer by an external display, which also provides a certain
degree of control over the CEMS. The LNAP has an interface to the Neighborhood Network Access
Point (NNAP) which itself connects to the Head End System (HES) with its subsequent set of devices
and roles. These are the Meter Data Management System (MDMS), Metering Data Aggregator
(MDA), Distribution Network Operator (DSO), Aggregator, Metering Operator and Energy Service
Provider.
Figure 20 delivers a detailed clustering structure of the use case. AMR and CEMS are in the center
and connect to sub use cases with their respective actors.
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Keys
Use Case Cluster
Use Case Cluster
Use Case
Reference to use case
document
ES.02. Manage supply
quality
ES.01. Tamper and
Fraud detection
ES.03. Monitoring
Collect AMI events
and status information
Actor A
[WGSP
Actor B]
Actor B
CI.01. Provide
Information to
consumer
Actor C
Actor D
[WGSP
Actor A]
Customer
information provision
MM.01. Obtain meter
reading on demand
<< extends >>
<< extends >>
AMR Use Cases
Measurement
MM.02. Obtain
scheduled meter
reading
MM.03. Set tariff
parameters
CEMS Use Cases
Demand and Generation
flexibility for technical and
commercial operations
Grid related REF:
Use Case Name:
and Island Mode
DG.01. Direct Load /
Generation
management
DG.02. HL-UC
Flexibility offerings
Electric Vehicle REF:
Use Case Name:
Electrical Vehicle
Charging in Low Voltage
Grids
DG.03. HL-UC Receiving consumption,
price or environmental information for
further action by consumer or a local
energy management system
Figure 20 Detailed use case clustering structure
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The sequence diagrams of the AMR / CEMS use case originate from the CEN-CENELEC-ETSI Smart
Meter Coordination Group and can be found with references in the corresponding use case template
located in the Annex B - UC templates.
Sequence Diagrams
Figure Nr.
Annex B
CEN
Designation
Obtain meter reading on demand
4
MM.01
Obtain remote meter reading on demand
5
MM.01.01
Obtain walk-by meter reading on demand
6
MM.01.02
Obtain scheduled meter reading
7
MM.02
Obtain scheduled meter reading (Sequence Diagram)
8
MM.02.01
Configure reading schedule
9
MM.02.02
Set tariff parameters
10
MM.03
Set tariff parameter in the smart meter
11
MM.03.01
Set tariff parameter in the LNAP/NNAP
12
MM.03.02
Customer information provision
13
Cl.01
Send information to meter display
14
CI.01.01
Send information to simple external consumer display
15
CI.01.02
Smart Meter publishes information on simple external consumer display 16
CI.01.03
Manage supply quality
17
ES.02
Configure power quality parameters to be monitored
18
ES.02.01
Smart meter sends information on power quality to display
Direct load / generation demand – appliance has end-decision about its
load adjustment
Direct load / generation demand - appliance has no control over its own
load adjustment
Information regarding power consumption / generation of individual
appliances
19
ES.02.02
20
DG.01.01
21
DG.01.02
22
DG.03.01
Information regarding total power consumption
23
DG.03.02
Price & environmental information
24
DG.03.03
Warning signals based individual appliances consumption
25
DG.03.04
Table 1 Overview of the CEN-CENELEC-ETSI AMR / CEMS sequence diagrams of Annex B - UC templates
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In this section the possible failures in the CEMS/AMR UC are considered. In particular, the focus is on
security threats that can hamper the CEMS main functionalities since the CEMS may operate in a very
hostile environment. Indeed, the CEMS can be connected to home automation devices and to the
EMG by means of shared network (e.g., the home WiFi, office LAN). The use of already deployed IP
network is extremely appealing since the cost for cabling and network interfaces is rapidly decreasing
[LECH08]. However, IP-based networks, when not well secured, are subject to cyber attacks.
The shift towards such a scenario may expose the communication and the CEMS critical
components, to attacks. For instance, an attacker can be:
 a hacker with no intent to cause damage and who is satisfied by the penetration of systems
accessible through the Internet;
 a criminal (e.g., disgruntled employee of the Energy Supplier or Energy Service Provider) who
wants to cause financial loss to the customer or to the energy service provider;
 a customer with malicious objectives, e.g., to tamper the system with fraud purposes.
The attack can be executed either from the Internet or from a device connected to the HAN which
has been previously tampered, such as a personal computer or the LNAP, and may have special
information or authorizations (e.g., EMG login credentials, remote management of home automation
devices).
All in-house components are assumed to be connected to the CEMS. Among the functionalities of the
CEMS depicted in the use case diagrams (see Figures 20-25), the most critical operations that must
be secured are: i) direct load/generation management (DG.01.01) and ii) communication of power
consumption information (DG.03.01). The considered misuse cases are depicted in Figure 21.
Figure 21 Mis-use diagrams for the considered CEMS functionalities
The alteration or missed delivery of load adjustment commands that can be performed by means of
active attacks, i.e., the attacker tries to alter system resources or affect their operations. This may
compromise the capability of the customer to use the smart appliances or even the execution of
emergency procedures. When the attacker is able to compromise a limited number of CEMS the
impact of the attack is low; however, when the attack is coordinated and several CEMS systems are
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compromised (e.g., more than 100) or when some critical CEMS are violated (e.g., police and fire
departments systems) the impact of the attack can range from moderate to high (e.g., when the
CEMS systems of a very extended area, such as a city, are all compromised in a limited interval of
time). In the following we refer to this misbehaviour as incorrect direct load generation management,
mis-use case DE.01 (see Figure 21). These mis-use cases extend the ones provided by CEN-CENELECETSI Smart Meter Coordination Group and are fully described in the template located in the Annex B
- UC templates of the deliverable.
The access to power consumption/generation data shall also be secured against non-authorized
accesses. In other words customer power-related data shall be protected against passive attacks, i.e.,
attempts to learn or make us of information from a system without affecting its resources. As a
matter of fact, this is mandatory according to privacy law in some countries of the European
Community, such as Germany. Moreover, sophisticated burglaries could be architected when such
information is not secured. For example, thieves can exploit power consumption data to infer when
persons are not in the buildings and then plan physical penetrations. The impact of such an attack
can be classified as low. In the following we refer to this misbehaviour as disclosure of power
consumption information, DE.02 (see Figure 21).
For the aforementioned motivation, the network security requirements that shall be guaranteed in
CEMS systems are confidentiality, integrity and availability . In particular, for the communication of
direct load/generation management operations (i.e., load and emergency commands) integrity and
availability shall be guaranteed; while confidentiality, integrity and availability shall be assured when
power consumption data are exchanged.
According to the CEMS logical architecture described in Section 1 the most critical components
involved in the aforementioned operations are the EMG and the CEMS. Indeed, these can be
connected to the home WiFi and the likelihood to be exposed to malicious attacks is higher with the
respect to the components that are in dedicated network and when not protected by firewall or
other security mechanisms (e.g., encryption).
Incorrect Direct load and generation management
The considered active attacks that compromise the integrity and/or the availability of EMG/CEMS
and lead to incorrect direct load generation management are:
 Man In the Middle (MIM) – an opponent captures messages exchanged between the EMG
and the CEMS. It can partially alter the content of the messages, or the messages are delayed
or reordered to produce an unauthorized effect.
 Masquerade – an opponent sends fake messages the EMG pretending to be a different
entity.
 Denial of Service (DoS) – the attacker floods anomalous messages to the EMG. It prevents or
inhibits the normal use or management of the communication facilities and/or the
components.
These attacks have been selected since they are usually performed by exploiting the most commonly
computer system and network vulnerabilities (e.g., sensitive data exposure, insecure object
references, broken authentication and session management, security misconfiguration). MIM and
Masquerade attacks can violate both integrity and availability; while, DoS violates only availability.
Tables Scenario D.01.01-D.01.03 and Figure 118-115, which can be located in the AMR / CEMS
template in Annex B - UC templates detail the considered active attack scenarios. It is worth noting
that just one interaction is considered for the mis-use cases DG.01.01 and DG.03.01; in particular, it is
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assumed that the Actor D starts the communication. However, a similar analysis can be applied when
Actor A initiates the communication.
The step by step description of the MIM attack is explained for the sake of clarity. As for other
attacks (i.e., masquerade and DoS) further explanations can be founded in the Annex B.
Figure 22: Mis-sequence diagram for the MIM attack
The MIM attack assumes an adversary can (i) observe messages exchanged, (ii) intercept messages
and (iii) reply messages with altered content (e.g., a load adjustment command sent by the EMG).
The attack takes place when the adversary intercepts the load adjustment command sent by the
EMG. Then, the attacker modifies the message previously intercepted and sends it to the CEMS. The
CEMS is not aware of the adversary modification and takes the load adjustment command as
appropriate and replies to the message. Hence, the attacker intercepts and alters the expected
change message sent by the CEMS (i.e. the reply to the load adjustment command) and finally sends
the altered message to the EMG. In this scenario, it is assumed that the CEMS sends the response
message to the EMG. However, the attacker might also be able to redirect all messages sent by the
CEMS to himself, e.g., by means of DNS tempering.
Disclosure of power consumption information
In this section the focus is on passive attacks that compromise the confidentiality of power
consumption information exchanged between the EMG and the smart appliances. As for the active
attacks that compromise the integrity and availability, similar analyses performed for the mis-use
case DE.01 also apply for the power consumption communication.
The considered passive attacks that compromise confidentiality are:
 Release of message content: the opponent tries to eavesdrop transmissions;
 Traffic analysis: the opponent observes the pattern of the messages to discover the location
and the identity of the parties involved in the transmissions, and the frequencies and the
length of exchanged messages.
The disclosure of message content scenario is detailed in Table Scenario DE.02.01, which is located in
AMR / CEMS template of the Annex A. When the smart appliance / generator sends information
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regarding consumption to the CEMS, the CEMS aggregates and/or forecasts total consumption and
sends this information to the display and to the EMG. The attacker may intercept the message and if
no cryptography method is used he/she reads the content about power consumption/ generation.
As for the traffic analysis attack the only differences with respect the disclosure of message attack
(depicted in Figure 29 in the AMR / CEMS template) is that we are assuming that the adversary
cannot understand the message. Hence, the opponent needs to intercept several messages in order
to observe the communication pattern and discover relevant information (e.g., location and the
identity of the parties involved in the transmissions).
Mis-sequence Diagrams
Figure Nr. Annex B
Man in the middle (MIM) attack
Figure 118
Masquerade attack
Figure 119
Denial of Service (DoS) attack
Figure 120
Disclosure of message attack
Figure 121
Table 2: Overview of the mis- sequence diagrams of Annex B - UC templates
4.4
Electrical Vehicle Charging in Low Voltage Grids
EV charging appears in both the Home scenario, where it is coordinated by the Energy Management
Gateway (EMG, see 2.4), and in the public and semi-public scenario below, in which a charging
station coordinates the operation of several charging spots.
4.4.1 Objective
The objectives of the EV charging sub-system, as described by this use-case, are listed below:
 Satisfy the charging demands of arriving EVs in such a way that the generated and stored
energy is efficiently used and the grid is not overloaded.
 Enable electrical vehicle charging to become a flexible consumption resource that can be
used to balance energy and power resources in the LV grid along with decentralized
production as well as other loads (e.g. households).
 Provide a system architecture enabling interoperation between new actors such as charging
station operators (charging aggregator) and their connection to existing actors such as DSOs
and energy providers.
 Enable DSOs to monitor state of low voltage grid under EV load conditions
For SmartC2Net it is significant to describe the view of the various ICT network technologies and
operations constraints (Figure 23):
Network 1 – Metering. The metering network is owned by the DSO or a metering infrastructure
operator. It is a network used to collect smart meter data measurements at the last mile. The smart
meter network is usually based on powerline communications, cellular or proprietary wireless
solutions.
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Network 2 – Sub-station network. This network is an internal bus-network in the secondary
substation. It is owned by the DSO and connects equipment in the substation. May be based on
Ethernet.
Network 3 – Public IP Network. The Public IP network represents the open Internet. This is the
easiest platform for third parties to provide their services, such as routing services to EV users, or
weather services. The public IP network can be based on everything from wired xDSL based
technologies to cellular data access.
Network 4 – eCar Communication. This communication is between the charging station and the
electrical vehicle itself. The communication is usually wired and may be running through the charging
cable itself. Information about the state of the car, e.g. state of charge, preferred charging speed,
etc. may be provided through this network.
Network 5 – Private IP Network The private IP network represents a local network infrastructure
utilized by the infrastructure owner to connect local elements. For instance charging spots may be
connected to the charging station through this network. It could be based on PLC or Ethernet.
Network 6 - LV Grid Management Network. The DSO may choose to deploy an own closed
networking architecture used for grid components to communicate. Thus could be to communicate
with inverters, protection devices as well as sensors in the grid.
Network 7 – DSO Network. The DSO network is the network connecting the DSO management and
control systems (e.g. SCADA) towards the secondary sub-station. These networks are usually closed.
They may be based on fibre put out by the DSO as the cables to substations were put in the ground.
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FP7-ICT-318023/ D1.1 ver 2
Cloud
DSO
Metering
Head-end
System
Market
(Distribution/Transport)
Meter Data
Management
System
Distribution
Management
System
(SCADA)
Information
Services
NW7: DSO Network
Charging
Station
Routing &
Reservation
Aggregated
Charging
Infrastructure
Management
Metering
Aggregation
(NNAP)
Low Voltage
Grid Controller
NW2: Sub-station NW
NW6: LV Grid Management Network
Local LV Grid
ressources (DER)
Photovoltaic
Inverter
NW5: Private IP Network
NW3: Public IP Network
Battery
Inverter
NW1: Metering
Private Charging Station
Public Charging Station
Private
Smart
Meter
Energy
Management
Gateway
EVprivch
NW4: eCar
Communication
Private
Charging
Spot
Charging
Station
Controller
EVpubch
NW4: eCar
Communication
Public
Smart
Meter
Public
Charging
Spot
Figure 23 Networks of the EV use case
To define how these components are foreseen to interact over the provided networks, the use case
has been divided into three primary scenarios (PS) covering different functions and parts of the
system: 1) a charging scenario, 2) an energy and power management scenario, and 3) a market
scenario.
The overview of the interactions is given in Figure 24:
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FP7-ICT-318023/ D1.1 ver 2
Aggregator & CSO
DMS
.3
PS3
PS
1.2
,P
S1
.5
PS
1.3
PS
1.
4,
PS
PS
1.
7
1.
3
PS3.4
.6
PS 3
PS
1.1
,
E-mobility
Charging
Service
Station
Operator
Routing &
Reservation
PS2.10
PS 2.4
PS 2.9
Low voltage
grid controller
PS2.6
1 .8
PS
PS
1
Charging
spot
.1
1
1.9
PS
.6,
1
PS
Meter Aggregation
Meter
PS2.7
PS2.8
PS
1.
9
DSO
PS2.5
Charging
Station
Controller
PS
1.
6,
Market
PS3.5
Aggregated
Charging
Infrastructure
Management
Battery PV Local
Storage Production
PS 1.11
Figure 24 Overview of the interactions between components
The EV charging scenario PS1.* describes the interactions between the EV owner, charging station
for reservation, plug-in, plug-out.
Scenario PS1
Scenario
Step
Event
No.
PS1: EV Charging
Name of
Process/
Activity
Find Charging
Station
PS1.1
Charging
Station
Lookup
PS1.2
Availability
Check
Availability
Check and
Response
PS1.3
Reservatio
n
Charging
Station
Routing
receives
reservation
Page 73 of 244
Description of
Process/Activity
Identify charging
station and
provide user
context
(expected stay
duration, needed
charge, …)
The Charging
Station
Infrastructure
Mgmt. identifies
charging station
options and
informs EV
Owner.
EV user selects
charging station,
arrival time
energy demand.
May get
Information
Producer
(Actor)
EV Owner
+ EV
Information
Receiver
(Actor)
Charging
Station
Routing
Information Exchanged
Charging
Station
Routing
EV Owner
Available charging
opportunities.
EV Owner
+ EV
Charging
Station
Controller
Reserve message
Charging Context.
FP7-ICT-318023/ D1.1 ver 2
request and
redirects it to
CSO
Reservation
handling at the
charging
station
CSO returns
OK
PS1.4
Process
Reservatio
n
PS1.5
Reservatio
n
successful
PS1.6
Plugin
EV Plugin
PS1.7
Plugin
Handling
Re-planning of
resources
PS1.8
Start/Stop
Charging,
Change
Charging
Speed
Charging
Process
Management
PS1.9
Plug-out
EV Plugout
PS1.1
0
Periodic
Metering
PS
1.11
Periodic
Metering
additional
information such
as routing advice.
Update Schedule,
allocate
resources
Charging
Station
Controller
Charging
station
Routing
Schedule update and
resource availability
OK response.
Charging station
Routing updates
its CS availability
list
An EV plugs into
the Charging Spot
and provides
additional/updat
ed context
information
The Charging
Station Controller
(re-)/plans the (if
needed) charging
plan
The charging
station controller
starts/stops
charging as well
as manages
charging speed
The EV plugs out
of the Charging
Spot. The
Charging Station
Controller
adapts.
Charging
Station
Controller
EV Owner
Reservation
confirmation
EV
Charging
Station
Controller/
Gateway
Updated Charging
Context.
Charging
Station
Controller
Charging
Station
Routing
Schedule update and
Resource availability
Charging
Station
Controller
EV
Start/Stop commands.
Updated charging
speeds.
EV
Charging
Station
Controller
Plug-out event
Send charging
metering data to
meter
aggregation
system for billing
purposes
Read meters for
state estimation
Smart
Meter
Meter
aggregatio
n
Meter data
Meter
Aggregatio
n
LVGC
Relevant Meter Data
The PS2.* Scenario relates to the energy balancing and power management at the LV grid level
Scenario PS2
Scenario
Ste
Event
p
Page 74 of 244
PS2: Energy Balancing& Power Management
Name of
Description of
Information
Process/Acti Process/Activity
Producer
Information
Receiver
Information
Exchanged
FP7-ICT-318023/ D1.1 ver 2
No.
vity
PS2.0
1
Update
LVGC
operation
Provide
update of
the LVGC
operation
settings
PS2.0
2
Update
LVGC
prediction
informatio
n
Provide
update of
the LVGC
data for
prediction
PS2.1
Periodic
Load and
Production
Prediction
PS2.2
Periodic
Metering
PS2.3
Periodic
Distributed
Generation
PS2.4
Periodic
PS2.5
Periodic
Control
Re-planning
PS2.6
Periodic
Charging
Load profile
update
PS2.7
Overvolta
ge/Curren
t
Limit
Production
Page 75 of 244
(Actor)
(Actor)
The DMS provides
information to the
LVGC to update highlevel operation
objectives as well as
changes in data
models such as grid
topology information,
newly connected
charging stations etc.
Information is pushed
(or pulled) from
information services
that are useful in the
LV grid management
operation such as
weather data.
DMS
LVGC
- Setpoints
- Settings
- Data models
(e.g. grid
topology)
Information
Services
LVGC
- Weather
data
- Expected
load profiles
-…
The LVGC predicts the
expected production
and load a predefined
time into the future
for planning purposes
Current load in
different busses of
the LV grid
Current generated
power in different
busses of the LV grid
Set Available power
for EV charging to all
charging stations
The LVGC plans the
local power and
energy resources to
maintain service
quality within
acceptable limits. It
may perform this
planning based on
setpoints from the
MV level.
CSO updates the
schedule considering
the preferred loads
from aggregator and
the CSO available
power constraints
If overvoltage/
over-current events
occur the LVGC can
choose to limit the
production in critical
periods to maintain
LVGC
LVGC
Updated
prediction
profiles
Metering
Aggregation
LVGC
Metering
Aggregation
LVGC
LVGC
Charging
Station
controller
LVGC
Load
information
on busses
Generated
information
on busses
Available
power profile
LVGC
Power and
Energy
control plan in
the LV grid.
Charging
Station
Controller
LVGC
EV Loads
update
LVGC
Photovoltai
c Inverter
Production
Limits
FP7-ICT-318023/ D1.1 ver 2
power quality.
PS2.8
Service
quality
deviations
Change
battery
control
objectives
PS2.9
Power
quality
deviations
Change
demand
objectives
PS2.1
0
Events/Al
arms
Monitoring
events/Alar
ms
A local battery in the
grid can be requested
to change its
objectives to
increase/decrease
load to aid in the
operational
parameters
The LVGC can request
flexibility services
from the Charging
Station Controller to
increase/decrease
load now and in the
future. This involves
hard constraints on
power availability.
A monitoring event or
alarm (depending on
criticality level) is
raised and sent to the
DMS to report about
the current and past
state of the LV grid.
LVGC
Battery
Inverter
Setpoints/obj
ectives for
battery
control
LVGC
Charging
Station
Controller
Setpoints/obj
ectives for
-charging
demand
flexibility
- Available
power profile
LVGC
DMS
Event/Alarm
Scenario PS3 adds the view of EV aggregator/Utility
Scenario (see Figure 80 & Figure 81)
Scenario:
Step
Event
No.
PS3: Energy Market
Name of
Description of
Process/Activi Process/Activity
ty
Sell
Local energy sources
Production
(storage and production)
sell energy resources to
an aggregator.
Sell
Local energy resources
Aggregated
across several LV/MV
Production
grids are aggregated
enabling the aggregator
to act on the retail
market
Information
Producer
(Actor)
DER/Battery
owner
Information
Receiver
(Actor)
Aggregator
Information
Exchanged
Aggregator
Market
Aggregated
energy
production
capabilities
PS3.1
Periodic
PS3.2
Periodic
PS3.3
Periodic
Provide
EV charging
demand
The charging station
forwards an already price
optimized demand curve.
(alternatively, it forwards
the demand plus its
flexibility and the
aggregator performs the
price optimization)
CSO
EV
Aggregator
(retailer)
demand +
flexibility
capabilities
PS3.4
Periodic
Price signals
pricing information is
provided to energy
providers/aggregators.
Market
EV
Aggregator
Price signals
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Energy
production
capabilities
FP7-ICT-318023/ D1.1 ver 2
PS3.6
Periodic
Price signals
The CSO uses the price
information and the
flexibility of the charging
operation to find an
optimal demand curve
EV Aggregator
CSO
Price
signals
PS3.5
Periodic
Price
Optimized
Energy buying
The aggregator buys
updates the energy need
by buying on the intraday
market
EV Aggregator
Market
Demand
The fault/anomaly scenarios AS1 and AS1 address network interruptions: AS1- the connection
between LVGC and a charging station and AS2 – the connection between meters and LVGC is
interrupted.
Scenario (Subscenario)
Scenario
AS1: EV demand control disrupted
Step
No.
Event
Name of
Process/Activity
Description of
Process/Activity
Information
Producer
AS1.1
LVGC CS
connection
lost
Scheduling under
av. power
uncertainty
Enter precautious
mode. Refuse new
requests
CSO
Information
Receiver
Charging
Spots
Information
Exchanged
reduced
charging
duration
Scenario
AS2: Metering data flow disrupted
Step
No.
Event
Name of
Process/Activ
ity
Description of
Process/Activit
y
Informati
on
Producer
Information
Receiver
AS2.1
consumption
Metering
samples
missing
Estimate
load under
uncertainity
Conservative
calculation of
available
power
LVGC
CS
controller
Reduced Available
power
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5 UC ICT requirements & success KPI
In any system development process the requirements represent the definition of the system
functions and their desired properties. As such the identification of UC requirements has been
considered as mandatory to the further development of the SmartC2Net UC.
In addition to UC requirements a list of Key Performance Indicators (KPI) has also been provided in
this initial phase as supporting the next development and evaluation activities of the SmartC2Net
components.
The requirements and the KPIs are determined from the use case analysis and they are studied under
several perspectives in order to identify those mostly related to the SmartC2Net objectives. Their
mapping with the SmartC2Net WPs allows understanding how the project developments will be
addressed and evaluated.
For the collection of the requirements and KPIs two templates have been used. For sake of simplicity
and readability the revised version of the requirement and KPI tables are collected in Annex C - Table
of Requirements and Annex D - Table of KPIs. In the next sections the respective templates are
presented first, followed by the relevance indications elaborated from the tables.
5.1
Requirement Template
Each requirement is characterized by several fields which both identify and characterize it. The
description of the characterization field is reported in Table 3:
Field
Value
Requirement ID REQ_<nnn>
Level
SYS
UC
CO
Priority
N
F
W
UC
Title
Category
Page 78 of 244
Name
Description
This field contains a unique identifier of the requirement
where <nnn> is a unique sequential number which
identifies the requirement
This field specifies the logical level where the
requirement is allocated. A requirement can be a
general one specified for the whole system or a specific
one for an individual component
Whole system oriented
Use Case oriented
Individual component oriented
This field specifies whether the requirement is
considered for being created right now, or is a future
development or is desirable
Now: the requirement is taken into serious
consideration inside the project
Future: to be considered at some point in time
Wish: the requirement is considered desirable but not
yet scheduled in the project activities
This field specifies the reference UC if applicable
This field reports a brief description of the requirement
This field specifies the category of the requirements. For
example if the requirement specifies a functionality or is
dictated by standards.
FP7-ICT-318023/ D1.1 ver 2
Field
Value
Functional
Description
This category comprises requirements about the
functionality of the system/component
including
technical constraints such as:
 voltage ranges
 active/reactive power ranges/limits
 generation/load coefficients
 sample rates
 EV schedule time horizon/resolution
 generation/load profile time horizon/resolution
Architectural
Dependability
This category comprises architectural requirements
this category contains requirements about
 Availability: readiness for correct service
 Reliability: continuity of correct service
 Integrity: absence of improper system alterations
 Maintainability: Ability to undergo modifications and
repairs
Security
This category is a composite of the attributes of:
 Availability for authorized actions only (access
control, authorization, deny of service)
 Confidentiality: absence of unauthorized disclosure
of information
 Integrity: data integrity, non-repudiation
Performance (Quality This category comprises some specific performance
of Service)
requirements including the following time constraints:
refresh time, response time, actuation time
Interface
This category comprises interface requirements.
Communication
This category comprises the requirement about the
communication infrastructure including the following
subcategories:
 Communication size: possible measures are:
bandwidth, data rate, range (Km), frequency band
 Communication performance: possible measures
are: delay, overhead
 Communication availability: possible measures are
sec-min-hour/year
 Communication security: possible measures are #
lost
packets/messages,
#
discarded
packets/messages, # faked messages
 Communication cost: possible measures are €/y per
connection point
Environment
This category comprises requirements about the
operational environment in which the system shall work.
Standard/Regulation
Description
This category comprises requirements dictated by the
standards.
The description of the requirement
Table 3 Requirements Template Description
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FP7-ICT-318023/ D1.1 ver 2
5.2
Requirement analysis
Requirements represent an essential step in order to understand what the specific necessities of the
different use cases are. These functional and technical properties will drive the developments in the
other WPs. In particular these requirements will be used as inputs for the adaptive monitoring
(WP2), for addressing the adaptive communication (WP3), for the grid control algorithms (WP4), for
the validation of the models in WP5 and for the testbeds developed in WP6. In the requirement
study the mapping between the specific item and the related project WP is presented and some
analysis proposed.
Figure 25 provides an overview of the distribution of the four use case requirements over the
different project WPs.
Figure 25 Requirements: Project WP mapping
WP5 and WP6 (modelling and experimental analysis) are the most represented because the major
part of the requirements offers input for the evaluation work packages. In particular Figure 26
displays the mapping with the Monitoring, Communication and Control WP and
Figure 27 shows
as the requirements are subdivided according to the model or testbed analysis.
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FP7-ICT-318023/ D1.1 ver 2
Figure 26 Requirements: WP2, WP3 and WP4 mapping
Figure 27 Requirements: WP5 and WP6 mapping
These requirements are obtained considering different aspects as functionality, performance
(availability, latency...), maintainability (monitoring), and security (protection, authentication,
authorization …). Detailed lists of requirements tend to be extensive. In this section an analysis of the
requirements annexed in Annex C - Table of Requirements is presented. The whole set of
requirements is composed by a total of 136 items.
The subdivision considering the different use cases is depicted in Figure 28. The Medium Voltage
Control use case includes 46 requirements, the Electric Vehicle in Low voltage use case includes 22
requirements, the External Generation Site use case includes 26 requirements and the AMR/CEMS
use case includes 42 requirements.
Figure 28 Requirements: Use Case
Figure 29 shows the distribution of the requirements considering the different categories: Functional,
Communication, Interface and Security are the most represented as can be inferred by the scope of
SmartC2Net project.
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FP7-ICT-318023/ D1.1 ver 2
Figure 29 Requirements: Category
Another index/view that can be considered by the requirement analysis is the Level field, whose
graph is represented in Figure 30. More than half of the total requirements are of system level.
Figure 30 Requirements: Level
The list of requirements comprises a large number of items, it is important to highlight which of them
are more relevant for the project development. In order to obtain this indication it is possible to
analyse the priority field assigned to each requirements. Figure 31 shows the distribution of the
priorities and it is possible to note that the main part is tagged as “N” (now). This means that these
requirements are currently addressed.
Figure 31 Requirements: Priority
In the following pictures (Figure 32 Figure 39) the graphs corresponding to UC specific
requirements are presented. From a first look, it can be observed that some UC, e.g. the EGS, only
included a subset of the template categories/levels. This means that those requirements have been
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FP7-ICT-318023/ D1.1 ver 2
identified as relevant to the SmartC2Net objectives, and it has not to be interpreted as a restriction
of the type of smart grid application that the UC is representing.
Figure 32 MVC UC Requirements: Category
Figure 33 MVC UC Requirements: Level
Figure 34 EV UC Requirements: Category
Figure 35 EV UC Requirements: Level
Figure 36 EGS UC Requirements: Category
Figure 37 EGS UC Requirements: Level
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FP7-ICT-318023/ D1.1 ver 2
Figure 38 CEMS AMR UC Requirements: Category
Figure 39 CEMS AMR UC Requirements: Level
The UC developments in the next phases of the project will allow refining the current list of UC
requirements in the Annex C.
5.3
KPI Template
As for the requirements, also for the KPIs a template is introduced. In Table 4 the fields involved and
their brief description are provided.
Field
Value
KPI_id
KPI_<nnn>
UC
KPI name
Description
text
text
text
Category
Scope
Goal
Technical_Power
Technical_Communication
Social
Economical
General
Customer
DSO
CSO
Aggregator
CSP
Description
This field contains a unique identification
number of the KPI where <nnn> is a unique
sequential number which identifies the KPI
UC reference
Name of the KPI
A brief description
This field specifies the category of the KPI, for
example if it is a technical ,or social or
economic KPI
KPI related to technical power aspects
KPI related to technical communication aspects
KPI related to social aspects
KPI related to economic aspects
General KPI
This field specifies the scope of the KPI, in
terms of the main entities involved
Customer oriented
DSO oriented
Charging Station Operator oriented
Aggregator oriented
Communication Service Provider oriented
Expectation, objective
Table 4 KPIs Template Description
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5.4
Key Performance Indicators (KPIs) analysis
The Key Performance Indicators (KPIs) represent a way to identify the important values to take into
account for the evaluation of the success of a proposed solution. Accordingly, choosing the right KPIs
relies upon a good understanding of what is important for the use case in relation to the SmartC2Net
objectives. The KPIs will be used in the others WPs, in particular in WP2 for the analysis of the
monitoring solutions, in WP3 for the validation of the communication architecture approaches
defined and in WP4 for estimate if the control techniques developed are satisfactory. Also the
assessment framework developed in WP5 and testbed implementation in WP6 take into account the
KPIs in order to evaluate the technologies and algorithms considered in the project.
Figure 40 shows the mapping of the KPI listed in the Annex D with the different project WP: we see
as the identified KPIs will be used in order to validate the model and testbed implementation. The
main WPs involved are the model related WP (WP5) and the testbed WP (WP6).
Figure 40 KPIs: Project WP mapping
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WP5 and WP6 (model and testbed work packages) implement the solutions developed in WP2, WP3
and WP4. All the KPIs addressed by Monitoring (WP2), Communication (WP3) and Control (WP4)
WPs are also addressed by one or both the model (WP5) and testbed (WP6) WPs. For this reason a
more interesting analysis is presented in
Figure 41 where we see as the Monitoring (WP2),
Communication (WP3) and Control (WP4) related KPIs are subdivided and in
Figure 42 as these KPIs are evaluated by means of model (WP5) and testbed (WP6) analysis. The ICT
related KPIs are relevant for the SmartC2Net project: they are spread over the different WPs.
The KPIs important for some aspect of smart grid, but not for the scope of the SmartC2Net project
are not addressed by any WP.
Figure 41 WP2, WP3 and WP4 mapping
Figure 42 WP5 and WP6 mapping
In the following we focus the KPI analysis considering the four use cases. The KPI complete list is
presented in the Annex D. In the progress of the project they will be refined and those KPIs that will
be common to all UCs will be identified as global or smart grid level KPIs.
Figure 43 KPIs: Use Case
A total of 68 KPIs are identified and Figure 43 plots their distribution per use case.
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Figure 44 KPIs: Scope
If the scope field is selected as the analysis index, in Figure 44 it is possible to notice that the major
part of KPIs is DSO oriented. This is not surprising, as many UC objectives are related to the
optimization from the utility perspective.
Figure 45 KPIs: Category
Another interesting field that can be considered is the category: in Figure 45 it is possible to see as
the main categories are the technical ones. In particular as we can suppose, the power and
communication categories are the most represented.
In the following pictures (Figure 46 - Figure 53) the specific use case graphs are presented showing
the UC specific focus.
Figure 46 MVC UC KPIs: Category
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Figure 47 MVC UC KPIs: Scope
FP7-ICT-318023/ D1.1 ver 2
Figure 48 EV UC KPIs: Scope
Figure 49 EV UC KPIs: Category
Figure 50 EGS UC KPIs: Scope
Figure 52 CEMS AMR UC KPIs: Scope
Figure 51 EGS UC KPIs: Category
Figure 53 CEMS AMR UC KPIs: Category
6 Preliminary overall architecture
Starting from a bottom-up analysis of the individual use case architectures a preliminary high level
architecture is derived at the aim of highlighting the interactions among the respective control
components and ICT networks. This integrated view allows having a comprehensive picture of the ICT
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aspects addressed by the SmartC2Net project. It is important to have not only the specific use case
view, but also a global outlook in order to understand what are the common aspects and interactions
as well as the parts of architecture that the different use cases share.
This preliminary version of the overall architecture is aimed at defining the logical interfaces of the
different control components. Where alternative architectures might be envisioned for a specific use
case, e.g. for the Home Energy Management UC, we decided to include all the alternatives to cover in
the overall architecture as many case instances as possible.
6.1
Global architecture
One of the main targets of the SmartC2Net project is to demonstrate that it is feasible to have a
robust control of the power grid using and open and heterogeneous communication infrastructure.
In fact, while at the Generation and Transmission areas, the communication infrastructures are
normally private and protected from external access, the Smart Grid extends the areas where the
communication between devices is required to the medium and low voltage areas, which were, till
now, unobserved and uncontrolled. The proposed preliminary architecture aims at satisfying the
requirements of power grid monitoring, communication network monitoring and grid control
associated with the Use Cases and that will be developed in WPs 2, 3 and 4. This architecture may
nevertheless be further tuned during the project evolution.
6.1.1 Layered architecture
The proposed architecture maps the architecture of the Distribution System, by having components
in the different sites that can be found in a typical electrical distribution grid.
Different areas are involved: there are equipment and systems located at the Central Management
Level, at the Primary Substations, at the Secondary Substations and at the Customer Premises.
In particular the Distribution Management System (SCADA/DMS) and the Demand Response System
are placed at the Central Management Level. Since they have a view of the entire power grid and
communication network, their actions may have a global scope.
The Medium Voltage Grid Controller (MVGC) is located at the Primary Substation (HV/MV). Its
actions will have a local scope, interacting with the Primary Substation and with other systems
connected to it, namely DERs (MV) and Secondary Substations.
The Low Voltage Grid Controller (LVGC) is located at the Secondary Substation (MV/LV). Its actions
will also have a local scope, with low voltage devices and systems, connected to the Secondary
Substation, namely Customer Installations and DERs (LV).
At the Customer Premises several equipment and systems are placed: Smart Meter, Customer Energy
Management System, PV inverter, EV Charger, flexible and non-flexible loads.
Other systems outside the Distribution Grid will also be taken into consideration, namely the Energy
Management System, owned by the TSO, Weather Forecast Information, Market Operators, EV
Charging Operators, Telecom Operators Information Systems and third party Aggregators.
Equipment and systems that may exist in the Distribution Grid but that may not be owned by the
DSO, like Distributed Energy Resources (Distributed Generation, Flexible Loads) are also considered.
The following figure shows the different sites, equipment and systems as well as the communication
networks that connect them.
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Figure 54 Overview of the SG architecture
6.1.2 Distribution of functions
The proposed architecture also allows the distribution of functions across several locations and
equipment, allowing the processing of data close to the data sources and data users.
At the Central Systems Level the following functions will be implemented:
 Global Grid Monitoring
 Global Grid Management
 Global Communications Network Monitoring
 Global Communications Network Management
 Demand Response
At the Primary Substations the following functions will be implemented:
 Distribution Grid Monitoring
 Distribution Grid Management
 Communications Network Monitoring
 Communications Network Management
 Distributed Energy Resources (DER) control (MV)
At the Secondary Substations the following functions will be implemented:
 Distribution Grid Monitoring
 Communications Network Monitoring
 Demand Response
 Load Management
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 Distributed Energy Resources (DER) control (LV)
At the Customer Premises the following functions will be implemented:
 Load Management
 Micro generation Management
 EV Charging
Some functions may extend a single location and will be distributed across several sites. The EV
Charging Use Case is an example of such a situation.
6.2
Use Case mapping
The following sections describe how the proposed architecture maps the chosen use cases.
In order to provide a global vision of the infrastructure and not only restricted to the single use case,
the following figures show how the different Use Cases and the different equipment, systems and
communication networks are related.
Figure 55 gives a general view of the Use Cases and the equipment, systems and communication
networks that are going to be involved in each of the Use Cases.
The figure shows for each use case, which sites and which equipment and systems are involved.
External systems are also shown.
It can be seen that the Use Cases are not isolated from each other and more than one Use Case
involves the same sites and the same equipment, systems and communication networks, sharing a
common architecture.
It can be seen in the figure that the Medium Voltage Grid Controller, DER (MV) and Flexible Loads are
involved in the Medium Voltage Control and the External Generation Site Use Cases.
Also the Low Voltage Grid Controller and several equipment and systems located at the Customer
Premises are involved the External Generation Site, Electrical Vehicle Charging and Customer Energy
Management System and Automated Meter Reading Use Cases.
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Legend:
DSO: Distribution System Operator
WAN: Wide Area Network
MVG: Medium Voltage Grid
DER: Distributed Energy Resource
AN: Access Network
LVG: Low Voltage Grid
UC: Use Case
MVC: Medium Voltage Control
CEMS: Customer Energy Management
System
AMR: Automated Meter Reading
EVC: Electrical Vechicle Charging
MVC UC
DMS - Distribution Management
System
DSO
Center
WAN
External Generation Site UC
Primary
Substation
MVG
External Systems
DER
WAN
Information Service
Flexible
Load
Aggregation Controller
LVG
Secondary
Substation
Charging Station &
Routing Reservation
CEMS & AMR UC
EVC UC
AN
Weather forecast
Distribution Market
Customer
CEMS
Charging
Station
Figure 55 Overview of Use Cases mapping
Figure 56 provides a detailed view of the system architecture, mapping all the involved equipment
and systems, either directly associated with the distribution grid or external, and also the
communication links that connect them. In particular the Logical Interfaces (LI) are represented.
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Legend
LI1: Internal Communication
TSO: Transmission System Operator
DSO: Distribution System Operator
WAN: Wide Area Network
MVG: Medium Voltage Grid
DER: Distributed Energy Resource
AN: Access Network
LVG: Low Voltage Grid
UC: Use Case
MVC: Medium Voltage Control
CEMS: Customer Energy Management System
AMR: Automated Meter Reading
EVC: Electrical Vechicle Charging
OLTC: On Load Tap Changer
NNAP: Neighborhood Network Access Point
LI2: TSO Communication
LI3: Control communication between Control Center and primary and secondary substation
LI4: Metering communication
LI5: Control communication inside LVG
LI6: Local control communication
LI7: Control communication inside MVG
LI8: Communication between External System and SmartC2Net
Central
Management
LI_DMS_DMC
LI_DMS_TSO
TSO
DMS
Demand/Response Management
Control
Metering Head-end
System (HES)
LI_DMC_TariffMgmt
External Systems
Weather Forecast
LI_CSRR_AggContr
LI_Weather_LoadForecast
Load Forecast
Automated
Meter Data
LI_GenForecast_MDMS Management
System
LI_Weather_GenForecast
Tariff Management
LI_AC_DM
LI_DM_Info
Information Service
LI_DMS_HES
LI_DMS_GenForecast
Distribution Market
Aggregator Site
(can be included
with DSO/TSO)
LI_DMS_LoadForecast
Generation
Forecast
LI_DMS_GridDB
LI_GenForecast_GridDB
Grid DB
Manage
ment
External Systems
MVC UC
LI_DMS_AggContr
Aggregator Controller
Charging Station &
Routing Reservation
HV/MV Primary
Substation
LI_DMS_MVGC
LI_MVGC_SAS
MVGC
Primary Substation
DER Control
LI_MVGC_EnergyStorage
Energy Storage
LI_SAS_OLTC
LI_SAS_CapBank
LI_MVGC_Wind
Capacitor Bank
Wind Turbines/plants
OLTC
LI_DMS_NNAP
LI_HES_NNAP
UPS
DER
(generic)
Flexible Load
(generic)
LI_MVGC_FlexLoad
Secondary
Substation
LI_DMS_LVGC
MV/LV
Secondary
Substation
LI_MVGC_LVGC
LI_MVGC_UPS
LI_MVGC_DER
(generic)
LI_LVGC_NNAP
Low Voltage Grid Controller
Flexible Load
Control
LI_MVGC_EVCS
EV Charging Station
LI_MVGC_Ref
Metering Aggregation
(NNAP)
Refrigerator System
External
Generation Site
UC
LI_HES_PSM
LI_PSM_NNAP
AN
LI_LVGC_CSC
LI_LVGC_AMR
LI_CSC_AggContr
Customer
LI_EMG_AggContr
LI_HES_AMR
LI_AMR_NNAP
Local LV grid
resources (DER)
LI_HES_SM
LI_SM_NNAP
LI_LVGC_PVInv
AMR
LI_EMG_AMR
Simple external
Consumer display
Charging Station
Controller
EMG
EVC UC
LI_SM_PV
Smart Meter
LI_EMG_FlexLoad
LI_AMR_FlexLoad
LI_AMR_DER
LI_SM_WT
LI_AMR_NonFlexLoad
EV
LI_SM_mCHP
LI_AMR_Display
LI_EMG_DER
LI_CS_EV
Charging Spot
Public
Smart Meter
LI_PSM_CS
Public
Charging
Station
LI_EMG_HA
LI_CSC_CS
LI_EMG_CS
Battery Inverter
LI_EMG_Display
LI_AMR_CS
LI_LVGC_BatteryInv
Private
Smart Meter
LI_EMG_NonFlexLoad
LI_PVInv_
BatteryInv
Photovoltaic Inverter
Micro-combined
Heat and power unit (Micro-CHP)
Photovoltaics
Wind Turbine(s)
Flexible Load
LI_PrSM_CS
Charging Spot
LI_CS_EV
Non flexible load Flexible Load
Home automation
DER
EV
end device
CEMS & AMR UC
Private
Charging
Station
Figure 56 Detailed view of Use Cases mapping
In the Medium Voltage Control use case, the SCADA/DMS, located at the Central Systems Level
communicates with the Medium Voltage Grid Controller located at the Primary Substation through
the logical interface LI_DMS_MVGC in Figure 56. To interact with the Primary Substation equipment,
communication between the Medium Voltage Grid Controller and the Substation Automation System
will be required (logical interface LI_MVGC_SAS).
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In order to perform the voltage control, the Medium Voltage Grid Controller needs to receive
measurements from and send setpoints to DER (MV) and Flexible loads. This exchange of data is
performed using the logical interfaces of type LI7.
Communications of the SCADA/DMS with external systems will also be required, namely
communications with the Energy Management System owned by the TSO (logical interface
LI_DMS_TSO), the Weather/Load Forecast Systems and Aggregator (logical interfaces
LI_DMS_GenForecast and LI_DMS_LoadForecast).
In the Electrical Vehicle Charging use case, the SCADA/DMS, located at the Central Systems Level, the
Low Voltage Grid Controller located at the Secondary Substation and the EV Charger, Smart Meter
and Micro-generation located at the Customer Premises will be involved.
Communication with external systems, namely Market Operators, Charging Station Operators and
Routing Reservation systems will be required.
In Public Charging Stations, the Charging Station Controller will also be involved.
n the External Generation Site use case, the SCADA/DMS and the Demand Response System, located
at the Central Systems Level, the Low Voltage Grid Controller located at the Secondary Substation
and the flexible loads and Micro-generation located at the Customer Premises will be involved.
DER (Distributed Generation and Flexible Loads) connected to the Medium Voltage Grid will also be
considered.
In the Automated Meter Reading and Home Energy Management use case, the SCADA/DMS, located
at the Central Systems Level, the Low Voltage Grid Controller located at the Secondary Substation
and the Home Energy Management System and Smart Meter located at the Customer Premises will
be involved.
Other devices like flexible loads, Micro-generation (PV inverters, Micro-CHP), EV chargers, in-Home
Automation devices, Consumer Display, will also be considered. The Aggregator, the Metering Headend System and an EV charging spot are also involved in providing the functionality of the
AMR/CEMS UC.
This first sketch of the high level architecture provides a view of each smart grid application
integrated in the global smart grid control, highlighting the main logical component interfaces. This
overall architecture has to be considered as preliminary and will be updated at the end of Year 2
according to the progress of WPs 2-5 and to the lab prototype setup in WP6. Starting from this
preliminary overview architecture the other WPs take inputs for monitoring, control and
communication aspects. Also the development of the System Assessment and the Test Beds need
information obtained from this architecture.
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7 Conclusions and Outlook
This deliverable includes the control scenarios analyzed in SmartC2Net and provides many
information about their ICT architectures. In particular four use cases representative of the Smart
Grid domain are described and critical anomalous scenarios related to faults and threats identified.
From the energy market model the business driver and requirements associated with the use cases
are analysed, allowing to compare the possible technological and architectural options in the use
case over their benefits and their architecture impacts.
A first sketch of the high level architecture is presented with the specific aim of developing a view of
each smart grid application integrated in the global smart grid control, highlighting the main logical
component interfaces. However the overall architecture has to be considered as preliminary at this
project phase and to be updated at the end of Year 2 according to the progress of WPs 2-5 and to the
lab prototype setup in WP6.
The outcome from the UC analysis and the overall architecture have provided inputs to all the other
project WPs, defining the requirements and the architecture border for the development of the
Adaptive Monitoring (WP2),the Adaptive Communication Solution (WP3), the Adaptive Control
(WP4), the System Assessment (WP5) and the Test Beds (WP6) that will focus on the UC
requirements. Some fault and attack scenarios identified by the UC analysis will be modeled in the
System Assessment (WP5) and implemented in the Experimental Prototypes (WP6), where the
impact of the use case integration in the overall architecture on the grid operation will be analyzed
from a technical stand point. In the last phase of the project the output of the economic analysis will
be re-considered in the exploitation task (WP7) to define the business impact of the SmartC2Net
solutions.
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8 Bibliography
[ADL12]
Arthur D. Little: Telco and Utility: Friend or Foe?, Energy & Utilities Viewpoint, 2012.
Web access:
http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_
Friend-or-Foe.pdfWeb access:
http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_
Friend-or-Foe.pdf
[AFSP07]
L’Abbate, A., Fulli, G., Starr, F., & Peteves, S. D. (2007). Distributed Power Generation
in Europe: technical issues for further integration. Joint Research Center Institute for
Energy. WWW. CaRBoNWaRRooM. CoM2007.
[ANME12]
Analysis Mason: Case study: Telenor Connexion’s approach to an M2M smart grid
implementation in the UK; May 2012; Steve Hilton
[BDCN12]
C Baldi, G Di Lembo, F Corti, F Nebiacolombo, “Monitoring and Control of Active
Distribution Grid” ”. CIRED 2012 Lisbona (PT), 29-30 May 2012
[DoW]
SmartC2Net – Description of Work
[DGPT12]
G. Dondossola, F. Garrone, G. Proserpio, C. Tornelli, 2012, “Impact of DER integration
on the cyber security of SCADA systems – the Medium Voltage regulation case
study”. CIRED 2012 Lisbona (PT), 29-30 May 2012
[EPRI10 ]
M. Wakefield: Methodological Approach for Estimating the Benefits and Costs of Smart
Grid Demonstration Projects. Electric Power Research Institute (EPRI), 2010.
[FIER11]
FierceSmartGrid: Telecom's evolving role in smart grid 2011. Web Access:
http://www.fiercesmartgrid.com/story/telecoms-evolving-role-smart-grid/2011-04-20
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[FIEX12]
Financial Express: M2M device connections in automotive sector to rise to 277m in
2020. 2013. Web access: http://www.thefinancialexpressbd.com/print.php?ref=MjBfMDNfMDVfMTNfMV84OV8xNjIwOTg
[FSS12]
SGCG/M490/B_Smart Grid Report First set of Standards Version 2.0 Nov 16th 2012
[HaSn89]
Hakansson, H., Snehota, I.: No Business is an Island: The Network Concept of Business
Strategy. Scandinavian Journal of Management (1989) 187–200
[IEC104]
IEC TC57 IEC 60870-5-104 International Standard
[IEC61850]
IEC TC57 IEC 61850(-7-420) International Standard
[IEC 62351]
IEC TC57 IEC 62351 International Standard
[IEC TC8]
Use Case Approach Part 2 - Definition of Use Case Template, Actor list and
Requirement List for Energy Systems – NWIP 8/1307/NP 20 June 2012
[INFO12]
Informa: M2M Communications - Turn Potential into Profit. 2012. Web Access:
[INT12]
http://www.informatandm.com/wp-content/uploads/2012/04/M2MCommunications.pdf
InTech: Wired vs. wireless in utility markets. Web Access
http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentD
isplay.cfm&ContentID=89205
[LECH08]
D. Lechner, W. Granzer, and W. Kastner. Security for KNXnet/IP. In Konnex Scientific
Conference, November 2008
[NoRa94]
Normann, R., Ramirez, R.: Designing Interactive Strategy: From the Value Chain to the
Value Constellation. John Wiley & Sons (1994)
[NTS12]
National Technical System – Advanced Technologies: Wired vs wireless in utility
markets, Web access http://smartgrid.testing-blog.com/2012/04/15/wired-vswireless-in-utility-markets/
[Petroni12]
Petroni P., Smart Grids Operation, automation and protection issues CIRED 2012
Lisbon (Portugal) 29-30 May 2012
[ScTa12]
Schleicher-Tappeser, R.: The Smart Grids Debate in Europe. SEFEP working paper,
2012. Web access: http://www.sefep.eu/activities/publications-1/SEFEPSmartGrids_EU.pdf
[SG-CG/IS 12] CEN-CENELEC-ETSI Smart Grid Coordination Group Smart Grid Information Security
2012
[UC200]
SGSP Working Group Use Case WGSP-0200
[UCC]
SGCG/M490/E_Smart Grid Use Case Management Process — Use Case Collection,
Management, Repository, Analysis and Harmonization
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9 Annex A - Value Networks
Based on the SmartC2Net use case description (see Section 4) two Value Network (VN) models are
created and presented in this section: a generic classical grid and new SmartC2Net / Smart Grid
model. In lieu of value chains (activity chains) or business models (intra-firm concept), VNs are
capable of expressing (non-sequential) value streams in an inter-firm context, also see [HaSn89] and
[NoRa94|.
Thus, the specified VNs aim at capturing relevant entities, i.e., actor roles, from a business
perspective. In this way, technical processes or systems are eliminated from this perspective.
9.1
Electrical Grid Value Network
In order to be able to extrapolate economic differences between the “classical view” on electrical
grids and on the smart grid presented by SmartC2Net, the VN of “classical” electrical grids will
subsequently be briefly revisited by means of its entities and main value flows, and illustrated in
Figure 57.
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long-term trading/reservat.
energy
Ene r gy
Aggr e ga t or
$
energy
$
W h ole sa le
Market
$
energy &
flexibility
energy
energy
$
Ener gy
Ge ne r a t or s
/ D ER
En e r gy
Pr osu m e r
$
Re gu la t or
1
Re t a ile r
5
energy &
pricing
trade
3
CAM
TSO
physical attacks
faulty devices
human errors
...
2
$
metering
Ene r gy
Con su m e r
d is t
ribu
relia
$
D SO
te
bilit
1 Trade energy/flexibility
for balancing
y
2 Metering information
long-term
price sensitivity of
demand
(assisting stability)
3 comply to
agreements
Legend
Ch a r gin g
St a t ion Op.
CAM
… use case
specific role
Ene r gy
Con sum e r
… "eye ball" consumer
(own demand)
… (central) grid role
Re gula t or
… public authorities
Figure 57: “Classical” Electrical Grid Value Network
Page 99 of 244
4 demand & supply
forecasts
5 supply sbj. to
long-term pricing
agreements
FP7-ICT-318023/ D1.1 ver 2
9.1.1 Entities
9.1.1.1


