- EvolvDSO

Transcription

- EvolvDSO

evolvDSO
Development of methodologies and tools for new and
evolving DSO roles for efficient DRES integration in
distribution networks
Schedule of field and laboratory tests and synchronisation with simulations
[Revision 1.0]
Schedule of field and laboratory tests
and synchronisation with simulations
Document Information
Programme
FP7 – Cooperation / Energy
Project acronym
evolvDSO
Grant agreement number
608732
Number of the Deliverable
D4.1
WP/Task related
WP4 / T4.1
Type (distribution level)
PU
Date of delivery
06-11-2015
Status and Version
V1.0
Number of pages
80
Document Responsible
ERDF (Task leader)
Author(s)
Maria SEBASTIAN VIANA (ERDF), Mathieu CAUJOLLE
(EDF R&D); Raphael CAIRE (G-INP), José Sanchez (GINP), Jorge ALVES (EDP Distribuição), Diogo LOPES (EDP
Distribuição), Ana Carina MORAIS (EDP Distribuição),
Ricardo BESSA (INESC Porto), Daniele CLERICI (RSE),
Eoghan OCALLAGHAN (ESB), Paul CUFFE (UCD), Andrew
KEANE (UCD), Alizera SOROUDI (UCD), Gabriele
BARTOLUCCI (ENEL)
Reviewers
Marco BARON (ENEL), Diana MONETA (RSE), Daniele
CLERICI (RSE)
Copyright evolvDSO project
Page 2 of 80
[Revision 1.0]
Revision History
Version Date
0.0
03/07/2015
Author/Reviewer
M. CAUJOLLE,
M. SEBASTIAN
0.1
22/07/2015
0.2
07/09/2015
0.3
18/09/2015
0.4
0.5
21/09/2015
30/09/2015
B. MYSOREVASUDEVARAO,
R. CAIRE
M. CAUJOLLE,
M. SEBASTIAN
R. BESSA, A.C.
MORAIS, D. LOPES,
J. ALVES
M. CAUJOLLE
D. CLERICI
0.6
05/10/2015
0.7
09/10/2015
0.8
0.9
0.95
22/10/2015
06/11/2015
13/11/2015
1.0
17/11/2015
R. BESSA, A.C.
MORAIS, D. LOPES,
J. ALVES
P. CUFFE, A KEANE,
E. OCALLAGHAN, A.
SOROUDI
J. SANCHEZ
G. BARTOLUCCI
M. BARON,
D. MONETA,
D. CLERICI
M. CAUJOLLE, J. BOS
Notes
First draft, initiation of the different chapter
title, skeleton and guidelines for the content
expected
Material for the methodology proposed is
presented in depth
1st content added for ERDF field test sections
1st content added for EDP field test sections
Completed ERDF field test sections
Correction to the Contingency Simulator
section
Completed EDP field test sections
Content ESB trial sections
Completed methodology section
ENEL field test sections
Format review of RSE and ENEL
Final version and approval Management
Board evolvDSO
Page 3 of 80
[Revision 1.0]
Executive Summary
The present deliverable D4.1, entitled “Schedule of field and laboratory tests and
synchronisation with simulations”, describes the methodology used for selecting the trials
considered in WP4. It also provides a detailed insight into the field and laboratory test sites
chosen by the DSOs as well as into the tools associated to these trials.
The report first provides information about the process inspired by IEC/PAS 62559 IntelliGrid
Methodology that was followed by each DSO to select which tools he would consider and to
which test site he would envision to apply them. The ten tools developed in the framework of
WP3 to support the new and evolving roles of the DSOs were considered.
In a second part, the report describes the field and laboratory tests selected by the DSOs and
the tools developed by the research institutes that will be applied in this context. These tests
complement the validation tests performed by the research institutes and detailed in
Deliverable D3.4. They will help the DSOs to operate the WP3 tools being considered and assess
their value and applicability within the real operational environment of distribution networks.
The system use cases defined in WP2 are used as a framework for the considered test scenarios.
Three domains out of the four considered in WP3 are covered by the field and laboratory tests:
TSO-DSO Coordination, Network Operation, and Network Maintenance. In this report, a
description of the trials is provided for each thematic after a short description of the involved
tools. The objectives, the outline of the test and its associated preparations and conditions are
given each time. Planning domain is not covered by the field and laboratory tests because the
DSOs involved in the evolvDSO project have already installed this kind of tools in their internal
systems.
Table 1 provides an overview of the six selected tools developed by the research institutes and
the different trials where they will be applied by the DSOs.
EDP
ENEL
ERDF
ESB
Field and laboratory Northern Site Southern Site Milano Centro
SOGRID
VENTEEA Various MV
tests
HV&MV test site HV&MV test site
Prove
MV&LV test site MV test site networks
(Lab)
(Field)
(Field)
(Lab)
(Field)
(Field)
Interval
Constrained
Tested
Tested
/
Tested
Tested
/
Power Flow
INESC Sequential
Tested
Tested
/
/
/
/
OPF
LV State
/
/
/
Tested
/
/
Estimation
Contingency
/
/
/
/
Tested
/
RSE Co-Simulation
ENEL
Replay
/
/
Tested
/
/
/
UCB
Advanced
Asset
Management
/
/
/
/
/
Tested
Table 1 – Synthesis of the trials and tools considered in WP4
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TSO-DSO Coordination Domain
Two tools are considered for the “TSO-DSO Coordination” domain:
 The Interval Constrained Power Flow (ICPF) tool that estimates the flexibility range
and cost in each primary substation node for the next hours;
 The Sequential Optimal Power Flow (SOPF) tool that computes a set of control actions
that keep the active and reactive power flow within pre-agreed limits at the primary
substations level.
Two field tests are considered in this context:
 The EDP field tests involve two HV & MV test sites, one in the North of Portugal in the
vicinity of Porto and the other one in the South in the vicinity of Lisbon. In these two
sites, both the ICPF and the SOPF will be considered and integrated into EDP
system infrastructure. An open-loop integration is envisioned for the SOPF since the
set-points it generates are presented to the operator and not directly transmitted to
network equipment. The ICPF is not concerned since it only provides forward-looking
information to the DSO network operator;
 The ERDF field tests involve two MV test sites, one in the North of France (VENTEEA)
and the other one in the South (SOGRID). In both sites, the ICPF will be considered and
integrated into ERDF system infrastructure. The integration will be limited to an
open-loop since the ICPF only provides forward-looking information to the DSO
network operator, no control signal is computed by the algorithm.
Operational Domain
Three tools are considered for the “Operational” domain:
 The Contingency Co-Simulation (CCS) tool. It selects and simulates realistic
contingencies. It also identifies suitable levers to provide corrective actions and policies
to solve them in the more efficient way, taking ICT performance into account;
 The LV State Estimator (LVSE) tool that predicts the state of the network by making
use of historical data and a low number of real-time measurements from Smart-Meters;
 The Replay tool that focuses on the investigation of grid management to analyse past
events and re-simulate them to improve grid management policies, as well as on new
software/hardware technical solutions testing and operators training.
Two field tests are considered in this context:
 The ERDF field tests involve a MV test site in the North of France (VENTEEA) and a LV
test site in the South (SOGRID):
o The CCS tool will be applied to the MV test site. It will be integrated into ERDF
system infrastructure in the same way as the ICPF tool. It will provide forwardlooking set-points to the operator that will help him to manage its network;
o The LVSE tool will be applied to the LV test site on several LV substations.
Decentralized real-time integration of the algorithm will be simulated based on
the measurement data collected from the field both in real-time and in batch that
is stored within ERDF system.
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
The ENEL trials involve several MV feeders that will be selected from the Cagliari
network (Sardinia). The Replay tool will be applied to these networks within the
Milano Smart Grid Lab in order to perform ex-post analysis of past real events or
predictive analysis by introducing events and/or managing the available network
flexibilities.
Maintenance Domain
One tool is considered for the “Maintenance” domain: the Advanced Asset Management
(AAM) tool. This tool is comprised of an Asset Renewal algorithm that aims at providing the
most efficient way to schedule the upgrade of network components and of a Maintenance
Priorities algorithm that helps distribution system operators to efficiently manage outage risks
on the networks they maintain.
In the ESB trials, the demonstration of the AAM tool will be done through computer simulation.
No field trial will be performed to demonstrate this tool, but the AAM will be used within the
asset management offices by ESB network design planners and strategists during a
series of interactive demonstration events. A number of networks with different topologies
will be considered to demonstrate the value and applicability of the tool in a real-life
environment.
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Table of contents
Revision History ......................................................................................................................................................... 3
Executive Summary ................................................................................................................................................... 4
Table of contents ........................................................................................................................................................ 7
List of Figures .............................................................................................................................................................. 9
List of Tables ..............................................................................................................................................................10
1.
2.
Introduction ......................................................................................................................................................11
1.1.
Scope of the document .........................................................................................................................11
1.2.
Structure of the document ..................................................................................................................12
1.3.
Notations, abbreviations and acronyms ........................................................................................12
Trials selection process ................................................................................................................................14
2.1.
Methodology description of the survey involving the questionnaires ..............................14
2.2.
Feedback from the survey and analysis of the responses ......................................................16
2.2.1.
3.
Major highlights ..............................................................................................................................19
Trials and tools for simulation ..................................................................................................................20
3.1.
Thematic: TSO-DSO Coordination ....................................................................................................20
3.1.1.
Introduction .....................................................................................................................................20
3.1.2.
Short description of the tested algorithms ..........................................................................20
3.1.2.1.
Interval Constrained Power Flow ...................................................................................20
3.1.2.2.
Sequential OPF .......................................................................................................................22
3.1.3.
3.1.3.1.
Test objectives ........................................................................................................................25
3.1.3.2.
Description of the test site .................................................................................................26
3.1.3.3.
General outline of the test scripts ...................................................................................30
3.1.3.4.
Preparations and conditions.............................................................................................31
3.1.4.
3.2.
Portuguese field tests / trials: EDP .........................................................................................25
French field test / trials: ERDF .................................................................................................34
3.1.4.1.
Test objectives ........................................................................................................................34
3.1.4.2.
Description of the test sites ...............................................................................................35
3.1.4.3.
3.1.4.4.
Thematic: Operation ..............................................................................................................................42
3.2.1.
Introduction .....................................................................................................................................42
3.2.2.
3.2.2.1.
State Estimation for LV networks ...................................................................................42
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3.2.2.2.
Contingency Co-Simulation ...............................................................................................45
3.2.2.3.
Replay ........................................................................................................................................48
3.2.3.
3.2.3.1.
Test objectives ........................................................................................................................50
3.2.3.2.
Description of the test site .................................................................................................52
3.2.3.3.
3.2.3.4.
3.2.4.
3.3.
French field tests / trials: ERDF ...............................................................................................50
Italian field tests / trials: ENEL ................................................................................................58
3.2.4.1.
Test objectives ........................................................................................................................58
3.2.4.2.
3.2.4.3.
3.2.4.4.
Thematic: Maintenance ........................................................................................................................67
3.3.1.
Introduction .....................................................................................................................................67
3.3.2.
3.3.2.1.
3.3.3.
4.
Optimal Asset Management ..............................................................................................67
Irish field test / trials: ESB .........................................................................................................74
3.3.3.1.
Test objectives ........................................................................................................................74
3.3.3.2.
3.3.3.3.
3.3.3.4.
Conclusions .......................................................................................................................................................78
REFERENCES .............................................................................................................................................................80
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List of Figures
Figure 1 - Relationship between P and Q in the boundary nodes (with no dependence between
P and Q) ........................................................................................................................................................................21
Figure 2 - Relationship between P and Q in the boundary nodes (considering a dependence
between them) ..........................................................................................................................................................21
Figure 3 – Sequential optimal power flow diagram process (VVC - Voltage Var Control) ..........23
Figure 4 – Inputs and outputs of the Sequential OPF tool ........................................................................24
Figure 5 - Geographical representation of the Portuguese demo sites ...............................................26
Figure 6 – HV network schematic representation (northern demo site)...........................................27
Figure 7 - Typical load diagram of N1 HV/MV substation .......................................................................28
Figure 8 - Typical load diagram of N2 HV/MV substation .......................................................................28
Figure 9 - HV network schematic representation (southern demo site) ...........................................29
Figure 10 - Typical load diagram of S1 HV/MV substation .....................................................................30
Figure 11 - Typical load diagram of S2 HV/MV substation .....................................................................30
Figure 12 – Location of the 2 MV field tests considered in France .......................................................36
Figure 13 – Anonymized topological representation of the MV feeders considered in the SOGRID
project...........................................................................................................................................................................37
Figure 14 – Anonymized topological representation of the 6 MV feeders considered in the
VENTEEA project .....................................................................................................................................................38
Figure 15 – Scheme of the proposed DSE algorithm ..................................................................................44
Figure 16 – Pseudo-sequential MCS applied to active distribution grid reliability analysis flow
chart ..............................................................................................................................................................................46
Figure 17 – Co-simulation module architecture. .........................................................................................47
Figure 18 – Data flow needed for Replay tool ...............................................................................................49
Figure 19 – Example of topological representation of a French LV network. The phase
connection of each component (source, transformer, lines, and loads) is displayed ....................53
Figure 20 – Replay tool running in the Smart Grid Lab and test site in Sardinia ............................63
Figure 21 – Simplified scheme of the network (Replay tool) .................................................................63
Figure 22 – Schematic for the Real Operation System (ST) in the Smart Grid Lab in Milano ....64
Figure 23 – Replay tool functional architecture...........................................................................................64
Figure 24 – General overview of the Asset Renewal sub-tool optimization process ....................68
Figure 25 – Detailed view of the Asset Renewal sub-tool optimization process ............................69
Figure 26 – General overview of the Maintenance Priorities sub-tool optimization process....70
Figure 27 – Detailed view of the Maintenance Priorities sub-tool optimization process ............71
Figure 28 – Nature of the inputs required by the Asset Renewal sub-tool .........................................72
Figure 29 – Nature of the inputs required by the Maintenance sub-tool ...........................................73
Figure 30 – Inputs and outputs of the Asset Management Software tool ..........................................75
Figure 31 - A sample network, where the branch thickness corresponds to the outage Risk
associated with that component ........................................................................................................................76
Figure 32 - Another sample network, where the branch thickness shows the degree to which
each conductor should be uprated in this planning period .....................................................................76
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List of Tables
Table 1 – Synthesis of the trials and tools considered in WP4 ................................................................. 4
Table 2 – Synthesis of the trials and tools considered in WP4 ...............................................................12
Table 3 - Mapping of Developer tools with its partner..............................................................................15
Table 4 - Extract from the actual survey questionnaire derived from the IEC 62559 IntelliGrid
standards .....................................................................................................................................................................15
Table 5 – Extract of the DSO survey (ERDF) regarding the Network State Estimation ................16
Table 6 – Extract of the DSO survey (ERDF) regarding the Interval Constrained Power Flow .17
Table 7 - Extract of the developer survey (INESC) regarding the Interval Constrained Power
Flow ...............................................................................................................................................................................19
Table 8 – Fulfilment of the WP2 System Use Case requirements in the Portuguese test-field
regarding the ICPF tool ..........................................................................................................................................33
Table 9 – Fulfilment of the WP2 System Use Case requirements in the Portuguese test-field
regarding the Sequential OPF tool.....................................................................................................................34
Table 10 – Fulfilment of the WP2 System Use Case requirements in the French field test
regarding the ICPF tool ..........................................................................................................................................41
regarding the Contingency Co-Simulation tool ............................................................................................57
regarding the LV DSE tool .....................................................................................................................................58
Table 13 – summary of test cases in WP3 (Replay tool)...........................................................................60
Table 14 – Overview of WP4 test cases (Replay tool) ...............................................................................61
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1. Introduction
1.1.
Scope of the document
The present deliverable D4.1, entitled “Schedule of field and laboratory tests and
synchronisation with simulations”, describes the methodology used for selecting the trials
considered in WP4. It also provides a detailed insight into the field and laboratory test sites
chosen by the DSOs as well as into the tools associated to these trials.
The report first provides information about the process inspired by IEC/PAS 62559 IntelliGrid
methodology that was followed by each DSO to select the tools to be considered and to which
test site apply them. The ten tools developed in the framework of WP3 to support the new and
evolving roles of the DSOs were considered. Six tools covering three out of the four domains
were retained at the end of this process.
In a second part, the report describes the field and laboratory tests selected by the DSOs and
the tools developed by the research institutes that will be applied in this context. These tests
complement the validation tests performed by the research institutes and detailed in
Deliverable D3.4. They will help the DSOs to operate the WP3 tools being considered and assess
their value and applicability within the real operational environment of distribution networks.
The system use cases defined in WP2 are used as a framework for the considered test scenarios.
Three domains out of the four considered in WP3 are covered by the field and laboratory tests:
TSO-DSO Coordination, Network Operation and Network Maintenance. In this report, a
description of the trials is provided for each thematic after a short description of the involved
tools. The objectives, the outline of the test and its associated preparations and conditions are
given each time. Planning domain is not covered by the field and laboratory tests because the
DSOs involved in the evolvDSO project have already installed this kind of tools in their internal
systems.
Table 2 provides an overview of the six selected tools developed by the research institutes and
the different trials where they will be applied by the DSOs.
Page 11 of 80
[Revision 1.0]
EDP
ENEL
ERDF
ESB
Field and laboratory Northern Site Southern Site Milano Centro
SOGRID
VENTEEA Various MV
tests
Prove
(Lab)
(Field)
(Field)
(Lab)
(Field)
(Field)
Interval
Constrained
Tested
Tested
/
Tested
Tested
/
Power Flow
INESC Sequential
Tested
Tested
/
/
/
/
OPF
LV State
/
/
/
Tested
/
/
Estimation
Contingency
/
/
/
/
Tested
/
RSE Co-Simulation
ENEL
Replay
/
/
Tested
/
/
/
UCB
Advanced
Asset
Management
/
/
/
/
/
Tested
Table 2 – Synthesis of the trials and tools considered in WP4
1.2.
Structure of the document
The document is organized as follows:
 Section 2 provides the feedback from the survey made it through questionnaires were
answered by the various partners and used for the trials selection process;
 Section 3 presents the trials and tools for simulation grouped on the three domains:
TSO-DSO Coordination, Network Operation and Network Maintenance;
 Section 4 presents the conclusions of the deliverable
1.3.
Notations, abbreviations and acronyms
ADEME
AE
CCS
CDF
CEI
CHP
CIM
CSV
DB
DC
DER
DMS
DRES
DSE
DSO
EMS
EHV
Agence de l'Environnement et de la Maîtrise de l'Énergie
Autoencoder
Contingency Co-Simulation
Common Data Format
Commission Electrotechnique International
Combined Heat and Power
Common Information Model
Comma Separated Value
Data Base
Direct Current
Distributed Energy Resources
Distribution Management System
Distributed Renewable Energy Sources
Distribution State Estimator
Distribution System Operator
Energy Management System
Extra High Voltage
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ELM-AE
EPSO
GPRS
GUI
HV
ICPF
ICT
IEC
IEEE
KPI
LF
LV
LVSE
MCS
MTTF
MTTR
MV
NPV
OLTC
OPF
PLC
RES
RETIM
RTU
SAIDI
SCADA
SM
SUC
TSO
UMTS
VVC
WP
Extreme Learning Machine Autoencoder
Evolutionary Particle Swarm Optimisation
General Packet Radio Service
Graphical User Interface
High Voltage
Interval Constrained Power Flow
Information and Communication Technologies
International Electrotechnical Commission
Institution of Electrical and Electronic Engineers
Key Performance Indicator
Load Flow
Low Voltage
Low Voltage State Estimator
Monte Carlo Simulation
Mean Time To Failure
Mean Time To Repair
Medium Voltage
Net Present Value
On Load Tap Changer
Optimal Power Flow
Power Line Communication
Renewable Energy Sources
Real Time Monitoring Interface
Remote Terminal Unit
System Average Interruption Duration Index
Supervisory Control And Data Acquisition
Smart Meters
System Use Case
Transmission System Operator
Universal Mobile Telecommunications System
Volt VAr Control
Work Package
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2. Trials selection process
2.1.
Methodology description of the survey involving the
questionnaires
The technologies of the project partners’ should be examined in the planning stage and
assessment of technologies is to be done. Therefore, Grenoble INP is proposing a survey to
perform a detailed assessment of the technologies of the partners.
The following questions are included in the survey which is inspired by IEC/PAS 62559
IntelliGrid methodology.











