der modelling - coordinet project

Deliverable D1.4

DER Modelling

V3.2

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

D1.4 – DER Modelling V3.2

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D1.4 – DER Modelling

Document Information

Programme Horizon 2020 – Cooperation / Energy

Project acronym Coordinet

Grant agreement number 824414

Number of the Deliverable D1.4

WP/Task related WP1 / T1.4

Type (distribution level) PU Public

Date of delivery [28/08/2019]

Status and Version Version 3.2

Number of pages 108 pages

Document Responsible Miguel Marroquin – Our New Energy

Author(s) Miguel Marroquin – Our New Energy

Pepi Jimenez – Our New Energy

Carlos Madina – Tecnalia

Maider Santos – Tecnalia

Inés Gomez – Tecnalia

Reviewers Dimitris Trakas – ICCS / NTUA

Christos Kaskouras – IPTO

Fernando David Martin Utrilla – Iberdrola

Santiago Otero Peña - Enel

Jose Pablo Chaves - Comillas


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Revision History

Version Date Author/Reviewer Notes

0.4 15/07/2019 Our New Energy

0.5 15/07/2019 Tecnalia

1.0 21/7/2019 Our New Energy Preliminary version sent for first feedback

1.5 25/8/2019 Our New Energy Intermediate version (internal ONE)

1.9 26/8/2019 Our New Energy Version sent for review

2.0 27/8/2019 Our New Energy Version for review

2.5 3/9/2019 Our New Energy Version following review

2.7 10/9/2019 Our New Energy Following last comments from Comillas and Enel. Sent to Tecnalia

3.0 19/9/2019 Our New Energy / Tecnalia Final version for submission to Executive Board

3.2 14/10/2019 Our New Energy / Tecnalia Final version after last review by Comillas and IPTO


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Acknowledgments

Partner Name

Our New Energy (ONE) Miguel Marroquín

Our New Energy (ONE) Pepi Jiménez

Tecnalia Carlos Madina

Tecnalia Ines Gómez

Tecnalia Joseba Jimeno

Tecnalia Iker Marino

Tecnalia Maider Santos

VITO/Energyville Kris Kessels

VITO/Energyville Enrique Rivero Puente

Comillas / Universidad Pontificia José Pablo Chaves Ávila


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Executive summary

This deliverable aims to analyse, characterise and quantify the feasible potential flexibility from DERs (Distributed Energy Resources) in order to identify and quantitatively assess what can be expected from the different market participants, and to test the capacities of the selected DERs during the demonstration experiences.

The document investigates the main processes (heating, ventilation, air-conditioning, lighting, cooling,

motors, specific process, others...,) within the major industries, as well as in the residential and tertiary sectors, as well as generation and storage facilities.

The links and interactions of this deliverable with the other WPs are presented in Figure 1 that shows the inter-relation of WP1 deliverables with the other WPs. As shown in Figure 1, the work in Task 1.4 (described in this deliverable) is part of Work Package 1 and is also tightly related to Task 1.2: "Ex-ante consumer engagement".

On the other hand, the two tasks described above are central to the demonstration preparation phase and the engagement activities for the three demonstration countries, Greece, Spain and Sweden.

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

Figure 2 below summarises the procedure followed to derive a qualification of the expected response by the different types of DER and an indicative estimation of the amount of flexibility that could be available in a 2030-scenario from these sorts of assets.

The process starts with a thorough understanding of the current electricity consumption in Europe in 3 main clusters: industry, tertiary sector and households. These three clusters are similar in size, although they present different patterns in evolution and flexibility. The analysis mainly focuses on the industrial sector, by dividing the data in the main industry families which share processes and flexibility patterns.


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Figure 2: Structure of the D1.4 document and methodology

Two different consumption and generation scenarios were created for 2030. For that purpose, 2017 data

were used and taken one and a half decade forward, by assuming two different alternatives:

- The ‘as-is’ scenario analyses and treats the data from the Business-As-Usual (BAU) point of view, in which it tries to estimate the situation in 2030, by assuming an evolution of the European electricity system without relevant structural changes.

- The ‘green’ scenario analyses and treats data from a more efficient and renewable point of view. It is the scenario that reflects a positive evolution towards sustainable responsibility and decarbonisation of the industry from various perspectives.

Once the scenarios were created, two parallel analyses were run:

- On the one hand, the processes within each major industry type, as well as in the household and tertiary sectors, were qualified, in order to dig deeper into the actual mix of processes and flexibilities that could be exploited behind the consumer branch. Storage (also under the form of deployment of electric vehicles) was treated in a specific analysis.

- On the other hand, the suitability of each of these sorts of flexibility types to the array of system

services we aim to investigate was discussed and analysed.

As a result, of these analyses, the ‘plausibility’ that a given DER (being a consumption process or distributed generator) could make its consumption / generation flexible was assessed, which is the basis for the provision of system services. Such plausibility was calculated by weighting the score of DER’s processes on 4 different aspects, namely: suitability, comfort, size and granularity.


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Such score shall represent the likelihood of displacing a constant share of the annual load of these different DERs. However, it is not in the scope of this document to attempt to quantify the actual amount of response, either in capacity (MWs) or in energy (MWh). On the contrary, this methodology and the results from this report shall be used in contrasting the actual findings from field experiences, such as the ones covered in CoordiNet under WP3, 4 and 5.

This deliverable also discusses the difference between estimating DER reserves and resources. DER resources relate to the total amount of flexibility that exists in the system, whereas DER reserves refer to those resources which are exploitable from a techno-economic point of view, under a given construction of market design, incentives and prices.

