DISCERN WP4 D4.2 New system functionality

Transcription

Distributed Intelligence for Cost-Effective and Reliable Distribution Network Operation
Deliverable (D) No: 4.2
New system functionality
Author:
OFFIS
Version:
3.0
Date:
28.01.2014
www.discern.eu
Confidential (Y / N): N
The research leading to these results has received funding from the European
Union Seventh Framework Programme (FP7/2007-2013) under grant agreement
No. 308913.
D4.2 New system functionality
Title of the
Deliverable
WP number
4
Task title
Main Author
Project partners
involved
New system functionality
WP title
System integration concept/SCADA compatibility/Other enhanced
functions
T4.2 New System Functionality
Rafael Santodomingo/ OFFIS
Miguel García/ GNF
Ángel Yunta / GNF
Raúl Bachiller / IBR
Johannes Reidick / RWE
Marius Storp / RWE
Olaf Neumann / RWE
Torsten Hammerschmidt / RWE
Stefan Willing / RWE
Sarah Rigby / SSEPD
Anders Johnson / VRD
Ralf Heisig / VRD
Anders Kim Johansson / VRD
WP leader
VRD
Type (Distribution level)
 PU, Public
 PP, Restricted to other program participants (including the Commission Services)
 RE, Restricted to other a group specified by the consortium (including the Commission Services)
 CO, Confidential, only for members of the consortium (including the Commission Services)
Status
 In Process
 In Revision
 Approved
Further information
www.discern.eu
DISCERN_WP4_D4.2_280114_v3.0
Executive Summary
Deliverable D4.2 presents the new system functionality that will be implemented during the project in
the demo-sites.
One of the main objectives of DISCERN is to facilitate knowledge sharing among European DSOs in
order to learn from previous research projects. In that way, the definition of new system functionalities
to be implemented in the demo-sites is given by the information exchange from DSOs with good
knowledge about the functionalities gained from previous research projects (Leaders) to DSOs that will
implement these functionalities during DISCERN (Learners) or carry out a feasibility analysis of the
functionalities (Listeners).
The methodology used to enable the knowledge sharing among DSOs within DISCERN was defined in
deliverable D1.3. Deliverable D4.2 follows this methodology and presents the Use Cases and SGAM
models produced by Leaders, by using the templates created in D1.3.
As proposed in D1.1, D4.2 groups these Use Cases and SGAM models in different sub-functionalities,
which derive from the Smart Grid functionalities defined by the EU Commission Task Force for Smart
Grids Expert Group 1 to provide the High-Level Smart Grid services identified by this group of experts.
For each sub-functionality, D4.2 presents Leaders’ Use Cases and SGAM models. Furthermore, an
assessment and comparison between different Leaders’ solutions is provided focusing on the
functional architectures defined in the Functional Layer of SGAM models.
Deliverable D4.2 will provide inputs for D4.3, in which Learners will define their preferable system
architectures taking into account their present system architecture (D4.1) and the new system
functionality described here. Moreover, the Use Cases and SGAM models presented in D4.2 will
provide inputs to T5.1 for developing the DISCERN Semantic Model. In addition, cost allocation of
assets in T8.1 will be based on the Use Cases and SGAM models presented in D4.2. Thus, the
information objects between actors represented in these descriptions will help DSOs identify which
classes, attributes and relationships of the Semantic Model are needed to define interoperable
solutions, and whether it is necessary to extend this model or not.
It is important to note that the Use Cases presented in D4.2 do not detail non-functional requirements
associated to each step of the Use Case. These requirements, including performance requirements for
real-time operation, will be collected in T2-3.1 with the aim of defining catalogs of devices and
communication elements for Learners’ solutions.
DISCERN_WP4_D4.2_280114_v3.0
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Table of Contents
Executive Summary .....................................................................................................................................................................5
Table of Contents .........................................................................................................................................................................6
List of Figures...............................................................................................................................................................................7
List of Tables ................................................................................................................................................................................8
Abbreviations and Acronyms ........................................................................................................................................................9
1.
Introduction.......................................................................................................................................................................10
1.1.
Scope of the document ...........................................................................................................................................10
1.2.
Structure of the document .......................................................................................................................................10
2.
Methodology .....................................................................................................................................................................12
3.
Use Cases and SGAM models .........................................................................................................................................15
3.1.
B6 – Enhanced monitoring and control of MV/LV network .......................................................................................15
3.1.1. DISCERN_GNF_Leader_B6...............................................................................................................................16
3.1.2. DISCERN_IBR_Leader_B6 ................................................................................................................................34
3.1.3. DISCERN_RWE_Leader_B6 ..............................................................................................................................48
3.1.4. Summary ............................................................................................................................................................64
3.2.
B7bd – Real time monitoring of LV grid ...................................................................................................................65
3.2.1. DISCERN_GNF_Leader_B7bd ...........................................................................................................................66
3.2.2. DISCERN_RWE_Leader_B7bd ..........................................................................................................................85
3.2.3. DISCERN_SSEPD_Leader_B7bd ....................................................................................................................105
3.2.4. Summary ..........................................................................................................................................................131
3.3.
B9a – Optimized AMR data collection and analysis using virtualized as well as physical concentrators ................ 133
3.3.1. DISCERN_VRD_Leader_B9a...........................................................................................................................133
3.3.2. Summary ..........................................................................................................................................................155
3.4.
B9b – Calculation and separation of non-technical losses .....................................................................................156
3.4.1. DISCERN_IBR_Leader_B9b ............................................................................................................................156
3.4.2. Summary ..........................................................................................................................................................176
4.
Conclusions ....................................................................................................................................................................177
5.
References .....................................................................................................................................................................180
5.1.
Project documents ................................................................................................................................................180
5.2.
External documents ..............................................................................................................................................180
6.
Revisions ........................................................................................................................................................................181
6.1.
Track changes ......................................................................................................................................................181
DISCERN_WP4_D4.2_280114_v3.0
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List of Figures
FIGURE 2-1. LEADERS’ USE CASES AND SGAM MODELS STORED IN THE E-ROOM ...................... 12
FIGURE 2-2. LISTS OF ACTORS, FUNCTIONS AND STANDARDS STORED IN THE E-ROOM ................ 13
FIGURE 2-3. W ORK PLAN FOR ORGANIZING REGULAR MEETINGS WITH LEADERS IN T4.2. ............. 14
FIGURE 3-1. KNOWLEDGE SHARING AMONG DSOS IN SUB-FUNCTIONALITY B6 ............................ 16
FIGURE 3-2. COMPARISON BETWEEN THE FUNCTIONAL ARCHITECTURES PROPOSED BY GNF AND
RWE IN SUB-FUNCTIONALITY B6 ...................................................................................... 64
FIGURE 3-3. KNOWLEDGE SHARING AMONG DSOS IN SUB-FUNCTIONALITY B7BD ........................ 65
FIGURE 3-4. COMPARISON BETWEEN THE FUNCTIONAL ARCHITECTURES PROPOSED BY GNF, RWE
AND SSEPD IN SUB-FUNCTIONALITY B7BD ..................................................................... 131
FIGURE 3-5. KNOWLEDGE SHARING AMONG DSOS IN SUB-FUNCTIONALITY B9A ........................ 133
FIGURE 3-6. KNOWLEDGE SHARING AMONG DSOS IN SUB-FUNCTIONALITY B9B ........................ 156
DISCERN_WP4_D4.2_280114_v3.0
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List of Tables
TABLE 1. ACRONYMS ................................................................................................................ 9
TABLE 3-1. NEW ACTORS ADDED FOR SUB-FUNCTIONALITY B6 ................................................... 65
TABLE 3-2. NEW ACTORS ADDED FOR SUB-FUNCTIONALITY B7BD ............................................. 131
TABLE 3-3. NEW FUNCTIONS ADDED FOR SUB-FUNCTIONALITY B7BD ........................................ 132
TABLE 3-4. NEW ACTORS ADDED FOR SUB-FUNCTIONALITY B9A ............................................... 155
TABLE 3-5. NEW FUNCTIONS ADDED FOR SUB-FUNCTIONALITY B9A .......................................... 155
TABLE 4-1. NEW ACTORS PROPOSED BY LEADERS .................................................................. 177
TABLE 4-2. NEW FUNCTIONS PROPOSED BY LEADERS.............................................................. 178
DISCERN_WP4_D4.2_280114_v3.0
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Abbreviations and Acronyms
Table 1. Acronyms
DoW
EC
EU
GA
Description of Work
European Commission
European Union
General assembly
GNF
Gas Natural Engineering
IBR
Iberdrola Distribución Eléctrica, S.A.
IEC
International Electrotechnical Commission
IRM
KPI
LN
MB
PAS
PC
QA
QAP
QAS
QM
QMO
QO
RWE
SGAM
Interface Reference Model
Key performance indicator
Logical Node
Management Board
Publicly Available Specification
Project Coordinator
Quality Assurance
Quality Assurance Plan
Quality Assurance System
Quality Manager
Quality Management Office
Quality Objective
RWE Deutschland Aktiengesellschaft
Smart Grid Architecture Model
Scottish and Southern Energy Power
Distribution
Technical Board
Technical Manager
Vattenfall Research and Development AB
Work package
Work package leader
SSEPD
TB
TM
VRD
WP
WPL
DISCERN_WP4_D4.2_280114_v3.0
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1. Introduction
1.1. Scope of the document
Deliverable D4.2 is the output of task T4.2 within the DISCERN work package WP4. This deliverable is
aimed at defining the new system functionalities that will be implemented during the project in the
demo-sites. In DISCERN, the definition of new system functionalities relies on the information
exchange from DSOs with good knowledge about the functionalities to DSOs willing to implement
them during the project.
Deliverable [D1.1] defined the high-level sub-functionalities that will be addressed in DISCERN. These
sub-functionalities are aligned to the High-level Smart Grid services defined by the EU Commission
Task Force for Smart Grids Expert Group 1 [EU-EG1]. For each DISCERN sub-functionality there can
be: Leaders, which are DSOs with good knowledge about the sub-functionality gained from previous
research projects; Learners, which are DSOs willing to implement the sub-functionality during the
project; and Listeners, which are DSOs performing feasibility analysis of the sub-functionality in order
to determine whether it is possible and useful to implement it in their systems or not.
Following the methodology defined in [D1.3] to facilitate knowledge sharing within the project, Leaders
will exchange information about new system functionalities to Learners and Listeners in the form of
Use Cases and SGAM models. Deliverable D4.2 presents these Use Cases and SGAM models
produced by Leaders by using the standard-based templates created in [D1.3]. The deliverable also
includes the processes and methodologies which have been applied.
The representation of Use Cases and SGAM models in common formats facilitates the comparison
between different Leaders’ solutions and the extraction of relevant data, which can be used by
Learners and Listeners in next steps of the project. In that way, deliverable D4.2 provides inputs to
D4.3, in which Learners will define their preferable system architectures considering their present
system architecture [D4.1] and the new system functionalities defined here. Furthermore, the Use
Cases and SGAM models presented in D4.2 will also be used in T5.1 for defining the DISCERN
Semantic Model. Lastly, it should be stressed that T8.1 will use the Use Cases and SGAM models
presented in D4.2 to allocate costs of assess enabling comparison of different technical solutions.
Given that the focus of D4.2 is on new system functionalities, the Use Cases presented in this
deliverable do not include non-functional requirements in their detailed descriptions (these
requirements, including performance requirements for real-time operation, will be added in T2-3.1),
and the analysis and comparison between Leaders’ solutions is based on the functional architectures
given in SGAM Function Layers.
NOTE: The Description of Work for Discern states that Task 4.2 shall analyse response time
requirements for real-time operations and to recommend relevant support systems where the
functionality will be placed. However the analysis of performance requirements has been moved to
WP2&3 and later in T4.3. The location of functionality will be described more in detail in Task 5.3.
1.2. Structure of the document
The document comprises the following main sections:
Section 1 introduces the document.
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Section 2 describes the methodology used in task 4.2 for defining Leader’s Use Cases and SGAM
models in a consistent manner.
Section 3 presents Leader’s Use Cases and SGAM models for each of the sub-functionalities
addressed in DISCERN.
Finally, Section 4 concludes the document and highlights the next steps within the project.
DISCERN_WP4_D4.2_280114_v3.0
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2. Methodology
The methodology followed in task 4.2 for producing Leaders’ Use Cases and SGAM models was
based on deliverable D1.3 [D1.3]. The sequence of activities carried out within this process is
summarized as follows:
•
First, the so-called “model manager”, who is the person responsible for ensuring the
consistency of the descriptions provided by different DSOs within the project, uploaded the
first versions of the actors and functions lists into a common repository.
o
These lists include the actors and functions that should be used in DISCERN Use
Cases and SGAM models, and are based on international standards and reports,
such as the SG-CG First Set of Standards [SGCG-FSS], the ENTSO-E Role Model
[ENTSOE-RM] and the Interface Reference Model (CIM IRM) [IEC 61968-1].
o
In the early stages of the project, the repository was the DISCERN e-Room . In
particular, the Use Cases and SGAM models were stored in the folder of task T4.2
(Figure 2-1), whereas the lists were stored in the folder “DISCERN Templates” in WP1
(Figure 2-2).
1
Figure 2-1. Leaders’ Use Cases and SGAM models stored in the e-Room
1
https://er42.deloitteonline.com/dol/login.aspx (only accessible for project partners)
DISCERN_WP4_D4.2_280114_v3.0
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Figure 2-2. Lists of actors, functions and standards stored in the e-Room
•
Then, an iterative process started for each Leader. This iterative process is described as
follows:
o
Step 1: The Leader sends a first version of the Use Cases and SGAM models as well
as proposals to modify or extend the actors and functions lists.
o
Step 2: The model manager revises the Use Cases and SGAM models and the
proposals to modify the lists.
o
Step 3: The revised versions of the Use Cases and SGAM are sent back and
discussed with the Leader in regular meetings following the work plan of T4.2. This
work plan was detailed in an Excel sheet (Figure 2-3) that was updated when new
versions of the Use Cases and SGAM models were revised by the model manager.
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Figure 2-3. Work plan for organizing regular meetings with Leaders in T4.2.
•
o
Step 4: The Leader sends a new version of the Use Cases and SGAM models. These
new versions are uploaded by the model manager in the e-Room.
o
Step 5: If both the model manager and the Leader approve this version, the process
stops here. Otherwise, the process starts again in Step 3.
Finally, the versions approved by both Leaders and the model manager were presented
together in a Workshop. In this workshop, Learners, Listeners as well as other partners were
able to make comments and questions on Leaders’ descriptions, and the final versions were
consolidated.
DISCERN_WP4_D4.2_280114_v3.0
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3. Use Cases and SGAM models
This section presents Leaders’ Use Cases and SGAM models. These descriptions will be grouped in
the DISCERN sub-functionalities defined in [D1.1]
Identifier
Title
Scope
B6
Enhanced monitoring and
control of MV/LV network
B7bd
Real time monitoring of LV
grid
B9a
Optimized AMR data
collection and analysis
using virtualized as well as
physical concentrators
B9b
Calculation and separation
of non-technical losses
control of power flows and
voltages
observability of network
components down to low
voltage levels, potentially
using the smart metering
infrastructure
Analysis of solutions for cases
when the number of
customers downstream the
LV side of the substation is
very low.
Identification of technical and
non-technical losses using
meter data
Leader
Learner
Listener
IBR, GNF, RWE
VRD
SSEPD
SSEPD, RWE, GNF
IBR
None
VRD
GNF
None
IBR
GNF
SSE
All these sub-functionalities are aimed at providing the same “High-level Smart Grid service”
highlighted by the European Commission Task Force for Smart Grids in [EU-EG1]. The common Highlevel Smart Grid service for these sub-functionalities is referred to as “B - Optimal MV network
monitoring and automation”. This means that all Use Cases presented in this section have the same
overall objective, which is to enhance monitoring and control of power flows and voltages in the
distribution networks.
For each sub-functionality, Leader’s Use Cases and SGAM models are presented, analysed and
briefly compared when the sub-functionality has more than one Leader.
It is worth noting that the Use Cases presented in this section do not already include the requirements
associated to the Use Case (sections 4.2, 5 and 6 of the Use Cases). This is because the Use Case
methodology is a step-wise process that may involve different experts at each step. In DISCERN, this
step-wise process is defined in [D1.3] and establishes that the requirements are added to the Use
Cases during task T2-3.1. Furthermore, KPIs are not included in the Use Cases (section 8 of the Use
Case Template – see [D1.3]) nor in the SGAM models (Business Layer), because KPIs are not yet
completely defined at this stage of the project.
3.1. B6 – Enhanced monitoring and control of MV/LV network
This sub-functionality refers to solutions aimed at enhancing monitoring and control of MV/LV
networks. The Leading DSOs that will share knowledge gained from previous projects about this subfunctionality are: GNF, IBR and RWE. The Learner that will implement this new functionality during the
project is VRD, and finally, the Listener that will carry out a feasibility analysis of this sub-functionality
is SSEPD (Figure 3-1).
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Figure 3-1. Knowledge sharing among DSOs in sub-functionality B6
The following sub-sections present the Leader’s Use Cases and SGAM models for this subfunctionality:
•
DISCERN_GNF_Leader_B6 – “MV monitoring and telecontrolled switches”
•
DISCERN_IBR_Leader_B6 – “Optimal MV network monitoring and automation”
•
DISCERN_RWE_Leader_B6 – “Wide Area Control”
3.1.1.
DISCERN_GNF_Leader_B6
The solution proposed by GNF for this sub-functionality is called “MV monitoring and telecontrolled
switches” and its objective is to improve MV network observability and operation by installing current
and voltage sensors as well as telecontrolled switches in secondary substations.
3.1.1.1
DISCERN_GNF_Leader_B6_Use Case
1 Description of the Use Case
1.1 Use Case Identification
Use Case Identification
Name of Use Case
ID
Domain(s)/Zone(s)
DISCERN_GNF_Leader_B6
Distribution / Process, Field,
Station, Operation
Enhanced monitoring and control of MV/LV network– MV
monitoring and telecontrolled switches
1.2 Version Management
Version No.
Date
Name
Author(s)
15.11.2013
GNF
Version Management
Changes
DISCERN_WP4_D4.2_280114_v3.0
Approval Status
draft, for comments, for voting, final
final
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1.3 Scope and Objectives
Scope
Objective
Related Business Case
Scope and Objectives of the Use Case
MV distribution grid monitoring, and operation of telecontrolled MV switchgears
Provide MV network observability, in order to improve quality of service and continuity of
supply. Generate alarms when faults are detected, and when power flows or voltages in
the MV grid go out of permissible levels. Provide the possibility of remote network
reconfiguration.
Enhancing efficiency in day-to-day grid operation
1.4 Narrative of Use Case
Short Description
Narrative of Use Case
This sub-functionality deals with the MV network supervision and the operation of telecontrolled switchgears to perform remote
MV network reconfigurations. MV supervision is performed using voltage and current sensors, as well as Fault Passage
Indicators. Grid supervisors (IEDs), also called MV supervisors have the capability to calculate power flows and generate signals
and alarms that are sent to central systems.
Complete Description
The status of the network is monitored using Intelligent Electronic Devices, also called MV supervisors. The MV supervision
system consist of voltage and current sensors and fault passage indicators located in MV lines feeding secondary substations.
MV supervisors have computing capabilities to calculate power flows, as well as RTU functionality that provide them with
communication capabilities. Collected measures, alarms from fault passage indicators, as well as alarms related to threshold
violation, are sent to SCADA.
The main steps of this sub-functionality are:
1. Voltage and current in MV cables feeding secondary substations are measured using sensors. MV supervisor systems
located in the secondary substations perform simple calculations related to active and reactive power flows.
2. In case a threshold violation related to over/under voltage or over current is detected, MV supervisors generate the
corresponding alarm.
3. In case of fault, Fault Passage Indicators indicate the presence of fault and its direction to the MV supervisor.
4. Measures of voltage, currents, calculated power flows and alarms are sent to the SCADA.
5. Operators analyze the information received in SCADA. If necessary, network is reconfigured by the means of remote
operation of telecontrolled switches, following operation procedures.
6. Switching operations are transmitted to telecontrolled switchgears.
1.5 General Remarks
General Remarks
This sub-functionality aims at MV network monitoring and remote operation of switchgears. Switching operations are performed
by human operators who make decisions based on the operation procedures.
2
Diagrams
Diagram(s) of Use Case
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DISCERN_WP4_D4.2_280114_v3.0
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sd DISCERN_GNF_Leader_B6_Sequence Diagram
MV Grid
Switch
Voltage Sensor
Current SensorFault Passage Indicator
IED
Data Aggregator
DMS Operator
SCADA
REPORT(Voltage measurement)
REPORT(Current measurement)
INTERNAL
PROCESS(Fault
indication)
REPORT(Fault indication)
REPORT(Switch position)
INTERNAL
PROCESS(Active P
and reactive Q power
flows)
REPORT(Active P and reactive Q
power flows)
REPORT(Active P and
reactive Q power flows)
REPORT(Network topology and
configuration)
INTERNAL
PROCESS(Threshold
violation)
REPORT(Threshold violation)
REPORT(Threshold
violation)
REPORT(Threshold violation)
INTERNAL
PROCESS(Network
reconfiguration)
CHANGE(Switch position)
CHANGED(Ack)
CHANGED(Ack)
CHANGED(Ack)
(from Actors)
(from Actors)
(from Actors)
(from Actors)
(from Actors)
(from Actors)
(from Actors)
DISCERN_WP4_D4.2_280114_v3.0
(from Actors)
(from Actors)
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3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Process
Actor Name
Actor Type
MV Grid
Component
Layer Actor
Switch
Actors in Process zone
Actor Description
Further information specific to
this Use Case
MV cables feeding secondary
substations are sensed.
Component
Layer Actor
Medium Voltage (MV) distribution network.
Process actuators (e.g. switches or tap
changers) and sensing devices (e.g. current
sensors or voltage sensors) within the
distribution network are represented as
separated Actors.
A generic device designed to close, or open,
or both, one or more electric circuits
Current Sensor
Component
Layer Actor
Devices, which are spread on the Grid lines,
continuously report dynamic status of current.
Voltage Sensor
Component
Layer Actor
continuously report dynamic status of voltage.
Grouping
Field
Group Description
Actor Name
Actor Type
Fault Passage Indicator
IED
Actor Description
this Use Case
Component
Layer Actor
Device that indicates the presence and
direction of a fault current in the cables where
the device is located.
Component
Layer Actor
Any other Intelligent Electronic Device (IED)
not included in the list. IEDs are devices
incorporating one or more processors with the
capability to receive or send data/control from
or to an external source (e.g., electronic
multifunction meters, digital relays, controllers)
FPIs located at MV cables
feeding secondary substations,
indicate the presence and
direction of fault current, from
current and voltage
measurements.
One MV supervisor (IED)
located at the secondary
substation collects
measurements from sensors
and fault indications from FPIs,
computes power flows and
generates alarms.
Grouping
Station
Group Description
Actor Name
Actor Type
Data Aggregator
Component
Layer Actor
Grouping
Operation
Actors in Field zone
Tele-controlled switchgears
located in secondary substation
that can be remotely operated
by DMS Operator.
MV current sensors located at
substations.
MV voltage sensors located at
substations.
Actors in Station zone
Actor Description
this Use Case
Devices which are intermediate machines in a
communication network and can aggregate
the same timing data from field sensing
devices.
In this Use Case, data
aggregation is carried out in
two levels: - An Integrated
Control Unit (UCI), located at
primary substations collect data
from RTUs.
- Dual
Concentrators/Telecontrol
Managers (CTD/GST)
concentrate data from several
UCIs
Group Description
Actor Name
Actor Type
SCADA
Component
Layer Actor
DMS Operator
Business
Layer Actor
Actors in Operation zone
Actor Description
Supervisory Control And Data Acquisition
(SCADA) application provides the basic
functionality for implementing EMS or DMS,
especially provides the communication with
the substations to monitor and control the grid
Operator of the Distribution Management
System
DISCERN_WP4_D4.2_280114_v3.0
this Use Case
A human operator supervises
and takes control of the
operations performed in the
grid, based on information from
MV supervision and other
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information received in SCADA,
and following operation
procedures.
3.2 Use Case Conditions
Use Case Conditions
Triggering Event
Pre-conditions
Actor/System/Information/Contract
Periodically.
MV Grid
Fault, over/under
voltage or overcurrent outside
threshold is detected.
IED
Assumption
Voltages and
currents are within
limits.
Communications
can be established
from IED up to
SCADA.
Communications
can be established
from IED up to
SCADA.
3.3 References
No.
