Deliverable D1.6 List of KPIs: KPI and process of measures

Deliverable D1.6

List of KPIs: KPI and process of measures

V1.4

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement n° 824414

Disclaimer This document reflects the Coordinet consortium view and the European Commission (or its delegated Agency INEA) is not responsible for any use that may be made of the information it contains

D1.6 – List of KPIs: KPI and process of measures V1.0

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D1.6 – List of KPIs: KPI and process of measures Document Information

Programme Horizon 2020 – Cooperation / Energy

Project acronym Coordinet

Grant agreement number 824414

Number of the Deliverable D1.6

WP/Task related [WP1, WP3-WP6/ T1.5, T1.6, T6.1, T6.2, T6.3]

Type (distribution level) PU Public

Date of delivery [23-07-2019]

Status and Version Version 1.6

Number of pages 62 pages

Document Responsible Dimitris Trakas – ICCS/NTUA

Author(s) Dimitris Trakas – ICCS/NTUA

Vasilis Kleftakis – ICCS/NTUA

Reviewers Christoffer Isendahl – E.ON

Agustín Díaz García – REE


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Revision History

Version Date Author/Reviewer Notes

0.1 07/06/2019 Dimitris Trakas (ICCS/NTUA) First draft

0.2 21/06/2019 Dimitris Trakas (ICCS/NTUA) Contributions to Chapters 2-4

0.3 01/07/2019 Dimitris Trakas (ICCS/NTUA) KPIs were added to deliverable

0.4 02/07/2019 Dimitris Trakas (ICCS/NTUA) Corrections to KPIs based on feedback

received from demo leaders

1.0 03/07/2019 Yvonne Ruwaida (Vattenfall)

Corrections to KPIs mapping to Swedish

BUCs based on comments received from

Swedish demo leader

1.1 05/07/2019

Christoffer Isendahl (E.ON)

Marios Sousounis (IPTO)

Pandelis Dratsas (IPTO)

Comments from E.ON and IPTO have

been incorporated

1.2 08/07/2019 Agustín Díaz García (REE) Comments from REE incorporated

1.3 17/07/2019 WP1 Task Leaders

Final changes on images, acronyms and

content on the basis of task leader

feedback

1.4 19/07/2019

Kris Kessels (VITO) - WP6

Leader

José Pablo Chaves Ávila

(Comillas) – WP7 Leader

Carlos Madina (Tecnalia) –

WP2 Leader

Comments from VITO, Comillas and

Tecnalia have been incorporated

1.5 22/07/2019 Spanish demo Final changes on Spanish demo KPIs

1.6 23/07/2019 (Marco Baron) Enel Comments from Enel have been

incorporated


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Acknowledgements

The following people are hereby duly acknowledged for their considerable contributions, which have served

as a basis for this deliverable.

Name Partner

José Pablo Chaves Ávila Comillas

Miguel Pardo Endesa

Carolina Manaresi Enel

Daniele Porcu Enel

Marco Baron Enel

Nazdya Silva Aguirre Enel

Luis Viguer Torres ETRA

Christoffer Isendahl E.ON

Emmamouil Voumvoulakis HEDNO

David Martin Iberdrola

Aris Dimeas ICCS/NTUA

Marios Sousounis IPTO

Pantelis Dratsas IPTO

Thanasis Bachoumis IPTO

Agustín Díaz García REE

Carlos Madina Tecnalia

Inés Gómez Tecnalia

Maider Santos Tecnalia

Yvonne Ruwaida Vattenfall

Kris Kessels VITO

Rivero Enrique VITO


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Executive summary

This deliverable aims at identifying the Key Performance Indicators (KPIs) which will be used to support the

monitoring process of Research and Innovation (R&I) activities, assess of the impacts of the proposed

activities and evaluate the overall contribution of the proposed activities to the EU policy goals:

Sustainability, Market Competitiveness and Security of Supply.

As depicted in Figure 1, the work in Task 1.6 (described in this deliverable) is closely related to task 1.3:

“Definition of products and coordination schemes” and task 1.5: “BUC definition for the demonstrators”.

All three mentioned tasks are fundamental for the demo preparation phase for the three demo countries,

Greece, Spain and Sweden. The KPIs that are analysed in each BUC and documented in D1.6, will play an

important role for the evaluation of the demo ambitions in WP3-5 as well as for a later assessment and

evaluation of the demonstration campaigns in WP6.

Figure 1: Main interactions and links of WP1 deliverables with the other WPs of the CoordiNet project

In order to identify the KPIs that will be used in each demo, the EEGI methodology was adopted. Relevant

European projects were analyzed and the most relevant KPIs for CoordiNet were selected. Then, some of

the selected KPIs were modified according to CoordiNet needs. Furthermore, new KPIs were defined by the

demo leaders and WP6 task leaders. A similar template was used for KPIs definition that provides several

information on KPIs, such as description, calculation formula and related BUCs. This template was also used

in order to provide information on KPIs taken from other European projects. Therefore, the final list of KPIs

identified by CoordiNet consists of KPIs directly adopted from other projects, adapted KPIs to CoordiNet

needs and new KPIs defined by CoordiNet. In addition, similar KPIs used by different demos were identified

and the KPIs were classified into technical, economic, environmental and social ones as well as into the

categories defined by the EEGI methodology.

The goal was to address each objective of the demos by at least one KPI. The identified KPIs will be used in

order to:

• monitor demo performance,

• assess and evaluate the demonstration campaigns results,

WP3 & WP4 & WP5

-

Demo Activities

D1.2 Ex-ante consumer

engagement

D1.4 DER Characteristics

D1.1 Current market &

regulatory framework

D1.3 Definition of products

and CS

D1.5 BUC definition for the

demonstrators

D1.6 KPI (technical,

environmental and economic)

Specification

for SW & HW

in Demos

Demo Setup &

Requirements

Feedback & Update

Generic

specification

of interfaces

Demo results Missing links

+ Demo Data

Inputs on

CAPEX / OPEX

Engagement

plan + Inputs

on DER

BUCs, products

+ CSs, KPIs

TSO & DSO

Needs, DER

Capabilities +

Product

Definitions

WP2

WP6

WP1


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• perform an economic assessment in order to provide recommendations for an adapted market

design at EU level and needed policies to support this,

• evaluate the user and customer engagement plan followed by each demo.

The procedure that was followed for KPIs identification is illustrated in Figure 2.

Figure 2: Procedure followed to identify KPIs

The CoordiNet project identified 39 KPIs that are presented in Table 1. Furthermore, Table 1 shows the

mapping of the KPIs to the different demos.

Table 1: Summary of identified KPIs

KPI ID KPI Name Spanish Demo

Swedish Demo

Greek Demo

KPI_1 Cost of counteractions needed based on the activated flexibility

✓

KPI_2 Estimation of the increment of reactive power flexibility for the network operators (TSO and DSO)

✓

KPI_3 Cost of R&I solution VS alternative grid solution

✓ ✓ ✓

KPI_4 OPEX - OPerational EXpenditures ✓ ✓ ✓

KPI_5 OPEX for service procurement ✓ ✓ ✓

KPI_6 Average cost per service for the examined period

✓ ✓ ✓

KPI_7 Increase RES and DER hosting capacity ✓

✓

KPI_8 Reduction in RES curtailment ✓ ✓ ✓

KPI_9 Share of fossil-based activated energy ✓ ✓

KPI_10 Accuracy of the RES production forecast calculated 1 hour in advance

✓

✓

KPI_11 Accuracy of the RES production forecast calculated 24 hours in advance

✓

✓

Review relevant European Projects

Directly adopted KPIs Adapted KPIs

New KPIs defined by WP6 task leaders

New KPIs defined by demo leaders

Identification of similar KPIs and classification of KPIs

Final list of KPIs


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KPI_12 Voltage variation ✓ ✓

KPI_13 Criticalities Reduction Index ✓

KPI_14 Islanding duration ✓

KPI_15 TIEPI - Equivalent interruption time related to the installed capacity

✓

KPI_16 Potential Offered flexibility ✓

✓

KPI_17 Increase in the amount of load capacity participating in DR

✓

✓

KPI_18 Volume of transactions ✓ ✓ ✓

KPI_19 Number of transactions ✓ ✓ ✓

KPI_20 ΙCT cost ✓ ✓ ✓

KPI_21 Deviation between accepted and actual activated mFRR

✓

KPI_22 Requested flexibility ✓

KPI_23 Data reliability ratio ✓

KPI_24 Accuracy of load forecast calculated 1

hour in advance ✓

KPI_25 Accuracy of load forecast calculated 24 hours in advance

✓

✓

KPI_26 State estimation performance evaluation ✓

KPI_27 Market utilization factor ✓

KPI_28 Increased grid connections ✓

KPI_29 Capacity increase with reactive management

✓

KPI_30 Peak load demand reduction ✓

KPI_31 Total activation time of a product ✓

KPI_32 Delivered energy in controlled island ✓

KPI_33 Maximum power (non-transient) in

controlled island ✓

KPI_34 Number of products per demo ✓ ✓ ✓

KPI_35 Ratio of forwarded flexibility bids ✓

KPI_36 Participant recruitment ✓ ✓

KPI_37 Active participation ✓ ✓ ✓

KPI_48 Type of flexibility providers per demo ✓ ✓ ✓

KPI_39 Total Computational Runtime ✓ ✓ ✓

In order to calculate the KPIs, the necessary datasets should be collected in WP3-5. The datasets collected

in these WPs would also be provided to WP6 to assess and evaluate the results of the demonstration

campaigns and perform the economic assessment.

This deliverable aims at identifying all the KPIs that will be used in CoordiNet. However, during the course

of the project, new KPIs might need to be defined in WP3-WP5 according to the needs of the demonstrations.