Level of Standardization - Who recognizes it as a standard?
Level of Openness – How easy/costly is it to obtain and use?
Level of Adoption – How widely used is it now? In the future?
Users’ Group Support – Does someone promote it? Improve it? Test it?
Security – Can it be secured? Is it inherently secure?
Manageability – Can it be controlled, monitored and/or upgraded automatically?
Scalability – Will it work when deployed at a large number of sites?
Object Modelling – Does it group and structure data?
Self-Description – Can it automatically configure and initialize itself?
Applicability to the Power Industry – Was it intended for use here?
Applicability to this particular problem domain.
Considering the methodology from IEC/PAS 62559 IntelliGrid, a test architecture is produced
which highlights all the tools to be Developed/Tested with respect to the partners involved.
This matrix clearly indicated what tools need to be developed and by which of the partners.
The next section of the survey involved questions for DSO partners. This involves a set of DSO
Generic questions and a set of DSO specific questions. By answering the DSO Generic questions,
a general inference about the overall technology architecture can be derived. By answering the
DSO specific questions, a specific inference about the tools and technologies of a DSO can be
derived.
Next part of the survey is the simulation questions. Like the DSO questions section, this section
is also divided into two parts: Generic simulation questions and Specific simulation questions.
It performs essentially the same function as before, i.e. providing general and specific
technological inferences from generic and specific questions respectively.
The next section of the survey involves the developer questions. The tools to be developed are
mapped on to the partner who is responsible for its development.
Table 3 describes the mapping of Developer tools with the partner.
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1: Interval Constrained Power Flow
2: Sequential OPF
3: State Estimation for LV Networks
Questions for the developer "INESC"
4: Voltage Control for LV Network
5: Robust Short-Term Economic Optimization Tool Questions for the developer
for Operational Planning
"INPG/VITO/RSE"
6: Co-Simulation
Questions for the developer "RSE"
7: Network Reliability
Questions for the developer "ENEL"
8: Advanced Asset Management
9: Short-term network reinforcements considering
flexibilities and ICT reliability (FLEXPLAN)
10: Long-term network topologies using stochastic
modelling (TOPPLAN)
Questions for the developer "UCD"
Questions for the developer "RWTHFGH"
Questions for the developer "INPG"
Table 3 - Mapping of Developer tools with its partner
The developers are presented with questions which are extracted from the IEC/PAS 62559
IntelliGrid methodology which is targeted to extract maximum information from a particular
developer with respect to a particular domain.
Table 4 is an extract from the actual survey questionnaire which describes the questions from
the IEC/PAS 62559 standards with respect to the domain exclusively adapted for the
developers and the project.
Domain
Level of Standardization
Level of Openness
Level of Adoption
Users' Group Support
Cyber-Security
Manageability
Scalability
Object Modeling
Self-Description
Cost
Questions to ask
Who recognizes it as a standard?
How easy/ costly is it to obtain and use?
How widely used is it now? In the future?
Does someone promote it? Improve it? Test it?
Can it be secured? Is it inherently secure?
Can it be controlled, monitored and/or upgraded automatically?
Will it work when deployed at a large number of sites?
Does it group and structure data (such as the 61850 or CIM
structures)?
Can it automatically configure and initialize itself?
The cost of adopting the tools developed during WP3 for WP4
experiments (e.g. License of specific software or database
compared to the use of free open source ones, that can be
commercially exploited, among others)
Table 4 - Extract from the actual survey questionnaire derived from the IEC 62559 IntelliGrid standards
The same question pattern is followed by all the developers in the projects. From this survey a
lot of information can be analysed and retained, which will be discussed in the section 2.2
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2.2.
Feedback from the survey and analysis of the responses
In the section 2.1, we discussed about the methodology description of the survey. In this section,
we will discuss about the feedback from the survey after the survey questionnaires were
answered by the various partners.
In order to do so let us consider each section step by step and analyse each response from the
project partners.
The first section describes the DSO questions. The DSO generic questions were discussed in
the previous section. The responses to the generic questions are targeted to get an overall
description about the architecture of technologies. For example, the first set of DSO generic
questions was about the Network State Estimation as shown in Table 5.
Questions to ask
Example of
possible answers
“ERDF” Answers (Answer as "too early to respond is
possible")
Presence of
sensors
Yes
No
Voltage & PQ sensor at MV feeder level
On some demonstration sites: Voltage & PQ sensors
at LV level.
Yes
No
Not at an industrial scale.
Work in progress:
 real-time (10 min) MV state-estimation
 day ahead optimization
Presence of
State Estimation
Table 5 – Extract of the DSO survey (ERDF) regarding the Network State Estimation
By answering such questions, each DSO sets a tone for the upcoming development of tools. It
gives overall information of the capabilities of the partner’s technology infrastructure. In the
case of Table 5, from the answers it can be retained that the DSO is planning to improve its
infrastructure by implementing the State-Estimation at the MV-Level. But, from other DSO it
could be retained that the State Estimation is not relevant.
The next part of the survey is the DSO specific questions. This section gives very specific
information about various technological architectures that a DSO possesses. It will help decide
the testing sites during the lifecycle of the project.
This is also a platform for the DSO partners to showcase their technologies. These showcases
will enable all the partners to select the suitable test sites by telling which tool can be tested or
deployed. This will give an added value to the DSOs technology infrastructure.
Let us consider a part of the DSO specific questionnaire from the survey response (Table 6).
This particular part of the survey concerns the Interval Constrained Power Flow. The questions
related to this are as shown in Table 6. By asking such specific questions, we can analyse the
current technological infrastructure of the DSO partners with respect to the evolvDSO project.
For example, the response from ERDF is as follows:
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Example of possible “ERDF” Answers (Answer as "too early to
answers
respond is possible")
- Existing
In progress but within a different context
- In progress
regarding the TSO/DSO contract :
Concerning the tool, is your - No
 P optimization: minimization of
company already having it
the overruns regarding the
included in an Internal
subscribed power(s) (-> no
Roadmap, leading to
objective for P defined by
developments in few
min/max values);
month/years?
 Q optimization: limit the Q
variations regarding specified
limits (-> same as here)
- Already covered
Not
up to date
Is this feature already
Not up to date. Development of the
covered by an Internal tool? Must be challenged
industrial tool in progress.
No equivalent
Information such as:
Prerequisite to test the tool
availability of Network
(e.g. either mandatory data,
information (from
see data set collection or
Forecasted load and generation curves.
sensors), actuators,
combination with other
market data and others
existing/external tools)
tools (Load flow, SE…)
If this specific tool is not
suiting to the main targeted
If No: Open description
trial site but can be tested
of the alternative trial
on an alternative trial;
description of it
Questions to ask
Table 6 – Extract of the DSO survey (ERDF) regarding the Interval Constrained Power Flow
In the first question “Concerning the tool, is your company already having it included in an
Internal Roadmap, leading to developments in few month/years?” with three possible
responses, the response is “In progress but within a different context regarding the TSO/DSO
contract:
 P optimization: minimization of the overruns regarding the subscribed power(s) (-> no
objective for P defined by min/max values);
 Q optimization: limit the Q variations regarding specified limits (-> same as here)”
Sometimes the tools intended to be developed in one project are already partially or completely
being developed for a different project. By identifying development of similar tools within a
firm, knowledge can be interchanged.
In the above response it can be noted that, ERDF is showcasing its ongoing research project
which is an added value.
The next part of the survey questionnaire is the INESC simulation. The questionnaire in this
section is exactly similar to the one in the DSO section consisting of both Generic and Specific
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Questions. The inference that can be made from the responses from INESC is that the Generic
questions responses are similar to that of the DSO ones but the Specific questions are based on
the Simulation technological architecture. Lot of the questions in this section are not applicable
since the test architecture is simulated.
Let us now discuss about the outcome of the survey questionnaires from the developer point of
view. In the previous section, the project partners are mapped with the technology that they
will be developing. Since the questionnaire is very specific, the answers are equally specific.
The developer questions follow the IEC 62559 IntelliGrid standards by asking exactly the
questions described in the previous section for each tool that has to be developed.
By adhering to the IEC 62559 IntelliGrid standards, one can extract maximum information for
a particular section from the survey.
Let us consider the developer responses in detail. For example, let us consider the INESC
responses.
Domain
Questions to ask
Level of
Standardizatio
n
Who recognizes it as a
standard?
Level of
Openness
How easy/ costly is it to
obtain and use?
Level of
Adoption
How widely used is it
now? In the future?
Users' Group
Support
Does someone promote
it? Improve it? Test it?
Cyber-Security
Can it be secured? Is it
inherently secure?
Manageability
Can it be controlled,
monitored and/or
upgraded remotely?
Answers (Answer as "too early to
respond” is possible)
This tool is not recognizable as a standard.
The idea of estimating the flexibility at the
primary substation level is not adopted in
any country. Nevertheless, it uses an OPF,
which can be considered as a widespread
adopted algorithm.
It is an innovative tool and therefore difficult
to purchase from a software vendor. The cost
of using the tool is only associated to receive
data close to real-time (e.g., communication
costs), buy or generate load and RES
forecasts and a license for using the tool.
Presently, this tool (or similar) is not being
used by any DSO. With the increasing
flexibility in the distribution system, it is
foreseen that an estimation of the flexibility
aggregated up to the primary substation
level will be useful in the future for TSO/DSO
cooperation tasks.
This tool was not improved or tested by a
third-party.
This tool does not interact with any resource
connected to the distribution grid, it is only
informative.
This possibility is not covered in the current
version of the tool.
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Domain
Scalability
Object
Modeling
SelfDescription
Cost
Questions to ask
Will it work when
deployed at a large
number of sites?
Does it group and
structure data (such as
the 61850 or CIM
structures)?
Can it automatically
configure and initialize
itself?
The cost of adopting the
tools developed during
WP3 for WP4
experiments (e.g. License
of specific software or
database compared to the
use of free open source
ones, that can be
commercially exploited,
among others)
Answers (Answer as "too early to
respond” is possible)
Scalability is not a problem. The tool can
handle MV and HV grids of different size.
Uses the Common Data Format (IEEE CDF)
This possibility is not covered in the current
version of the tool.
Proprietary software is not embedded. All
the modules are distributed under a license
distributed by INESC Porto, according to the
Consortium Agreement.
Table 7 - Extract of the developer survey (INESC) regarding the Interval Constrained Power Flow
From the above table, it can be noted that the amount of information that can be extracted from
a particular domain is immense. INESC was able to answer questions precisely and to the point
which is very important. The survey enables us to target the extraction of data for a specific
task.
Partners can easily refer to the section and can interpret a lot of data from it at any point during
the lifecycle of the project.
2.2.1. Major highlights