Reference Type
Reference
Standard
IEC 60870-5-104
Standard
IEC 60870-5-101
References
Status
Impact on Use
Case
Originator/
Organisation
Communication
Layer
Communication
Layer
IEC
Link
IEC
3.4 Classification Information
Relation to Other Sub-functionalities
Classification Information
Level of Depth
Individual Use Case
Prioritization
Operational track 2 2
Generic, Regional or National Relation
European
Viewpoint
Technical
Further Keywords for Classification
MV supervision, network monitoring, network reconfiguration
2
Operational track 2 means that “the sub-functionality will be simulated in WP6 and also implemented in WP7,
either in sequence or in parallel.” [D1.1]
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4
Step by Step Analysis of the Use Case
4.1 Steps – Scenario Name
Scenario Conditions
Triggering Event
No.
Scenario Name
Primary
actor
1
Measuring
Voltage
Sensor,
Current
Sensor
Periodically, voltage and
current sensors get
voltage and current
measurements from the
MV Grid
2
Substation State
Supervision
Switch
Switch position is
changed.
3
Alarm Supervision
IED,
Fault
Passage
Indicator
Some voltage or current
is out of limits, or a fault is
detected.
4
Process and Network Data
Management
Data
Aggregator
Periodically, IED reports
voltage measurements,
current measurements
and power flows to
SCADA
5
Substation Display
SCADA
Some voltage or current
is out of limits, or a fault is
detected.
Communication can
be established from
SCADA to HMI where
DMS Operator is
located. SCADA is up
and running
6
Assisted Control
DMS
Operator
Some alarm has been
received in SCADA.
Tele-controllable
switchgears in
secondary
substations are up
and running.
Communication can
be established from
SCADA to Switch.
Control Operation
procedures are known
by DMS Operator.
DISCERN_WP4_D4.2_280114_v3.0
Pre-Condition
Voltages and currents
are within limits.
Voltage Sensor,
Current Sensor and
IED are up and
running.
Communication can
be established from
Voltage Sensor and
Current Sensor to IED
Switch and IED are
up and running.
Communication can
be established from
Switch to IED
Threshold values are
predefined.
Communication can
be established from
IED to SCADA. IED,
Data Aggregator and
SCADA are up and
running.
Communication can
be established from
IED to SCADA. IED,
Data Aggregator and
SCADA are up and
running.
Post-Condition
IED (MV
supervisor)
receives collected
voltage and
current measures
and computes
power flows
IED receives
switch position.
IED (MV
supervisor)
generates alarms
and reports these
alarms to central
systems
(SCADA).
Voltage
measurements,
current
measurements
and power flows
calculations are
stored in SCADA.
Voltage
measurements,
current
measurements,
power flows and
fault indications
are shown to
DMS Operator
Network is
reconfigured and
exploited in a
more efficient and
safe manner.
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4.2 Steps – Scenarios
Scenario Name :
Step Event
No.
Measuring
1a
Periodically
Scenario
Name of Process/Activity
Description of
Process/Activity
Service
Information Producer
Information Receiver
Information
Exchanged
Measure voltage in MV
Grid
Voltage sensors
get voltage
measurements
from MV cables
Current sensors
get current
measurements
from MV Grid.
Voltage sensors
make voltage
measurements
available to IED
Current sensors
make current
measurements
available to IED
Active and
reactive power
flows are
computed by IED
Voltage sensors
make voltage
measurements
available to FPI
Current sensors
make current
measurements
available to FPI
Voltage
measurements
are sent from IED
to Data
Aggregator,
Current
measurements
are sent from IED
to Data
Aggregator
Power flows are
sent from IED to
REPORT
MV Grid
Voltage Sensor
Voltage
measurement
REPORT
MV Grid
Current Sensor
Current
measurement
REPORT
Voltage Sensor
IED
Voltage
measurement
REPORT
Current Sensor
IED
Current
measurement
INTERNAL
PROCESS
IED
IED
Active P and
reactive Q
power flows
REPORT
Voltage Sensor
Fault Passage
Indicator
Voltage
Measurement
REPORT
Current Sensor
Fault Passage
Indicator
Current
Measurement
REPORT
IED
Data Aggregator
Voltage
measurement
REPORT
IED
Data Aggregator
Current
measurement
REPORT
IED
Data Aggregator
Active P and
reactive Q
1b
Periodically
Measure current in MV
Grid.
2a
Periodically
Report voltage
measurements to IED
2b
Periodically
Report current
measurements to IED
3
Periodically
Power flow calculations
4a
Periodically
Report voltage
measurements to Fault
Passage Indicator
4b
Periodically
Report current
measurements to Fault
Passage Indicator
5a
Periodically
Report voltage
measurements to Data
Aggregator
5b
Periodically
Report current
Aggregator
5c
Periodically
Report power flows to Data
Aggregator
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Data Aggregator
Substation State Supervision
1c
Spontaneously,
Switch position information
when position is
changed
2c
Spontaneously,
when position is
changed
Operation Alarm Supervision
5d
Short circuit
Alarm generation
occurs
6
Fault detected by
FPI
Report fault alarm to IED
7a
IED received
report on fault
alarm from FPI
Data Aggregator
received report
on fault alarm
from IED
Voltage or
current
measurements
out of limits
(Threshold
violation)
Report fault alarm to Data
Aggregator
Alarms
generated in IED
Report alarms to Data
Aggregator
8a
9a
7b
8b
Report fault alarm to
SCADA
Alarm generation
Data Aggregator
Report alarms to SCADA
received reports
on alarms from
IED
Process and Network Data Management
8c
Periodically
Report voltage
power flows
Switch sensors
indicate the switch
position
IED reports
Switch position to
Data Aggregator
REPORT
Switch
IED
Switch position
REPORT
IED
Data Aggregator
Switch position
FPI compares
currents with
predefined
thresholds. In
case of fault
current, FPI
generates fault
indication alarm
FPI makes fault
information
available to IED
IED reports the
fault alarm to the
Data Aggregator
Data Aggregator
reports fault alarm
to SCADA
INTERNAL
PROCESS
Fault Passage
Indicator
Fault indication
REPORT
IED
Fault indication
REPORT
IED
Data Aggregator
Fault Indication
REPORT
Data Aggregator
SCADA
Fault Indication
IED compares
voltage and
current
measurements
with predefined
thresholds. In
case of
over/under
voltage or over
current, IED
generates an
alarm.
IED reports the
alarms to the Data
Aggregator
Data Aggregator
reports alarms to
SCADA
INTERNAL
PROCESS
IED
IED
Threshold
violation
REPORT
IED
Data Aggregator
Threshold
violation
REPORT
Data Aggregator
SCADA
Threshold
violation
Voltage
REPORT
Data Aggregator
SCADA
Voltage
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measurements to SCADA
8d
Periodically
Report current
measurements to SCADA
8e
Periodically
Report power flows to
SCADA
8f
Spontaneously,
when position is
changed
Report Switch position
information to SCADA
Substation Display
9a
Threshold
violation or fault
indication
received in
SCADA
9b
Threshold
violation or fault
indication
received in
SCADA
9c
Threshold
violation or fault
indication
received in
SCADA
9d
Threshold
violation or fault
indication
received in
SCADA
9e
Fault indication
received in
SCADA
Assisted Control
10
Threshold
violation
measurements
are sent from
Data Aggregator
to SCADA
Current
measurements
are sent from
Data Aggregator
to SCADA
Power flows are
sent from Data
Aggregator to
SCADA
Data Aggregator
reports Switch
position to
SCADA
measurements
REPORT
Data Aggregator
SCADA
Current
measurements
REPORT
Data Aggregator
SCADA
Active P and
reactive Q
power flows
REPORT
Data Aggregator
SCADA
Switch position
Report voltage
measurements to DMS
Operator
Voltage
measurements
are shown to DMS
Operator.
REPORT
SCADA
DMS Operator
Voltage
measurement
Report current
measurements to DMS
Operator
Current
measurements
are shown to DMS
Operator.
REPORT
SCADA
DMS Operator
Current
measurement
Report power flows to
DMS Operator
Power flows are
shown to DMS
Operator.
REPORT
SCADA
DMS Operator
Active P and
reactive Q
power flows
Report switch positions to
DMS Operator
Switch positions
are shown to DMS
Operator.
REPORT
SCADA
DMS Operator
Switch positions
Report fault indication to
DMS Operator
Fault indication is
shown to DMS
Operator
REPORT
SCADA
DMS Operator
Fault indication
DMS Operator identifies
required switching
operations to reconfigure
the network.
DMS Operator
identifies switches
to operate
following
operation
procedures.
INTERNAL
PROCESS
DMS Operator
DMS Operator
Switch position
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11
DMS operator
selected
switching
operations
Selected switching
operation
12
DMS Operator
selected
switching
operations
Command to
change switch
position received
in Data
Aggregator
Command to
change switch
position received
in IED
Switch position
changed
Send command to Data
Aggregator
15
Switch position
changed
16
Switch position
changed
12
13
14
Send command to IED
Execute switch position
command
Human operator
selects some of
switching based
on experience and
operation
procedures.
Switch operation
is communicated
to Data
Aggregator
Switch operation
is communicated
to the IED.
CHANGE
DMS Operator
SCADA
Switch position
CHANGE
SCADA
Data Aggregator
Switch position
CHANGE
Data Aggregator
IED
Switch position
Switch operation
is communicated
to Switch
Controller
Switch sensors
indicate the switch
position
IED reports
Acknowledge to
Data Aggregator
Data Aggregator
reports
Acknowledge to
SCADA
CHANGE
IED
Switch
Switch position
REPORT
Switch
IED
Acknowledge
REPORT
IED
Data Aggregator
Acknowledge
REPORT
Data Aggregator
SCADA
Acknowledge
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5
Information Exchanged
Name of Information
Exchanged
Voltage measurement
Current measurement
Active P and reactive Q power
flows.
Fault indication
Threshold violation
Switch position
Description of Information Exchanged
Requirements to Information Data
Measurement indicating voltages in the
three phases of the MV lines feeding the
secondary substations, with timestamp.
Measurement indicating currents in the
three phases of the MV lines feeding the
secondary substations, with timestamp.
Active and reactive power flows calculated
in IED from voltage and current
measurements.
Presence of a fault current and its direction
in any of the phases of the MV lines feeding
the secondary substation.
Over/under voltage and over-current alarms
generated in IED by comparing voltage and
current measurements with predefined
thresholds.
Information about the position of a switch.
This information object should clearly
identify the switch. It can be used to create
a message about the current position of a
switch. It can also be used to create a
command defining the new switch position.
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3.1.1.2
DISCERN_GNF_Leader_B6_SGAM
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3.1.2.
DISCERN_IBR_Leader_B6
The solution proposed by IBR is called “Optimal MV network monitoring and automation” and it is
aimed at finding the optimal level of automation in MV networks ensuring high QoS while minimizing
the investment. For that purpose, applications at Operation and Enterprise level are used. These
applications help determine the optimal automation level from data bases containing historical data on
fault rates and costs of automation units.
3.1.2.1
1
DISCERN_IBR_Leader_B6_Use Case
Description of the Use Case
Name of Use Case
ID
Domain(s)/Zone(s)
DISCERN_IBR_Leader_B6
Distribution / Operation,
Enterprise
Enhanced monitoring and control of MV/LV network –
Optimal MV network monitoring and automation
Version No.
Date
Name
Author(s)
04.12.2013
IBR
Version Management
Changes
Approval Status
final
Scope
Objective
Analysis for optimal automation and monitoring of MV/LV networks
Facilitate the selection of level of automation in terms of Quality of Service and
investment.
Short Description
Nowadays the operation of MV networks creates new challenges for automation. Coupling this with the worldwide economic
situation, efforts for reaching a balance between Quality of Service indexes and investments in automation and grid
reinforcement through simplify methods are worthy. This Use Case describes this process.
Requirements for increasing the level of automation in actual MV networks are rising currently. The relation between investment
in automation and Quality of Service it is not linear. For example, the location of the same number of devices could lead to a
variety of costs as well. Moreover, initial investment plans might be not affordable due to the actual economic crisis. Therefore, a
simulation program to evaluate different scenarios is proposed to select a compromised point between costs, number of
equipment and propose criterion to locate them.
It is expected a definition of a methodology to decide the level of automation in MV grids in a simplify manner. It would be based
on a simulation algorithm taking into account investment on equipment in different types of SS and lines, power reinforcements
and evaluation of their impact on the Quality of Service (ASIDI). It is intended to facilitate decisions during the network planning
phase fulfilling technical, cost and regulatory constraints.
The main three steps in the process are:
1.
Use average values of outages (for example rate of outages in SS, lines, cables...) and cost units of work to
install telecontrol equipment (cabinet at SS and breakers at lines) to increase the automation of the network. These
data are managed by the DSO after analysing historical records collected in their systems.
2.
Simulation phase to evaluate different scenarios of outages over a simplified MV network portion
3.
Selection of compromise solution between cost and quality of service achieved
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1.5 General Remarks
General Remarks
The hypotheses/conditions under which the Use Case is developed are the following:
-
-
The analysed MV network area is divided in small sections. These sub-sections are selected between two
consecutive automatic Secondary Substations (SS).
A simplified MV network representation is required in PSS/E to simulate each outage scenario (power flow
calculations)
Average rates of outages are needed to know the network performance of each area to identified critical zones. These
values would be for example per SS (outage/100SS/year), underground lines (outages/100km/year) and aerial lines
(outages/100km/year).
Regulatory values are used to decide objective targets for simulation (penalties due to QoS).
Through the results (graph of QoS vs Investment) a criterion of location for pieces of control equipment (automatic
cabinets and telecontrol breakers at lines) is proposed.
The proposed level of automation is taking into account by the responsible of each control zone to install the
equipment.
In Spain the Distribution of electricity is a regulated activity. The remuneration of DSO is charged on customers through the
Access Tariffs. This tax joins different concepts. One of them is devoted to cover, theoretically, the distribution activity. The
value is decided by the Ministry. From 2008, all DSO are subjected to the same procedure and legal conditions. The
remuneration is individually assigned to each DSO taking into account issues such as: incentives per Quality of Service
improvements, incentives to reduce the losses, valuation of overcast, effects to cover the foreseen demand and geographical
restrictions. Each four (4) year the base value is fixed while yearly some parameters are corrected depending on the DSO
performance.
The architecture developed in the following section corresponds to the Use Case implementation within a DSO system
architecture. However, in the PRICE pilot the approach has been simpler.
2
Diagrams
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3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Operation
Actor Name
Actor Type
Network Operation
Statistics and Reporting
Component
Layer Actor
Network Operation
Simulation
Component
Layer Actor
Grouping
Enterprise
Actors in Operation Zone
Actor Description
this Use Case
This actor makes it possible to archive on-line
data and to perform feedback analysis about
system efficiency and reliability.
In the pilot this actor represents
the fact of having already
average ratios of outages.
This actor performs network simulations in
order to allow facilities to define, prepare and
optimise the sequence of operations required
for carrying out maintenance work on the
system (release/clearance orders) and
operational planning.
One possible way to get these
values is to analyse historical
outages tickets (normally in the
DMS- Distribution Management
Systems) where information
about the outages are stored
(start/end times, equipment that
failed, power shortage, number
of client affected...)
the fact of performing
simulations with electrical tools.
These analyses consist on
evaluating scenarios with
different level of automation.
Group Description
Actor Name
Actor Type
Asset Investment Planning
Component
Layer Actor
Actors in Enterprise Zone
Actor Description
this Use Case
Asset investment planning involves strategy
definition and prioritisation, maintenance
strategy planning, risk management,
programme management and decisionmaking. It drives the condition, configuration,
performance, operating costs, and flexibility of
the asset base, with the aim of maximising
value.
the process of analysing the
result of the simulation (a curve
of QoS vs Investment)
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Use Case Conditions
Triggering Event
Pre-conditions
Need for taking a
decision about the
amount of
automation level for
certain MV network
zone.
Asset Investment Planning (AM-AIP)
Assumption
Availability of
historical records
of outages, quality
indexes and cost
for field operations
for the selected
MV zone.
3.3 References
References
Status
Impact on Use Case
No.
Reference
Type
Reference
1
Regulatory
constraint
RD 1955/2000 from
December 1st
Release 2000
2
Regulatory
constraint
RD 1634/2006 from
December 29th
Release 2006
3
Regulatory
constraint
RD 222/2008
Release 2008
4
Regulatory
constraint
Orden ICT/3801/2008
Release 2008
5
Regulatory
constraint
Orden ITC/2524/2009
Release 2009
6
Report
Ministry web page
Web page
Business Layer –
Definition of QoS
indexes and their
regulatory limits
Business Layer –
update of some QoS
limits
Business Layer –
description
remuneration
methodology for
DSO activities
Business Layer –
incentives/penalties
for QoS
Business Layer –
for losses
Business Layer –
Spanish data base
of QoS
Originator/
Organisation
Link
Ministry/Syste
m Operator
http://www.bo
e.es/
Ministry/Syste
m Operator
http://www.bo
e.es/
Ministry/Syste
m Operator
http://www.bo
e.es/
Ministry/Syste
m Operator
http://www.bo
e.es/
Ministry/Syste
m Operator
http://www.bo
e.es/
Ministry/DSO
https://oficinav
irtual.mityc.es/
eee/Conexion
/listadoNotas.
aspx
Level of Depth
Individual Use Case
Prioritization
Operational track 2
European level
Viewpoint
Technical
MV automation, QoS indexes
4
No.
Scenario Name
1
Quality Index Analysis
Scenario Conditions
Primary actor
Triggering Event
Pre-Condition
Network
Operation
The outage
consequences are
An outage happens
in the network
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Post-Condition
QoS indexes and
outage ratios are
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No.
Scenario Name
2
Switching Simulation
3
Decision Support
Scenario Conditions
Primary actor
Triggering Event
Statistics and
Reporting
Network
Operation
Simulation
Asset
Investment
Planning
Need for simulating
different levels and
location of
automation.
End of the simulation
of automation
scenarios
DISCERN_WP4_D4.2_280114_v3.0
Pre-Condition
Post-Condition
storage
calculated
-The model of the
network is available
with the capacity to
simulate different
scenarios.
-Availability of
average cost units for
field operations
-Availability of
average fault rates
The curve with
Investment vs QoS
achieved per each
scenario is available
Investment vs
QoS achieved per
each scenario is
calculated.
A compromise
solution for the
level of
automation is
taken based on
technical,
economical and
regulated aspects.
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Scenario Name :
Step Event
No.
Scenario
Description of
Process/Activity
Service
Information
Exchanged
Quality Index Analysis
1
Periodically
Get outage average ratio
Outage average
ratios are already
made available to
identify more
critical network
zones prior
simulation.
INTERNAL
PROCESS
Network Operation
Network Operation
Statistics and
Reporting
QoS
Switching Simulation
2
Punctual
Ask for simulation
GET
Asset Investment
Planning
Network Operation
Simulation
Identification of
the MV network
sub-area to be
evaluate
3
Punctual
Ask for information
GET
Network Operation
Simulation
Network Operation
Statistics and
Reporting
Request for
information
4
Punctual
Send information
A simulation of
different
automation
scenarios is
requested to get
an investment vs
QoS curve.
Average values of
fault rates, quality
of service are
requested
The request
information about
average values
are sent
SHOW
Network Operation
Network Operation
Simulation
5
Iterative
Algorithm operation
The algorithm to
evaluate the
impact on
investment and
QoS of different
strategies of
automation is
evaluated
INTERNAL
PROCESS
Network Operation
Simulation
Network Operation
Simulation
-Average cost
units for field
operations
-Average fault
rates
Investment vs
QoS curve
Decision Support
6
Punctual
Send simulation results
SHOW
Network Operation
Simulation
Asset Investment
Planning
Investment vs
QoS curve
7
Decision taken process
Results from the
simulation are
sent
Based on the
simulation results
and other criteria
a compromise
INTERNAL
PROCESS
Asset Investment
Planning
Asset Investment
Planning
Compromise
level of
automation, type
of equipment
Punctual
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solution for the
level of
automation is
decided
and proposal of
location
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5
Name of Information
Exchanged
QoS
Identification of the MV network
sub-area to be evaluate
Request for information
-Average cost units for field
operations
-Average fault rates
Investment vs QoS curve
Compromise level of automation,
type of equipment and proposal
of location
7
Results of the analyses of outages and their
impact.
Area of the MV network over which it is
desire to calculate the optimal level of
automation.
Signal to inform the receiver about the need
of information.
Information about:
-average cost units for typical actuation in
field regarding automation (mainly
installation)
-average fault rates in terms of type of
installation: number of SS, length of cable
and aerial line.
Group of pair of data, one per each scenario
of level of automation. That is, investment
required to achieve certain Quality of
Service objective.
% of automation to be implemented,
number and type of automation equipment
and proposed location in terms of rates
based on nº of SS or length of lines/cables
Common Terms and Definitions
Term
Definition
vs
SS
MV
ASIDI
QoS
NO-OST
OP-SIM
AM-AIP
DSO
versus
Secondary Substation
Middle Voltage
Average System Interruption Duration Index
Quality of Service
Network Operation Statistics and Reporting
Network Operation Simulation
Asset Investment Planning
Distribution System Operator
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3.1.2.2
DISCERN_IBR_Leader_B6_SGAM
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3.1.3.
DISCERN_RWE_Leader_B6
The solution proposed by RWE is called “Wide Area Control” and its objective is to improve MV
network monitoring and operation by means of a Wide Area Control system that automatically controls
the position of tap power transformers in secondary substations.
3.1.3.1
1
DISCERN_RWE_Leader_B6_Use Case
Name of Use Case
ID
Domain(s)/Zone(s)
DISCERN_RWE_Leader_B6
Distribution / Process, Field,
Station, Operation
Enhanced monitoring and control of MV/LV network– Wide
area control
Version No.
Date
Name
Author(s)
29.11.2013
RWE
Version Management
Changes
Approval Status
final
Scope
Permanent measuring of voltage values at critical measuring points in low and medium
voltage grid which were identified before the wide area control is set up. Neuralgic
measuring points are defined as nodes which show the highest variation of nominal
voltage in normal operation and fault. A central control station is part of the system.
Measuring points at neuralgic points in the LV/MV-network provide data about the voltage
status. In the primary substation a controller calculates the appropriate setting of the tapchanger. Thus the tap-changer always reacts on the current grid condition in order to keep
the voltage within the required limits. In the image below an example of a wide area
control setup with 5 measuring points is given.
110 / 20 kV
„Wide area
controller“
U
U
…
…
U
20 / 0,4 kV
…
U
U
(Final Report “Future Energy Grids”, Page 206, Figure 159)
Objective
Reconstitution of grid monitoring under the presence of high renewable generation and
wide area control on MV level. The growing feed-in of energy by renewables creates
voltages fluctuation. This happens especially in rural regions with higher grid lengths. The
main objective of wide area control is to stabilize these voltage fluctuations in the low
voltage grid in order to meet the limits required by the EN 50160 (10% variation of nominal
voltage). The approach of the wide area control differs from typical existing solutions. The
target is not to control one special node to a constant value but to control a set of nodes in
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a voltage range.
Short Description
This Use Case describes a system that helps stabilize voltages in medium and low voltage grids. With the help of the “wide area
control” the voltage level of neuralgic measuring points is collected and tap changers at primary substations are automatically
operated based on this information.
Traditionally the tap changer position at the primary substation is regulated based on a voltage measurement at secondary side
of the transformer. Therefore, it is possible that the transformer tap position is not changed even though the voltage violates the
voltage band limits at some nodes in the downstream grid (low voltage grid). This happens because in the traditional system, the
controller of the tap changer in the primary substation has no information about the low voltage grid state. A Wide Area Control
(WAC) system can be used to resolve this problem. In this system more measuring points in the downstream grid are included
in the derivation of the ideal tap changer position.
To implement a wide area control system a determination of the neuralgic nodes has to be done. The neuralgic nodes are
identified by load calculation with several scenarios (maximum feed in with low load / minimum feed in with high load),
simulations, operational experience, load forecasts and measurements in the grid. These nodes have to be equipped with
voltage sensors. These sensors are connected via ICT to the SCADA system in order to include the measured values in the
algorithm which determines the optimal tap changer position of the primary substation.
At the beginning of the Algorithm the measured values are checked. This is done to avoid that a node with no measured voltage
is used in the algorithm. After that the maximum voltage difference between the nodes voltage and the nominal voltage is
calculated. With that a violation of the voltage profile is determined. If there is a violation the controller will change the tap
position. If there are over voltages and under voltages the controller will act in order to fix the overvoltage. Before a switching
operation is done the controller has to check if the maximum position of the tap changer already is reached. The algorithm is
shown in the image below.