It is hard to estimate the different levels of incentive required by a large variety of independent, non-energy-market-expert, disconnected parties (such as large portfolios of DERs) to react in the way that could be useful for system service purposes. Instead, it was assumed that DERs have enough economic incentives so that their participation is marginally competitive against other sources of response available in the market. Therefore, the work described in this deliverable focused on the estimation of DER resources.

Concerning the capabilities of DERs to provide future system services, the report presents and explains the reasons why specific technologies are best for specific system services. For instance, the best resources to provide frequency control services are the storage systems, which have higher performances and fewer constraints than other types of resources. Combined heat and power (CHPs) and industrial shiftable loads show high performances, due to their thermal storage systems and the good monitoring and control (industrial processes) strategies.

Wind turbines, photovoltaics and curtailable loads are quite widespread, but show lower performance for long-duration ancillary services due to lower predictability. On the contrary, the shiftable loads (from tertiary sector or wet appliances in household) are more suitable for long-time horizon, due to the latency of the response. Regarding thermostatically controlled loads (TCLs), they can provide quite good capabilities from fast responses (e.g. frequency containment reserves) to longer duration (such as frequency restoration reserves or even replacement reserves in some cases), which is linked to the thermal inertia. In general, loads are not well-suited for voltage control services, as it is difficult to change their reactive power output and consumption.

On the other hand, with part of the obtained information, a questionnaire was elaborated to understand the willingness of different industries and generators to participate in the market for ancillary services, considering both current and future aspects, barriers and catalysts. Out of the 19 prospective surveys, 7 completed forms have been received (see sections 6 and 8.5). From the answers to the questionnaire, the following conclusions can be drawn:

A large number of respondents agree that there is dormant ability to make their consumption flexible for the provision of system services. However, when asked about the number of business interruptions, the aversion towards discomfort is noticeable, as respondents could only agree to a limited number of activations.

Some industries confirm their current participation in the primary and tertiary reserves. Through

another participant we know that energy storage systems typically provide frequency containment reserves (FCR), frequency restoration reserves (FRR) and replacement reserves (RR), depending on whether these services are offered in the market and eligibility.

One of the barriers that the interviewees name more frequently for not providing this service is the current legislation (regulation). Most of the interviewees also indicate that they are willing to participate in system services directly or indirectly via upstream aggregators.


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Table of contents

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

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

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

List of figures ................................................................................................................. 10

List of tables .................................................................................................................. 11

Notations, abbreviations and acronyms ................................................................................. 12

1. Introduction ............................................................................................................. 14

1.1. The CoordiNet project .......................................................................................... 14

1.2. Scope of the document ......................................................................................... 15

1.3. Structure .......................................................................................................... 15

2. Data Collection ......................................................................................................... 16

3. Characteristics of the DERs ........................................................................................... 18

3.1. Demand Response (Consumers) ............................................................................... 18

3.1.1. Industry ........................................................................................................ 19

3.1.2. Tertiary......................................................................................................... 21

3.1.3. Households ..................................................................................................... 21

3.2. Distributed Generation ......................................................................................... 21

3.3. DER technologies characterization ........................................................................... 22

3.3.1. Conventional Fossil Fuelled Technologies ................................................................ 23

3.3.2. Variable Renewable Energy Sources ...................................................................... 24

3.3.3. Energy storage systems ...................................................................................... 26

3.3.4. Electric vehicles .............................................................................................. 30

3.4. Qualitative analysis ......................................................................................... 32

4. Characterisation DER capabilities ................................................................................... 35

5. Quantification of feasible flexibility potential from DERs ...................................................... 41

5.1. Methodology ...................................................................................................... 41

5.2. Generation ........................................................................................................ 42

5.3. Industry............................................................................................................ 42

5.4. Tertiary and household sectors ............................................................................... 44

5.5. Quantitative Analysis ........................................................................................... 45

5.6. Additional considerations ...................................................................................... 50

6. Stakeholder interviews ................................................................................................ 51

7. Conclusions .............................................................................................................. 53

8. Annexes .................................................................................................................. 55

8.1. Analysis of Selected EU Projects .............................................................................. 55

8.1.1. Remodece Project ............................................................................................ 55

8.1.2. GIFT project ................................................................................................... 55

8.1.3. NatConsumers project ....................................................................................... 56

8.1.4. IndustRE project .............................................................................................. 56

8.1.5. GOFLEX project ............................................................................................... 57

8.1.6. Flexiciency project ........................................................................................... 58


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8.1.7. Pentagon project ............................................................................................. 58

8.1.8. MAGNITUDE project .......................................................................................... 58

8.1.9. SmartNet project ............................................................................................. 59

8.2. Selected industry details ....................................................................................... 60

8.2.1. Iron and Steel ................................................................................................. 60

8.2.2. Chemical and Petrochemical ............................................................................... 60

8.2.3. Machinery ...................................................................................................... 61

8.3. Analysis of barriers to market participation and needs .................................................. 61

8.3.1. Barriers ......................................................................................................... 61

8.3.2. Policy ........................................................................................................... 63

8.3.3. Good practices ................................................................................................ 65

8.3.4. Volume of batteries .......................................................................................... 67

8.4. Questionnaire .................................................................................................... 71

8.4.1. Objective and instruction of the Questionnaire ........................................................ 71

8.4.2. Introduction ................................................................................................... 71

8.4.3. Definitions ..................................................................................................... 73