The survey was able to give an overall description of the technological infrastructure of
each and every partner in the project.
The survey is a platform on which the partners were able to showcase their technologies
which adds values.
Detailed description of the technological capabilities of each partner with respect to a
particular tool can be extracted.
It also opens up communication channels between partners to enable sharing of
technological support with respect to the tools which are being developed. The
partners will thus be able to give precise and detailed feedback for the tools which are
being tested.
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3. Trials and tools for simulation
3.1.
Thematic: TSO-DSO Coordination
3.1.1. Introduction
The tools and the field tests associated to the “TSO-DSO Coordination” domain that were
selected after the application of the methodology described in Chapter 2 are presented here.
Two tools are considered: the Interval Constrained Power Flow tool estimating the flexibility
range in each primary substation node for the next hours, and the Sequential Optimal Power
Flow tool computing a set of control actions that keep the active and reactive power flow within
pre-agreed limits at the primary substations level. The principles used by these algorithms are
briefly recalled.
The EDP and the ERDF field tests are then presented in details. Each involves at least one of
these tools. The objectives, the description and the general outline of the trials as well as their
associated preparations and conditions are provided.
3.1.2. Short description of the tested algorithms
3.1.2.1. Interval Constrained Power Flow
3.1.2.1.1. Algorithm objectives
The Interval Constrained Power Flow (ICPF) tool developed by INESC TEC (formerly INESC
Porto) is a tool that works in the “TSO-DSO coordination” domain. Its main goal is to estimate
the flexibility range at the TSO-DSO boundary (primary substations) by aggregating the
distribution network flexibility in order to enable a technical and economic evaluation of the
flexibility required from the bulk power system point of view.
This tool estimates a region of feasible values of active and reactive power for the power flow
exchanged at the boundary nodes between the transmission and distribution networks.
Several kinds of flexibility levers can be considered by the ICPF tool in order to optimize the
network operation regarding the active and reactive power boundaries imposed at the TSO /
DSO level in a fixed topology of the network:
 DSO assets:
o On-load tap-changers (OLTC);
o Reactive power compensation (e.g., capacitor banks).
 Loads and generators:
o Active power flexibility (flexibility band and price) from different mechanisms.
o Dynamic (or non-firm) connection contracts of loads and generators;
o Mid-term bilateral flexibility contracts → flexibility tenders;
o Flexibility offers submitted to the constraints management market or any other
short-term flexibility market.
More information about the ICPF tool features can be found in Deliverable D3.3 [3].
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3.1.2.1.2. General overview of the algorithm operation
The ICPF tool allows to find a region of feasible values for the active (P) and reactive (Q) powers
exchanged at the TSO-DSO boundary nodes. If there is no dependence between P and Q, the
flexibility region that might be provided at the boundary nodes by the distribution network
would be only constrained by the active and reactive power limits. Figure 1 illustrates this case.
Figure 1 - Relationship between P and Q in the
boundary nodes (with no dependence between P
and Q)
However, due to the dependence between both powers, every P and Q values inside the region
cannot occur at the same time. In this case the flexibility region that might be provided at the
boundary nodes is presented in Figure 2.
The algorithm developed by INESC in order to find the feasible values within this region is
based on:
 Maximizing/minimizing the active power in the boundary node, while keeping the
reactive power constant in that node;
 Performing this optimization for different reactive power values between Qmin and
Qmax.
Figure 2 - Relationship between P
and Q in the boundary nodes
(considering a dependence
between them)
The objective function integrated in the ICPF tool does not need to keep constant the reactive
power and avoids running optimization processes for unfeasible values of the reactive power.
The coefficient 𝛽 that corresponds to the identification of the tangent lines of the flexibility area
perimeter and their respective intersection points in the (P, Q) plan, could be defined in an
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intelligent way in order to better explore the flexibility perimeter, which minimizes the
computational effort.
3.1.2.1.3. Input data requirements
Several input data types are required by the ICPF tool:
 Grid topology and electrical parameters data. The file with the network topology and
electrical parameters should be updated automatically for any change in the network
topology (component disabled, switch opening / closure…);
 Load and generation data. The static data of the loads and generators (e.g., rated
power, contracted power) should be available in the network file;
 Grid current state. The current state of the network equipment (e.g. tap position of
OLTC and capacitor banks) should be available. The ideal would be to have the future
(or planned) states for the next hours;
 Technical constraints of the network;
 Active power flexibility from loads and generators. Information about the flexibility
band and cost for the next hours. This should be automatically updated in case of any
change;
 Load (net-load) and RES forecasts for each network node. These short-term
forecasts should include information regarding active and reactive power (or a power
factor) for each network node;
 Operating points of power plants and loads. Operating point (i.e., result of the market
dispatch) of power plants and loads that participate in the electricity market is required.
3.1.2.2. Sequential OPF
The Sequential Optimal Power Flow (Sequential OPF) tool developed by INESC TEC (formerly
INESC Porto) is a tool that works in the “TSO-DSO coordination” domain. Its main goal is to
reduce the flexibility operational costs, assuring the proper functioning of the network within
a given timeframe. Generically, this tool proposes to define the state of the contracted flexible
resources and the resources owned by the DSO for each time interval during the desired
operational planning period, aiming to guarantee to the TSO agreed active and reactive power
domains at primary substations.
The Sequential OPF tool returns the best configuration scheme and the optimal value for the
other control variables of the problem. To do this, the module needs all the information about
the elements of the network and their characteristics as tool inputs. The information about
power injection and flexibilities range should come from forecasts, while the information about
the network devices characteristics is constant over the timeframes. Figure 3 shows the steps
which the SOPF tool follows in order to achieve the final solution.
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Figure 3 – Sequential optimal power flow diagram process (VVC - Voltage Var Control)
The objective of the algorithm is to find a solution with smaller operation costs associated to
activation of flexibility resources and penalties for violating active and reactive power limits at
the TSO/DSO boundary. For that, the algorithm searches for the best topology configuration
and optimal values for control variables related to Voltage Var Control (VVC) including
limitations on DSO-TSO active and reactive power flows interchanges. The mathematical
formulation is defined in Deliverable D3.3 [3].
The algorithm implemented to solve this problem starts with an initial topological
configuration, and then generates a set of different configurations which are moving in the
space of solutions (change the switches’ state) in order to find the optimal configuration (i.e.,
minimum power losses). All configurations which do not belong to the admissible space
because they are violating the technical limits should be penalized in order not to be chosen.
The algorithm chosen to solve this problem is the Evolutionary Particle Swarm Optimization
(EPSO) together with some local heuristics which have the information about the relation
between the decision variables and their effects on constraints. These heuristics have the
function of assuring the topological admissibility of found solutions and adjusting variables
related to voltage control. Thus, these heuristics change some variables related to voltage
control so that some penalized solutions (that are not satisfying the voltage criteria or branch
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limits) may become feasible solutions. In the end, the Sequential OPF tool is capable to provide
as outputs the initial and final network topology, the corresponding power profile at each
substation and the changes of all control variables.
After the execution of EPSO to perform network reconfiguration and reactive power dispatch,
a Voltage-Var control algorithm is applied to make the final adjustments of control taps,
improving the final solution for the problem.
Regarding this tool, the main contribution from the evolvDSO project is the design of a single
tool that integrates different types of flexibility (e.g., demand-response, flexible generation,
capacitors banks, and network reconfiguration) and that fully tackles the problem of managing
the active and reactive power flows in the TSO-DSO boundary.
The module needs all the information about the elements of the network and their
characteristics as tool inputs. As we can see in the Figure 4, the module needs the information
about all network assets, their technical characteristics and settings. In order to perform the
optimization considering consecutive timeframes, the tool receives the information about all
the power injection profiles for each period. The tool retrieves data from the input grid (e.g.,
equipment status, “normal” network topology), but there is some additional information such
as flexibility prices and inter-temporal constraints which this format does not include.
Figure 4 – Inputs and outputs of the Sequential OPF tool
The information about power injection and flexibilities range should come from forecasts,
while the information about the network devices characteristics is constant over the
timeframes.
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3.1.3. Portuguese field tests / trials: EDP
3.1.3.1. Test objectives
The Portuguese field tests encompass two tools, ICPF and Sequential OPF.
The ICPF tool contributes to estimate the flexibility range of active (P) and reactive (Q) power,
with a specific time horizon and update rate (according to the prediction system available at
EDP and rate of information exchange), at the nodes in the boundary between transmission and
distribution systems (primary substation), considering the available flexibility at the
distribution network level. The sequential OPF defines a set of control set-points to control the
P and Q power exchange between the transmission and distribution grids.
Only the flexibility resources available in the selected networks are considered. They mainly
consists of capacitor banks, OLTC, bilateral flexibility contracts of MV loads and wind farms
with non-firm connection contract (i.e., repowering license). Other types of flexibilities, such as
demand response, were already explored in the simulation phase of WP3. Furthermore, the setpoints generated by the Sequential OPF tool are only provided to the operator in EDP control
centre in a consultative way. It is up to the operator to decide if this set-point can be followed /
implemented or not. Details about the risks associated to this control are explained in D4.2.
The following objectives are defined for the ICPF tool field tests:
 Estimate the range of technically feasible active (P) and reactive (Q) power flexibility at
the primary substation nodes;
 Provide the TSO with information about how much flexibility can the distribution
network “offer” for a time horizon of 48 hours ahead and its expected operating point.
This information is essential to define operating strategies of the distribution network
in order to minimize the financial penalties associated to the tan φ. Furthermore, it also
contributes to increase the information provided by the DSO to the TSO (this means a
new operating practice);
 Support reactive power control in order to increase the efficiency of the transmission
and distribution networks, e.g. improve voltage profiles.
The following objectives are defined for the Sequential OPF tool field tests:
 Provide suggestions of control actions to the operator (i.e., operate as a decision-support
tool);
 Evaluate the impact of different control actions in the distribution network and its
potential implementation in the future (i.e., after the project).
3.1.3.1.1. Synchronization with WP3 Simulations
Only the flexibility resources available in the networks selected for the field tests are
considered. They mainly consist of capacitor banks, OLTC, bilateral flexibility contracts of MV
loads and wind farms with non-firm connection contract. Other types of flexibilities, such as
demand response, were already explored in the simulation phase of WP3. In task 3.4, future
scenarios (based on the ones created in WP1) were elaborated with additional degrees of
flexibility and DRES integration. These field-tests enable an evaluation of the tool in an
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operational environment, while WP3 simulations provided a test under different regulatory
and technical contexts.
3.1.3.2. Description of the test site
In the Portuguese electrical system the nominal high voltage (HV) distribution level is 60kV
while nominal medium voltages (MV) are 30kV, 15kV and 10kV. Typically DSO responsibility
starts at HV feeders from the primary substation (EHV/HV) and both high and medium voltage
distribution networks are meshed networks. While HV network may be radially or closed loop
operated, MV network is exclusively radially explored. Both HV and MV represent 4% and 33%,
respectively, of the overall distribution network length. Like MV network, low voltage (LV)
network is purely a radial network and its overall extension comprises about 63% of the total
distribution network length.
Two geographical unconnected network areas were chosen as test sites, with different
characteristics as presented in Figure 5. The main motivation to select these two sites is related
with data availability for consumption and distributed generation forecast, in all network
nodes.
Figure 5 - Geographical representation of the Portuguese demo sites
The first chosen network is located in the northern area of Portugal, more precisely in the
vicinity of Porto. The other chosen network is located in the southern area of Portugal, in the
vicinity of Lisbon.
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The Northern EHV/HV transport substation has three power transformers with a total power
transformation capacity of 510 MVA, with 10 HV feeders. The MV network selected as demo
site for this project is supplied by two main HV/MV substations, which in turn are connected to
the Northern EHV/HV substation, as represented in Figure 6.
Figure 6 – HV network schematic representation (northern demo site)
With reference to the above scheme, the N1 HV/MV substation supplies about 17201
customers, distributed by 7 MV feeders with about 204 secondary substations. A total installed
power capacity of 40 MVA is available at N1 HV/MV substation, provided by two 20 MVA power
transformers, both supporting On Load Tap Changer (OLTC) capability with 21 available taps,
a voltage range of 52 to 72 kV and 1.0 kV per tap. Also two 6 MVAr capacitors banks are
available at the substation MV side, each divided into two 3 MVAr levels that can be operated
independently, used for reactive network compensation. Is important to mention that the two
power transformers, usually, are operated independently, each connected to its MV busbarparallel operation is possible by closing the inter-busbar switch. No other flexibility is currently
available in this network.
The typical N1 HV/MV substation load diagram is presented in Figure 7.
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14
12
10
8
6
4
2
0
Transformer 1 (MW)
Transformer 2 (MW)
Figure 7 - Typical load diagram of N1 HV/MV substation
The N2 HV/MV substation supplies about 21249 customers, connected to 10 MV feeders that
in turn are connected to about 206 secondary substations. The total installed power capacity is
63 MVA, with two OLTC capable power transformers of 31.5 MVA each, with OLTC capability of
23 available taps, a voltage range of 50 to 70 kV and 1.0 kV per tap. Two 6 MVAr capacitor banks
connected at the MV side are available, one with two 3 MVAr independently operated levels
and the other only with one 6 MVAr level available. A 3.6 MVA distribution generation capacity
is present at the MV network side, corresponding to a cogeneration station.
The typical N2 HV/MV substation load diagram is presented in Figure 8.
14
12
10
8
6
4
2
0
Transformer 1 (MW)
Transformer 2 (MW)
Figure 8 - Typical load diagram of N2 HV/MV substation
The Southern EHV/HV transport substation has four power transformers with a total power
transformation capacity of 680 MVA, with 16 HV feeders. The MV network selected as demo
site for this project is supplied by two main HV/MV substations, which in turn are connected to
the Southern EHV/HV substation, as represented in Figure 9.
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Figure 9 - HV network schematic representation (southern demo site)
The S1 HV/MV substation supplies about 10363 customers, distributed among 8 MV feeders
with 66 secondary substations. A total installed power capacity of 40 MVA is available at S1
HV/MV substation, provided by one power transformer, supporting an OLTC capability with 23
available taps, a voltage range of 50.1 to 69.9 kV and 0.9 kV per tap. Also a 6 MVAr capacitor
bank is available at the MV substation side, this bank is divided into two 3 MVAr levels that can
be operated independently, used for reactive network compensation.
The typical S1 HV/MV substation load diagram is presented in Figure 10.
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10
9
8
7
6
5
4
3
2
1
0
Transformer 1 (MW)
Figure 10 - Typical load diagram of S1 HV/MV substation
The S2 HV/MV substation supplies 16848 customers, on 17 MV feeders connected with 91
secondary substations. The total installed power capacity is 40 MVA, with two OLTC capable
power transformers of 20 MVA each, capability with 23 available taps, a voltage range of 50.1
to 69.9 kV and 0.9 kV per tap. No capacitor banks are connected at this site.
The typical S2 HV/MV substation load diagram is presented in Figure 11.
10
9
8
7
6
5
4
3
2
1
0
Transformer 1 (MW)
Transformer 2 (MW)
Figure 11 - Typical load diagram of S2 HV/MV substation
3.1.3.3. General outline of the test scripts
The ICPF and Sequential OPF tools will be tested online and integrated with different EDP
systems: PREDIS (forecasting system); DPLAN (network topology); SCADA-BI (equipment
states); PowerOn (switch states). The benefits of the tool in terms of information provided to
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the operator and operational KPI will be demonstrated here. It should be noted that only the
available real flexible resources are considered for the field test. Therefore, the emphasis will
be on the reactive power control at the TSO-DSO interface, which presently is a key issue for
both TSO and DSO in Portugal. It is worth mentioning that currently in Portugal there is no
flexibility contracted with consumers in LV distribution networks, only load curtailment
contracts are available for industrial customer’s, managed by the Portuguese TSO (as described
in Deliverable D1.2 [1]).
The online demonstration of both tools follows the same reference test script, in fact, both tools
will run in parallel inside the same process. The procedure main steps are given below:
 Receive information on distribution network equipment state (i.e., differences to the
typical network topology), typical network topology and flexibility range of available
resources, current operating state of OLTC. This information will be used to construct
an interval of flexibility in each node/equipment of the HV and MV networks.
 Get net-load forecasts for each MV/LV substation, HV loads, MV loads and nodes with
distributed generation (e.g., wind farms, CHP). Pre-process the network topology;
 Execute the ICPF and Sequential OPF for the selected HV and MV networks;
 Display, in the ICPF GUI, information about the range of flexibility at each EHV/HV
substation, as well the operating point. Generate a text file with a set of control set-points
for the available resources, generated by the Sequential OPF tool, which the operator
can decide to implement or not. These outputs will be used to evaluate the accuracy of
the power flow values in the TSO-DSO interface and also for a qualitative evaluation of
the information provided to the operator.
As mentioned above in Test Objectives, the set-points generated by the sequential OPF are
presented to the operator and not directly transmitted to the network equipment. The tests will
be used to shorten the learning curve of the operators and promote the implementation of
internal validation procedures of these set-points (e.g., validation via SCADA/DMS system).
Finally, no direct interaction between the two tools is foreseen since the idea is to test them
both separately in order to better understand their limitations and benefits. In the future, it
may be possible to use the output of the ICPF to better design reactive power control actions
and to use the sequential OPF to define the “optimal” control set-points for the distribution
network.
3.1.3.4. Preparations and conditions
The preparations for testing the tools in the Portuguese networks are the following:
 The algorithms were validated through computer simulation in Task 3.4 with data
provided by EDP. Issues such as network data format conversion were checked
beforehand;
 A network topology processer to be developed by INESC Porto is necessary to separate
cables (in general, connections inside substations) and overhead/underground lines
from the distribution network. The inclusion of substation cables can result in numerical
convergence problems in the power flow calculations. Moreover, the switches for
network reconfiguration should also be included in the network topology;
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