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Table of contents

Revision History ........................................................................................................... 3

Acknowledgements........................................................................................................ 4

Executive summary ....................................................................................................... 5

Table of contents ......................................................................................................... 8

List of figures .............................................................................................................. 9

List of tables ............................................................................................................. 10

Abbreviations and Acronyms ........................................................................................... 11

1. Introduction ........................................................................................................ 12

1.1. The CoordiNet project ...................................................................................... 12

1.2. Objective and scope ........................................................................................ 13

1.3. Methodology .................................................................................................. 13

1.4. Structure...................................................................................................... 14

2. EEGI developed framework ....................................................................................... 16

2.1. Introduction to EEGI methodology ........................................................................ 16

2.2. KPI design..................................................................................................... 16

2.3. KPI calculation methodology ............................................................................... 19

3. CoordiNet KPIs ..................................................................................................... 20

3.1. KPIs identification ........................................................................................... 20

3.2. KPIs definition ............................................................................................... 21

3.3. KPIs evolution ................................................................................................ 22

4. List of CoordiNet KPIs ............................................................................................. 24

4.1. KPIs of Spanish demonstration BUCs ...................................................................... 26

4.2. KPIs of Swedish demonstration BUCs ..................................................................... 28

4.3. KPIs of Greek demonstration BUCs ........................................................................ 29

5. Conclusions ......................................................................................................... 31

6. References .......................................................................................................... 32

7. ANNEX A - KPIs ..................................................................................................... 33

7.1. Specific KPIs .................................................................................................. 33

7.1.1. A.2 Increased system flexibility at acceptable cost ................................................. 33

7.1.2. B.1 Increased RES and DER hosting capacity .......................................................... 38

7.1.3. B.2 Reduction in energy not supplied from DER ...................................................... 38

7.1.4. B.3 Power quality and quality of supply ............................................................... 41

7.1.5. B.5 Increased flexibility from energy players ......................................................... 45

7.1.6. B.6 Improved competitiveness pf the electricity market ........................................... 46

7.1.7. B.8 Reduce CAPEX and OPEX of ICT infrastructures ................................................. 48

7.2. Project KPIs .................................................................................................. 49


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List of figures

Figure 1: Main interactions and links of WP1 deliverables with the other WPs of the CoordiNet project..... 5

Figure 2: Procedure followed to identify KPIs ......................................................................... 6

Figure 3: Overall CoordiNet approach ................................................................................ 13

Figure 4: Procedure followed to identify KPIs ....................................................................... 14

Figure 5: EEGI Expected Impact KPI Levels (GRID+, 2013). ........................................................ 17

Figure 6: Comparison between R&I and BaU solutions (GRID+, 2013). ........................................... 19

Figure 7: Template used for KPI definition .......................................................................... 22

Figure 8: KPIs evolution ................................................................................................ 23

Figure 9: Overview of BUCs (CoordiNet, 2019) ...................................................................... 24


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List of tables

Table 1: Summary of identified KPIs ................................................................................... 6

Table 2: Acronyms list .................................................................................................. 11

Table 3: Functional objectives addressed by CoordiNet ........................................................... 20

Table 4: List of identified KPIs ........................................................................................ 24

Table 5: KPIs of the Spanish demonstration BUCS .................................................................. 26

Table 6: KPIs of the Swedish demonstration BUCS.................................................................. 28

Table 7: KPIs of the Greek demonstration BUCS .................................................................... 29


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Abbreviations and Acronyms

aFRR automatic Frequency Restoration Reserves

BaU Business as Usual

BUC Business Use Case

CAPEX CAPital EXpenditure

CBA Cost Benefit Analysis

DER Distributed Energy Resource

DG Distributed Generator

DR Demand Response

DSO Distribution System Operator

EEGI European Electricity Grid Initiative

EIIs European Industrial Initiatives

ES Spain

ETO Economic Trade-Off

ETIP SNET European Technology and Innovation Platform Smart Networks for Energy Transition

EV Electric Vehicle

FCR Frequency Containment Reserves

FFR Fast Frequency Response

FO Functional Objective

FSP Flexibility Service Provider

GR Greece

ICT Information and Communication Technologies

KPI Key Performance Indicator

mFRR manual Frequency Restoration Reserves

MV / LV Medium Voltage / Low Voltage

OPEX OPerational EXpenditure

RES Renewable Energy Resource

RD&D Research, Development and Demonstration

RR Replacement Reserves

R&I Research and Innovation

TIEPI Equivalent interruption time related to the installed capacity (used in Spain)

TSO Transmission System Operator

SAIFI System Average Interruption Frequency Index

SE Sweden

SET-Plan Strategic Energy Technology Plan

SO System Operator

WP Work Package

Table 2: Acronyms list


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1. Introduction

1.1. The CoordiNet project

The CoordiNet project is a response to the call LC-SC3-ES-5-2018-2020, entitled “TSO – DSO – Consumer:

Large-scale demonstrations of innovative grid services through demand response, storage and small-scale

generation” of the Horizon 2020 programme. The project aims at demonstrating how Distribution System

Operators (DSOs) and Transmission System Operators (TSOs) shall act in a coordinated manner to procure

and activate grid services in the most reliable and efficient way through the implementation of three large-

scale demonstrations. The CoordiNet project is centered around three key objectives:

1. To demonstrate to which extent coordination between TSO/DSO will lead to a cheaper, more

reliable and more environmentally friendly electricity supply to the consumers through the

implementation of three demonstrations at large scale, in cooperation with market participants.

2. To define and test a set of standardized products and the related key parameters for grid services,

including the reservation and activation process for the use of the assets and finally the settlement

process.

3. To specify and develop a TSO-DSO-Consumers cooperation platform starting with the necessary

building blocks for the demonstration sites. These components will pave the way for the

interoperable development of a pan-European market that will allow all market participants to

provide energy services and opens up new revenue streams for consumers providing grid services.

In total, eight demo activities will be carried out in three different countries, namely Greece, Spain, and

Sweden. In each demo activity, different products will be tested, in different time frames and relying on

the provision of flexibility by different types of Distributed Energy Resources (DERs). Figure 3 presents an

approach to identify preliminary standardized products, grid services, and coordination schemes to

incorporate them into the future CoordiNet platform for the realization of the planned demo activities1.

1 Considering that this Deliverable D1.6 is being published at an early stage of the project, these characteristics may change. Please refer to the latest CoordiNet deliverables for updated information.


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Figure 3: Overall CoordiNet approach (FFR: Fast Frequency Response, FCR: Frequency Containment Reserves, aFRR: automatic

Frequency Restoration Reserves, mFRR: manual Frequency Restoration Reserves, RR: Replacement Reserves)

1.2. Objective and scope

This deliverable describes the work carried out in Task 1.6 for the definition and formulation of Key

Performance Indicators (KPIs) and presents the KPIs that will be used to evaluate the results of the solutions

proposed and implemented within the CoordiNet project. These KPIs will be used to measure the impact of

the new solutions proposed by CoordiNet and monitor their performance. In addition, KPIs will be used to

compare the demonstration activities.

The objective of this report is to provide WP3, WP4 and WP5 with technical, economic, environmental and

social KPIs in order to quantify and evaluate the impact of the new solutions in the demonstration sites. In

addition, some of the identified KPIs will be used in WP6 to assess and evaluate the results of the

demonstration campaigns and perform an economic assessment in order to provide recommendations for an

adapted market design at EU level and needed policies to support this. Moreover, KPIs will be used to

evaluate the user and customer engagement plan followed by each demo.

The scope of this document is to list the identified KPIs that address the objectives of the BUCs, as they

have been defined in D1.5, monitor demos’ performance in WP3-5 and enable the assessment and evaluation

of the results in WP6. It is noted that since the project is at an early stage, further KPIs might need to be

defined in WP3-5 and others might still need to be adapted or withdrawn for specific demos.

1.3. Methodology

In order to define the KPIs and accomplish the goals mentioned in Section 1.2, the European Electricity Grid

Initiative (EEGI) (European Electricity Grid Initiative (EEGI), n.d.) methodology has been followed. For KPIs

definition, two main activities were carried out: the review of relevant European Projects in order to borrow

KPIs defined in the analyzed projects and the definition of new KPIs.

Initially, a list of KPIs was compiled by reviewing 11 European projects (most of which were EEGI labelled

projects). Some of the KPIs have been modified according to the objectives and needs of the demo activities.


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Demo leaders selected the KPIs included in this list to be used for their BUCs. In addition, demo leaders

defined new KPIs that were not included in the aforementioned list to address all the objectives of their

demo activities and measure the performance of the demonstrations. The same template was used by all

the demo leaders for the KPIs definition. The used template included KPI information as well as information

on the necessary data that has to be collected during the demonstration to calculate the KPIs. Since this

deliverable is being published at an early stage of the project, the necessary data could not yet be defined

at this stage. This information should be gathered in WP3-5. However, the relevant fields are included in

the template in order to present the information which should be collected in WP3-5. Furthermore, new

KPIs were defined by WP6 task leaders, in cooperation with demo leaders, in order to address CoordiNet

objectives and enable the evaluation of the results in WP6.

Finally, similar KPIs used by different demos were identified and all the selected KPIs to be used in CoordiNet

were classified into different categories, such as technical, economic, environmental and social KPIs in order

to be sure that different aspects are addressed. Moreover, following the GRID+ methodology that is

presented in Section 2.2, the identified KPIs were declared as “Specific” KPIs (clarified and indicated in

which “specific” category they belong to) or as “Project” KPIs.

The general procedure followed to identify the KPIs, is presented in Figure 4.

Figure 4: Procedure followed to identify KPIs

1.4. Structure

Chapter 2 presents the main characteristics of the KPIs and introduces the EEGI methodology which was

adopted by the CoordiNet project in order to define the KPIs. Furthermore, the different levels of KPIs

defined by the EEGI developed framework as well as the steps that are followed to calculate KPIs in a

differential mode are presented.