8.4.4. Products for grid services ................................................................................... 73

8.4.5. Data Protection ............................................................................................... 81

8.4.6. Questionnaire - Document .................................................................................. 82

8.5. Replies received on the questionnaire ...................................................................... 86

9. References ............................................................................................................. 103


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List of figures

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

Figure 2: Structure of the D1.4 document and methodology ..........................................................6

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) ................................................................................................ 14

Figure 4: Final electricity consumption 2017 by sectors (Eurostat, n.d.) ..................................... 18

Figure 5: Business as usual projections of final energy consumption through 2050 for EU ..................... 20

Figure 6: Services that batteries can provide to three stakeholders (Garrett Fitzgerald et al., 2015). 27

Figure 7: Storage installed capacity on distribution networks by primary use case (CIGRE WG C6.30 and

WG C6.30, 2018) ............................................................................................................ 30

Figure 8: Capabilities of DERs to provide future system services (Julien Le Bault et al., 2017) ......... 34

Figure 9: Breakdown of the Tertiary sector consumption for EU (Paolo Bertoldi and Bogdan Atanasiu,

2009) .......................................................................................................................... 38

Figure 10: Breakdown of Households sector consumption for EU (Paolo Bertoldi and Bogdan Atanasiu,

2009) .......................................................................................................................... 38

Figure 11: Composition of consumption in 2030 in main process clusters .................................... 40

Figure 12:Treemap of cumulated score on the demand side by consumer segment ............................ 49

Figure 13: Treemap of cumulated score on the demand side by related process ............................... 50

Figure 14: Storage capacity by country (own elaboration with data from (Department of Energy - USA,

2019). ......................................................................................................................... 68

Figure 15: Battery storage capacity in MW by technology (own elaboration with data from (Department

of Energy - USA, 2019). ................................................................................................... 69


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List of tables

Table 1: Acronyms list ...................................................................................................... 12

Table 2: Electricity consumption details by different sectors and scenarios ..................................... 19

Table 3: Economic and technical saving potential of industrial final energy consumption in 2030 .......... 20

Table 4: Estimate production mix for two different scenarios in 2030 (FTI Consulting LLP, 2018), (Eurostat,

2019) ........................................................................................................................... 21

Table 5: Summary of 2030 expected energies in two scenarios ..................................................... 36

Table 6: Process examples in selected consumer segments ......................................................... 37

Table 7: Estimated consumptions by use in the main sectors (own elaboration) ................................ 39

Table 8: Estimated consumptions in two different scenarios for 2030 by the main types of consumers .... 40

Table 9: Suitability for the provision of different flexibility methods from different clusters ................ 44

Table 10: Proposed scoring of DERs according to their suitability .................................................. 47

Table 11: Proposed scoring of DERs according to their level of comfort .......................................... 47

Table 12: Proposed scoring of DERs according to their size ......................................................... 48

Table 13: Proposed scoring of DERs according to their granularity ................................................. 48

Table 14: Total score of DERs according to their proposed weighting formula .................................. 49

Table 15: Total score of DERs according to their proposed weighting formula .................................. 54


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Notations, abbreviations and acronyms

Table 1: Acronyms list

Acronym Description

aFRR Automatic Frequency Restoration Reserves

BAU Business as Usual

BESS Battery Energy Storage System

BEV Battery electric vehicles

CAES Compressed-air Energy Storage

CAGR Constant Annual Growth Rate

CCGT Combined Cycle Gas Turbines

DER Distributed Energy Resources

DRES Distributed Renewable Energy Sources

DSO Distribution System Operator

EDSO European Distribution System Operators for Smart Grids

ENTSO-E European Network of Transmission System Operators for Electricity

EU European Union

EUROFER The European Steel Association

EUROSTAT Statistical office of the European Union

EV Electric Vehicle

FC Fuel Cells

FCR Frequency Containment Reserves

FRCI Fast Reactive Current Injection

FFR Fast Frequency Response

FORATOM The European Atomic Forum

G2V Grid-to-vehicle

GA Grant Agreement

GDP Gross Domestic Product

GT Gas Turbine

HVAC Heating, Ventilation and Air Conditioning

ICE Internal Combustion Engine

LAES Liquid-air Energy Storage

LOLE Loss of Load Expectation

LV Low Voltage

LVRT Low Voltage Ride Through

mFRR Manual Frequency Restoration Reserves

MV Medium Voltage

MTOE Million Tonnes of Oil Equivalent

NACE Nomenclature statistique des activités économiques dans la Communauté européenne: numbers used for all industries and service activities in the EU

OCGT Open Cycle Gas Turbine


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OECD Organization for Economic Co-operation and Development

PHES Pumped-hydro energy storage

PHEV Plug-in hybrid electric vehicles

PS Pumped Storage

PV Photovoltaic

RES Renewable Energy Sources

RR Replacement Reserves

SNG Storage of natural gas

SSVC Steady State Voltage Control

ST Steam Turbines

TCL Thermostatically-controlled loads

TSO Transmission System Operator

VRE Variable Renewable Energy

WP Work Package


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1. Introduction

1.1. The CoordiNet project

The CoordiNet project (www.coordinet-project.eu) 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 (DSO) and Transmission System Operators (TSO) 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 centred on 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 (DER). 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.