The two test networks were selected because both have all MV/LV substations with
Remote Terminal Units (RTU) or smart meters installed and capable of monitoring
active and reactive power consumption/injection with 15 minutes intervals. This data
is essential to generate net-load forecasts for each network node;
The access to other IT systems at EDP is necessary to get the following information:
typical or “normal” network topology; current state of capacitor banks and OLTC;
changes in the network topology. Pre-processing methods developed by EDP to gather
information from these different systems will be necessary, as well as a validation of the
file formats;
A short-term forecasting system for the net-load will be operational before the start of
the demonstration phase and it is capable of producing forecasts for each node, load and
generation unit of the test networks. The performance will also depend on the quality of
the measurement data and the time depth of the measurement data base. The reactive
power will be forecasted based on historical data collected to the MV/LV substations
and using expert knowledge from EDP;
The interface must be comprehensive enough to be used by DSO network operators in
the control centre. A preliminary assessment will be conducted to understand how the
operators want to have access to the information displayed by both tools;
The information about the future network topology is not available for the field tests
and represents a limitation that it is not possible to solve during the time duration of the
demonstration. In this case, the hours with a network topology different from what was
expected are removed from the ex-post analysis of the results.
Table 8 explains how the requirements identified in the System Use Cases of WP2 are fulfilled
in the Portuguese field-test regarding the ICPF tool. Table 9 presents the same information for
the Sequential OPF tool.
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Req. ID
(from D2.2)
Cnf 1
Cnf 2
QoS 1
QoS 2
QoS 3
QoS 4
Requirements
Requirement Description
(from D2.2)
Communication channels with the
resources (flexibility operators,
capacitor banks, transformers, etc.)
Existence of a data sharing platform
between TSO and DSO
Time horizon of the operational
period to be considered must be
stated
Sampling
interval
of
the
operational planning period must
be specified
Access to flexibility offers (or
market bids), bilateral flexibility
contracts, dynamic (or non-firm)
connection contracts
The data regarding the resources
owned by the DSO, such as on-line
tap-changing
transformer
or
capacity banks, as well as the
possibility of active network
reconfiguration
ISL 1
Authentication
database
ISL 2
Encrypted information
DM 1
DM 2
in
the
SCADA
Active and reactive power profiles
at primary substations sent by the
TSO
Access to updated forecasts of the
net-load in each substation
DM 3
Access to the current MV network
configuration
DM 4
Access to information that enables
to determine the observability of
the distribution network
Degree of Fulfilment in the Test-Trial
All the resources in the HV and MV networks are directly
connected to the DMS/SCADA system.
This platform exists and give to both entities’ control
centres real time information generically about: (a) Circuit
breakers state information from the TSO-DSO
interconnection panels; (b) Real time measurements of
currents, active and reactive power and voltage.
This platform will not be adapted for this use case/tool.
The EDP load/RES forecasting system (PREDIS) is capable
of generating forecasts for the next 48 hours and for each
HV/MV and MV/LV network nodes or substations.
The sampling interval is defined by the forecasting system
and corresponds to an hourly interval in this Portuguese
test-trial case.
Presently, there are no flexibility markets or tenders in
Portugal. The network selected for test-field has only one
wind farm with a non-firm connection contract.
The current status of the DSO resources (e.g., OLTC,
capacitor banks) is available in real-time via SCADA.
The ICPF will not have direct access to the SCADA
database. The access will be indirect through exported
files.
Encrypted information will not be used since the tool will
be installed in the dispatch centre.
The current regulation already imposes limits in the tan φ
at the TSO-DSO interface. This information is available.
The forecasting system updates the forecasts for each
network node two times per day.
The network topology is updated every month in order to
handle new lines and loads. Moreover, a file with the
differences to normal operation is created two times per
day.
The selected network for test-field is fully observable
considering the access to SCADA data and load/RES
forecasting for each node.
Table 8 – Fulfilment of the WP2 System Use Case requirements in the Portuguese test-field regarding the ICPF
tool
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Req. ID
(from D2.2)
Cnf 1
Cnf 2
QoS 1
QoS 2
QoS 3
QoS 4
Requirements
(from D2.2)
resources (flexibility operators,
between TSO and DSO
Time horizon of the operational
period to be considered must be
stated
Sampling
interval
of
the
operational planning period must
be specified
Access to flexibility offers (or
market bids), bilateral flexibility
contracts, dynamic (or non-firm)
connection contracts
The data regarding the resources
owned by the DSO, such as on-line
tap-changing
transformer
or
capacity banks, as well as the
possibility of active network
reconfiguration
ISL 1
Authentication
database
ISL 2
DM 1
DM 2
in
the
SCADA
Active and reactive power profiles
at primary substations sent by the
TSO
Access to updated forecasts of the
net-load in each substation
DM 3
Access to the current MV network
configuration
DM 4
Access to information that enables
to determine the observability of
the distribution network
All the resources in the HV and MV networks are directly
connected to the DMS/SCADA system.
This platform exists and give to both entities’ control
centres real time information generically about: (a) Circuit
breakers state information from the TSO-DSO
interconnection panels; (b) Real time measurements of
currents, active and reactive power and voltage.
This platform will not be adapted for this use case/tool.
The EDP load/RES forecasting system (PREDIS) is capable
of generating forecasts for the next 48 hours and for each
HV/MV and MV/LV network nodes or substations.
The sampling interval is defined by the forecasting system
and corresponds to an hourly interval in this Portuguese
test-trial case.
Presently, there are no flexibility markets or tenders in
Portugal. The network selected for test-field has only one
wind farm with a non-firm connection contract.
The current status of the DSO resources (e.g., OLTC,
capacitor banks) is available in real-time via SCADA.
The ICPF will not have direct access to the SCADA
database. The access will be indirect through exported
files.
Encrypted information will not be used since the tool will
be installed in the dispatch centre.
The current regulation already imposes limits in the tan φ
at the TSO-DSO interface. This information is available.
The forecasting system updates the forecasts for each
network node two times per day.
The network topology is updated every month in order to
handle new lines and loads. Moreover, a file with the
differences to normal operation is created two times per
day.
The selected network for test-field is fully observable
considering the access to SCADA data and load/RES
forecasting for each node.
Table 9 – Fulfilment of the WP2 System Use Case requirements in the Portuguese test-field regarding the
Sequential OPF tool
3.1.4. French field test / trials: ERDF
One tool belonging to the “TSO-DSO Coordination” thematic is considered by ERDF in its field
tests: the ICPF solution developed by INESC TEC (§3.1.2.1).
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The main objective of this field test is to demonstrate the benefits of the ICPF tool in regards to
the short-term optimization of network operation. For the scope of the tool, it means the
evaluation of the possible flexibility exchanges at the TSO-DSO interface by using the flexibility
levers available.
Several of the levers managed by the tool will be considered in the field tests in WP4: the DSO
assets such as the OLTC and the capacitor banks, and the loads, generators and storage
providing flexibility from different market / contract mechanisms.
Several objectives will be considered for the ICPF tool:
 Evaluate the active power and the reactive power flexibility available at the TSO-DSO
boundary based on short-term consumption and production forecasts;
 Provide its expected operating point without using this flexibility;
 Provide a cost map of this flexibility over a short-term period for different kinds of
configurations, i.e. various available flexibility assets and activation conditions.
All of these tests are performed while verifying that the operational (Imax of the lines, Smax of the
transformers) and contractual (voltage limits, flexibility usage conditions…) requirements are
fulfilled.
The information provided by the algorithm will support the DSO in defining short-term
operating strategies of the distribution network that will be used to optimize its costs.
It is to be noted that the experiments described here correspond to the field tests as currently
envisioned based on information and data presently available, but also the installation schedule
of some upcoming equipment. This description is thus submitted to several risks, such as the
availability of all the required input data during the field tests. More details about these risks
and associated mitigation plans are provided in D4.2.
3.1.4.1.1. Synchronization with WP3 Simulations
In WP3 simulations, future scenarios (based on the ones created in WP1) were outlined with
additional degrees of flexibility (e.g., demand response), DRES integration and load growth. For
the WP4 field tests, the actual DRES integration and flexibility levers of the selected networks
are considered. Demand response will also be considered in the simulation. Depending on the
flexibility lever, various activation conditions will be investigated, as well as band and costs.
In comparison to WP3 simulations, these field tests enable an evaluation of the tool in an
operational environment (real operating condition, real historical data and associated
forecasts…) and the online sensitivity analysis of the flexibility parameters.
3.1.4.2. Description of the test sites
3.1.4.2.1. General location
Two site locations are considered for the French trials in the frame of the evolvDSO project.
Both field test locations are illustrated in Figure 12.
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