Model of the Wide Area Control algorithm
The wide area control process consists of three major parts:
1. Collecting data from measuring points
- measuring points have to be defined before the wide area control system is implemented
- voltages are measured at neuralgic nodes in the medium voltage grid. Neuralgic nodes are those in which a high
deviation of the nominal voltage in normal operation or fault could be predicted.
- the neuralgic nodes could be identified by load flow calculation or measurements. Neuralgic nodes could be
measuring points on secondary substations, customer connection points or middle voltage generation plants with
existing voltage measurement and communication infrastructure. In case of secondary substations the voltages are
measured on the secondary side. The values of primary side voltages are calculated by the IED located in the
secondary substation, based on the transformer specifications.
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2. Transferring and processing the data
- the collected data is transferred to a central Unit via GPRS, Tetra Radio Systems or DSL
- Protocols for the data transfer are IEC 61850-8-1, IEC 60870-5-101/-104
- the data is processed and a set value is calculated
- switching tap position operations are derived, as shown in the model of the Wide Area Control algorithm.
- switching orders are transferred to Tap Changer
3. Switching operations
- the central voltage regulator initiates the operations to change transformer tap position
The following image shows the principal structure of data-acquisition and -transfer in the wide area control system.
Simulations have shown that the Wide Area Control system is particularly advantageous in grids with homogeneous load. In
these scenarios, the WAC is can decrease voltage band from 10 % Un to 5%.
1.5 General Remarks
General Remarks
2
Diagrams
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3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Process
Actor Name
Actor Type
Grid
Component
Layer Actor
Component
Layer Actor
Voltage Sensor
Tap Changer
Component
Layer Actor
Actor Name
Actor Type
IED
Component
Layer Actor
Actor Name
Actor Type
Data Aggregator
Component
Layer Actor
Power systems including power generation,
transmission and MV/LV distribution
continuously report current dynamic status of
voltage
Mechanism for changing transformer winding
tap positions.
MV / LV Grid
Actors in Field Zone
Actor Name
Actor Type
Automatic Tap Changer
Controller
Network Operation
Monitoring
Voltage Sensors are located in
the measuring points
The Tap Changer is controlled
by the Automatic Tap Changer
Controller in this Use Case
Actor Description
this Use Case
multifunction meters, digital relays, controllers)
Remote Control Point in the
neuralgic points. It receives
measurements from the
sensors, calculates a new
voltage value and sends this
data to the Data Aggregator
Actors in Station Zone
Actor Description
this Use Case
devices.
The Data Aggregator gets the
voltage values from the IED,
aggregates them and forwards
it to the Automatic Tap Changer
Controller
Actors
Group Description
Grouping
Operation
this Use Case
Actors
Group Description
Grouping
Station
Actor Description
Actors
Group Description
Grouping
Field
Actors in Process Zone
Actor Description
this Use Case
Component
Layer Actor
Device or application which operates the tap
changer automatically according to given
setpoints or by direct operator commands
(manual mode).
Component
Layer Actor
Provides the means for supervising main
substation topology (breaker and switch state)
and control equipment status. It also provides
the utilities for handling network connectivity
and loading conditions. It also makes it
possible to locate customer telephone
complaints and supervise the location of field
crews.
Application including the
algorithm that calculates the
new Tap Position from the
voltage measurements sent by
the IEDs in the neuralgic points.
This includes a GUI showing
the current state of the voltages
in a single line diagram.
In this use case the network
operation monitoring enables
the DSO to monitor the values
which are measured within the
wide area control system.
Use Case Conditions
Triggering Event
Pre-conditions
Voltage changes
within limits
Grid
Assumption
The
communication
between Grid,
Process Sensing
Device, RTU and
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Over/Under voltage
outside threshold is
detected.
IED
Automatic Tap
Changer
Controller could
be established
Communications
can be established
from IED up to
Automatic Tap
Changer
Controller
3.3 References
References
Status
No.
Reference Type
Reference
1
document
2
conference paper
Netztechnischer Standard
Übergreifende
Sekundärtechnik für Nieder
und Mittelspannung
B. Gwisdorf, T. Borchard, T.
Hammerschmidt,C. Rehtanz,
“Technical and economic
evaluation of voltage
regulation strategies for
distribution grids with a high
amount of fluctuating
dispersed generation units”,
IEEE Conference, V1 Boston,
September, 27-29, 2010
Impact on Use
Case
Originator/
Organisation
Draft
RWE
final
RWE
Link
-
Level of Depth
Individual Use Case
Prioritization
Operational track 2
European
Viewpoint
Technical
Wide Area Control, Voltage regulation, Automatic Tap Changer Controller, ICT
4
No.
Scenario Name
Primary
actor
Scenario Conditions
Triggering Event
Pre-Condition
1
Measuring
Voltage
Sensor
Voltage Sensor sends
voltage measurements to
IED
Voltage Sensors and
IED are running and
able to measure the
voltage
2
Management
Data
Aggregator
Data aggregator
aggregates voltage
values received from IED.
Communication can
be established from
Data Aggregator to
Automatic Tap
Changer Controller
and Network
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Post-Condition
Data aggregator
receives
calculated
medium voltage
values from the
IED
Calculated
Voltage values
are received at
Automatic Tap
Changer
Controller and at
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No.
Scenario Name
Primary
actor
Scenario Conditions
Triggering Event
Pre-Condition
3a
Network Displays
Network
Operation
Monitoring
Network Operation
Monitoring receives
voltage values from Data
Aggregator
Operation Monitoring.
Data Aggregator and
Automatic Tap
Changer Controller
and Network
Operation Monitoring
are up and running.
Network Operation
Monitoring can create
displays of the
network
3b
Operation Alarm
Supervision
Automatic
Tap
Changer
Controller
The Automatic Tap
Changer Controller
detects under/over
voltage faults in the Grid
Threshold values for
the voltages in
measuring points are
predefined.
4
Automatic Controls
Automatic
Tap
Changer
Controller
The Automatic Tap
Changer Controller
detects an under/over
voltage
Communication can
be established from
Automatic Tap
Controller to Tap
Changer. Automatic
Tap Changer
Controller and Tap
Changer are up and
running
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Post-Condition
Network
Operation
Monitoring.
Current state of
the network
(voltages) is
shown in the
Network
Operation
Monitoring display
Under/over
voltage faults
detected in the
Network Control
application
Tap position is
reconfigured to
resolve
under/over
voltage faults
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Scenario Name :
Step Event
No.
Measuring
1
Continuously
Scenario
Description of
Process/Activity
Service
Information
Exchanged
Measure voltages from the
Grid
Voltage Sensor
measures
voltages in
neuralgic points of
the Grid
Voltage Sensor
reports the
voltage
measurements to
IED
IED calculates
medium voltage
values from the
low and medium
voltage
measurements
received from
Voltage Sensor
When a voltage
value changes
more than a
predefined value,
the IED reports
this value to the
Data Aggregator
REPORT
Grid
Voltage Sensor
Voltage
measurements
REPORT
Voltage Sensor
IED
Voltage
measurements
INTERNAL
PROCESS
IED
IED
Calculated
voltage values
REPORT
IED
Data Aggregator
Calculated
voltage values
Data aggregator
aggregates
voltage values
received from IED
The Data
Aggregator
forwards
aggregated
voltage values to
Network
Monitoring
Operation
The Data
Aggregator
INTERNAL
PROCESS
Data Aggregator
Data Aggregator
Aggregated
voltage values
REPORT
Data Aggregator
Network Monitoring
Operation
Aggregated
voltage values
REPORT
Data Aggregator
Automatic Tap
Changer Controller
Aggregated
voltage values
2
Periodically
Report voltage
measurements to IED
3
Periodically
Calculate medium voltage
values from voltage
measurements
4
Voltage value
changed more
than a
predefined
threshold
Report voltage values to
Data Aggregator
5
Periodically
Aggregate voltage values
at station level
6a
Periodically
Transfer of aggregated
voltage values to Network
Monitoring Operation
6b
Periodically
Transfer of aggregated
voltage values to
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Network Displays
7a
Periodically
Controller
forwards
aggregated
voltage values to
Automatic Tap
Changer
Controller
Present current state of the
network in screen displays
Network
Operation
Monitoring
presents current
state of the
network in screen
displays
INTERNAL
PROCESS
Network Operation
Monitoring
Network Operation
Monitoring
Network
displays
The Automatic
Tap Changer
Controller detects
voltage dead band
violations
The Automatic
Tap Changer
Controller reports
the voltage dead
band violations
that has detected
INTERNAL
PROCESS
Controller
Automatic Tap
Changer Controller
Voltage dead
band violation
REPORT
Controller
Network Operation
Monitoring
Voltage dead
band violation
The Automatic
Tap Changer
Controller
calculates the
optimal tap
position
The Automatic
Tap Changer
Controller
transfers the
optimal tap
position to the Tap
Changer
The Tap Change
Controller
changes the
optimal Tap
position
INTERNAL
PROCESS
Controller
Automatic Tap
Changer Controller
Tap position
CHANGE
Controller
Tap Changer
Tap position
CHANGE
Tap Changer
Grid
Tap position
7b
Periodically
Detect voltage dead band
violation
8
A voltage dead
band violation is
detected
Automatic Controls
9
Periodically
Report voltage dead band
violation to Network
Operation Monitoring
Calculate optimal tap
position
10
current tap
position is not
the optimal one
Send command to Tap
Changer to change tap
position
11
Tap Changer
has received the
command from
Automatic Tap
Changer
Controller
Change tap position
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5
Name of Information
Exchanged
Voltage measurements
Calculated voltage values
Aggregated voltage values
Network displays
Tap Position
Measurement indicating the analogue value
of the voltage in a particular point of the
distribution network. This information object
should clearly identify which voltage
measures within the network. Moreover it
should include the timestamp, source, and
information about the quality of the
measurement.
Calculated voltage value at the neuralgic
node for the middle voltage
All calculated voltage values of neuralgic
points aggregated
Representation of current voltages in a
single line diagram of the network that is
being controlled
Command defining the new position of a
power transformer tap. This information
object should clearly identify the power
transformer tap. It also should include
precise information about the new position
and the source of the command.
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3.1.3.2
DISCERN_RWE_Leader_B6_SGAM
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3.1.4.
Summary
Three different Use Cases (with their corresponding SGAM models) have been proposed by Leading
DSOs for sub-functionality “B6 – Enhanced monitoring and control of MV/LV network”.
•
The Use Cases proposed by GNF and RWE are aimed at improving MV monitoring and
control by installing new automation systems. Whereas in GNF’s Use Case the operation is
carried out by a human operator, who can send commands to change switch positions from
remote control centres, in RWE’s Use Case the operation is carried out automatically by an
Automatic Tap Changer Controller that controls the tap position of power transformers in
secondary substations. Figure 3-2 compares the functional architectures of both solutions
highlighting the main differences explained above.
Figure 3-2. Comparison between the functional architectures proposed by GNF and RWE in sub-functionality B6
•
The Use Case proposed by IBR has different perspective and scope compared with the Use
Cases from GNF and RWE. IBR’s Use Case takes advantage of a data base containing
historical data on fault rates and costs of automation units to calculate “Investment vs QoS”
curves, which help DSOs to decide the optimal level of automation in their networks.
Therefore, IBR’s Use Case and SGAM model are focused on Operation and Enterprise
applications and do not include Process, Field, Station actors and functions, since no new
automation systems are implemented in this solution.
Table 3-1 shows the list of new actors used in this sub-functionality that were not included to the
original lists. As can be seen, all these new actors refer to components in automation or monitoring
systems. This is because the original lists of actors were based on standards (such as CIM IRM [IEC
61968-1] or Entso-e Role Model [ENTSOE-RM) which are not focused on automation solutions in
process, field or station zones.
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Table 3-1. New actors added for sub-functionality B6
Actor
Description
Controller
Current Sensor
Device or application which operates the tap changer automatically according to given set
points or by direct operator commands (manual mode)
Devices, which are spread on the Grid lines, continuously reporting dynamic status of
current
Device that indicates the presence and direction of a fault current in the cables where the
device is located
Mechanism for changing transformer winding tap positions
Tap Changer
Voltage Sensor
voltage
However, it was not necessary to add new functions in the original list for this sub-functionality. This
means that, even though GNF’s and RWE’s Use Cases focused on automation and monitoring
systems at process, field and station zones, the abstract components defined in the CIM IRM [IEC
61968-1] were sufficient to represent the technical functions realized within these systems.
Finally, in regards to the Communication and Information Layers of the SGAM models, it is worth
noting that only three international standards are used in the solutions proposed by Leaders: IEC
60850-4-101, IEC 60850-4-104 and IEC 61850. All of these standards are used for the information
exchanges between field devices and controllers or SCADA applications at operation zone. Further,
most of the data models at Information Layer are proprietary data models. A detailed analysis on these
issues will be elaborated in tasks T2-3.3 and T5.3 in order to provide recommendations to the DSOs
and, if necessary, to the standardization bodies with the aim of improving interoperability in European
distribution networks.
3.2. B7bd – Real time monitoring of LV grid
The same as sub-functionality B6, sub-functionality B7bd refers to solutions aimed at enhancing
monitoring and control of power flows and voltages. However, whereas B6 was more focused on MV
networks, B7bd focuses on real time monitoring of LV networks. Figure 3-3 shows the knowledge
sharing carried out in DISCERN for this sub-functionality. As can be seen, three Leaders (GNF, RWE
and SSEPD) exchange their knowledge about the sub-functionality with one Learner, IBR.
Figure 3-3. Knowledge sharing among DSOs in sub-functionality B7bd
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3.2.1.
DISCERN_GNF_Leader_B7bd
The solution proposed by GNF for this sub-functionality is called “LV monitoring for future power
quality analysis”. The objective of GNF’s solution is to collect and store electric measurements, events
and alarms generated by Intelligent Electronic Devices (IED) in LV networks. This information could be
used in the future for performing power quality analysis with the aim of improving LV network
operation.
3.2.1.1
1
DISCERN_GNF_Leader_B7bd_Use Case
Domain(s)/Zone(s)
Name of Use Case
ID
DISCERN_GNF_Leader_B7bd
Distribution /Process, Field,
Station, Operation
Real time monitoring of LV grid – LV monitoring for future
power quality analysis
Version No.
Date
Name
Author(s)
15.11.2013
GNF
Version Management
Changes
Approval Status
final
Scope
Objective
Monitor voltages and currents in LV distribution grids, and compute and supervise Power
Quality indices
Monitor power quality of the LV distribution grid in order to gather information for further
actions to maintain currents, voltages and Power Quality indices within permissible levels
Short Description
This Use Case deals with the analysis of continuity of service and power quality issues in the LV side of secondary substations,
and generates related signals and alarms.
Quality of supply is monitored by the means of intelligent electronic devices (IED) called LV supervisors. These collect voltage
and current measures from sensors in the LV side of secondary substations, perform registrations of energy, measures and
events, and generate alarms when some voltages or currents are out of margins.
The main steps of this sub-functionality are:
1.
Voltages and currents are measured with LV sensors from the LV output cables of secondary substations.
2.
LV supervisor collects these data from sensors and perform calculations on power flows as well as power
quality issues, generating also events reports:
Energy registration (similar to meters), absolute and incremental values
•
Active energy in both directions
•
Reactive energy in four quadrants
Registration of real and calculated measures
•
•
Active P and reactive Q calculation
•
MV voltages calculation
•
Neutral current
•
Symmetric components
•
Voltage unbalances
•
Harmonic registration and THD
Events reports
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•
•
•
•
•
•
•
3.
4.
Supply interruptions
Under/over voltages
Overloading
Load unbalances
Neutral overcurrent
Loss of neutral
Loss of LV phases
Selected events will generate alarms in LV supervisor that are spontaneously sent to upper systems, up to the
Distribution Management System.
LV data monitoring collected is periodically sent to upper systems. Further corrective actions can be taken in
order to prevent malfunction.
1.5 General Remarks
General Remarks
Specific preventive or corrective actions are out of the scope of this sub-functionality. LV data is recorded and stored in a
repository making it available for further studies on power quality.
2
Diagrams
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3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Process
Actor Name
Actor Type
LV Grid
System
Current Sensor
Component
Voltage Sensor
Component
Grouping
Field
Actor Type
IED
Component
Grouping
Actor Type
Data Aggregator
Component
Grouping
Low Voltage (LV) distribution network.
Process actuators (e.g. switches or tap
distribution network are represented as
separated Actors
continuously report dynamic status of current.
continuously report dynamic status of voltage.
LV output cables of secondary
transformers are sensed (LV
distribution board input)
LV current sensors located at
LV output of transformers.
LV voltage sensors located at
LV output of transformers
Actor Description
this Use Case
multifunction meters, digital relays,
controllers)
One LV supervisor (IED)
located at the secondary
substation collects
measurements from sensors
and computes power flows and
Power Quality indices.
Actor Description
this Use Case
devices.
One concentrator located in
secondary substation collects
data from LV supervisor and
Smart Meters, and sends it to
upper systems
Group Description
Actor Name
Actor Type
Meter Data Management
System
System
Distribution Management
System
this Use Case
Group Description
Actor Name
Enterprise
Actor Description
Group Description
Actor Name
Station
System
Actors in Enterprise zone
Actor Description
this Use Case
Meter Data Management System is a system
or an application which maintains all
information to be able to calculate the energy
bill for a customer based on the meter data
retrieved from AMI head end(s). The energy
bill information is typically forwarded to
consumer relationship and billing systems.
Reports from LV supervisors
(and also from smart meters)
are collected and stored in a
repository (SATURNE), making
these data available for other
applications.
The Meter Data Management systems also
collects, validates, stores and distributes
readings and event-related data from other
end devices to other enterprise functions and
systems, supporting diverse end-use
applications including but not limited to load
management, load forecasting, demand
response, outage management, asset
management and distribution network
planning and maintenance.
DMS SCADA System refers to the real-time
information system and all the elements
needed to support all the relevant operational
activities and functions used in distribution
automation at dispatch centers and control
rooms.
DMS will collect data from
supervisors, although not in
real time, for further off-line
analysis of data that will help to
identify corrective actions to
improve power quality and
security.
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Use Case Conditions
Triggering Event
Pre-conditions
LV Grid
Periodically
Selected events that
generate alarms
IED
Assumption
Voltages and
currents are within
limits.
Communications
can be stablished
from LV
supervisor (IED)
through Data
Aggregator up to
Meter Data
Management
System.
Communications
can be stablished
from LV
supervisor (IED)
up to Meter Data
Management
System.
3.3 References
No.
Reference
Type
Reference
Status
Standard
Standard
IEC 62056
(DLMS/COSEM)
IEC 62051-1
Draft
Specification
PRIME Specification
revision v1.3.6
References
Impact on
Use Case
Originator/
Organisation
Link
IEC
Release
2004
Draft
IEC
PRIME
Alliance
http://www.primealliance.org/wpcontent/uploads/2013/04/PRIMESpec_v1.3.6.pdf
Level of Depth
Individual Use Case
Prioritization
Operational track 1 3
European
Viewpoint
Technical
LV supervision, network monitoring, power quality
3
Operation track 1 means that “the sub-functionality will be implemented as a part of WP7 in one or more of the
demo sites [D1.1]
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4
Scenario Conditions
Triggering Event
No.
Scenario Name
Primary
actor
1
Measuring
Voltage
Sensor,
Current
Sensor
Periodically
Communication can
be established from
sensors to IED
2
Sequences and Imbalances
IED
Periodically
Measures have been
collected so that
sequences and
imbalance indices can
be computed.
3
Harmonics and
Interharmonics
IED
Periodically
Measures have been
collected so that
Harmonics/Interharmo
nicsindices can be
computed.
Harmonics & THD
indices are
calculated
4
Operator and Event Logs
IED
Periodically
Measures have been
collected so that
power quality events
can be identified.
Events reported
5
Alarm Supervision
IED
Some selected event is
out of limits.
Alarm is
generated to be
sent to DMS
6
Process and network Data
Management
Data
Aggregator
Periodically
7
Information for Planning
Meter Data
Manageme
nt System
Periodically /
Spontaneously when
some selected event is
out of limits
Threshold values are
predefined.
Communication can
be established from
IED up to the Meter
Data Management
System
Communication can
be established from
IED up to the Meter
Data Management
System
Meter Data
Management System
is up and running
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Pre-Condition
Post-Condition
IED (LV
supervisor)
collects measures
(voltage, current)
from LV sensors
Sequence and
imbalance indices
are calculated
Collected
measures and
event reports are
sent to DMS
Collected data is
stored for further
analysis
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Scenario Name :
Step Event
No.
Scenario
Description of
Process/Activity
Service
Information
Exchanged
Measuring
1a
Periodically
Measure voltage in LV Grid
REPORT
LV Grid
Voltage Sensor
Voltage
measurement
1b
Periodically
Measure current in LV Grid
REPORT
LV Grid
Current Sensor
Current
measurement
2a
Periodically
Report voltage
measurements to IED
REPORT
Voltage Sensor
IED
Voltage
measurement
2b
Periodically
Report current
measurements to IED
REPORT
Current Sensor
IED
Current
measurement
3a
Periodically
Measurement calculation
of power flows and MV
side voltages
INTERNAL
PROCESS
IED
IED
Active P and
reactive Q
power flows. MV
voltages.
3b
Periodically
Registration of active and
reactive energy
INTERNAL
PROCESS
IED
IED
Active and
reactive energy
4a
Periodically
Report voltage
Aggregator
REPORT
IED
Data Aggregator
Voltage
measurement
4b
Periodically
Report current
Voltage Sensors
get
measurements
from LV Grid
Current Sensors
get
measurements
from LV Grid
Voltage sensors
make voltage
measurements
available to IED
Current sensors
make current
measurements
available to IED
Active P and
reactive Q power
flows, and voltage
at the MV side of
the transformer
are calculated by
IED from voltage
and current
measures.
Active energy in
both directions
and reactive
energy in four
quadrants, are
calculated by IED
from voltage and
current measures.
Voltage
measurements
are sent from IED
to Data
Aggregator,
Current
measurements
REPORT
IED
Data Aggregator
Current
measurement
DISCERN_WP4_D4.2_280114_v3.0
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Aggregator
4c
Periodically
Report power flows and
MV voltages to Data
Aggregator
4d
Periodically
Report active and reactive
energy to Data Aggregator
5a
Periodically
Sequence and imbalances
calculations
Harmonics and Interharmonics
5b
Periodically
Harmonics calculation
Operator and Event Logs
5c
Periodically
Events calculation and
identification
5d
Selected events
Alarm generation
are out of
threshold
are sent from IED
to Data
Aggregator
Active P and
reactive Q power
flows and MV
voltage
calculations are
sent from IED to
Data Aggregator
Active and
reactive energy
are sent from IED
to Data
Aggregator
REPORT
IED
Data Aggregator
P,Q, MV
voltages
REPORT
IED
Data Aggregator
Active and
reactive energy
Neutral current,
symmetric
components and
voltage
unbalances are
calculated by the
IED from voltage
and current
measures.
INTERNAL
PROCESS
IED
IED
Neutral current,
Symmetric
components,
Voltage
unbalances
Harmonics &THD
are calculated by
the IED from
voltage and
current measures.
INTERNAL
PROCESS
IED
IED
Harmonics &
THD
Supply
interruptions,
Under-over
voltages,
Overloading, Load
unbalances,
Neutral
overcurrent, Loss
of neutral, Loss of
MV phase are
calculated by the
IED from
measurements.
INTERNAL
PROCESS
IED
IED
Event reports:
Supply
interruptions,
Under-over
voltages,
Overloading,
Load
unbalances,
Neutral
overcurrent,
Loss of neutral,
Loss of MV
phase
Selected events in
IED generate
alarms.