In Chapter 3, the procedure followed in order to identify the list of KPIs that will be used in CoordiNet is

described. In addition, the template used to provide information on all the KPIs identified in the project

and the necessary future actions for the calculation of the KPIs are presented.

Review relevant European Projects

Directly adopted KPIs Adapted KPIs

New KPIs defined by WP6 task leaders

New KPIs defined by demo leaders

Identification of similar KPIs and classification of KPIs

Final list of KPIs


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Chapter 4 lists the identified KPIs and links them to the defined BUCs in D1.5 of this project. Furthermore,

the KPIs are categorized and they are divided into Specific and Project KPIs.

Chapter 5 concludes this deliverable by providing an overview of the identified KPIs and their main use.


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2. EEGI developed framework

2.1. Introduction to EEGI methodology

In order to measure the contribution of the new solutions proposed by CoordiNet to specific EU policy goals

and evaluate their results, it is necessary to define KPIs. For their definition, CoordiNet will rely on the EEGI

Roadmap 2013-2022 (EEGI, 2013) and its update and extension proposed by the Final 10 year European

Technology and Innovation Platform Smart Networks for Energy Transition (ETIP SNET) R&I Roadmap 2017-

2026 (ETIP-SNET, 2016) and ENTSO-E Research, Development and Innovation Roadmap 2017-2026 (ENTSO-E,

2016).

The EEGI is one of the European Industrial Initiatives (EIIs) under the Strategic energy Technology Plan (SET-

Plan) and proposes a nine-year European research, development and demonstration (RD&D) programme to

accelerate innovation and the development of the electricity networks of the future in Europe. EIIs are

industry-driven strategic technology alliances to address key low-carbon energy technologies. ETIP have

been created by the European Commission in the framework of the new Integrated Roadmap (SET Plan) by

bringing together a multitude of stakeholders and experts from the energy sector while the ETIP SNET role

is to guide Research, Development & Innovation (RD&I) to support Europe’s energy transition.

The EEGI framework was developed under the GRID+ project (GRID+, 2013). One of the objectives of the

GRID+ project was to develop a methodological guide to design and use a set of KPIs in view of managing

the European EEGI R&I Roadmap 2013-2022. The proposed indicators pinpoint the enabling role of electricity

networks in view of achieving the European energy policy targets, i.e. sustainability, competitiveness and

security of supply. The method for the definition of KPIs proposed by the GRID+ project was adopted by

CoordiNet. According to GRID+ the KPIs can be divided into two categories:

• Implementation Effectiveness KPIs, which measure the progress of research and innovation

activities, as percentage of completion of the EEGI Roadmap.

• Expected Impact KPIs, which estimate the benefits of European R&I projects achievements.

All the defined KPIs should be:

• Meaningful, which means that a KPI relates with one or several expected innovation impacts, and

therefore makes sense as it contributes to reach the program/project overarching goals.

• Understandable, which means that the KPI definition relates clearly with the expected impacts of

the studied innovation.

• Quantifiable, which means that experimental values coming from field testing at an appropriate

scale are used to develop ad-hoc simulation tools able to estimate the expected innovation impacts.

2.2. KPI design

The Expected Impact KPIs according to the EEGI framework, which was developed under GRID+ project

(GRID+, 2013), are divided into three levels as presented in Figure 5.


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Figure 5: EEGI Expected Impact KPI Levels (GRID+, 2013).

• Level 1 - Overarching KPIs appraise the progress brought by EEGI R&I activities towards the

overarching goal of the EEGI 2013-2022 Roadmap.

• Level 2 - Specific KPIs to appraise the progress brought by R&I activities relative to the different

clusters and functional objectives of the EEGI 2013-2022 Roadmap. Clusters and objective can be

found in (EEGI, 2013).

• Level 3 – Project KPIs are proposed by each R&I project addressing the R&I activities specified in

the different clusters and functional objectives of the EEGI 2013-2022 Roadmap.

The overarching KPIs and the specific KPIs that were proposed in the GRID+ project for the EEGI 2013-2022

Roadmap are the following:

Overarching KPIs:

• A.1 Increased network capacity at affordable cost: Increase the network capacity for all grid-

users wherever and whenever necessary while keeping the cost of increased network capacity

affordable, i.e. maximizing the added network capacity per euro of investment.

• A.2 Increased system flexibility at affordable cost: Increase system flexibility for all grid-players

while keeping the cost of the increased system flexibility as affordable as possible.

Specific KPIs:

• B.1 Increased RES and DER hosting capacity: Increase the amount (MW/GW) of RES/DER

integration by intelligent network investment, using advance power technologies or better

coordination of system operation.

• B.2 Reduced energy curtailment of RES and DER: Reduce energy curtailment (GWh/MWh) of

RES/DER generation due to technical and operational problems such as over-voltage, over-

frequency, local congestion, i.e. maximize the electricity generation from green energy of RES with

low marginal operation cost.


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• B.3 Power quality and quality of supply: Maintain high quality of power supply to end-users via

preventive actions with early warning system, advanced and optimal system development and

operation tools, as well as high availability of assets via optimal maintenance strategies and planning

tools.

• B.4 Extended asset life-time: Increase the life-time of assets while operating closer to their limits

without endangering the system reliability; reduce total cost of replacements; increase efficiency

of the electricity system by reducing the down-time of assets.

• B.5 Increased flexibility from energy players: Increase flexibility of power system to maintain

system security via new cost-effective non-conventional sources of flexibility services; increased

number and wider distribution of flexibility sources to mitigate single source of failure, etc.

• B.6 Improved competitiveness of the electricity market: Improve competitiveness of the

electricity market, by providing energy and ancillary services to the grid at affordable costs, which

will translate in increased welfare for the end-users.

• B.7 Increased hosting capacity for EVs and other new loads: Measure the contribution that

different relevant smart grid projects have in increasing the capacity of distribution network to host

Electric Vehicles (EVs).

In their latest Roadmap (ENTSO-E, 2016), TSOs have proposed to keep the existing EEGI implementation

effectiveness KPIs. For the distribution system, ETIP SNET Roadmap (ETIP-SNET, 2016) proposed some

changes to Specific KPIs in order to adapt the EEGI framework to the future R&I needs of the electricity

system. Overarching KPI A.2 is now used as a Specific KPI and it has been renamed to “Increased system

flexibility at acceptable cost”. Furthermore, adaptation of some of the existing KPIs and new KPIs were

proposed. The list below presents the new and renamed Specific KPIs for distribution system.

• A.2 Increased system flexibility at acceptable cost

• B.1’ Reduction in cost of DG integration

• B.1’a Reduction in costs to stay within network capacity limits

• B.1’b Reduction in costs to stay within PQ limits

• B.2 Reduction in energy not supplied from DER

• B.4 Optimize (CAPEX and OPEX) asset lifespan

• B.7 Increased network hosting capacity for EVs

• B.8 Reduce CAPEX and OPEX of ICT infrastructures

• B.9 Planning tools readiness

• B.10 Planning rules readiness

Concerning Overarching KPIs, it was proposed to keep the existing KPIs and to add a new one related to

reliability, for example the “System Average Interruption Frequency Index” (SAIFI).


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2.3. KPI calculation methodology

As mentioned above, the Expected Impact KPIs are used to quantify the impact delivered by R&I solutions.

The EEGI methodology proposes to compare the benefits of applying the R&I solutions with the expected

benefits of applying Business as Usual (BaU) solutions, as shown in Figure 6. Therefore, BaU solutions, which

are the solutions using traditional technologies, are used as reference in order to quantify the benefits that

are gained by applying the solution proposed by R&I projects.

Figure 6: Comparison between R&I and BaU solutions (GRID+, 2013).

Assuming that a BaU solution exists, the steps that are followed in order to calculate KPIs in a differential

way, are listed below:

1. Determination of the initial condition and identification of the problems that need to be solved or

situations that need to be improved.

2. Determination of the possible future situation(s) implementing BaU solutions and estimation of the

results and the progress made after applying this approach.

3. Determination of the possible future situation(s) implementing R&I solutions in order to analyze the

improvements from applying innovative technologies and estimate the results and the progress made

after applying this approach.

4. Calculation of the KPIs by applying the proposed formula for each KPI in order to compare the R&I

and BaU solutions.

Impact R&I

BaU


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3. CoordiNet KPIs

3.1. KPIs identif ication

A list of KPIs was identified in the CoordiNet project to enable the evaluation of the impact of the proposed

solutions in the demonstration sites. The KPIs will also be used to ensure an unimpeachable comparison

between the demonstration activities. Both, Specific and Project KPIs were identified to capture the impact

of the solutions proposed by CoordiNet. The list of identified KPIs consists of technical, economic,

environmental and social ones in order to investigate all the aspects of the proposed solutions. Furthermore,

the calculation methodology of each KPI was defined.

The list of KPIs consists of directly adopted KPIs from relevant European projects, adapted KPIs (KPIs taken

from another project but they have been adapted according to CoordiNet needs) and new KPIs proposed by

CoordiNet. Table 3 shows the Functional Objectives (FOs) of ETIP SNET Roadmap (ETIP-SNET, 2016) to which

CoordiNet will contribute and are addressed by the identified KPIs. The letters “T” and “D” in the FO ID

column of Table 3 indicate the transmission and distribution system FOs, respectively. As it is noted in ETIP

SNET Roadmap (ETIP-SNET, 2016), via coordinated activities between TSO and DSO, a) DSO can be identified

as contributor to the achievement of several transmission system FOs and b) TSO as a contributor to several

achievement of the distribution system FOs. For example, new ancillary services with more active

contribution from demand and units connected at DSOs networks and from DSO facilities could contribute

to FO T9 “Enhanced ancillary services for network operation”.

Further FOs might be added to this list as the CoordiNet project progresses. In this case new KPIs will be

defined so that a) all FOs are addressed by at least one KPI and b) the CoordiNet contribution to these FOs

can be determined.