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 Considering that this Deliverable D1.4 is being published at an early stage of the project, these characteristics may change. Please refer to the latest CoordiNet deliverables for updated information.

http://www.coordinet-project.eu/


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1.2. Scope of the document

The scope of this document is to analyse the main sectors characterising and quantifying the feasible flexibility potential from DERs in order to identify and quantitatively assess what can be expected from the different market participants, and to test the capacities of the selected DERs during the demonstration experiences. The document investigates the main processes, such as heat ventilation air conditioning (HVAC), lighting, cooling, motors, specific process, etc., within the major industries, in the tertiary sector and in households.

During the analysis of this document, and taking into account the different literature findings, as well as some own assumptions, the different consumptions have been exploded until 2030 with the hypothesis of two different scenarios. In addition, with part of the obtained information a questionnaire has been elaborated to understand the perspective of participation of different industries and generators in the system services in the power markets, considering both current and future aspects, barriers and catalysts.

1.3. Structure

The document is structured in three main blocks:

The first one, composed of chapters 2 and 3 review the characteristics of the different types of DER, including industrial, commercial and household demand, distributed and centralized generation and storage systems. Chapter 2 presents the main findings of previous EU-funded projects (which are further described in the Annex presented in section 8.1), while chapter 3 describes the characteristics of different types of DER and qualitatively assesses their suitability for the provision of different services for grid operation.

The second block quantifies the feasible potential of demand response in different sectors. For that purpose,

chapter 4 describes the main productive processes involved in different industrial sectors and chapter 5 quantifies the potential of each type of DER.

The third block is made up of the interviews with stakeholders, including the questionnaires presented to different industrial consumers (annexes in sections 8.4 and 8.5) and their analysis in chapter 6.


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2. Data Collection

The analysis of the potential of demand response (together with other new technologies, such as electric mobility of distributed storage systems) to provide value added services for power systems is a hot topic in the recent years. As a result, there have been several EU-funded projects whose activities and results can be very useful for the success of the CoordiNet project. This report summarises the main contribution of the following projects:

Remodece Project (“REMODECE Project,” n.d.)

Gift Project (“Geographical Islands FlexibiliTy | GIFT Project | H2020-EC | CORDIS | European Commission,” n.d.)

NatConsumers Project (“NATural Language Energy for Promoting CONSUMER Sustainable Behaviour | NATCONSUMERS Project | H2020-EC | CORDIS | European Commission,” n.d.)

IndustRe Project (“IndustRE - Integration of renewable energy through flexible industrial demand,” n.d.)

GOFLEX Project (“GOFLEX - Project,” 2017)

Flexiciency Project (“Energy services demonstrations of demand response, FLEXibility and energy effICIENCY based on metering data | FLEXICIENCY Project | H2020-EC | CORDIS | European Commission,” n.d.)

Pentagon Project (“Unlocking European grid local flexibility trough augmented energy conversion capabilities at district-level | PENTAGON Project | H2020-EC | CORDIS | European Commission,” n.d.)

Magnitude Project (“MAGNITUDE - Project,” n.d.)

SmartNet Project (“SmartNet - Integrating renewable energy in transmission networks,” n.d.)

In particular, the SmartNet project was one of the seeds of the CoordiNet project, as it was one of the first attempts to define and analyse TSO-DSO interaction schemes, market architectures and ICT solutions for the procurement of ancillary services from demand response and distributed generation. For that purpose, SmartNet defined different TSO-DSO coordination schemes, deployed real-life pilots in three European countries (Italy, Denmark and Spain) to identify technological, regulatory and implementation barriers for the different coordination schemes and performed a Cost-Benefit Analysis to compare the coordination schemes under 2030-scenarios for the three countries.

These scenarios considered plausible evolutions of different types of flexible DER, including conventional and renewable generators, storage systems and several types of loads (shiftable loads, e.g. wet appliances, curtailable loads, Thermostatically Controlled Loads (TCL), etc). The quantification of the potential of different industrial processes is partially based on the types of DER defined in SmartNet (Mario Dzamarija et al., 2018).

An example of the potential of industrial demand response, the project IndustrRE aimed to create win-win situations between the European industry and the renewable energy generators. Among the literature reviewed, this is one of the few projects in which flexibility in demand is analysed. The renewable energy generators can minimise balancing costs and optimise their generation profile and resulting overall profit, while the industry can benefit by using their flexibility in various ways (summarised below) to create value for the power system:

Currently, many Variable Renewable Energy (VRE) plant operators generate as much as possible, irrespective of the wholesale prices and the grid limitations, because very often they benefit from priority grid access and fixed tariffs as a result of governmental support programs. However, due to the steady growth and the decreasing support, they are getting more exposed to market prices and becoming more subjected to standard balancing responsibilities. In order to manage this change, they might consider entering bilateral contracts for selling their electricity directly to large end-users. The flexibility potential of the industrial electricity demand has been identified as an opportunity that - through innovative business models - can facilitate further growth and integration of variable renewable energy, while reducing the industrial electricity costs.


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Largely, energy-intensive industrial consumers could have flexibility in their demand arisen through a combination of;

1. a number of process specific properties such as 'direct' and 'indirect' storage of energy,

2. storage of semi-finished products,

3. a certain amount of over-capacity in the production or installation. Depending on the possible rewards that can be reaped by the industry in exchange to their electricity demand flexibility, certain industrial consumers might decide to enhance their flexibility potential through capital investment in e.g. energy storage, CHP unit and/or production equipment/capacity upgrades, etc.

When a Renewable Energy Generator unit is installed on the site of the flexible user, there are more options for benefits to be shared between the industrial electricity user and the Renewable Energy Generator. In this case, when the Renewable Energy Generator units are installed “on the site” of the flexible user means that this installation can supply electricity to the industry without using the public grid, reducing the associated costs and possibly benefiting from carbon credits. Specifically, the Renewable Energy Generator installation is “behind” the user’s meter and it could be owned by the electricity user or by a third party.