An urban type network in Toulouse. It is part of the ADEME sponsored project SOGRID1
involving 11 partners (utilities, academics and industrials);
A rural type network in Vendeuvre-sur-Barse in the vicinity of Troyes. It is part of the
ADEME sponsored project VENTEEA 2 involving 10 partners (utilities, academics and
industrials).
The characteristics of these two geographically distinct network areas are presented below.
One of the main motivations for selecting these two sites is related with the availability of
consumption and distributed generation data: while every network node is not monitored,
measurement equipment is installed at several locations of the feeders considered in the tests.
Figure 12 – Location of the 2
MV field tests considered in
France
3.1.4.2.2. SOGRID network
The network considered in the SOGRID project involves two primary substations supplying
mainly urban locations. These substations consist of 32 MV feeders supplied by several 36 MVA
power transformers, but only 5 MV feeders fed by 5 HV/MV transformers are considered by the
SOGRID project.
The feeders considered comprise 16 km of overhead lines and 42 km of underground cables,
for a total of 58 km of 20 kV lines. To these feeders 128 MV/LV substations feeding about 11000
1
2
http://www.so-grid.com/
http://www.venteea.fr/en/
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customer premises for a total amount of about 12 MVA are connected, as well as 9 MV
customers for a total amount of about 2 MVA. No MV producers and storage units are present
on the 7 feeders. Neither are load flexibility players. Five capacitor banks (two 1.8 MVAr units
and three 4.8 MVAr units) are connected to the bus bars of each substation. Ten remotely
controllable load break switches are also present in the perimeter of the experiment.
The voltage, active power and reactive power are monitored at several MV/LV substations of
these feeders. The same quantities are also monitored at the primary substation level for the
MV feeders involved in the experiment.
Figure 13 provides an overview of the MV feeders considered by the SOGRID project, each being
represented with a different colour.
01-Reference
MV feeder-01-01-02
MV feeder-01-02-02
02-Reference
MV feeder-02-01-02
MV feeder-02-02-02
MV feeder-02-03-02
Figure 13 – Anonymized topological representation of the MV feeders considered in the SOGRID project
3.1.4.2.3. VENTEEA network
The network considered in the VENTEEA project involves one primary substation supplying
mainly rural locations. This substations consists of 6 MV feeders supplied by one 20 MVA power
transformer. All feeders are considered here.
The 6 feeders comprise 97 km of overhead lines and 43 km of underground cables, for a total
of 140 km of 20 kV lines. To these feeders are connected: 114 MV/LV substations feeding about
3200 customer premises for a total amount of about 6.5 MVA and 15 MV customers for a total
amount of about 3.5 MVA.
Two MV production units are also present, one being a 12 MW wind farm unit connected to a
dedicated feeder, the other one being a 6 MW wind farm unit connected at the end of one of the
feeders. A storage unit of 1 MWh at the hand of the producer owning both farms is also
considered. The geographical locations of both production units and the storage unit are very
close. This configuration is made to allow switching the battery connection either to the
dedicated feeder or to the mixed feeder. No load flexibility player is present on the network.
One capacitor bank (a 2.4 MVAr unit) is connected to the bus bar of the primary substation; 12
remotely controllable load break switches are present in the perimeter of the experiment.
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The voltage and/or active power and reactive power are monitored at about twenty MV/LV
substations. The voltage, as well as active and reactive powers, is also monitored at the primary
substation level for the MV feeders considered in the experiment.
Figure 14 provides an overview of the 6 MV feeders considered by the VENTEEA project, each
being represented with a different colour.
Figure 14 – Anonymized topological representation of the 6 MV feeders considered in the VENTEEA project
The ICPF tool will be tested in different configurations in order to technically validate the tool
on real network and field data (measurement, network configuration…) and demonstrate its
benefits in regards to the short-term optimization of network operation.
The situations considered are provided here:
 Actual DSO flexibility levers (voltage reference of transformer OLTC, capacitor banks…)
and flexibilities on distributed generation and storage units;
 Actual flexibility levers (DSO owned assets, as well as distributed generation and storage
units), but also foreseen flexibilities on consumption (industrial or residential).
Depending on the flexibility lever, various activation conditions will be investigated. Also, for
the tests considering consumption as flexibility lever, different flexibility bands and costs will
be considered depending on the time of the year.
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The situations described above can all be tested by following the same reference test procedure.
Its main steps are given below:
1. The network description is assembled. It includes the static electrotechnical and
topological description of the network assets, as well as its dynamic aspects: updated
switch positions are provided after every state change. The current state of some assets
such the capacitor banks or the reference voltages controlling the tap changers are also
being provided.
2. Load and generation forecasts are computed and attributed to each node. When the
power flow of a node is measured, forecasts can be associated directly to this
component. Otherwise, when no measurement is available for a node, its forecast is
computed by a weighting method using its relative power contribution, the forecast of
the considered feeder as well as the forecasts obtained for the measured assets
connected to this feeder.
3. The considered flexibility levers are defined and the available flexibility volumes are
fixed for each lever (consumption, production and storage units).
4. The ICPF tool is executed. The flexibility area in the TSO/DSO interface is computed and
the flexibility cost map is published. These outputs are displayed in the tool GUI and
provided to the operator for a qualitative evaluation of the information.
For the situation involving already available assets, the ICPF tool will be tested on-line
connected with different ERDF systems. This connection will only be indirect because of
potential cybersecurity issues; more details are provided in D4.2. The situation where foreseen
flexibilities are considered will be simulated outside from this integrated system.
The preparations for testing the ICPF tool in the French trials are the following:
 The algorithms have been validated in the lab tests on the data provided by ERDF to the
tool developers for WP3; issues such as network data conversion, management of
network nodes not monitored, usage of the voltage reference of the tap changer instead
of its position (since it cannot be known) have been checked beforehand;
 The measurement equipment have been installed at the different MV locations (MV/LV
substations, MV customers’ premises and MV feeders) considered in the trial;
 The communication should be tested so that potential communication issues
(communication loss, uncertainty of the measured values) with the measurement
equipment installed at the different MV locations (primary substations and MV/LV
substations) are limited;
 Historical consumption and production measurements are available for a sufficient time
interval. At least 2 weeks of consistent measurement data should be available before
providing short-term forecasts;
 The short-term forecasting algorithms of the active power of both consumption and
production are operational. This will also depend on the quality of the measurement
data and the time depth of the measurement database. The larger this time interval the
better the forecast accuracy. The power factors used for reactive power computation
will be set based on the expert knowledge from ERDF;
 The pre-processing methods developed by ERDF for gathering the network data from
the SCADA (network topology, measures…) and feeding them in appropriate formats to
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
the ICPF tool should be validated. Reliability and cybersecurity aspects should be
considered;
The interface and the associated documents must be comprehensive enough to be used
by DSO network operators in the control center.
in the French field test regarding the ICPF tool.
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Requirements
Req. ID
(from D2.2)
(from D2.2)
Cnf 1
resources
(flexibility
operators, All the MV resources are connected to the SCADA system.
A platform gives to both entities’ control centres information
mainly about the state information of the switches at the
Cnf 2
TSO-DSO interconnection and the measurements of the
between TSO and DSO
electrical quantities at the TSO-DSO interface.
This platform will not be used for this use case/tool.
ERDF forecasting system (SYPEL) is able to produce
consumption and production forecasts for time horizons up
Time horizon of the operational period
QoS 1
to 96 hours for different kinds of network locations when
to be considered must be stated
they are monitored: HV/MV substation, MV feeder, MV/LV
substation.
Sampling interval of the operational The sampling interval considered for the field test is the
QoS 2
planning period must be specified
same as the forecasts: half an hour.
Access to flexibility offers (or market In France, there is currently no flexibility market at a local
bids), bilateral flexibility contracts, level, or bilateral contracts between the DSO and a flexibility
QoS 3
dynamic or non-firm connection provider. Even if this possibility is currently not available, it
contracts
will be considered during field test simulations.
Data regarding the resources owned The status of the DSO owned resources (e.g., switched on
by the DSO, such as OLTC or capacitor capacitor banks, OLTC voltage reference, position of manual
QoS 4
banks, as well as the possibility of and controllable switches) is available in real-time in ERDF
active network reconfiguration
SCADA.
Direct access to ERDF SCADA will not be authorized for the
field tests because of cybersecurity aspects. The ICPF tool
ISL 1
Authentication in the SCADA database
will be provided files exported from the SCADA and
converted in a format comprehensible by the tool.
Encrypted information is not relevant for the tests because
ISL 2
of the tool location (within ERDF control center).
TSO/DSO power exchanges at their interface are
Active and reactive power profiles at contractually specified: the limits, imposed to both the active
DM 1
primary substations sent by the TSO
power (TURPE 4) and reactive power, are known. The
pricing structure and the associated costs are available.
Active power forecasts are computed every 6 hours for the
locations equipped with meters monitoring the power flows
Access to updated forecasts of the net- of the network. Power estimates are computed for the
DM 2
load in each substation
network nodes that are not monitored using a
weighting system.
More information is provided in D4.2.
Static network topology will be updated in case one or more
network asset is installed, renewed or removed.
Access to the current MV network Dynamic network data will be fetched from the SCADA and
DM 3
configuration
provided in a form comprehensible by the ICPF tool. This file
contains the changes between the current and the normal
operation states of the network.
The considered networks are monitored at the primary
Access to information that enables to
substation level as well as at several MV network locations:
DM 4
determine the observability of the
every MV DRES and storage units and a limited number of
distribution network
MV/LV substations.
Table 10 – Fulfilment of the WP2 System Use Case requirements in the French field test regarding the ICPF tool
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3.2.
Thematic: Operation
3.2.1. Introduction
The tools and the field tests associated to the “Operation” domain that were selected after the
application of the methodology described in Chapter 2 are presented here.
Three tools are considered: the Contingency Co-Simulation tool simulating realistic
contingencies and identifying suitable levers to provide corrective actions to solve them
efficiently, the LV State Estimator tool predicting the state of the network by making use of
historical data and a low number of real-time measurements from Smart-Meters and the
Replay tool focusing on the investigation of grid management to analyse past events and resimulate them. The principles behind these algorithms are briefly recalled.
The ERDF and the ENEL field tests are then presented in details. Each involves at least one of
these tools. The objectives, the description and the general outline of the trials as well as their
associated preparations and conditions are provided.
3.2.2.1. State Estimation for LV networks
The Distribution State Estimator-DSE algorithm proposed for LV networks and developed by
INESC TEC (formerly INESC Porto) is based on artificial intelligence concepts. It is capable of
dealing with the partial or complete absence of knowledge of the network parameters and
topology, as well as taking advantage from an advanced metering infrastructure.
The proposed DSE is a real-time function designed to provide a voltage solution in terms of
voltage magnitudes (state variable). In addition, active and/or reactive power injections at
customers’ premise may also be estimated.
The DSE algorithm is based on the use of artificial intelligence and relies on a specific type of
artificial neural networks – the Autoencoders (AE). Moreover, the present algorithm exploits
the concept of Extreme Learning Machine Autoencoder (ELM-AE), which applies ELM
techniques to properly train the AE. The trained AE can be seen as the “brain” of the DSE
algorithm and its solution can be used as an input for other power system related modules (e.g.
analysis modules, control modules, etc.).
The major benefits of the proposed DSE algorithm, when compared to the traditional state
estimation techniques (e.g., Weighted Least Squares algorithm), are that information about
some network parameters (branch technical characteristics namely) and topology are not
required to achieve a state estimation solution.
It is also important to state that when a real-time measurement becomes no longer available
following some event, the proposed DSE algorithm overcomes this limitation by turning this
measurement into variables that will be estimated, but to the detriment of results accuracy.
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More information about the LV DSE tool features can be found in Deliverable D3.2 [2].
Performing LV network state estimations requires two different stages:
 An off-line stage during which the data set is prepared and the DSE model is configured
and trained;
 A real-time state where the DSE model uses the real-time measurements to estimate the
unbalanced voltage levels of the LV network nodes.
Both stages presented below are illustrated in Figure 15.
Preparation and training stage
A preparation stage is required before running the DSE in real-time. This stage comprises two
main processes:
 Building a synchronised historical data set. This data set should contain synchronised
measurements of the voltage and power gathered by telemetry equipment, such as
Smart Meters (SM) located at customers’ place or measurement devices installed at the
MV/LV substation bus bar level. Several weeks of synchronous data are at least required
but they do not need to be continuous, meaning that several separate time intervals can
be considered.
 Training the Autoencoder (ELM-AE). This step is highly relevant since it greatly impacts
the accuracy of the state estimation. The historical data set should first be standardised
and then the training algorithm, the activation function and the hidden nodes number
of the AE should be selected. These operations having been carried out, the training
process of the algorithm can be performed.
Real time operation
Once previous preparation processes have been completed, the resulting DSE model can be
used for real-time application. The measurements available in real-time are used as inputs to
the AE in order to guide the optimisation algorithm to achieving the system state estimation.
The meta-heuristic selected to reconstruct the missing signals is an Evolutionary Particle
Swarm Optimisation (EPSO) which has been successfully applied in several problems in the
power systems area.
The number and the type of variables to be estimated will depend on their availability in the
historical data set as well as on the amount and type of measurements being telemetered in
real-time. It should be noted that the proposed DSE algorithm is able to deal with either singlephase or three-phase data (gathered per phase) depending on the variables existing in the
historical data set used in the training procedure.
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Telemetry equipment
historical data
DSE Training
β1
ELM-AE
1
1
h1
(w1,b1)
1
X
T
L
(wL,bL)
hL
m
m
βm
t1
x1
Running DSE
Real-time
measurements
Missing data
ELM-AE
properly trained
Missing data
EPSO reconstructed
tm
xm
EPSO fitness function
(Outp Inp)
No
2
EPSO
convergence
achieved?
Yes
Final estimated
values
Figure 15 – Scheme of the proposed DSE algorithm
Regarding the network description, no electrotechnical parameter of the network components
is required, the phase connection of the LV customers (AN, BN, CN and ABCN) and the feeder to
which they belong are the only parameters that should be provided to the tool.
Regarding the input measurements, the DSE tool should be fed by synchronised measurements
of the voltage, active power and reactive power gathered by telemetry equipment such as Smart
Meters (SM) located at customers’ place, and by measurement devices installed at the MV/LV
substation level, preferably on each LV feeder. Additionally, the measurements should be in
sufficient number for each time instant, otherwise the AE will not learn effectively the
patterns/correlations between the electrical variables of a given network, or provide an
accurate state estimation.
An effective state estimation through the use of AE requires a large historical database. This
database needs to contain data about the variables that will be passed to the AE during its
training stage (both for the missing signals and for the measurements that will be available in
real-time). There is no rule of thumb regarding the quantity of data that the historical data set
should contain. However, it is experimentally known that too few or too much data will lead to
an inaccurate AE. A trial and error approach can be followed to identify the optimal quantity of
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data in the historical database to be passed to the AE whenever a large amount of historical is
available. Of course, if the data records are scarce (for example, less than a week), all data
should be considered.
3.2.2.2. Contingency Co-Simulation
The Contingency Co-Simulation (CCS) tool developed by RSE is applied in the context of
Operational Planning. The time horizon it analyses spans from short-term to day-ahead, i.e.
from 72 to 24 hours before the considered period. It aims at fulfilling the System Use Case
“Simulate contingency analysis in Operational Planning (asset unavailability analysis)”.
The CCS tool simulates realistic contingencies in order to identify the suitable flexibility levers
of the network and, as a consequence, the corrective actions and policies required to solve them
in the most efficient and effective way. ICT performance analysis is also performed through an
innovative co-simulation module.
Several kinds of flexibility levers can be considered by the CCS tool in order to optimize the
network operation when confronted to contingencies:
 DSO assets:
o Controllable load break switches for network reconfiguration;
o On-load tap-changers (OLTC);
o Reactive power compensation (e.g., capacitor banks);
 Loads, generators and storage units providing active and/or reactive power flexibility.
More information about the CCS tool features can be found in Deliverable D3.3 [3].
The tool comprises of two algorithmic parts both controlled by a GUI:
 A “contingency selection” module that identifies failure states of network assets
through a statistical reliability analysis. Its GUI displays the identified contingencies and
also allows operators to add manually other relevant contingencies;
 A “Load-Flow/Co-simulation” module that analyses the grid operation based on the
grid data and defined contingencies: all the constraint violations are detected and
adequate levers are selected to relieve them. The selection of the levers is performed
by centralized Distribution/Energy Management System (DMS/EMS) that tries to
minimize DSO operating costs while solving at the same time the anticipated technical
and economic constraints. The ICT criticalities and constraints are also identified, but
this analysis is optional.
It is to be noted that the structure of the CCS tool is modular. This will allow in the future to
integrate new functionalities and update existing algorithms/modules quite easily.
3.2.2.2.2.1. Contingency Selection module
The algorithm used by the Contingency Selection module uses an approach based on Pseudosequential Monte Carlo Simulations (MCS). This hybrid approach employs a non-sequential
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technique to investigate the system state and uses a sequential simulation method when a
failure state is detected in order to explore its neighbourhood and identify the total extent of
the failure. This allows to identify both the start time and the duration of each failure state.
The Contingency Selection module exploits different kinds of information: network physical
data (network topology, conductors data, lines length, loads and generators types, substations
elements and devices, etc..), reliability data (failure rates of lines, transformers, generators,
power stations, communications systems, ...), temporal trends of electricity demand for
different types of users, temporal trends of DRES generation (wind and solar radiation).
The network assets are modelled using two distinct types of models:
 Stochastic models, such as Markov models, are used for the power lines, the primary
substations, the active control systems, and also for the dispatchable generators (biogas,
biodiesel…);
 The chronological models are used to describe the loads and DRES, whose production is
normally not predictable and therefore not dispatchable.
Network elements such as switches, disconnectors and MV/LV transformers found in
secondary substations are considered ideal, .i.e. not damageable.
Using this information, the reliability analysis goes through the steps presented in Figure 16.
Figure 16 – Pseudo-sequential MCS applied to active distribution grid reliability analysis flow chart
3.2.2.2.2.2. Co-simulation module
In this module, MATLAB software acts as the integrator of the co-simulation environment: it
manages and coordinates the power system simulation software (OpenDSS) and the
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communication system simulation software (NS-2). The architecture of the co-simulation
module is presented in Figure 17.
During the co-simulation process, the DMS/EMS cyclically verifies the network state by
performing load flow calculations with OpenDSS. The current grid configuration, as well as
short-term load, generation and weather forecasts are considered in addition to the
contingencies provided by the tool and/or defined by the operator. When technical constraints
are violated, measurement systems detect a critical state and send a signal to the DMS through
the ICT system. The DMS identifies the corrective actions by optimizing the operation costs:
network losses, active and/or reactive power flexibility purchase of customers, DRES or storage
systems are considered. Then it generates the set-points to be sent to generators and loads in
order to modulate the power injection or to command the curtailment.
NS-2 operates in parallel and simulates the transmission of signals, such as new set point
signals (ΔP, ΔQ). Depending on the selected ICT technology, the signals attenuation is calculated
considering appropriate binary parameters (, ) and communication delays ΔtDMS and ΔtICT,
which are respectively related to the DMS system computer processing and to the transmission
through the communication medium.
The synchronisation of the electrical and ICT simulations is ensured by the Matlab master.
Distribution System
Load Flow calculation
(
MATLAB
WINDOWS
X(t0)
ΔP(t0)
ΔQ(t0)
OpenDSS)
COM
αΔP(t0 + ΔtDMS + ΔtICT)
βΔQ(t0 + ΔtDMS + ΔtICT)
Control System
DMS/EMS
LAN
SSH/SCP
CO-SIMULATION
MANAGEMENT
(geographic coordinates)
Distribution
Network data
ΔtDMS
α, β, ΔtICT
ICT System
TLC Network data
LINUX
Technologies and Protocols
(ns-2)
Figure 17 – Co-simulation module architecture.
Several input data types are required by the CCS tool:
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