Table 3: Functional objectives addressed by CoordiNet

FO ID Functional Objectives

T5 Grid Observability

T9 Enhanced ancillary services for network operation

T10 Storage integration

T11 Demand response

T12 RES forecasting & optimal capacity operation

T13 Flexible grid use

T15 Market/grid integration

T16 Business models

T17 Flexible market design

T18 Big Data management

T19 Standardisation, protocols for communication and data exchange

D1 Active Demand Response

D3 System integration of small DER

D4 System integration of medium DER

D5 Integration of storage in network management

In order to collect KPIs used in other European projects that could be useful for CoordiNet, the KPIs of 11

on-going and completed European projects were analyzed. The reviewed European projects were UPGRID

(UPGRID, 2015), SmartNet (SmartNet, 2019), InterFLEX (InterFLEX, 2017), UTILITEE (UTILITEE, 2018),

FLEXCoop (FLEXCoop, 2018), HOLISDER (HOLISDER, 2018), evolvDSO (evolvDSO, 2014), EU-SysFlex (EU-

SysFlex, 2019), WiseGRID (WiseGRID, 2017), CROSSBOW (CROSSBOW, 2018) and Nobel Grid (NobelGrid,

2017). The collected KPIs were further reviewed to keep the most interesting KPIs for CoordiNet and some


GA 824414 Page 21 of 62

of them were adapted in order to fit better with CoordiNet needs. Finally, these KPIs were reviewed by

demo leaders in order to select the KPIs that address the objectives of their demos and which they are able

to calculate by means of the data that will be collected / generated. Moreover, new KPIs were defined by

the demo leaders to measure the impact of CoordiNet solutions and by the WP6 task leaders in order to

enable the comparison between the demonstration activities and perform an economic assessment.

3.2. KPIs definit ion

For the KPI definition the same template was used by all the demo leaders. This template was also used in

order to provide information on directly adopted KPIs from other projects and adapted KPIs. The information

needed for the optimal definition of KPIs is categorized and presented as follows:

KPI INFORMATION: The fields included in this category are the main characteristics of the indicator, all the

details for its calculation, its connection with other relevant European projects and its relation with the

BUCs.

1. Name: KPI name.

2. ID: KPI ID.

3. Strategic Objective(s): European energy policy targets addressed by KPI (Sustainability, Market

competitiveness and/or Security of supply).

4. Project Objective(s): The CoordiNet objectives (presented in Table 3) addressed by the KPI.

5. Description: A short description of the KPI, including a description of what the KPI measures and

for what it is used.

6. Formula: The formula to calculate the KPI and define all the variables.

7. Unit of measurement: KPI unit of measurement.

8. Link with other relevant projects KPI: Name of the project from which KPI was taken.

9. Related BUC(s): List the BUC(s) addressed through this KPI.

GENERAL COMMENTS: Describe any specific details surrounding this KPI or add any general comments

deemed necessary.

DATA INFORMATION: The fields included in this category are the main characteristics of the necessary data

that has to be collected during the demos in order to calculate the KPIs.

1. ID: Data ID.

2. Source/Tools/Instruments: Source/Tools/Instruments for data collection.

3. Location: Location of data collection.

4. Frequency: Required frequency of data collection.

5. Minimum monitoring period: Minimum required period of data collection.

6. Data collection responsible: Partner(s) responsible for data collection.


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Since this deliverable is being published at an early stage of the project, the necessary data could not yet

be defined at this stage. This information should be gathered in WP3-5. However, the relevant fields are

included in the template in order to present the information which should be collected in WP3-5. Therefore,

the fields about DATA INFORMATION will be filled out during the course of WP3-5.

Figure 7 shows the template used to define the KPIs and the data for their calculation

KPI INFROMATION

Name

ID

Strategic Objective(s)

Project Objective

Description

Formula

Unit of measurement

Link with other relevant

projects KPI

Related UC(s)

GENERAL COMMENTS

DATA COLLECTION

ID Source/Tools/Instruments Location Frequency Minimum monitoring

period

Data

collection

responsible

Figure 7: Template used for KPI definition

3.3. KPIs evolution

Based on the CoordiNet plan, the first step after the identification of the KPIs in WP1 is to define the

necessary data for the calculation of the KPIs in WP3-5. For the definition of the necessary data the

investigations in WP2 will be taken into account. Next, during the course of WP3-5, the data should be

gathered. It is of high importance, to gather all the information that is required for the calculation of the

KPIs during the demonstrations. Following the collection of data, some of the KPIs will be calculated in WP3-

5 to monitor the demos’ performance. The last step is the calculation of KPIs in WP6 in order to assess and

evaluate the demonstration campaigns’ results and perform an economic assessment in order to provide

recommendations for an adapted market design at EU level and needed policies to support this. The

aforementioned steps are illustrated in Figure 8.


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Figure 8: KPIs evolution

WP6WP3-5WP1

Calculate KPIs to assess and

evaluate results and

compare demonstration

activities

Calculate KPIs to monitor

demo performance

Collect necessary data

to calculate KPIs

Define dataneeded to

calculate KPIs

KPI identification


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4. List of CoordiNet KPIs

Following the methodology described in Section 1.3, 39 KPIs were identified. The details of the KPIs are

presented in Annex A. 19 KPIs fall into in the Specific KPIs categories, while 20 of them are Project KPIs. In

addition, KPIs are are mapped to the BUCs defined in D1.5 (CoordiNet, 2019) of the CoordiNet project. An

overview of the BUCs is presented in Figure 9 in order to facilitate the mapping of the KPIs to the BUCs for

the reader.

Figure 9: Overview of BUCs (CoordiNet, 2019)

It is observed that for each demonstration campaign, four different BUCs have been identified. The Spanish

demo (marked in red), targets to solve congestion, balancing, voltage and islanding issues. The Swedish

demo (marked in yellow) focuses on congestion in the distribution grid or between the transmission and

distribution grid and balancing, while in the Greek demo (marked in blue), two main grid services are of

high interest: voltage control and congestion management.

Table 4 shows the identified KPIs. In addition, the category (technical, economic, environmental, social) of

the KPIs as well as the mapping of the KPIs to the BUCs are presented in Table 4. Out of them, 26 technical,

8 economic, 3 social and 2 environmental KPIs were identified. Each BUC uses more than one KPI, while one

KPI can be used in more than one BUC. It is noted that more KPIs might need to be defined (especially

technical KPIs) in WP3-5 in case further services would be tested in the demonstrations, such as black start

and inertial response.

Table 4: List of identified KPIs

KPI ID KPI Name KPI Type KPI Category BUCs


Specific (A.2)

Economic ES-1

KPI_2

Estimation of the increment of reactive power flexibility for the network operators (TSO and DSO)

Specific (A.2)

Technical ES-3

KPI_3 Cost of R&I solution VS grid alternative solution

Specific (A.2)

Economic ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b


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KPI_4 OPEX - OPerational EXpenditures

Specific (A.2)

Economic ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b

KPI_5 OPEX for service procurement Specific (A.2)

Economic ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b, SE-2, SE-3


Specific (A.2)

Economic ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b, SE-2, SE-3

KPI_7 Increase RES and DER hosting capacity

Specific (B.1)

Technical ES-1, GR-2a, GR-2b

KPI_8 Reduction in RES curtailment Specific (B.2)

Environmental ES-1, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1b

KPI_9 Share of fossil-based activated energy

Specific (B.2)

Environmental ES-1


Specific (B.2)

Technical ES-1, ES-2, GR-1a, GR-1b, GR-2a, GR-2b


Specific (B.2)


KPI_12 Voltage variation Specific (B.3)

Technical ES-3, GR-1a, GR-1b

KPI_13 Criticalities Reduction Index Specific (B.3)

Technical ES-1

KPI_14 Islanding duration Specific (B.3)

Technical ES-4


Project Technical ES-4

KPI_16 Potential Offered flexibility Specific (B.5)



Specific (B.5)

Social ES-1, ES-2, GR-1a, GR-1b

KPI_18 Volume of transactions Specific (B.6)

Economic ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b, SE-2

KPI_19 Number of transactions Specific (B.6)


KPI_20 ΙCT cost Specific (B.8)




KPI_22 Requested flexibility Project Technical ES-1, ES-2

KPI_23 Data reliability ratio Project Technical GR-1a, GR-1b, GR-2a, GR-2b,

KPI_24 Accuracy of load forecast calculated 1 hour in advance

Project Technical GR-1a, GR-1b, GR-2a, GR-2b


Project Technical ES-1, ES-2, GR-1a, GR-1b, GR-2a, GR-2b

KPI_26 State estimation performance evaluation


KPI_27 Market utilization factor Project Technical SE-1a, SE-1b, SE-2

KPI_28 Increased grid connections Project Technical SE-1a


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KPI_30 Peak load demand reduction Project Technical ES-1

KPI_31 Total activation time of a product

Project Technical ES-1, ES-2, ES-3, ES-4

KPI_32 Delivered energy in controlled island


KPI_33 Maximum power (non-transient) in controlled island


KPI_34 Percentage of tested products per demo

Project Technical All the demos

KPI_35 Ratio of forwarded flexibility bids

Project Technical SE-1b

KPI_36 Participant recruitment Project Social ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b

KPI_37 Active participation Project Social ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, SE-1a, SE-1b

KPI_38 Type of flexibility providers per

demo Project Technical

ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b, SE-2, SE-3

KPI_39 Total Computational Runtime Project Technical ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b, GR-2a, GR-2b, SE-1a, SE-1b, SE-2

4.1. KPIs of Spanish demonstration BUCs

Table 5 presents the list of KPIs which will be used in the Spanish demonstration BUCs. The list consists of

20 technical, 8 economic, 2 environmental and 3 social KPIs (33 KPIs in total).