9.1.1.2
“Eye ball” consumer in two flavours:
Energy consumer: The energy consumer is the classical consumer not providing any energy or
energy service to any other party.
Energy prosumer: The prosumer extends the role of a consumer by also generating energy
(see dedicated roles).
Energy sector:
Generation/Aggregation:
 Energy Generators / Distributed Energy Resources (DER): Power plants and small energy
generators (e.g. PVs) producing the energy to be delivered to customers or traded on
markets.
 Energy Aggregator: Aggregating individual DERs in order to act on (wholesale) markets
o Representing small actors (like individuals with their PVs) on wholesale market by
trading their resources appropriately
Market & Sales:
 Wholesale Market: A (wholesale) market where it is possible to buy and sell energy and
demand flexibility, i.e., short-term (next day, intraday), long-term, and energy balancing
trading.
o Often operated by “Power Exchange” entity
o Scheduled energy exchange & flexibilities (e.g. in terms of primary, secondary, and
tertiary reserves)
o High transmission capacity required in order to avoid arbitrage business due to
different price levels in Control Areas accessing the market
o Incentives for precise reservation requests, e.g. tailored auction mechanisms
o Base load and peak load differentiation
o Trading of intermittent energy resources, e.g., realized in Spanish and US markets4
 Retailer (Supplier, Trader): The retailer is the energy role having access to eyeball customers
by selling energy to them. It relies on an existing distribution network and the energy trading
on the wholesale market. It is responsible for acquiring required resources on the wholesale
market and may be confronted with compensation payments in case of unsatisfactory
physical delivery.
o Demand matching dynamicity in minutes (e.g. each 5 minutes) and price dynamicity
at ~ 30 minutes to 60 minutes5 at the minimum.
Distribution / Transmission / Balancing:
 Distribution System Operator (DSO): According to the Article 2.6 of the Directive: "a natural
or legal person responsible for operating, ensuring the maintenance of and, if necessary,
developing the distribution system in a given area and, where applicable, its interconnections
4
5
http://www.smartpowergeneration.com/spg/discussion/flexibility_is_needed_-_but_th
National
Electricity
Market
(Australia):
http://eex.gov.au/energy-management/energyprocurement/energy-pricing/how-the-energy-market-operates/
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with other systems and for ensuring the long-term ability of the system to meet reasonable
demands for the distribution of electricity".

Control Area Manager (CAM): The European interconnected grid is subdivided into large number of
control areas that control the power that flows across it. These areas are largely independently
operated. Power meters are installed on every power line that crosses a control area boundary, and
the readings are transmitted online to the respective control centres. The Control Area Manger (CAM)
is then responsible for the system stability. The CAM calculates in advance how much
electricity will be needed to cross the control area boundaries to fulfil the supply contracts in
place. The power stations within the control areas are operated in accordance with these
schedules. In many countries a differentiation between the roles of TSOs (see next
paragraph) and CAMs may not exist.
o Corrects short-term and long-term imbalances of energy demand and supply caused by
retailers (whether due to incorrect energy reservation or unexpected demand/supply
patterns), e.g. by using cold reserves, and forwards incurred costs to retailers → balancing of
Control Area
o Actively trades on wholesale market
 Transmission System Operator (TSO): According to the Article 2.4 of the Electricity Directive
2009/72/EC (Directive): "a natural or legal person responsible for operating, ensuring the
maintenance of and, if necessary, developing the transmission system in a given area and,
where applicable, its interconnections with other systems, and for ensuring the long- and
short-term (minutes) ability of the system to meet reasonable demands for the transmission
of electricity".
In addition, some use case specific roles may have to be acknowledged, which are detailed in Section
9.1.2.
9.1.2 Main Value Flows
The value flows capture relationships among actors. Here we identify three most significant value
flows and the main issue each of them addresses: (1) stability of the grid, (2) energy generation,
trading and delivery, and (3) regulation.
Stability of the grid: The CAM cares about stability on medium and long term and short term by
acting on the wholesale markets based on monitoring data and information exchanged with DSOs in
order to constantly balance the grid. The DSO and TSO globally coordinate agreements ensuring the
stability of the grid on coarser granular level, i.e. typically the interface is the CAM role.
Energy generation, trading & delivery: Generated resources are directly marketed on (wholesale)
marketplaces or first aggregated and then traded. Retailers then buy required energy to satisfy the
demands of their eyeball consumers. In some cases, energy may directly be sold by the aggregators
to industrial end consumers.
Regulation: The energy market is closely followed by regulatory authorities. The VN captures the
most important relationships where regulators (directly or indirectly) influence the business activities
of roles.
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9.2
SmartC2Net Value Network
With the transition towards smart grids, the resulting Value Network (cf. Figure 58) has to reflect a
series of changes.
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FP7-ICT-318023/ D1.1 ver 2
trade energy
long-term trading/reservat.
energy
energy
dynamic
trade-off
consumption –
trading
Ene r gy
Aggr e ga t or
$
{
$
Ener gy
Ge n e r a t or s
/ D ER
(semiautomatically)
modified
supply
flexibility
3
Re t a ile r
EV
Cha r gin g
St a t ion
Ope r a t or
$
registration
.
4
modified
demand
communication
problems
...
Ve n dor s
$
1
$+
erin
g in
fo
e.g., lookup service
$ / advertisement
7
D SO
reliability
attacks
faulty devices
human errors
metering
ring
mete c.
t
.
r
f
in e network infr.
$
1 (dynamic) self-control
incentives ($)
& metering inf.
Com .
N e t w or k
Ow ne r
m et
charge/
reserve
$
TSO
$
2
$
Ene r gy
Con su m e r
Re gu la t or
Con t r ol
Ar e a
M a n a ge r
$
energy &
(dyn.) pricing
En e r gy
Pr osu m e r
Aggr e ga t e d
EV Ch a r gin g
I n fr a st ruct ure
M a n a ge m e n t
trade
6
energy energy &
energy
$
W h ole sa le
Market
$
$
For e ca st e r
license
3 compensation if not
agreement compliant
Com .
Se r v ice
Pr ovide r
5
( Consult ing/
W e a t he r /
D e m a nd) $
2 Metering &
compensation claims
$
4 demand & supply
forecasts
5 Paid network services,
QoS guarantees, ...
{all-smart-grid-actors}
6 Trade energy/flexibility
for balancing the CA
I n fSP
7 Collective
energy trading
Legend
Ch a r gin g
St a t ion Op.
CAM
Ene rgy
Con sum e r
… use case
specific role
… (central) grid role
Com .
N e t w ork
Re gula t or
… "eye ball" consumer
(own demand)
Figure 58 – SmartC2Net Value Network (with special consideration of chosen use cases)
Page 103 of 244
… communication
services
… public authorities
FP7-ICT-318023/ D1.1 ver 2
Main aspects of these changes are summarized as follows:
 The dynamicity of interaction, information exchange and trading is most significantly
changed. More fine-granular interaction and cooperation is required – being enabled via
improved communication capabilities, i.e., introduction of communication service provider
to the VN
 Capabilities for influencing demand and supply are substantially improved
 Finer-granular metering capabilities in cooperation with modern communication
technologies are newly introduced
 Balancing requirements in the distribution grid are substantially changed
 The role of DSOs becomes more demanding when facing more DERs to be accommodated for
while maintaining a stable grid with the required power quality. Combined with liberalized
market structures, more intensive interaction between DSOs and retailers may be required;
however the current regulation of DSO role does not provide for it
 In the LV grid, aggregation of all information from grid assets for technical and commercial
purposes. Data exchange between different actors on the LV grids and upstream.
 More systematic integration of Electrical Vehicle (EV) charging, PVs, wind turbines, and
different size DERs or important new energy usages on the LV, MV and HV is required to
meet soaring demands and mitigate arising grid issues
 Usage, collection and transmission of more information lead to more regulatory
requirements in respect of data management
 Attack scenarios may also shift from physical-only scenarios to new constellations involving
communication networks and data manipulations.
On the other hand, the long-term business perspective modelled by the interaction of CAMs, DSOs,
and TSOs (see description below) will remain similar to the classical grid case.
The remainder of this section is organized in the description of entities and main value flows
depicted in the SmartC2Net Value Network representation.
9.2.1 Entities (Revised)
There are two different types of consumers: on the one-hand eyeball consumers aiming at satisfying
their own demands and on the other hand use case-specific additions.
9.2.1.1
“Eye ball” consumer
o Energy consumer: same as in the classical grid.
 The energy consumer may (but need not) provide Smart Metering Data to all
interested parties and might allow flexible load scheduling (this a specific
function for use cases such as AMR / CEMS) as a 3rd party service for energy
efficiency.
o Energy prosumer: same as classical grid.
 Adaptation of demand to the local supply may be offered as a 3rd party
service with high automation requirements
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
9.2.1.2
 E.g. via virtual metering, prosumers may directly trade their
resources with other consumers/prosumers. Virtual metering may
also be used in the case of separation of supply and demand location
of individual prosumers.
Dynamic demand & supply adaption as a service requires
customers/prosumers willingness to adapt their behaviour based on
perceived economic benefits.
Energy sector

Energy Generators / Distributed Energy Resources (DER): see classical grid.
o More flexibility and interaction with DSO may be required for balancing the grid
 Energy Aggregator: see classical grid.
The energy supply is then utilised by market entities (trading & sales):
 Wholesale Market / Local Markets: A (wholesale) market where it is possible to buy and sell
energy and demand flexibility
o See classical grid above
o Trading of local energy flexibilities / local balancing & shorter-term trading are
essential new features
 More dynamicity required esp. for distribution grid resources trading, e.g. in
seconds, and supply-demand balancing, e.g. in milliseconds.
 Higher importance of efficient trading of ancillary services (flexibilities), i.e.
entity requiring flexibility the most should be rewarded with an efficient
assignment (requires incentives and suitable auction mechanisms)
 Retailer
o More efficient trading may be required with ability to snatch more efficient deals on
better metering/ forecasting
The following central grid roles are recognized:
 Distribution System Operator (DSO): In addition to the classical case, the DSO is now
responsible for two-directional power flows and regional grid access for DERs, grid stability,
efficient integration/regulation of renewables at the distribution level and regional load
balancing (please also see CAM) for the case of smart grids. The DSO has central
responsibility for maintaining the stability and power quality in the distribution grid. Under
changed regulatory constraints, DSOs may aim at directly controlling local demand and
supply, offered as a special service. Beyond that, the use of metering information now
shared with the CAM (see next paragraph) may be diversified. The costs for maintaining the
power quality may also be diversified based on the new role of local supply or trading
(supply incentives; retailers compensation etc.) facilitating DSOs in active control of power
lines and flows in the distribution grid.
o Pricing updates (incentives) e.g. in milliseconds for balancing parts of the distribution
network
 Control Area Manager (CAM):
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
9.2.1.3