Static grid topology data (conductors data, lines length, loads and generators types,
substations elements and devices);
Technical data of grid assets (ICT, equipment, loads and generators technical and
reliability data etc.);
Installed capacity in the grid;
Technical Constraints.
In particular, for the Contingency Selection module:
 DRES and Load Time Series providing yearly tendencies; load and generation profiles
for all the loads and generators included in the grid under study are required for a
specific time interval, generally at least one year;
 Historic operational data (list of faults, outages and contingencies occurred in the past
as well as specific contingencies introduced by the operator).
And for the Co-Simulation module should also be considered:
 Current network state;
 Short-term forecasts for load, generation and weather;
 ICT equipment location and characteristics.
3.2.2.3. Replay
3.2.2.3.1. Algorithm Objectives
Replay is a field-oriented application which focuses on the investigation of grid management;
its main purpose is to perform a pro-active analysis of grid control actions by the means of an
off-line fully operational SCADA platform. Its main goal is to analyse past events and actual real
data and re-simulate them for improving grid management policies, as well as new
software/hardware technical solutions testing and operators training.
The Replay tool performs two types of analysis reproducing the network and its dynamics with
a high fidelity and using a real time approach:
 Ex-Post analysis:
o Revision of the events occurred in the past timeframe;
o Analysis of the effects in terms of quality of service.
The purpose of this functionality is the analysis of the occurred events, alarms, faults and
other criticalities, i.e. the analysis of the signals collected from the field and recorded in
the SCADA database.

Predictive analysis:
o Possibility to modify occurred events by analysing the complete list of events;
o Calculation of the network operation set points;
o Analysis of the effects in terms of quality of service.
This analysis allows a wide group of operators, including those that do not usually work
in the DSO control room, to operate the electricity network by the use of a SCADA
simulation tool and to support them in the choices in the short-term planning domain.
Different scenarios could be built to simulate, for instance, the effects of criticalities on
the networks, maintenance activities, or the consequences of the flexibility activation.
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The definition of a brand-new algorithm is out of the scope of the tool. Rather, Replay allows
the optimized integration of several tools already available in DSO systems.
The fundamental concept behind the Replay tool is the possibility to have a simulation platform
and not a simple tool able to be a network simulator. The Replay system is an integration
platform able to connect the most important tools currently used in the real control center
enabling a new approach of analysis methodology. The possibility to use simulations on the
network supported by all the monitoring and graphical tools currently used by Enel
Distribuzione can give an important added value to the validation of the tool.
It is worth to mention that a load flow calculation of the tool is based on the one already
developed in the ongoing FP7 European project GRID4EU3.
Figure 18 shows the data flow needed to use the Replay tool.
Figure 18 – Data flow needed for Replay tool
Four main inputs are relevant for the Replay tool:
 Network scheme from the SCADA;
 Network events;
 Forecasted consumption and production data;
 Data on Quality of Service.
Regarding the network scheme from the SCADA a real-time asset of the network as well as the
normal state is available, while all the occurred events signals from the fault detectors and
3
www.grid4eu.eu
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protections are recorded from the real-time SCADA. To allow the modification of the network
configuration and to elaborate load flow calculation, customers/producers measurements and
load/generation forecasts data are collected from a specific Enel Distribuzione tool, namely the
“MAGO” tool.
An ad-hoc Enel interface (RETIM) is used for analysis of Quality of Service in the real SCADA
system as well as in the Replay simulations. Therefore, the quality of service of a real network
can be compared with the quality of service assessed in simulations mode.
In a future perspective, the Replay tool could be also used to evaluate the impact of flexibility
in the short term (e.g. bilateral contracts with producers). In this case, an additional
information flow stored in a specific database is expected.
3.2.3. French field tests / trials: ERDF
Two tools are considered in the “Operation” thematic for the French trials:
 The Co-Simulation tool developed by RSE dealing with MV networks;
 The State Estimation tool developed by INESC dealing with LV networks.
Even if these tools belong to the same thematic, the associated expectations and test conditions
are very different. Thus each time they will be dealt with separately.
It is to be noted that the experiments described here correspond to the field tests as currently
envisioned, based on the data currently available but also the installation schedule of some
upcoming equipment. This description is thus subjected to several risks, such as the availability
of all the required input data during the field tests. More details about these risks and associated
mitigation plans are provided in D4.2.
3.2.3.1.1. Contingency Co-Simulation
When studying electric networks, most of the time reliability studies are limited to one single
domain: the electrical network assets. But, with the development of Smart Grid, an additional
layer should also be considered: the communication system used to monitor the network and
send control orders to specific assets.
Both systems should be considered at the same time in order to assess the reliability and
operation performance of the power system as a whole. In fact, an electric system failure might
impact the communication system, but conversely a failure of the ICT might also impact the grid
operation. Both systems are thus deeply intertwined.
The Contingency Co-Simulation tool (§3.2.2.2) considered in the French trials for the
“Operation” thematic proposes a methodology to manage the reliability of both systems and
adapt the network operation in consequence.
The objectives of this trial are to demonstrate the technical approach of the Co-Simulation tool
for real network and field data. The failure states of network assets as well as network
contingencies are to be identified through a statistical reliability analysis, and associated
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optimized corrective actions should be provided thanks to the DMS/EMS integrated within the
tool. Improvements of different indicators are expected: reduction of the SAIDI index, the asset
unavailability and the energy curtailed. The operation costs should also be improved. The
impact of the tool on the operation costs and the quality of service will also be assessed.
3.2.3.1.1.1. Synchronization with WP3 Simulations
For the simulations of the French MV networks, various scenarios were created based on the
ones created in WP1. Current DSO owned flexibility assets as well as various degrees of
flexibility on demand response, DRES integration and load growth were considered to illustrate
future situations.
For the WP4 test-fields, the actual DRES integration and flexibility levers of the selected
networks are considered, as well as foreseen demand response. Depending on the flexibility
lever, various activation conditions will be investigated, as well as band and costs.
Compared to WP3 simulations, these field tests enable an evaluation of the tool in a real
operational environment (real operating condition, real historical data and associated
forecasts, real operation historical data…).
3.2.3.1.2. LV State Estimation
LV networks are nowadays still scarcely monitored. But with the upcoming generalized
installation of Smart Meters, more information will be available to observe and operate these
networks. Better constraints detection (e.g. voltage limits violation) and thus better quality of
service are expected thanks to algorithms such as State Estimation.
The LV State Estimation tool (§3.2.2.1) considered in ERDF trials addresses this problem by
proposing an original solution that does not require the complete electrotechnical data of the
grid assets. In regard to this algorithm, we focus on several questions, among which:
 What voltage estimation performance could be expected in an unbalanced context from
a State Estimator having a limited knowledge of the electrotechnical parameters of the
LV network?
 Can reliable detection of voltage constraints be expected regarding this performance in
an operational context?
 Collecting measurement is complex and costly, all the more when real-time
measurements are required. The Smart Meters used to constitute the database and
those providing real-time measurement should thus be considered separately. How
many and where should SMs of both sets be positioned to achieve a reliable state
estimation?
 What time horizon is required for the training database to be efficient and achieve the
required performance?
3.2.3.1.2.1. Synchronization with WP3 Simulations
For the WP3 simulations in the LV French network, a set of synthetic active power and voltage
measurements were generated from historical data with a 30-minutes time step collected from
LV customer’s Smart Meters. This was due to the fact that the original historical data had a
substantial number of missing values. In these simulations, other variables, such as active and
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reactive power flow, were also estimated. Moreover, this approach allowed a combination of
the LV state estimator and voltage control tools for different test scenarios.
The field test considered in WP4 will use real measurements of active power and voltage
collected from a test-pilot with Smart Meters measuring the voltage and the active power, but
also the reactive power of the customers, with a configurable time step (from 10 min to one
hour). This will enable an evaluation of the tool in an operational scenario and study its capacity
to assess voltage limits violation under different network configurations and various
communication constraints.
3.2.3.2. Description of the test site
The site considered for the French trials of the Contingency Co-Simulation tool is one of the two
sites already considered for the ICPF tool, namely the MV network studied in VENTEEA project.
More information can be found in paragraph 3.1.4.2.3. The SOGRID network was not selected
since it could not fulfil a condition required for the algorithm given the limited timeframe of the
tests, i.e. the availability of at least one year of load curve data.
The only difference between both tests is linked to the nature of the tool. Since the tool is not
expected to be used for real-time operation but rather for short-term planning, it will be
operated off-line. It will not get data in real-time from the information system of the network
operator, but data will be manually updated on a regular basis.
The site considered for the French trials of the LV DSE tool is a part of the one considered in the
ADEME sponsored project SOGRID (§3.1.4.2.1). Its location (Toulouse) is thus identical to the
one used for the MV tools discussed before.
The LV network considered in the SOGRID project consists of 11 MV/LV substations and 13 bus
bars (some substations have more than one bus bar). This represents about 1250 LV customers,
most being residential with a reduced number being of the commercial type. These are split
between about 50 feeders and 15 km of LV lines with a mix of both overhead lines and
underground cables. No photovoltaic generation unit or storage unit are present on this
network.
The voltage of the bus bar as well as the powers transiting through each feeder should be
measured at the MV/LV substation level for several of these substations. About 1000 of the LV
customers should be equipped with Smart Meters sending regularly information about their
voltage as well as active and reactive powers. Their exact phase connection should also be
known. This information as well as measurement data will not be available for the remaining
customers, i.e. those not equipped with a Smart Meter.
A subset of these MV/LV substations will be selected for the evolvDSO trials in order to apply
the LV State Estimation tool in an off-line manner: due to time constraints and implementation
complexities, the algorithm will not be integrated into local computation units that would be
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part of a decentralized architecture. The data will be regularly collected and treated a posteriori
with the DSE algorithm located in a centralized system emulating real-time operation
conditions.
AN
BN
CN
ABC
ABCN
Unknown
Figure 19 – Example of topological
representation of a French LV network. The
phase connection of each component (source,
transformer, lines, and loads) is displayed
The Contingency Co-Simulation tool will be applied in different situations illustrating different
topology configurations of the network with different reliability data for its assets. Several
situations regarding the flexibility levers (flexibility available, way the flexibility can be used…)
will be considered in WP4. These situations can all be tested by following the same reference
test script. Its main steps are given below:
1. Provision of the network electrotechnical parameters, grid topology and asset reliability
information.
2. Constitution of the historical database containing the power measurements for the
monitored MV/LV substations, MV customers and MV production units. For the not
monitored network nodes, a load curve is constructed based on the measurements of
their feeder and their weight considering all the nodes of the feeder.
3. Constitution of the database containing the operational data (list of faults, outages and
contingencies occurred in the past).
4. Provision of the geographical location of the communication assets of the network.
5. Execution of the Contingency Selection module of the tool.
6. Compilation of a list of contingencies to be considered for simulation with Co-simulation
module; contingencies come from the results of the Contingency Selection, operational
data database or directly from the operator (manually inserted through the control GUI).
Network contingencies (if any) due to the current operation state of the network (e.g. in
case of maintenance) are considered in the network current state update
7. Update of the network current state.
8. Selection of the levers (topology reconfiguration, production curtailment, consumption
flexibility…) that can be considered to help resolve contractual or operational
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constraints and under what conditions and at what costs they can be used (contract,
market…).
9. Computation of the short-term consumption and generation forecasts and attribution to
each node of the network.
10. Execution of the Co-Simulation module of the tool and publication of the found
contingencies and the list of levers used to relieve them.
The steps 1 to 5 are dedicated to the Contingency Selection module of the tool. Since the results
it provides are linked to annual consumption and generation tendencies it is not to be run every
time. The following steps (6 to 10) are dedicated to the Co-Simulation module and can directly
use these results if the configuration of the network stays the same. These last steps are
however required to be run on a regular basis because of the short-term nature of the results
provided.
It is to be noticed that the communication media used for the MV distribution network is mainly
wireless but also wired depending of the asset location. Two protocols are used depending of
the criticality of the transmitted signals: the HNZ protocol and the IEC 104 standard protocol
(60870-5-104). More information is provided in D4.2. The Contingency Co-Simulation tool does
manage neither these media nor these protocols. So, during ERDF trials, the communication
system will be emulated by a WiMax network within the NS2 simulation software. Even if the
technology and protocols are not the same, it should give a realistic behaviour from the system
reliability point of view when wireless communications –with given availability and latency are considered (radio or GPRS/UMTS).
Regarding the test objectives, the state estimation algorithm will be applied in different
situations illustrating different levels of network instrumentation and communication
conditions. In particular, several variations will be considered in the data set:
 Different values will be considered for the ratios between metered customers
(customers whose voltage and power quantities load curves are measured and stored)
and connected customers;
 Different values will also be considered for the percentage of meters used for real-time
measurement;
 Estimation will be performed with and without considering voltage and power
measurements for each feeder at the substation level. If no measurement is available for
the feeders, only the bus bar voltage will be considered.
These different situations can all be tested by following a same reference test script. Its main
steps are given below:
1. Constitution of the historical database containing the voltage and power measurements
for the considered LV network.
2. Provision of the required network information (known phase connections, feeder
associated).
3. Selection of the set of meters to be considered in the training stage.
4. Training of the ELM-AE state estimation model.
5. Selection of the meters to be used as real-time measurement providers.
6. Computation of the state estimation and publication of the voltage profile information.
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These steps should be performed for each MV/LV substation considered in the trials.
It is to be noted that the steps 1 to 4 correspond to the training stage of the DSE model. They
are thus not required to be run on a regular basis. The following steps concern directly the LV
state estimation of the network. They will thus be run for every time instant considered during
the field experiment in a way that simulates real-time operation.
The preparations for testing the Co-Simulation tool in the French trials are the following:
tool developers for WP3;
 The measurement equipment has been installed at the locations considered in the trial;
 Historical consumption and production measurement representative of every element
of the network should be available for a sufficient time interval. At least one year of
consistent measurement data should be available. This database is constituted prior to
the start of the evolvDSO field tests;
 Historic operational data (list of faults, outages and contingencies occurred in the past)
should be gathered for the same period;
 Reliability data of the grid assets should be provided;
 The short-term forecasting algorithms of both consumption and production are
operational. This will also depend on the quality of the measurement data and the time
depth of the measurement data base. The larger this time interval the better the
accuracy;
 The pre-processing methods developed by ERDF for gathering the network data from
the SCADA (network topology, measures…) and feeding them in appropriate formats to
the CCS tool should be validated. Reliability and cybersecurity aspects should be
considered.
The preparations for testing the State Estimation tool in the French trials are the following:
tool developers for WP3; issues such as the management of unbalanced customers or of
the loss of metering devices should be checked beforehand;
 The measurement equipment have been installed at the different LV locations (MV/LV
substations and LV customers’ premises) considered in the trial;
 The communication should be tested so that potential communication issues
(communication loss, uncertainty of the measured values) with the measurement
equipment that will be or have already been installed are limited;
 Historical load profiles are available for a sufficient time interval. A minimum set of
historical data (at least 2 months) where all measurements are available is required. For
instance, there cannot be a missing value for one smart meter, at least in terms of voltage
value, during this period. The training period is however not required to be continuous,
there can be interruptions within.
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For both tools, the interface and associated documents must be comprehensive enough to be
used by DSO network operators.
in the French field test regarding the Contingency Co-Simulation tool, while Table 12 does the
same for the LV State Estimation.
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Req. ID
(from D2.2)
T-1
T-2
Cnf-3
DM-1
to
DM-5
DM-6
DM-7
DM-10
ICT-1
Requirements
(from D2.2)
The Co-Simulation tool is expected to run in a short-term
time horizon, i.e. up to 72 hours ahead.
Application period
The application period can be selected by the user in the
GUI control panel.
The timeframe for the collection of historic data depends
Specify the time frame for the collection on the data availability; inside the time interval of the
of the historic data
available data, the user can choose the desired time frame
and related data.
The output of the contingency selection module (list of
A list of faults occurred in the selected
contingencies) is reported in the GUI control panel and it
timeframe has to be shown
is editable. Constraints that happened during the real
network operation will be considered.
Network data model (equipment &
All the static data regarding the network topology and
topology), bus specification (voltage
equipment/asset characteristics will be fetched from the
limits…), branch details (impedances,
MERCATOR system and converted into a format
Imax…), devices, load, generation and
comprehensible by both modules of the Contingency Costorage data (rated power & voltage…) Simulation algorithm.
Net load and generation forecasts will be provided for the
Load and generation forecasts:
MV feeders and the MV/LV substations monitored.
- Name;
For the remaining substations, a power profile will be
- Location;
attributed using a weighting process considering the
- Type;
associated feeder forecast, the forecasts of its monitored
- Active power profile;
substations and power index of each substation.
- Reactive power profile;
Reactive power will be computed based on power factors
defined on the expert knowledge from ERDF.
Reliability data of all the grid
equipment and devices:
Reliability data will be provided based on ERDF generic
- MTTF; MTTR; Failure rate;
reliability information.
Common format (e.g. .txt, .csv).
Details for the considered violated
constraints:
- Type of constraint;
- Element affected by the constraint
(e.g. overloaded line or transformer,
busbar overvoltage, etc.);
All the details of both the contingencies considered and the
- Depth (comparison to nominal
constraints violations detected are available through the
values, risk of occurrence);
GUI control panel of the tool.
- Emergency (priority classification);
- Start point;
- Duration;
- Frequency of occurrence;
- Common format (e.g. .txt, .csv).
Operator panel on PC desktop for data
The tool is managed through a GUI architecture which can
merging, compilation of contingencies
be run directly by the user on a standard PC.
list, tool operation control, etc.
Table 11 – Fulfilment of the WP2 System Use Case requirements in the French field test regarding the
Contingency Co-Simulation tool
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Req. ID
(from D2.2)
R-4
T-1
Cnf-1
QoS-1
QoS-2
DM-0
DM-11
Requirements
(from D2.2)
The SMs will communicate with the DC using DMS-COSEM
Standard communication protocol for protocol over a G3 PLC communication media.
the communication between the
Communication with the system handling the historical data
involved parties
located at the control center will use IEC -60870-5-104
standard protocol.
The LV state estimation tool can be applied to the current
Define the application period
snapshot of the network, as well to past snapshots stored
within the database.
The system has to save all the solution The result of each state estimation is going to be stored
in a related database
within a dedicated local result database.
The system has to provide the results
in 30 seconds
The state estimation runs in less than 5 seconds. The model
The network configuration and learning is more time consuming but it is performed off-line,
measurements at the defined time has so without time constraint.
to be shown in 30 seconds.
The network data model for:
- Equipment;
Only the meter naming, association to a network node and
- Topology;
connection phase (AN, BN, CN or ABCN) have to be provided
- State and measurements;
to the LV State Estimation algorithm.
could be complied with IEC 60968 CIM
standard.
Constraints information:
The state estimation tool provides:
 Location;
 the voltage between all phases and the neutral wire in
 Involved network element(s)
each network bus;
 Type;
 the power injections per phase in each network bus;
 Status;
 an error code if no success on estimation.
Common format (e.g. .txt, .csv).
Table 12 – Fulfilment of the WP2 System Use Case requirements in the French field test regarding the LV DSE tool
3.2.4. Italian field tests / trials: ENEL
Here below is the list of the main features of the WP4 tests for the Replay tool:
Replay – Features of the WP4 tests
Database tested
Type of generated events
Location of the tool installation
Available levers for the simulations
Complete network Scheme of Cagliari (Sardegna, Italy)
Simulated events
Enel Centro Prove Milano
Modification of the network configuration
Active Power Modulation and investigation of flexibility contracts
(Power flow integrated in the tool)
With respect to the simulations performed in WP3, the Replay tool will be tested in WP4 by
using a complete portion of the real network of Cagliari (Region of Sardegna, Italy).
In order to solve the criticalities occurred in the network, operators will be able to use an
additional lever, i.e. the active power modulation of the users connected to the grid.
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By involving real operators on the activities, Enel will be able to calculate the following KPIs
(please see the Deliverable D5.1 for more details).