INTERNAL
PROCESS
IED
IED
Alarm
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6a
Alarm generated
in IED
Report alarms to Data
Aggregator
7a
Data Aggregator
received reports
on alarms from
IED
Report alarms to Meter
Data Management System
8a
Meter Data
Report alarms to
Management
System received
System
reports on
alarms from Data
Aggregator
6b
Periodically
Report sequence and
imbalances calculations to
Data Aggregator
6c
Periodically
Report harmonics
calculations to Data
Aggregator
6d
Periodically
Report Event reports to
Data Aggregator
7b
Periodically
Report voltage
measurements to Meter
7c
Periodically
Report current
measurements to Meter
IED reports
alarms to Data
Aggregator
Data Aggregator
reports alarms to
Meter Data
Management
System
Meter Data
Management
System reports
alarms to DMS
REPORT
IED
Data Aggregator
Alarm
REPORT
Data Aggregator
Meter Data
Management System
Alarm
REPORT
Meter Data
Management System
DMS
Alarm
Neutral current,
symmetric
components and
voltage
unbalances are
sent from IED to
Data Aggregator
Harmonics and
THD calculations
are sent from IED
to Data
Aggregator
Event reports are
sent from IED to
Data Aggregator
REPORT
IED
Data Aggregator
Neutral current,
Symmetric
components,
Voltage
unbalances
REPORT
IED
Data Aggregator
Harmonics and
THD
REPORT
IED
Data Aggregator
Voltage
measurements
are sent from
Data Aggregator
to Meter Data
Management
System
Current
measurements
REPORT
Data Aggregator
Meter Data
Management System
Event reports:
Supply
interruptions,
Under-over
voltages,
Overloading,
Load
unbalances,
Neutral
overcurrent,
Loss of neutral,
Loss of MV
phase
Voltage
measurement
REPORT
Data Aggregator
Meter Data
Management System
Current
measurements
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7d
Periodically
MV voltages to Meter Data
Management System
7e
Periodically
Report Active and Reactive
energy to Meter Data
Management System
7f
Periodically
Report sequence and
System
7g
Periodically
Report harmonics
calculations to Meter Data
Management System
7h
Periodically
System
are sent from
Data Aggregator
to Meter Data
Management
System
Active P and
reactive Q power
flows and MV
voltage
calculations are
sent from Data
Aggregator to
Meter Data
Management
System
Active and
Reactive energy
are sent from
Data Aggregator
to Meter Data
Management
System
Neutral current,
symmetric
components and
voltage
unbalances are
sent from Data
Aggregator to
Meter Data
Management
System
Harmonics and
THD calculations
are sent from
Data Aggregator
to Meter Data
Management
System
Event reports are
sent from Data
Aggregator to
Meter Data
Management
System
REPORT
Data Aggregator
Meter Data
Management System
P,Q, MV
voltages
REPORT
Data Aggregator
Meter Data
Management System
Active and
Reactive energy
REPORT
Data Aggregator
Meter Data
Management System
Neutral current,
Symmetric
components,
Voltage
unbalances
REPORT
Data Aggregator
Meter Data
Management System
Harmonics and
THD
REPORT
Data Aggregator
Meter Data
Management System
Event reports:
Supply
interruptions,
Under-over
voltages,
Overloading,
Load
unbalances,
Neutral
overcurrent,
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8b
Periodically
Report voltage
measurements to
System
8c
Periodically
Report current
measurements to
System
8d
Periodically
MV voltages to Distribution
Management System
8e
Periodically
Report Active and Reactive
energy to Distribution
Management System
8f
Periodically
Report sequence and
System
8g
Periodically
Report harmonics
calculations to Distribution
Management System
8h
Periodically
System
Voltage
measurements
are sent from
Meter Data
Management
System to DMS
Current
measurements
are sent from
Meter Data
Management
System to DMS
Active P and
reactive Q power
flows and MV
voltage
calculations are
sent from Meter
Data
Management
System to DMS
Active and
reactive energy
are sent from
Meter Data
Management
System to DMS
Neutral current,
symmetric
components and
voltage
unbalances are
sent from Meter
Data
Management
System to DMS
Harmonics and
THD calculations
are sent from
Meter Data
Management
System to DMS
Event reports are
sent from Meter
Data
Management
Loss of neutral,
Loss of MV
phase
Voltage
measurement
REPORT
Meter Data
Management System
DMS
REPORT
Meter Data
Management System
DMS
Current
measurements
REPORT
Meter Data
Management System
DMS
P,Q, MV
voltages
REPORT
Meter Data
Management System
DMS
Active and
Reactive energy
REPORT
Meter Data
Management System
DMS
Neutral current,
Symmetric
components,
Voltage
unbalances
REPORT
Meter Data
Management System
DMS
Harmonics and
THD
REPORT
Meter Data
Management System
DMS
Event reports:
Supply
interruptions,
Under-over
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System to DMS
Information for Planning
9
Periodically /
Spontaneously if
alarm is received
Store measurements,
energy flows, events and
alarms
Measurements,
energy flows,
events and alarms
are stored in
Meter Data
Management
System
voltages,
Overloading,
Load
unbalances,
Neutral
overcurrent,
Loss of neutral,
Loss of MV
phase
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
DISCERN_WP4_D4.2_280114_v3.0
Voltage
measurement,
Current
measurements,
P,Q, MV
voltages, Active
and Reactive
energy,
Neutral current,
Symmetric
components,
Voltage
unbalances,
Harmonics and
THD, Supply
interruptions,
Under-over
voltages,
Overloading,
Load
unbalances,
Neutral
overcurrent,
Loss of neutral,
Loss of MV
phase
Page 77 of 181
5
Name of Information
Exchanged
Voltage measurement
Current measurement
Active P and reactive Q power
flows, and MV voltage
Neutral current, Symmetric
components, Voltage unbalances
Harmonics and THD
Events reports
Alarms
Measurement indicating voltages in the
three phases of the LV output of distribution
transformers, with timestamp.
Measurement indicating currents in the
three phases of the LV output of distribution
transformers, with timestamp.
Active and reactive power flows calculated
in IED from voltage and current
measurements. Voltage at the MV side of
the transformer is also calculated from LV
voltages and currents.
Sequence and imbalances indices
calculated by IED from voltage and current
measurements.
Harmonics and Total Harmonic Distortion
calculated by IED from voltage and current
measurements
Event reports generated from previously
calculated measurements and power quality
calculations.
A configurable selection of events generate
alarms in IED.
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3.2.1.2
DISCERN_GNF_Leader_B7bd_SGAM
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3.2.2.
DISCERN_RWE_Leader_B7bd
The solution proposed by RWE for this sub-functionality is called “Smart Operator”. It is based on a
Station Controller (the Smart Operator) capable of automatically controlling numerous components
located at LV networks, such as: load break switches, batteries, home automation gateways and
power transformer tap changers. The objective is to optimize LV grid efficiency minimizing the need for
grid reinforcement.
3.2.2.1
1
DISCERN_RWE_Leader_B7bd_Use Case
ID
DISCERN_RWE_Leader_
B7bd
Domain(s)/Zone(s)
Name of Use Case
Customer Premises, Distribution /
Process, Field, Station, Operation,
Enterprise
Real time monitoring of LV grid - Smart Operator
Version No.
Date
Name
Author(s)
18.12.2013
RWE
Version Management
Changes
Approval Status
final
Scope
Objective
Innovative secondary substation equipped with a specialized controller. Dedicated
sensors along the lines will deliver voltage and current values, ICT gateways at customer
connection points will deliver possible consumption profiles of the households. This data is
used to operate the LV grid efficiently.
Gather LV grid measurements at substation level to increase monitoring of the grid
condition. Control flexible loads, generators and storage devices in order to operate the
grid in the most appropriate way and to react on fluctuations (avoidance of exceeding
voltage limits, overloads etc.). This optimizes grid efficiency and reduces the need for
conventional grid reinforcement (economic target).
Short Description
In times of more and more local generation the monitoring and control in low voltage grid has become more important. This Use
Case describes an approach based on the Smart Operator, which is a controller located at the secondary substation that
monitors the LV grid and uses existing flexibility to operate the grid more efficiently.
The Smart Operator (SmOp) is a specialised controller that is installed in the secondary substation. The SmOp is responsible for
the LV grid connected to its substation.
Functionality of the SmOp
Input:
The SmOp uses voltage and current measurements in the LV network,
weather forecasts from the SmOp Manager,
possible consumption profiles of the households from Home Energy Controllers (HEC),
tap changer positions,
load switch states and charging states of batteries in the low voltage Grid.
Functional Architecture of the SmOp:
The SmOp stores and analyses measured values from the grid and calculates state estimations in points of the LV grid that are
DISCERN_WP4_D4.2_280114_v3.0
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not measured.
In order to manage the LV grid indipendently, it is necessary to develop a suitable control algorithm for the operation of the grid,
which would stipulate how the Smart Operator reacts in certain situations. The Smart Operator controls the low voltage grid
every minute and improves constantly its efficiency by learning from historical data. The algorithm is being developed by the
IFHT of the RWTH Aachen University.
As a basis for its commands the Smart Operator uses a matrix in which all possible switching options are saved.
It randomly selects an option from this matrix and checks the new grid situation with a load-flow calculation. If no overloading or
voltage outside the allowed limits is detected the grid situation will be set accordingly.
When the Smart Operator first goes into operation all switching options are of equal weighting. If a switching option is
successful, for instance, keeping the voltage within the allowed limits by charging a battery, then this switch option gets a higher
weighting and the next time it will be the more likely option. In this way the algorithm constantly learns how to optimally control
the LV grid.
Output of the SmOp Algorithm:
The SmOp sends the most suitable consumption profile for each household to the HEC.
Furthermore it controls Energy storages, tap changers, and load switches.
The SmOp offers three main advantages to optimze LV grid operation:
1. Monitoring and evaluation of LV grid condition provides a transparent data base for
- Grid planning
- Grid operation
- Limitation of faults
- Quality assurance
2. Exploiting flexibility of producers and consumers to optimize the use of assets
- Avoiding grid expansion despite increasing PV feed in
- Better use of existing resources
- Operating longer lines with more connection points on one transformer
3. With help of measured and stored values it is possible to get detailed experience data about the low voltage grid.- Dimensioning of the grid based on real data
In order to do this, the SmOp uses a model of the LV grid consisting of a transformer, lines, load switches, busbars, connection
points, meters (consumption / feed in), storages and home automation network gateway..
The following figure shows the operation steps of the SmOp algorithm.
(“22nd International Conference on Electricity Distribution”: CIRED2013_0718_final .pdf Page 2)
As shown in Figure 1, at first, the Smart Operator receives measurements from the grid. These measurements are taken at
various points in the grid as well as in smart meter of the households.
Next to the consumption data these meters can also transmit voltage data. At selected points in the grid additional measuring
DISCERN_WP4_D4.2_280114_v3.0
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instruments are installed.
Measuring instruments are also installed in the transformer substation, at the low voltage switch and at the battery. The grid
conditions which cannot be measured are estimated.
The expected grid conditions for the next 24 hours are calculated. The basis for this calculation is a combination of grid data
from the past and expected weather conditions. With this data it is possible to make a prognosis of supply and demand. With
this prognosis an uncritical grid operation can be set up. In this way it is possible to prevent potential overloading or exceeding
voltage limits.
Every command determined by the Smart Operator is checked by a load flow calculation before being sent.
Through the continuous monitoring of the grid by means of the measurement data the forecasts are constantly checked. If
differences from the forecast are identified a re-optimization of the grid is carried out and, if required, new switch commands are
sent. This approach ensures the safe operation of the grid at all times. In the event of a fault in the Smart Operator an alarm is
sent to a superordinate system and all the components switch from the regulated grid operation to operate independently. In this
way the secondary substation (regulated local grid transformer). can be controlled by the Smart Operator but it can also
independently keep the voltage at the busbar within allowed limits.
1.5 General Remarks
General Remarks
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2
Diagrams
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3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Process
Actor Name
Actor Type
LV Grid
Component
Layer Actor
Switch
Component
Layer Actor
Voltage Sensor
Component
Layer Actor
Battery
Component
Layer Actor
Controller
Component
Layer Actor
Grouping
Field
Actors in Process Zone
Actor Description
this Use Case
Process actuators (e.g. switch controllers or
tap changer controllers) and sensing devices
(e.g. current sensors or voltage sensors)
within the network are represented as
separated Actors.
A generic device designed to close, or open,
or both, one or more electric circuits.
LV Grid including the load
switch
continuously report current dynamic status of
voltage
One or more cells fitted with devices
necessary for use, for example case,
terminals, marking and protective devices.
Device or application which operates the tap
changer automatically according to given
setpoints or by direct operator commands
(manual mode).
Group Description
Actor Name
Actor Type
Switch Controller
Component
Layer Actor
Actors in Field Zone
load switch that can be
controlled from the Station
Controller in order to change
the topology of the LV Grid
Additional Voltage Sensors
can be located at certain points
in the grid.
The Station controller can
remotely manage the charge
cycle of the battery, which is
located next to the secondary
substation
The control unit of the tap
changer in the secondary
substation, which is always
controlled by the SmOp. By
disconnection to the SmOp it
operates automatically.
Actor Description
this Use Case
An IED that controls any switchgear. It
enables the control from remote centers (telecontrol) and also from related automatics. It
supervises the command execution and gives
an alarm in case if improper ending of the
IED that enables the control of
Switch positions from the
Station Controller
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Battery Controller
Component
Layer Actor
Smart Meter
Component
Layer Actor
Home Automation Network
Gateway
Component
Layer Actor
Grouping
Station
Actor Type
Station Controller
Component
Layer Actor
Grouping
Actors in Station Zone
Actor Type
Operational Controller
Component
Layer Actor
Grouping
Actor Type
Weather Forecast and
Observation System
Component
Layer Actor
The HANG offers three different
schemes with possible
consumption trends to the
Smart Operator. The Smart
Operator is able to choose the
one which fits the best in his
control schedule. The
consumption trends are created
with the help of flexible
operation of home appliances.
this Use Case
Automation system monitoring and controlling
the devices in a substation. Provides interface
to network control center.
The Station Controller is
represented by the SmOp. The
SmOp is located in the
secondary substation and it’s
functionality is described in
chapter 1.4
Actor Description
this Use Case
Automation system located at operation level
(typically in the network control centre of the
DSO) monitoring and controlling the devices
in the network.
The Operational Controller is
the SmOp Manager. In the
future, the SmOp Manager
should enable automatic control
at operation level by controlling
different Smart Operators
(Station Controllers) within its
region. In this Use Case,
however, the Operation
Controller only provides
Weather data to Smart
Operators in its region.
Group Description
Actor Name
IED that enables the control of
Batteries from the Station
Controller
In this use case the Smart
Meter are equipped with an
additional voltage sensor and
they are used to measure the
voltage level at the customer
connection points and the
electric vehicle charging point.
Actor Description
Group Description
Actor Name
Enterprise
The metering end device is a combination of
the following meter-related 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
A specialized gateway device or application
which establishes the communication
between external systems and the Home
Automation Network (HANG) devices
Group Description
Actor Name
Operation
command. It can also ask for releases from
interlocking, synchrocheck, autoreclosure if
applicable.
An IED that provides data about battery status
and controls the charging/de-charging cycles
Actors in Enterprise Zone
Actor Description
this Use Case
System which intends to perform weather
forecast and observation calculation and to
distribute the calculated geospatially
referenced information to all connected other
systems such as Distribution management
systems, Transmission management systems,
DER/Generation management systems, EMS
or VPPs systems for DER, … enabling in
many cases optimized decision processes or
automation
The Weather Forecast and
Observation System offers the
Weather data to the SmOp
Manager.
Use Case Conditions
Triggering Event
Pre-conditions
LV Grid
Periodically.
Assumption
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Fault, over/under
voltage or overcurrent outside
threshold is detected
or the algorithm the
SmOp indicates that
a change of the load
float situation is
useful.
Station Controller
are within limits.
Communications can be
established from the
Sensors up to Station
Controller.
Communications can be
established from Station
Controller to the
connected Actors (listed
in Chapter 3.1)
3.3 References
References
Status
No.
Reference Type
Reference
1
Conference Paper
S. Willing et al., Improving
Quality of Supply and Usage
of Assets in Distribution Grids
by Introducing a “Smart
Operator”, CIGRE - 22nd
International Conference on
Electricity Distribution,
Stockholm, 10-13 June 2013.
Impact on Use
Case
final
Originator/
Organisation
Link
RWE, Westnetz
GmbH ,
Maschinenfabrik
Reinhausen,
RWTH Aachen
University, PSI AG,
-
Level of Depth
Individual Use Case
Prioritization
Operational Track 1
European
Viewpoint
Technical
Low voltage grid control, low voltage grid operation
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4
Scenario Conditions
Triggering Event
No.
Scenario Name
Primary
actor
1a
Measuring
Voltage
Sensor,
Smart
Meter
Periodically
1b
Substation State
Supervision
Automatic
Tap
Changer
Controller
Periodically
1c
Network State Supervision
Battery,
Switch
Periodically for battery
state of charge,
Switching event for switch
position
2
Load Flow / Voltage Profile
Home
Automation
Network
Gateway
Periodically
3
Weather Monitoring
Weather
Forecast
and
Observation
System
Periodically
4
Management
Station
Controller
5
Load Estimation
Station
Controller
6
Automatic Controls
Station
Controller
The Station Controller
receives data from
Measuring, Substation
State Supervision and
Network State
Supervision
has stored all data in
Process and Network
Data Management, it has
received Consumption
Trends in Load Flow /
Voltage Profile, and the
Weather data and
forecasts from Weather
Monitoring
has carried out Load
Estimation
7
Power Flows Computation
Station
Controller
The Automatic Controls
has been done.
DISCERN_WP4_D4.2_280114_v3.0
Pre-Condition
Station Controller is
running and the
communication to one
or more of the assets
in the grid can be
established
running and the
in the grid can be
established
running and the
in the grid can be
established
Station Controller and
Home Automation
Network Gateway are
running, and
communications
between them can be
established
Station Controller,
Operation Controller
and Weather Forecast
and Observation
System are running.
Communications can
be established
between them
running and has
received data
Post-Condition
The measured
data is available
at the Station
Controller
The current state
of the tap position
is available at the
Station Controller
The current state
of charge of the
battery and the
current switch
position is
available at the
Station Controller
The current Load
Flow at the LV
Grid is calculated
Weather forecast
data is available
for load estimation
Received data is
saved
running and received
data is available
The estimated
Load Flows at the
LV Grid is
calculated
running and
connection to the
actors can be
established
running and the grid
state data is available
The grid state has
changed in the
way which was
expected by the
Station Controller
Efficiency of
previous assisted
control is
evaluated and a
changing of the
parameters for
new assisted
control actions
has been
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No.
Scenario Name
Primary
actor
Scenario Conditions
Triggering Event
Pre-Condition
Post-Condition
determined
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Scenario Name :
Step Event
No.
Measuring
1a
Periodically
(every minute)
Scenario
Description of
Process/Activity
Service
Information
Exchanged
Doing measurements in
order to get voltage and
current from LV Grid
The LV Grid
shows the Smart
Meters the
measured values
REPORT
LV Grid
Smart Meter
Voltage and
Current
measurements
The LV Grid
sends voltage
measurements to
the Voltage
Sensors
The Station
Controller request
for a voltage
measurement.
The Voltage
Sensors sends
voltage values to
the Station
Controller
The Smart Meter
calculates the
active and
reactive power
REPORT
LV Grid
Voltage Sensor
Voltage
measurements
GET
Station Controller
Voltage Sensor
Voltage
measurements
REPORT
Voltage Sensor
Station Controller
Voltage
measurements
INTERNAL
PROCESS
Smart Meter
Smart Meter
Active and
Apparent power
The Smart Meters
send measured
values to the
Station Controller
REPORT
Smart Meter
Station Controller
Voltage, Current
Active and
Apparent power
The Battery
Controller gets the
state of charge of
the Battery
The Battery
Controller sends
the state of
charge to the
Station Controller
REPORT
Battery
Battery Controller
State of battery
charge
REPORT
Battery Controller
Station Controller
State of battery
charge
1b
Periodically
(every minute)
Do measurements in order
to get voltage of
measurement point
1c
Periodically
(every minute)
Initialising measurements
on LV Grid
2a
After
measurement
Transfer of voltage values
to the Station Controller
3
Periodically
(every minute)
active and apparent power
calculation
4
Periodically
(every minute)
Report measurements to
the Station Controller
Network State Supervision
1d
Periodically
Report the battery state to
(every minute)
Battery Controller
2b
Periodically
(every minute)
Report battery state to
Station Controller
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1e
2c
Switching event
(load switch
changes its
position)
Switch Controller
detects a
switching event
in a load switch
Reporting of switch state to
the Switch Controller
The Switch
Controller gets the
state of the Switch
REPORT
Switch
Switch Controller
load switch
position
Reporting of switch state to
the Station Controller
The Switch
Controller sends
the state of the
load switch to the
Station Controller
REPORT
Switch Controller
Station Controller
load switch
position
The Automatic
Tap Changer
Controller sends
the tap changer
position to the
Station Controller
REPORT
Controller
Station Controller
Tap position
The Home
Automation
Network Gateway
Sends five
possible
consumption
trends to the
Station Controller
The Station
Controller
calculates current
load Flow and
voltage profile
REPORT
Home Automation
Network Gateway
Station Controller
Consumption
trends
INTERNAL
PROCESS
Station Controller
Station Controller
Load flow /
voltage profile
The Weather
Forecast and
Observation
System sends the
weather data to
the Operation
Controller
The Operation
Controller sends
the weather data
to the Station
Controller
REPORT
Weather Forecast and
Observation System
Weather data
REPORT
Station Controller
Weather data
Substation State Supervision
1e
Switching event
Sending state of tap
in an Automatic
changer position to Station
Tap Changer
Controller
Controller
Load Flow / Voltage Profile
1f
periodically
Show possible
consumption trends
5
Periodically
(every minute)
after receiving
Voltage, Current,
Active and
Apparent
Measurements,
as well as
Consumption
Trends
Weather Monitoring
6
Periodically (12
hours)
Calculate load flow /
voltage profile
7
Transfering weather data
from Operation Controller
to Station Controller
Periodically (12
hours)
Transfering Weather
Forecast and Observation
System toOperation
Controller
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8
Periodically
Load Estimation
9
Periodically
(every 6 hours)
Aggregate and save data
The Station
Controller saves
the received data
on SQL database
INTERNAL
PROCESS
Station Controller
Station Controller
Aggregated data
saving at station
level
load estimation for the next
24 hours
The Station
Controller
calculates the
estimated Power
Flows saved
measurements
and empirical
values
INTERNAL
PROCESS
Station Controller
Station Controller
Load estimation
The Station
Controller
transfers the
optimal
consumption
trends to the
Home Automation
Network
Gateways
The Station
Controller sends
the Battery
Controller the
order to charge or
discharge
The Station
Controllerl torders
the Switch
Controller to open
or to close the
circuit
The Switch
Controller open or
close the circuit
CHANGE
Station Controller
Home Automation
Network Gateway
Consumption
trends
CHANGE
Station Controller
Battery Controller
Operation mode
of the battery
CHANGE
Station Controller
Switch Controller
load
switchposition
CHANGE
Switch Controller
LV Grid
load switch
position
The Station
Controller orders
the Automatic Tap
Changer
Controller to
change the
position
CHANGE
Station Controller
Automatic Tap
Changer Controller
Tap position
Automatic Control
10
periodically
(every minute)
Transferring the optimal
consumption trends
11a
Periodically
(every minute)
Order to charge or
discharge
11b
If algorithm of
Station
Controller
indicates that its
necessity
Order to open or close the
load switch
11c
If algorithm of
Station
Controller
indicates that its
necessity
If algorithm of
Station
Controller
indicates that its
necessity
Open or close the load
switch
11d
Order to change tap
position
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12
Periodically
The Station
Controller checks
the efficiency of
previous assisted
control actions
and a changing of
the parameters for
new assisted
control actions will
be determined
INTERNAL
PROCESS
Station Controller
Station Controller
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5
Name of Information
Exchanged
Weather data
Consumption trends
Voltage, current, apparent and
active power
Aggregated data at station Level:
State of battery charge
load switch position
Tap position
Operation mode of the Battery
Load flow / voltage profile
Power flow
7
Data indicating the current weather and it
also includes a forecast.
The consumption trend of a household
gives information about the load in a certain
time. The consumption trend could be
changed by shifting the load of home
appliances to other times.
Measurement indicating the analogue value
of the voltage, current, apparent power and
effective power in a particular point of the
distribution network. This information object
should clearly identify which value
measures within the network. Moreover it
should include the timestamp, source, and
information about the quality of the
measurement.
Aggregated data of measured and
calculated values which are stored in the
database of the Station Controller: Voltage,
current, apparent, active power, Weather
Data and consumption trends.
Voltage Measurement indicating the
analogue value on certain points in the LV
Grid.
The state of charge is the percentage value
of the maximum charging capacity of a
battery. It determines how much energy can
be additionally taken by the battery.
The state of the load switch determines if
the switch is open or closed. In most cases,
changes to the state of the load breaker
change the topology of the grid.
Command defining the new position of a
power transformer tap. This information
object should clearly identify the power
transformer tap. It also should include
precise information about the new position
and the source of the command.
The operation mode for battery commands
the controller of the battery either to charge
or to discharge the battery.
Data describing the current load flow and
voltage profile. This Data is calculated
within the Station Controller with the help of
measured values.