Among the rest of the projects analysed, there is no finished project that draws clear conclusions on flexibility options for the household sector or for the tertiary sector. However, all of them agree that the flexibility of electricity systems should be improved, by increasing synergies between electricity, heating/cooling and gas grids and their associated systems. One of such projects, still in the middle of its life, is the MAGNITUDE project which will provide technical solutions, market design and business models in order to be integrated into ongoing policy debates.

The GIFT project, which is still in a very early stage, is focused on the decarbonization of the European islands. It is expected that, once completed, this project will provide interesting information on highly integrated and digitalised smart grids based on high flexibility services from distributed generation, demand response and synergy between electrical, heating and transport networks.


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3. Characteristics of the DERs

This chapter characterizes the main players in the energy value chain from generators to main consumption clusters (industrial, tertiary and residential). Within the industry and tertiary sector, the shares of each type of industrial / commercial activity are described.

3.1. Demand Response (Consumers)

Figure 4 below is a scheme of the different consumers by sectors along with their final electricity consumption in 2017 for countries in the EU-28, as provided by Eurostat.

Figure 4: Final electricity consumption 2017 by sectors (Eurostat, n.d.)

The demand for energy services depends directly on the economic growth (OECD, 2012). For the execution of the simulation exercise, a constant annual growth rate (CAGR) of 2% in the Gross Domestic Product (GDP) over the period 2015-2030 is assumed, which is in line with the OECD forecast (OECD, 2012). Based on the current and historical consumption for each segment, two scenarios are inferred and proposed for future electricity consumption growth until 2030, thereby deriving two scenarios for 2030 consumption by industry as well as tertiary and household sector. In general, for all sectors, the bases used for the two scenarios are the following ones:

Scenario 1 (‘as-is’ scenario): analyses and treats the data from the Business-As-Usual (BAU) point of view, in which it tries to estimate the situation in 2030, by assuming an evolution of the European electricity system without relevant structural changes.

Scenario 2 (‘green scenario’): analyses and treats the data from a more efficient and renewable point of view. It is the scenario that reflects a positive evolution towards sustainable responsibility and decarbonization of our industry from various perspectives. In this sense, it shows a lower consumption rate than scenario 1 due to the sustainable responsibility of consumers, among other reasons.


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The projections made for the different industrial segments until 2030 for both scenarios 1 and 2 have been derived from a variety of sources providing insights on different industries. These sources include documents from ICF Consulting (Yeen Chan and Ravi Kantamaneni, 2015), the JRC (Proceedings of the 6th International Conference EEDAL’11 Energy Efficiency in Domestic Appliances and Lighting, 2013) as well as others published on the website of the European Commission such as (“EUROFER - European Steel in Figures,” 2019), (FTI Consulting LLP, 2018). Furthermore, information about household and tertiary sectors has been obtained from different publications (Eu Energy, Transport And Ghg Emissions Trends To 2050reference Scenario 2013, n.d.), (Paolo Bertoldi and Bogdan Atanasiu, 2009). These inputs have been aligned for coherence and their summary is presented in the Table 2 below.

Table 2 presents the consumption data for 2017 alongside with the growth rate (CAGR) over the past 5, 10 and 15 years for illustration. Next, the expected growth rates are introduced going forward between 2017 and 2030 for the two proposed scenarios (‘as-is’ and ‘green’). Compounding the 2017 consumption by the expected growth rates for each scenario, the reference consumption for each scenario in 2030 is obtained. These values will be used in a later stage to infer the potential for response.

Table 2: Electricity consumption details by different sectors and scenarios

3.1.1. Industry

The progress of the industrial sector towards lower carbon intensity due to energy consumption will be conditioned by the achievements in the combined implementation of various measures: energy efficiency, carrier substitution and electrification, and increased local use of renewable energy.

On the one hand, it is necessary to continue reducing consumption levels by improving the energy efficiency of industrial processes in the implementation of savings and cogeneration measures. Through 2030, only two sectors (iron & steel and the chemicals) are anticipated to increase their energy consumption. The rest of the sectors will remain quite stable, with no major difference except for petroleum refineries, which are expected to have a considerable decline.