Reduction of criticalities:
Within the context of the ex-post as well as the predictive analysis, a set of 3 different
MV feeders could be considered with the related potential criticalities.
Different network solutions could be considered using new network configurations and
flexibility. For each network line, the identified criticalities could be related to:
o Over current;
o Voltage violations (out of range);
o Potential over current related to planned work needs.
The set of best solutions could be evaluated on the basis of the calculated KPIs.

Reduction of service interruption duration:
The aim is to decrease the potential duration of the interruptions for fault management
by the use of the Replay tool. The use of specific optimization actions could improve the
quality of service by a specific ex-post analysis.
Also in this case, a set of 3 MV feeders is selected on the basis of the experiences of the
operators who will try to perform a set of actions to improve the quality of service for
occurred events. The events will be randomly generated by an event simulator on the
real network database and at the same time other critical conditions could be introduced
to train operators. By an evaluation of the SAIDI reduction by using the RETIM module
it will be possible to consider if the levers acted for the specific situations have been
effective or not.

Time Activity Saving (not addressed in the WP3 simulations):
The Time Activity Saving KPI is related to the effective support that the Replay tool could
give to the control room operator in terms of time saving.
To evaluate the time saving, first of all a sheet with a list of the main daily activities for
the control room operator will be produced. A comparison between the execution of
daily activities with or without the Replay tool will be given in order to evaluate its
benefits.
Regarding these aspects, a critical point could be represented by the low performance
of the HW in the prototype as well as the potential room for improvement in the Replay
interface. Indeed, in the Replay development (prototype) the need of testing the single
functionalities resulted in a non-optimized integration of the different modules.
As for any tool to be integrated for a the first time in the utility systems, the introduction
of Replay, at least in the first phase, could lead to a not optimized reduction of the Time
Activity Saving KPI.

Training Cost Saving (not addressed in WP3 simulations):
To date, Enel newly recruited operators join a training period in which they are
supported by skilled operators in the analysis of the critical events occurred on the
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network. This activity requires a certain time since it leverages on real events which
occurred during the training period with an unpredictable frequency.
The provision of the Replay platform allows the operators to train themselves on a set
of simulated events that can be randomly generated. Therefore, thanks to the provision
of the Replay training platform, this time is expected to lower.
The aim is to evaluate the training cost saved by the use of Replay in order to train a
SCADA operator to become independent in its daily activities. The real person-month
expenditure is considered confidential. Nevertheless a cost estimation will be provided
based on the average cost of Enel network operators.
In the following table a schematic summary of the cases realized in the D3.4 is represented. The
table shows a macro description of the specific test cases that include a group of defined check
on all the single functionalities in order to validate the correct behaviour of the tool.
WP 3
D3.4
D3.4
D3.4
D3.4
Test Case
Description
Network Portion
Functionalities Tested
Real Operation
System
MV Line with active and
passive customers (NTW
dB of Cagliari);
selection of a defined time
interval in the past
considering
a
long
interruption (t>3min);
 visualization of the list of events created by the
simulator
 visualization of the NTW scheme on the basis
of the list of events
 visualization on the RETIM tool of the data
related to the highlighted interruption (SAIDI).
Replay System
Simulation
dB of Cagliari);
considering
a
long
 visualization of the list of events in the Replay
System
 visualization of the NTW scheme in the Replay
System
 visualization on the RETIM tool of the data
related to the highlighted interruption (SAIDI).
Replay System
Ex post analysis
dB of Cagliari);
considering
a
long
 possibility to modify directly from the list, the
events imported in Replay.
 network configuration: possibility to open and
close MV breakers on the network changing
Replay System
Predictive
analysis
dB of Cagliari);
considering
a
long
 network configuration: possibility to open and
close MV breakers on the network changing.
 network power modulation: possibility to
change the injection power customer and
producer
Table 13 – summary of test cases in WP3 (Replay tool)
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In the following table a schematic representation of the tests within the WP4 is represented.
The approach to develop the deliverable D4.3, related to the data collection, is described with
an overview of tests to be realized. Basically the same functionalities introduced within the
WP3 are used in WP4, but with a different aim since WP4 applies the new methodology to a
large scale network analysis. In this context, real lines are considered with their characteristics
and potential criticalities. The possibility to solve network criticalities by new network
configurations and by using flexibility (active power modulation based on specific agreement
with the customers and producers) is foreseen.
Particular attention is given to the KPIs calculation on the basis of real cases occurred on the
selected MV lines with the possibility to evaluate the effective benefits introduced by the Replay
tool on a large scale.
WP 4
D4.3
D4.3
Test Case
Description
Real Operation
System
Replay System
Simulation
D4.3
Replay System
Ex post analysis
D4.3
Replay System
Predictive
analysis
Network
Portion
Functionalities
Tested
Entire MV
network
 visualization of the list of events created by the simulator
 visualization of the NTW scheme on the basis of the list of events
 visualization on the RETIM tool of the data related to the
highlighted interruption (SAIDI).
Entire MV
Network
 visualization of the list of events in the Replay System
 visualization of the NTW scheme in the Replay System
 visualization on the RETIM tool of the data related to the
highlighted interruption (SAIDI).
 KPIs measurements
Entire MV
network
Entire MV
network
 possibility to modify directly from the list, the events imported in
Replay.
 network configuration: possibility to open and close MV breakers
on the network changing
 network configuration: possibility to open and close MV breakers
on the network changing.
 network power modulation: possibility to change the injection
power customer and producer
Table 14 – Overview of WP4 test cases (Replay tool)
The Replay tool has been installed for the first time in Milano Smart Grid Lab., where all the
Smart Grids Technologies are tested and the ENEL unit responsible for the development and
testing phase is headquartered.
In the Smart Grid Lab, the most innovative equipment that will be installed on the field is tested
by the use of specific network simulators able to be connected with the real equipment.
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In particular in the Smart grid Lab there are infrastructures to test all the functionalities related
to the remote control automation as well as systems to manage EV-smart charging and study
aspects related to electric mobility.
The Smart Grid Lab is generally used for:
 Simulation on network portion with specific software and systems, without having a
direct impact on the system in operation before the installation on the field;
 Analysis and simulations of the behaviour of “Smart equipment” as well as new
protection systems installed on the network and new operation procedures;
 Show room for presentations of Enel innovative technologies (see the picture below).
Collaborations with universities and research institutes guarantee a continuous improvement
in the innovation and in the deployment of new network technologies.
The Replay system is installed in the Milano Smart Grid Lab where a real system in operation
is present. The test phases are running on the Cagliari network database using all the network
DB of Cagliari (Sardegna area) in the Replay System in Milano. A simulator included in the
Replay tool is able to reproduce a list of events as they will occur on the real network in order
to replicate testing phases. Within the evolvDSO project, in the following map, the location of
the test site is represented.
For the scalability and the deployment of the Replay in the operation centers, the real DB events
must be considered. At this development phase, the consideration of real DB events is out of
the scope of the project because this input requires the installation of the Replay in a control
room under “real” operation.
As described in the deliverable D3.2 [2], a network section including eight primary substations
and the related MV feeders will be considered.
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Figure 20 – Replay tool running in the Smart Grid Lab and test site in Sardinia
A simple scheme of the network is represented in the picture below, with distinct colours for
the different voltage levels. In the Enel SCADA system a representation of the primary
substation is given as well as the medium voltage level.
Referring to the following representation, within the evolvDSO project the medium voltage
network is considered including the MV section of the primary substations (red lines) whereas
the HV section in the primary substation as well as the LV network (blue and green lines) are
not considered.
HV
VHV/HV substation
Primary Substation
(HV/MV substation)
HV customer
MV
MV customer
Secondary Substation
(MV or MV/LV
LV substation)
LV customers
Figure 21 – Simplified scheme of the network (Replay tool)
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A schematic representation of the Real Operation System (ST) installed in all the Enel
Operation Control Centers as well as in the Milano Smart grid Lab is given.
STM: Central System for HV/MV
Substations and MV network