9.2.1.4
o Smart Grid: Clearer incentives / compensation mechanisms for unbalanced energy
demand & supply by retailers are required
Transmission System Operator (TSO): see classical grid.
Telco sector (complementary roles)
Communication Service Provider (CSP): The smart grid is about embedding advanced
communications and remote sensing into the electric power system to improve reliability,
optimize energy delivery, engage the consumer and expand the usage of renewable energy
resources. Wireless embedded machine-to-machine (M2M) solutions for utility automation
are becoming more important as they relate to the smart grid. Leveraging on established
relations with end user for wireless connectivity and on cost efficiency for deploying and
offering connectivity to DSO and TSO, Telecommunications companies will be playing an
increasingly greater role in common applications such as Automatic Meter Infrastructure,
Distribution Automation, Demand Response, supervisory control, data acquisition for SCADA,
building management, home energy management and electrical vehicle charging [FIER11].
The CSP is therefore the operator of the required communication network, i.e., provider of
telecommunication services like wireless access to meters. The CSP is also responsible for
providing Internet access to end customers at Customer Premises (CPs) – this may be
handled as bundled service or as independent contracts.
In addition the CSP can supply connectivity services to the DSO and the TSO for monitoring
and managing smart grid equipment. Depending on business conditions the connectivity
services provided could extend to a deeper integration between the CSP network and its
enablers and the DSO/TSO communication network and grid. In this case CSP can also enable
a series of market driver positively affecting the smart grid business case.
Communication Network Owner (CNO): CNOs are the owners of the communication
network on which the CSP operates. Often one entity may overtake both roles.
Vendor: Vendors provide infrastructure for communication networks, but also for metering
the grid and/or its data processing. Communication network vendors may act in the role of
the CSP by operating a network for a communication network owner (or several owners) due
to efficiency reason. This is a standard model common to mobile networks today.
3rd Party Forecasting Service: Beyond technical components assisting the forecasting of
supply or demand patterns in the future, external consulting services may be used.
Use case-specific roles
o EV Charging Station Operator (CSO): Operator of a Charging station – which is an
electrified parking lot with several Charging Stations (CSs) – is independent or owned
by Energy provider, DSO, etc. Thus, providing an equivalent service to filling stations
– please refer to the use case description for more detailed definitions.
 Somehow cooperates with DSOs (ensuring sufficient energy can be delivered
to cars of customers)
 Reservation system or comparable mechanism for balancing demand
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
Establishment of a sustainable business case, e.g., by combination with other
services like paid parking lots or garages
o E-Mobility Service Operator: System including services for EV owners to find charging
stations as well as for the charging station operator to manage several charging
stations (may sometimes legally be owned be CSOs or CS chains).
 Balancing of customers according ‘available energy’ (grid utilization, charging
slots, …)
 Guidance of customers / providing lookup services, e.g. integration with
SatNavs or apps and the related integration with navigation service
providers.
 Potential issue: Who operates this service across different charging station
providers? (Problem of universal access of information)
 Link to Information Service Providers potentially visualizing or using provided
data
o Information Service Providers: Commonly available services provided by a third
party, e.g. weather information needed to predict PV production or Aggregated EV
Charging Infrastructure Management (see below):
 May require access to data → potential problems with confidentiality of
information or varying market interests (e.g. competitors may not agree on a
single platform)
 Openness of market access may be nutritious, but difficult
 E.g., Aggregated EV Charging Infrastructure Management: Collectively acts on
energy markets, especially intra-day markets, for individual CSOs by
aggregating their energy demand requirements and placing bids at
marketplaces. If no such role exists, retailers may provide the energy directly
to CSOs–see Energy Consumer.
9.2.2 Main Value Flows (Revised)
The following paragraphs summarize and aggregate the main value flows in the VN. Further details
can be inferred from the visual representation as well as from the entity descriptions:
Stability of the grid: The CAM cares about short-, medium-, and long-term stability by carefully
monitoring the grid and influencing other actors to modify the demand or supply levels. Thus, CAMs
get active on the wholesale market, exchange information with DSOs and set energy reservation
requirements for retailers. CAMs finally correct imbalances between supply and demand through
reserves from the wholesale market. DSOs in contrast are responsible for assuring grid stability and
power quality on dynamic short-term basis in the distribution grid. Thus, in smart grids they may
actively influence demand of end customers or supply on the axis of DERs. This may be based on
incentives or regulated. The DSO and TSO globally coordinate agreements ensuring the stability of
the grid on coarser granular level, i.e. typically the interface is the CAM role. Long-term wholesale
agreements may also be dedicated to the role of TSO (besides the active balancing of the CAM role).
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Energy generation, provisioning & trading: In the case of SmartC2Net, DERs will have higher
importance and thus need to be better integrated and (decentrally) managed.
Regulation: Additional regulation may be necessary regarding the DER connection rules, the safety
and security of the smart grid and the protection of individuals, e.g., privacy and sensitive handling of
information.
Communication in Smart Grids: Communication networks are required for all smart grid entities due
to their requirement for exchanging information. All entities not operating their own network are,
hence, customers of a CSP. The most direct relationship may be established with DSOs probably
managing a series of sites with devices requiring the access to reliable communication infrastructure.
Nevertheless, also charging station owners, consumers, etc. may deliver information required for
balancing the smart grid or may receive information as added value (e.g. consumption statistics and
price signals). An important relationship also exists to consumers who themselves require Internet
access, but also Customer Premises Equipment (CPE) for realizing SmartC2Net use cases may require
connectivity. Thus, communication services essentially link the smart grid entities.
EV Charging: The central place for charging is the CS where demand and supply also need to be
balanced or coordinated. The purchasing of energy for each CS is typically collectively handled. This is
further assisted by a macroscopic view such as provided by E-Mobility Service Operators potentially
redirecting costumers in early stages. Such services may require a listing fee (registration) to be part
of a nation wide / EU-wide / global assistance. Eye-ball consumers may also pay fees for better
support or may have to consume advertisements (may not be possible on typical SatNav devices)
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10 Annex B - UC templates
10.1 USE CASE NAME: Medium Voltage Control
10.1.1 Description of the Use Case
10.1.1.1 Name of Use Case
ID
Use Case Identification
Name of Use Case
Domain(s)
Distribution Grid
Management / Smart
Substation Automation/
Distributed Energy
Resources
Voltage Control in Medium Voltage Grids connecting DERs
10.1.1.2 Version Management
Changes / Version
Version Management
Name
Domain
Author(s) or Committee
Expert
Date
v.0
based on the
CEN/CENELEC/ETSI
SGCG Use Case
WGSP-0200
25/01/2013
Giovanna Dondossola RSE
Roberta Terruggia RSE
v.1
11/03/2013
v.2
EAB feedback,
protocols
15/05/2013
Area of
Expertise /
Domain /
Role
Title
ICT for
Distribution
Grid
Operation
and
Substation
Automation
Researchers
Approval
Status
draft, for
comments, for
voting, final
Draft
Draft
Final
10.1.1.3 Scope and Objectives of Use Case
Scope and Objectives of Use Case
Related business case
Scope
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The introduction of Distributed Energy Resources (DERs) can influence the status of the
power grid. The behaviour of DERs can affects the capacity of the DSO to comply with the
contracted terms with the TSO and directly the quality of service of their neighbour grids.
DSO has to face with units whose behaviour is both unknown and uncontrollable and
investments on conventional reactive power control devices in substations may become
ineffective. This difficulty to meet the contracted terms and the quality of service standards
not only could be transferred into charges to the DSO, but also affects the TSO operation
because the scheduled voltages at grid nodes could not be observed and voltage stability
problems cannot be managed properly. In order to maintain stable voltages in the
distribution grid the Voltage Control function is introduced. This main goal can be extended
FP7-ICT-318023/ D1.1 ver 2
Objective
in order to achieve other important objectives as supply ancillary services, minimize the cost
and the KWh consumption, provide reactive power support for distribution buses, reduce
energy losses and provide compatible combinations of the above objectives.
The primary aim of this use case is to address the communication needs of a Voltage Control
(VC) function for medium voltage grids connecting Distributed Energy Resources (DERs). The
actions derived from the VC function are evaluated with the objective of defining an ICT
architecture suitable for security analysis. The VC use case is a didactic case illustrating the
need of cyber security in smart grid applications, first because its behaviour influences both
system operation and economy, second because of the high level inter-networking
requirements of its ICT architecture.
10.1.1.4 Narrative of Use Case
Narrative of Use Case
Short description – max 3 sentences
The Medium Voltage Control function optimizes the voltage profile and power flows to maintain a stable voltage at
customer site in a defined area of the distribution grid with distributed generators, flexible loads and other deployed power
equipment. The function involves different data flows both from internal and external actors that must be considered in
order to perform a cyber security analysis. The loss or corruption of the measurements and set points may cause cascading
effects with high impact on the power grid.
Complete description
The connection of DERs to medium voltage grids can influence the status of the whole power grid. Voltage profiles and
power flows in active distribution grids change dynamically, mainly because of the stochastic production of the renewable
sources. The power injected by distributed generators can overload feeder segments or raise the voltage beyond the limits
in parts of the grid. The behaviour of DERs can affect both the capacity of the DSO (Distribution System Operator) to comply
with the terms contracted with the TSO (Transmission System Operator) and the quality of service of their neighbour grids.
The automatic voltage regulation provided by the OLTCs (On Load Tap Changer) of the substation transformers and
compensation measures, as used in passive grids, may be insufficient to grant the supply requirements established by the
norm EN 50160. This difficulty to meet the contracted terms and the quality of service standards beside causing the
imposition of sanctions to the DSO, can also affect the TSO’s operation because grid nodes cannot maintain the scheduled
voltages and voltage stability problems cannot be managed properly.
The main purpose of the VC function is to monitor the status of the active distribution grid from field measurements and to
compute optimized set points for DERs, flexible loads and power equipment deployed in HV/MV substations. The function
monitors the voltage and power flow in critical points of the controlled grid. The status of the grid based on actual
measurements and grid topology as required by the control algorithm, is computed by a State Estimator, that creates an
accurate profile from available measurements. Optimization of the voltage profile is acquired by controlling reactive and
active power injection by distributed generators and energy storage equipment, and setting OLTCs and switched capacitor
banks. Besides, costs of control actions and load/generation forecasts in the area have to be taken into account to select
the appropriate control strategy. Considering the hierarchical architecture of the electric grid, a controlled area is a Medium
Voltage (MV) section of the grid, typically underlying a primary (HV/MV) substation and having points of common coupling
with low voltage distribution buses or the upper level grid.
The VC function is performed by the Controller on a node of a HV/MV substation control network. Figure 59 schematizes
the Voltage Control Function: starting from the inputs the function computes a Voltage profile and makes it operative by
sending set points to customer and utility devices.
In order to pursue the previously defined objective, the Controller computes the optimal states of the controllable devices
across the substation area. In a generic case, the optimization algorithm takes into account combinations of
technical/economic objectives and constraints, including requirements on power exchange at points of common coupling
with the upper grid. As part of a coordinated optimization process within the substation, suitable devices for control actions
are selected. Depending on the grid area to which the voltage control is applied and on the objectives of the optimization
process, generation/load units can be controlled directly by the Controller or via the Flexibility Operator (in the following
referred with the term Aggregator).
After every change of equipment state, due to an explicit request or to an automatic action, the substation is notified the
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new state or the operating point, inclusive of the information on available regulation ranges. If during the execution of the
optimization steps the topology of the grid changes, the application is interrupted and the solution is re-optimized. If during
the execution some operations are unsuccessful, then the solution is re-optimized excluding the malfunctioning devices. If
some controllable devices are unavailable for remote control, then the solution does not involve these devices but takes
into account their reaction to changes in operating conditions.
The main actors and how they interact are presented in
Figure 60. The control strategy requires information from sources external to the DSO domain. From the operational point
of view, the optimization function has to accept voltage regulation requests by the TSO whenever a transmission grid
contingency requires the application of preventive measures to avoid voltage collapse. Load and generation forecasts are
used to optimize the operation of distributed devices, while the economic optimization is based on market prices and DER
operation costs. A first major design assumption underlying the use case’s ICT architecture is that all the information
related to DER features, grid topology changes, requests by TSO, load/generation forecasts and market data are sent to the
Controller by the DMS (Distribution Management System) application in the DSO centre. This design choice preserves the
integrity of the distribution grid operation by limiting the number of communication channels at the substation level and
concentrating the communications with the external actors at the DSO centre level. In absence of criticalities, the VC
function is executed periodically (e.g. every 15 minutes) for optimization purposes, but its execution can be triggered
asynchronously by critical events (e.g. under/over voltage event, TSO requests, grid topology changes). The total response
time from the start of the elaboration to the end of the set point actuation, depends on actuation time constants of OLTC
and DER power electronics plus the communication overhead.
Figure 61 shows the UML Use case diagram where the actors and the (sub-)use case are depicted considering a normal
behaviour. The actors interact with the (sub-) use case “Voltage Control” that represents the main functionality of the
system.
Figure 63 shows how the actors and the functions of the Medium Voltage Control Use Case can be mapped to the smart
grid plane of Smart Grid Architecture Model (SGAM).
The main elements of the use case are placed into the Distribution and DER domains. The zones varying from the Market
zone of the Aggregator to the Field zone of control functions of the OLTC, Capacitor bank, DER and Flexible Load.
In the middle we have the Generation and Load Forecast functions placed in the cell Enterprise zone/Distribution domain
and integrated with the DMS.
TSO EMS and DMS Control Functions are in the Operation zone hosting all the active grid operation functions. The
Substation Automation System and the Voltage Control Functions with the SetPoint Calculation are placed in the Station
zone.
The architectural layout deployed for implementing the VC function depends on the responsibilities attributed to the use
case roles according to country-specific organisation and regulation. This Use Case assumes that the control of HV/MV
substations is under the responsibility of the DSO who has a network connection to the DERs. The data supply chain of the
VC function depends on several communication links enabling remote access from systems outside the perimeter of the
DSO operation. The DMS application in the DSO centre has permanent links (the green WAN in Figure 64) with four actors
(TSO, Aggregator, Generation Forecaster and Load Forecast); the Controller in the DSO substation has permanent
communication links (the red WAN in Figure 64) with third party DERs, possibly deploying heterogeneous communication
technologies, located in different geographical areas; communications between DMS and the substation automation and
control system through the DSO SCADA links (the blue WAN), eventually based on telecommunication services.
As seen the Medium Voltage Control use case involves different main area networks: Aggregator, TSO, DSO (Center), (DSO)
Substation, DER and Flexible Load networks. The communications can be intra area or inter area. In Figure 65 we observe a
schema of the different areas and of the communications. It is possible to identify the following different networks:
 NW1: Wired LAN local to Substation, distinguishing different network segments that corresponds to separate
control layers, e.g. station, bay and process layers
 NW2: Wireless/wired WAN that may use commercial cellular or private wireless technology. This network
connects the substation with the DER sites
 NW3: Private wired WAN. This network connects the DSO Operation Center with the Substation. It may be based
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on dedicated communication services via wired WAN
 NW4: Wired LAN local to DSO Operation Center, distinguishing different network segments that corresponds to
separate operation layers, e.g. DMS and MDMS
 NW5: Wired WAN. This network connects the TSO Center with the DSO Operation Center. It may be based on
dedicated communication services via wired WAN
 NW6: Public IP. This network connects the Aggregator with the DSO Enterprise Center
 NW7: Wired WAN. This network connects the DSO Operation Center with the DSO Enterprise Center. Most
probably it will be based on dedicated communication services via wired WAN.
Note that the networks involving DER and Aggregator are WAN network and can be wired or wireless. In particular for the
network to the DER the wireless technology is desirable.
The main control and communication components are depicted in Figure 66. In this use case different communication
protocols are involved, in Figure 66 the main of them are represented.
The sequence diagram of the VC function is presented in Figure 69 where the information exchange is addressed.
One of the inputs of the VC function is the generation forecast: Figure 67 shows a sketch of the generation estimation
function. Figure 68 shows the sequence diagram with the main information flow.
By focusing on the core of the VC scheme, it is clear that the correct computation of the optimal set points depends on the
provision of correct operation and economic data from all communication sources. A malicious attack to one of the
communication links may cause either the loss of input data (generation forecasts, economic data from the Aggregator, TSO
requests, topological changes), or the loss of output setpoints, or the introduction of faked input/output values/setpoints.
The use case highlights sample communication attacks that may lead the control function to diverge from optimum set
point values or, even worse, to produce inadequate set points with cascading effects on connected generators. In Figure 62
an anomalous scenarios is represented through the (mis)use case diagram. The figure depicts how a (mis)user can attack
the system. Such abnormal scenarios to the VC function support the evaluation of the impact on the supplied power that
will depend on the size of the grid section, the amount of installed distributed generation, the control network topology
over the power grid structure and the extension of the attack itself. The evaluation of attack processes to the VC function is
aimed at identifying security controls to counteract those attacks which might compromise the voltage profile.
The global impact of such cyber attacks to the Voltage Control functions on the supplied power depends on the grid size
and the amount of distributed generation, both these factors varying on a geographical base. By focussing on the Italian
profile and targeting the integration of an amount of renewable energy of about 40 GW within 2020, the distribution grid
development plan requires the building of about 10% new HV/MV substations.
The analysis of the attack impact on the supplied power depends on the control network topology on the top of the power
grid structure. By applying an extreme case approach, the impact value associated to future smart grids endowed with the
Voltage Control function depends by the extension of the attack effect. For example, an attack to the DER network could
cause the disconnection of all the generators connected to the MV feeders of a given substation (e.g. less than 100MW); an
attack to the substation networks could be able to disconnect one or several substations (e.g. less than 1 GW); a control
centre attack, causing the disconnection of all the substations in a given control centre, could count 6 GW of unsupplied
power.
By mapping such impact values on the power scales identified by the SGIS working group, it results that the impact of those
cyber attacks to the communications of the Voltage Control functions may be associated, respectively, to the Medium, High
and Critical impact levels.
In section 4.2 of the template some anomalous scenarios are analysed with focus on the effect of different attacks (floding
based DoS and fake messages) to the communications involved in the Use Case. The related Sequence Diagrams are
presented in Figure 70, Figure 71, Figure 72, Figure 73 and Figure 74.
10.1.1.5 General Remarks
General Remarks
10.1.2 Diagrams of Use Case
Diagram of Use Case
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Field
measurem
ent
Grid
Topology
Market
prices
Resource
Operation
costs
Generation
Forecast
Voltage
Control
Function
Load
Forecast
TSO
signals
Voltage
Profile
Third party DER
Distributor’s device
Figure 59 - Voltage Control
Aggregator
Generation
Forecast
Load Forecast
TSO
DMS
Medium Voltage Grid Controller (MVGC)
DER
Flexible Load
OLTC
Capacitor
Bank
Figure 60 - Voltage Control - Actors Interactions
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Figure 61 - Voltage Control - Use Case Diagram
Figure 62 - Voltage Control - Use Case Diagram - attack scenarios
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Market
Aggregator
Gen.
Forecast
TSO
EMS
Enterprise
Load
Forecast
DMS
Operation
MVCG
Station
Sub.Autom.
System
DER Ctrl
OLTC Ctrl
Capacito
Bank Ctrl
Field
Flexible
Load Ctrl
Process
Generation
Transmission
Distribution
Customer
Premise
DER
Figure 63 - Voltage Control – Mapping on SGAM
Generation
Forecast
Transmission Grid
Control
DSO Comm. Network
(WAN)
TSO
Control
HV
Load
Forecast
Control
Primary Substation
Automation&Control
OLTC
Control
Control
DSO
MV
Control
Capacitor Bank
Aggregator
Control
Control
DER
Energy
Storage
Flexible loads
Control
Control
Control
MV
Enterprise Comm.
Network
(WAN)
Automation&Control
Control
LV
DER Comm. Network
(WAN)
Technical Flexibility
&Performance
Figure 64 - Voltage Control - Overview of involved communications
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Commercial
Feasibility
& Flexibility
FP7-ICT-318023/ D1.1 ver 2
Aggregator Site
NW6
TSO Center
Enterprise
Systems
NW5
NW7
NW4
DMS
NW3
Flexible load site
DSO/Customer
NW1
NW2
DSO Substation
Field
DER Site
DSO/Customer
Figure 65 – Voltage Control – Communications
Figure 66 – Voltage Control - Component Layer
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MVGC
Substation
Automation
System
FP7-ICT-318023/ D1.1 ver 2
Automated
Meter
Management
Weather
Forecast
Grid DB
Management
Generation
Forecast
DMS
Figure 67 - Generation Forecast
Figure 68 - Generation Forecast - Sequence Diagram
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Figure 69 – Voltage Control - Sequence Diagram
Figure 70 - Voltage Control - DoS Attack to DER
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Figure 71 - Voltage Control - DoS Attack to MVGC
Figure 72 - Voltage Control - Fake DER Set point
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Figure 73 - Voltage Control - Fake DER Set point (Man in the Middle)
Figure 74 - Voltage Control - Fake TSO signal
10.1.3 Technical Details
10.1.3.1 Actors: People, Systems, Applications, Databases, the Power System, and Other
Stakeholders
Grouping (Community)
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Actors
Group Description
FP7-ICT-318023/ D1.1 ver 2
Actor Name
Actor Type
Actor Description
see Actor List
see Actor List
see Actor List
Meter Data Management
System
System
Weather forecast
System
Grid DB Management
System
Aggregator
Role
Transmission System
Operator (TSO)
Role
Generation forecast
System
Load forecast
System
DMS
System
Medium Voltage Grid
System
System for validating, storing,
processing and analyzing large
quantities of meter data
Provides weather forecast used for
different utility business processes
(scheduling, planning, operational
planning, operation ...)
System that manages the DB of the
electric network consistency
Offers services to aggregate energy
production from different sources
(generators) and acts towards the grid
as one entity, including local
aggregation of demand (Demand
Response management) and supply
(generation management). In cases
where the aggregator is not a supplier,
it maintains a contract with the
supplier.
According to the Article 2.4 of the
Electricity Directive 2009/72/EC
(Directive): "a natural or legal person
responsible for operating, ensuring the
maintenance of and, if necessary,
developing the transmission system in
a given area and, where applicable, its
interconnections with other systems,
and for ensuring the long-term ability
of the system to meet reasonable
demands for the transmission of
electricity". Moreover, the TSO is
responsible for connection of all grid
users at the transmission level and
connection of the DSOs within the TSO
control area.
Computes forecast for renewable
generation in controlled area based on
weather forecast
Computes forecast for load in
controlled area
Distribution Management System a
system which provides applications to
monitor and control a distribution grid
from a centralized location, typically
the control center. A DMS typically has
interfaces to other systems, like an GIS
or an OMS
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Further information
specific to this Use Case
FP7-ICT-318023/ D1.1 ver 2
Controller (MVGC)
Substation Automation
System (SAS)
System
DER
Device
Flexible load
Capacitor bank
Device
Device
OLTC
Device
implementing the Voltage Control
Function
implementing the automation
sequences and the control functions of
interfacing process level control
devices
Generic Distributed Energy Resource "DER devices are generation and
energy storage systems that are
connected to a power distribution
system" (IEC 62357)
Load that can be modulated
A switchable bank of shunt capacitors.
May be generalized as
Shunt Compensator
(A section of a shunt
compensator is an
individual capacitor or
reactor). (IEC 61970)
On Load Tap Changer. Mechanism for
changing transformer winding tap
positions.
10.1.3.2 Preconditions, Assumptions, Post condition, Events
Actor/System/Information/Contract
DER ancillary services
Costs of DER ancillary services
Page 122 of 244
Use Case Conditions
Triggering Event
Pre-conditions
Assumption
The Voltage Control algorithm
applies to a MV grid under a
Primary Substation and operate
only controllable device directly
installed on the MV grid.
The use of DER ancillary services
is defined by contracts or regional
regulation.
Substation Control System can
operate only DERs having
subscribed some agreement with
Distribution System Operator.
Generally only a subset of
installed DER is controllable.
The algorithm takes in account
dispatching costs for DER active
and reactive power.
Different
remuneration
of
ancillary services offered by DERs
are possible:
- administrated price: fixed
price established by Authority
bodies;
- Market scheme: DER operators
FP7-ICT-318023/ D1.1 ver 2
fix prices for their services (not
fully
realistic
for
MV
networks);
- Mixed approach.
It is assumed that storage units
are owned and operated directly
by the Distribution Company in
order to increase grid control
capabilities.
There is an integral constraint on
control strategies to maintaining
the same level of charge on 24
hour time horizon.
DMS knows:
- DERs features (Nominal
power,
Capability,
Controllability, etc.)
- Load forecast for each MV
load,
- Generation forecast for each
DER, controllable or not.
DER storage
DMS
Grid measurements are available
from substation devices and from
DERs.
State estimation of controlled MV
grid under a Primary Substation is
performed by either the Medium
Voltage Grid Controller or the
Control Centre (DMS).
Grid measurements
State Estimation
Control loop is executed:
Periodically (15’)
On
critical
under/overvoltage event
On grid topology change
Execution
algorithm
of
control
voltage
Generation Forecast
10.1.3.3 References /Issues
References
Page 123 of 244
Signals related to grid stability
(normal, critical, alarm, …)
coming from TSO can influence
the execution of control voltage
algorithm
(e.g.
changing
optimization criteria or overriding
commands).
Forecasts updated every 12 hours
with granularity of 1 hour. Valid
for 36 hours
FP7-ICT-318023/ D1.1 ver 2
No
.
References Type
Reference
Status
Impact on Use Case
Originator/O
rganisation
1
European Report
Public
Specification
CEN/CENELE
C/ETSI
2
Use Case
SGCG/M490/E_Smart
Grid
Use
Case
Management Process
—
Use
Case
Collection,
Management,
Repository, Analysis
and Harmonization
SGSP Working Group
Use Case WGSP-0200
Public
Specification
3
European Report
Public
Standards
4
IS
Communication
IEC 61850(-7-420)
IS
IEC 62351
TS
Communication
Data Model
Security
NIST SP800-53 & 80082, IR 7628
IEC 61970
SP, IR
Security
NIST
IS
Data Model
IEC TC57
IEC 61968
IS
Data Model
IEC TC57
10
International
Standard
International
Standard
International
Standard
International
Standard
International
Standard
International
Standard
Article
SGCG/M490/B_Smart
Grid Report First set
of Standards Version
th
2.0 Nov 16 2012
IEC 60870-5-104
CEN /
CENELEC /
ETSI
CEN/CENELE
C/ETSI
Public
Specification
CIRED 2012
http://www.cired2
012-workshop.org/
11
Article
Public
Security Issue
CIRED 2012
http://www.cired2
012-workshop.org/
12
Project
Monitoring
and
Control of Active
Distribution Grid
Impact
of
DER
Integration on the
Cyber Security of
SCADA Systems –The
Medium
Voltage
Regulation
Case
Study
FINSENY
Public
Specification
EU FP7
project
http://www.fi-pppfinseny.eu/
5
6
7
8
9
Link
IEC TC57
/
IEC TC57
IEC TC57
10.1.3.4 Further Information to the Use Case for Classification / Mapping
Classification Information
Relation to Other Use Cases
Grid monitoring and control, State Estimation, Generation management, Load management, Storage management,
Advanced DMS and Distribution Automation, Grid emergency management, Power quality, Weather forecast, market signal
Management
Level of Depth
High Level
Page 124 of 244
FP7-ICT-318023/ D1.1 ver 2
Prioritisation
Needed for countries with high DER penetration on distribution grid
Generic, Regional or National Relation
Generic
View
Technical
Further Keywords for Classification
Voltage and VAR Control, DER Management, Cyber security, ICT architectures
10.1.4 Step by Step Analysis of Use Case
Scenario Conditions
Scenario
Primary
Triggering
Name
Actor
Event
Generation
Forecast
Estimation
Information
acquisition
Forwarded info
Generation
forecast
Periodically
New info available
New generation forecast available
DMS
Third party DER
/ Distributor’s
device
Medium
Voltage Grid
Controller
TSO signal or new
info
DMS receives new
data
Field dispatches
new measurements
Info integrated with local data
Grid
measurement
dispatch
Forward of grid
measurements
Periodically /
Asynchronous
Periodically
/Asynchronous
Periodically
Periodically
DMS receives new measurements
4.1.7
Execution of
control voltage
algorithm
Set Setpoints
New setpoints
computed
Devices change their settings
4.2.1
DoS Attack: DER
Medium
Voltage Grid
Controller
Substation
Automation
System /
Medium
Voltage Grid
Controller
DER
Substation Control
System has new
SCADA and DER
measurements
The state is not
acceptable
4.2.2
DoS Attack:
Medium Voltage
Grid Controller
Fake DER Setpoint
Medium
Voltage Grid
Controller
DER
Fake DER Setpoint
(Man in the
Middle)
Fake TSO signal
DER
No.
4.1.1
4.1.2
4.1.3
4.1.4
4.1.5
4.1.6
4.2.3
4.2.4
4.2.5
Page 125 of 244
DMS
Medium
Voltage Grid
Controller
Values out of
range
New setpoint
Pre-Condition
Post-Condition
Medium Voltage Grid Controller obtains
input for the control algorithm
Medium Voltage Grid Controller obtains
new measurements
Computation of new setpoints (horizon 24
h)
Attacker launches
an attack
Attacker launches
an attack
Missing measurements
Attacker launches
an attack
Attacker launches
an attack
Abnormal behaviour
Attacker launches
an attack
Incorrect State estimation leads to
abnormal behaviour
Missing measurements
Abnormal behaviour
FP7-ICT-318023/ D1.1 ver 2
10.1.4.1 Steps – Normal
Scenario 4.1.1
Scenario
Name :
Generation Forecast Estimation
Step
No.
Event
Name of
Process/Activit
y
Description of
Process/Activity
Servic
e
Information
Producer
(Actor)
Informatio
n Receiver
(Actor)
Informatio
n
Exchanged
1
Periodic
Meter data
collection
Collecting data from
meters about the
grid status
GET
Meter Data
Management
System
Generation
Forecast
Grid status
2
Periodic
every 12
hours
Weather data
collection
GET
Weather
forecast
Generation
Forecast
Weather
forecast
3
Periodic
Grid topology
data collection
GET
Grid DB
Management
Generation
Forecast
Updated
Grid
Topology
4
Periodic
every 12
hours
Forecast
estimation
weather forecast
service about the
weather forecast
Grid DB
Management about
the grid topology
Calculate the
forecast of active
power generation
EXECU
TE
Generation
Forecast
Generation
Forecast
Updated
Generation
forecast for
each DER
Technical
Requirement
s R-ID
Scenario 4.1.2
Scenario
Name :
Information acquisition
Ste
p
No.
Event
Name of
Process/
Activity
Description of
Process/Activity
Service
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
1
TSO
changes
algorithm
paramete
rs
(Asynchr
onous)
Periodic
every 12
hours
TSO
message
Send signals influencing
the execution of
control voltage
algorithm (e.g.
changing optimization
criteria or overriding
commands).
Update Generation
forecast for each DER
REPORT/C
REATE
TSO
DMS
TSO Signals
CREATE
Generation
forecast
DMS
Updated
Generation
forecast for
each DER
3
Periodic
Load
Forecast
Update load forecast
CREATE
Load
forecast
DMS
4
Periodic
Energy /
Ancillary
Costs
Update Energy /
Ancillary Costs
CREATE
Aggregator
DMS
5
Periodic
Load/Gen
Customer
program
Programs of load and
generation of the
customers
CREATE
Aggregator
DMS
Updated
Load
forecast
Updated
Energy /
Ancillary
Costs
Load/Gen
Customer
program
2
DER
Generatio
n Forecast
Scenario 4.1.3
Page 126 of 244
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
Scenario Name :
Step
No.
Event
1
TSO
signal
received
TSO
changes
algorithm
paramete
rs
(Asynchr
onous)
Periodic
2
Forwarded info
Name of Description of
Process Process/Activity
/Activity
Service
Informatio
n
Producer
(Actor)
Information
Receiver
(Actor)
Informatio
n
Exchange
d
TSO
signal
forward
Send signals influencing
the execution of control
voltage algorithm (e.g.
changing optimization
criteria or overriding
commands).
CREATE
DMS
Medium
Voltage Grid
Controller
TSO Signals
Update
DER
features
informati
on
Update Features
information (Nominal
power, Capability,
Controllability, etc.) of
DER installed on the MV
grid
REPORT
DMS
Medium
Voltage Grid
Controller
Updated
Load/DER
Features
Send configuration
change of the controlled
MV grid (grid topology
reconfiguration, new
DER/load installation)
Update Gen forecast for
each DER
REPORT
DMS
Medium
Voltage Grid
Controller
Updated
Grid
Topology
CREATE
DMS
Medium
Voltage Grid
Controller
Updated
Gen
Forecast
for each
DER
Updated
Load
Forecast
for each
Load
Updated
Energy /
Ancillary
Costs
3
Grid
topology
changes
Update
grid
change
4
Periodic
every 12
hours
Forward
generatio
n
forecast
5
Periodic
Forward
load
forecast
Update Load / forecast
for each Load
CREATE
DMS
Medium
Voltage Grid
Controller
6
Periodic
Forward
Energy /
Ancillary
Costs
Update Energy /
Ancillary Costs
CREATE
DMS
Medium
Voltage Grid
Controller
Technical
Requirements RID
Scenario 4.1.4
Scenario
Name :
Grid measurement Acquisition
Ste
p
No.
Name of
Process
/Activity
Event
Page 127 of 244
Description of
Process/Activity
Service
Informatio
n
Producer
Information
Receiver
(Actor)
Informatio
n
Exchange
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
(Actor)
1
Periodic
seconds
2
Periodic
seconds
3
d
OLTC
Measure
ments
Capacitor
bank
Measure
ments
OLTC Measurements
CREATE
OLTC
Substation
Automation
System
Substation
Automation
System
Capacitor bank
Measurements
CREATE
Capacitor
bank
Periodic
seconds
DER
Measure
ments
DER Measurements
CREATE
DER
Medium
Voltage Grid
Controller
4
Periodic
seconds
Flexible
load
Measure
ments
Flexible load
Measurements
CREATE
Flexible
load
Medium
Voltage Grid
Controller
5
Periodic
seconds
Field
Measure
ments
OLT/Capacitor bank
Measurements
CREATE
Substation
Automatio
n System
Medium
Voltage Grid
Controller
OLTC
Measurem
ents (P,Q,V)
Capacitor
bank
Measurem
ents
(P,Q,V)
DER
Measurem
ents
(P,Q,V)
Flexible
load
Measurem
ents
(P,Q,V)
OLTC/Capa
citor bank
Measurem
ents
(P,Q,V)
Scenario 4.1.5
Scenario
Name :
Forward of grid measurements
Step
No.
Event
Name of
Process
/Activity
Description of
Process/Activity
Service
Informatio
n
Producer
(Actor)
Information
Receiver
(Actor)
Informatio
n
Exchange
d
1
Periodic
Measure
ments
forward
Medium Voltage Grid
Controller forward the
SCADA and DER
measurements
CREATE
Medium
Voltage
Grid
Controller
DMS
SCADA and
DER
measureme
nts
Information
Receiver
(Actor)
Information
Exchanged
Scenario
Name :
Step
No.
Event
Technical
Requirements
R-ID
Scenario 4.1.6
Execution of control voltage algorithm
Name of
Process/Activity
Page 128 of 244
Description of
Process/Activity
Service
Information
Producer
(Actor)
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
1
Periodic
every 15
/Triggered
by grid
topology
changes
minutes /
State Estimation
Execute State
Estimation
EXECUTE
Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Estimation
of the Grid
state
2
State from
state
estimation
Triggered
by TSO
signal /
Check state
Check if the
parameters are
within the limits
Optimized Set
point calculation
Algorithm
(horizon 24 hours)
EXECUTE
Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Estimation
of the Grid
state
Set point
Calculation
3
Set point
calculation
EXECUTE
Scenario 4.1.7
Scenario
Name :
Set Setpoints
Step
No.
Event
Name of
Process/Activity
Description of
Process/Activity
Service
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
1
New set
point
OLTC / Capacitor
bank Set point
Send OLTC/
Capacitor bank
Set point
CREATE
Medium
Voltage Grid
Controller
Substation
Automation
System
Capacitor
bank Set
point ΔQ +/ΔV +/OLTC Set
point
ΔV +/-
2
New set
point
OLTC / Capacitor
bank Set point
Send OLTC /
Capacitor bank
Set point
CREATE
Substation
Automation
System
OLTC /
Capacitor
bank
Capacitor
bank Set
point ΔQ +/ΔV +/OLTC Set
point
ΔV +/-
3
New set
point
DER Set point
Send DER Set
point
CREATE
Medium
Voltage Grid
Controller
DER
DER Set
point
ΔP +/ΔQ +/-
4
New set
point
Flexible load Set
point
Send flexible load
Set point
CREATE
Medium
Voltage Grid
Controller
Flexible load
Flexible load
Set point
ΔP +/ΔQ +/-
Technical
Requirements
R-ID
10.1.4.2 Steps – Alternative, Error Management, and/or Maintenance/Backup Scenario
Scenario 4.2.1
Scenario Name:
Step
No.
Event
1
Attacker
launches
DoS Attack: DER
Name of
Description of
Process/Activity Process/Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
DoS Attack
CREATE
Attacker
DER
Anomalous
traffic
Page 129 of 244
The attack floods
the DER with
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
an attack
2
DER is
under
attack
DER
communications
down
Scenario Name :
abnormal
messages
The Medium
Voltage Grid
Controller doesn’t
receive the
measurements
from DER
GET
DER
Medium
Voltage Grid
Controller
Scenario 4.2.2
DoS Attack: Medium Voltage Grid Controller
Name of
Description of
Service Information
Producer
Step
No.
Event
1
Attacker
launches an
attack
DoS Attack
2
Medium
Voltage Grid
Controller is
under attack
Medium Voltage
Grid Controller
communications
down
The attack floods
the MVGC with
abnormal
messages
The DER and
SCADA
measurements
don’t reach the
DMS
Missing
measurements
Information
Receiver
Information
Exchanged
CREATE
Attacker
Medium
Voltage Grid
Controller
Anomalous
traffic
GET
Medium
Voltage Grid
Controller
DMS
Missing
measurements
Technical
Requirements
R-ID
Scenario 4.2.3
Scenario Name :
Step
No.
Event
1
Attacker
launches
an attack
Page 130 of 244
Fake DER Setpoint
Name of
Description of
Service
Information
Producer
Information
Receiver
Information
Exchanged
Fake setpoint
CREATE
Attacker
DER
DER Setpoint
The attacker
sends a fake
setpoint to DER
Technic
al
Require
ments
R-ID
FP7-ICT-318023/ D1.1 ver 2
2
DER
changes
its
settings
Scenario
Name :
Abnormal
execution
DER receives a
setpoint and
changes its
settings
EXECUTE
DER
DER
Settings
Scenario 4.2.4
Fake DER Setpoint (Man in the Middle)
Step
No.
Event
Name of
Process/Activity
Description of
Process/Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
1
Medium
Voltage
Grid
Controller
sends
DER
setpoint
Attacker
changes
message
Attacker
forwards
the fake
message
DER
changes
its
settings
Message
interception
Attacker
intercepts the
setpoint message
from Medium
Voltage Grid
Controller
CREATE
Medium
Voltage Grid
Controller
Attacker
DER setpoint
Message change
Attacker changes
the values of
setpoint
Attacker forwards
the fake message
EXECUTE
Attacker
Attacker
Fake DER
setpoint
CHANGE
Attacker
DER
Fake DER
setpoint
DER receives a
setpoint and
changes its
settings
EXECUTE
DER
DER
Settings
2
3
4
Page 131 of 244
Message forward
Abnormal
execution
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
Scenario 4.2.5
Scenario Name :
Step
No.
Event
1
Attacker
launches an
attack
Receive of
TSO signal
2
Page 132 of 244
Fake TSO signal
Name of
Process/Activity
Fake TSO signal
State Estimation
Description of
Process/Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
Attacker sends a
fake TSO signal
message
MVGC executes
algorithm
CREATE
Attacker
TSO signal
EXECUTE
Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Incorrect
state
estimation
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
10.1.5 Information Exchanged
Name of Information
Exchanged
Updated Grid Topology
Weather forecast
TSO signals
Updated generation forecast
Updated load forecast
Updated Energy/Ancillary costs
Updated Load/DER Features
OLTC Measurements and States
Description of Information Exchanged
Information regarding the characteristics of the
grid elements (nodes, loads, generators and
lines). Configuration change of the controlled
MV grid (grid topology reconfiguration, new
DER/load installation)
Weather forecast, weather data
Signal influencing the execution of control
voltage algorithm (e.g. changing optimization
criteria or overriding commands).
Voltage setting, Reactive Power setting, AVR
inclusion/exclusion
Active power production plan on an hour base
on a time horizon of 36 hours (36 values of
active power). Generation coefficient 0<C<1
The future load is predicted on the basis of
reference loads (seasonal patterns), stochastic
fluctuations, active demand effects, weather
forecast, day type. Load coefficient 0<C<1
Costs for the modulation of active and reactive
power and reward schemes
Update Features information (Nominal power,
Capability, Controllability, etc.) of DER
Voltage values, AVR included/excluded
Capacitor bank Measurements and
States
DER Measurements
Voltage values, Reactive power values,
included/excluded
Voltage values, Active and Reactive power
values
Flexible load Measurements
Voltage values, Active and Reactive power
values
Grid state estimation
Estimation of the current state of the grid
Capacitor bank Set point
Capacitor bank Set point ΔQ +/ΔV +/OLTC Set point
ΔV +/DER Set point
ΔP +/ΔQ +/Flexible load Set point
ΔP +/ΔQ +/-
OLTC Set point
DER Set point
Flexible load Set point
Page 133 of 244
Requirements to information data R-ID
Standard Protocols: IEC 60870-5-104, TCP/IP
Standard Protocols: Web services, TCP/IP
Standard Protocols: IEC 60870-5-104, TCP/IP
Standard Protocols: IEC 61968-100, IEC 608706, IEC 60870-5-104, TCP/IP
Standard Protocols: IEC 61968-100, IEC 608706, IEC 60870-5-104, TCP/IP
Standard Protocols: IEC 62325, IEC 61968-100,
IEC 60870-6, IEC 60870-5-104, TCP/IP
Standard Protocols: IEC 61968, IEC 61850-7420, IEC 60870-5-104, TCP/IP
Standard Protocols: IEC 61850-8-1, IEC 608705-104, TCP/IP
Standard Protocols: IEC 61850-8-1, IEC 608705-104, TCP/IP
Time Requirements: 4 sec [refresh time on the
CC HMI]
Standard Protocols: IEC 61850-7-420, IEC
61850-8-1, IEC 61850-90-5, IEC 61850-90-1, IEC
60870-5-104, TCP/IP, UDP/IP
Standard Protocols: IEC 61850-8-1, IEC 6185090-5, IEC 61850-90-1, IEC 60870-5-104, TCP/IP,
UDP/IP
Standard Protocols: IEC 61970, IEC 61968, IEC
60870-5-104, TCP/IP
61850-8-1, TCP/IP
61850-8-1, TCP/IP
60870-5-104, IEC 61850-90-5, IEC 61850-90-1,
IEC 61850-8-1, TCP/IP
61850-90-5, IEC 61850-90-1, IEC 61850-8-1,
TCP/IP
FP7-ICT-318023/ D1.1 ver 2
10.1.6 Common Terms and Definitions
Common Terms and Definitions
Term
Definition
AVR
Automatic Voltage Regulator
DER
DMS
Distribution Management System
DSO
Distribution System Operator
EMS
Energy Management System
GIS
Geographic information system
HV
High Voltage
IP
Internet Protocol
LAN
Local Area Network
MV
Medium Voltage
MVGC
OMS
Outage Management System
OLTC
On Load Tap Changer
PEV
Plug-in Electric Vehicle
P(f)
SAS
Active power P(f) is a function of frequency f. The active power generated and active power consumed
at each moment should be equal. A deviation from this equilibrium results in a deviation from the 50 Hz
frequency. So keeping this equilibrium between active power generation and consumption means
maintain frequency
Reactive power Q(U) is a function of voltage U. The reactive power on the grid should be kept in
equilibrium. Reactive power is an extra load for the grid, leaving less capacity for active power, resulting
in a local voltage drop. So keeping reactive power in equilibrium means maintaining voltage.
SGAM
Smart Grid Architecture Model
TSO
Transmission System Operator
V
Voltage
VPP
Virtual Power Plant
WAN
Wide Area Network
Q(U)
Page 134 of 244
FP7-ICT-318023/ D1.1 ver 2
10.2 USE CASE NAME: Electrical Vehicle Charging in Low Voltage Grids
ID
Domain(s)
Name of Use Case
Distribution Grid
Electric Vehicle Charging in Low Voltage Grids
Changes /
Version
0.2
0.4
Date
Version Management
Name
Domain
Expert
SB, JG/FTW
SB, JG/FTW
1.0
1.1
Jan.2013
Feb/Mar
13
8.03.13
27.03.13
1.2
1.3
25.04.13
31.05.13
SB
SB/JG
Area of
Expertise /
Domain /
Role
Title
Approval
Status
draft, for comments,
for voting, final
draft
draft
SB/JG FTW
SB
V1.0 released
Changes after
review
EAB feedback
Add “Aggregated
charging
infrastructure
entity”, price info
Scope and Objectives od Use Case
Scope
Objective