2017 CAGR 15Y CAGR 10Y CAGR 5Y

EU-28 Electricity Scenario 1 Scenario 2

TWh % % % % % TWh TWh

Total Final Consumption 2798 1.3% -0.4% 0.0% 3165 2652

Total Industry 1035 -0.9% -1.9% 0.3% 1035 1035

Iron & Steel 115 -2.2% -3.6% -0.6% 0.5% 0.2% 123 118

Chemical and Petrochemical 184 -1.5% -1.8% 0.6% 1.2% 0.8% 215 204

Non-Ferrous Metals 69 -2.4% -2.6% 1.5% -0.8% -1.3% 62 58

Non-Metallic Minerals 69 -3.4% -4.6% -0.3% -0.1% -0.4% 68 65

Transport Equipment 54 0.7% -0.5% 1.8% 0.0% 0.0% 54 54

Machinery 124 5.1% 0.8% 0.2% -0.2% -0.7% 121 113

Mining and Quarrying 20 4.0% 3.7% 2.1% 0.0% 0.0% 20 20

Food, Beverages and Tobacco 118 2.5% 1.0% 0.9% -0.7% -1.2% 108 101

Paper, Pulp and Printing 117 -2.9% -4.4% -1.1% -0.7% -1.1% 107 102

Wood and Wood Products 26 1.9% -1.3% 1.6% 26 26

Construction 21 8.1% 4.8% -0.3% 21 21

Textile and Leather 21 -12.4% -7.7% -1.3% 21 21

Others 98 -2.5% -2.2% 1.2% 98 98

Commercial and public services 837 4.4% 1.2% 0.0% 2.5% 1.3% 1153 989

Households 808 1.5% 0.0% -0.6% 0.4% -3.0% 851 544

Total Transport 65 -1.8% 1.0% 0.7% 65 65

Rail 53 -0.8% 0.6% 0.3% 53 53

Road 2 44.8% 33.1% 21.5% 2 2

Pipeline Transport 2 10.1% 8.3% -0.1% 2 2

Others 8 -10.1% -0.5% 0.8% 8 8

Not Elsewhere Specified 54 2.7% 0.4% 1.0% 54 54

Consumption by 2030Expected CAGR to 2030

Scenario 1 Scenario 2


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Built on a literature review of economic indicators, market statistics, energy consumption trends and business strategies, a perspective on the possible sectoral BAU energy consumption trends through 2030 was created. For scenario 1 (‘as-is’), the percentage change in energy growth from 2015 versus 2030 has been used as the assumption of growth from 2017 to 2030, as shown in the following table extracted from the ICF Consulting report (Yeen Chan and Ravi Kantamaneni, 2015). These trends are shown below in Figure 5.

Figure 5: Business as usual projections of final energy consumption through 2050 for EU

(Yeen Chan and Ravi Kantamaneni, 2015)

On the other hand, scenario 2 (‘green’) has been projected taking into account the economic potential for energy savings, according to the Commission Directorate-General Energy proposal (Yeen Chan and Ravi Kantamaneni, 2015). The corresponding values are gathered in Table 3, where it has been considered that the electricity consumption decline is the same as the reduction in all other energy sources.

Sector

Business as usual energy

consumption (MTOE/yr)

Economic potential – 1

(MTOE)

Economic potential – 2

(MTOE)

Technical potential (MTOE)

Pulp and paper 37.3 1.1 (2.9%) 1.4 (3.8%) 7.2 (19%)

Iron & Steel 67.5 2.9 (4.3%) 3.1 (4.6% 16.3 (24%)

Non-metallic mineral 36.9 1.2 (3.3%) 1.3 (3.6%) 7.1 (19%)

Chemical and pharmaceutical

66.4 2.6 (4%) 3.2 (4.9%) 16.5 (25%)

Non-ferrous metal 8.6 0.5 (5.5%) 0.5 (5.8%) 1.9 (22%)

Petroleum refineries 42.5 1.7 (4.0%) 1.9 (4.5%) 10.6 (25%)

Food and beverage 26.4 1.4 (5.2%) 1.7 (6.5%) 6.8 (26%)

Machinery 19.8 1.0 (5.2%) 1.3 (6.5%) 5.3 (27%)

Table 3: Economic and technical saving potential of industrial final energy consumption in 2030

(Yeen Chan and Ravi Kantamaneni, 2015)


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3.1.2. Tertiary

In this report, the tertiary sector refers to the public sector, education, healthcare, services and commerce. On the contrary to the industrial sector, the availability of information in the tertiary sector, as well as in the household sector, is very limited. In spite of the intense search for literature and the attempt to analyse different sources, the data obtained has been scarce, so an estimation exercise was performed, based on the data provided by Eurostat (Eurostat, 2019), in which the commercial and public sectors are grouped in one.

In general, the tertiary sector has increased its final energy consumption over the analysed period, with particular contribution from the commercial and public sectors. In the estimation exercise performed, the increasing trend in the tertiary sector is expected to continue during the next years due to the shift in end consumer preferences towards services. Moreover, service providers will also need to procure more services from other service companies, so the demand increase will be further fostered. These elements suggest a general trend of tertiarization related to the labour force and production.

3.1.3. Households

According to Figure 4, household consumption is responsible for 30% of total electricity demand in Europe. Households play an important role in future electricity systems as they provide an increasing share of power generation capacity and are at the same time an important electricity consumer. In spite of having such an important weight in consumption, a good understanding of their consumption and load profiles is missing.

The three main factors that affect household consumption, which are closely interrelated, are socio-demographic factors, the degree of penetration of electric appliances and the electrification rate of the household energy consumption (whether electricity is also used for heat, cooling, mobility, etc.)

3.2. Distributed Generation

From the point of view of generators, their EU-28 production mix in 2017 has been analysed and their generation forecasts for two different scenarios have been taken into account from Foratom's perspective for 2030 (FTI Consulting LLP, 2018): a low scenario (scenario 2) and a high scenario (scenario 1).

The corresponding values are shown in Table 4 for the main technologies considered in this analysis (wind,

solar, hydraulic, nuclear, fossils and others).

The low scenario is largely based on variable renewable energy sources and backup sources. A reduction in nuclear energy would require the RES share to be around 80%, above the current acceptable level of renewable energy penetration across the EU. A high nuclear scenario would manage to contain the variable RES share at around 60%, which would reinforce the long-term stability of the system.