Data about the current grid state which is
used by the station controller to check his
efficiency.
Term
Definition
SmOp
Smart Operator
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3.2.2.2
DISCERN_RWE_Leader_B7bd_SGAM
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3.2.3.
DISCERN_SSEPD_Leader_B7bd
The solution proposed by SSEPD for this sub-functionality is called “New Thames Valley Vision”. It
provides a detailed description of the actors, functions and steps necessary to determine the optimal
level of monitoring in LV networks.
3.2.3.1
1
DISCERN_SSEPD_Leader_B7bd_Use Case
Description of the Use Cases
Domain(s)/Zone(s)
Name of Use Case
ID
DISCERN_SSEPD_Leader_B7bd
Distribution, DER, Customer
Premises
/
Enterprise, Operation, Station,
Field, Process
Real time monitoring of LV grid - New Thames Valley
Vision
Version No.
Date
Name
Author(s)
04.12.2013
SSEPD
Version Management
Changes
Approval Status
final
Scope
Objective
Monitor LV networks at an enhanced level and develop analytical approaches to both
forecast power flows using scenarios and to establish the optimal level of monitoring
required to facilitate such forecasting.
The scope of the NTVV project as relevant to DISCERN covers the implementation of new
real-time monitoring solutions together with the development of analytical approaches and
tools for identifying patterns in energy profiles using both the data obtained from
monitoring and further information available on the LV grid & connected customers.
Determine the optimal level of monitoring required to provide data for observing the grid in
sufficient detail for monitoring, modelling & controlling, and to develop operational models
& methodologies which may subsequently be transferred to BAU application including LV
monitoring, modelling & controlling through scenario based forecasting of future energy
requirements.
Short Description
This sub-functionality deals with the real time monitoring of LV grids with minimal AMR for observability purposes.
The DISCERN sub-functionality associated with the New Thames Valley Vision (NTVV) project (B7b - Real time monitoring of
LV grid with minimal AMR for observability purposes) relates to the development of methods for improving real-time monitoring
of LV networks through measurement (inc. smart meters where available) and subsequently using the data available to provide
system state information to the network operators.
The NTVV project will install secondary (11kV/400V) substation monitoring which measure each phase on every low-voltage
feeder at that substation together with ‘end point’ monitoring equipment at domestic and business properties (to include smart
metering data where available). The intention is to identify to what level physical end point and substation monitoring can be
reduced to still provide meaningful data. The data collected will be used to establish LV network power flows, and analytic tools
will be applied to:
•
•
•
•
categorise energy usage patterns
establish how individual energy profiles aggregate up to the substation level
identify trends
inform the use of scenarios to create forecasts for future energy requirements
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The NTVV activities of relevance to the DISCERN project and Sub-functionality B7b are as follows:
Substations
• Install substation monitors to communicate power information (voltage & ac current on each phase collated in a processor
located within the substation and communicated back to the data repository for the NTVV project via the business’s generic
DMS framework) - 100 substation monitors installed and phased installation of further substation monitors (not more than
325 in total)
• Assess initial effectiveness of substation monitoring
• Produce a methodology for determining the number and distribution of substation monitors, informed by customer profiling
• Evaluate approach in terms of installation, operation, application & standardisation
End Points
• Install 250 in-house end point monitors at selected, suitable end point monitoring locations (based on concentrated
monitoring), followed by installation of cut-out monitors
• Assess initial effectiveness of end point monitoring (inc. selection of trial locations and monitored properties)
• Integrate already monitored data as available from half-hourly metering of large & small commercial customers, cut-out
based monitoring & smart meter data from suppliers
• Evaluate approach in terms of system performance, operation, application & standardisation and benchmark against
potential alternatives
ICT Requirements
• Design the meter communications and data management service to facilitate end point monitoring
• Establish alternative communications for cut-out based monitoring
• Engage potential vendors and appraise respective equipment performances
• Describe project data integration points including supply business data (smart meters), internal IT systems data, real-time
systems, SCADA data and 3rd party information stores (potentially inc. weather, OS Master Map, SMOS, Land Registry,
Mosaic, Electoral Register)
• Ensure compliance with the NTVV data protection strategy, relating to the privacy, integrity, ownership & accessibility of
new data
Characterisation
• Characterise and categorise customer energy demand profiles
• Use customer categorisation to improve network monitoring and demand prediction
• Develop monitoring deployment strategy based on the optimal balance between substation monitoring and end point
monitoring
Aggregation
• Develop feeder power flow profiles by aggregating the modelled demand and usage profiles of domestic and SME
customers
• Create a 'buddying engine' methodology to pair non-metered households with metered households, to facilitate 'virtual'
customer monitoring
• Assess the reduction in number of network monitoring points and target optimal placement of network monitoring devices
using the aggregation techniques (the use of such techniques will become less necessary as smart meters are rolled out)
• Validate the methodology developed for forecasting feeder power flow against actual monitoring data from NTVV
• Classify and understand the characteristics and drivers that cause the network to exhibit a particular volatility of peaks
observed in the aggregated profiles.
Forecasting
• Create an agent-based forecasting engine to produce short, medium and long-term network demand forecasts
1.5 General Remarks
General Remarks
The NTVV project aims to determine the optimal level of monitoring required on an LV grid and develop operational models &
methodologies which can enhance the efficient operation of grids as they adapt to future changes. Business decisions will need
to be taken based on the findings from the project before any new approaches developed are adopted as BAU.
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2
Diagrams
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3
Technical Details
3.1 Actors
Grouping
Process
Group Description
Actor Name
Actor Type
LV Grid
Component
Layer Actor
Customer Premises
Component
Layer Actor
Component
Layer Actor
Voltage Sensor
Actor Description
Process actuators (e.g. Switches or tap
network are represented as separated Actors.
The premises of a domestic, commercial or
industrial electricity consumer
Voltage sensing devices, which are spread on
the Grid lines, continuously report voltage
status
Current Sensor
Component
Layer Actor
Current sensing devices, which are spread on
the Grid lines, continuously report current
status
Distributed Energy
Resource
Component
Layer Actor
Small unit which generates energy and which
is connected to the distribution grid. Loads
which could modify their consumption
according to external set points are often also
considered as DER
for SSEPD this is the
substation deployed voltage
sensor to monitor a given
feeder and phase
for SSEPD this is the
substation deployed sensor
using Rogowski coil technology
to monitor a given feeder and
phase
for SSEPD this relates to
distributed generation (solar
PV, small wind, biomass, etc.)
or energy storage
Actors
Group Description
Grouping
Field
this Use Case
Actor Name
Actor Type
End Point Monitor
Actor Description
this Use Case
Component
Layer Actor
A monitor of electricity not used for billing
purposes and deployed by the DNO for the
purposes of LV visibility of per-premises
consumption
Smart Meter
Component
Layer Actor
IED
Component
Layer Actor
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
multifunction meters, digital relays,
controllers)
for SSEPD this is the monitor
installed at a customer’s
premises to gather energy
consumption/feed-in data but
not used for billing purposes
for SSEPD this relates to the
SMETS2 standard Smart
Meters rolled out by the SSE
Supply business and other
Suppliers and used for billing
purposes
Grouping
Operation
for SSEPD these are installed
within substations to collate
substation sensing device data
and forward it to the Data
Repository
Group Description
Actor Name
Actor Type
Data Repository
AMI Head End
Actor Description
this Use Case
Component
Layer Actor
data repository for data archiving, analysis or
reporting purposes
Component
Layer Actor
A system which acts as back-end for the
metering communication and controls and
monitors the communication to the meter
devices. The collected meter information is
provided for other system like meter data
management
for SSEPD this incorporates the
PI Historian data repository for
DMS
for SSEPD the AMI Head End
is SMOS which collates End
Point Monitor data and
forwards it to the Data
Repository
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System
Component
Layer Actor
Actors
Group Description
Grouping
Enterprise
DMS SCADA System refers to the real time
information system and all the elements
needed to support all the relevant operational
activities and functions used in distribution
automation at dispatch centers and control
rooms.
Actor Name
Actor Type
Geographical Inventory
Component
Layer Actor
Power Analysis Tool
Component
Layer Actor
Demand Response
Management System
Component
Layer Actor
Project Definition
Business
Layer Actor
Grid Communications
Network Providers
Business
Layer Actor
Maintenance and
Inspection
Business
Layer Actor
for SSEPD this is the PowerOn
Fusion DMS system which is
used to monitor and control the
distribution system equipment,
and is integrated with the PI
Historian data repository
Actor Description
this Use Case
Provides management of geospatial data,
typically by utilizing computer graphics
technology to enter, store, and update graphic
and non-graphic information. Geographic
depictions and related non-graphic data
elements for each entity are typically stored in
some form of a data store. The graphic
representations are referenced using a
coordinate system that relates to locations on
the surface of the earth. Information in the
data store can be queried and displayed
based upon either the graphic or non-graphic
attributes of the entities.
Application used to undertake power flow
analyses, generate energy profile data,
perform simulation, etc.
for SSEPD this is SmallWorld
Electric Office hosted within the
Network Modelling Environment
for the NTVV project, which will
interface with PowerOn Fusion
and CYMDIST
Demand Response Management System
(DRMS) is a system or an application which
maintains the control of many load devices to
curtail their energy consumption in response
to energy shortages or high energy prices.
This actor plans work activities to enhance or
extend the network and/or other assets.
Examples include line extension for new
housing development, a new substation,
switchgear change at a substation. Capital
development projects (i.e., not billed to a
customer) are usually justified with a business
case.
Plan, build and maintain the communications
systems that enable the data communication
required to maintain grid stability, load
balancing and fault protection systems by a
TSO or DSO. This function is mostly executed
by the TSO or the DSO, or may be performed
by an independent actor but the overall
responsibility and ownership of information
remains with TSO and DSO. Grid
communications network provider ensures
compliance with the agreed service levels
(Service Level Agreements including quality of
service, data security and privacy) and
compliance with any national and/or
international regulations as necessary;
This actor provides work involving inspection,
cleaning, adjustment, or other service of
equipment to enable it to perform better or to
extend its service life. Examples of
maintenance work are routine oil changes and
painting. Examples of inspection work are
pole inspections, vault inspections, and
substation inspections.
DISCERN_WP4_D4.2_280114_v3.0
for SSEPD this is the CYMDIST
application and associated
algorithms hosted within the
Network Modelling Environment
for the NTVV project, which will
interface with GIS (SmallWorld
Electric Office), contains an
energy profile manager
for SSEPD this is an external
project supplier & operator of
the DR solution for the NTVV
project
for SSEPD this is the NTVV
project team
for SSEPD this is the SSE
department who provide (but
not necessarily operate) the
DMS, SCADA, Telemetry and
PI Historian capabilities and will
provide the telecomms for
substation data acquisition
(‘Telecontrol Database’
function) and End Point
Monitoring data acquisition
(‘AMI Meter and
Communication Network Asset
Management’ function)
Depot based department
responsible for operation,
maintenance and development,
they will be installing the
substation Voltage Sensing
Device, Current Sensing
Device & Front-End Processor
(IED) kit for the NTVV project
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AMI Service Engineer
Business
Layer Actor
Investigative Analysis
Business
Layer Actor
IT
Business
Layer Actor
Systems Interfacing
Support
Business
Layer Actor
Actor responsible for delivering & ensuring
functional system interfaces
DMS Operator
Business
Layer Actor
Operator of the Distribution Management
System
Grouping
Market
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)
External actor responsible for creating &
undertaking analysis including modelling,
statistical analysis or comparative analysis of
options or generation of forecasts to provide
conclusions which may inform future business
strategy decisions
Actor providing IT systems support &
maintenance and custodians of digital data
inc. storage, access levels & IT security
Group Description
Actor Name
Actor Type
Supplier
Business
Layer Actor
Demographic Data
Provider
Component
Layer Actor
DER Management System
Component
Layer Actor
Actors in Market zone
for SSEPD for SSEPD this is
the SSE Depot based
department responsible for
operation, maintenance and
development, they will be
installing the End Point Monitor
(EPM) kit to monitor individual
customers and provide data for
the NTVV project
for SSEPD this is an external
project partner analysing data
and creating models for the
NTVV project
Corporate IT department
responsible for all aspects of IT
systems support and
maintenance
for SSEPD this is the external
supplier/project partner for
systems integration the NTVV
project DMS (PowerOn
Fusion), GIS (SmallWorld
Electric Office) & Power
Analysis Tool (CYMDIST), etc.
for SSEPD these are the SSE
individuals responsible for
planning new LV work &
connections, undertaking power
flow analysis, etc.
Actor Description
this Use Case
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
Third party provider of demographic data
associated with properties within a geographic
area, e.g. local council
for SSEPD this may be the
SSE Supply retail business or
any other Supplier responsible
for metering, billing, customer
service & settlements
for SSEPD this is the Local
Authority, Land Registry,
Ordnance Survey, etc. who are
able to provide demographic
data associated with properties
within the NTVV project area
for SSEPD this is the system
able to provide embedded
generation asset characteristics
Refers to the operation and enterprise
management system and all the elements
needed to control the generation process of a
single DER entity
Use Case Conditions
Triggering Event
Pre-conditions
LV Grid
Periodically
Customer Premises
Periodically
Assumption
voltages and currents are within
limits; communications can be
established from Current Sensor
& Voltage Sensor to IED and
from IED to Data Repository
communications can be
established from End Point
Monitoring to AMI Head End and
from AMI Head End to Data
Repository
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3.3 References
No.
References
Status
Impact on Use Case
Reference Type
Reference
Standard
DNP3
Standard
Standard
IEC 62056
(DLMS/COSEM)
UK SMETS2
Communication Layer,
Information Layer
Communication Layer,
Information Layer
Information Layer
Standard
Standard
IEC 61968-11 (CIM)
IEC 61970-301 (CIM)
Information Layer
Information Layer
Originator/
Organisation
Link
IEC
Department of
Energy & Climate
Change (DECC),
UK
IEC
IEC
Level of Depth
Individual Use Case
Prioritization
Operational Track 1
European
Viewpoint
Technical
LV observability, optimal intelligence
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4
Scenario Conditions
Triggering Event
No.
Scenario Name
Primary actor
1
Work Planning
Project Definition
project implementation
•
project approval
obtain
2a
Telecontrol Database
Grid
Communications
Network
Providers
AMI Meter and
Grid
Communication Network Communications
Asset Management
Network
Providers
Measuring
Voltage Sensor,
Current Sensor
•
working agreement
in place between
parties
•
working agreement
in place between
parties
periodically - voltage and
current sensors get voltage
and current measurements
from substations on the LV
Grid
•
periodically
•
voltage sensor,
current sensor and
IED are operating
correctly
functioning
communication from
voltage sensor and
current sensor to
IED
IED is operating
correctly
functioning
communication from
IED to Data
Repository
End Point Monitoring
is operating correctly
functioning
communication from
to AMI Head End
functioning
communication from
AMI Head End to
Data Repository
functioning
communication from
Supplier to Data
Repository
legal and regulatory
obligations are met
with respect to
information sharing
and data privacy
customers with DR
resources have
been identified
2b
3a
3b
Process and Network
Data Management
IED
Pre-Condition
•
•
3c
Automated Meter
Reading
End Point Monitor periodically - End Point
Monitors get energy
measurements (demand
consumption & generation
feed-in) from customer
properties
•
•
•
3d
Meter Data Collection
Smart Meter
periodically
•
•
4a
Demand Response
Management
4b
DER Planning and
Estimation
5
Decision Support
Demand
Response
Management
System
DER
Management
System
•
•
customers with
embedded
generation DER
resources have
been identified
IT
project implementation /
periodically - data is
received from IEDs & AMI
Head End
•
systems and
applications are
operational and
appropriate access
is granted
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Post-Condition
substation
monitoring kit and
end point
monitoring kit
installed
substation
monitoring
communications
installed
end point
monitoring
communications
installed
Voltage and
Current Sensors
send
measurements to
IED
IED sends voltage
and current
measurement data
to Data Repository
HES sends End
Point Monitoring
energy
measurement data
to Data Repository
Smart Meter data
is integrated with
End Point
Monitoring data in
Data Repository
DR capability/
characteristics are
captured in Data
Repository
embedded
generation DER
capability/
characteristics are
captured in Data
Repository
all project
monitoring data is
captured in Data
Repository and
available for
analysis
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Scenario Conditions
Triggering Event
No.
Scenario Name
Primary actor
Pre-Condition
6
Connectivity Model
Project Definition
and Maintenance
and Inspection
•
7
Power Flows
Computation
Power Analysis
Tool
adhoc - receipt of sufficient
monitoring data
•
8
Load Pattern
Identification
Investigative
Analysis
monitoring data
•
9
Customer Profiling
Investigative
Analysis
customer demand profile
data and third party
demographic data
•
•
10
Load Forecast
Investigative
Analysis
adhoc - load patterns have
been identified
•
11
Monitoring Optimisation
Investigative
Analysis
analytical data
•
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connectivity model
application is
functional and
appropriate access
is granted
sufficient data is
available for use in
the analysis
sufficient data is
the analysis
Post-Condition
a geospatial
connectivity model
of the LV network
is created
project specific
analysis can be
undertaken
patterns in load
profiles are
identified (temporal
or spatial,
individual or
aggregated, etc)
energy profile
cohorts of End
manager application Point Monitoring
is functional and
customers with
appropriate access
similar load profiles
is granted
identified and
demographic data is demographic data
reasonably accurate used to create
virtual profiles for
non-EPM
customers
confidence in the
load forecasts are
load patterns
developed for
identified
various scenarios
sufficient data is
optimal
configuration for
the analysis
effective
observability is
defined
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Scenario Name :
Step Event
No.
Work Planning
1a
Project
approval
obtained
1b
Project
approval
obtained
1c
Project
approval
obtained
2a
Scenario
Description of
Process/Activity
Service
Information
Exchanged
Instruct Substation
Monitoring Installation
Work Plan
Instruct End Point Monitor
Installation Work Plan
substation monitoring
equipment installation
instructions issued
end point monitoring
equipment installation
instructions issued
substation and end
point monitoring
comms equipment
installation instructions
issued
Voltage Sensors
installed at substations
INSTRUCT
Project Definition
Maintenance and
Inspection
work plan
INSTRUCT
Project Definition
work plan
INSTRUCT
Project Definition
Grid Communications
Network Provider
work plan
EXECUTE
Maintenance and
Inspection
Voltage Sensor
work plan
EXECUTE
Maintenance and
Inspection
Current Sensor
work plan
EXECUTE
End Point Monitor
work plan
EXECUTE
Grid Communications
Network Provider
Project Definition
work plan
EXECUTE
Grid Communications
Network Provider
Project Definition
work plan
CREATE
LV Grid
Voltage Sensor
substation
voltage
measurements
Instruct Substation & End
Point Monitor
Communication Installation
Work Plan
Working
Install Substation
agreement in
Monitoring
place between
parties
2a
Working
Install Substation
Current Sensors
agreement in
Monitoring
installed at substations
place between
parties
2b
Working
Install End Point Monitoring End Point Monitors
agreement in
installed at customer
place between
premises
parties
Telecontrol Database
3a
Working
Substation Comms
substation monitoring
agreement in
Installed
comms installed
place between
parties
AMI Meter and Communication Network Asset Management
3b
Working
end point monitoring
agreement in
Comms Installed
comms installed
place between
parties
Measuring
4a
Periodically
Measure Voltage in LV Grid Voltage Sensors take
measurements from
LV Grid at substation
feeder & phase level
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4b
Periodically
Measure Current in LV Grid
5a
Periodically
Report Voltage
Measurements to IED
5b
Periodically
Report Current
Measurements to IED
6
Periodically
Store Voltage and Current
Measurements
Process & Network Data Management
7
Periodically
Report Voltage and Current
Measurements to Data
Repository
Automated Meter Reading
8
Periodically
Measure Usage at
Customer Premises
9
Periodically
Report Power
Measurements to AMI
Head End
10
Periodically
Store Power
Measurements
11
Periodically
Report Power
Measurements to Data
Repository
Meter Data Collection
12
Periodically
Measure Usage at Smart
Meter Customer Premises
Current Sensors take
measurements from
LV Grid at substation
feeder & phase level
Voltage Sensors pass
substation voltage
measurements to IED
Current Sensors pass
substation current
measurements to IED
IED retains the
substation
measurement data
prior to transfer to Data
Repository
CREATE
LV Grid
Current Sensor
substation
current
measurements
REPORT
Voltage Sensor
IED
REPORT
Current Sensor
IED
INTERNAL
PROCESS
IED
IED
substation
voltage
measurements
substation
current
measurements
substation
voltage &
current
measurements
by feeder &
phase
Data Repository polls
IED and IED transfers
substation
measurement data to
Data Repository via
GPRS
REPORT
IED
Data Repository
substation
voltage &
current
measurements
by feeder &
phase
End Point Monitors
measure consumed &
generated energy at
customer premises
End Point Monitor pass
customer consumed &
generated energy data
to AMI Head End via
GPRS
AMI Head End retains
customer consumed &
generated energy data
prior to transfer to Data
Repository
AMI Head End
transfers customer
consumed & generated
energy data to Data
Repository over a VPN
CREATE
Customer Premises
End Point Monitor
customer
consumption
data
REPORT
End Point Monitor
AMI Head End
customer
consumption
data
INTERNAL
PROCESS
AMI Head End
AMI Head End
REPORT
AMI Head End
Data Repository
customer
consumption
data by
customer
premises
customer
consumption
data by
customer
premises
Smart Meters measure
consumption at Smart
Meter customer
premises
REPORT
Customer Premises
Smart Meter
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consumption
data
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13
Periodically
Report Smart Meter Data
Supplier obtains the
Smart Meter data
REPORT
Smart Meter
Supplier
14
Periodically
Store Smart Meter Data
Supplier retains the
Smart Meter data prior
to transfer to Data
Repository
INTERNAL
PROCESS
Supplier
Supplier
15
Periodically
Report Smart Meter Data
Supplier makes Smart
Meter data available to
Data Repository
REPORT
Supplier
Data Repository
Demand Response
capability/
characteristics
captured in Data
Repository
REPORT
Demand Response
Data Repository
DR
characteristics
Distributed Energy
Resource capability/
characteristics
captured in Data
Repository
REPORT
Distributed Energy
Resource
Data Repository
DER
characteristics
Data Repository for
monitoring data is
configured &
maintained; End Point
Monitor customer IDs
verified identifying their
location in the network,
which substation they
are connected to & the
phase they are
connected to; Voltage
Sensor & Current
Sensor IDs verified
identifying which
substation they are
connected to & the
phase they are
connected to; IT
ensure customer data
security & privacy and
set appropriate user
access levels for
monitoring and asset
CONFIGURE
IT
Data Repository
End Point
Monitor IDs,
Customer IDs
(MPAN/NRN),
Voltage Sensor
IDs, Current
Sensor IDs,
connected
phase, user
access levels
Demand Response Management
16
Project
Identify Demand Response
Implementation Capability
Distributed Energy Resource Planning and Estimation
17
Project
Identify Embedded
Implementation Generation Distributed
Energy Resource
Capability
Decision Support
18
Project
Implementation
Configure the Monitoring
Data Capture and Storage
Facility
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customer
consumption
data
customer
consumption
data by
customer
premises
customer
consumption
data by
customer
premises
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identification data
19
Periodically
Store Monitoring Data
data received from
IEDs & AMI Head End
is validated and stored
such that all project
monitoring data is
captured in Data
Repository and
available for analysis
INTERNAL
PROCESS
Data Repository
Data Repository
20
Adhoc
Report Monitoring Data to
Power Analysis Tool
monitoring data is
available to Power
Analysis Tool
REPORT
Data Repository
Power Analysis Tool
21
Adhoc
Report Monitoring Data to
System
monitoring data is
available to DMS
REPORT
Data Repository
DMS
Configure the Connectivity
Model for the Network
Physical Assets
Connectivity Model for
the LV Grid is
configured containing
verified geospatial
asset data for existing
assets and new project
specific assets
interfacing capabilities
between Geographical
Inventory, DMS and
Power Analysis Tool
are provided and
tested
CONFIGURE
Project Definition
Geographical
Inventory
connectivity
model
CONFIGURE
Geographical
Inventory, DMS
Power Analysis Tool
substation
voltage
measurements,
substation
current
measurements,
customer
consumption
data,
connectivity
data, electrical
characteristics
data
Connectivity Model
22
Project
Implementation
23
Project
Implementation
Establish Functional
System Interfacing Within
the Project’s Network
Modelling Environment
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substation
voltage
measurements,
substation
current
measurements,
customer
consumption
data
substation
voltage
measurements,
substation
current
measurements,
customer
consumption
data
substation
voltage
measurements,
substation
current
measurements
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24
Adhoc
Access LV Grid
Connectivity Data
obtain data required for
analysis from the
Geographical Inventory
load the monitoring
data into the Power
Analysis Tool such that
it is available to the
Energy Profile
Manager facility
REPORT
Geographical
Inventory
Power Analysis Tool
connectivity
model
REPORT
Power Analysis Tool
substation
voltage
measurements,
substation
current
measurements,
customer
consumption
data
substation
voltage
measurements,
substation
current
measurements
customer
consumption
data
25
Adhoc
Import LV Grid Monitoring
Data into Energy Profile
Manager
26
Adhoc
Compute Substation
Energy Profiles
energy profiles
analysis is undertaken
on substation
monitoring data
CREATE
Power Analysis Tool
27
Adhoc
Compute Customer Energy
Profiles
CREATE
Power Analysis Tool
28
Adhoc
Store Energy Profiles
energy profiles
analysis is undertaken
on customer
monitoring data
store calculated energy
profiles in the Data
Repository
REPORT
Power Analysis Tool
Data Repository
load profiles
patterns in load profiles
are identified (temporal
or spatial, individual
customer, aggregated
customers, customer
cohorts, substation
level, etc)
INTERNAL
PROCESS
load patterns
access calculated load
profiles from the Data
Repository
cohorts of End Point
Monitor customers with
similar load profiles are
identified
demographic data
obtained from third
party provider
characterised
customer cohorts are
matched to non-NTVV
participant customers
REPORT
Data Repository
load profiles
INTERNAL
PROCESS
customer
cohorts
REPORT
Demographic Data
Provider
demographic
data
INTERNAL
PROCESS
customer
cohorts
Load Pattern Identification
29
Adhoc
Customer Profiling
30
Adhoc
Access Load Profiles
31
Adhoc
Characterise NTVV
Participant Customer
Profiles
32
Adhoc
Obtain Demographic Data
33
Adhoc
‘Buddy’ NTVV Participant
Customers with Non-NTVV
Participant Customers
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within the region
34
Adhoc
Create Virtual Load Profiles
35
Adhoc
Store Virtual Load Profiles
Load Forecast
36a
Adhoc
Define Future Scenarios
36b
Adhoc
Define Future Scenarios
37
Adhoc
Load Forecast
38
Adhoc
Report Load Forecast
Results
39
Adhoc
Undertake Comparative
Analysis
virtual load profiles for
non-End Point Monitor
customers using
demographic data are
created, results are
tested and validated,
‘buddying’
methodology is refined
as necessary
store virtual energy
profiles in the Data
Repository
INTERNAL
PROCESS
virtual load
profiles
REPORT
Power Analysis Tool
Data Repository
load profiles
possible future
scenarios to be
investigated are
defined
possible future
scenarios to be
investigated are
defined
forecasting
methodologies (inc.