Low voltage distribution grids
Markets
Distribution grid operation
Satisfy the charging demands of arriving EVs in such a way that the
generated and stored energy is efficiently used and the grid is not
overloaded.
Enable electrical vehicle charging to become a flexible consumption
resource that can be used to balance energy and power resources in
the LV grid along with decentralized production as well as other
loads (e.g. households).
Provide a system architecture enabling interoperation between new
actors such as charging station operators (charging aggregator) and
their connection to existing actors such as DSOs and energy
providers.
Enable DSOs to monitor state of low voltage grid under EV load
conditions.
Page 135 of 244
FP7-ICT-318023/ D1.1 ver 2
Charging of electrical vehicles in low voltage grids is challenging due to highly synchronized demand patterns of charging as
well as high loads. This use case covers the controlled charging of electrical vehicles in a low voltage grid, taking into
consideration the EV owner, a charging infrastructure owner/provider as well as the DSO. Regarding the latter, the use case
aims to utilize the high demand flexibility of the charging process to balance grid and energy in the low voltage grid.
The overall electrical vehicle charging deployment overview is depicted in
Figure 75. It consists of 5 main parts listed in the following:
1) A Charging Station installation is provided that can be represented by a) private charging
scenario with a few charging spots. The private sector at home includes garages, carports
and parking grounds around single or multi-family homes. b) In the semi-public sector, the
charging stations are operated for example in parking grounds or underground parking of
hotels, banks, gastronomy companies, shopping centres or at car dealerships c) be
represented by a public charging scenarios where several charging spots are controlled by a
charging station controller. The charging spots are public, meaning that a public group of EV
owners can charge their electrical vehicles at them.
2) Local LV Grid resources being local production and storage that will operate in an interplay
with the electrical vehicle charging to provide energy management services towards the grid
as well as cost and environmentally efficient charging operations.
3) Secondary Substation containing DSO equipment to manage metering, monitoring as well as
grid control.
4) The DSO domain representing the link of the low voltage grid to the DSO operations;
including requirements towards significant low voltage grid sub-systems such as electrical
vehicle charging.
5) The “Cloud” representing services in the open networks/internet used to: a) provide a
market for trading energy and flexibility resources, b) to enable information needed for local
control (e.g. weather) and finally, c) for a charging station operator to coordinate the
allocation on its CS controllers, define prices for its services and provide routing services for
the EV owners/drivers (using the Charging Station Routing). For this service, the CSO would
pay.
Details of the individual components/systems are described in the actor lists.
For the given electrical vehicle deployment scenario a total of 7 networks have been identified. A
network here represents a given network infrastructure with a specific purpose. In reality, each
network may be realized by different or similar technologies or several networks may be operated as
a single network. This identification of different networks enables to define different deployment
scenarios and resulting networking architectures in which advanced control tasks must operate. A
scenario and its analysis can help to clarify which networks are involved and thereby how the
communications may affect the scenario. The networks are defined as follows:
Network 1 – Metering. The metering network is owned by the DSO or a metering infrastructure
operator. It is a network used to collect smart meter data measurements at the last mile. The smart
meter network is usually based on powerline communications, cellular or proprietary wireless
solutions.
Network 2 – Sub-station network. This network is an internal bus-network in the secondary
substation. It is owned by the DSO and connects equipment in the substation. May be based on
Ethernet.
Page 136 of 244
FP7-ICT-318023/ D1.1 ver 2
Network 3 – Public IP Network. The Public IP network represents the open Internet. This is the
easiest platform for third parties to provide their services, such as routing services to EV users, or
weather services. The public IP network can be based on everything from wired xDSL based
technologies to cellular data access.
Network 4 – eCar Communication. This communication is between the charging station and the
electrical vehicle itself. The communication is usually wired and may be running through the charging
cable itself. Information about the state of the car, e.g. state of charge, preferred charging speed,
etc. may be provided through this network.
Network 5 – Private IP Network The private IP network represents a local network infrastructure
utilized by the infrastructure owner to connect local elements. For instance charging spots may be
connected to the charging station through this network. It could be based on PLC or Ethernet.
Network 6 - LV Grid Management Network. The DSO may choose to deploy an own closed
networking architecture used for grid components to communicate. Thus could be to communicate
with inverters, protection devices as well as sensors in the grid.
Network 7 – DSO Network. The DSO network is the network connecting the DSO management and
control systems (e.g. SCADA) towards the secondary sub-station. These networks are usually closed.
They may be based on fibre put out by the DSO as the cables to substations were put in the ground.
To define how these components are foreseen to interact over the provided networks, a total of
three main scenarios have been defined. 1) A charging scenario, 2) an energy and power
management scenario and 3) a market scenario. Each scenario is described pictorially through a use
case diagram identifying actors, their sub-use cases and their interactions to support the scenario
and a message sequence diagram to define how components and actors communicate. These
scenarios are briefly described in the following:
Charging Scenario:
See Figure 76 and Figure 77.
This scenario has the EV Owner/driver as the main actor. The scenario defines how the EV
Owner/driver is interested in charging his/her electrical vehicle and having it fully charged when
needed again. In the private charging case it is clear where to charge. In the public charging case, also
a pre-charging phase exist where EV owners/drivers can search for charging stations.
The charging operations are controlled locally by a charging station controller. The controller is
responsible for trying to make charging cheapest (for the EV owner if he/she pays after energy
consumption and/or the charging station (infrastructure) operator, if he/she provides a flat-rate
charging service. The control further needs to take into consideration local limitations provided by
the DSO such as grid limits or load objectives provided by the operator to maintain the service quality
and help improve utilization of local resources.
The pre-charging phase called reservation is not mandatory, but allows a better planning of the
resources at a public charging station and improves the probability to find available resources when
the EV user tries to plug in. The use case continues with plug-in in which the schedule is updated. A
periodic event calculates the grid situation taking into account generation, consumption and storage
and might lead to a plan update. The charging period ends with the stop charging event created
either by completion of the plan or by a plug-out and leave event.
Page 137 of 244
FP7-ICT-318023/ D1.1 ver 2
Energy and Power Management:
This scenario considers the DSO as the main actor. Based on local LV grid conditions as well as
requirements on MV level, the DSO tries to balance the power resources in the low voltage grid. The
goal is to make sure the grid operation is within acceptable limits, to ensure that grid components
are not overloaded and also to make sure that enough energy can be provided to supply the charging
service. The DSO provides requirements towards local production, storage and consumption. E.g. the
DSO will ensure to signal to the charging station controller when grid power resources are sparse or
the voltage is too low as well as to request certain load flexibility behavior that enables to balance
the grid.
Energy Market Operation:
This scenario covers the interactions between the actors of this use case in relation to the market.
Important aspects here are a distribution market where not only energy is sold, but also flexibility.
I.e. the charging station operator may include in the business model to sell flexibility while
maintaining the interests of his/her customers to charge vehicles when they are to be used. The DSO
can purchase such flexibility on the market or in a direct business relationship with the CSO to have
power quality management resources. The scenario also considers interactions with new energy
providers/aggregators that have local resources that should be utilized locally, e.g. for charging, or, in
combination with charging, to provide services towards the MV grid level.
The functions of the use case are depicted in Figure 82 based on the Smart Grid Architecture Model
(SGAM). Most functions are provided in the distribution domain to monitor and manage the Low
Voltage grid considering load and flexibility of EV charging processes. In the DER and Customer
Premise Domain exist local energy application controllers as well as monitoring (e.g. metering and
events by registering EVs) and actuation (start/stop charging, change charging intensity, …). In the
market zone the aggregation of LV grid energy resources (production, storage) and demand
resources provides a market to exchange such resources.
General Remarks
-
Diagram of Use Case
Page 138 of 244
FP7-ICT-318023/ D1.1 ver 2
Cloud
DSO
Metering
Head-end
System
Market
(Distribution/Transport)
Meter Data
Management
System
Distribution
Management
System
(SCADA)
Information
Services
NW7: DSO Network
Charging
Station
Routing &
Reservation
Aggregated
Charging
Infrastructure
Management
Metering
Aggregation
(NNAP)
Low Voltage
Grid Controller
NW2: Sub-station NW
NW6: LV Grid Management Network
Local LV Grid
ressources (DER)
Photovoltaic
Inverter
NW5: Private IP Network
NW3: Public IP Network
Battery
Inverter
NW1: Metering
Private Charging Station
Energy
Management
Gateway
EVprivch
NW4: eCar
Communication
Public Charging Station
Private
Smart
Meter
Private
Charging
Spot
Charging
Station
Controller
EVpubch
NW4: eCar
Communication
Public
Smart
Meter
Public
Charging
Spot
Figure 75 Use case components and Networking Connectivity Options
Page 139 of 244
FP7-ICT-318023/ D1.1 ver 2
Sell Energy
nc
<<
ex
i
<<
te
n
ds
>>
Energy
Providers
lu
de
Metering
DSO
Manage Energy and
Power (Quality)
<<include>>
<<
inc
lud
e>
>
>>
Provide Energy
Negotiate energy
prices
inc
<<
lud
>
e>
Provide Charging Control
Directives (price motivation)
Charge
<<in
cl
<<include>>
EV Owner/
Driver
ude
>>
Provide Charging
Infrastructure
Plug in/out EV
<<include>>
Reserve Charging
Space
E-mobility
Service
Operator
Figure 76 - Use Case Diagram for EV charging scenario
Page 140 of 244
Charging
Station
Operator
FP7-ICT-318023/ D1.1 ver 2
EV Owner
/Driver
Charging
Station
Routing &
Reservation
EVpubch
Availability
Check
Aggregated
Charging
Infrastructure
Management
Charging
Station
Controller/
Gateway
Charging
Spot
Low Voltage
Grid Controller
Available Resources?
Available Resources?  Current & Future
Demand, Flexibility
Available Place, Energy (& Price)
Smart
Meter
Metering
Aggregation
Energy
Providers
Planning &
Estimation
Available Power & Load Objectives
Market Conditions
Negotiate Price
Price Signals
Ideal Charging
Periods/Price
Signals
Find Charging Station with Context
Availability
Check
Charging Opportunities
Reservation
Plugin & Context (SOC, Stay duration)
Plugin & Context
Available Resources?  Current & Future
Demand, Flexibility
Planning
Start/Stop Charging
Start/Stop Charging
AP Update
...
...
Planning
Start/Stop Charging
Start/Stop Charging
Plugout
Metering
Metering Data
Energy Consumption
Billing
Figure 77 - Message Sequence Diagram for EV charging scenario
Page 141 of 244
FP7-ICT-318023/ D1.1 ver 2
Provide Energy
Energy
Providers /
Aggregators
in
<<
d
cl u
n
<<i
Manage Power in Grid
(Plan & Control)
<<include>>
DSO
>
e>
cl u
>
de >
<<include>>
<<
inc
lud
Provide & Plan
Energy
Provide &
Plan Load
e>
>
DER Owner
Battery (DER)
Owner
Provide Load
Metering and Sensoring
Charging
Station
Operator
Consumers
Figure 78 - Use Case Diagram for energy and power management scenario
Page 142 of 244
FP7-ICT-318023/ D1.1 ver 2
Metering
Aggregation
Charging
Station
Controller/
Gateway
Photovoltaic
Inverter
Battery
Inverter
DMS
(SCADA)
Low Voltage
Grid Controller
Information
Services
DSO
LV Grid Mgmt.
GIS Data,
Operation
Objectives and
set-points
Data for
prediction
(Metering,
Weather)
Power & Energy
Control Loop
Consumption Now
Load & Production
Prediction
Production Now
Current and Planned State
(SoC, Charging, Providing)
Available Resources?  Current & Future Demand, Flexibility
Planning &
Estimation
Production Limits
Storage Control Objectives
Storage Control
Planning & Control
Monitoring &
Alarms
Figure 79 - Message Sequence Diagram for energy and power management scenario
Page 143 of 244
FP7-ICT-318023/ D1.1 ver 2
Generate &
Sell Energy
Energy
Providers/
Aggregators
Buy Energy
lu
inc
<
<
>>
de
de
<<inclu
DER Owner
>>
Sell Load Flexibility
Buy Reserves for Balancing
<<include>>
DSO
Metering
Buy Charging Service
EV Owner/
Driver
Sell Charging Service
<<include>>
<<include>>
Buy Energy
Load
Energy
Customers
Figure 80 - Use Case Diagram for Energy Market scenario
Page 144 of 244
Battery (DER)
Owner
Charging
Station
Operator
FP7-ICT-318023/ D1.1 ver 2
Meter Data
Management
DSO
Battery Owner Energy
DER Owner
Providers &
Aggregators
Market
(Distribution
/Transport)
DMS/
SCADA
Charging
Station
Controller
Aggregated
Charging
Infrastructure
Management
EV Owner/
Driver
Charging
Station
Operator
Sell Production
Sell Decentralized
Energy Production
Sell Decentralized
Energy Production
Sell Aggregated Energy
Production
Sell Decentralized
Energy Production
Sell Demand
Flexibility
Sell Demand Flexibility
Sell Demand Flexibility
DSO Demands
Power/Energy Control Need
Buy Energy & Demand Flexibility
CSO Demands
Negotiate Prices
Price Signals
Price Signals
Ideal Charging Periods/
Price Signals
Billing
Metering
Billing
Billing
Billing
Figure 81 - Message Sequence Diagram for Energy Market Scenario
Page 145 of 244
Billing
Consumer
FP7-ICT-318023/ D1.1 ver 2
Energy Provider / Aggregator
Transport & Distribution Market
Market
Charging Station Operation
Information
Services
Charging
Infrastructure
Management
Enterprise
Meter Data
Management
System
Operation
DMS
Low Voltage Grid
Control
Station
Metering
Aggegation
Charging
Station
Control
Production
Control
Metering
Actuation &
Monitoring
Generation
Transmission
Distribution
Home
Control
Actuation &
Monitoring
Actuation &
Monitoring
Field
Process
Customer
Premise
DER
Figure 82 - SGAM Function Layer
EVpubch
Metering
Aggregation
PV
Inverter
Charging
Station
Controller
Low Voltage
Grid Controller
MDM
Get Consumption now
Data missing error
Get production now
Metering Data Error
Query MDM
MDM Error
Reduced available power
Start/stop
charging
Change
schedule
Figure 83 – AS3 Metering information interrupted
Page 146 of 244
Estimate load
Under
uncertainty
FP7-ICT-318023/ D1.1 ver 2
PV
Inverter
EVpubch
Charging
Station
Controller
Low Voltage
Grid Controller
EV Owner
/Driver
Heartbit
Heartbit
timeout
Schedule
With power
constraints
Start/stop
charging
New reservation/plugin
Refuse temporarily (service
restricted)
Figure 84 – AS2 LVGC-CSO connection interrupted
Page 147 of 244
FP7-ICT-318023/ D1.1 ver 2
Aggregator & CSO
.3
PS3
PS
1.3
,P
S1
.5
DMS
PS
1.2
Low voltage
grid controller
PS2.6
1.9
PS
.6,
1
PS
Charging
spot
.1
1
1 .8
PS
Meter Aggregation
Meter
PS2.7
PS2.8
PS
1.
9
DSO
PS2.5
Charging
Station
Controller
PS
1.
6,
PS2.10
PS 2.4
PS 2.9
PS
1
PS
1.1
,
PS
1.
4,
PS
PS
1.
7
1.
3
PS3.4
.6
PS 3
E-mobility
Charging
Service
Station
Operator
Routing &
Reservation
Market
PS3.5
Aggregated
Charging
Infrastructure
Management
Battery PV Local
Storage Production
PS 1.11
Figure 85: Diagram of the Interactions described in section 4.1
Stakeholders
Actor Name
Actor Type
Actors
Group Description
Actor Description
see Actor List
see Actor List
see Actor List
Electrical Vehicle
Owner
Person
The owner or user of an
electrical vehicle demanding
charging services.
Requests charging service
(demand, time window),
Further information
Components associated
EV or Plug-In Hybrid
Electrical Vehicle
(PHEV)
Charging Station
Operator (CSO).
Page 148 of 244
Role
Operator of a Charging station
(which is an electrified parking
lot with several Charging Spots)
is an independent enterprise or
owned by Energy provider,
DSO, etc.
- it aggregates EV load, offers
demand flexibility.
- Builds and maintains the
-
CS controller
Charging spots
(CS), sub-meters
Grid node/main
meter
FP7-ICT-318023/ D1.1 ver 2
charging schedule for all EVs
connected to its charging spots
- Receives from DSO (LVGC)
actual and predicted available
power profile
- reports the EV load profile
- handles user payment for EV
services
- clearance with energy
provider or market
E-Mobility Service
Operator
Role
Distribution System
Operator (DSO)
Role
Every Charging station in a LV
grid, even from different CSOs,
becomes allocated an amount
of energy resources
proportionally to the number
of charging spots.
- Lists the best charging station
locations to EVs,
- Handles reservations
- Receives from CSPs
availability updates
-
-
Energy Provider
Role
-
Aggregator
Role
Consumer
Person
Page 149 of 244
limits charging capacity of
CS
LVGC receives load
max/min profile from
primary station
LVGC receives price
information from
LVGC calculates set points
for aggregators, DG,
storage
Provides energy to
customers.
Sends price signals,
receives load information,
An entity able to aggregate
several production units as well
as demand flexibility. This
enables the aggregator to
operate on the market.
Other consumers in a LV grid
that provide loads and needs
to be considered in the
power/energy management
- May be owned by
charging station
operator.
- Reservation mgmt.
- Routing server
-
LVGC/sec.station,
Primary station
Grid
-
May be an
aggregator An
Energy Provider
may also be an
actor aggregating
many distributed
energy resources.
May be an energy
provider as well as
provider of demand
flexibility.
-
-
FP7-ICT-318023/ D1.1 ver 2
views.
receives set points for Storage
charging and discharge from
DSO (LVGC)
Battery (storage)
Owner
Role
Charging Spot (CS)
System
-
Distributed Energy
Resource (DER)
System
-
Meter Data
Management
System (MDMS)
Distribution Market
System
Information Services
System
Charging Station
Routing &
Reservation
System
-
System
Aggregated Charging System
Infrastructure
Management
Distribution
Management
System (DMS)
System
Metering Head-end
System (HES)
System
Metering
Aggregation OR
System
Page 150 of 244
A dumb unit connecting an
EV electrically to the grid
via a plug. It is controlled by
a home gateway/charging
station controller.
receives set points from
DSO (LVGC)
reports generation
System for validating, storing,
processing and analyzing large
quantities of meter data.
A market where it is possible to
buy and sell energy and
demand flexibility
Commonly available services
provided by a third party. E.g.
weather information needed to
predict PV production.
System including services for
EV owners to find charging
stations as well as for the
charging station operator to
manage several charging
stations.
System enabling to manage
several charging stations
providing interfaces to external
sub-systems (routing +
reservation), monitoring and
management of flexibility.
Overall grid monitoring and
control system for the
distribution grid providing high
level control objectives
towards lower grid levels.
Central component residing at
the DSO.
Provides interfaces towards
and MDM system.
Local aggregation point OR
Neighbourhood Network
-
Fixed Storage,
controller, meter
-
PV system, Wind mill
Inverter power Control,
meter
-
-
-
-
Operated by the CSO
Part of the SCADA
system of the DSO.
-
Ref: Smart Meters Coordination Group -
FP7-ICT-318023/ D1.1 ver 2
NNAP
Low Voltage Grid
Controller (LVGC)
System
Photovoltaic
inverter
System
Battery Inverter
System
Charging Station
Controller
System
Energy Management System
Gateway
EV
System
Smart Meter (SM)
System
Page 151 of 244
Access Point (NNAP) is a
functional entity that provides
access to one or more LNAP’s,
metering end devices,
connected to the
neighbourhood network (NN).
Local DSO driven controller
located in the secondary substation.
PV Inverter enabling to reduce
the production output to the
grid if strictly needed.
Battery Inverter also including
a control system to manage the
batteru charging/discharging.
In cases where a large storage
exist in the LV grid, this
inverter is usually providing
main control functions – e.g.
frequency stability control.
A control box controlling when
charging spots can be activated
and at which charging speeds.
It plans charging in relation to
DSO’s and CSO’s requirements.
Same as charging station
controller. Only controls a few
charging spots. Is also
responsible for controlling
other in-household flexible
loads and production. It is also
known and referred to as a
Home Gateway due to its
capabilities for home
automation beyond energy
management.
Electrical vehicle or Plug-In
Hybrid Electrical Vehicle (PHEV)
A smart meter providing
production and consumption
values. May also enable
advanced sensoring providing
active/reactive production,
frequency monitoring, voltage
Smart Metering Use
Cases
The LVGC implements
a Substation Control
System.
-
-
-
This system implements
the Customer Energy
Management System.
-
FP7-ICT-318023/ D1.1 ver 2
monitoring, etc.
Use Case Conditions
Triggering Event
Pre-conditions
Assumption
It serves several charging stations and
their CSOs for instance redirects
reservation requests from traveling EV
users to free charging stations. This
actor is optional, a simpler approach
would be to find charging stations as
POI using the navigation system (but
without knowing their availability)
It is assumed for now that reservation
is done without any commitment or
payment
It is important that any EV owner
receives service, even she is not
registered at a certain CSO or system
wide (openness). Since a full charging
costs about 3-4€ and parking in the
same order, we recommend simpler
prepaid approach. However payment
is not considered here in detail.
Charging Station Infrastructure
Management
Reservation in PS1
User registration, payment in PS1
References
Status
Impact on Use Case
No.
References Type
Referen
ce
Originator/Or
ganisation
Link
1
EV Communication
Standard
V0.0.1
Prelimina
ry draft
2
ISO/IEC 15118
DTS/IT
S00100
31
IEC
15118
Communication
ETSI
ETSI ITS
WG1
Final
Describes the
interface between an
electric vehicle and
the charging spot
including securit
IEC
IEC
62196
(1-3)
1- Final
3 – exp.
Dec 13.
Standard for electrical
connectors and
charging modes for
electrical vehicles.
IEC
IEC
Work in
progress
E- Mobility coordination group (EM-
CEN-
http://e
mic-
Road vehicles –
Communication
protocol between
electric vehicles and
grid
3
Standard
4
E-Mobility Use cases
Page 152 of 244
FP7-ICT-318023/ D1.1 ver 2
CG),
CENELEC
SG-CG/M490 smart
grids
bg.org/fi
les/plugi
nindex.pd
f
Will be a sub-use case of the generic Low Voltage grid use-case. Will share functions with the household use case as these operate in the same domain.
Level of Depth
High Level
Prioritisation
Under conditions of large penetration of electrical vehicles (pure as well as plug-in hybrids)
management of charging is needed unless large investments in grid reinforcements are made. The EV
control will provide an interesting new resource for demand flexibility due to the ability of absorbing
large quantities of energy as well as high flexibility in consumption.
Generic
View
Technical, partially market options
Electrical Vehicle Charging, Demand Flexibility, Low Voltage Grid Management, Aggregator Role,
Charging Station Operator.
Scenario Conditions
No.
Scenario
Primary
Triggering Event
Pre-Condition
Post-Condition
Actor(s)
PS1
EV Charging
EV owner
EV owner seeks a
charging station
EV and owner are valid
(credentials).
PS2
Energy &
Power
Manageme
nt
DSO
Periodical update or
dramatic change in
available power
resources
PS3
Energy
Market
Energy
Providers,
Aggregators
Data Links are OK,
agreements exist with
charging station
operator and energy
resource providers to
enable control.
Established business
relations between
primary actors and a
Page 153 of 244
Periodic, based on
types of market
EV owner has a valid
reservation at a certain
charging station, has travelled
there and successfully received
desired charge.
No alarms, i.e. the grid power
quality is maintained and
energy resources are available
for future power management.
Price agreements and billing
closed.
FP7-ICT-318023/ D1.1 ver 2
Scenario Conditions
No.
Scenario
Primary
Triggering Event
Pre-Condition
Post-Condition
Actor(s)
and CSO
AS1
AS2
AS3
market platform
Plugged in
Charging
aborted
EV demand
control
disrupted
EV owner
Plugin Event
Reservation OK
Av. Power alarm, no or
partial charging, plugout, leave
CSO
Detection of Comm.
failure
Data flow LVGC CSO
interrupted
Schedule with reduced load
until the condition ends
Metering
Data flow
disrupted
DSO
(LVGC)
Detection of
missing data
Grid state is OK
Conservative Available
Power estimates are
distributed until the
condition ends
For a better understanding of the following steps, the main interactions are depicted in Figure
85 .
Scenario (see Figure 76 & Figure 77, Figure 11)
Scenario
Step
Event
No.
PS1: EV Charging
Name of
Description of
Process/
Process/Activity
Activity
PS1.1
Charging
Station
Lookup
Find Charging
Station
PS1.2
Availability
Check
Availability
Check and
Response
PS1.3
Reservatio
n
Charging
Station
Routing
receives
reservation
request and
Page 154 of 244
Identify charging
station and
provide user
context
(expected stay
duration, needed
charge, …)
The Charging
Station
Infrastructure
Mgmt. identifies
charging station
options and
informs EV
Owner.
EV user selects
charging station,
arrival time
energy demand.
May get
additional
Service
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Optional
EV Owner
+ EV
Charging
Station
Routing
Charging
Context.
Optional
Charging
Station
Routing
EV Owner
Available
charging
opportuniti
es.
Optional
EV Owner
+ EV
Charging
Station
Controller
Reserve
message
Technic
al
Require
ments
R-ID
FP7-ICT-318023/ D1.1 ver 2
redirects it to
CSO
Reservation
handling at the
charging
station
CSO returns
OK
PS1.4
Process
Reservatio
n
PS1.5
Reservatio
n
successful
PS1.6
Plugin
EV Plugin
PS1.7
Plugin
Handling
Re-planning of
resources
PS1.8
Start/Stop
Charging,
Change
Charging
Speed
Charging
Process
Management
PS1.9
Plug-out
EV Plugout
PS1.1
0
Periodic
Metering
PS
1.11
Periodic
Metering
information such
as routing advice.
Update Schedule,
allocate
resources
OK response.
Charging station
Routing updates
its CS availability
list
An EV plugs into
the Charging Spot
and provides
additional/updat
ed context
information
The Charging
Station Controller
(re-)/plans the (if
needed) charging
plan
The charging
station controller
starts/stops
charging as well
as manages
charging speed
The EV plugs out
of the Charging
Spot. The
Charging Station
Controller
adapts.
Optional
Send charging
metering data to
meter
aggregation
system for billing
purposes
Read meters for
state estimation
Charging
Station
Controller
Charging
station
Routing
Schedule
update and
resource
availability
Reservatio
n
confirmatio
n
Charging
Station
Controller
EV Owner
EV
Charging
Station
Controller/
Gateway
Updated
Charging
Context.
Charging
Station
Controller
Charging
Station
Routing
Schedule
update and
Resource
availability
Charging
Station
Controller
EV
Start/Stop
commands.
Updated
charging
speeds.
EV
Charging
Station
Controller
Plug-out
event
Smart
Meter
Meter
aggregatio
n
Meter data
Meter
Aggregatio
n
LVGC
Relevant
Meter Data
Informati
on
Produce
r (Actor)
Information
Receiver (Actor)
Information
Exchanged
DMS
LVGC
- Setpoints
Scenario
Ste
Event
p
No.
PS2: Energy Balancing& Power Management
Name of
Description of
Servic
Process/Activit
Process/Activity
e
y
-
Provide update
Update
Page 155 of 244
The DMS provides
Technic
al
Require
ments RID
FP7-ICT-318023/ D1.1 ver 2
LVGC
operatio
n
of the LVGC
operation
settings
-
Update
LVGC
predictio
n
informati
on
Provide update
of the LVGC
data for
prediction
2.1
Periodic
Load and
Production
Prediction
2.2
Periodic
Metering
2.3
Periodic
Distributed
Generation
2.4
Periodic
2.5
Periodic
Control
Re-planning
2.6
Periodic
Charging Load
profile update
2.7
Overvolt
age/Curr
ent
Limit
Production
Page 156 of 244
information to the
LVGC to update highlevel operation
objectives as well as
changes in data
models such as grid
topology information,
newly connected
charging stations etc.
Information is pushed
(or pulled) from
information services
that are useful in the
LV grid management
operation such as
weather data.
The LVGC predicts the
expected production
and load a predefined
time into the future
for planning purposes
Current load in
different busses of
the LV grid
Current generated
power in different
busses of the LV grid
Set Available power
for EV charging to all
charging stations
The LVGC plans the
local power and
energy resources to
maintain service
quality within
acceptable limits. It
may perform this
planning based on
setpoints from the
MV level.
CSO updates the
schedule considering
the preferred loads
from aggregator and
the CSO available
power constraints
If overvoltage/
over-current events
occur the LVGC can
choose to limit the
production in critical
- Settings
- Data
models (e.g.
grid
topology)
Informa
tion
Services
LVGC
- Weather
data
- Expected
load profiles
-…
LVGC
LVGC
Updated
prediction
profiles
Meterin
g
Aggrega
tion
Meterin
g
Aggrega
tion
LVGC
LVGC
Load
information
on busses
LVGC
Generated
information
on busses
Charging
Station
controller
LVGC
Available
power
profile
Power and
Energy
control plan
in the LV
grid.
Chargin
g
Station
Controll
er
LVGC
EV Loads
update
LVGC
Photovoltaic
Inverter
Production
Limits
LVGC
FP7-ICT-318023/ D1.1 ver 2
2.8
Service
quality
deviation
s
Change battery
control
objectives
2.9
Power
quality
deviation
s
Change
demand
objectives
2.1
0
Events/A
larms
Monitoring
events/Alarms
periods to maintain
power quality.
A local battery in the
grid can be requested
to change its
objectives to
increase/decrease
load to aid in the
operational
parameters
The LVGC can request
flexibility services
from the Charging
Station Controller to
increase/decrease
load now and in the
future. This involves
hard constraints on
power availability.
A monitoring event or
alarm (depending on
criticality level) is
raised and sent to the
DMS to report about
the current and past
state of the LV grid.
LVGC
Battery Inverter
Setpoints/o
bjectives for
battery
control
LVGC
Charging
Station
Controller
Setpoints/o
bjectives for
-charging
demand
flexibility
- Available
power
profile
LVGC
DMS
Event/Alar
m
Scenario:
Step Event
No.
PS3: Energy Market
Name of
Description of
Process/Activi Process/Activity
ty
3.1
Periodic
Sell
Production
3.2
Periodic
Sell
Aggregated
Production
3.3
Periodic
Provide
EV charging
demand
Page 157 of 244
Se
rvi
ce
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Local energy sources
(storage and production)
sell energy resources to
an aggregator.
Local energy resources
across several LV/MV
grids are aggregated
enabling the aggregator
to act on the retail
market
DER/Battery
owner
Aggregator
Energy
production
capabilities
Aggregator
Market
Aggregated
energy
production
capabilities
The charging station
forwards an already price
optimized demand curve.
CSO
EV
Aggregator
(retailer)
demand +
flexibility
capabilities
Techni
cal
Requir
ement
s R-ID
FP7-ICT-318023/ D1.1 ver 2
(alternatively, it forwards
the demand plus its
flexibility and the
aggregator performs the
price optimization)
3.4
Periodic
Price signals
pricing information is
provided to energy
providers/aggregators.
Market
EV
Aggregator
Price signals
3.6
Periodic
Price signals
The CSO uses the price
information and the
flexibility of the charging
operation to find an
optimal demand curve
EV
Aggregator
CSO
Price signals
3.5
Periodic
Price
Optimized
Energy buying
The aggregator buys
updates the energy need
by buying on the intraday
market
EV
Aggregator
Market
Demand
Scenario
AS2: EV demand control disrupted
Step
No.
Event
Name of
Process/Activity
1
LVGC CS Scheduling
connection under av.
lost
power
uncertainty
Description of
Process/Activity
Service
Enter
precautious
mode.
Refuse new
requests
Information
Producer
Information
Receiver
Information
Exchanged
CSO
Charging
Spots
reduced
charging
duration
Technical
Requirements
R-ID
Scenario
AS3: Metering data flow disrupted
Step
No.
Event
Name of
Process/Activity
1
consumption Estimate
Metering
load under
samples
uncertainity
missing
Page 158 of 244
Description of
Process/Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
Conservative
calculation of
available
power
CHANGE
LVGC
CS
Reduced
controller Available
power
Technical
Requirements
R-ID
FP7-ICT-318023/ D1.1 ver 2
Name of Information
Exchanged
Reservation
Available power
Charging load profile
Metered Consumption bus load
Metered Generation power
Generation output limitation
Charging start/Stop
Information from vehicle: arrival, expected
departure time, min charging energy, maximum
energy,
Calculation of maximum power that can be
pulled out from a node for charging
Aggregated load profile (plan) for a charging
station
Aggregated domestic load metered in one
period
Aggregated bus gen .power in one metering
period
Control signal to the PV inverted 0<c<=1
Sub-meter on/off signal
Term
Definition
LVGC
Low voltage grid controller
CS
Charging spot
EV
Electric vehicle
CSO
Routing
Charging station operator (controls EV parking with several CPs), aggregates EV load, is owned by Energy
provider or charging station infrastructure provider
Pre-charging User Service to find the best CS
EV demand
Amount of energy required by an EV
Plugin event
User is at CP and plugs in charging (and data) cable
Page 159 of 244
FP7-ICT-318023/ D1.1 ver 2
10.3 USE CASE NAME: External generation site
ID
Domain(s)
Name of Use Case
Changes /
Version
Date
0.00
25.01.2013
0.3
0.4
0.5
0.8
18.02.2013
10.03.2013
18.03.2013
19.07.2013
Version Management
Name
Domain
Expert
Area of
Expertise /
Domain /