Remote control of HV/MV substations
Real time electronic management of the
MV network diagram
Remote control of Secondary Substation
Remote control of Pole top MV Switches
Remote management of MV fault detectors
Automation setting and enabling of the Enel
standardized HV/MV RTU (UP)
Remote control of LV breakers
Figure 22 – Schematic for the Real Operation System (ST) in the Smart Grid Lab in Milano
In Figure 23 a representation of the Replay System (ST-Replay) at the moment installed in
the Smart grid Lab is given with its general architecture.
Figure 23 – Replay tool functional architecture
As shown in the picture above, Replay tool acts as an independent platform using a copy of the
real SCADA system (and its ad-hoc web sections) to elaborate studies in the control room4.
The possibility to open a connection to the external remote PC DSO units is not investigated in this project, but it
will be explored in the near future.
4
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Due to safety reasons, to date, external operators have access to the network real-time schemes
without the possibility to act on them and use all the related tools available in the control room.
A full access will be enabled, allowing a large number of operators to train themselves on a
“future active network”.
Finally to complete the overview of the test, it is interesting to see that two systems will be
available in the Smart Grid Lab:
 A real operation system (ST) with the real Cagliari network and with a simulator of
events;
 A replay system (ST-Replay) with the real Cagliari network with the possibility to
simulate the real operation system.
The Replay tool will be tested on real network portions, considering a real list of occurred
events in order to technically validate the tool on real network and field data (electric schemes,
measurement, network configuration, active power modulation).
The test conditions considered within the analysis context are provided here.
 Ex-post analysis: trying to optimize the outage management (potential SAIDI reduction)
by the operator considering new network configurations;
 Predictive analysis: solving criticalities by the use of a Load flow calculation available in
the tool acting on new network configuration and the possibility to simulate flexibility
in particular active power modulation.
The purpose of test within the WP3 is different from the WP4. The WP3 is mainly related to the
possibility of testing the single modules of the tool with a particular attention to the correct
implementation of the functionalities.
The real test simulation will be implemented in the WP4 involving people of the control centers
collaborating to concretely use the Replay prototype in Milano to adapt the tool for the scalable
diffusion. Furthermore it is necessary to fix bugs and find the room for improvement related to
the operator interface in order to create a product that could be used as an analysis tool.
The preparation of the test in the Italian trials previously consisted in the installation of the
Replay tool in the Siemens’ factory where it has taken place as a specific “Factory Acceptance
Test”. At a later stage, another installation in the Milano Smart Grid Lab has been organized to
connect the real system in operation (ST) installed in the lab with the Replay tool.
The preparations of the tool simulations are based on the preparation of a sheet in order to
organize the test cases. This sheet will be completed on the basis of the MV feeder selected.
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Anyway all the following conditions must be considered:
 Real network sections;
 Elaboration of a list of events occurred on the network on the basis of a simulator
elaborations;
 Possibility to operate on the real network scheme (Enel SCADA interface);
 Availability of LF calculation results based on the Power Flow calculation module
developed within the GRID4EU project in the DEMO4;
 Historical consumption and production measurement representative of every element
of the network are available by the use of the MAGO tool;
 Historic operational data: occurred network events from the real operation system
should be available with particular attention to faults, outages, contingencies;
 Reliability data of the grid assets should be provided by the use of a dedicated interface
called RETIM (Real Time Monitoring Interface) to measure the potential SAIDI
reduction.
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3.3.
Thematic: Maintenance
3.3.1. Introduction
The two sub-tools that comprise the advanced asset management tool sit within the “Operation
and Maintenance” domain. Each is intended to offer useful insights to the distribution system
operator, to improve the quality of asset renewal and maintenance planning. The overall goal
of the software is to give distribution network engineers usable insights on each electrical
component’s role in a distribution network.
Asset Renewal: What is the most efficient way to schedule the upgrade of network components?
For instance, uprating a line sooner means reducing losses sooner; however the time value of
money implies that deferring investment is preferable. Optimization techniques are required
to decide between these trades-offs. This sub-tool optimizes within both a financial and a load
flow framework, so that a potential upgrade’s effect on loss performance, and its discounted
cost, can be considered simultaneously.
Maintenance Priorities: How can a distribution system operator efficiently manage outage risks
on the networks they maintain? This sub-tool calculates the Severity of the outage of each
electrical component in a distribution network. As modern smart distribution networks
increasingly have smart switches and reclosing devices, this sub-tool, crucially, accounts for
how the network may be optimally reconfigured post outage, so only the remaining customers
not served are considered. By calculating these Severity figures, a compelling diagram of
component Risk on the network can be produced, which informs how network maintenance
activities should be prioritized and scheduled on these emerging smart networks.
3.3.2.1. Optimal Asset Management
The two sub-tools that comprise the advanced asset management tool lie within the “Operation
and Maintenance” functional area. Each sub-tool is designed to offer timely insights to the
distribution system operator, to improve the quality of asset renewal and maintenance
planning decisions.
The software gives planning engineers usable insights on each electrical component’s role in a
distribution network. How critical would the failure of a particular transformer be? What would
be the financial implications of uprating a length of overhead line? These questions are
answered using two distinct sub-tools: an assets-renewal component, and a maintenance
priorities component. Each of these analysis sub-tools utilizes mathematical optimization
techniques. A unified frontend permits interaction with both, displaying their output in an
insightful way on a novel visualization of the network under study. Taken together, these three
elements – two optimization components and a novel visualization frontend – make the
“Advanced Assets Management” tool an insights engine.
From January 2016, the tool developers, UCD, will embark upon a period of structured
engagement, to demonstrate the tool in a hands-on way within ESB Networks asset
management. This demonstration initiative will serve as a qualitative test of the tool’s efficacy.
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3.3.2.1.1.
Algorithm Objectives
The goal of the Asset Renewal sub-tool is to give insights on the optimal asset renewal decisions
over a defined study period. These decisions include information on which components to
upgrade, upgrade extent, and upgrade timing.
Each investment plan will describe:
Asset
renewal
decisions
• Timing
• Location
• How much
Fitness
functions
• Active losses (NPV)
• Investment costs (NPV)
The output of the developed tool finds the
optimal asset renewal decisions. These
decisions include information on which
component, upgrade extent, and when it
should be renewed.
The Net Present Value is used since this tool
finds a set of time dependent decision variables
which minimizes the investment costs as well as
the active losses. These two objective functions
can be translated to money. No matter which
entity is responsible for the payment.
The goal of the Maintenance Priorities sub-tool is to offer insight on the varying criticalities of
components within a distribution network section.
3.3.2.1.2.
General overview of the algorithm operation
The asset renewal sub-tool optimizes on net present value to find a set of time dependent
decision variables which minimizes the investment costs as well as the active losses.
- Select .m file via GUI
- Investment horizon
- Discount rate
- Upgrade options
Select
network
Set
investment
parameters
Compute
asset
renewal plan
- Graphical and numerical results
Retune parameters if necessary
Visualize
plan on
network
Actionable insights
Figure 24 – General overview of the Asset Renewal sub-tool optimization process
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Figure 25 – Detailed view of the Asset Renewal sub-tool optimization process
To provide its insights, the maintenance priorities sub-tool calculates the impact of each line
outage, the Severity, by enumerating all single contingencies and calculating the curtailed
power of each node, taking into account the potential for smart reconfiguration of the network.
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- Select .m file via GUI
Select
network
- Add outage probabilities
to network description
Set
Frequency
parameters
- Computes Severity
for each outage
- Graphical and numerical results
Compute
Severity
levels
Visualize
Risk on
network
Actionable insights
Figure 26 – General overview of the Maintenance Priorities sub-tool optimization process
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Figure 27 – Detailed view of the Maintenance Priorities sub-tool optimization process
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3.3.2.1.3.
Input data requirements
Inputs required by the Asset Renewal sub-tool:
Network Data
•Network topology
•Feeder data (R,X)
•Capacitors
Demand data
•Demand pattern
•Residential share
•Commercial share
•Industrial share
DER characteristics
•Characteristic curves
•Voltage control capabilities
Network switches
•Innitial topology
•Switch locations
•Switching costs
•Financial data
•Interest rate
•Upgrade costs
•Maximum investment budget
Investment
constraints
Figure 28 – Nature of the inputs required by the Asset Renewal sub-tool
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Inputs required by the Maintenance sub-tool:
Figure 29 – Nature of the inputs required by the Maintenance sub-tool
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3.3.3. Irish field test / trials: ESB
UCD are developing an asset management software tool for the Irish trial. The main objective
of the software is to give distribution network engineers usable insights on each component’s
role in a distribution network and assist in their maintenance and renewal planning. This tool
is timely given that the emergence of renewables and smart networks technology is
transforming how distribution system are operated, planned and maintained. The tool answers
questions such as:


How critical would the failure of a particular transformer be?
What would be the financial implications of uprating a length of overhead line?
These questions, among others, which are relevant to the management of ESB Networks assets
can be answered using two distinct sub-tools: an Assets Renewal component, and a
Maintenance Priorities component. The Asset Management tool developed by UCD will be
trialled within the ESB Networks Asset Management division to provide valuable insight into
asset management maintenance and renewal decisions. The feedback from the Asset
Management team in ESB Networks will provide relevant information to UCD to refine and alter
the tool if necessary. The demonstration tests aim to capture the benefit of using the tool, and
the data acquired during these tests will feed into the impact assessment in WP5.
The demonstration of this asset management tool will be done through computer simulation.
The simulation will be divided into two distinct sub-tools: an Assets-Renewal component, and
a Maintenance Priorities component. Each of these analysis backend components will utilize
rigorous mathematical optimization techniques. A unified frontend will permit interaction with
both, displaying their output in a meaningful way on a novel visualization of the network under
study. Taken together, these three elements – two optimization components and a novel
visualization frontend – make the Advanced Assets Managements tool an insights engine.
No field trial will be required to demonstrate this tool. However, this tool will be used within
the asset management offices by ESB Networks network design planners and strategists during
a series of interactive demonstration events. The tool will examine a number of networks with
different topologies with the aim of demonstrating the value and applicability of the tool in a
real-life environment.
The first section of network that ESB Networks will test in the demonstration phase consists of
three 20 kV outlets – two coming from one 38 kV station and the other one out of another 38 kV
station.
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Sub-tool
Asset Renewal
1
Network electrical
parameters
+
2
+
Financial
parameters
Asset renewal
financial analysis
(SUC_O&M_01A)
Sub-tool
Maintenance
Reliability
data
Insights
engine
Component Risk
analysis
(SUC_O&M_01B)
Enhanced
maintenance
priorities
Optimized asset
upgrade schedule
Insightful
visualization
Figure 30 – Inputs and outputs of the Asset Management Software tool
Each interactive demonstration event, with various sets of participants, will follow this outline:
i.
ii.
iii.
iv.
v.
Introduction of the tool by the developers, UCD;
Sample exposition of an analysis of a network by the developers;
Interactive use of the tool by ESB Networks participants;
Structured feedback on the tool via a standardized survey;
Discussion of tools’ strengths and weaknesses.
By holding these events at intervals over the period of structured engagement, a broad-cross
section of distribution system engineers can be reached. It also permits ongoing tweaking and
development of the tool. Results from simulations carried out in the tool will be produced in
system diagram format.
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3.3.3.3.1.
Visualization
The inherent structural characteristics of a distribution network can be meaningfully
represented using force-directed layout algorithms. UCD will leverage its expertise in this area
to produce system diagrams that meaningfully, and interactively, portray the results of the
intricate optimization processes.
Figure 31 - A sample network, where the branch thickness corresponds to the outage Risk associated with that
component
Figure 32 - Another sample network, where the branch thickness shows the degree to which each conductor
should be uprated in this planning period
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The preparations for simulation of the tool in the Irish trials are the following:
 Representative cost and performance data from ESB Networks assets will need to be
parameterised in the tool’s input format, which is based on the MATPOWER standard;
 The data provided by ESB Networks will be adapted to suit the requirements of the tool
prior to demonstration;
 UCD will provide tutorials on how to use the tool to the ESB Networks Asset
Management staff that will be using the tool during the demonstration days.
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4. Conclusions
The methodology inspired from IEC/PAS 62559 IntelliGrid allowed to perform a detailed
assessment of the available technologies of the partners, both research institutes as innovative
tool developers and DSOs. This assessment was carried out through a generic survey composed
of two separate but complementary sections:
 the one aimed to the research institutes to provide information about the
standardization, openness, scalability… levels and input data requirement of their tools;
 the one aimed at the DSOs helps to derive the general inference about their overall
technology and tool architecture.
This process helped to open communication channels between partners and contributed to the
selection of which tool developed in WP3 should be applied by which DSO for which field or
laboratory tests in which operational conditions. These tests complement the validation tests
performed by the research institutes and detailed in Deliverable D3.4. Tools related strictly to
planning are not furtherly tested in WP4.
The results of this process lead to the selection of six tools covering three domains (Operation,
TSO/DSO Coordination and Maintenance) out of the ten tools covering the four domains
considered in WP3. These tools will be applied to six field or laboratory tests, with a few tools
applied in more than one trial. The main goal will be to assess the value and the applicability of
the tools within the real operational environment of distribution networks.
The table below illustrates the association between the tools developed by the research
institutes and the trials considered by each DSO.
EDP
ENEL
ERDF
ESB
Northern Site Southern Site Milano Centro
SOGRID
VENTEEA Various MV
Prove
(Lab)
(Field)
(Field)
(Lab)
(Field)
(Field)
Interval
Constrained
Power Flow
INESC Sequential
OPF
LV State
Estimation
Contingency
RSE Co-Simulation
Tested
Tested
/
Tested
Tested
/
Tested
Tested
/
/
/
/
/
/
/
Tested
/
/
/
/
/
/
Tested
/
ENEL
Replay
/
/
Tested
/
/
/
UCB
Advanced
Asset
Management
/
/
/
/
/
Tested
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TSO-DSO Coordination Domain
Two field tests are considered for the “TSO-DSO Coordination” Domain:
 The EDP field tests involve two HV & MV test sites, one in the North of Portugal in the
vicinity of Porto and the other one in the South in the vicinity of Lisboa. In these two
sites, both the ICPF and the SOPF will be considered and integrated into EDP
system infrastructure;
 The ERDF field tests involve two MV test sites, one in the North of France (VENTEEA)
and the other one in the South (SOGRID). In both sites, the ICPF will be considered and
integrated into ERDF system infrastructure.
Operational Domain
Two field tests are considered for the “Operational” Domain:
 The ERDF field tests involve a MV test site in the North of France (VENTEEA) and a LV
test site in the South (SOGRID):
o The CCS tool will be applied to the MV test site. It will be integrated into ERDF
system infrastructure in the same way as the ICPF tool. It will provide forwardlooking set-points to the operator that will help him to manage its network;
o The LVSE tool will be applied to the LV test site on several LV substations.
Decentralized real-time integration of the algorithm will be simulated based on
the measurement data collected from the field both in real-time and in batch that
is stored within ERDF system.
 The ENEL trials involve several MV feeders that will be selected from the Cagliari
network (Sardinia). The Replay tool will be applied to these networks within the
Milano Smart Grid Lab in order to perform ex-post analysis of past real events or
predictive analysis by introducing events and/or managing the available network
flexibilities.
Maintenance Domain
The Advanced Asset Management tool will be demonstrated in the ESB trials through
computer simulation. No field trial will be performed to demonstrate this tool, but the AAM
will be used within the asset management offices by ESB network design planners and
strategists during a series of interactive demonstration events.
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REFERENCES
[1] Rivero, E., Ramos, A. & Six, D., 2014. Evaluation of current market architectures and
regulatory frameworks and the role of DSOs (D1.2), evolvDSO Project.
[2] Clerici D. et al., 2015. Advanced Tools and Methodologies for Forecasting, Operational
Scheduling and Grid Optimisation (D3.2), evolvDSO Project.
[3] Bessa R. et al., 2015. Advanced Methodologies and Tools for Operation and Maintenance of
Distribution Grids with DRES (D3.3), evolvDSO Project.
Page 80 of 80

- EvolvDSO

Transcription

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