Table 5: KPIs of the Spanish demonstration BUCS



Specific (A.2)

Economic ES-1

KPI_2

Estimation of the increment of reactive power flexibility for the network operators (TSO and DSO)

Specific (A.2)

Technical ES-3


Specific (A.2)

Economic ES-1, ES-2, ES-3, ES-4


Specific (A.2)


KPI_5 OPEX for service procurement Specific

(A.2) Economic ES-1, ES-2, ES-3, ES-4


Specific (A.2)



Specific (B.1)

Technical ES-1


Environmental ES-1, ES-4


Specific (B.2)

Environmental ES-1, SE-1a, SE-1b


GA 824414 Page 27 of 62


Specific (B.2)

Technical ES-1, ES-2


Specific (B.2)



Technical ES-3

KPI_13 Criticalities Reduction Index Specific (B.3)

Technical ES-1

KPI_14 Islanding duration Specific (B.3)

Technical ES-4






Specific (B.5)

Social ES-1, ES-2









KPI_22 Requested flexibility Project Technical ES-1, ES-2

KPI_25 Accuracy of load forecast

calculated 24 hours in advance Project Technical ES-1, ES-2



KPI_30 Peak load demand reduction Project Technical ES-1

KPI_31 Total activation time of a product


KPI_32 Delivered energy in controlled island


KPI_33 Maximum power (non-transient) in controlled island




KPI_36 Participant recruitment Project Social ES-1, ES-2, ES-3, ES-4

KPI_37 Active participation Project Social ES-1, ES-2, ES-3, ES-4

KPI_38 Type of flexibility providers per demo


KPI_39 Total Computational Runtime Project Technical ES-1, ES-2, ES-3, ES-4


GA 824414 Page 28 of 62

4.2. KPIs of Swedish demonstration BUCs

Table 6 presents the list of KPIs which will be used in the Swedish demonstration BUCs. The list consists of

6 technical, 7 economic, 2 environmental and 1 social KPIs (16 KPIs in total).

Table 6: KPIs of the Swedish demonstration BUCS



Specific (A.2)

Economic SE-1a, SE-1b


Specific (A.2)

Economic SE-1a, SE-1b


Economic SE-1a, SE-1b, SE-2, SE-3


Specific (A.2)

Economic SE-1a, SE-1b, SE-2, SE-3


Environmental SE-1b


Specific (B.2)

Environmental SE-1a, SE-1b


Economic SE-1a, SE-1b, SE-2





KPI_27 Market utilization factor Project Technical SE-1a, SE-1b, SE-2

KPI_28 Increased grid connections Project Technical SE-1a



KPI_35 Ratio of forwarded flexibility bids

Project Technical SE-1b

KPI_37 Active participation Project Social SE-1a, SE-1b


Project Technical SE-1a, SE-1b, SE-2, SE-3

KPI_39 Total Computational Runtime Project Technical SE-1a, SE-1b, SE-2


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4.3. KPIs of Greek demonstration BUCs

Table 7 presents the list of KPIs which will be used in the Greek demonstration BUCs. The list consists of 12

technical, 7 economic, 1 environmental and 3 social KPIs (23 KPIs in total).

Table 7: KPIs of the Greek demonstration BUCS



Specific (A.2)

Economic GR-1a, GR-1b, GR-2a, GR-2b


Specific (A.2)





Specific (A.2)



Specific (B.1)

Technical GR-2a, GR-2b


Environmental GR-1a, GR-1b, GR-2a, GR-2b


Specific (B.2)

Technical GR-1a, GR-1b, GR-2a, GR-2b


Specific (B.2)



Technical GR-1a, GR-1b




Specific (B.5)

Social GR-1a, GR-1b







KPI_23 Data reliability ratio Project Technical GR-1a, GR-1b, GR-2a, GR-

2b,

KPI_24 Accuracy of load forecast calculated 1 hour in advance




KPI_26 State estimation performance evaluation




KPI_36 Participant recruitment Project Social GR-1a, GR-1b

KPI_37 Active participation Project Social GR-1a, GR-1b


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KPI_39 Total Computational Runtime Project Technical GR-1a, GR-1b, GR-2a, GR-2b


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5. Conclusions

This document presents the identified KPIs that will be used in order to:

• monitor demo performance,

• assess and evaluate the demonstration campaigns results,

• perform an economic assessment in WP6 in order to provide recommendations for an adapted

market design at EU level and needed policies to support this,

• evaluate the user and customer engagement plan followed by each demo.

The scope of this document is to define the KPIs and provide their calculation methodology. The EEGI

methodology was adopted for the KPI definition. The final list of KPIs consists of directly adopted KPIs from

relevant projects (11 European Projects were analyzed), adapted KPIs, which are adopted KPIs that were

modified in order to fit with CoordiNet needs and objectives, and new KPIs defined by CoordiNet.

A total of 39 KPIs have been identified in the CoordiNet project and can be classified as:

• Technical (26 KPIs), which evaluate the technical feasibility of the CoordiNet solutions.

• Economic (8 KPIs), which enable the CBA analysis of the CoordiNet solutions.

• Environmental (2 KPIs), which measure the environmental performance of CoordiNet solutions.

• Social (3 KPIs), which evaluate the customer engagement plan followed by the CoordiNet project.

This report aims at identifying the KPIs that will be used in the demonstration work packages (WP3-5) and

in WP6 that focuses on the assessment and evaluation of the demonstration campaigns results. However,

during the course of the project, further KPIs might need to be defined in WP3-5 according to the needs of

the demonstrations. For the calculation of the KPIs, the necessary data will be defined and collected in

WP3-WP5. For the definition of the necessary data the investigations in WP2 will be taken into account.


GA 824414 Page 32 of 62

6. References

CoordiNet. (2019). Deliverable D1.5: Business use case: Business use case definition.

CROSSBOW. (2018). Deliverable D2.2: CROSSBOW Use cases, scenarios and KPIs identification.

EEGI. (2013). European Electricity Grid Initiative Research and Innovation Roadmap 2013-2022.

ENTSO-E. (2016). Research innovation and development roadmap 2017–2026.

ETIP-SNET. (2016). Final 10-year ETIP SNET R&I roadmap covering 2017-26.

European Electricity Grid Initiative (EEGI). (n.d.). Retrieved from

https://www.edsoforsmartgrids.eu/policy/eu-steering-initiatives/eegi/

EU-SysFlex. (2019). Deliverable D10.1: Report on the selection of KPIs for the demonstrations.

evolvDSO. (2014). Deliverable D2.2: System Use Cases definition and functional and non-functional

requirements for tools and methods, and definition of KPIs.

FLEXCoop. (2018). Deliverable D2.5: FLEXCoop PMV Methodology Specifications – Preliminary Version.

GRID+. (2013). Deliverable D3.4: Define EEGI Project and Programme KPIs.

HOLISDER. (2018). Deliverable D2.2: HOLISDER PMV Methodology Specifications.

InterFLEX. (2017). Deliverable D2.2: Minimal set of use case KPIs and measurement methods to perform

the technical and economic analysis of the resulting definitions.

NobelGrid. (2017). Deliverable D13.2: Evaluation and technical validation Framework.

SmartNet. (2019). Deliverable D4.3: Cost-benefit analysis of the selected national case.

UPGRID. (2015). Deliverable D1.4 r2: Report on common KPIs.

UTILITEE. (2018). Deliverabl D1.3: Building Performance Rating Model and UtilitEE PMV.

WiseGRID. (2017). Deliverable D2.1: WiseGRID requirements, Use cases and pilot sites analysis.


GA 824414 Page 33 of 62

7. ANNEX A - KPIs

7.1. Specific KPIs

7.1.1. A.2 Increased system flexibility at acceptable cost

KPI INFORMATION

Name Cost of counteractions needed based on the activated flexibility

ID KPI_1

Strategic Objective(s) Sustainability, Competitiveness, Security of supply

Project Objective T9 Enhanced ancillary services for network operation T12 RES forecasting & optimal capacity operation T13 Flexible grid use T15 Market/grid integration T16 Business models T17 Flexible market design D9 Automation and control of MV network

Description Each coordination scheme considered in the CoordiNet project results in a different

market setup. Depending on the market setup adopted, the grid model included in

the market clearing process, which aims at solving and avoiding congestion and

voltage issues in the network, is more or less detailed. The simplifications adopted,

which allow a faster execution of the market clearing algorithm, may create

infeasibilities when dispatching units cleared in the market. This way, some bids

accepted in the market may create congestions or voltage violations not identified

by the grid model used. In this case, grid operators may need to take emergency

actions to re-dispatch some resources aiming to solve real congestions and voltage

violations in the grid. They can be caused by the partial activation of accepted bids

or by the activation of non-accepted bids (flexibility requested to be activated even

if the market did not select the related bid).

Formula

Costredispatch = ∑ ∑ Ei,tRd ∗ Pi,t

mFRR bid

I

n=1

T

t=1

Ei,tRd: Redispatched energy of ith flexible resource at time t (kWh)

Pi,tmFRR bid: Price of bids submitted to mFRR market of the ith flexible resource at

time t (€/kWh)

I: set of flexible resources.

T: examined period of time.

Unit of measurement €

Link with other relevant projects KPI SmartΝet

Related UC(s) ES-1

GENERAL COMMENTS

KPI DATA COLLECTION


GA 824414 Page 34 of 62

Data ID Source/Tools/Instruments Location of data

collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Estimation of the increment of reactive power flexibility for the network

operators (TSO and DSO)

ID KPI_2


Project Objective T9 Enhanced ancillary services for network operation T13 Flexible grid Use T15 Market/grid Integration T16 Business models T17 Flexible market design

Description The increment of reactive power regulation will depend on the technical features of

wind generators and electronic equipment, but also on the regulatory changes

allowing the provision of this service with the proposed market, to benefit from the

existing distribution grid flexibility.

Formula IRPF =

RPFR&I − RPFBaU

RPFBaU∙ 100

where,

RPF = ∑ Q ∙ ∆t

I

i=1

RPFBaU: Reactive power flexibility of Business as Usual scenario (kVArh).