Table 4: Estimate production mix for two different scenarios in 2030 (FTI Consulting LLP, 2018), (Eurostat, 2019)

2017


TWh TWh TWh

Total Final Generation

Wind 344 770 750

Solar 114 275 300

Hydro 280 458 280

Nuclear 787 745 500

Fossil 1147 677 577

Other 126 240 245

Generation by 2030


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From the point of view of the low scenario (scenario 2), until 2030, the lack of commercial maturity of the storage technologies will require that dispatchable technologies (including both fossil and nuclear power plants) are kept in operation to ensure system stability. Moreover, anticipated nuclear shutdown would entail the need to build 20 GW of new thermal capacity by 2030 and would require extending the lifetime of 7 GW of high-carbon thermal power plants. Furthermore, scenario 1 (high scenario) takes into account the life extension of nuclear plants.

3.3. DER technologies characterization

A literature review has been carried out in order to define the current status and future expectations regarding the participation of DER in the provision of system services, mainly focusing on the resources deployed in the CoordiNet demos; i.e. wind power, photovoltaic (PV) and loads. The study covers the work performed in European projects, such as SmartNet (Julien Le Bault et al., 2017), ReserviceS (Faiella et al., 2013; Paul Kreutzkamp et al., 2013; Van Hulle et al., 2014) and also general reports on the provision of system services by DERs (Braun, 2006; Rehtanz et al., 2014).

The current and expected changes in the generation mix, caused by the entry of large number of decentralized plants, require new solutions for the provision of system services in order to guarantee the safety, reliability and stability of the power supply.

The participation of these decentralized resources in the provision of system services depends on the characteristics of the system, on their own characteristics (e. g. technical characteristics, location, etc.) and on the requirements that must be fulfilled for the provision of each specific service, such as the minimum bid size, service duration, full activation time, etc.

Therefore, when quantifying the availability of DERs for the provision of the system services, all these issues

should be considered, since there are capability differences even within each type of DER.

In addition, a relevant matter to be considered is the influence of the grid-coupling technology. All distributed generation units have a grid-coupling device, which feeds electrical energy into the grid as the last element of a chain of energy converters of the unit and the capability of the same flexibility resource varies significantly depending on the technology used. There are four typical grid-coupling technologies currently in use:

1. Directly-coupled induction generators (IG): the generator is directly connected to the grid through a transformer. Although this solution is simple and reliable, direct connection only allows the speed to vary in a very narrow range, reducing the power output range. In addition, these generators are not grid friendly in terms of reactive power, low voltage ride through and flicker (Pillai et al., 2019; Reddy and Kumar, 2015). A capacitor bank is included for reactive power compensation and a soft starter is used for smooth grid connections (Pillai et al., 2019). However, this type of grid-coupling technology is no longer used due to the mentioned drawbacks.

2. Directly-coupled synchronous generator (SG): these generators are the primary source of electricity generation in the grid. Using a directly coupled wound rotor synchronous generator with a variable transmission has several benefits; reactive power control capability, harmonic free, transformer free, fault current contribution and reliability. However, they have some challenges such as low voltage ride through, complex gearbox and increased drive train mass (Pillai et al., 2019).

3. Doubly-fed induction generator (DFIG): the stator of the generator is directly connected to the grid while the rotor is connected by means of a back-to-back-converter and a crowbar (Pillai et al., 2019). The converter, that consists of two bidirectional converters and a direct current (DC) link, acts as an optimal operation tracking interface between the generator and grid. Field-oriented control (FOC) is applied to both rotor-and stator-side converters to achieve desirable control on voltage and power. According to the maximum active and reactive power control capability, the power rating of the converter is determined. The DFIG solution has higher energy capture efficiency than the directly-coupled one and an improved power quality (Reddy and Kumar, 2015).

4. Full-converter (FC), including inverter-coupled IG and SG: the generator is connected through a full-scale inverter which gives a high control capability. These generators have decoupled active and reactive control capability. The main disadvantage of this solution is the lack of inertial response


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due to the inverter. Different options are proposed in the literature from additional control loops to batteries / flywheels.

The technical capability of different grid-coupling technologies for providing system services depends on some basic control capabilities. For instance, inverters present excellent controllable characteristics and currently all modern inverters can provide active and reactive power control (they are able to ramp up to full power within 500 ms to 1 s, depending on the design). However, the converters decoupled the generation from the grid which reduces the total inertia of the power system, i.e. for the same frequency perturbance due to generation and demand events, the frequency suffers from higher deviation and the power system becomes more unstable.

The sections below summarize some technical characteristics to be considered when determining the feasibility of the specific technology for the provision of the services. Furthermore, section 3.4 shows a summary of the qualitative analysis carried out in the SmartNet project, as well as brief conclusions by each type of service.

3.3.1. Conventional Fossil Fuelled Technologies

The most common conventional fossil fuelled technologies commercially available are; internal combustion engine (ICE), fuel cells (FC), steam turbines (ST), gas turbines (GT), diesel and gas generators and combined cycle gas turbines (CCGT). FCs are used as micro-CHP units and are becoming more and more available.

Small ICEs are very typical in small systems such as small islands and closed and isolated systems. Their response capabilities will be analysed in detail in the Greek demo within the scope of CoordiNet.

A special mention must be made to CHP solutions since these are very common within industrial sites and

their technology is also widespread across the domestic domain: steam and combustion turbines are incorporated as industrial and district heating CHPs, while micro-turbines are used in residential and commercial CHP applications.