using customer
catergorisations) for
use in demand
prediction are
developed, results are
tested and validated,
forecasting
methodology is refined
as necessary
findings are reported
and data for use in
network studies is
provided
CREATE
Project Definition
scenarios
CREATE
DMS Operator
scenarios
INTERNAL
PROCESS
load forecasts
REPORT
Project Definition
load forecasts
individual and
aggregated sets of
customer and
substation energy
profiles and monitoring
data are compared
INTERNAL
PROCESS
load profiles
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40
Adhoc
Define Optimal Monitoring
Configuration
41
Adhoc
Report Monitoring
Optimisation Results
optimal monitoring
configuration for
effective LV Grid
observability is
determined and
defined, results are
tested and validated
the results,
optimisation variants
are defined as
necessary
optimal monitoring
configuration
conclusions and
recommendations are
reported
INTERNAL
PROCESS
optimal
monitoring
configuration
REPORT
Project Definition
optimal
monitoring
configuration
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5
Name of Information
Exchanged
work plan
substation voltage
measurements
substation current
measurements
customer consumption data
End Point Monitor IDs
Customer IDs (MPAN/NRN)
Voltage Sensor IDs
Current Sensor IDs
connected phase
user access levels
DR characteristics
DER characteristics
connectivity model
electrical characteristics data
demographic data
load profiles
customer cohorts
load forecast
scenarios
optimal monitoring configuration
detailed work programme including
instructions, tasks, locations, resources &
scheduling information and notifications that
a task or set of tasks has been successfully
completed
measurement data relating to voltages in
the three phases of the LV lines feeding the
secondary substations, with timestamp
measurement data relating to currents in
the three phases of the LV lines feeding the
secondary substations, with timestamp
measurement date relating to demand
consumption & generation feed-in at a
customer premises
individual End Point Monitor identification
number
individual customer identification number
individual Voltage Sensor identification
number
individual Current Sensor identification
number
identifies the substation phase in question
identifies individual user access levels for
systems and applications to ensure data
security
export/import characteristics for DR assets
export/import characteristics for embedded
generation DER assets
connectivity model data for both existing
network physical assets and project specific
assets or reconfigurations, asset
connectivity, cable types, position/status of
link boxes and switches, etc.
impedance, etc., for each asset type
demographic data associated with
properties within a geographic area
calculated load profiles
cohorts of customers with similar load
profiles
calculated load forecasts for various
scenarios
scenarios for possible future energy
technology uptake and/or customer
behaviours
conclusions on the optimal monitoring
deployment strategy to achieve sufficient
observability of the LV network for
forecasting and planning purposes
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3.2.3.2
DISCERN_SSEPD_Leader_B7bd_SGAM
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3.2.4.
Summary
All the three solutions proposed by GNF, RWE and SSEPD in sub-functionality B7bd are aimed at
improving monitoring and control of LV networks. However, from the functional architectures defined in
the SGAM Function Layers, it can be concluded that each of these solutions sets their main technical
functions in different zones (Figure 3-4):
•
In GNF’s solution the functions to calculate power quality parameters (harmonics,
imbalances, etc.) in the LV grid are performed at Field zone by Intelligent Electronic Devices
(IEDs).
•
In RWE’s solution the main functions for controlling the LV network are performing at Station
zone by the Smart Operator.
•
In SSEPD’s solution the main functions to optimize monitoring (load pattern identification,
power flows computation, etc.) are carried out at Enterprise zone by a Power Analysis Tool.
Figure 3-4. Comparison between the functional architectures proposed by GNF, RWE and SSEPD in subfunctionality B7bd
Table 3-2 shows the new actors added by B7bd Leaders to the original actor list. These new actors
refer mainly to process and field components for LV grid monitoring (e.g. battery, switch, controllers,
etc.) and also to roles involved in the planning and execution of projects in DSOs, such as: IT,
Investigative Analysis, or System Interfacing Support.
Table 3-2. New actors added for sub-functionality B7bd
Actor
Description
Battery
One or more cells fitted with devices necessary for use, for example case, terminals,
marking and protective devices.
Battery Controller
An IED that provides data about battery status and controls the charging/de-charging cycles
Current Sensor
current
Data Repository
Data repository for data archiving, analysis or reporting purposes
DISCERN_WP4_D4.2_280114_v3.0
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Actor
Description
Demographic Data Provider
Third party provider of demographic data associated with properties within a geographic
area, e.g. local council
End Point Monitor
A monitor of electricity not used for billing purposes and deployed by the DNO for the
purposes of LV visibility of per-premises consumption
External actor responsible for creating and undertaking analyses providing conclusions that
may inform future business strategy decisions. These analyses include but are not limited
to: modelling, statistical analysis, comparative analysis of options, or generation of
forecasts.
IT
Actor providing IT systems support & maintenance and custodians of digital data inc.
storage, access levels & IT security
LV Grid
Low Voltage (LV) distribution network. Process actuators (e.g. switches or tap changers)
and sensing devices (e.g. current sensors or voltage sensors) within the network are
represented as separated Actors.
Automation system located at operation level (typically in the network control centre of the
DSO) monitoring and controlling the devices in the network.
Power Analysis Tool
Application used to undertake power system analyses, including: power flow analyses,
generation of energy profile data, simulation, etc.
Switch
A generic device designed to close, or open, or both, one or more electric circuits.
Switch Controller
An IED that controls any switchgear. It enables the control from remote centers (tele-control)
and also from related automatics. It supervises the command execution and gives an alarm
in case if improper ending of the command. It can also ask for releases from interlocking,
synchrocheck, autoreclosure if applicable.
Systems Interfacing Support
Actor responsible for delivering & ensuring functional system interfaces,
Tap Changer
Mechanism for changing transformer winding tap positions.
Voltage Sensor
voltage
Table 3-3 shows the five new functions added by B7bd Leaders to the CIM IRM-based abstract
components [IEC 61968-1]. Two of these new functions (Harmonics & Interharmonics and Sequences
& Imbalances) were obtained from [IEC 61850-5] to represent detailed monitoring functions for power
quality analyses. The other ones are extensions to IRM abstract components for better representing
key technical functions in sub-functionality B7bd.
Table 3-3. New functions added for sub-functionality B7bd
Function
Description
Harmonics and Interharmonics
To acquire values from CTs and VTs (or other sensing devices) and to calculate harmonics,
interharmonics and related values in the power system mainly used for determining power
quality
To acquire values from CTs and VTs (or other sensing devices) and to calculate sequences
and imbalances in a three/multiphase power system
Identify optimal monitoring deployment level for effective observability by analysing &
aggregating monitoring data from various sources and assessing results for comparability
and/or using Customer Profiling data for given sections of the distribution network
Identify patterns in the historic load data, whether temporal or spatial, individual or
aggregated, etc.
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Function
Description
This function collects, validates, stores and distributes readings and event-related data
from meters and other end devices to other enterprise functions and systems. The meter
data management function supports diverse end-use applications including but not limited to
billing, load management, load forecasting, demand response, outage management, asset
management and distribution network planning and maintenance.
As regards the standards used by B7bd Leaders to improve interoperability in Communication and
Information Layers it is worth noting the use of IEC 62056 standards (DLMS/COSEM) for
communications in Process, Field and Station zones (see GNF’s and RWE’s solutions), as well as
CIM-based standards in Operation and Enterprise zones (see SSEPD solutions). A detailed analysis
will be realized in tasks T2-3.3 and T5.3.
3.3. B9a – Optimized AMR data collection and analysis using
virtualized as well as physical concentrators
Sub-functionality B9a addresses the optimization of Advanced Meter Reading (AMR) data collection
and analysis using virtualized as well as physical concentrators. As shown in Figure 3-5, in this subfunctionality there is only one Leader (VRD) and one Learner (GNF).
Figure 3-5. Knowledge sharing among DSOs in sub-functionality B9a
3.3.1.
DISCERN_VRD_Leader_B9a
The solution proposed by VRD for sub-functionality B9a is aimed at collecting and storing Smart Meter
readings meeting the collection performance requirements defined by the metering department. The
information obtained from the Smart Meters is stored and analysed at Enterprise level to extract useful
data.
3.3.1.1
1
DISCERN_VRD_Leader_B9a_Use Case
Domain(s)/Zone(s)
ID
DISCERN_VRD_Leader_B9a
Distribution/Process/Field/Station/Customer
Premise/Operation
Name of Use Case
Optimized AMR data collection and analysis
using virtualized as well as physical
concentrators
Version No.
Date
Name
Version Management
Changes
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Approval Status
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Author(s)
11.12.2013
VRD
final
Scope
Objective
AMR, Automated Meter Reading, data collection from residential and small business
customers (max 63A fuse). Collection of data can be both meter readings (hourly, daily,
monthly) and events or alarms, which the meter register.
To meet the requirement of the collection performance of meter readings, defined by the
Metering departments performance criteria. One such criteria is for example, from the turn
of the month the collection performance shall within 96 hours from midnight deliver meter
readings for 99,5% of the available* sites.
The second objective is to collect useful additional information, which the meter can
register, store and export to the collection system. This information are events and alarms,
describing power quality status etc at the location of the meter. Some of the information
are collected in real time, other is collected once per day.
*Available means those meters not being excluded due to an agreed and approved
reason, e.g. power outage.
Short Description
This use case aims to describe the automatic meter reading collection implemented at Vattenfall today, using smart meters as
the foundation for the meter data management. The AMR process at Vattenfall includes all customers. The meters are installed
at each customer and are connected with a Meter Data Concentrator, normally installed in the overlying secondary substation.
The use case will focus on the collection of meter readings, events, alarms and some other functions that the meter supports.
The AMR process is tuned to optimize the meter reading collection for billing purpose, though the process itself produces much
more information which is used, to some extent, in the other operational processes than only billing.
The collection of meter readings, events and alarms within the AMR process is made on a daily basis and to some extent in real
time. The AMR process uses smart meters at the customer site, together with Meter Data Concentrators , normally in the
secondary substation. All data is collected and stored in the AMI Head end (collection system), which reports to the overlying
Meter Data Management System (MDMS). The process main steps for scheduled meter reading collection are:
1. The meter registers the energy consumption meter reading, event or alarm. Vattenfall has defined the meter to register the
accumulated meter stands every hour, starting 00.00. Events or alarms are registered when at the time of occurrence.
2. At regular intervals the Meter Data Concentrator asks the meters for the latest stored meter stands. These are collected
and stored in the Meter Data Concentrator.
3. After midnight the following day the automatic meter reading collection starts. The system calling functions dials each of
the Meter Data Concentrator’s and asks for the meter readings.
4. The Meter Data Concentrator’s sends the last day meter readings (on an hourly basis) to the collection system
5. The collection system makes a check against the meter register if all meters have submitted meter readings. Those meters
missing a meter reading are asked again.
6. The collection performance analysis controls the daily performance and match those meters not having submitted any
meter readings against agreed and approved events. Those meters having an approved event registered at the same time
as the meter reading collection was performed are excluded in the first run in the AMR process.
7. The meters not delivering any meter readings are handled separately in the fault identification and maintenance process.
Most of these meters must be restored within contracted service time to meet the overall contracted SLA level for the
monthly collection performance.
8. The metering collection department makes a first fault analysis and starts a field service errand, which is sent to the field
service entrepreneur.
The process follows the same logic for registering and collecting events and alarms. It is a difference between events and alarm
when it comes to the exporting schedule. Events are collected once a day, but alarms are acted on in “real time”, thereby placed
in a separate “real time export” group to overlying receiving systems.
1. An event or alarms occurs
2. The meter register the event/alarm, together with a time stamp
3. The Meter Data Concentrator collects the information
4. The event/alarm information is exported from the Meter Data Concentrator to the collection system
5. The collection system export the defined events/alarms to the Enterprise system, (Performance Evaluation Reporting
system)
1.5 General Remarks
General Remarks
The deployment of AMR meters ended in 2008 and included in the scope new meters, data collection infrastructure, new
systems and process re-engineering. This use case will in particular focus on the AMR collection using Power Line
Communication (PLC), together with GPRS communication as the main carriers in the data collection process. The meter
DISCERN_WP4_D4.2_280114_v3.0
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communication with the Meter Data Concentrator goes through PLC A-band on the low voltage network and the infrastructure
between the Meter Data Concentrator and the data collection system is the public service GPRS network. The PLC system
consists of Smart Meter device, power cable as transmitter line and Meter Data Concentrator, all in property of Vattenfall. The
GPRS system is from external third party service supplier (telecommunication service), only the front-end device is in property of
Vattenfall. The AMR process is not fully 100% automatic. The meter reading collection can be supported by manually ondemand meter reading requests and the supervision of the daily performance, fault identification and creation of service errands
are made by human operators.
2
Diagram
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Data
Aggregator
LV Grid
(Customer)
Smart meter
AMI Head end
(Secondary
Substation)
PLC
(Titanium)
AMI
Operator
Meter Data
Management
System
Performance
Evaluation
Reporting
MDM Operator
PER Operator
GPRS
Meter readings
Event
Alarm
Meter readings
Event
Alarm
Event
Alarm
Energy
consumption
(kWh)
Meter reading
On-demand reading
Power Switch on/off commands
AMI meter and communication
Asset Management
3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Process
Actor Name
Actor Type
LV Grid
System
Actor Description
this Use Case
Process actuators (e.g. switch controllers or
tap changer controllers) and sensing devices
(e.g. current sensors or voltage sensors)
within the network are represented as
separated Actors.
Actors
Group Description
Grouping
Field
Actor Name
Actor Type
Smart Meter
Component
Actor Description
this Use Case
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
Device designed to be located
at the customer site in order to
register meter readings, power
quality events and alarms.
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A smart meter that can be
controlled remotely to switch on
and of the power by the
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-
-
operator.
Presently in Vattenfall only the
Echelon meters supports
events and alarms. The meter
memory can store 100 events
and a capacity to register
approx. 40 unique
events/alarms. Not all
events/alarms are collected and
exported higher up in the value
chain.
Actors
Group Description
Grouping
Station
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
Actor Name
Actor Type
Meter Data Concentrator
Component
Actor Description
this Use Case
Device or application typically in a substation
which establishes the communication to smart
meters to collect the metered information and
send it in concentrated form to an AMI head
end.
Device designed to be located
either (normally) in the
secondary substation or at
customer site in order to collect
all registered information in the
meters connected to the same
Meter Data Concentrator. The
Meter Data Concentrator stores
all information from the meters
until the information is
submitted to the AMI Head end
system.
The Meter Data Concentrator
itself is a hub with capacity to
also register and log
events/alarms. Together with
the smart meter over 100
unique events/alarms can be
recognized. The memory can
store 100 events. Some of the
events are for example no PLC
connection with the smart
meter, tamper detection, rebooting required, low battery
etc.
Alarms, such as events to be
reported in real time are
colleted by the AMI Head end
system within 5-10 minutes
after occurrence.
The Meter Data Concentrator
also forwards controls from the
AMI Head End to the Smart
Meter.
Service operator GPRS
Role
Operator of the GPRS system
The Meter Data Concentrator is
connected to the low voltage
outgoing feeders from the
secondary substation. Each
Meter Data Concentrator has
the capacity of handling approx.
1000 customers, but the normal
condition is between 600-700
customers.
Operator of the GPRS
communication system.
Actors
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Grouping
Operation
Group Description
Actor Name
Actor Type
AMI Head End
Application
AMI operator
Role
Actor Description
this Use Case
A system which acts as a back-end for the
metering collection and data management.
The system handles and monitors the
collection of information from the Smart
meters and Meter Data Concentrators, by
using the infrastructure of Power Line and
GPRS communication. The collected meter
information is provided for other systems, like
meter data management.
A system for data
management of meter
readings, events and alarms.
Not all events collected from
the smart meters and Meter
Data Concentrator are exported
to the Enterprise systems.
The system monitors the data
collection from the
communication system.
General Operator of the AMI system
The AMI Head end (Titanium)
platform is used for data
collection and management,
device installation
management, reporting,
incident handling and support
and demand side management.
The system is integrated with
the Meter Data Concentrators
and Smart meters through the
software NES, to which it
communicate by XML-file data
exchange.
Operator of the collection
system Titanium, at the data
collection service provider.
A human person supervising
and analyzing the meter
reading process, collection
performance and fault
administration.
Actors
Group Description
Grouping
Enterprise
Actor Name
Actor Type
System
Application
Performance Evaluation
Reporting Database
Application
MDM operator
Role
Actor Description
this Use Case
Meter Data Management System is a system
or an application which maintains all
information to be able to calculate the energy
bill for a customer based on the meter data
retrieved from AMI head end(s). The energy
bill information is typically forwarded to
consumer relationship and billing systems.
System for all meters, as well
as customer information (from
CIS) and information of how the
meter is related to the
secondary substations. The
system also is the data
warehouse for all the meter
readings, except for those
customers (>63A fuse) obliged
to have an hourly meter.
receives, validates, stores and distributes
readings and event-related data from other
end devices to other enterprise functions and
management and distribution network
planning and maintenance.
Application and database to handle the
events, alarms and to follow up the collection
performance of meter readings, according to
the terms and conditions in the data collection
service contract.
Operator of the MDMS system at Distribution.
DISCERN_WP4_D4.2_280114_v3.0
Integrated with AMI Head end
(Titanium) by VPN tunnel using
GS2 file format.
An in-house developed web
based application and database
to handle the events, alarms
and to follow up the collection
performance of meter readings,
according to the terms and
conditions in the data collection
service contract
Integrated with AMI Head end
(Titanium) by VPN tunnel using
XML file format.
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PER operator
Role
Operator of the PER system at Distribution.
Actors
Group Description
Grouping
Market
Actor Name
performance and fault
administration.
performance, events and
alarms.
Actor Type
Actors in Market zone
Actor Description
this Use Case
Use Case Conditions
Triggering Event
Pre-conditions
Smart meter
Time and Events
Events and request
commands from the
Titanium system
AMI Head End
Time and on-demand
request by operators
The meter registeres
the meter readings
every hour.
The meter registers the
defined events and
alarms, together with a
time stamp, at the time
of occurrence.
The Meter Data
Concentrator submitt
the collected data from
the meter in real time
for certain
events/alarms. The
main batches of
measurement values
are submitted after
request from AMI Head
End, mostly at defined
regular intervals. The
Meter Data
Concentrator can also
be triggered to act after
on-demand requests
from AMI Head End
The bulk collection is
started automatically
and made once a day,
starting at midnight.
The on-demand*
requests can be
executed at any time.
The real time events
will be gathered within
0-10 minutes after
occurrence.
(*On-demand
commands also
available through webservice interface, but
requires a log on
account).
Assumption
A reading can be triggered by
change of the electricity supplier or
change of tariff type for the low
voltage consumer of electricity.
3.3 References
No.
Reference Type
Reference
References
Status
Impact on Use
Case
DISCERN_WP4_D4.2_280114_v3.0
Originator/
Organisation
Link
Page 139 of 181
Standard
Standard
Standard
OSGP, (a family of
specifications published by
the European
Telecommunications
Standards Institute (ETSI)
used in conjunction with the
ISO/IEC 14908)
IEC61000-4-30, a standard
which defines Power Quality
phenomena like voltage dip,
swell, unbalanced
PLC CENELEC-A Band
(3 kHz – 95 kHz) are
exclusively for energy
providers
Communication
Layer
ETSI / IEC
Component
,Defines PQ
events used in
Smart meter
devices
Communication
Layer ,
Used for
communication
between smart
meter and data
concentrator via
power line
IEC
Cenelec
Level of Depth
Individual Use Case
Prioritization
Operational track 1
European
Viewpoint
Technical
AMR, AMM, Data collection, Smart Meter, Meter Data Concentrator
4
Scenario Conditions
Triggering Event
No.
Scenario Name
Primary
actor
1
Smart
Meter
Periodically, every hour.
The meter register the
meter readings every
hour
The meter must have
power from the main
fuse. During outages
no registration of
readings are made.
2
AMI Event Service
Management
Smart
Meter
Occurrence of general
events, defined in the
meter, or Meter Data
Concentrator, to be
registered
In general the device
has to support this
functionality.
The device must have
power from the main
no registration of
events or alarms are
DISCERN_WP4_D4.2_280114_v3.0
Pre-Condition
Post-Condition
The smart meter
submits all meter
readings to the
Meter Data
Concentrator, on
request. The
Meter Data
Concentrator
collects and keep
storage of the
meter readings
until the
information is
exported to the
data collection
system
The smart meter
submits all events
to the Meter Data
Concentrator. The
Meter Data
Concentrator
collects and keep
storage of the
Page 140 of 181
No.
Scenario Name
Primary
actor
Scenario Conditions
Triggering Event
Pre-Condition
made.
3
AMI Alarm Supervision
Smart
Meter
Occurrence of urgent
alarms, defined in the
meter, or Meter Data
Concentrator, to be
registered
In general the device
has to support this
functionality.
The device must have
power from the main
no registration of
events or alarms are
made.
4
Meter Data Aggregation
Meter Data
Concentrat
or
Meter readings are sent
from Smart Meter
5
On-demand meter readings
AMI
Operator
On-demand command
from AMI Operator to the
meter for a spontaneous
meter reading
6
Meter power switch on and
off commands
AMI
Operator
On-demand command to
the meter for remote
switch on or off.
7
Meter Data
Manageme
nt System
Meter readings are sent
from the Meter Data
Concentrator
8
AMI Meter and
Communication Network
Asset Management
Performanc
e
Evaluation
Reporting
Database
Missing meter readings
Meter Data
Concentrator is up
and running, and
communications can
be established with
Smart Meters
In general the meter
has to support this
functionality.
The meter(s) must
have power from the
main fuse.
In general the meter
has to support this
functionality.
The meter(s) must
have power from the
main fuse.
Meter Data
Management System
is up and running, and
communications can
be established with
Meter Data
Concentrator
The meters are not
submitting meter
readings or the
communication with
the Meter Data
Concentrator is down.