RPFR&I: Reactive power flexibility of R&I scenario (kVArh).

Δt: examined period (h).

I: set of flexibility providers.

Q: Reactive power that is provided (kVAr).

Unit of measurement (%)

Link with other relevant projects KPI EU-SysFlex

Related BUC(s) ES-3

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


GA 824414 Page 35 of 62

KPI INFORMATION

Name Cost of R&I solution VS grid alternative solution

ID KPI_3


Project Objective T15 Market-grid integration

T16 Business models


Description Spanish and Greek demos: Compare CAPEX of CoordiNet solution with the

investment costs required to apply alternative solutions in an annual basis.

Sweden demo: Compare cost for flexibility with avoided exceeding subscription cost.

Formula Spanish and Greek demos:

Costvariation =CAPEXBAU − CAPEXR&I

CAPEXBAU∙ 100

CAPEXBAU: CAPEX of Business as Usual scenario (€)

CAPEXR&I: CAPEX of R&I scenario (€)

Swedish demo: Costvariation =Costflex

CostSub∙ 100

CostSub: Avoided exceeding subscription cost (€)

Costflex: Cost of flexibility (€)


Link with other relevant projects KPI -

Related BUC(s) ES-1, ES-2, ES-3, ES-4, SE-1a, SE-1b, GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name OPEX - OPerational EXpenditures

ID KPI_4



T16 Business models


Description This indicator calculates the recurrent costs that are required in order to operate

and maintain the installed equipment

Formula OPEXrecurrent_cost = ∑ ∑ recurrent_costi,t

IT

recurrent_costi: ith recurrent cost at time t (€).


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I: set of recurrent cost

T: examined period

Unit of measurement (€)


Related BUC(s) ES-1, ES-2, ES-3, ES-4, SE-1a, SE-1b, GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name OPEX for service procurement

ID KPI_5



T16 Business models


Description This indicator measures the cost for services procurement. The cost compromises

by the

Formula OPEXservie_procurement = ∑ ∑ PAS,i,tcPAS,i,t + EAS,i,tcEAS,i,t

IT

PAS,i,t: reserved capacity for ancillary services of ith flexi at time t (kW)

EAS,i,t: provided energy for ancillary services of ith unit at time t (kWh)

cPAS,i,t: cost of reserved capacity for ancillary services of ith unit at time t (€/kW)

cEAS,i,t: energy cost for ancillary services of ith unit at time t (€/kWh)

I: set flexible resources T: examined period


Link with other relevant projects KPI SmartNet

Related BUC(s) ES-1, ES-2, ES-3, ES-4, SE-1a, SE-1b, SE-2, SE-3, GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


GA 824414 Page 37 of 62

KPI INFORMATION

Name Average cost per service for the examined period

ID KPI_6


Project Objective T13 Flexible grid use

T15 Market-grid integration

T16 Business models


Description The indicator measures the average cost for providing ancillary services in the

different markets. This indicator is used to measure the average cos of the reserved

capacity and provided energy.

Formula 𝐶𝐴𝑆 =

∑ ∑ (𝑃𝐴𝑆,𝑖,𝑡𝑐𝑃𝐴𝑆,𝑖,𝑡)𝑇𝑡=1

𝐼𝑖=1

∑ (𝑃𝐴𝑆,𝑖,𝑡)𝛪𝜄=1

or

𝐶𝐴𝑆 =∑ ∑ (𝛦𝐴𝑆,𝑖,𝑡𝑐𝛦𝐴𝑆,𝑖,𝑡)

𝑇𝑡=1

𝐼𝑖=1

∑ (𝛦𝐴𝑆,𝑖,𝑡)𝛪𝜄=1

PAS,i,t: reserved capacity for service procurement of ith flexible resource at time t

(kW)

cPAS,i,t: cost of reserved capacity for service procurement of ith flexible resource at

time t (€/kW)

EAS,i,t: provided energy for service procurement of ith flexible resource at time t

(kWh)

cEAS,i,t: energy cost for service procurement of ith flexible resource at time t

(€/kWh)

I: set of flexible resources

T: examined period

Unit of measurement (€/kW or €/kWh)



GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


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7.1.2. B.1 Increased RES and DER hosting capacity

KPI INFORMATION

Name Increase RES and DER hosting capacity

ID KPI_7


Project Objective T9 Enhanced ancillary services for network operation


T11 Demand response, tools for using DSR, load profile, EV impact


D1 Active demand response

D3 DSO integration of small DER


Description This indicator measures the potential increase of hosting capacity for DERs with

Innovative grid services compared to the baseline situation where no “smart”

actions are performed on the network. The indicator gives a statement about the

additional DERs that can be installed in the network thanks to innovative grid

services without the need for conventional reinforcements (i.e. new grid lines).

Formula HC(%) =

HCR&I − HCBaU

HCBaU∙ 100

HCBaU: Hosting Capacity of Business as Usual scenario (kW).

HCR&I: Hosting Capacity of Research & Innovation scenario (kW).


Link with other relevant projects KPI Wisegrid

Related BUC(s) ES-1, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

7.1.3. B.2 Reduction in energy not supplied from DER

KPI INFORMATION

Name Reduction in RES curtailment

ID KPI_8


Project Objective T10 Storage integration, use of storage services




GA 824414 Page 39 of 62

T15 Market/grid operation integration





D8 Monitoring and control of LV networks

D9 Automation and control of MV network

Description This indicator measures the reduction in the amount of energy from Renewable

Energy Sources (RES) that is not injected to the grid (even though it is available) due

to operational limits of the grid, such as voltage violations or congestions

Formula RCRES =

CRES_BaU − CRE_R&I

CRES_BaU

∙ 100

where,

CRES = ∑ ∑(Pi,tprod

− Pi,tinj)

T

t=1

I

i=1

CRE_R&I: RES curtailment for the R&I scenario (kWh or MWh)

CRES_BaU: RES curtailment for the BaU scenario (kWh or MWh)

I: set of RES facilities under consideration.

T: set of time intervals of period under consideration excluding periods of scheduled maintenance and outages.

Pi,tprod

: available energy production of the ith RES facility at period t (kWh or MWh).

Pi,tinj

: injected energy of the ith RES facility at period t (kWh or MWh).



Related BUC(s) ES-1, ES-4, SE-1b, GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Share of fossil-based activated energy

ID KPI_9


Project Objective T9 Enhanced ancillary services for network operation T11 Demand response, tools for using DSR, load profile, EV impact T13 Flexible grid use T15 Market/grid operation integration D1 Active demand response


GA 824414 Page 40 of 62

Description This indicator measures the ratio of activated energy bids that are fossil-fuel based

with respect to the total amount of offered energy bids. Formula

∑fossil_act_bidst

total_energy_bidst∙ 100

T

fossil_act_bidst: fossil-fuel based activated energy bids at time t (kWh).

total_energy_bidst: total amount of offered energy bids at time t (kWh).

T: examined period



Related BUC(s) ES-1, SE-1a, SE-1b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Accuracy of the RES production forecast calculated 1 hour in advance

ID KPI_10


Project Objective T12 Improved RES forecasting and optimal capacity operation

T18 Big data management

D3 Integration of small DER

D11 Cybersecurity

Description This indicator measures the Normalized Mean Absolute Percentage Error (MAPE) of RES forecast in transmission and distribution system. Different KPIs will be calculated per production type (Wind, photovoltaic).

Formula

RES_FA_1h =|FC_RES_prod − RL_RES_prod

RL_RES_prod|

N ∙ RES_cap∙ 100

FC_RES_prod: RES production estimated 1h in advance (MW).

RL_RES_prod: Real RES production (MW).

N: Number of available data points.

RES_cap: Installed capacity of RES (MW).


Link with other relevant projects KPI Crossbow

Related BUC(s) ES-1, ES-2, GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS


GA 824414 Page 41 of 62

KPI DATA COLLECTION

Data ID Source/Tools/Instruments Location of

data collection

Frequency of

data collection

Minimum

monitoring

period

Data

collection

responsible

KPI INFORMATION

Name Accuracy of the RES production forecast calculated 24 hours in advance

ID KPI_11





D11 Cybersecurity

Description This indicator measures the Normalized Mean Absolute Percentage Error (MAPE) of RES forecast in transmission and distribution system. Different KPIs will be calculated per production type (Wind, photovoltaic).

Formula

RES_FA_24h =|FC_RES_prod − RL_RES_prod

RL_RES_prod|

N ∙ RES_cap∙ 100

FC_RES_prod: RES production estimated 24hrs in advance (MW).

RL_RES_prod: Real RES production (MW).


RES_cap: Installed capacity of RES.




GENERAL COMMENTS

KPI DATA COLLECTION

Data ID Source/Tools/Instruments Location of

data collection

Frequency of

data collection

Minimum

monitoring

period

Data

collection

responsible

7.1.4. B.3 Power quality and quality of supply

KPI INFORMATION

Name Voltage variation

ID KPI_12

Strategic Objective(s) Sustainability, Security of supply


GA 824414 Page 42 of 62


T10 Storage integration, use of storage services








D8 Monitoring and control of LV networks D9 Automation and control of MV network

Description This indicator measures the decrease in the deviation of the voltage on the network

nodes as a result of using market platform and products proposed by CoordiNet. As

a basis, the nominal voltage per node will be used.

Formula RδV =

δV_R&I − δV_BaU

δV_BaU

where,

δV =√∑ ∑ (Vn,t − Vn,nom)2N

n=1Tt=1

N ∙ T

δV_R&I: voltage deviation for the R&I scenario (%).

δV_BaU: voltage deviation for the BaU scenario (%).

T:examined period.

N: number of nodes under consideration.

Vn,t: voltage on node n at time period t (V or pu).

Vn,nom: nominal voltage on node n (V or pu).