Role
Rasmus Løvenstein Olsen,
Florin Iov, Jayakrishnan
Radhakrishna Pillai, Rafael
Wisniewski, Christoffer Sloth
Rasmus Løvenstein Olsen,
Christoffer Sloth, Florin Iov
Title
Approval
Status
for voting, final
draft
Update
Update
Update
Scope
Page 160 of 244
Use case 2: Self-Optimized Low Voltage Grid Domain
With the anticipated increase in small decentralized energy resources from
primary wind and photovoltaic (PV), the low voltage (LV) grids are exposed
to new load scenarios than originally designed for. Further, new high
consumer demands from Electrical Vehicle (EV) mobility and heat pumps
challenge existing LV grid infrastructures additionally. As a result, there is an
increased interest in technologies to improve the LV grid operation. These
mainly entail: local energy storage, active control of energy fed in electrical
grid, flexible demand control (entailing both end-user managed demand
response and autonomic demand control) for house-holds and EVs. This use
case covers the automation and control techniques required for future LV
grids and enables the DSO to utilize the flexibility of the LV grid assets.
The reference scenario for this use case consists of a MV and LV grid
containing: 1) fixed and shift-able energy consumption from households,
small enterprises and EVs, 2) production from PVs and wind turbines, 3)
Energy storage. Hierarchical controller architecture is utilized, where a
distribution management system (DMS) is at the upper most level. This
provides commands to the MV grid controller, which sends commands to
the LV grid controllers as well as flexible generation and consumption in the
MV grid. Finally, the LV grid controller sends commands to flexible assets in
FP7-ICT-318023/ D1.1 ver 2
Objective
the LV grid. The LV grids are connected to the MV grid via a controllable
transformer station with an online tap changer (OLTC).
It is considered that all components in the architecture are connected with a
communication network providing monitoring data from and control of the
individual components. The LV grid implements its own control mechanisms
which are responsible for: a) maintaining an acceptable voltage profile,
security and safety, b) balancing available power resources (energy storage
and generation) with the (flexible) demand, and c) handling the interactions
between a) and b). The control infrastructure is managed by one or more
dedicated LV grid controllers which provide functionality to support the subuse cases introduced in the following sections. This Use Case is considering
only faults and performance degradation within the public communication
network, and the system’s overall ability to perform normal grid operation
even during network faults and performance degradation.
The objective is to demonstrate the feasibility of distribution grid operation
over an imperfect communication network
The Use Case is focusing on demonstrating the feasibility of controlling flexible loads and renewable
energy resources in LV grids over an imperfect communication network. Flexibility of LV grids for
upper hierarchical control levels is also investigated
Under these settings, two main scenarios are defined as to show the above characteristics:
models).
Page 161 of 244
FP7-ICT-318023/ D1.1 ver 2
WAN
HV Grid
Markets
Forecast
Providers
HV
Primary Substation
Automation&Control
MVGC
TSO
Retailers
MV
DMS
Prosumer
Large DER
Large DER
Prosumer
WAN
Provider(s)
MV
Aggregators
MV/LV
LVGC
LV
MV
MV
Secondary
Substation
Automation
&Control
Secondary
Substation
Automation
&Control
LV
Prosumer
SME
Consumer
Farm
Interm.
DER
SME
...
Consumer
Energy
Storage
...
MicroDER
…
...
LV
...
AN Provider(s)
AN Provider(s)
AN
Commercial
Feasibility
& Flexibility
Technical
Flexibility
&Performance
Use Case
2.3
Figure 86 Overview of Use Case
General Remarks
The definitions for distributed energy resources used for this Use Case are defined in the table
below. These definitions are taken into account the voltage and current at the connection point as
well as the power rating of the device.
DER Definition
Voltage
Ratings
[kV]
<1
Current
Ratings
[A]
<16
Installed
Capacity
[kW]
<5
Intermediate DER
<1
> 16
5 < …< 500
Large DER
>1
> 16
> 500
Micro DER
Page 162 of 244
DER Type
DER at Household level
e.g. micro CHP, PV
system, wind turbine,
energy storage,
DER connected to low
voltage feeders.
Examples: standalone
systems e.g. PV panels
and heat pumps, single
wind turbine, battery
storage, charging spot for
EVs, etc
DER connected to
FP7-ICT-318023/ D1.1 ver 2
medium voltage grids.
Examples: wind or PV
power plants, Combined
Heat and Power plants,
Supermarkets with
refrigeration systems and
charging stations for EVs,
etc.
Diagram of Use Case
Page 163 of 244
FP7-ICT-318023/ D1.1 ver 2
WAN Provider(s)
Forecast
Provider(s)
Market(s)
Retailer
Large DER
Data Transport
(WAN)
DMS
Network
congestion
TSO
DSO
Network
performance
change
Medium Voltage
Grid Controller
Prosumer
Lost
Network
connectivity
Control of
assets
Micro DER
Prosumer
Aggregator
Technical (MV/LV)
Low Voltage Grid
Controller
AN Provider(s)
Data Transport
(AN)
Lost network
connectivity
Network
performance
change
Intermediate DER
Network
congestion
Consumer
Figure 87 Overview of use cases
The use cases as defined in the following document will be running on top of a system described in
slightly more details in the following using SGAM depicturing methodology.
Based on SGAM Framework the component layer of the Use Case is shown in Figure 88. In the
following a brief overview of the architecture and functionality of the use case diagram is provided in
component and functional layers as described in [UCC]. This approach describes the relation
between components and functions in terms of electrical grid components (x-axis) and zones of
operation (y-axis) which is helpful also to understand the need for communication between the
various components and functions. This shows the generic interaction between assets and
controllers for the Control of Assets use case.
Page 164 of 244
FP7-ICT-318023/ D1.1 ver 2
Component Layer
Private Channel(s)
WAN Channel(s)
AN Channel(s)
Markets
Market
Enterprise
Forecast Provider
Operation
TSO
Station
Retailer
DMS
Technical
Aggregation
(MV)
Technical
Aggregation (LV)
MV grid control
LV grid control
AN Network
Provider(s)
WAN Network
Provider(s)
Field
MV Grid
Components
Process
Transmission
LV Grid
Components
Distribution
Large DER
Prosumer
DER
Smart
Meter
Smart
Meter
Smart
Meter
Smart
Meter
Prosumer
Micro DER
Intermediat
e DER
Consumer
Customer Premises
Figure 88 Set of physical components and their locations in the smart grid setup
Communication layer of the Use Case describing different potential communication technologies
between various components is given in Figure 89. Faults and errors causes performance
degradation that needs to be taken into account, which creates the error scenarios for the Data
Transport use cases at Access Network and Wide Area Network level.
Page 165 of 244
FP7-ICT-318023/ D1.1 ver 2
Communication Layer
Market
Enterprise
Operation
Markets
Public internet
Retailer
Cable, UMTS, WiMAX
xDSL,
Fiber,
Forecast
Provider
TSO
DMS
Private net
Fiber, Ethernet, ATM
Private net
Technical
PLC,Fiber, Technical
Aggregation
Aggregation (LV)
Ethernet, ATM
(MV)
Station
MV grid control
LV grid control
Public Access Networks
xDSL, Cellular (UMTS, GPRS), WiMAX, PLC
Private net
PLC,Fiber,
Ethernet, AT, TETRA
Field
MV Grid
Components
Process
Transmission
LV Grid
Components
Distribution
AN Network
Provider(s)
WAN Network
internet
Provider(s)
Public
xDSL, Fiber, Cable, UMTS, WiMAX
Large DER
Prosumer
DER
Smart
Meter
Smart
Meter
Smart
Meter
Smart
Meter
Site comm.
WLAN, Ethernet, WB-PLC,
Zigbee, Z-wave
Intermediat
Prosumer
Micro DER
e DER
Consumer
Customer Premises
Figure 89 Different communication means used for the various components to interact with each other
Functionalities in the grid that allows the operation and the two cases; commercial and technical
flexibility scenarios. These are connected with the communication lines as shown above, and is
executed on the various grid components as illustrated in Figure 88.
Page 166 of 244
FP7-ICT-318023/ D1.1 ver 2
Functional Layer
Market
Market
prices
Markets
Weather
Enterprise
Operation
information
Forecast
Provider
HV grid management,
GIS system data,
planning
TSOtools,
visualisation
Commercial
Retailer
aggregation
MV/LV grid
management, GIS
system DMS
data, planning
tools,
visualisation
Technical aggregation
GridTechnical
resynch., fault detection and
Technical
Aggregation
isolation, demand Aggregation
side mngt(LV)
and
response,(MV)
curtailment, ancillery services
Station
Protection and monitoring
LV grid control
Warnings and alarms for
grid failure
MV grid control
AN Network
Provider(s)
WAN Network
Provider(s)
Field
Smart
Meter
MV Grid ActuationLV Grid
Components
Components
Process
Transmission
Distribution
Large DER
Actuation Prosumer
DER
Prosumer
Smart
Smart
Smart
Protection
metering Meter
Meter and Meter
Intermediat
Actuation
Micro DER
e DER
Consumer
Customer Premises
Figure 90 Different functionalities used in the system in order to be able to execute the use cases over the
network on the different physical components
In the following part of this document, high level descriptions of the use cases, step by step, will be
done.
Page 167 of 244
FP7-ICT-318023/ D1.1 ver 2
Stakeholders
Actors
Group Description
Actor Name
Actor Type
Actor Description
see Actor List
see Actor List
see Actor List
Micro DER
Intermediate DER
Large DER
Consumers
Role
Prosumers
Role
Smart Meter (SM)
System
Comm. Network Provider
Role
Distribution System
Operator (DSO)
Role
Page 168 of 244
Distributed energy resources at house hold
level. Examples of such resources are: wind
turbine, PV system, micro CHP, energy
storage, EVs, etc
Distributed energy resources connected to
low voltage feeders. Examples of such
resources are: standalone systems e.g. PV
panels and heat pumps, single wind turbine,
energy storage, charging spot for EVs, etc.
Distributed energy resources connected
to medium voltage grids. Examples of
such resources are: wind and PV power
plants, Combined Heat and Power
plants, Supermarkets with refrigeration
systems and charging stations for EVs,
etc.
Consumers that are not offering flexibility in
operation and control such as: households,
small enterprises
Consumers that are offering flexibility in
operation and control. They can be
connected at LV or MV grids and can
contain micro, intermediate, or large
DER.
The metering end device is a
combination of the following meterrelated functions from the Smart
Metering reference architecture:
• Metrology functions including the
conventional meter display (register or
index) that are under legal metrological
control. When under metrological
control, these functions shall meet the
essential requirements of the MID;
• One or more additional functions not
covered by the MID. These may also
make use of the display;
• Meter communication functions.
Provides communication services to the
system, e.g. M2M infrastructure.
Directive: "a natural or legal person
developing the distribution system in a
given area and, where applicable, its
interconnections with other systems and
for ensuring the long-term ability of the
system to meet reasonable demands for
the distribution of electricity". Moreover,
the DSO is responsible for regional grid
access and grid stability, integration of
renewables at the distribution level and
regional load balancing.
Further information
Entities connected to the LV
grid, but not belonging to
households or small
enterprises
Smart household or small
enterprise
Every household is equipped
with a smart meter.
Utility companies
FP7-ICT-318023/ D1.1 ver 2
Transmission System
Operator (TSO)
Role
Technical Aggregators MV/LV
Role
Retailer
Role
Markets
Forecast Provider
System
Low Voltage Grid
Controller
System
Medium Voltage Grid
Controller
System
LV Grid Components
System
MV Grid Components
System
Distribution Management
System
System
Electricity Directive 2009/72/EC
(Directive): "a natural or legal person
developing the transmission system in a
given area and, where applicable, its
interconnections with other systems,
and for ensuring the long-term ability of
the system to meet reasonable
demands for the transmission of
electricity". Moreover, the TSO is
responsible for connection of all grid
users at the transmission level and
connection of the DSOs within the TSO
control area.
Offers services to aggregate
signals/information regarding flexibility
of different consumers and prosumers
from MV and LV grids respectively. This
aggregated information is used by
hierarchical control levels.
Entity selling electrical energy to
consumers - could also be a grid user
who has a grid connection and access
contract with the TSO or DSO. In
addition, multiple combinations of
different grid user groups (e.g. those
grid users that do both consume and
produce electricity) exist. In the
remainder of this document, the terms
customer/consumer and grid user are
used interchangeably where
appropriate.
Market for trading energy and ancillary
services
Compute forecast for consumption and
renewable generation in a given area
based on weather forecast, historical
data, etc.
System placed in the secondary
substation aiming to control assets on
LV feeders and provide flexibility to
upper control levels.
System placed in the primary substation
aiming to control assets on MV feeders
and provide flexibility to TSO and DMS.
Grid components such as transformers,
cables, breakers, etc.
Grid components such as transformers,
cables, breakers, etc.
A system which provides application to
monitor and control a distribution grid
from a centralized location, typically a
control centre
Transmission system
operator(s)
Power, Energy, Ancillary
Services
May be separate for wind,
Solar Irradiance, consumption,
etc.
Use Case Conditions
Triggering Event
Pre-conditions
AN/WAN between communicating
entities (MVGC, LVGC and Assets)
Change in network
performance (no-congestion)
Page 169 of 244
“Normal” cross
traffic patterns in
network
Assumption
-Bidirectional communication with
consumers can be done for effective
network reconfiguration.
-Traffic increase is caused by external
factors, i.e. uncorrelated with the
control traffic.
FP7-ICT-318023/ D1.1 ver 2
AN/WAN between communicating
entities (MVGC, LVGC and Assets)
Congestion in network
High load network
condition
- Bidirectional communication with
- Some QoS configuration possibilities
exists
-Traffic increase is caused by external
factors, i.e. uncorrelated with the
control traffic.
AN
Wired/wireless network
Network connection is lost
Pre-existent
connection at
network layer
AN
Wireless networks
Link conditions changed
“Normal” channel
condition
AN
Wireless networks
Link capacity reached
High load on AN
AN
Wireless networks
Link connection is lost
Pre-existent
connection at link
layer
- Requires a notion of logic
connectivity between entities at
network layer.
- The cause of lost connectivity is in
the network (i.e. we delimit from nonresponsive devices/crashed devices).
- Some link reconfiguration
possibilities exists and is accessible
- Change of channel conditions are
uncorrelated with the power grid and
happen at random time intervals.
- Some QoS options exists for
reconfiguration of the link
- Factor that triggers the congestion
state is not correlated with the control
system, e.g. too many customers in
the network
- Alternative AN’s are available.
No.
References Type
Reference
1
Public
SG-CG/M490/C
Smart GridReference
Architecture
2
Public
References
Status
Impact on
Use Case
Originator/Organisation
V 3.0
This sub-use case must exploit the flexibility offered in sub-use cases 1 and 2 in the low voltage grid controller.
Level of Depth
High level description
Prioritisation
High/Mandatory
Regional
Page 170 of 244
Link
FP7-ICT-318023/ D1.1 ver 2
View
Technical
Smart grid control, network failure resilience
Page 171 of 244
FP7-ICT-318023/ D1.1 ver 2
Scenario Conditions
Scenario
Primary
Name
Actor
4.1
Base Case
4.2
Network
Performanc
e Changed
Network
Congestion
Lost
Network
Connectivit
y
No.
4.3
4.4
Triggering Event
Pre-Condition
Post-Condition
WAN/ANPro
vider
WAN/ANPro
vider
No events in WAN/AN
Normal Operation
Change in network
performance
Normal Operation
WAN/AN
Provider
WAN/AN
Provider
Normal Operation
Congestion
Network connection is lost
Normal Operation
Loss of connectivity
Normal operation
Each of these scenarios is considering three subcases as:
 Energy balance – where the operation of MV grids is targeted. LV grids are considered
aggregated and the LVGC is offering flexibility to MVGC. Thus MVCG is primarly controlling
the assets such as Large DER, prosumers and LV grid via LVGC to keep the energy balance.
The primary actor involved here is the WAN Provider
 MV control – where the focus is to control the voltage profile on MV grids using reactive
power capabilities offered by Large DER, MV prosumers and the secondary substations on
MV side. The primary actor involved here is the WAN Provider
 LV control - where the focus is to control the voltage profile on LV grids using reactive power
capabilities offered by Micro and Intermediate DER, flexible consumption and production at
household or small and medium enterprises. The primary actor involved here is the AN
Provider(s)
These subcases may involve only some of the actors while other are neglected as mentioned above.
Grid operations
In normal operation the grid is operated as follows. Starting from the lowest level (right in the
figure), consumers and DERs sent measurements to the LV grid controller and receive setpoints from
the LV grid controller. The measurements from LV assets are aggregated before they are sent to the
MV grid controller. Similarly, the LV grid control receives an aggregated setpoint from the MV grid
controller that must be dispatched to the individual LV assets. The MV grid controller communicates
with Large DERs and LV grid controllers to exchange aggregated flexibility, measurements, and
setpoints. Additionally, the MV grid controller sends the aggregated flexibility to the DMS, which
generates setpoints based on the available flexibility, weather information, and market conditions.
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Forecast Provider
Technical
Aggregation (MV)
TSO
Retailer
Markets
DMS
WAN Network
Provider(s)
MV grid control
Measurements
Technical
Aggregation (LV)
Large DER
Network
Status/
performance
Network
Status/
performance
Measurements
Measurements
AN Network
Provider(s)
Consumer
Micro DER/
Intermediate
DER/Prosumer
LV grid control
Network
Status/
performance
Network
Status/
performance
Measurements
Measurements
Measurements
Measureme
nts
Price signal
Weather
information
Weather information
Aggregated
Flexibility (LV)
Aggregated
flexibility (LV)
Network
Status/
performance
Aggregated
Flexibility (MV)
Network
Status/
performance
Bids
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Measurements
Setpoint
Accepted bids
Setpoints
Network
Status/
performance
Network
Status/
performance
Individual
setpoints (MV)
Individual
setpoints (MV)
Aggregated
setpoint (MV)
Individual
setpoints (MV)
Aggregated set
point
Network
Status/
performance
Network
Status/
performance
Individual
setpoints
Individual
setpoints
Individual
setpoints
Scenario
Scenario
Name :
Base Case
Step
No.
Event
Name of
Process/Activ
ity
Description of
Process/Activit
y
Servic
e
Information
Producer
Information
Receiver
Information
Exchanged
1
Periodica
lly
Status and
measurement
collection
GET
Periodica
lly
Actuation
calculations
MV grid
controller, grid
sensors, smart
meters, grid
components
Technical
Aggregator, LV
grid controller
Technical
aggregator, LV
grid controller,
MV/LV grid
management
Actuators, LV
grid controller
Grid status
data (Voltage,
frequency, …)
2
Data regarding
status of the grid
is collected and
other information
such as wind
Determine
response to
demand/supply
EXECU
TE/SET
Technical
Requiremen
ts R-ID
Actuation
signals,
reference
signal to LV
grid
controller
Change in network performance
This scenario deals with time varying performance in the network, and the adaptation of
access methods to provide reliable data exchange between entities communicating.
Scenario
Scenario Name :
Network performance change
Step
No.
Name of
Process/Activit
y
Event
Page 173 of 244
Description
of
Process/Act
Service
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requiremen
ts R-ID
FP7-ICT-318023/ D1.1 ver 2
ivity
1
Change in
network
performanc
e (nocongestion
Network
monitoring;
access adaptation
mechanisms
2
Monitoring of
network
performance
leads to
detection of
performance
loss
Change and
recalculation
of access
reconfigurati
on
parameters
GET
Communicati
on Network
Provider
Monitoring
Potentially
network
performance
measurement
data, and signal
to controller
EXECUTE
Monitoring
Information
access manager
Access
configuration
parameters
* This scenario is relevant for both WAN and AN.
Forecast Provider
Technical
Aggregation (MV)
TSO
Retailer
Markets
DMS
WAN Network
Provider(s)
Technical
Aggregation (LV)
MV grid control
Large DER
Network
Status/
performance
AN Network
Provider(s)
WAN network
change
AN network condition
change
Network
Status/
performance
Aceess
reconfiguration
Measurements
Micro DER/
Intermediate
DER/Prosumer
LV grid control
Network condition
Status/
performance
Consumer
Measurements
Network
Status/
performance
Aceess
reconfiguration
Aceess
reconfiguration
Price signal
Measurements
Weather
information
Measurements
Weather information
Aggregated
Flexibility (LV)
Aggregated
flexibility (LV)
Network
Status/
performance
Aggregated
Flexibility (MV)
Measurements
Network
Status/
performance
Network
Status/
performance
Bids
Network
Status/
performance
Measurements
Setpoint
Accepted bids
Setpoints
WAN network
condition change
Aggregated
setpoint (MV)
Network
Status/
performance
Network
Status/
performance
Aceess
reconfiguration
Individual
setpoints (MV)
AN network condition
change
Individual setpoints (MV)
Network
Status/
performance
Aggregated set
point
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Aceess
reconfiguration
Individual
setpoints
Individual setpoints
This scenario deals with more severe network conditions, i.e. congestions in the network, and
the adaptation of access methods to provide reliable data exchange between entities
communicating.
Scenario
Scenario Name :
Congestion in network detected
Step
No.
Name of
Process/Activit
y
Event
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Description
of
Process/Act
ivity
Service
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requiremen
ts R-ID
FP7-ICT-318023/ D1.1 ver 2
1
Network
congestion
detected
Network
monitoring;
access adaptation
mechanisms
2
3
Monitoring of
network
performance
leads to
detection of
performance
loss
QoS/network
option
availability
and
reconfigurati
on
Change and
recalculation
of access
reconfigurati
on
parameters
GET
Communicati
on Network
Provider
Monitoring
Potentially
network
performance
measurement
data, and signal
to controller
GET/EXE
CUTE
Communicati
on Network
Provider
Communication
Network
Provider
QoS parameter
settings
EXECUTE
Monitoring
Information
access manager
Access
configuration
parameters
*NB This scenario is relevant for both WAN and AN
Forecast Provider
Technical
Aggregation (MV)
TSO
Retailer
Markets
DMS
WAN Network
Provider(s)
MV grid control
Large DER
AN Network
Provider(s)
Status/
performance
Consumer
Micro DER/
Intermediate
DER/Prosumer
LV grid control
WAN congestion
Networkdetection and reaction
Network
Status/
performance
Measurements
Technical
Aggregation (LV)
AN congestion detection
and reaction
Aceess
reconfiguration
Network
Status/
performance
Network
Status/
performance
Measurements
QoS/Network/
reconfiguration
QoS/Network/
reconfiguration
Aceess reconfiguration
Aceess reconfiguration
Price signal
Measurements
Weather
information
Measurements
Weather information
Aggregated
Flexibility (LV)
Aggregated
flexibility (LV)
Network
Status/
performance
Aggregated
Flexibility (MV)
Measurements
Network
Status/
performance
Network
Status/
performance
Bids
Network
Status/
performance
Measurements
Setpoint
Accepted bids
Setpoints
WAN congestion
detection and reaction
Aggregated
setpoint (MV)
Network
Status/
performance
Network
Status/
performance
Aceess
reconfiguration
Individual
setpoints (MV)
AN congestion detection
and reaction
Aggregated set
point
Network
Status/
performance
Network
Status/
performance
Individual
setpoints
Network
Status/
performance
Network
Status/
performance
QoS/Network/
reconfiguration
QoS/Network/
reconfiguration
Aceess
reconfiguration
Lost network connectivity
This scenario addresses the case where devices loose connectivity at the network layer. The
case assumes a certain notion of connectivity, e.g. as in TCP.
Scenario
Scenario Name :
Lost Network Connectivity
Step
No.
Name of
Process/Activit
Event
Page 175 of 244
Description
of
Service
Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requiremen
FP7-ICT-318023/ D1.1 ver 2
1
Network
connection
is lost
y
Process/Act
ivity
Network manager
A timeout or
other type of
error triggers
a detection of
a lost
network
connection.
Assumes a
notion of a
logic
connection
between
entities.
Reestablishm
ent of
connection;
potentially try
different
network
interfaces in
this process.
2
Forecast Provider
(Actor)
GET
Network
provider
Information
access manager
Error signal
EXECUTE
Information
access
manager
Target device
Connection
signals
Technical
Aggregation (MV)
TSO
Retailer
Markets
(Actor)
DMS
WAN Network
Provider(s)
MV grid control
Measurements
Technical
Aggregation (LV)
Large DER
Network
Status/
performance
ts R-ID
AN Network
Provider(s)
Micro DER/
Intermediate
DER/Prosumer
LV grid control
Network
Status/
performance
Consumer
AN Lost network
connection
Network
Status/
performance
Timeout
message
Measurements
Network
Status/
performance
Timeout
message
Reconnect&
pot. net. Reconf.
Re-establishment of access
Price signal
Success OK
Weather
information
Weather information
Aggregated
flexibility (LV)
Aggregated
Flexibility (MV)
Measurements
Aggregated
Flexibility (LV)
Measurements
Measurements
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Network
Status/
performance
Bids
Network
Status/
performance
Measurements
Accepted bids
Setpoint
Setpoints
Aggregated
setpoint (MV)
Individual
setpoints (MV)
AN Lost network
connection
Network
Status/
performance
Timeout
message
Aggregated set
point
Network
Status/
performance
Timeout
message
Reconnect&
pot. net. Reconf.
Re-establishment of access
Network
Status/
performance
Network
Status/
performance
Individual
setpoints
Success OK
Name of Information
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Exchanged
Measurements
Set of measurements from assets to upper level
control.
Setpoints for assets in MV/LV grids such as
active and reactive power references, voltage
references, etc.
Network Status/Performance
Registration information; entity
capability
Deregistration information; who is
deregistering
Network location information,
interface specification
Request for information or
subscription request for information
IP address of information source; capability;
IP address; interface possibilities;
Request information for information
subscription; requirements to information
quality, delivery times etc.
Term
Definition
Entity
An entity is defined as some functional component (SW and HW) that will need to interact with the
smartc2net platform
The communication platform that provides services and functionality for the control algorithms to
efficiently and reliably access distributed information elements
Platform
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10.4 USE CASE NAME: Automated Meter Reading (AMR) and Customer Energy
Management Systems (CEMS)
ID
Domain(s)
Name of Use Case
Distribution Grid,
Customer
Systems (CEMS)
Changes /
Version
Date
Version Management
Name
Domain
Expert
0.01
0.02
0.05
11.01.2013
27.01.2013
28.01.2013
CH/TUDO
FTW
CH/TUDO
0.06
0.08
0.09
0.10
10.03.2013
21.03.2013
25.03.2013
15.05.2013
CH/TUDO
TUDO
TUDO
Antonio Bovenzi (RT)
0.12
0.15
17.05.2013
07.06.2013
FK/TUDO
FK/TUDO
Area of
Expertise /
Domain /
Role
Title
Approval
Status
for voting, final
Draft
Draft
Draft for
comments
Threat
Analysis
Researcher
Draft
Draft
Draft
Draft
Scope
-
Power Grid domains:
- Distribution networks
- Households
ICT domains:
- Home Area Networks
- Neighbourhood Area Networks
Objective
Automated Meter Reading:
 Collection of energy consumption data from electric, gas, water and
heating metering devices
 Transmission of aggregated data from the households to the energy
utilities/meter reading operators for billing and accounting
 Provide (local) feedback system to the customers in order to provide
transparent insight on the current energy consumption and enabling
indirect demand side management
 Aggregate information of energy consumption in order to balance the
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distribution grid by enabling direct demand side management
Customer Energy Management Systems:
 Improve distribution grid stability by enabling direct demand side
management
 Reduce energy costs for consumers by shifting flexible loads to less
expensive time slots or improve utilization of local energy resources
 Provide added-value services to the customers
Automated Meter Reading (AMR) is an enabling technology, which is capable of generating precise
multi-sector metering data and aggregate them on local grid operator side for large-area and inhouse analysis of current energy consumptions as well as grid load conditions. Additionally, current
efforts in context of the Internet of Things aim to connect more devices in the household to create a
more intelligent Home Area Network (HAN) including components of Customer Energy Management
Systems (CEMS) like Distributed Energy Resources (DER) and storages, demand side management,
domestic electric vehicle charging and user interaction. In context of AMR, this adds an additional
way of home building automation by combining the energy consumption of accordant components
with the current status of the energy grid to improve its stability by shifting flexible loads balanced
with the neighborhood area network.
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AMR is often referred to as the key application for enabling a Smart Grid. Basically, AMR represent
different approaches for automatically collecting energy consumption data from electric, gas, water
and heating metering devices and transmitting these data to the meter reading operator for billing
and accounting. This information enables the energy utilities for an accurate meter reading and a
detailed forecast of the predicted energy consumption. Since several years AMR systems are already
deployed mainly for industrial and commercial customers, based upon an integrative approach by
combing the actual metering components and a WAN interface for remote meter reading. Due to the
European Mandate M/441, a monthly billing for the customer and a roll-out of Smart Meter in 80%
of all European households until 2020 is targeted, which requires cost-efficient, modular concepts for
the comprehensive deployment of Smart Metering devices in a large number of households
considering a variety of application scenarios. Due to different technology life cycles for energy
components and ICT components a modular system is targeted in most of the approaches. Usually a
Metering HAN Gateways collect and store metering data from several metering devices, like
electricity, gas, water and heating meters by short range radio, e.g. ZigBee or Wireless M-Bus. The
collected data is securely transmitted bundled to the meter reading operator by different access
technologies, based on wireless, wired or PLC technologies. Moreover, a local feedback system gives
the consumer/prosumer transparent insight into his current energy consumption. In conjunction
with available tariff information motivation for reducing overall power consumption can be achieved.
The high-level AMR system architecture is depicted in Figure 91 consisting of the following
components:
1) Electricity metering devices collecting electrical energy consumption in short term intervals
enabling variable time intervals and different tariff options.
2) Sub-Metering devices for gas, water, heating collecting energy consumption in long term
intervals in order to provide automated meter reading
3) A communication gateway (HAN metering gateway) collects data from the metering and submetering devices via short range transmission technologies and aggregates data for
providing wide area connectivity to the meter reading operator/energy utility.
4) A user feedback system, which can consist of a display or a PC application, provides feedback
on a short term interval to the customers in order to enable indirect DSM by providing
current pricing and consumption information.
5) A meter reading operator is providing the infrastructure for the metering devices and is
located on the backend system side.
In the context of SmartC2Net, the following AMR scenarios with reference to [4-9] have been
identified. A detailed scenario structure with appropriate use cases is illustrated in Figure 93. It is
depicted how the individual physical components are laid out. The Smart Meters (SM) of the AMR
use case measure the amount of energy, gas and water used in the household. Therefore a
connection between the flexible and non-flexible loads and the Smart Meter is necessary. The SM
interfaces with the Local Network Access Point (LNAP) which provides the WAN connection for
upload of the metering data. It is to be considered that, due to legal restrictions out of privacy
concerns, it is possible that a direct connection between SM and Energy Management Gateway
(EMG) might not exist. A EMG has the ability to controls flexible loads, private parking spots and
home automation devices. The state of these devices, along with current tariff and consumption
information, is made available for the consumer by an external display which also provides a certain
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degree of control over the CEMS. The LNAP has an interface to the Neighborhood Network Access
Point (NNAP) which itself connects to the Head End System (HES) with its subsequent set of devices
and roles. These are the Meter Data Management System (MDMS), Metering Data Aggregator
(MDA), Distribution Network Operator (DSO), Aggregator, Metering Operator and Energy Service
Provider.
Scenario 1: Measurement (MM)
For considering all amount of customer’s supply, meter reading and tariff configuration are
integrated in the measurement procedure. Different actors (A, B, C – see chapter 10.4.3.1)
participate in the measurement procedure to ensure that tariff parameters are kept valid (Set tariff
parameters) on provider- and customer side. Meter reading can be divided in two sub-procedures,
Reading on demand and Scheduled reading:

MM.01 Reading on demand
See Figure 94 and Figure 95
This use case describes how a request may be made to the AMI (Advanced Monitoring
Infrastructure) for an on demand reading and how the AMI responds. The request may relate
to current register / index readings or to historical values (e.g. stored at the end of a billing
period). The request may be issued by Actor A or Actor B. This use case may be used to
retrieve not only the values of billing registers / indexes but any values that need to be read
on demand, under the conditions that it is for authenticated authorized actors and with full
respect of data privacy.

MM.02 Scheduled reading
See Figure 97, Figure 98 and Figure 99
This use case describes how Actor A obtains meter readings at regular intervals and how a
meter reading schedule (which indicates what data has to be read from the smart meter at
which point in time) is configured.

MM.03 Set tariff parameters
For billing configuration, the setup of billing parameters is needed. The use case Set billing
parameters describes Actor A setting the parameters that represents consumer account
arrangements. Billing parameters are Payment mode, Tariff scheme, Prices, Thresholds and
response actions and Data sets.
Scenario 2: Customer information provision (CI)

CI.01 Provide information to consumer
See Figure 103, Figure 104, Figure 105 and Figure 106
This use case describes how information may be provided to consumers by the AMI system
via the simple external consumer display.
Information may be generated by actors outside the AMI system and communicated via the
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AMI infrastructure or may be generated within the system and presented for display on
devices within the metering system.
Scenario 3: Collect AMI events and status information (ES)
The AMI provides functionality to screen and manage AMR related information with focus on supply
quality as well as tamper and fraud detection.

ES.01 Tamper and fraud detection
Detect tampering of the metering system (physical integrity, electromagnetic field,
communication, security, fraudulent use of the meter by customer, etc.) and detect tamper
of connection to network.

ES.02 Manage supply quality
This primary use case describes how information concerning supply quality is being
monitored by providing it on a regular basis to actor A and/or sending it on a regular basis to
a simple external consumer display.

ES.03 Advanced monitoring
Uploading of data and information to permit e.g. monitoring of outages (electricity), network
leakage detection (water) and identification of possible meter malfunction.
In addition, diagnostics (mainly for electronic components), the meter / metering system,
status information (e.g. battery condition credit/prepayment mode) and identification of
incorrectly sized or blocked meters(water) can be performed.
Additionally to the basic functionality of the AMR deployment, a more balanced usage of volatile
renewable energy sources (RES) and shift-able and controllable load system (CLS) in the distribution
grids is possible by an actively integration of the components on the customers side. In this context,
several customer energy management system (CEMS) are presented, like locally managed and selfsustaining Micro Grids, virtual power plant and centralized load coordination like DSM or DER based
on dynamic energy prices. All approaches focus on the bidirectional integration of DER and
prosumers (producers and consumers) from both power and communication engineering's point of
view. This includes volatile RES such as wind farms and photovoltaic systems, as well as energy-aware
households, which are enabled by AMR to get a detailed forecast of the energy demand and
additional transparency in energy consumption at the customer's side. Moreover, based on CLS and
Distributed Generation (DG) through combined heat and Power (CHP) generation, micro-turbines
and intelligent photovoltaic (PV) panels, the ability to balance load peaks and valleys is given. These
approaches require, however because of the distributed installations and small shift-able load
potential, an aggregation of multiple DER, which creates a common control, for example by means of
incentive systems and a sufficient amount of potential shift provides. Through concepts such as VPP,
microgrids and energy hubs, different components are combined using various networking concepts
into a logical, partly independent group (e.g. isolated networks). At this point, the seamless
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integration and reliable and near real-time connectivity within the households by a CEMS, which is
required for DER and DSM at the customers side, are key capabilities of reliable power distribution
grids.
The high-level CEMS system architecture is depicted in Figure Figure 91 consisting of the following
components:
6) Flexible and non-flexible load systems within the households (e.g. air conditioning units,
household appliance, etc.)
7) Decentralized power production / distributed energy resources (e.g. photovoltaic panels,
local CHP, micro wind turbines, etc.)
8) A communication gateway (control hub) providing connectivity to the in-house networks and
components and enabling remote access and data services to the WAN.
9) Electricity metering devices collecting electrical energy consumption in short term intervals
enabling variable time intervals and different tariff options.
10) An enhanced user feedback system, which provides the basic metering functionality and
additional services for indirect and direct DSM, e.g. the customers provide flexibilities by
enabling a flexible start time for their household appliances, like washing machines or dish
washers.
11) In order to aggregate a large number of customers, an external service provider collects and
manages the flexibilities, which are provided by the customers. This service can be covered
by energy utilities or external service providers.
All in-house components assume to be connected via a CEMS, which can be realized by a dedicated
wired or wireless home automation system (e.g. narrowband PLC, broadband PLC, BUS systems,
ZigBee, W-MBus, etc.) or a shared medium provided by the customers in-house networks (e.g.
wireless LAN, broadband PLC, etc.). At least one access technology (at least cellular networks), but
possible more communication means depending on the existing possibilities, e.g. power line, 3G or
fiber (if already installed in the household) and communication technologies as well as operators
may differ between households.
In the communication infrastructure some entities exists that performs the important role of a) data
aggregation from the various sources of large numbers of households and other buildings/sites that
extracts features usable by the prediction and control algorithms applied, b) power prediction based
on the aggregated information, as well as other information such as weather forecasts and finally c)
the control of the energy grid based on the predicted power need. All of this operates, as mentioned
in local environment and will need to be coordinated with the MV grid whereas communication on
the various levels also needs to happen here.
The control network is shown in Figure 91 and consist of the following domains:
12)Connected to the control hub within households via the communication hub
13)Connected to data aggregation, power prediction and control units within the low voltage
grid
In the context of SmartC2Net, the following CEMS scenarios with reference to [9-16] have been
identified. A detailed scenario structure with appropriate use cases is illustrated in Figure 93. It is to
be considered that, due to legal restrictions out of privacy concerns, it is possible that a direct
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connection between SM and EMG might not exist.
Scenario 1: Demand and generation flexibility for technical and commercial operations
This scenario is providing use cases on flexibility features as DER, active customers/active load and
flexibility use for markets, services or grid operation. The use cases direct load and generation
management, flexibility offerings as well as receiving consumption, price or environmental
information for further action by consumer or a local energy management system are contained in
this scenario.

Direct load and generation management
See Figure 110 and Figure 111
Signals and metrological information are provided to the home/building via an interface
called the Smart Grid Connection Point (SGCP). The following signals can be distinguished:
1. Direct - load / generation / storage management
2. Emergencies
The functions described below can be labelled as a “Direct load control” use case, following
the definition of Eurelectric, which is referenced in the Sustainable Processes workgroup’s
report.

Not included within this use case
Flexibility offerings are sent from flexibility providers to one or more (potential) users of
flexibility. These offerings are negotiated and if successful exercised by the acquiring party.
The offerings state the available flexibility in the dimensions of time, power/energy and
finance.