Post-Condition
meter events until
the information is
exported to the
data collection
system
The smart meter
submits all urgent
alarms to the
Meter Data
Concentrator.
The Meter Data
Concentrator
collect and
identifies the
alarm as a real
time event for
immediate export
to the overlying
Titanium system.
Meter readings
are collected in
the Meter Data
Concentrator
The system
receives a meter
reading “in
between” the
ordinary readings
every hour.
The meter is
switched on or off
from remote after
the command.
Meter data is
stored in Meter
Data
Management
System
Fault identification
with field service
requirements.
Fault may be
individual for
meters or Meter
Data
Concentrator’s, or
they could also be
systematic in
character
Remarks to section 4.1
The scenarios no 8 above will not be described in the next section –4.2 Steps Scenarios. The work within this scenario covers
several different sub-scenarios, depending on the triggering event. The work is also classified as internal business processes at
Vattenfall. Major part of the work is also within the responsibility of contracted entrepreneurs, thereby not known in detail by
Vattenfall.
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Scenario Name:
Step Event
No.
Scenario
1
Continuously
Get voltages and currents
from LV Grid in customer
premises
2a
Periodically
Measure energy
consumption
3a
Periodically
Report meter readings to
Meter Data Aggregation
Periodically
Aggregate meter readings
4a
Periodically
Meter reading collection
5a
Periodically
Meter reading reporting
6a
Periodically
Store meter data in central
Description of
Process/Activity
Service
Information
Exchanged
Smart Meters get
voltages and
currents from LV
Grid
Smart Meters
register the
accumulated
energy used at
the premise where
the meter is being
installed
Meter Data
Concentrator is
collecting the
meter readings
from the smart
meters and stores
the data until the
data is exported to
AMI Head End
(Titanium)
REPORT
LV Grid
Smart Meter
Voltages and
Currents
INTERNAL
PROCESS
Smart Meter
Smart Meter
Meter readings
Smart Meter
Meter Data
Concentrator
Meter readings
INTERNAL
PROCESS
REPORT
Meter Data
Concentrator
Meter Data
Concentrator
Meter Data
Concentrator
AMI Head End
Meter readings
REPORT
AMI Head End
Meter Data
Management System
Meter readings
INTERNAL
Meter Data
Meter Data
Meter readings
Export the
collected meter
readings from the
Meter Data
Concentrator’s to
the AMI Head End
system (Titanium)
Report the
collected meter
readings in
Titanium to the
Meter Data
Management
System.
The Meter Data
REPORT
DISCERN_WP4_D4.2_280114_v3.0
Meter readings
Page 142 of 181
System
7a
On demand by
MDM Operator
Show meter data to MDM
Operator
AMI Event Service Management
2b
Randomly, or
Detect general events*
when the event
occurs
(*General events are
incidents in the network
which are not needed to be
analyzed and acted on in
real time)
3b
Randomly, or
Report general event to
when the event
occurs
4b
Periodically
General event collection
5b
Periodically
General event collection
6b
Randomly, or
periodically when
event occurs
Event follow-up
Management
System stores
meter data
received from
Meter Data
Concentrator
The MDM
Operator access
the meter data
stored in the
Meter Data
Management
System
PROCESS
Management System
Management System
REPORT
Meter Data
Management System
MDM Operator
Meter readings
Smart Meters
register the
incident occurred
in the network at
the premise where
the meter is being
installed
Meter Data
Concentrator is
collecting the
general event
from the smart
meters and stores
the data until the
data is exported to
AMI Head End
system Titanium
Collect the
general events in
the Meter Data
Concentrator’s
into the AMI Head
End system
Titanium
Report the
collected general
events in AMI
Head End
Titanium to the
Performance
Evaluation
Reporting system
Action taken in
different business
processes due to
INTERNAL
PROCESS
Smart Meter
Smart Meter
Events
Smart Meter
Meter Data
Concentrator
Events
REPORT
Meter Data
Concentrator
AMI Head End
Events
REPORT
AMI Head End
Performance
Evaluation Reporting
system
Events
REPORT
Reporting system
PER Operator
Events
REPORT
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an event outcome
received from the
device (Smart
meter or Meter
Data
Concentrator)
2c
On event
3c
On event
4c
On event
5c
On event
Measure urgent alarms*
(*Urgent alarms are events
exported in real time.
Incidents in the network
which are defined to be
passed on to the collection
system immediately after
occurrence to be analyzed
and acted on in “real time”)
Report urgent alarms (real
time events) to Meter Data
Concentrator
Urgent alarm (real time
event) collection
Urgent alarm (real time
Smart Meters
register the
incident occurred
in the network at
the premise where
the meter is being
installed
INTERNAL
PROCESS
Smart Meter
Smart Meter
Alarms
Meter Data
Concentrator is
collecting the
urgent alarms
from the smart
meters and
identifies these as
“real time events”.
Collect the urgent
alarms (real time
events) from the
Meter Data
Concentrator’s
into the AMI Head
End system
Titanium.
The Meter Data
Concentrator
identifies the
urgent alarm as a
“real time event”
and calls
immediately the
overlying Titanium
system to say “I
have an urgent
message”.
Titanium responds
by calling back to
retrieve the urgent
alarm information.
Report the
REPORT
Smart Meter
Meter Data
Concentrator
Alarms
Meter Data
Concentrator
AMI Head End
Alarms
REPORT
REPORT
AMI Head End
Performance
Alarms
DISCERN_WP4_D4.2_280114_v3.0
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event) collection
6c
Randomly, or
periodically when
alarm occurs
Alarm follow-up
On-demand meter readings
8a
On request by
Request an on-demand
AMI Operator
reading of the Smart Meter
9a
On request by
AMI Operator
Send the on-demand
reading request to the
10a
On request by
AMI Operator
Send the on-demand
reading request to the
Smart Meter
11a
On request by
AMI Operator
Show meter readings to
collected urgent
alarms in AMI
Head End
Titanium to the
PER system
Action taken in
different business
processes due to
an alarm outcome
received from the
device (Smart
meter or Meter
Data
Concentrator)
The request is
triggered via the
collection system
Titanium or via a
web interface to
Titanium. The
process is
manual. The AMI
operator registers
the ID of the
Smart Meter and
sends the
command. The
system calls the
Meter Data
Concentrator and
sends the request
for an on-demand
reading.
The on-demand
reading request is
sent from the AMI
Head End to the
Meter Data
Concentrator
The on-demand
reading request is
sent from the
Meter Data
Concentrator to
the Smart Meter
Meter Data
Concentrator is
collecting the
Evaluation Reporting
system
REPORT
Reporting system
PER Operator
Alarms
GET
AMI Operator
AMI Head End
Meter readings
GET
AMI Head End
Meter Data
Concentrator
Meter readings
GET
Meter Data
Concentrator
Smart Meter
Meter readings
Smart Meter
Meter Data
Concentrator
Meter readings
SHOW
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12a
R On request by
AMI Operator
Meter reading collection
13a
Randomly, after
request
Meter reading reporting
Meter power switch on and off commands
8b
On request by
Request a power switch
AMI Operator
on/off of a Smart Meter
9b
On request by
AMI Operator
Send the meter power
switch on/off command to
the Meter Data
Concentrator
meter readings in
the smart meter,
on request by the
AMI Head End
Titanium system.
Export the ondemand
requested and
collected meter
readings from the
Meter Data
Concentrator’s to
the AMI Head End
system Titanium.
Report file with
meter reading
values from the
smart meter being
requested to
submit ondemand readings
Report the
collected meter
readings in AMI
Head End
Titanium to the
Meter Data
Management
System MDMS
The request is
triggered via the
collection system
Titanium or via a
web interface to
Titanium. The
process is
manual. The
operator registers
the ID of the
Smart Meter and
sends the
command.
The system calls
the Meter Data
Concentrator and
sends the request
for an on-demand
reading.
SHOW
Meter Data
Concentrator
AMI Head End
Meter readings
SHOW
AMI Head End
Meter Data
Management System
Meter readings
CHANGE
AMI Operator
AMI Head End
Power On/Off
Commands
CHANGE
AMI Head End
Meter Data
Concentrator
Power On/Off
Commands
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10b
On request by
AMI Operator
Send the meter power
switch on/off command to
the Smart Meter
11b
Randomly, after
request
Meter power switch on/off
execution
12b
Randomly, after
request
feedback
13b
Randomly, after
request
feedback from Meter Data
Concentrator to Titanium
14b
Randomly, after
request
general event from meter
to Meter Data Concentrator
15b
Randomly, after
request
general event from Meter
Data Concentrator to
Titanium
The request from
Titanium is
passed on
through the Meter
Data Concentrator
to the meter of
interest.
The meter
executes the
instruction and
turn on/off the
power supply to
the premise.
The meter
responds by
confirming
success or failure
of the command
The Meter Data
Concentrator
sends the
success/failure
feedback report to
the AMI Head End
system Titanium
The meter sends
one general
event, confirming
the status
The Meter Data
Concentrator
sends the general
event, confirming
the status to AMI
Head End system
Titanium
CHANGE
Meter Data
Concentrator
Smart Meter
Power On/Off
Commands
INTERNAL
PROCESS
Smart Meter
Smart Meter
Power On/Off
Commands
REPORT
Smart Meter
Meter Data
Concentrator
Command
confirmation
REPORT
Meter Data
Concentrator
AMI Head End
Command
confirmation
REPORT
Smart Meter
Meter Data
Concentrator
On/Off report
REPORT
Meter Data
Concentrator
AMI Head End
On/Off report
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5
Name of Information Exchanged
Voltages and Currents
Meter readings
General Events
Alarms
Meter reading showing the value according to
the meter register at the time of the meter
reading. The meter readings are reported
without decimals.
The event and alarms are grouped into the
two categories “General Events” and
“Alarms”. The meter can register something
between 30-40 individual events, but are only
configured to collect and report a sub-portion
of all events available to collect. Some of the
general events are:

Power outage, (start and stop time)

Tamper detection, (for both Smart Meter
and Meter Data Concentrator)

Phase inversion

Reverse energy flow
The event and alarms are grouped into the
two categories “General Events” and
“Alarms”. The meter can register something
between 30-40 individual events, but are only
configured to collect and report a sub-portion
of all events available to collect. Some of the
urgent alarms are:

Meter down (no PLC connection)

Meter up (PLC connection established)

voltage sag

voltage surge

over-current

phase loss

Current flow with no voltage
Power On/Off Commands
Command to the meter to turn on/off the
power supply to the premise.
Command confirmation
The meter responds by confirming success or
failure of the command.
The meter sends a general event, confirming
the status.
On/Off report
7
The two types of events (general and alarm)
are grouped into two different exporting
groups from Titanium to the Enterprise
system Performance Evaluation Reporting.
General events are incidents that can be
reported in the ordinary meter reading
exports to the Enterprise systems.
The two types of events (general and alarm)
are grouped into two different exporting
groups from AMI Head end (Titanium) to the
Enterprise system Performance Evaluation
Reporting. Alarms are urgent events that are
defined to be reported in real time. These are
collected by the Meter Data Concentrator and
“pushed” on to the AMI Head end system
(Titanium). The AMI Head end system
recognize the alarm as urgent and responds
to the signal from the Meter Data
Concentrator by dialing up the Meter Data
Concentrator to collect the alarm information
and export the value in real time to the
Enterprise system. (“Real time” is defined to
be within 5-10 minutes).
The request is triggered via the collection
system Titanium or via a web interface to
Titanium. The process is manual. The
operator registers the ID of the Smart Meter
and sends the command. The system calls
the Meter Data Concentrator and sends the
request for an on-demand reading
Term
Definition
AMI
AMM
AMR
DC
DMS
Echolon
EMI
Advanced Metering Infrastructure
Advanced Meter Management
Data concentrator
Distribution Management System
Smart Meter vendor
The Swedish Government commissioned an investigation on net metering and hourly meter
readings through the Swedish Energy Markets Inspectorate (EMI)
European Telecommunications Standards Institute
Meter Data Management System
Open Smart Grid Protocol fom ETSI
Performance Evaluation Reporting database
Power Line Communication, PLC band A is foreseen for utilities
Power Quality. Definitions based on IEC61000-4-30 e.g. voltage dip, sag
Service Level Agreement
Smart Meter
Virtual Private Network
ETSI
MDMS
OSGP
PER
PLC
PQ
SLA
SM
VPN
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3.3.1.2
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3.3.2.
Summary
Given that there is only one Leader in this sub-functionality it is not possible to compare different
functional architectures. The functional architecture defined in the SGAM Functional Layer of VRD’s
solution shows that Smart Meters generate meter readings, alarms and events. These data are
aggregated at station level in a Meter Data Concentrator and then stored at Enterprise level. Another key
aspect of the solution proposed in terms of functionality is the ability of the AMI Head End to send
commands for performing on-demand readings and switching on/off the Smart Meters.
Table 3-4 shows the new actors added in this sub-functionality to the original actors lists with the aim of
better representing the solution proposed by VRD.
Table 3-4. New actors added for sub-functionality B9a
Actor
Description
LV Grid
Low Voltage (LV) distribution network. Process actuators (e.g. Switches or tap
changers) and sensing devices (e.g. current sensors or voltage sensors) within
the network are represented as separated Actors.
MDM Operator
Operator of the MDM system
PER Operator
Operator of the PER system
Performance Evaluation Reporting Database
Application and database to handle the events, alarms and to follow up the
collection performance of meter readings, according to the terms and conditions
in the data collection service contract
Table 3-5 shows the new functions added in VRD solution to the CIM-IRM abstract components defined
in [IEC 61968-1]. Particularly interesting are the new functions added to represent the commands sent
from the AMI Head End System to the Smart Meters.
Table 3-5. New functions added for sub-functionality B9a
Function
Description
AMI Event Service Management
Provides information on a specific meter or meter group for a particular event. It
acts as a gateway to communicate between utility enterprise systems and field
devices (mostly AMI meters) through AMI network. Allows customer service
representatives and other business personnel to query specific devices to
resolve issues in a short period of time (but not in real time).
Supervision of alarms indicating AMI failure
Meter Power Switch On and Off Commands
Function to switch on/off a meter
On-demand Meter Readings
Function to get on-demand readings from meters
As for the Communication and Information layers it is worth noting again the lack of standard canonical
data models in Leaders’ solutions to improve interoperability within the proposed system. These issues
will be further analysed in T2-3.3 and T5.3.
DISCERN_WP4_D4.2_280114_v3.0
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3.4. B9b – Calculation and separation of non-technical losses
Sub-functionality B9b comprises the solutions for calculating technical and non-technical losses in LV
networks. Figure 3-6 shows the knowledge sharing among DSOs in this sub-functionality. As can be
seen, in this case there is only one Leader (IBR), one Learner (GNF) and one Listener (SSEPD).
Figure 3-6. Knowledge sharing among DSOs in sub-functionality B9b
3.4.1.
DISCERN_IBR_Leader_B9b
The solution proposed by IBR is based on a set of novel algorithms that estimate technical and nontechnical losses for the next day and calculate the real values for the present day.
3.4.1.1
1
DISCERN_IBR_Leader_B9b_Use Case
Name of Use Case
ID
Domain(s)/Zone(s)
DISCERN_IBR_Leader_B9b
Distribution / Operation
Calculation and separation of non-technical losses
Version No.
Date
Name
Author(s)
0.1
0.2
14.10.2013
29.11.2013
IBERDROLA
IBERDROLA
1
04.12.2013
IBERDROLA
Version Management
Changes
First version
Changes after Telco with OFFIS
(12.11.2013)
Consolidate final version
Approval Status
draft
for comments
final
Scope
Objective
Network losses and energy balance
Increase knowledge regarding LV network losses and power flow
DISCERN_WP4_D4.2_280114_v3.0
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Short Description
This Use Case combines real data captured by both SM at customer’s premises and sensors in Secondary Substation with
algorithms to calculate technical and non-technical losses in LV networks and forecast SM consumption.
Taking advantage of the installation of SM at customer’s premises and measurement sensors at Secondary Substations, LV
network losses (technical and non-technical), energy balance and client consumption are estimated for one day ahead before
receiving real measurements and calculated from actual readings to evaluate the precision of the estimations. The information
collected by the latter devices and stored in the Meter Data Management System (MR-MDM) at DSO facilities is used for this aim.
That is: hourly and daily registers of Energies (active and reactive) and Voltage/Current. They are organized in standard reports
defined by the PRIME Alliance in the STG-DC protocol (S02, S05 and S14). The algorithms have these reports along with electrical
data of the LV networks (cables lengths, network layout and cables parameters) and other information such as temperature and
type of day as inputs. The algorithms are launched automatically every day when the information is already in the MR-MDM. The
results are displayed in a graphical visualization tool.
The mentioned reports, S02, S05 and S14 consist on:
S02 – Daily Incremental = Energy: Active (AI, AE) and Reactive (R1, R2, R3, R4) per hour and SM
S05 – Daily Billing Values Profile =Energy: Active (AI, AE) and Reactive (R1, R2, R3, R4) per day and SM
S14 – Voltage and current profile = Voltages and Currents in the LV voltage side of SS per hour and SS
The information contained in these reports for day D-1 (yesterday) is sent from the data concentrators at Secondary Substations to
the Meter Data Management System during day D (today) from 00.00 taking some hours until completion. This process is repeated
daily.
Consequently the Use Case consists on different algorithms which inputs and outputs are in form of reports that are stored in the
MR-MDM and retrieved from there any time they are requested for a calculation. The format of these reports is xml and based on
the standard STG. They are namely univocally using a code close to the denomination of the incoming reports. The algorithms can
be categorized in two groups according to it propose:
•
•
Demand Estimation and the error
Energy Balance and Loss Estimation and the error
It is important to take into account that in day D (today) all algorithms are executed. On the one hand, magnitudes estimation for day
D (because the real reports would be not available jet) are calculated. On the other hand, errors in the estimations for day D-1 are
obtained.
The algorithms are detailed next. It is assumed that the real reports from SM for day D (today) are not available in the MR-MDM
when demands and losses are estimated for day D.
The algorithm runs on
day...
D
Inputs
1. Real S02 and S05
reports for 7 days
before day D (demand
values)
Algorithm
Outputs
Alg1
Demand Estimation
Estimation of the
Demand for day D.
Results in reports
similar to S02 and
S05
2. Other information:
Temperature, type of
day
Alg1 estimates the Demand in hourly and daily bases for day D (today) from real demand reports (S02 and S05) of seven (7) days
coming from SM at client’s premises. They have been stored in the MR-MDM before running the algorithm. The inputs are adjusted
according to temperature records and type of day (labor or holiday). The result are two reports with the same structure of S02 and
S05 that contain the demand estimation for day D (today) That is: Active Energy (AI, AE) and Reactive Energy (R1, R2, R3, R4) per
hour and day for each SM.
day...
Inputs
Algorithm
DISCERN_WP4_D4.2_280114_v3.0
Outputs
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1. Real S02 and
S05 reports for
day D
D+1
2. Estimation of
the Demand for
day D (Alg1)
Alg2
Error in the Demand
Estimation
Error in the Demand
estimation for day D
(hourly and daily).
Alg2 calculates the error in the Demand estimation (hourly and daily). To do that, the output of Alg1 (Demand estimation for day D)
and the real Demand reports collected of day D are compared. The objective of this step is twofold. First, knowing the precision of
the estimation. Second, this value is used by the algorithm itself to learn and then improve its precision for next calculations.
day...
Inputs
Algorithm
Outputs
Alg3
Estimation of
Technical Losses
Estimation of
Technical Losses for
day D
1. Network
characteristics
D
2. Real S02, S05
and S14 for day
D-1 (Demand
values)
Alg3 estimates the Technical Losses for day D (today) from real data from day D-1 and technical data of the LV network (layout,
length and electrical parameter of cables) The output is a report with the following information per SM and section: Active energy
(AI, AE) and Reactive energy (R1, R2, R3, R4) per hour (using S02 as input) and per day (using S05 as input)
day...
D
Inputs
1. Estimation of
the Demand for
day D in form of
S02 and S05
reports (Alg1)
2. Estimation of
Technical
Losses for day D
(Alg3)
Algorithm
Outputs
Alg4
Estimation of Energy
Balance and
Technical and Nontechnical Losses
Balance and
Technical and Nontechnical Losses for
day D
Alg4 estimates the Energy Balance and Technical and Non-technical Losses for day D (today) using the results of Alg1 and 3 as
inputs. That is, Estimation of the Demand for day D and Estimation of Technical Losses for day D respectively. The result is the
estimation of Energy Balance and Technical and Non-Technical Losses for day D.
day...
Inputs
Algorithm
Outputs
Alg5
Technical Losses
Technical Losses for
day D
1. Network
characteristics
D+1
2. Real S02,S05
and S014 for day
D (Demand
values)
Alg5, as Alg3 does, calculates Technical Losses, but instead of a estimation for day D, it returns the actual values because uses
real demand reports (S02, S05 and S14) for day D.
Inputs
Algorithm
Outputs
day...
DISCERN_WP4_D4.2_280114_v3.0
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1. Technical
Losses for day D
(Alg5)
D+1
2. Real S02, S05
and S014 for day
D (Demand
values)
Alg6
Energy Balance and
Energy Balance and
day D
Alg6, as Alg4 does, calculates Energy Balance and Technical and Non-technical Losses, but instead of estimations for day D, it
returns the actual values because uses real demand reports (S02, S05 and S014) and Technical Losses for day D.
day...
Inputs
1. Estimation of
Energy Balance
and Technical
and Nontechnical Losses
for day D
D+1
2. Energy
Balance and
Technical and
Non-technical
Losses for day D
Algorithm
Outputs
Alg7
Error in the Energy
Balance and
Error in the Energy
Balance and
day D.
Alg7 compares both the estimations (Alg4) and real values (Alg6) of Energy Balance and Technical and Non-technical Losses to
determine the error in the calculation.
Finally the results are displayed in a graphical visualization tool downstream from SS. The interface has different options of
visualization: mainly real data (for day D-1) and estimations (day D). Being day D (today) when the operator looks at the
visualization tool, the following information can be obtained:
Real Values from
measurements
Estimations
Other information
Information
Real SM readings (hourly and daily)
Energy Balance
Technical and Non-technical losses
From day...
D-1
D-1
D-1
Estimation of hourly and daily Demand
Error in the Demand estimation (hourly and daily)
Estimation of Energy Balance
Error in the Energy Balance
Estimation of technical and non-technical losses
Error in the technical and non-technical losses estimation
D
D
D
D
D
D
Statistics
Maps
-
1.5 General Remarks
General Remarks
Pilot Implementation
The implementation of the present Use Case in the PRICE pilot combines both an already deployed AMI infrastructure and some
servers, out of the DSO systems, used exclusively for the pilot. To help the reader to go through the Use Case, it has been decided
to include the chain of main actors and flow of information downstream of the core of the Use Case, that is the algorithms
philosophy. It is not intended to provide an executive description of the AMI architecture.
The architecture outside of the DSO systems is explained in the following figure
DISCERN_WP4_D4.2_280114_v3.0
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System
ftp server
Data (real
S02, S05,
S014 reports)
coming from
the DSO
Systems
Server
- Network data
- Algorithms
- Report from DSO and generated in each
step
- Visualization tool
The main pieces of equipment at field are: Smart Meters at client’s premises, Meter Data Concentrators, Voltage Sensors (normally
included within the Meter Data Concentrator) and Current Sensors at Secondary Substations; while in the DSO facilities there is the
AMI End Head. Basically, the flow of information downstream of the Use Case core is established as followed. First, Smart Meters,
among other functions, measure Active and Reactive power flowing to/from the client houses. This information is received by the
AMI End Head every day after having been both collected and sent upwards by the Meter Data Concentrators. The mentioned S0x
files in xml format are created at the AMI End Head.
A script has been developed to be able to send periodically and automatically real S02, S05 and S014 reports to a ftp server which
needs to be emptied periodically. Therefore, it is used as a mailbox for these reports before being stored in other servers. All
algorithms, data needed to run them, reports generated in each step and the visualization motor are housed likewise in these
servers. All of these machines belong to one partner of the pilot, outside of the DSO systems. The visualization tool is accessible
remotely.
The electrical parameters of the network for the grid modelling and calculations are given only once and stored in the servers. The
communication protocol used between the DSO systems and the ftp server is a secured TCP/IP.
This Use Case, at its first stage, considers measurement equipment installed in SS and clients’ premises in the LV (P < 15kW).
Therefore, later equipment for P > 15 kW would be necessary to perform a complete LV network analysis.