Related BUC(s) ES-3, GR-1a, GR-1b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Criticalities Reduction Index

ID KPI_13


Project Objective T5 Grid observability T9 Enhanced ancillary services for network operation T13 Flexible grid Use


GA 824414 Page 43 of 62

T15 Market/grid Integration T16 Business models T17 Flexible market design

Description This indicator measures the reduction of the number of criticalities on the network

under consideration in terms of overvoltage and overcurrent.

Formula CRI =

Νcr_BaU − Νcr_R&I

Νcr_BaU∙ 100

Νcr_BaU: Number of criticalities when applying Business as Usual solution.

Νcr_R&I: Number of criticalities when applying R&I solution.


Link with other relevant projects KPI evolvDSO

Related BUC(s) ES-1

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Islanding duration

ID KPI_14







D8 Monitoring and control of LV network D9 Automation and control of MV network

Description Capacity of the energy system to switch to islanding whilst keeping the power quality

requirement and meeting the total demand of the island.

This indicator measures the capacity of an islanding to last as long as required. This

indicator is calculated as the relation (in %) between the duration of a single

islanding and the required duration of an islanding after an intentional or

unintentional disconnection from the grid.

Formula Icap =

∑ Disl,iNi=1

∑ Dreq,iNi=1

∙ 100

Disl,i: The duration of a single islanding (h).

Dreq,i: The required duration of an islanding, after an intentional or unintentional

disconnection from the grid (h).

N: Number of disconnections.



GA 824414 Page 44 of 62

Link with other relevant projects KPI InterFLEX

Related BUC(s) ES-4

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name TIEPI - Equivalent interruption time related to the installed capacity

ID KPI_15


Project Objective D8 Monitoring and control of LV network D9 Automation and control of MV network

Description The indicator measures the total amount of TIEPI avoided, measured in hours, as result of using market Platform and products proposed by CoordiNet.

Formula TIEPIi =

PIi x Hi

PItotal

PIi= Installed Power of the MV / LV secondary substations of the DSO plus the power

contracted in MV (KVA) affected by the interruption i.

Hi= Time of supply disruption that affects the power PIi (hours)

PItotal= Total power installed in the MV / LV secondary substations of the distributor

plus the power contracted in MT (KVA)

Unit of measurement (h)


Related BUC(s) ES-4

GENERAL COMMENTS

Other quality KPIs could be monitored e.g. SAIDI. (TIEPI is the KPI used by the Spanish regulator)

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


GA 824414 Page 45 of 62

7.1.5. B.5 Increased flexibility from energy players

KPI INFORMATION

Name Potential Offered flexibility

ID KPI_16


Project Objective T9 Enhanced ancillary services for network operation T13 Flexible grid use D8 Monitoring and control of LV network

Description This indicator measures the potential offered flexibility. This is the potential amount

of flexibility that all flexible resources of the portfolio are able to offer to the market

platform.

Formula FlexPO = ∑ ∑ P_flexPOi,t

T

t=1

I

i=1

or

FlexPO = ∑ ∑ E_flexPOi,t

T

t=1

I

i=1

P_flexPOi,t: Τhe amount of power send from the ith flexible resource at time t to offer

flexibility for sale. It contains the potential flexibility that is available to market

platform (kW).

E_flexPOi,t Τhe amount of energy send from the ith flexible resource at time t to

market platform to offer flexibility for sale. It contains the potential flexibility that is

available to market platform (kWh).

I: set of flexible resources.

T: examined period.

Unit of measurement (kW or kWh)

Link with other relevant projects KPI UtilitEE


GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Increase in the amount of load capacity participating in DR

ID KPI_17



GA 824414 Page 46 of 62






D8 Monitoring and control of LV network


Description This indicator measures the increase in the amount of load that participate in

demand response in order to offer flexibility to system operators as a result of using

market platform and products proposed by CoordiNet.

Formula ILCP =

LCPR&I − LCPBau

LCPBau

where,

LCP =∑ ∑ Pi,t

DRTt=1

Ii=1

∑ ∑ Pi,tTt=1

Ii=1

∙ 100

LCPR&I: Load capacity participation for the R&I scenario (%).

LCPBaU: Load capacity participation for the BaU scenario %).

I: set of loads participate in demand response

T: set of time intervals of period under consideration

Pi,tDR: Amount of power capacity of the ith load at period t that participate in demand

response (kW).

Pi,t: Consumption of the ith load at period t (kW).



Related BUC(s) ES-1, ES-2, GR-1a, GR-1b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

7.1.6. B.6 Improved competitiveness pf the electricity market

KPI INFORMATION

Name Volume of transactions

ID KPI_18

Strategic Objective(s) Sustainability, Competitiveness



T16 Business models


GA 824414 Page 47 of 62


Description This indicator measures the volume of transactions in kW or kWh depending on the service that is provided. This indicator will be used in order to measure the volume of offered and cleared bids for each service.

Formula ∑ ∑ Pi,t

IT

or

∑ ∑ Ei,t

IT

Pi,t: volume of offered or cleared capacity by the ith flexible resource at time t (kW)

Ei,t: volume of offered or cleared energy by the ith flexible resource at time t (kWh)

I: set of flexible resources

T: examined period

Unit of measurement (kW/kWh)


Related BUC(s) ES-1, ES-2, ES-3, ES-4, SE-1a, SE-1b, SE-2, GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Number of transactions

ID KPI_19




T16 Business models


Description This indicator measures the number of transactions. This indicator will be used in order to measure the number of offered and cleared bids for each service.

Formula ∑ nBids,t

T

nBids: Number of offered or cleared bids at time t (kW or kWh)

T: examined period

Unit of measurement -




GA 824414 Page 48 of 62

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

7.1.7. B.8 Reduce CAPEX and OPEX of ICT infrastructures

KPI INFORMATION

Name ΙCT cost

ID KPI_20


Project Objective T9 Grid Observability


Description The term ICT cost comprises the communications and information technologies,

including the software for the aggregation and market clearing process. Only those

ICT costs that are directly related to the implementation of each coordination

scheme will be considered.

Formula ICTcost =Summation of ICT costs that are directly related to the implementation of

each coordination scheme




GENERAL COMMENTS

The term implementation is used to refer to the work in designing, specifying, coding, testing, validating and documenting

software.

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


GA 824414 Page 49 of 62

7.2. Project KPIs

KPI INFORMATION

Name Deviation between accepted and actual activated mFRR

ID KPI_21


Project Objective T9 Enhanced ancillary services for network operation T13 Flexible grid use T15 Market/grid integration T16 Business models T17 Flexible market design D8 Monitoring and control of LV network D9 Automation and control of MV network

Description This term also refers to deviations between market activations (mFRR) and actual

activations, but in this case, they are not due to limitations in the grid models used,

but because the requested flexibility cannot be physically activated due to either

flexibility modelling errors and/or flexibility forecasting errors. They can be caused

by the partial activation of accepted bids or by the activation of non-accepted bids

(flexibility requested to be activated even if the market did not select the related

bid).

Formula δΕ = Ei,tActual − Ei,t

mFRR

Ei,tActual: Actual activated energy of the ith flexible resource at time t (kWh).

Ei,tmFRR: Market activated activation of the ith flexible resource at time t (kWh).

For each period, t, the positive values will be added on one hand, and the negative

values will be added on the other hand

Unit of measurement kWh


Related BUC(s) ES-2

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Requested flexibility

ID KPI_22



GA 824414 Page 50 of 62

Project Objective T9 Enhanced ancillary services for network operation T13 Flexible grid use T15 Market/grid integration T16 Business models T17 Flexible market design D8 Monitoring and control of LV network D9 Automation and control of MV network

Description This indicator measures the amount of flexibility requested by the Platform for

ancillary services from all the flexible resources of the portfolio.

Formula FlexR = ∑ P_flex𝑅t

T

or

FlexR = ∑ E_flex𝑅t

T

P_flex𝑅t : Τhe amount of power requested by the market Platform for ancillary

services at time t (kW).

E_flex𝑅t : Τhe amount of energy requested by the market Platform for ancillary

services at time t (kWh).

T: examined period.

Unit of measurement (kW or kWh)

Link with other relevant projects KPI UtilitEE

Related BUC(s) ES-1, ES-2

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFROMATION

Name Data reliability ratio

ID KPI_23


Project Objective T18 Big data management T19 Standardization protocols for communication D11 Cybersecurity

Description This indicator calculates the percentage of reliable data according to all the data received in the examined period

Formula DRR = ∑nreliable

nreceivedT

∙ 100

nreliable: amount of reliable data that received over period T.

nreceived: amount of data that received over period T.


GA 824414 Page 51 of 62

T: examined period.



Related BUC(s) GR-1a, GR-1b, GR-2a, GR-2b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Accuracy of load forecast calculated 1 hour in advance

ID KPI_24





D11 Cybersecurity

Description This indicator measures the Mean Absolute Percentage Error (MAPE) of the load forecast in transmission and distribution system

Formula

Load_FA_1h =|FC_load − RL_load

RL_load |

N∙ 100

FC_load: Load estimated 1h in advance (MW).

RL_load: Real load (MW).





GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data

collection

responsible


GA 824414 Page 52 of 62

KPI INFORMATION

Name Accuracy of load forecast calculated 24 hours in advance

ID KPI_25


Project Objective T11 Demand response, tools for using DSR, load profile, EV impact



D11 Cybersecurity

Description This indicator measures the Mean Absolute Percentage Error (MAPE) of the load forecast in transmission and distribution system

Formula

Load_FC_accuracy_24hrs =|FC_load − RL_load

RL_load |

N∙ 100

FC_load: Load estimated 24hrs in advance (MW).

RL_load: Real load (MW).