Receiving consumption, price or environmental information for further action by consumer
or a local energy management system
See Figure 112, Figure 113, Figure 114 and Figure 115
This use case describes how information regarding price and environmental aspects is sent
from upstream actors to CEMS and how information regarding energy consumption or
generation as well as smart device statuses are being sent back to the consumer and
upstream actors.
Scenario 2: Grid related use cases
Several use cases are describing existing functionalities, especially coming from power automation,
network operation and monitoring (SCADA). Those use cases are well known today, but have to be
adapted to the Smart Grid in order to realize spreading of intermittent power sources (generation or
storage) at any level of voltage.
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FP7-ICT-318023/ D1.1 ver 2
Grid related use cases in smartC2net are divided in sub use cases Voltage control and power flow
optimization VVO, Microgrid management, Monitoring the distribution grid, Fault Location,
Isolation and Restoration (FLIR) as well as Forecast. This use cases are driven by grid management
and control algorithms and are detailed in [18].
Scenario 3: Electric vehicle charging and low voltage grids
Charging of electrical vehicles in low voltage grids is challenging due to highly synchronized demand
patterns of charging as well as high loads. This use case covers the controlled charging of electrical
vehicles in a low voltage grid, taking into consideration the EV owner, a charging infrastructure
owner/provider as well as the DSO. Regarding the latter, the use case aims to utilize the high demand
flexibility of the charging process to balance grid and energy in the low voltage grid [19].
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FP7-ICT-318023/ D1.1 ver 2
General Remarks
-
Diagram of Use Case
Figure 91: Advanced Smart Meter Reading and Customer Energy Management System Scenario
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FP7-ICT-318023/ D1.1 ver 2
Meter Data
Management System
Customer Energy Management System (CEMS)
Home
automation
end device
Simple
external
consumer
display
Metering Data
Aggregator
Distribution Network
Operator
Related to EV Use Case
Private
Charging Spot
Energy Management
Gateway (EMG)
Local
Network
Access
Point
(LNAP)
Neighborhood
Network Access
Point (NNAP)
Head End
System
(HES)
Aggregator
Flexible Loads
Metering Operator
Use Case
Smart
Meter (SM)
Non-Flexible
Loads
Energy Service
Provider
Use Case
Automated Meter Reading (AMR)
Substation Level
Operator Level
Figure 92: Physical components of the use case and their locations in the Smart Grid setup
Page 187 of 244
FP7-ICT-318023/ D1.1 ver 2
Keys
Use Case Cluster
Use Case Cluster
Use Case
Reference to use case
document
ES.02. Manage supply
quality
ES.01. Tamper and
Fraud detection
ES.03. Monitoring
Collect AMI events
and status information
Actor A
[WGSP
Actor B]
Actor B
CI.01. Provide
Information to
consumer
Actor C
MM.01. Obtain meter
reading on demand
Actor D
[WGSP
Actor A]
<< extends >>
Customer
information provision
<< extends >>
AMR Use Cases
Measurement
MM.02. Obtain
scheduled meter
reading
MM.03. Set tariff
parameters
Demand and Generation
flexibility for technical and
commercial operations
CEMS Use Cases
Grid related REF:
Use Case Name:
and Island Mode
DG.01. Direct Load /
Generation
management
DG.02. HL-UC
Electric Vehicle REF:
Use Case Name:
Electrical Vehicle
Charging in Low Voltage
Grids
DG.03. HL-UC Receiving consumption,
price or environmental information for
further action by consumer or a local
energy management system
Figure 93: Detailed use case clustering structure
Page 188 of 244
FP7-ICT-318023/ D1.1 ver 2
Diagrams of AMR Use Case
The diagrams of AMR use case are structured in sub-processes billing, customer information
provision as well as collect AMI events and status information.
Diagrams of sub-process Measurement (MM)
Diagram of Use Case
MM.01. Obtain meter
reading on demand
<<includes>>
SU3. Read meter
Actor A
Actor B
Figure 94: MM.01 Obtain meter reading on demand (refer to [4])
Actor A
EMG
Smart Meter
1: Send (Meter read request)
2: Invoke SU3()
3: SU3 invoked()
4: Send (Requested reading)
Figure 95: Sequence diagram MM.01.01 - Obtain remote meter reading on demand (refer to [4])
Page 189 of 244
FP7-ICT-318023/ D1.1 ver 2
Actor A
Smart Meter
1: Send(Meter read request)
2: Send (Meter read)
Figure 96: Sequence diagram MM.01.02 - Obtain walk-by meter reading on demand (refer to [4])
MM.02. Obtain
scheduled meter reading
ActorA
<<extends>>
MM.02.01. Configure
reading schedule
<<includes>>
<<includes>>
SU1. Write
information
SU3. Read Meter
Figure 97: MM.02 Obtain scheduled meter reading (refer to [5])
Actor A
EMG
Smart meter
1: SU3 invoked()
2: Send (Meter read)()
Figure 98: Sequence diagram MM.02.01 - Obtain scheduled meter reading (refer to [5])
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FP7-ICT-318023/ D1.1 ver 2
Actor A
EMG
Smart Meter
1: Send (Reading schedule)
2: Invoke SU1()
sd optional
3: SU1 invoked()()
4: Send (Confirmation)
Figure 99: Sequence diagram MM.02.02 - Configure reading schedule (refer to [5])
MM.03. Set billing
parameters
<<includes>>
SU1. Write
information
Actor A
Actor B
Figure 100: MM.03 Set tariff parameters (refer to [6])
Actor A
EMG
Smart meter
Display
1: Send (Billing parameter)
2: Invoke SU1()
sd optional
3: Send(Notification)
sd optional
4: SU1 invoked()
5: Send(information)
Figure 101: Sequence diagram MM.03.01 - Set tariff parameter in the smart meter (refer to [6])
Page 191 of 244
FP7-ICT-318023/ D1.1 ver 2
Actor A
EMG
NNAP / LNAP
1: Send(Billing parameter)
2: Invoke SU1
sd optional
3: SU1 invoked
4: Send(confirmation)
Figure 102: Sequence diagram MM.03.02 - Set tariff parameter in the LNAP/NNAP(refer to [6])
Diagrams of sub-process customer information provision
Diagram of Use Case
CI.01. Provide
information to customer
Actor A
Actor C
Actor B
SU1. Write
information
Figure 103: CI.01. customer information provision (refer to [8])
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FP7-ICT-318023/ D1.1 ver 2
Actor A
EMG
Smart meter
1: Send(information message)
2: Invoke SU1()
sd optional
3: SU1 invoked()
Figure 104: Sequence diagram CI.01.01 - Send information to meter display (refer to [8])
Actor A
EMG
Smart meter
Smart meter
1: Send(information message)
2: Invoke SU1()
3: Send(Information message)
sd optional
4: SU1 invoked()
Figure 105: Sequence diagram CI.01.02 - Send information to simple external consumer display (refer to [8])
Smart meter
Display
1: Send(Actual meter reads / power quality and/or device status)
Figure 106: Sequence diagram CI.01.03 -– Smart Meter publishes information on simple external consumer
display (refer to [8])
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FP7-ICT-318023/ D1.1 ver 2
Diagrams of sub-process collect AMI events and status information
Diagram of Use Case
ES.02 Manage
supply quality
<<extends>>
ES.02.01 Configure power
quality parameters to be
monitored
<<extends>>
MM.01 Obtain meter
reading on demand
SU1. Write
information
<<extends>>
<<extends>>
MM.02 Obtain
scheduled meter reading
CI.01.01 Send to
information to meter display
SU3. Read meter
Actor C
Actor A
Figure 107: ES.02 - Manage supply quality (refer to [7])
Actor A
EMG
Smart Meter
1: Send(Power quality parameters)()
2: Invoke SU1()
sd optional
3: SU1 invoked()
4: Send (Confirmation)
Figure 108: Sequence diagram ES.02.01 - Configure power quality parameters to be monitored (ref. [7])
Smart Meter
Display
1: Send (Supply quality message)
Figure 109: Sequence diagram ES.02.02 - Smart meter sends information on power quality to display (refer to
[7])
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FP7-ICT-318023/ D1.1 ver 2
Diagrams of CEMS Use Case
The diagrams of CEMS Use case are structured in sub-processes grid related use cases as well as
demand and generation flexibility for technical and commercial operations.
Diagrams of sub-process demand and generation flexibility for technical and commercial
operations (DG)
Diagram of Use Case
Actor A
MDM
EMG
NNAP
Smart Metering Gateway
(LNAP)
CCM
Actor D
CEMS
Smart Appliance / Generators
Load Mgmt. Command
Load Mgmt. command
Announcement of load adjustment
Load management system
par
Start of load adjustment notification
Order of load adjustmend
Feedback status
Expected change in consumption
Expected change in consumption
par
End of load adjustment notification
End of load adjustment
Feedback status
End of load adjustment period + sending load curve recorded for this period
End of load adjustment period + sending load curve recorded for this period
Figure 110: DG.01.01 - Direct load / generation demand – appliance has end-decision about its load
adjustment (refer to [14])
Page 195 of 244
Display
FP7-ICT-318023/ D1.1 ver 2
Actor A
MDM
EMG
(LNAP)
NNAP
CCM
Actor D
CEMS
Load Mgmt. Command
Load Mgmt. command
par
Load adjustment notification
Start of load adjustmend period
Feedback status
par
End of load adjustment notification
End of load adjustment period
Confirmation that load has been adjusted
Feedback status
Confirmation that load has been adjusted
Figure 111: DG.01.02 - Direct load / generation demand - appliance has no control over its own load
adjustment (refer to [14])
Actor A
MDM
EMG
NNAP
(LNAP)
Actor D
CEMS
Display
Individual appliance consumption / generation information
par
Total and / or forecased house consumption / generation
Total and / or forcased house consumption / generation
Total and/or forecased house consumption / generation
Total and/or forecased house consumption/generation
Figure 112: Sequence diagram DG.03.01 - Information regarding power consumption / generation of
individual appliances (refer to [16])
Page 196 of 244
Display
FP7-ICT-318023/ D1.1 ver 2
Actor A
MDM
EMG
(LNAP)
NNAP
Actor D
Smart Meter Functionality
CEMS
Smart Appliance/Generators
Display
Total house consumption
Total house consumption
par
Total and / or forecased house consumption / generation
Total and / or forcased house consumption / generation
Total and/or forecased house consumption / generation
Figure 113: Sequence diagram DG.03.02 - Information regarding total power consumption (refer to [16])
Actor A
MDM
EMG
(LNAP)
NNAP
Actor D
CEMS
Display
Price and environmental information
par
Gateway
par
Confirmation
Confirmation
New price and environmental information
Confirmation
New price and environmental information
Confirmation reception new price and environmental information
Figure 114: Sequence diagram DG.03.03 - Price & environmental information (refer to [16])
CEMS
Display
Information on total consumption & subscribed power
Warning signal
Warning signal
Figure 115: Sequence diagram DG.03.04 - Warning signals based individual appliances consumption (refer to
[16])
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FP7-ICT-318023/ D1.1 ver 2
Stakeholders
Figures
Supplier
Consumer
Actor B
Metering End Device
Meter Operator
Metered Data Aggregator
Actor D
Actor C
External Consumer Display
Home Automation End Device
Actor A
Head End System (HES)
Meter Data Collector
Meter Data Management
Figure 116: External Actors (refer to [1])
Actors
Group Description
Actor Name
Actor Type
Actor Description
see Actor List
see Actor List
see Actor List
A
Summarized Actors (
Figure 116, refer to [1])
System
EXTERNAL ACTORS
MDA (belongs to Actor A)
MDMS / MDM (belongs to
Actor A)
Page 198 of 244
System
External actor interacting with the system
functions and components via the HES
Entity which offers services to aggregate
metering data by grid supply point on a
contractual basis.
NOTE: The contract is with a supplier. The
aggregate is of all a supplier's consumers
connected to a particular grid supply point.
The aggregate may include both metering
data and data estimated by reference to
standard load profiles
System for validating, storing, processing
Further information
FP7-ICT-318023/ D1.1 ver 2
MO (belongs to Actor B)
People/Company
C
Summarized Role (
Role
and analysing large quantities of meter
data.
External actor interacting directly with the
smart meter (Metering End Device).
End user of electricity, gas, water or heat.
NOTE: As the consumer can also generate
energy using a Distributed Energy Resource,
he is sometimes called the "Prosumer".
Meter Operator
Entity which offers services on a contractual
basis to provide, install, maintain, test,
certify and decommission physical metering
equipment related to a supply.
simple external consumer display.
Consumer/Prosumer
Summarized Role (
-
home automation end device.
Consumer/Prosumer
People/Company
Energy Service Provider: Organization
offering energy services to the consumer.
NOTE: an example consists of a role
responsible for creating awareness
regarding rational energy consumption.
They also provide the required knowledge
to the consumer allowing him to reduce his
energy consumption. Within this role he will
supply data / information to the consumer
through the meter.
Entity that offers contracts for supply of
energy to a consumer (the supply contract).
Within this role he will initiate DSM
activities
NOTE: In some countries referred to as
Retailer
External actor responsible for the
installation, operation, maintenance and
de-installation of the system components. It
may access, if properly identified and
authorized, those components either
directly, via local operation and
maintenance interfaces, or from a system
component from a higher hierarchical level
(e.g. meters may be accessed for
maintenance purposes via NNAPs or the
HES).
Meter Operator
Entity, which offers services on a
contractual basis to provide, install,
maintain, test, certify and decommission
physical metering equipment related to a
supply.
Actor responsible for evaluating the
conformity of the Metering End Device to
the requirements of Directive (2004/22/EC).
The smart appliance with integrated EM,
directly receiving data from the grid,
B
Consumer (belongs to Actor
B)
C)
D
D)
ESP (belongs to Actor D)
Summarized Actors (
-
Supplier
People/Company
E
Summarized Role (refer
to [1])
MO (belongs to Actor E)
People/Company
DNO (belongs to E)
Market surveyor (belongs to
Actor E)
People/Company
People/Company
Smart appliance / Generator
(external actor)
System
Page 199 of 244
FP7-ICT-318023/ D1.1 ver 2
through the SGCP. The appliance may
contain of be connected to a Plug in
electricity meters that measures individual
appliance consumption or output.
Since the smart appliance / generator is
outside the scope of the SGCG, it must be
seen as an external actor
INTERNAL ACTORS (refer to [1])
Head End System (HES)
System
NNAP
System
LNAP
System
Smart Meter (SM)
System
Simple external consumer
display
System
Home automation end
device
System
CEMS (Customer Energy
Management System)
System
Energy Management
Gateway
System
Central Data System collecting data via the
AMI of various meters in its service area. It
communicates via a WAN directly to the
meters and/or to the NNAP or LNAP.
The Neighbourhood Network Access Point
is a functional entity that provides access to
one or more LNAP’s, metering end devices,
displays and home automation end devices
connected to the neighbourhood network
(NN). It may allow data exchange between
different functional entities connected to
the same NN.
The Local Network Access Point is a
functional entity that provides access to
one or more metering end devices, displays
and home automation end devices
connected to the local network (LN). It may
allow data exchange between different
functional entities connected to the same
LN.
Meter with additional functionalities one of
which is data communication.
Display providing accurate information on
consumption, tariffs and so on in order to
increase consumer awareness.
Device providing additional functionalities
enabling consumers to interact with their
own environment.
CEMS is any device/software or group of
them installed in the customer facilities
which allows the visualization of
metrological information, price and warning
signals by the customer and has the
capability to take action automatically or
after approval by customer on any home
appliances.
Equipment sending and receiving smart grid
related information and commands
between actor A and the CEMS, letting the
CEMS decide how to process the events.
The communication is often achieved
through an internet connection of through
a wireless connection
Page 200 of 244
Use Case Conditions
Triggering Event
Pre-conditions
Assumption
FP7-ICT-318023/ D1.1 ver 2
No triggering event
Access ICT Networks
Households
No triggering event
Households are
equipped with
control and
communication hubs
Houses are equipped
with smart meters
Primary network is cellular networks
As a minimum the household power
consumption/production is measured
No.
References Type
Reference
1
Report
2
Report
3
CEN/CLC/ETSI/TR
50572:2011 E
4
Report
5
Report
6
Report
7
Report
8
Report
9
Report
Smart Meters Coordination Group Smart Metering Use
Cases
CEN-CENELEC-ETSI
Smart Grid
Coordination Group
– Sustainable
Processes
Functional reference
architecture for
communications in
smart metering
systems
BI.01. Obtain meter
reading on demand
BI.02. Obtain
scheduled meter
reading
BI.03. Set billing
parameters
MSQ.01. Manage
supply quality
CI.01. Provide
information to
consumer
WGSP-0301 Short
term load and
generation
forecasting
10
Report
11
Report
12
Report
13
Report
14
Report
WGSP-0200 Voltage
control and power
flows optimization
VVO
WGSP-0400
Microgrid
management
WGSP-0600
Monitoring the
distribution grid
WGSP-0901
Congestion
management by
direct control
GENERIC USE CASE
WGSP-2120
Managing energy
Page 201 of 244
References
Status
Impact on
Use Case
Originator/Organization
Link
final
All AMR use
cases
Smart Meters
Coordination Group
-
final
ES.01, ES.03
CEN-CENELEC-ETSI Smart
Grid Coordination Group
-
final
All CEMS use
cases
CEN/CLC/ETSI/
-
draft
MM.01
CEN/CLC/ETSI/
-
draft
MM.02
CEN/CLC/ETSI/
-
draft
MM.03
CEN/CLC/ETSI/
-
draft
ES.02
CEN/CLC/ETSI/
-
draft
CI.01
CEN/CLC/ETSI
-
draft
GR.01
CEN/CLC/ETSI/
SM-CG
Use case
repository
draft
GR.02
CEN/CLC/ETSI/
SM-CG
Use case
repository
draft
GR.03
CEN/CLC/ETSI/
draft
GR.04
CEN/CLC/ETSI/
draft
GR.05
CEN/CLC/ETSI/
SM-CG
Use case
repository
SM-CG
Use case
repository
SM-CG
Use case
repository
draft
DG.01
CEN/CLC/ETSI/
Link
FP7-ICT-318023/ D1.1 ver 2
15
Report
16
Report
17
18
EU mandate
SmartC2Net Use case
description
19
SmartC2Net Use case
description
20
Research Paper
consumption or
generation with
smart appliances
WGSP-2128 - High
level use case Flexibility offerings
GENERIC USE CASE
WGSP-2110
Receiving
metrological, price
or environmental
information for
further action by
consumer or a local
energy management
system
M/441
Sub-use Case 2.3:
External Generation
Site
USE CASE NAME:
Electrical Vehicle
Charging in
Low Voltage Grids
Basic concepts and
taxonomy of
dependable and
secure computing
draft
DG.02
CEN/CLC/ETSI/
draft
DG.03
CEN/CLC/ETSI/
SM-CQ
Use case
repository
Link
draft
SmartC2Net consortium
-
draft
SmartC2Net consortium
-
Avizienis, A. ; Vytautas
Magnus Univ., Kaunas,
Lithuania ; Laprie, J.-C. ;
Randell, B. ; Landwehr, C.
Link
Published
-
Electric vehicle charging within the households is covered by the EV UC and information exchange is required. Interfaces to the control
algorithms of the MW UC needs to be specified.
Level of Depth
HL-UC
Prioritization
Mandatory
Smart metering has a generic relation to all European countries due to the mandate M/441 of the EU to get 80% smart metering
deployments until 2020. The control aspect needs to be aligned to the European mandate M/490, but depends on the actual regional and
national deployed system architecture and needs to be evaluated for all different scenarios.
View
Technical
Scenario Conditions
No.
Scenario
Primary Actor
Triggering Event
Pre-Condition
Actor A
Scenario AMR
Measurement (MM), (refer to [4-6])
Actor A decides he wants a
The metering and
particular meter read or
communications are
meter reads.
installed, operating.
Post-Condition
Name
PS1
MM.01.01 Obtain
remote
Page 202 of 244
Success
Actor A has the read he requested.
FP7-ICT-318023/ D1.1 ver 2
Scenario Conditions
No.
Scenario
Primary Actor
Triggering Event
Pre-Condition
Post-Condition
Name
meter
reading on
demand
PS2
Minimal Guarantee
The metering system is operating as
before the request.
Actor A is aware of the reason for not
receiving the read.
MM.01.02
- Obtain
walk-by
meter
reading on
demand
Actor B
MM.02.01 Obtain
scheduled
meter
reading
Actor A
PS4
MM.02.02 Configure
reading
schedule
Actor A
PS5
MM.03.01
– Set tariff
parameter
in the
smart
meter
PS3
PS6
M.03.02 –
Set tariff
parameter
Page 203 of 244
Actor B decides he wants a
particular meter read or
meter reads.
The timer triggers a meter
reading.
Actor A needs readings from
the meter on a regular basis
Actor A wants to set a billing
parameter that is not yet
known by the Smart Meter.
Success
Actor B has the read he requested.
There is a valid
contract between
actor A and
consumer.
Communication
with the meter is
established.
A reading schedule
and data collection
scheme (e.g. load
profile) are
established and
activated in the
system.
Communication
between all actors
can be established.
Communication
between all actors
can be established.
Actor A
Actor A
Actor A wants to set a billing
parameter that is not yet
known by the LNAP/NNAP.
Communication
between all actors
can be established.
Minimal Guarantee
before the request.
Actor B is aware of a reason for not
receiving the read.
Success:
Actor A has received all required metering
data.
Minimal Guarantee:
Actor A has the reason explaining why he
did not receive the expected information
Success:
Reading schedule is established in the
system.
Optionally, reading schedule has been
activated.
Optionally, confirmation is received by
Actor A.
Minimal Guarantee
before the request.
Actor A has the reason explaining why the
request was or will not be completed.
Success
The billing parameter is received by the
Smart Meter.
Optionally, billing parameter has been
activated.
Optionally, the change of parameter is
shown on the display
Actor A.
Minimal Guarantee:
Actor A has a reason explaining why the
request was or will not be completed
Success
The billing parameter is received by the
LNAP/NNAP.
FP7-ICT-318023/ D1.1 ver 2
Scenario Conditions
No.
Scenario
Primary Actor
Triggering Event
Pre-Condition
Post-Condition
Name
in the
LNAP/NNA
P
Optionally, billing parameter has been
activated.
Actor A.
Minimal Guarantee:
Actor A has a reason explaining why the
request was or will not be completed
PS7
PS8
PS9
CI.01.01 Send
information
to meter
display
Actor A
CI.01.02 Send
information
to simple
external
consumer
display
Actor A
CI.01.03 Smart
Meter
publishes
information
on simple
external
consumer
display
Timer
PS1
0
ES.02.01 –
Configure
power
quality
parameters
to be
monitored
Timer
PS1
1
ES.02.02 –
Smart
meter
sends
information
on power
quality to
display
Smart Meter
Customer information provision (CI), (refer to [8])
Actor A wants to show
Communication
information on the meter
between all actors
display.
can be established.
Actor A wants to show
information on a simple
external consumer display.
Timer triggers to smart
meter to display
information on actual meter
reads / power quality
and/or device status on the
simple external consumer
display
Communication
between all actors
can be established.
Smart meter has a
schedule indicating
at which times
which information
needs to be pushed
to the simple
external consumer
display
Minimal Guarantee
The message is not displayed
Success:
The information is received by a simple
Optionally, actor A received a
confirmation.
Minimal Guarantee
Success:
The information is received by a simple
Minimal Guarantee
Communication
between all actors
can be established.
Collect AMI events and status information (ES) (refer to [7])
Actor A wants to configure
Communication
Success:
power quality parameters
between all actors
Power quality parameters are received by
to be monitored
can be established.
the Smart Meter.
There is a valid
Actor A
contract between
Actor A and the
Minimal Guarantee:
consumer.
Actor A is aware of the reason for failure
Smart Meter is triggered to
Information about
Success:
display information about
supply quality is
Information is received by a display
supply quality
available in Smart
Meter.
Minimal Guarantee:
Information is not received by display
Communication
between all actors
can be established.
Smart Meter has an
active schedule
Page 204 of 244
Success:
The information is received by the meter
display.
Optionally, actor A received confirmation.
FP7-ICT-318023/ D1.1 ver 2
Scenario Conditions
No.
Scenario
Primary Actor
Triggering Event
Pre-Condition
Post-Condition
Name
PS1
2
PS1
3
PS1
4
indicating when to
send messages to
the display.
Scenario CEMS
Demand and Generation flexibility for technical and commercial operations (DG) (refer to 14, 16]
DG.01 –
Actor A or
Actor A or Actor B wants to
Communication
The Smart Appliance / generator
appliance
Actor B
send a load management
connection between executed the load management command
has endcommand to the market
all actors is
and Actor A or Actor B received the
decision
established
feedback with a load curve recorded for
about its
this period
load
The consumer
adjustment
configured the
CEMS and/or the
participating devices
(appliances and
generators). The
consumer
configured the
device settings and
thresholds
DG.01.02 –
appliance
has no
control
over its
own load
adjustment
DG.03.01 –
Information
regarding
power
consumptio
n/
generation
of
Page 205 of 244
Actor A or
Actor B
Actor A or Actor B wants to
send a load management
command to the market
Information on total
consumption or
consumption per
appliance is
available in the
CEMS
Communication
between all actors
can be established
The appliance executed the load
management command and Actor A or
Actor B received the feedback
The consumer
configured the
CEMS and/or the
participating devices
(appliances and
generators). The
consumer
configured the
device settings and
thresholds
Smart
appliance /
Generator
New consumption /
generation information is
available in the smart
appliance / generator
Information on total
consumption or
consumption per
appliance is
available in the
CEMS
Communication
connection between
all actors is
established
(forecasted) consumption / generation is
received by actor A and/or actor B and/or
display
FP7-ICT-318023/ D1.1 ver 2
Scenario Conditions
No.
Scenario
Primary Actor
Triggering Event
Pre-Condition
Post-Condition
Smart Meter
New
consumption/generation
information is available in
the Smart Meter
Communication
connection between
all actors is
established
(forecasted) consumption/generation
information is received by actor A and/or
or Actor B and/or display
Actor A or
actor B
New price and
environmental information
is available in Actor A or
Actor B
Communication
connection between
all actors is
established
Price and environmental information is
received by Smart Appliances
Smart
appliance
The CEMS received
information on a new
operation to be executed
The subscribed
power limits are
made known to the
smart appliance
Warning signal is received by display
and/or smart appliances
Name
PS1
5
PS1
6
PS1
7
individual
appliances
DG.03.02 –
Information
regarding
total power
consumptio
n
DG.03.03 –
Price &
environme
ntal
information
DG.03.04 –
Warning
signals
based
individual
appliances
Scenario Name :
Reference:
Scenario AMR
Measurement (MM)
MM.01.01 - Obtain remote meter reading on demand
Ref. [4], subchapter 3.1.1
MM.01.02 - Obtain walk-by meter reading on demand
MM.02.01 - Obtain scheduled meter reading
MM.02.02 - Configure reading schedule
MM.03.01 - Set tariff parameter in the smart meter
MM.03.02 – Set tariff parameter in the LNAP/NNAP
Customer information provision (CI)
CI.01.01 – Send information to meter display
CI.01.02 - Send information to simple external consumer
display
CI.01.03 – Smart Meter publishes information on simple
external consumer display
Collect AMI events and status information (ES)
ES.02.01 – Configure power quality parameters to be
monitored
ES.02.02 – Smart meter sends information on power quality to
display
Scenario CEMS
Demand and Generation flexibility for technical and commercial operations (DG)
DG.01.01 – appliance has end-decision about its load
Ref. [14], subchapter 2.1
adjustment
DG.01.02 – appliance has no control over its own load
adjustment
DG.03.01 – Information regarding power consumption /
generation of individual appliances
DG.03.02 - Information regarding total power consumption
DG.03.03 - Price & environmental information
DG.03.04 - Warning signals based individual appliances
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consumption
Scenario AMR
Measurement (MM)
Reference:
Scenario Name :
MM.01.01 - The metering system finds the request to be
invalid
MM.01.01 - The metering system finds that the role fulfilled by Ref. [4], subchapter 3.3
actor A does not have the necessary access rights
MM.02.01 - System finds the data nor plausible or missing
Customer information provision (CI)
CI.01 Provide information to consumer
Collect AMI events and status information (ES)
ES.02 Manage supply quality
Scenario CEMS
Demand and Generation flexibility for technical and commercial operations (DG)
DG.01 Direct load / generation management
Ref. [14]
DG.02 HL-UC Flexibility offerings
Ref. [16]
Fault/threat analysis/scenarios
In this section the possible failures in the CEMS/AMR UC are considered. In particular, the focus is on
security threats that can hamper the CEMS main functionalities. Indeed, the CEMS may operate in a
very hostile environment since it can be connected to home automation devices and to the EMG by
means of shared network (e.g., the home WiFi, office LAN). The use of already deployed IP network is
extremely appealing since the cost for cabling and network interfaces is rapidly. However, IP-based
networks, when not well secured are subject to cyber security attacks.
The shift towards such a scenario may expose the communication and the CEMS critical components,
to attacks. For instance, an attacker can be:
a hacker with no intent to cause damage and who is satisfied by the penetration of systems
accessible through the Internet;
a criminal (e.g., disgruntled employee of the Energy Supplier or Energy Service Provider) who wants
to cause financial loss to the customer or to the energy service provider;
a customer with malicious objectives, e.g., to tamper the system with fraud purposes.
The attack can be executed either from the Internet or from a device connected to the HAN which
has been previously tampered, such as a personal computer or the LNAP, and may have special
information or authorizations (e.g., EMG login credentials, remote management of home automation
devices).
All in-house components are assumed to be connected to the CEMS. Among the functionalities of the
CEMS depicted in the use case diagrams (see Figures 20-25), the most critical operations that must
be secured are: i) direct load/generation management (DG.01.01) and ii) communication of power
consumption information (DG.03.01). The considered misuse cases are depicted in Figure 21.
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Figure 117:Mis-use diagrams for the considered CEMS functionalities
The alteration or missed delivery of load adjustment commands that can be performed by means of
active attacks, i.e., the attacker tries to alter system resources or affect their operations. This may
compromise the capability of the customer to use the smart appliances or even the execution of
emergency procedures Figure 104 When the attacker is able to compromise a limited number of
CEMS the impact of the attack is low; however, when the attack is coordinated and several CEMS
systems are compromised (e.g., more than 100) or when some critical CEMS are violated (e.g., police
and fire departments systems) the impact of the attack can range from moderate to high (e.g., when
the CEMS systems of a very extended area, such as a city, are all compromised in a limited interval of
time). In the following we refer to this misbehaviour as incorrect direct load generation management,
mis-use case DE.01 (see Figure 21).
The access to power consumption/generation data shall also be secured against non-authorized
accesses. In other words customer power-related data shall be protected against passive attacks, i.e.,
attempts to learn or make us of information from a system without affecting its resources. As a
matter of fact, this is mandatory according to privacy law in some countries of the European
Community, such as Germany. Moreover, sophisticated burglaries could be architected when such
information is not secured. For example, thieves can exploit power consumption data to infer when
persons are not in the buildings and then plan physical penetrations. The impact of such an attack
can be classified as low. In the following we refer to this misbehaviour as disclosure of power
consumption information, DE.02 (see Figure 21).
For the aforementioned motivation, the network security requirements that shall be guaranteed in
CEMS systems are confidentiality, integrity and availability. In particular, for the communication of
direct load/generation management operations (i.e., load and emergency commands) integrity and
availability shall be guaranteed; while confidentiality, integrity and availability shall be assured when
power consumption data are exchanged.
According to the CEMS logical architecture described in Section 1 the most critical components
involved in the aforementioned operations are the EMG and the CEMS. Indeed, these can be
connected to the home WiFi and the likelihood to be exposed to malicious attacks is higher with the
respect to the components that are in dedicated network and when not protected by firewall or
other security mechanisms (e.g., encryption).
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Incorrect Direct load and generation management (DE.01)
The considered active attacks that compromise the integrity and/or the availability of EMG/CEMS
and lead to incorrect direct load generation management, are:
 Man In the Middle (MIM) – an opponent captures messages exchanged between the EMG
and the CEMS. It can partially alter the content of the messages, or the messages are delayed
or reordered to produce an unauthorized effect.
 Masquerade – an opponent sends fake messages the EMG pretending to be a different
entity.
 Denial of Service (DoS) – the attacker floods anomalous messages to the EMG. It prevents or
inhibits the normal use or management of the communication facilities and/or the
components.
These attacks have been selected since they are usually performed by exploiting the most commonly
computer system and network vulnerabilities (e.g., sensitive data exposure, insecure object
references, broken authentication and session management, security misconfiguration). MIM and
Masquerade attacks can violate both integrity and availability; while, DoS violates only availability.
Tables Scenario D.01.01-D.01.03 detail the considered active attack scenarios. It is worth noting that
just one interaction is considered for the mis-use cases DG.01.01 and DG.03.01; in particular, it is
assumed that the Actor D starts the communication. However, a similar analysis can be applied when
Actor A initiates the communication.
The step by step description of the MIM attack is also explained for the sake of clarity. As for other
attacks (i.e., masquerade and DoS) the explanations can be extracted from the Description of
Process/Activity field.
Scenario DE.01.01
Scenario Name:
Step
Event
No.
MIM
Name of
Process /
Activity
1
2
3
Attacker
captures
a
message
that
wants to
alter
Attacker
replies an
altered
load
message
Attacker
captures
the reply
to the
previousl
y altered
message
Page 209 of 244
Description of
Process/Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
MIM – load
command
interceptio
n
The attacker
intercepts and alters
a load adjustment
command sent by
the EMG
Load
Manage
ment
EMG
Attacker
Load
management
command
MIM –
sending
altered
load
command
MIM –
interceptin
g and
altering
expected
change
message
The attacker
modifies the
message
intercepted at step
1 and then sends it
The attacker
intercepts and alters
the expected
change message
(i.e. the reply to the
load adjustment
command )
Load
Manage
ment
Attacker
CEMS
Altered load
management
command
Expected
change
CEMS
Attacker
Expected
change
message
Technical
Requirements RID
FP7-ICT-318023/ D1.1 ver 2
4
Attacker
replies an
altered
expected
change
message
MIM –
sending
altered
expected
change
message
The attacker sends
the message altered
at step 3
Expected
change
Attacker
EMG
Altered
expected
change
message
Figure 118 Mis-sequence diagram for the MIM attack
The MIM attack assumes an adversary can (i) observe messages exchanged, (ii) intercept messages
and (iii) reply messages with altered content (e.g., a load adjustment command sent by the EMG).
The attack takes place when the adversary intercepts the load adjustment command sent by the
EMG. Then, the attacker modifies the message previously intercepted (step 2 in Table Scenario
DE.01.01) and sends it to the CEMS. The CEMS is not aware of the adversary modification and takes
the load adjustment command as appropriate and reply to the message. Hence, the attacker
intercepts and alters the expected change message sent by the CEMS (i.e. the reply to the load
adjustment command) and finally sends the altered message to the EMG. In this scenario, it is
assumed that the CEMS sends the response message to the EMG. However, the attacker might also
be able to redirect all messages sent by the CEMS to himself, e.g., by means of DNS tempering.
Scenario DE.01.02
Scenario
Name:
Masquerade
Step
No.
Event
Name of
Process /
Activity
Description of
Process /
Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
1
Attacker
sends a
fake
message
Masquerade –
sending fake
load
adjustment
The attacker
pretending to be
an authorized
entity (e.g.,
Load
Management
Attacker
EMG
Fake load
management
command
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Technical
Requirements RID
FP7-ICT-318023/ D1.1 ver 2
command
2
The EMG
receives
the load
adjustment
command
EMG – sending
load
management
command
3
CEMS
receives
the load
managem
ent
command
from
EMG
CEMS
receives
the load
managem
ent
command
from
EMG
CEMS – sending
the load
management
command
Smart
Appliance
s/
generator
s receive
the order
of load
adjustme
nt
CEMS
receives
feedback
from
smart
appliance
s/
generator
s
EMG
receives
the
change in
consumpt
ion from
CEMS
Smart
Appliances /
generators –
sending
adjustment
feedback
4
5
6
7
energy service
provider) sends a
fake load
adjustment
command
The EMG believes
the message
received at step 1
was transmitted
by an authorized
entity and it
forwards the load
management to
CEMS
CEMS sends the
start of load
management
notification to
Display
Load
Management
EMG
CEMS
Altered load
management
command
Visualizat
ion of
load
management
CEMS
Display
Load
management
command
CEMS - decides
which Smart
Appliances needs
to be adjusted
and sends an
order of load
adjustment to the
Smart Appliances
/ generators
The Smart
Appliances /
generators decide
to switch on/off
based on the
consumer’s
settings and send
feedback to CEMS
Load
Manage
ment
CEMS
Smart
Appliances /
generators
Order of load
adjustment
Load
Manage
ment
Smart
Appliances /
generators
CEMS
Load
adjustment
feedback
CEMS – sending
change
consumption
CEMS informs
EMG on which
change in
consumption to
expect.
Load
Manage
ment
CEMS
EMG
Change in
consumption
EMG – sending
change
consumption
EMG forwards the
change in
consumption to
what it believes is
the authorized
entity
Load
Manage
ment
EMG
Attacker
Change in
consumption
CEMS – sending
load
adjustment
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FP7-ICT-318023/ D1.1 ver 2
Figure 119: Mis-sequence diagram for the Masquerade attack
Scenario DE.01.03
Scenario Name:
Step
No.
Event
1
Attacker
replies an
altered
load
message
Attacker
replies an
altered
load
message
Actor D
sends an
emergency
load
adjustment
command
N
N+1
Page 212 of 244
DoS
Name of
Process /
Activity
DoS – sending
anomalous
message
DoS – sending
anomalous
message
Impossibility
to receive the
emergency
load management
procedure
Description of
Process /
Activity
Service
Information
Producer
Information
Receiver
Information
Exchanged
The attacker
sends an
anomalous
message to the
EMG
The attacker
sends an
anomalous
message to the
EMG
The EMG is
overloaded due
anomalous
messages
received by the
attacker
-
Attacker
EMG
Anomalous
management
command
-
Attacker
EMG
Anomalous
management
command
Emergency
load
management
Actor D
-
Emergency
load
management
command
Technical
Requirements R-ID
FP7-ICT-318023/ D1.1 ver 2
Figure 120 Mis-sequence diagram for the DoS attack
Disclosure of power consumption information (DE.02)
In this section the focus is on passive attacks that compromise the confidentiality of power
consumption information exchanged between the EMG and the smart appliances. As for the active
attacks that compromise the integrity and availability, similar analyses performed for the mis-use
case DE.01 also apply for the power consumption communication.
The considered passive attacks that compromise confidentiality are:
 Release of message content: the opponent tries to eavesdrop transmissions;
 Traffic analysis: the opponent observes the pattern of the messages to discover the location
and the identity of the parties involved in the transmissions, and the frequencies and the
length of exchanged messages.
Scenario DE.02.01
Scenario Name:
Step Event
Release of message content
Name of
Description of
Process /
Process /
Activity
Activity
1
SA/Gen –
sending new
powerrelated
information
No.
2
New
consumption
/ generation
information is
available for
the SA/
generator
CEMS
received