Important:
The PRIME project is still developing this Use Case. Therefore, it might happen that the content of the present Use Case
can be modified as the project evolved.
Pending to confirm if finally the S014 will be used.
2
Diagrams
DISCERN_WP4_D4.2_280114_v3.0
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DISCERN_WP4_D4.2_280114_v3.0
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3
Technical Details
3.1 Actors
Actors
Group Description
Grouping
Process
Actor Name
LV Grid
Actor Type
Component
Layer Actor
Actor Description
this Use Case
Low Voltage (LV) distribution network. Process
actuators (e.g. Switches or tap changers) and
sensing devices (e.g. current sensors or voltage
sensors) within the network are represented as
Measurements are taken from
cables or control panels at the
LV site of Secondary
Substations
DISCERN_WP4_D4.2_280114_v3.0
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Current Sensor
Component
Layer Actor
separated Actors.
continuously reporting dynamic status of current
Voltage Sensor
Component
Layer Actor
continuously reporting dynamic status of voltage
Grouping
Field
Actor Name
Smart Meter
Group Description
Actor Type
Component
Grouping
Station
Actor Type
Component
Grouping
this Use Case
The metering end device is a combination of the
following meter-related 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
Smart Meters are located at
client’s premises.
Actor Description
this Use Case
Device or application typically in a substation
which establishes the communication to smart
meters to collect the metered information and
send it in concentrated form to an AMI head end
One Meter Data Concentrator
located in each Secondary
Substation. They collect Smart
Meter measurements to be
send to upper systems.
Group Description
Actor Name
Actor Type
AMI Head End
Component
AMI Operator
Role
Grouping
Enterprise
Actor Description
Group Description
Actor Name
Operation
LV current sensors located
close to the LV panel in
LV voltage sensors located
close to the LV panel in
Secondary Substation.
Sometimes these
measurements are performed
internally in the Meter Data
Concentrator
Actor Description
this Use Case
A system which acts as back-end for the
metering communication and controls and
monitors the communication to the meter
devices. The collected meter information is
provided for other system like meter data
management
General Operator of the AMI system
It collects data from Smart
Meters and measurements from
different sensors installed at the
LV side of Secondary
Substations.
Group Description
Actor Name
Actor Type
System
System
This would represent the people
that use the graphical interface
to calculate and monitor the
losses.
Actor Description
this Use Case
Meter Data Management System is a system or
an application which maintains all information to
be able to calculate the energy bill for a
customer based on the meter data retrieved
from AMI head end(s). The energy bill
information is typically forwarded to consumer
relationship and billing systems.
collects, validates, stores and distributes
readings and event-related data from other end
devices to other enterprise functions and
management and distribution network planning
and maintenance.
This actor would represent the
servers used in the pilot,
although are external to the
DSO systems. They are used to
storage reports from the DSO
systems, reports with the results
of the algorithms, house and run
the algorithms and the graphical
interfaced tool.
DISCERN_WP4_D4.2_280114_v3.0
Named in this document as
MDM
Page 163 of 181
Use Case Conditions
Triggering Event
Pre-conditions
Reports needed for
each specific
algorithm are already
stored there. These
reports can be those
sent by the Data
Concentrator in the
SS or the results of
previous algorithms
Assumption
The process to
send the reports
from SS or
previous
algorithms to
generate them
have been
launched and
finished
3.3 References
References
Impact on Use Case
No.
Reference
Type
Reference
Status
1
Regulatory
constraint
RD 1955/2000
from December
1st
Release 2000
2
Regulatory
constraint
Release 2006
3
Regulatory
constraint
RD 1634/2006
from December
29th
RD 222/2008
4
Regulatory
constraint
Orden
ICT/3801/2008
Release 2008
5
Regulatory
constraint
Orden
ITC/2524/2009
Release 2009
6
Report
Ministry web page
Web page
7
Standard
8
Standard
IEC 62056
(DLMS/COSEM)
PRIME
Specification
revision v1.3.6
Release 2008
Business Layer –
Definition of QoS
indexes and their
regulatory limits
Business Layer –
update of some QoS
limits
Business Layer –
description
remuneration
methodology for
DSO activities
Business Layer –
for QoS
Business Layer –
for losses
Business Layer –
Spanish data base
of QoS
Originator/
Organisation
Link
Ministry/System
Operator
http://www.boe.es/
Ministry/System
Operator
http://www.boe.es/
Ministry/System
Operator
http://www.boe.es/
Ministry/System
Operator
http://www.boe.es/
Ministry/System
Operator
http://www.boe.es/
Ministry/DSO
https://oficinavirtual.
mityc.es/eee/Conexi
on/listadoNotas.asp
x
IEC
Draft
PRIME Alliance
http://www.primealliance.org/wpcontent/uploads/201
3/04/PRIMESpec_v1.3.6.pdf
Level of Depth
Individual Use Case
Prioritization
Operational track 2
European level
Viewpoint
Technical
LV losses, Power Flow, Energy Balance
DISCERN_WP4_D4.2_280114_v3.0
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4
Scenario Conditions
Triggering Event
No.
Scenario Name
Primary
actor
1
Measuring
Periodically
The communication
are established
between the devices
The Mater Data
Concentrator
collect the data
2
Smart
Meter,
Voltage
Sensor,
Current
Sensor
Smart
Meters
Periodically
3
Management
Meter Data
Managemen
t System
Periodically
4
Load Forecast
Meter Data
Managemen
t System
-The algorithm received
the starting signal
-The information
requested is received
The Mater Data
Concentrator
collect the data
The information is
received by the
Meter Data
Management
System from the
AMI Head End
Demand is
forecasted
5
Line Losses
Meter Data
Managemen
t System
the starting signal
-The request information is
received by the Meter
6
Management
Meter Data
Managemen
t System
Periodically
7
Load Forecast
Meter Data
Managemen
t System
the starting signal
-The information
requested is received
8
Line Losses
Meter Data
Managemen
t System
the starting signal
-The request information is
received by the Meter
9
Network Displays
The communication
are established
between the devices
The algorithms Alg1,3
& 4 have been
programmed to start
periodically at certain
time over an specific
LV network
-The information
needed by the
algorithm has been
received and it is
ready to be used.
-There is not any issue
that stops the
algorithm to start.
-The information
needed by the
algorithms has been
received and it is
ready to be used.
that stops the
algorithms to start.
Algorithms Alg2,,5, 6 &
7 have been
programmed to start
periodically at certain
time over an specific
LV network
-The information
needed by the
algorithm has been
received and it is
ready to be used.
that stops the
algorithm to start.
-The information
needed by the
algorithms has been
received and it is
ready to be used.
that stops the
algorithm to start.
-All algorithms have
finished
-All information is
available for the
graphical tool
AMI
Operator
There is the need to
visualise the LV network
status regarding losses
and demands
DISCERN_WP4_D4.2_280114_v3.0
Pre-Condition
Post-Condition
Energy Balance,
Technical and
Non-technical
losses estimation
are estimated
The information is
received by the
Meter Data
Management
System from the
AMI Head End
Error in the
demand estimation
is calculated
-Line losses are
estimated.
-Error in the line
losses are
calculated.
The information is
displayed on a
screen.
Page 165 of 181
Scenario Name :
Ste
Event
p
No.
1a
Run in day D Periodically
2a
Measuring
1b
Scenario
Description of
Process/Activity
Service
Information
Exchanged
Active power,
Reactive power,
voltages (pending to
confirm) at
household level
[among other
data out of the
scope of the Use
Case]
Active power,
Reactive power,
voltages (pending to
Measure consumption at
client’s premises
Smart Meters
collect electrical
measurements
from clients
premises
REPORT
LV Grid
Smart Meter
Report Smart Meter
readings to Meter Data
Concentrator
Smart Meter
readings are made
available for the
Meter Data
Concentrator
REPORT
Smart Meter
Meter Data
Concentrator
Voltage Sensors
get measures from
LV Grid
Current Sensors
get measures from
LV Grid
Voltage Sensors
readings are
made available for
the Meter Data
Concentrator
Current Sensors
readings are made
available for the
Meter Data
Concentrator
REPORT
LV Grid
Voltage Sensor
Voltage
measurement
REPORT
LV Grid
Current Sensor
Current
measurement
REPORT
Voltage Sensor
Meter Data
Concentrator
Voltage
measurement
REPORT
Current Sensor
Meter Data
Concentrator
Current
measurement
AMI Head End
Voltage and
Current
measurement,
Active power,
Reactive power,
voltages
(pending to
confirm) ) at
1c
2b
Measure voltage in LV
grid (Secondary
Substation)
Measure current in LV
Grid (Secondary
Substation)
Report LV voltages to
2c
Report LV currents to
3
Run in day D Report LV data to the
Periodically
AMI Head End
All the LV data
collected are made
available to be
storage in the AMI
Head End
confirm)
REPORT
Meter Data
Concentrator
DISCERN_WP4_D4.2_280114_v3.0
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household level
4
Report the LV reports to
the Meter Data
Management System
The LV reports are
made available to
the Meter Data
Management
System
REPORT
AMI Head End
Meter Data
Management System
5
Provide LV network data
to be used be some
algorithms (only once)
REPORT
AMI Operator
Meter Data
management System
6
Start of algorithms
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Start signal
10
Run in day D+1 Periodically
Start of algorithms
Algorithms (Alg3 &
5) need this
information to
estimate and
calculate Technical
Losses
Algorithms (Alg1, 3
& 4) start
automatically in day
D at the
programmed time
Algorithms (Alg2, 5,
6 & 7) start
automatically in day
D+1 at the
programmed time
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Start signal
The demand is
estimated for day D
in hourly and daily
bases
The Error in the
demand estimation
for day D is
calculated
The algorithm for
demand estimation
learns from the
accuracy of
previous
calculations
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Demand
estimation
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Error in the
estimation
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Modifications in
the algorithm
The Technical
losses are
estimated for day D
Energy Balance,
Technical and Nontechnical losses are
estimated for day D
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Technical losses
estimation
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Energy Balance,
Technical and
Non-technical
losses
estimation
Load Forecast
7
Run in day D Alg1 operates
Estimation of demand
11
Run in day D+1 Alg2 operates
Error calculation in the
demand estimation for
day D
12
Run in day D+1 Alg2 finishes
Alg1 learns from the error
Line Losses
8
9
Estimation of Technical
losses
Balance, Technical and
Non-technical losses
DISCERN_WP4_D4.2_280114_v3.0
Voltage and
Current
measurement,
Active power,
Reactive power,
voltages
(pending to
confirm)
LV network data
Page 167 of 181
13
Technical losses
14
Energy Balance, Technical
and Non-technical losses
15
Error in the estimation of
Energy Balance, Technical
and Non-technical for day
D
Network Displays
16a
Run in day D+1 All algorithms are
finished
Get the results of the
algorithms
17a
Show the results of the
algorithms
16b
Get the results of the
algorithms
17b
Show the results of the
algorithms
The Technical
losses are
calculated for day
D from actual
reports
Energy Balance,
Technical and
Non-technical
losses are
estimated for day
D
The Error in the
estimation of
Energy Balance,
Technical and
Non-technical for
day D is calculated
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Technical losses
calculation
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Energy Balance,
Technical and
Non-technical
losses
calculation
INTERNAL
PROCESS
Meter Data
Management System
Meter Data
Management System
Error in the
estimation
The AMI operator
checks the
graphical
information tool to
visualize data
The request
information is sent
by the AMI Head
End
Information to be
displayed is
requested to the
AMI Head End
The information is
displayed in the
graphical
information tool
and seen by the
AMI operator
GET
AMI operator
Meter Data
Management System
Results of the
algorithms
SHOW
AMI Head End
Meter Data
Management System
Results of the
algorithms
GET
Meter Data
Management System
AMI Head End
Results of the
algorithms.
SHOW
Meter Data
Management System
AMI operator
Results of the
algorithms.
DISCERN_WP4_D4.2_280114_v3.0
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5
Name of Information
Exchanged
Measurements of voltage for the three phases of the LV
side in Secondary Substations.
Measurements of current for the three phases of the LV
side in Secondary Substations.
Smart Meters readings that are used in the development
of the Use Case. They are reading of Active Power (in
two quadrants) and Reactive Power (in four quadrants)
for all Smart Meters with a granularity of 1 hour.
Current measurements
Active power, Reactive power,
voltages (pending to confirm) at
household level [among other
data out of the scope of the Use
Case]
LV network data
Results of the algorithms and
real reports.
7
Requirements to Information
Data
This information is collected by Meter Data Concentrator
(including voltage and current at LV level at Secondary
Substations) and send to the AMI End Head. From this
system, this information in made available to the Meter
Data Management System (the servers in the pilot) in
form of standardised reports to be used by the
algorithms.
S02, S05 and S14 are the reports used by some of the
algorithms. S02 contains hourly active (AI, AE) and
reactive (R1, R2, R3, R4) energy per SM. S04 contains
daily active (AI, AE) and reactive (R1, R2, R3, R4)
energy per SM. S14 contains hourly voltage and currents
per Secondary Substation. These reports are defined
and standardized by the PRIME Alliance in the STG-DC
protocol in xml format.
Electrical data to characterised cables and voltages
levels in the LV network
Information displayed in the graphical interface tool
(results of the algorithms)
Term
Definition
AI / AE
Alg
D
D+1
D-1
MDM
R1 / R2 / R3 / R4
S02
S05
S14
SM
SS
LV
DSO
Import and Export Active Energy
Algorithm
Today
Tomorrow
Yesterday
Reactive Energy in the four quadrants
Daily Incremental report
Daily Billing Values Profile
Voltage and current profile
Smart Meter
Low Voltage
Distribution System Operator
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3.4.1.2
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3.4.2.
Summary
As in sub-functionality B9a, it is not possible to compare different functional architectures in subfunctionality B9b. The functional architecture proposed by IBR shows that the main technical functions
in this sub-functionality (Load Estimation and Line Losses calculation) are performed at Enterprise
level in a Meter Data Management System, which collects the data from an AMI infrastructure similar
to that defined by VRD in B9a.
No new actors and functions were needed for representing the solution of IBR. This means that the
standard-based actors and functions in the original lists were sufficient to represent the system to
calculate technical and non-technical losses.
In Communication and Information layers it should be noted the use of IEC 62056 DMLS/COSEM for
communications between Smart Meters and the Meter Data Concentrator as well as the PRIME
Alliance STG-DC 3.0 data model for the information exchanges at Enterprise level.
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4. Conclusions
The objective of task T4.2 was to define new system functionalities for the demo-sites. In DISCERN,
the definition of new system functionalities is given by knowledge sharing from Leading DSOs (with
good knowledge on the functionalities gained from previous research and demonstration projects) to
Learning DSOs, which are willing to implement these functionalities in DISCERN. Therefore,
deliverable D4.2 presented the solutions proposed by Leaders in the form of Use Cases and SGAM
models by using the standard-based templates created in [D1.3]. These Use Cases and SGAM
models were grouped into the following DISCERN sub-functionalities identified in [D1.1]:
•
B6 – Optimal MV network monitoring and automation
•
B7 – Real time monitoring of LV grid
•
B9a – Optimized AMR data collection and analysis using virtualized as well as physical
concentrators
•
B9b – Identification of technical and non-technical losses
For all these DISCERN sub-functionalities, Leaders’ Use Cases and SGAM models were presented
and analysed. The analyses were focused on the actors and functions used in the descriptions,
highlighting the proposed extensions to the available lists of actors and functions in the state of the art
[SGCG-FSS], [ENTSOE-RM], [IEC 61968-1]. This resulted in a first assessment of the existing
standards (particularly the CIM Interface Reference Model [IEC 61968-1]) in the context of DISCERN
solutions. Moreover, the refined lists of actors and functions produced in T4.2 is a first step towards
the definition of consolidated lists (or taxonomies) that could be reused beyond the project with the aim
of facilitating knowledge sharing among European DSOs. Table 4-1 and Table 4-2 show the new
actors and functions proposed in this task, respectively. The final lists will be obtained after T4.3 (in
which Learners will define their own Use Cases and SGAM models) and will be annexed in deliverable
D1.3.
Table 4-1. New actors proposed by Leaders
Actor
Description
Controller
Battery
Battery Controller
Current Sensor
Data Repository
Demographic Data Provider
Device or application which operates the tap changer
automatically according to given set points or by direct
operator commands (manual mode).
One or more cells fitted with devices necessary for use,
for example case, terminals, marking and protective
devices.
An IED that provides data about battery status and
controls the charging/de-charging cycles
continuously reporting dynamic status of current
B6
B7bd
B9b
X
X
X
X
X
Data repository for data archiving, analysis or reporting
purposes
X
Third party provider of demographic data associated with
properties within a geographic area, e.g. local council
X
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Actor
Description
End Point Monitor
IT
LV Grid
MDM Operator
Device that indicates the presence and direction of a
fault current in the cables where the device is located
External actor responsible for creating and undertaking
analyses providing conclusions that may inform future
business strategy decisions. These analyses include but
are not limited to: modelling, statistical analysis,
comparative analysis of options, or generation of
forecasts.
Actor providing IT systems support & maintenance and
custodians of digital data inc. storage, access levels & IT
security
Low Voltage (LV) distribution network. Process
actuators (e.g. Switch or tap changers) and sensing
devices (e.g. current sensors or voltage sensors) within
PER Operator
B7bd
B9a
X
X
X
X
X
X
X
Automation system located at operation level (typically in
the network control centre of the DSO) monitoring and
controlling the devices in the network.
X
Operator of the PER system
X
Reporting Database
Application and database to handle the events, alarms
and to follow up the collection performance of meter
readings, according to the terms and conditions in the
data collection service contract
X
Power Analysis Tool
Application used to undertake power system analyses,
including: power flow analyses, generation of energy
profile data, simulation, etc.
Switch
Switch Controller
Systems Interfacing Support
Tap Changer
Voltage Sensor
A generic device designed to close, or open, or both, one
or more electric circuits.
An IED that controls any switchgear. It enables the
control from remote centers (tele-control) and also from
related automatics. It supervises the command execution
and gives an alarm in case if improper ending of the
command. It can also ask for releases from interlocking,
synchrocheck, autoreclosure if applicable.
Actor responsible for delivering & ensuring functional
system interfaces,
Mechanism for changing transformer winding tap
positions.
continuously reporting dynamic status of voltage
B9b
X
Operator of the MDM system
Medium Voltage (MV) distribution network. Process
actuators (e.g. Switchs or tap changers) and sensing
devices (e.g. current sensors or voltage sensors) within
MV Grid
B6
A monitor of electricity not used for billing purposes and
deployed by the DNO for the purposes of LV visibility of
per-premises consumption
X
X
X
X
X
X
X
X
X
B6
B7bd
Table 4-2. New functions proposed by Leaders
Group
Function
Network
Operation
Monitoring
Harmonics and
Interharmonics
Network
Operation
Monitoring
Sequences and
Imbalances
Network
Operation
Monitoring
Monitoring
Optimisation
Description
To acquire values from CTs and VTs (or other sensing
devices) and to calculate harmonics, interharmonics and
related values in the power system mainly used for
determining power quality
To acquire values from CTs and VTs (or other sensing
devices) and to calculate sequences and imbalances in
a three/multiphase power system
Identify optimal monitoring deployment level for effective
observability by analysing & aggregating monitoring data
from various sources and assessing results for
comparability and/or using Customer Profiling data for
given sections of the distribution network
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B9a
B9b
X
X
X
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Group
Function
Description
B6
B7bd
X
X
B9a
Network
Control
Automatic
Controls
Automatic controls, functions to optimize network
operation, such as: automatic tap changer control,
automatic voltage control, reactive control, load
shedding, busbar change, etc.
Network
Operation
Calculations
Load Pattern
Identification
Identify patterns in the historic load data, whether
temporal or spatial, individual or aggregated, etc.
Advanced
Metering
Infrastructure
AMI Event
Service
Management
Provides information on a specific meter or meter group
for a particular event. It acts as a gateway to
communicate between utility enterprise systems and
field devices (mostly AMI meters) through AMI network.
Allows customer service representatives and other
business personnel to query specific devices to resolve
issues in a short period of time (but not in real time).
X
Advanced
Metering
Infrastructure
AMI Alarm
Supervision
Supervision of alarms indicating AMI failure
X
Function to switch on/off a meter
X
Function to get on-demand readings from meters
X
Metering
System
Metering
System
Metering
System
Meter Power
Switch On and
Off Commands
On-demand
Meter Readings
Meter Data
Management
This function collects, validates, stores and distributes
readings and event-related data
from meters and other end devices to other enterprise
functions and systems. The meter data management
function supports diverse end-use applications including
but not limited to billing, load management, load
forecasting, demand response, outage management,
asset management and distribution network planning
and maintenance.
B9b
X
X
In sub-functionalities B6 and B7bd there was more than one Leader. This enabled the comparison
between different solutions having different perspectives and scope. Deliverable D4.2 showed how the
use of common standard-based formats for representing the solutions facilitated this task. Given that
the objective of D4.2 referred to new system functionalities, these comparisons were focused on the
functional architectures defined in the SGAM Function Layers.
Regarding the next steps of the project:
•
In T4.3 Learners will define their preferable system architectures taking into account the
present system architectures [D4.1] and the new system functionalities provided by Leaders in
D4.2.
•
All the Use Cases and SGAM models defined by both Leaders (T4.2) and Learners (T4.3) will
be stored in a common repository (T2-3.2), which will be a Web-based application enabling
the access and editing of the models, as well as the automatic analysis of Use Cases and
SGAM models in order to extract relevant data from them.
•
Learners will then define the technical specifications of their solutions (T5.3) and the
implementation plan (WP7), and the technical assessment based on KPIs will be carried out in
WP8.
•
Detailed standards assessments (introduced in D4.2) will be performed in T2-3.3 and T5.3.
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5. References
5.1. Project documents
[D1.1] – Deliverable 1.1: “List of agreed KPIs with associated metrics and refined smart grids
functionalities list”
[D1.3] – Deliverable 1.3: “List of agreed KPIs with associated metrics and refined smart grids
functionalities list”
[D2.1/3.1] – Deliverable 2-3.1: “Catalogues and description requirements for distributed devices and
communication architectures”
[D4.1] – Deliverable 4.1: “Identification of present system architecture”
[D4.3] – Deliverable 4.3: “Preferable general system architecture, integrations and user interface”
5.2. External documents
[EU-EG1] – “Functionalities of smart grids and smart meters”, EU Commission Task Force for Smart
Grids Expert Group 1, 2010.
[EG3-Roles&Responsabilities] – “Expert Group 3: Roles and Responsibilities”, EG3 Deliverable, EU
Commission Task Force for Smart Grids of Actors involved in the Smart Grids Deployment, April 2011.
[ENTSOE-RM] – “The Harmonised Electricity Market Role Model”, European Network of Transmission
System Operators for Electricity (ENTSO-E), January 2011.
[IEC 61850-5] – “Communication Networks and Systems in Substations - Part 5: Communication
Requirements for Functions and Device Models”, IEC TC57 WG10, April 2013.
[IEC 61968-1] – “Application integration at electric utilities – System interfaces for distribution
Management - Part 1: Interface architecture and general recommendations”, IEC TC57 WG13,
October 2010.
[IEC 62357] – “TC 57 Architecture - Part 1: Reference Architecture for TC 57”, IEC TC57 WG19,
September 2009.
[IEC 62559-2] – “Use case methodology - Part 2: Definition of use case template, actor list and
requirement list”, IEC TC8, April 2013.
[M/490] – “Smart Grid Mandate: Standardization Mandate to European Standardisation
Organisations(ESOs) to support European Smart Grid deployment”, European Commission
Directorate-General for Energy, March 2011.
[SGCG-FSS] – “First Set of Standards”, CEN-CENELEC-ETSI Smart Grid Coordination Group,
November 2012.
[SGCG-SGAM] – “Smart Grid Reference Architecture”, CEN-CENELEC-ETSI Smart Grid Coordination
Group, November 2012.
[SGCG-UCMP] – “Sustainable Processes”, CEN-CENELEC-ETSI Smart Grid Coordination Group,
November 2012.
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6. Revisions
6.1. Track changes
Name
Date
(dd.mm.jjjj)
Version
Changes
Subject of change
Rafael Santodomingo / OFFIS
09.12.2013
0.1
First draft version
19.12.2013
0.2
Complete Use Cases and
SGAM models
11.01.2013
1.0
New version after internal
revision by WP4 members
Miguel García / Ángel Yunta /
GNF
17.01.2013
2.0
Revision – step 1
All
Thomas Theisen / Carmen
Calpe / Olaf Neumann / RWE
DAG
28.01.2014
3.0
Revision – step 2
All
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DISCERN WP4 D4.2 New system functionality

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