N: Number of available data points




GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data

collection

responsible

KPI INFORMATION

Name State estimation performance evaluation

ID KPI_26


Project Objective T5 Grid observability T18 Big data management D11 Cybersecurity

Description This indicator consists of three sub-indicators: 1) The first sub-indicator will measure the Mean Absolute Error (MAE), the Root Mean Squared Error (RMSE) and the Maximum Error (ME) between the true (or the measured) and the estimated system state. 2) The second sub-indicator will measure the Autocorrelation Function (ACF) to evaluate the properties of a time series, which in this case is the estimated system state. It is, therefore, necessary to verify whether the residuals yt − yt−1 are non-correlated, where yt is the estimated system state at time-step t. If the residuals are

non-correlated, the ACF should be within the noise margins ±1.96/√Ns with 95% of

probability, where Ns is the total number of time-steps. The ACF is plotted for the

first ~√Ns lags.


GA 824414 Page 53 of 62

3) The third sub-indicator will measure the Refresh Rate (RR) of the state estimation process.

Formula Mean Absolute Error (MAE) between true (or measured) and estimated system state:

MAE =∑ |et|

Nst=1

Ns

Root Mean Squared Error (RMSE) between true (or measured) and estimated system state:

RMSE = √∑ et

2Nst=1

Ns

Maximum Error (ME) between true (or measured) and estimated system state: ME = max{et,1, … , et,nb

}

Autocorrelation Function (ACF):

ACF = γ(h)

γ(0)

𝛾(ℎ): auto covariance function:

γ(h) = Cov(Xt+h, Xt )

Refresh Rate (RR) is the difference between two consecutive time-steps, during which the system state is estimated.

RR = ti − ti−1

et: estimation error at time-step t (et = yt − yt)

yt: true (or measured) system state at time-step t yt: estimated system state at time-step t

Ns: number of time-steps

nb: number of electrical network buses Xt: stationary time series (estimated system state) h: 1, 2, 3, etc. (defines the time-steps back in the past)

Unit of measurement 1) Depending on the definition of the system state (i.e., if it is in polar or in rectangular coordinates), it can be:

• V (Volt) or p.u. (per unit) for the voltage magnitude and rad (radians) for the voltage phase,

• V (Volt) or p.u. (per unit) for the real and imaginary part of the voltage. 2) For any stationary process, γ(h) is bounded between -1 and 1. 3) min, s or ms



GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data

collection

responsible


GA 824414 Page 54 of 62

KPI INFORMATION

Name Market utilization factor

ID KPI_27

Strategic Objective(s) Sustainability, Security of supply, Competitiveness

Project Objective T9 Enhanced ancillary services for network operation T13 Flexible grid Use T15 Market/grid Integration T16 Business models T17 Flexible market design

Description Calculation of the number of times that the market is being used annually.

Formula MUF: Number of times of market utiliaztion over the examined period of time

Unit of measurement (-)


Related BUC(s) SE-1a, SE-1b, SE-2

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Increased grid connections

ID KPI_28

Strategic Objective(s) Security of supply, Competitiveness


Description This indicator measures the ratio of increased grid connections

Formula IGC =

FCIGC

SL∙ 100

FCIGC: Feasible connection of increased grid connections (MW)

SL: Subscription level (MW)



Related BUC(s) SE-1a


GA 824414 Page 55 of 62

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Capacity increase with reactive management

ID KPI_29


Project Objective D12 New planning approaches and tools

Description The indicator measures the percentage difference, or in other words percentage increase, in Capacity (Apparent Power) as result of using market Platform and products proposed by CoordiNet.

Formula ΔCap =

CapR&I − CapBaU

CapBaU

CapBaU: Apparent power capacity of Business as Usual scenario (MVA)

CapR&I: Apparent power capacity of R&I scenario (MVA)



Related BUC(s) ES-3

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Peak load demand reduction

ID KPI_30


Project Objective T9 Enhanced ancillary services for network operation T10 Storage integration T11 Demand response D1 Active Demand Response

Description This indicator measures the maximum percentage decrease of peak load demand in an area by a flexibility provider resource.


GA 824414 Page 56 of 62

Formula ΔPeakLoad =

PeakLoadBaU − PeakLoadR&I

PeakLoadBaU

PeakLoadBaU: Peak load of Business as Usual scenario (MW)

PeakLoadR&I: Peak load of R&I scenario (MW)



Related BUC(s) ES-1

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Total activation time of a product

ID KPI_31


Project Objective D3 DSO integration of small DER

D4 System integration of DER

Description The indicator measures the total time of product activation. It will allow knowing the use of a product.

Formula Total_act = ∑ t_actn

N

t_actn: duration of nth product activation (h).

N: Times of activation.

Unit of measurement (h)


Related BUC(s) ES-1, ES-2, ES-3, ES-4

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Delivered energy in controlled island

ID KPI_32


GA 824414 Page 57 of 62





Description The indicator measures the total energy supplied to the island. It is calculated as the sum of the net energy supplied by the Flexibility Service Provider (FSP) and the net energy supplied by other generators. • The net energy provided by the FSP shows if the island lasted as

requested. • The net energy provided by other generators shows the increase in

generation availability (in case of an outage). Formula Eisl = EFSP + Egen

EFSP= Energy provided by the FSP during the island (kWh).

Egen= Energy provided by other generators connected in the island (kWh). Unit of measurement (kWh)


Related BUC(s) ES-4

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Maximum power (non-transient) in controlled island

ID KPI_33





Description The indicator measures the maximum power of the island, ignoring transients. This could be used to assess to which extent the service allows to create the island depending not only in FSP but in other generation. The indicator is equal to the maximum of the sum of power provided by the FSP and other generators.

Formula Pmax,isl = max(PFSP + Pgen)

PFSP= Power injected to the grid by the FSP (kW).

Pgen= Power produced by other generators connected in the island (kW).

Unit of measurement (kW)


GA 824414 Page 58 of 62


Related BUC(s) ES-4

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Percentage of tested products per demo

ID KPI_34

Strategic Objective(s) Sustainability, Security of supply, Competitiveness



T16 Business models T17 Flexible market design

Description This indicator measures the percentage of products tested in the demos with respect

to the number of products initially targeted by the demos.

Formula NPD =

nPtested

nPtargeted∙ 100

nPtested: Number of products tested in the demos.

nPtargeted: Number of products initially targeted by the demos.



Related BUC(s) This indicator will be calculated for each demo.

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Ratio of forwarded flexibility bids

ID KPI_35


GA 824414 Page 59 of 62

Strategic Objective(s) Security of supply, Competitiveness


Description This indicator measures the ratio of flexibility bids forwarded from a LV DSO market

to a MV DSO market and the ratio of flexibility bids forwarded from HV DSO market

to the balancing market

Formula FBF =

Bidsforwarded

Bidstotal

∙ 100

Bidsforwarded: Volume of bids forwarded from a LV DSO (HV DSO) market to a MV

DSO (Balancing) market (MWh)

Bidstotal: Volume of bids in LV DSO (HV DSO) market (MWh)



Related BUC(s) SE-1b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Participant recruitment

ID KPI_36


Project Objective T5 Grid observability

T9 Enhance ancillary services for network operation

T11 Demand response





Description This indicator calculates the percentage of customers accepted their participation in

the demo in relation with the total amount of customers contacted to participate in

the demo. This indicator will be used to evaluate customer engagement plan.

Formula R =

Naccept

Ntotal∙ 100

Naccept: customers participate in the demo.

Ntotal: customers contacted to participate in the demo.



GA 824414 Page 60 of 62

Link with other relevant projects KPI UPGRID

Related BUC(s) ES-1, ES-2, ES-3, ES-4, GR-1a, GR-1b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

KPI INFORMATION

Name Active participation

ID KPI_37


Project Objective T5 Grid observability

T9 Enhance ancillary services for network operation

T11 Demand response





Description This indicator measures the percentage of customers actively participating in the CoordiNet demo with respect to the total customers that accepted the participation. This indicator will be used to evaluate customer engagement plan.

Formula R =

Nactive

Naccept∙ 100

Nactive: customers actively participating in the demo

Naccept: customers accepted to participate in the demo.


Link with other relevant projects KPI UPGRID

Related BUC(s) ES-1, ES-2, ES-3, ES-4, SE-1a, SE-1b, GR-1a, GR-1b

GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


GA 824414 Page 61 of 62

KPI INFORMATION

Name Type of flexibility providers per demo

ID KPI_38


Project Objective T9 Enhanced ancillary services





D3 System integration of small DER

D4 System integration of medium DER


Description This indicator reflects how versatile the demos are in leveraging flexibility from different technologies. The demos aspire to make use of flexibility from different technologies. If and how different types of technologies can actually be accessed and utilized during the demo phase depends on the number of different technologies that are available in the region of the demos as well as on the general capabilities of the demo. This KPI is measured as the relation (in %) between the number of different technologies leveraged in the demo and the number of types of technologies initially targeted by the demo. The following technologies will be considered for the KPI calculation: • Renewables • Conventional generators connected to the distribution system • Conventional generators connected to the transmission system • Aggregators • Consumers • Storage • Gensets • Electrical vehicles

Formula TFP =

Nleverage_technology

Ntarget_technology∙ 100

Nleverage_technology: Number of different type of technologies utilized during the

demo.

Ntarget_technology: Number of different type of technologies available in the region of

the demo.




GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible


GA 824414 Page 62 of 62

KPI INFORMATION

Name Total Computational Runtime

ID KPI_39




Description This indicator measures the execution time of market clearance under different coordination schemes.

Formula RT = Tfinal − Tinitial

or

∆RT = 100(RTreference − RTCS)/RTreference

Tinitial: time at the end of running the algorithm (s)

Tfinal: time at the beginning of running the algorithm (s)

RTreference: Running time of reference algorithm (s)

RTCS: Running time of Coordination Scheme algorithm (s)

Unit of measurement (s) or (%)

Link with other relevant projects KPI evolvDSO


GENERAL COMMENTS

KPI DATA COLLECTION


collection

Frequency of

data collection

Minimum

monitoring

period

Data collection

responsible

Deliverable D1.6 List of KPIs: KPI and process of measures

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