Page 213 of 244
CEMS –
sending new
Smart appliance
/ generator
sends
information
regarding
consumption to
the CEMS
The CEMS
aggregates
Service
Information
Producer
Information
Receiver
Information
Exchanged
SA Power
consumption
/ generation
information
SA /
generator
CEMS
Individual
appliance
consumption
/ generation
House power
consumption
CEMS
Display
Total and/or
forecasted
Technical
Requirements RID
FP7-ICT-318023/ D1.1 ver 2
consumption
/ generation
information
per individual
appliance
house powerrelated
information
3
CEMS
received
consumption
/ generation
information
per individual
appliance
CEMS –
sending new
house powerrelated
information
4
The attacker
intercepts the
message
Attacker –
reading
house powerrelated
information
5
EMG received
(forecasted)
consumption
/ generation
EMG –
sending new
house powerrelated
information
and/or
forecasts total
consumption
and sends this
information to
the display
The CEMS
aggregates
and/or
forecasts total
consumption
and sends this
information to
the EMG
The attacker
intercepts the
message and
reads the
content about
power
consumption/
generation
EMG forwards
information to
Actor D
/ generation
information
house
consumption
/ generation
House power
consumption
/ generation
information
CEMS
EMG
Total and/or
forecasted
house
consumption
/ generation
House power
consumption
/ generation
information
SA
/generator
Attacker
Total and/or
forecasted
house
consumption
/ generation
House power
consumption
/ generation
information
EMG
Actor D
Total and/or
forecasted
house
consumption
/ generation
Figure 121: Mis-sequence diagram for the Disclosure of message attack
Table Scenario DE.02.01 details the disclosure of message content scenario. When the smart
appliance / generator sends information regarding consumption to the CEMS, the CEMS aggregates
and/or forecasts total consumption and sends this information to the display and to the EMG. The
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FP7-ICT-318023/ D1.1 ver 2
attacker may intercept the message and if no cryptography method is used he/she reads the content
about power consumption/ generation.
As for the traffic analysis attack the only differences with respect the attack depicted in Figure 29
(i.e., the scenario DE.02.01) is that we are assuming that the adversary cannot understand the
message. Hence, the opponent needs to intercept several messages in order to observe the
communication pattern and discover relevant information (e.g., location and the identity of the
parties involved in the transmissions).
Name of Information
Exchanged
Metering – Metering Values
(periodically)
Metering – Metering Values
(aggregated)
Metering – Metering Values (Billing)
Metering – Parameter
Sub Metering – Metering Values
(periodically)
Sub Metering – Parameter
Control – Switching Command
Control – Status Information
Control – Parameter
Term
Definition
AC
Air Conditioning Unit
AMI
Advanced Monitoring Infrastructure
AMR
Automated Meter Reading
Cellular Network
Cellular Network
CEMS
Customer Energy Management System
CHP
Local CHP
CI
Customer Information
CLS
Controllable Load System
DER
DG
Distributed Generation
DNO
DoS
Denial of Service
DSM
Demand Side Management
ES
Events and Status
ESP
FLIR
Fault Location, Isolation and Restoration
HAN
Home Area Network
EMG
HES
Head End System
ICT Network
Communication Network
LNAP
Local Network Access Point
MDA
MDMS
MIM
Man In the Middle
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MM
Measurement
MO
Meter Operator
NAN
Neighbourhood Area Network
NNAP
Neighbourhood Network Access Point
Power Grid
Power Grid
RES
renewable energy sources
SM
Smart Metering
SSM
Supply Side Management
UI
User Interface
WAN
Wide Area Network
Communication Hub
Control Hub
Household Appliance
Power Predictor
Control Entity
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11 Annex C - Table of Requirements
This annex contains the list of Requirements with the mapping on the project WP where are addressed.
Considering the priority of the Requirements these are marked as follows:
Now (the requirement is taken into serious consideration inside the project)
Wish (the requirement is considered desirable but not yet scheduled in the project
activities)
Future (to be considered at some point in time)
11.1 Requirements for Medium Voltage Control Use Case
Requirement
ID
Title
Description
WP2
WP3
WP4
WP5
x
x
x
x
x
x
System Level Requirements
Architectural
REQ_001
Number of primary
substation per center
REQ_002
Grid topology
REQ_003
Hosting capacity
Communication
Page 217 of 244
Each center controls <min,max> primary
substations.Min, max values depend on the specific
topology of the telecontrol grid. In the scenario
addressed in SmartC2Net Min=20, Max = 100, Avg=60
Per each substation includes all the topological
parameters, e.g. number of HV/MV transformers (i.e.
n=2), number of MV lines(i.e. n=12), number of DER per
MV line (i.e.n=10), number of MV loads per MV line(i.e.
n=60/100), number of Secondary Substations per MV
lines(i.e. n=40/100)
<0,15>MW generated by DERs connected to the MV
lines of a primary substation
WP6
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
REQ_004
DER network availability
x
REQ_005
Compliance with standards
Any DER communication link should be available 8755
hs / year
The VC communications will be compliant with
standard protocols, if available
The communication infrastructure for control
operations should be available with a value of at least
99.999%(*) (Center -Substation communication) and
99.95 (DER- Substation communication)
(*) This very restrictive requirement is meant to
highlight that the availability needs to be near 100% on
each time instant
operations should use redundant heterogeneous
communication links as backup solutions to fault
tolerance
x
x
x
x
Dependability
REQ_006
Control infrastructure
reliability and availability
REQ_007
Security
REQ_008
redundancy
security
REQ_009
ICT maintenance
REQ_010
ICT maintenance logging
operations should guarantee protection against
intentional threats
Remote ICT maintenance activity to substation devices
does not adversely affect the VC operation
Remote ICT maintenance actions to substation devices
are logged
Use Case Level Requirements
Communication
Page 218 of 244
WP2
WP3
x
WP4
WP5
WP6
x
x
x
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
REQ_011
DER network heterogeneity
REQ_012
Substation-DER data
communication
REQ_013
Centre-Substation data
communication
REQ_014
Frequency of radio-based
substation-DER
communications
Centre-Substation
transmission time
Substation-DER
transmission time
Due to differences in the geographical coverage of
communication technologies the VC shall work with
heterogeneous DER networks (e.g., wired, wireless)
The Substation - DER communication main measures
are: bandwidth (i.e. 10 - 56 Kbps), data rate (i.e.
measurements every 2 seconds)
The Center - Substation main measures are: bandwidth
(i.e. 10 kbps), data rate (i.e. generation forecast update
every 12 hours)
frequency band, i.e. in Europe LTE allowed frequencies
are 800, 900, 1800, 2600 MHz and band numbers are 3,
7, 20
end-to-end transmission delay (i.e. 20 ms-2 sec)
REQ_015
REQ_016
Functional
REQ_017
REQ_018
Control loop
Time out of voltage bound
violation
REQ_019
Voltage deviation
Performance (Quality of Service)
Page 219 of 244
end-to-end transmission delay (i.e. 20 ms-15 sec)
WP2
WP3
WP4
WP5
x
WP6
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
The control loop is triggered by critical events (e.g.
under/over voltage event, TSO request, grid topology
change). In absence of criticalities, the VC function is
executed on a periodic base (e.g. every 15 minutes) for
optimization purposes.
<n> unit of time allowed to be out of voltage ranges
(i.e. max frequency n= 0.1 sec 50.3 Hz (restrictive
range), n=1.0 sec 51.5 Hz(permissive range). Min
frequency n=0.1 sec 49.7 Hz (restrictive range), n=4.0
sec 47.5 Hz (permissive range))
x
+/- 10% Vn
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
WP2
REQ_020
REQ_022
OLTC Actuation Time
REQ_023
Inverter Actuation Time
REQ_024
Synchronisation Time
The data values on the central operator interface are
refreshed every 2 seconds
The response time of the VC closed control loop, from
the command issue to the end of the set point
actuation, including the transmission time and the
actuation time. It depends on actuation time constants
of OLTC and DER power electronics. It is of the order of
seconds
The time taken by OLTC for actuating a set point is 3
seconds
The time taken by the inverter for actuating a set point
is 1-2 seconds
The substation and DER controllers provide
functionality to synchronise their internal clock
x
REQ_021
Refresh Time of the DMS
Operator HMI
Response Time
WP3
WP4
WP5
WP6
x
x
x
x
x
x
x
Standard/Regulation
REQ_025
DER power wrt grid voltage
Page 220 of 244
Norm CEI 0-16
P < 0.1 MW: plants are connected to the LV grids
0.1 MW < P < 0.2 MW: plants may be connected either
to the LV or to the MV grids
0.2 MW < P < 3 (6 in case of generation) MW: plants are
connected to the MV grids
3 (6 in case of generation) MW < P < 10 MW: plants
may be connected either to the MV or to the HV grids
10 MW < P < 100 MW: load plants are connected to the
HV grids
10 MW < P < 200 MW: generation plants are connected
to the HV grids
x
x
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
REQ_026
DER communication
systems
Norm CEI 0-16
In order to allow the evolution of distribution grids
towards smart grids, it is necessary that all active
customers are endowed with a communication system
allowing the (real time) data exchange with the DSO.
This will allow the DSO to implement optimization
logics and to send all customers the signals
implementing the actions (e.g. disconnection) needed
to guarantee the security of the whole power system.
WP2
WP3
WP4
x
WP5
WP6
x
Component Level Requirements
Architectural
REQ_027
Substation Network
Integrity
Communication
REQ_028
Ordered data streams
REQ_029
REQ_030
REQ_031
REQ_032
Functional
REQ_033
Load Forecast Transmission
Rate
Generation Forecast
Transmission Rate
Cost Transmission Rate
Range of substation-DER
communications
Generation Forecast Time
Horizon
Page 221 of 244
In order to support the operation integrity of substation
systems the communication interfaces in the substation
devices have to be limited to essential functions
x
The VC algorithm requires the undisturbed execution of
acquisition and actuation sequences based on orders
flows of status, events and commands
Load profiles are transmitted every 12 hours
x
x
x
Generation forecasts are transmitted every 12 hours
x
x
Cost data are transmitted every 1 hour
The DER-substation distance is within the range of the
MV line length, in the order of 5 Km
x
x
x
x
Active power production plans are given for 36 hours
x
x
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
REQ_034
Generation Forecast Time
Resolution
Active power production plans are given with resolution
of 1 hours
x
x
REQ_035
Generation Forecast Update
Rate
Active power production plans are updated every 12
hours
x
x
REQ_036
REQ_037
Load Forecast Time Horizon
Load Forecast Time
Resolution
Load plans are given for 36 hours
Load plans are given with a resolution of 1 hours
x
x
x
x
REQ_038
Load Forecast Update Rate
Load plans are updated every 12 hours
x
x
Cost values are updated every 1 hour
x
x
REQ_039
Cost Update
Standard/Regulation
REQ_040
End-to-End communication
integrity
REQ_041
Message Authentication
IEC 62351 Part 3
End-to-end integrity of VC communications should be
guaranteed through an appropriate configuration of the
TLS protocol
IEC 62351 Part 6
Message authentication of VC communications will
follow the standard indications for the specific protocol
WP2
WP3
WP4
WP5
WP6
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Security
REQ_042
REQ_043
REQ_044
REQ_045
Integrity of transmitted data Transmitted data/measurements/commands are
protected against intentional changes (Integrity of
transmitted data is preserved in all data exchanges)
Integrity of stored data
Stored data/measurements are protected against
intentional changes
Action authorization
Data are available to authorized actions only
Authenticity of data
Authenticity of data/measurements/commands is
ensured
Page 222 of 244
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
WP2
REQ_046
Communication logging
Appropriate logs of VC application messages are made
available
x
WP3
WP4
WP5
WP6
x
x
WP5
WP6
Table 5 Requirements for Medium Voltage Control Use Case
11.2 Requirements for EV Charging Use Case
Requirement
ID
Title
Description
WP2
WP3
WP4
Architectural
REQ_200
REQ_201
Aggregator interaction
Meter aggregation
The charging station has to report the aggregated
demand, and the aggregator has to provide energy
price information.
In order to realize the decentralized architecture, it is
required that all the smart meters readings for
households, charging station (aggregated metering), PV
production and battery storage in that LV grid can be
queried, forwarded or stored by the LV grid controller
from a meter aggregation component.
x
x
x
Functional
REQ_202
Demand response
The demand management control target of reducing for
example the load in a LV by x% must affect the
setpoints calculated by the MV controller accordingly.
REQ_203
Charging station reaction to
local load increase or
production decrease
sudden reduction of the available power in a charging
station has to reduce the energy amount (not below the
minimum) and the charging duration accordingly
Interface
Page 223 of 244
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
REQ_204
Interface LV controllercharging controller
the LV grid controller and the charging controller have
to be able to exchange asynchronous unidirectional
messages
REQ_205
Aggregator connection
Each charging station must interact with an aggregator
(aggr. Charging infrastructure manag.)
x
LV Grid-MV grid interface
The MV controller must be able to set setpoints on the
LV controllers as a part of the VC goal and to determine
P and Q injected, based on the flexibility reported by
the LV controller
x
REQ_206
WP2
WP3
WP4
WP6
x
Use Case Level Requirements
Architectural
REQ_207
Charging spots
Charging spots are controlled either by the EMS (home
scenario) or by a charging station controller
x
REQ_208
Routing and reservation
The routing and reservation service must select the
charging station and allocate charging resources to
approaching EVs.
x
REQ_209
EV demand flexibility
An EV has to provide the charging station following
demand flexibility data: plug-in time or an estimate of
it, minimum amount of energy, maximum amout (full
charging) , charging speed supported by the EV. It MAY
provide the estimated parking duration.
x
REQ_210
Routing and reservation
Charging stations have to report their load forecasts to
the routing service, and would receive reservation
requests.
x
Interface
Page 224 of 244
WP5
x
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
REQ_211
EV connectivity with
reservation service
Standard/Regulation
The EV has to communicate wirelessly with the
reservation server.
REQ_212
The charging power can vary from zero up to a
maximum charging power supported by both the
charging spot and the vehicle
Charging speeds
WP2
WP3
WP4
x
Communication
REQ_213
Metering Network
Monitoring
Metering network disfunction has to be recognized at
the LV grid controller
x
REQ_214
LVcontroller-CS controller
link monitoring
A connection disruption of the link LVGC to CS
Controller has to be identified
x
REQ_215
Control links to charging
points monitoring
Communication disfunction of a charging point
connection has to be identified
x
Functional
REQ_216
Charging station controller
function
REQ_217
Charging schedule
REQ_218
Meter readings
Page 225 of 244
The charging station has to be able to
calculate/estimate at any point in time the current and
the future EV charging demand (time horizon of 6 hours
for instance)
A charging station maintains a plan (schedule) for all
known charging jobs, which is updated in case of event
updates.
The meter reading interval for some components is as
low as 1 second.
x
x
x
x
WP5
WP6
FP7-ICT-318023/ D1.1 ver 2
Requirement
ID
Title
Description
WP2
WP3
WP4
REQ_219
PV control
Sudden increase of LV voltage at a PV generation bus
has to be corrected by controlling signal from the LV
controller to the PV inverter in a matter of X seconds
x
REQ_220
Interface between car and
CP
The EV should provide periodical energy flexibility
profile (min and max). This may go beyond the interface
specified in IEC15118
x
Secure channel
The communication between LVGC and charging
stations shall be secured (encrypted, authenticated,
etc.)
WP5
WP6
x
Security
REQ_221
x
Table 6 Requirements for EV Charging Use Case
11.3 Requirements for External Generation Use Case
Requiremen
t ID
Title
Description
WP2
WP3
WP4
WP5
WP6
Up-to-date Round Trip times measurements of the AN
shall be available to the LVGC as well as the assets.
RTT estimations shall be expressed in ms.
x
x
x
Up-to-date throughput measurements of the AN shall
be available to the LVGC as well as the assets.
Throughput estimations shall be expressed in bps.
Up-to-date packet loss probability measurements of
the AN shall be available to the LVGC as well as the
assets. Packet loss probability estimations shall be
expressed in %.
x
x
x
x
x
x
Communication
REQ_400
Access network RTT
measurements
REQ_401
Access network throughput
measurements
REQ_402
Access network packet loss
probability measurements
Page 226 of 244
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
WP2
WP3
REQ_403
Access network connectivity
measurements
x
x
x
REQ_404
Access network
reconfiguration access
Up-to-date connectivity measurements of the AN shall
be available to the LVGC as well as the assets.
Connectivity estimations shall be expressed as
boolean.
SmartC2Net platform should be able to reconfigure
the AN network layers down to the data link layer.
x
x
REQ_405
Provisioning of meta quality
data of accessed data
The ITC system shall be able to provide meta data that
indicates the reliability of the data being provided
x
x
x
Functional
REQ_406
Voltage variations
REQ_407
Voltage dips/swells
The voltage profile in LV and MV feeders shall not
exceed +/- 10% from the rated value as a 10 min
average value. This is stated in DS/EN 50160 and in
the Danish Recomedation 16 - Voltage Quality in LV
grids.
A voltage dip is not allowed to exceed -5% from the
rated nominal value. A voltage swell is not allowed to
exceed +5% from the rated nominal value. This is
stated the Danish Recomedation 16 - Voltage Quality
in LV grids. A voltage dip or swell is a rapid decrease or
increase in voltage from one sample to the next. This
is stated in DS/EN 50160 and in the Danish
Recomedation 16 - Voltage Quality in LV grids.
Dependability
REQ_408
Resilient network
performance operation
REQ_409
Reliable middleware
components
Page 227 of 244
Even during network performance degradation, the
system shall be able to continue without major loss of
control
Developed middleware components shall be
operational to the extend that the components
themselves will not fail during tests
WP4
WP5
WP6
x
x
x
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
WP2
WP3
WP4
WP5
WP6
Aggregation of available reactive power shall be
computed at secondary substation level. This
algorithm shall consider the status and available
power from flexible assets in LV feeders.
x
x
x
All flexible assets in MV/LV grids shall be able to
receive and follow an admissible setpoint for active
power from upper hierarchical controller(s). A positive
sign means power injection into the grid while a
negative sign means power consumption. This
setpoint shall be expressed in [kW].
All flexible assets connected through a power
converter to MV/LV grids or having reactive power
control capabilities shall be able to receive and follow
an admissible setpoint for reactive power from upper
hierarchical controller(s). A positive sign means power
injection into the grid while a negative sign means
power consumption. This setpoint shall be expressed
in [kVAR].
All flexible assets in MV/LV grids shall be able to send
information about available active power to upper
hierarchical controller(s). This availability shall be
defined as the difference from rated/potential active
power of the device and the actual
production/consumption. A positive sign means
power injection into the grid while a negative sign
x
x
x
x
x
x
x
x
x
x
x
x
Communication
REQ_410
Aggregation of Available
Reactive Power
Functional
REQ_411
Individual Setpoint for active
power - Asset
REQ_412
Individual Setpoint for
reactive power - Asset
REQ_413
Available active power Asset
Page 228 of 244
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
WP2
WP3
WP4
WP5
WP6
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
means power consumption. The signal shall be
expressed in [kW].
REQ_414
Available reactive power Asset
REQ_415
Active Power Production Asset
REQ_416
Reactive Power Production Asset
REQ_417
Voltage measurements Asset
Page 229 of 244
control capabilities shall be able to send information
about available reactive power to upper hierarchical
controller(s). A positive sign means power injection
into the grid while a negative sign means power
consumption. The signal shall be expressed in [kW].
All flexible assets in MV/LV grids shall be able to send
information about active power production to upper
hierarchical controller(s). A positive sign means
means power consumption. This signal shall be
expressed in [kW].
control capabilities shall be able to send information
about reactive power production/consumption to
upper hierarchical controller(s). A positive sign means
means power consumption.The signal shall be
expressed in [kVAR].
All flexible assets in MV/LV grids equipped with
voltage measurement devices at their Point of
Connection (PoC) shall be able to provide
measurement of voltage in PoC to upper hierarchical
controller(s). This measurement signal shall be
expressed in [V].
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
REQ_418
State-of-Charge - Asset
REQ_419
Setpoint for active power LVGC
REQ_420
Setpoint for reactive power LVGC
REQ_421
Active power control - LVGC
REQ_422
Active power dispatch LVGC
Energy storage systems connected to MV/LV grids
x
shall provide to upper hierarchical control levels a
signal reflecting their State-of-Charge (SoC). This signal
shall be expressed in [%] based on the energy
storages rated capacity.
LVGC shall be able to receive and follow an admissible x
setpoint for active power received from MVGC. These
setpoints shall be expressed in [kW].
LVGC shall be able to receive and follow a setpoint for x
reactive power received from MVGC. These setpoints
shall be expressed in [kVAR].
LVGC shall be able to control active power on MV side
of the secondary substation. The active power control
shall be made using the Setpoint from MVGC,
measured active power from assets in LV grids as well
as the total available power from the LV assets. The
output of the active power control shall be a
reference signal for the all flexible assets connected to
LV feeders. in [kW].
LVGC shall be able to distribute the reference signal
from active power control to flexible assets in LV grids
as individual setpoints for active power. The individual
setpoints for active power shall take into account
actual power production and availability from the
flexible assets . These individual setpoints signal shall
be expressedin [kW].
Page 230 of 244
WP2
WP3
WP4
WP5
WP6
x
x
x
x
x
x
x
x
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
REQ_423
Reactive power control LVGC
REQ_424
Reactive power dispatch LVGC
REQ_425
Aggregation of Available
Active Power
LVGC shall be able to control reactive power on MV
side of the secondary substation. The reactive power
control shall be made using the reactive power
setpoint from MVGC or the reactive power reference
from Voltage Control in LVGC, measured reactive
power from flexible assets in LV grids as well as the
total available power from the LV assets. The output
of the reactive power control shall be a reference
signal for the all flexible assets connected to LV
feeders. This reference signal shall be expressed in
[kVAR].
LVGC shall be able to compute and distribute the
reference signal from reactive power control in LVGC
to flexible assets in LV grids as individual setpoints for
reactive power. The individual setpoints for reactive
power shall take into account actual reactive power
production and availability from the flexible assets .
These individual setpoints signal shall be expressed in
[kVAR].
Aggregation of available active power shall be
computed at secondary substation level. This
algorithm shall consider the status and available
power from flexible assets in LV feeders.
WP2
x
WP3
WP4
WP5
WP6
x
x
x
x
x
x
WP3
WP4
Table 7 Requirements for External Generation Use Case
11.4 Requirements for AMR and CEMS Use Case
Requiremen
t ID
Title
Page 231 of 244
Description
WP2
WP5
WP6
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
WP2
WP3
WP4
WP5
WP6
x
x
x
x
x
x
x
x
x
x
x
x
Architectural
REQ_600
CEMS communication
functionalities extensibility
REQ_601
CEMS integrity
The CEMS shall be extensible for the implementation
of further / future communication functionalities
The components of the CEMS shall be limited to the
minimal necessary functionality to avoid costs and
security risks
Communication
REQ_602
Home network
heterogeneity
The CEMS shall work with heterogeneous home area
network (e.g., wired, wireless)
REQ_603
Home network conditions
heterogeneity
The CEMS shall work in variable network conditions
(e.g., available bandwidth, delay, packet loss)
x
REQ_604
Cost Transmission Rate
Cost data are transmitted every <n> time intervals
x
REQ_605
Smart Meter reading
The smart meter periodically or on request provides
meter readings and complete state and logging
information.
REQ_606
EMG metering data
computation
REQ_607
EMG load shifting
REQ_608
Tariff information updates
x
Functional
Interface
Page 232 of 244
The EMG shall apply any necessary pre-computation
on the local metering data (if applicable)
The EMG shall be able to issue commands for load
shifting when allowed and possible, as requested by
the HES
The CEMS shall be provided with actual tariff
information in intervals of <n> / on tariff change
x
x
x
x
x
x
x
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
REQ_609
Control gateway network
interfaces
The CEMS energy control sub-system shall have both
WAN network interface and HAN interface
REQ_610
Metering Gateway network
interfaces
REQ_611
DER communication
REQ_612
Flexible loads
communication
REQ_613
User interaction system
communication
REQ_614
Metering Data Aggregation
communication
The Smart Meter shall interface with the HES
x
REQ_615
Aggregation communication
The CEMS / AMR shall interface with the Aggregator
(i.e., the Flexible load and DER aggregation) for
controlling purpose
REQ_616
CEMS Network
communication
The CEMS shall interface with the communication
network
x
REQ_617
CEMS power grid interface
The CEMS shall interface with the power grid operator
REQ_618
CEMS metering
communication
The CEMS shall interface with the metering operator
REQ_619
Private vehicle charging spot
interaction
The CEMS house network shall allow the
communication with private vehicle charging spots
REQ_620
CEMS and home automation
communication
communication with home building automation
Page 233 of 244
WP2
WP3
WP4
WP5
WP6
x
x
x
The metering gateway sub-system shall have a WAN
network interface as well as an interface with HAN
x
x
x
The CEMS / AMR house network shall allow the
communication with house related DER
x
x
x
communication with house related flexible load
communication with the house related user
interaction subsystem (e.g., the external consumer
display)
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
WP2
WP3
WP4
WP5
WP6
equipment
Smart Meter EMG
connection
Smart meter and EMG might interface if not
prohibited due to legal ruling
x
x
x
availability
operations should be highly available
x
x
x
operations should be reliable
x
x
x
REQ_625
reliability
Energy Management
Gateway reliability
Smart Meter availability
REQ_626
CEMS reliability
REQ_621
Dependability
REQ_622
REQ_623
REQ_624
x
x
x
x
x
The Smart Meters shall be available 99% of the year
The components of the CEMS shall possess a MTBF
equal or greater than <n>
x
x
x
x
x
x
False positives in signaling the attempt to tamper the
components and/or the communication shall be
limited to a MAX_FP extent
The EMG and Smart Meters shall be able to
synchronize their clocks with the HES
The EMG / HES and Smart Meters shall be able to
exchange metering data in intervals of down to 1
second / on demand
The LNAP / NNAP shall provide a minimum data rate
of approx. 20 Kbit/s per connected SM with a
maximum Delay of 15 min.
x
x
x
The EMG shall have an availability of 99%
Performance (Quality of Service)
REQ_627
Intrusion detection false
alarm rate
REQ_628
Time Synchronization
REQ_629
Metering Data Transmission
REQ_630
Access Point WAN
Communication
Page 234 of 244
x
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
REQ_631
Title
Description
WP2
WP3
Communication quality of
service reports
The LNAP / NNAP shall monitor the quality of its WAN
connection and report any deviation from normal
operation to the EMG and HES
X
x
The Communication Interfaces and Protocols shall be
in compliance with standards wherever applicable
The intervall in which customer usage information is
supplied shall be in accordance with national
regulations
x
x
WP4
WP5
WP6
x
x
x
x
x
x
x
x
x
Standard/Regulation
REQ_632
REQ_633
Compliance with standards
Usage data intervall
x
x
Security
REQ_634
In-house message
authentication
The messages exchanged between the components
within the HAN that may exploit a shared medium
(e.g. WiFi LAN) shall be secured against unauthorized
accesses and modifications
x
x
REQ_635
The messages exchanged between the CEMS / AMR
and external entities (e.g., Metering Aggregator) shall
be secured against unauthorized accesses and
modifications
x
WAN message
authentication
x
x
x
house message
confidentiality and privacy
The messages exchanged between the components
on the customer shared network (e.g., Wi-Fi LAN) shall
be secured against disclosure of information and
traffic analysis
x
x
x
WAN message
confidentiality and privacy
The messages exchanged between the CEMS / AMR
and external entities (e.g., Metering Aggregator) shall
be secured against disclosure of information and
traffic analysis
REQ_636
REQ_637
Page 235 of 244
FP7-ICT-318023/ D1.1 ver 2
Requiremen
t ID
Title
Description
WP2
REQ_638
Tamper and fraud detection
/ protection
x
REQ_639
Software Security
REQ_640
Attack logging and reporting
The physical components of the CEMS / AMR shall be
guarded against manipulation
The EMG, Smart Meters and LNAP shall be robust
against software attacks (for example no standard
passwords)
The EMG, Smart Meters and LNAP shall be able to
report detected attacks and tempering attempts
REQ_641
Access logging
Any access (especially remote ICT access) to the CEMS
/AMR components shall be logged
X
Table 8 Requirements of the AMR / CEMS Use Case
Page 236 of 244
x
WP3
WP4
WP5
WP6
x
x
x
x
x
FP7-ICT-318023/ D1.1 ver 2
12 Annex D - Table of KPIs
This annex contains the list of Key performance Indicators with the mapping on the project WP where are addressed.
Considering the scope of the KPI these are marked as follows:
DSO oriented
CSP oriented
CSO oriented
Aggregator oriented
Customer oriented
12.1 Key Performance Indicators for Medium Voltage Control Use Case
WP2
KPI_id
KPI name
Definition
Goal
WP3
WP
4
WP
5
Power related KPIs
KPI_001
Unsupplied power
KPI_002
DER involved
KPI_003
Lines involved
KPI_004
Loads involved
KPI_005
Substation involved
Size of grid affected by an attack/fault
# DERs per HV/MV substation affected by an ICT
attack/fault
# MV lines per HV/MV substation affected by an ICT
attack/fault
# unsupplied MV loads per HV/MV substation affected
by an ICT attack/fault
# HV/MV substations per Control Centre affected by an
ICT attack/fault
KPI_006
KPI_007
KPI_008
Energy losses
Grid Hosting Capacity
Power Quality improvements
Amount of lost energy
Amount of RES power per MV line
Percentage reduction of voltage variations in MV lines
Page 237 of 244
0 MW
x
0
x
0
x
0
x
0
Min value
KWatt/h
Max value MW
Min value
x
x
x
WP
6
FP7-ICT-318023/ D1.1 ver 2
WP2
KPI_id
KPI_009
KPI_010
KPI_011
KPI_012
KPI name
KPI_013
KPI_014
KPI_015
Grid events
Power grid stability
Integrity of measurements
Integrity of state estimation
Correct setpoints
computation
Cost optimization
Correct setpoint receipt
KPI_016
Security gain_overvoltages
KPI_017
Security gain_undervoltages
KPI_018
KPI_019
KPI_020
Voltage value (V)
Active Power (P)
Reactive Power (Q)
Definition
Goal
# Overvoltages
# Undervoltages
# Topological changes
Deviation from optimal voltage profile
# Correct measurements
# Correct state estimations
Min value
Min value
Max value
Max value
# Setpoints computed correctly
DSO cost to obtain an optimize voltage profile
# Setpoints received correctly
# Overvoltages w/o security/ # Overvoltages with
security
# Undervoltages w/o security/ # Undervoltages with
security
The actual voltage Vh(t) for each electrical component
h at time t
The actual active Ph(t) for each electrical component h
at time t
The actual reactive Qh(t) power, for each electrical
component h at time t.
WP3
WP
4
WP
5
WP
6
x
x
x
x
Max value
Min value
Max value
x
x
x
Max value
x
Max value
x
Setpoint value
x
Setpoint value
x
Setpoint value
x
Communication related KPIs
KPI_021
Communication Network
Availability
Page 238 of 244
Mean Time To Failure / Mean Time Between Failure
99,999% (5
minutes per year)
for Control
Center - Primary
Substation
communication
99.95% for
x
x
x
FP7-ICT-318023/ D1.1 ver 2
WP2
WP3
WP
4
WP
5
WP
6
KPI_id
KPI name
Definition
Goal
Primary
Substation -DER
communication
KPI_022
Fault Awareness
Fault detection time
Min value T (sec)
x
KPI_023
Localization and Isolation
Time
Faster reaction time to grid faults and ICT attacks
Min value T (sec)
x
KPI_024
Security gain_measurements
# Correct measurements received w/o security /#
correct measurements received with security
Min value
x
x
x
Min value
x
x
x
Min value
x
x
x
x
Min value
x
x
x
x
# Legal msgs (packets) discarded with security /# legal
msgs (pakets) discarded w/o security
Availability w/o security /availability with security
(Transmission) delay with security /# delay w/o security
# Intrusion attempts detected
Min value
Min value
Min value
Max value
x
x
x
x
x
x
x
x
x
x
x
x
x
# Prevented illegal actions with security
Max value
x
KPI_025
Security gain_setpoints
KPI_026
Security gain_legal data rate
Security gain_lost msgs
(packets)
KPI_027
KPI_028
KPI_029
KPI_030
KPI_031
KPI_032
Security gain_discarded msgs
(packets)
Security gain_availability
Security delay
Security_IDS
Security_prevention_illegal_a
ction
# Correct setpoints received w/o security /# correct
setpoints received with security
Legal data rate w/o security / legal data rate with
security
# Legal msgs (packets) lost with security /# legal msgs
(packets) lost w/o security
Generic KPIs
KPI_033
Population involved
Page 239 of 244
Percentage of people affected by an attack/fault
0%
x
FP7-ICT-318023/ D1.1 ver 2
WP2
KPI_id
KPI_034
KPI name
Satisfied requirements
Definition
# Requirements satisfied
WP3
Goal
Max value
WP
4
WP
5
x
WP
6
x
Table 9 Key Performance Indicators for Medium Voltage Control Use Case
12.2 Key Performance Indicators for EV charging Use Case
In Table 10 we list a number of performance indicators for the EV charging use case. With other words, running the scenario with a certain configuration of
energy demand, supply, topology, charging demand, presence of failures or not, daily prices, etc. will create a (unique) set of these performance indicators,
that should reflect the objectives of users, CSO, DSO, etc.
WP2 WP3 WP4 WP5
WP6
KPI_id
KPI name
Definition
Goal
Power related KPIs
KPI_200
Number of Grid Events
KPI_201
Severity of Grid Events
Amount of grid events and type. [#] Types are:Over-current
(line/trafo), Overvoltage (Bus), Undervoltage (Bus)
relative value of a grid event: Over-current: I/I_max-1
(branch), Over-voltage: [U/U_max-1/ (Bus), Under-voltage:
U_min/U-1 (Bus)
Renewable energy fed into grid/ Renewable energy
generated without curtailment
0
fraction
<1 (0)
x
x
x
x
x
x
KPI_202
Renewable resource
efficiency, general
KPI_203
EV Demand reduction
control
Demand actual reduction/demand reduction target
difference
in % (0)
x
x
KPI_204
accuracy of LV following
MV set points
Accuracy of actual achieving the target P/Q using EV
flexibility and PV control
difference
in %
x
x
Page 240 of 244
%
FP7-ICT-318023/ D1.1 ver 2
KPI_id
KPI name
Definition
KPI_205
Degradation of power
quality without meter data
Define degradation criteria (duration of operation without
grid events, etc.) if flexibility/meter data is disrupted (CS or
CEMS).
KPI_206
Degradation of power
quality if LV grid controller
- charging station fails
Define degradation criteria, if a charging station does not
receive actuation from the LV controller for a duration
Degradation if PV control
network fails
Define degradation criteria in case CEMS with PV and
storage does not receive actuation
KPI_207
Goal
failure
duration
# of
sampling
periods
minutes
max
Value
minutes
max
Value
WP2
WP3
WP4
WP5
WP6
x
x
x
x
x
x
x
x
x
Economical related KPIs
KPI_208
KPI_209
charging load balancing
among close charging
stations
distribution of load =charged energy/available charging
energy
variance
0
cost performance
minimum cost of energy that could be achieved by the
aggregator given the EV flexibility divided by actual CSO
costs of energy constrained by the DSO
100%
x
x
x
Generic KPIs
KPI_210
KPI_211
User satisfaction – Level of
Service
User satisfaction –
Availability of Service
Average over all EVs Charged energy/maximum requested
energy [%].
100%
Number of served users/number of users requesting service
100%
Table 10 Key Performance Indicators for EV charging Use Case
Page 241 of 244
x
x
FP7-ICT-318023/ D1.1 ver 2
12.3 Key Performance Indicators for External Generation Use Case
KPI_id
KPI name
Definition
Goal
WP2
WP3
WP4
WP5
WP6
Power related KPIs
KPI_400
Voltage limits in LV and MV
feeders
The voltage profile in LV and MV feeders shall not exceed +10% from the rated value as a 10 min average value.
10%
KPI_401
Rapid Voltage change limit
in LV feeders
Rapid voltage changes should not exceed +-5% of the rated
value.
5%
KPI_402
Rapid Voltage change limit
in MV feeders
Rapid voltage changes should not exceed +-4% of the rated
value.
4%
x
x
x
x
x
x
KPI_403
Access network packet loss
limit
The application layer packet loss probability shall be low
enough to allow the LVGC to adhere to its voltage limits.
<0.01 %*
KPI_404
Wide area network packet
loss limit
The application layer packet loss probability shall be low
enough to allow the MVGC to adhere to its voltage limits.
<0.01%*
x
x
KPI_405
Access network delay limit
The application layer packet delay shall be low enough to
allow the LVGC to adhere to its voltage limits.
<1 ms*
x
x
The application layer packet delay shall be low enough to
allow the MVGC to adhere to its voltage limits.
<1 ms*
KPI_406
Wide area network delay
limit
x
x
x
Table 11 Key Performance Indicators for External Generation Use Case
Page 242 of 244
x
x
x
FP7-ICT-318023/ D1.1 ver 2
12.4 Key Performance Indicators for AMR and CEMS Use Case
The Key Performance Indicators (KPI) of the AMR and CEMS use case are listed in Table 12
KPI_id
KPI name
Definition
Goal
WP2 WP3 WP4 WP5
WP6
x
x
Power related KPIs
KPI_600
KPI_601
KPI_602
KPI_603
Accuracy of energy
consumption
measurement /
estimation
Balancing and
maximization of power
grid utilization
Improvement of power
grid stability
DER utilization
Accuracy of energy consumption measurement /
estimation
% Max Value
Avoidance of peaks and valley of energy consumption in
the smart grid
100%
Average deviation of grid frequency and phase from
normal operation and duration of power grid outages
% Min value
Utilization of distributed energy resources
100%
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
KPI_604
KPI_605
KPI_606
KPI_607
Availability of the Service, i.e. downtimes / failures
100%
Successful transmissions
of metering data
Currentness of customer
feedback system and
metering data
Ration of successful metering data transmissions to failed
transmissions (i.e. necessary retransmissions)
100%
Currentness of energy usage and tariff data displayed to
the customer and metering data send to the HES
delta t Max Value
Maintainability
Ease of deploying Soft- and Hardware upgrades
€ & time Max Value
Page 243 of 244
x
x
x
FP7-ICT-318023/ D1.1 ver 2
KPI_id
KPI name
Definition
Goal
WP2 WP3 WP4 WP5
WP6
Economical related KPIs
KPI_608
Amount of energy saved
Energy saved per month
kWh Max Value
KPI_609
Reduction of energy costs
Energy costs saved per month
€ Max Value
KPI_610
Amount of acquired
energy consumption data
Ratio of metered consumption to unmetered consumption
100%
KPI_611
Accuracy of energy tariff
data
Deviation of customer energy tariffs and prices on the
energy market
€ Min Value
KPI_612
Reduction of nontechnical energy losses
Minimization of non-technical energy losses (i.e. illegal,
unbilled energy consumption)
100%
x
x
x
x
Generic KPIs
KPI_613
User satisfaction with
AMR / CEMS
General user satisfaction with AMR / CEMS functionality
100%
KPI_614
User satisfaction –
Served users / users requesting service
100%
KPI_615
End-user usability
Ease of use of the CEMS from an end-user perspective (for
example through a user friendly interface)
Max. value
Table 12 Key Performance Indicators of the AMR / CEMS Use Case
Page 244 of 244
x
x
x
x
x
x

Page 1 of 244 Project Number: 318023 Project acronym

Transcription

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