CHP plants generate both electricity and heat from a central process, but, most of the time, the CHP

production follows a heat-driven operation, since there is often less flexibility in the demand for heat. Thus, CHPs are generally quite inflexible. In general, CHPs can be incorporated regardless of time-of-day (contrary to wind turbines and photovoltaic generation), but they may however exhibit less flexibility depending on the flexibility of the heat demand and/or the presence or not of a heat storage (to decouple heat production and demand). Their main limit is in ramping delay, so, they are less suitable for system services requiring fast-reaction times. Therefore, more capability may be indicated for secondary and tertiary frequency control, although the usage of CHPs even for primary control has been reported in countries like Denmark. Specifically, focusing on the grid coupling technology, the synchronous generator and fixed-speed induction generator versions are more capable of frequency regulation because of their rotational inertia.

Regarding the reactive power, CHP capabilities depend on the grid-connection type: they can either have rectangular (synchronous generator), semi-circular (inverter connection) or fixed power factor (induction generator) capabilities. Therefore, they are quite suitable for voltage regulatory services (except for limited capabilities of the induction generator version). Most likely, voltage regulation capabilities will be improved in the future, since more advanced inverters are expected to be developed. The CHPs with inverter connection are more capable of providing power quality services, because the power factor is highly adjustable, being the capabilities very similar to a PV plant.

CHPs can also be used for black start since the initial source of energy is chemical (not dependent on weather

or time-of-day).


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3.3.2. Variable Renewable Energy Sources

This category includes technologies such as PV, wind turbines and run-of-river power plants in which the electric power output is directly proportional to the primary energy resource. These energy resources have in common that the availability of the primary energy source (e.g. wind, solar, water flow) is highly variable and that the electric power output is limited by the primary energy resource. Therefore, the electric power generated is highly variable and to a large extent, cannot be controlled (only curtailment is possible in some cases).

Currently, these installations do not include any coupled storage unit, but, it can be expected that in 2030 most of these installations will include some storage for different purposes, such as to avoid unwanted curtailment, or to better forecast the production profile and reduce its uncertainty, since the forecast of these variable renewable energy sources with no storage is quite complex.

In general, renewable sources do not have the same flexibility as conventional plants, due to their non-programmable nature and because they can seldom increase their power output. In fact, the control systems of these resources are usually optimized to maximize the power output and not to give other services. However, for the future, the required need of more flexibility would result in an evolution of the power converters, control solutions and aggregation procedures that would allow the participation of small units in the system services (Rehtanz et al., 2014). Therefore, the design of markets and products should be adapted, considering characteristics such as separation of upward/downward bids, definition of gate closure times as close as possible to delivery, minimised time frames, etc. (Van Hulle et al., 2014).

The next two sections provide more specific details regarding wind and photovoltaic technologies, due to

their importance in the CoordiNet demos.

3.3.2.1. Wind power

In general, technologies such as wind and PV generation are penalized by their low predictability, which makes them inadequate for system services requiring long activation time. Wind power plants of relevant size are already providing some system services. In particular, the wind generators coupled by inverter or DFIG have great capabilities for system services exploitation. Furthermore, full-converter wind turbines have higher reactive power control capabilities than those connected with doubly-fed induction generators.

The European project REserviceS investigated the potential of wind and solar to provide grid support services at EU level (Van Hulle et al., 2014) and several important conclusions regarding these technologies were reached:

Most of the functionalities necessary for delivering the system services are either already existing in wind power plants, or can be implemented, but they not used yet, mainly because there is no business case for them. From a technical point of view, most of the necessary enhancements are related to communication, which needs to be fast and reliable, and controllers, that need to be developed and/or tuned for delivering the required performances.

Accurate wind power forecasting is a key element in increasing the utilisation of wind power in system services markets.

Regarding frequency control, modern wind turbines can go from the lowest power level to full, rated power in a maximum response time of 6 to 10 seconds, provided that wind resource is available. In general, the wind turbine technology offers advanced capabilities for frequency support and only few technical constraints have to be overcome to deliver frequency services on a sustained basis.

Regarding reactive power support, where there are several technological limitations, they could be overcome using hardware that is available today. Structural, mechanical and electrical design changes may also be required in wind turbines, depending on more exact specifications of the services. In the case of full-converter wind turbines, however, reactive power support is possible by defining a simple power factor at the inverter, as long as wind energy is available.

However, further efforts to enable an enhanced delivery of system services by wind energy technology are needed (Faiella et al., 2013):


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o For Frequency Containment Reserve (FCR) service: Improved TSO specifications for the active control mode of wind farms is needed. Also, wind turbine structural design may need adaptations to consider increased mechanical loading of a sustained delivery of FCR. Finally, development of improved methods for defining and sensing the system frequency at wind turbine and plant level, especially with respect to higher measurement resolution.

o For Frequency Restoration Reserves (FRR) and Replacement Reserves (RR) services: In addition to the wind turbine design challenges of FCR, improved forecasting through better methods and by pooling wind farms into clusters2 is needed. Also, there is a need for reliable methods to estimate available power as input for active power control in wind farms.

o For the newly proposed Fast Frequency Response3: Improved TSOs specifications for the desired wind power plant control response are needed. Moreover, additional efforts are needed for developing reliable methods to detect and measure system frequency deviations at wind turbine and plant level, as well as for fast and reliable communication between the plant and the network operator.

For the system services regarding the voltage control, some conclusions were also reached (Faiella et al., 2013):

o Reactive Power can be supplied up to certain value. The range is normally defined by PQ diagrams. Using converters with self-commutated switching device, independent supply of active and reactive power is possible.

o For the existing ancillary service Steady State Voltage Control (SSVC), the essentially needed capability from wind power is the controlled provision of reactive power, ranging from slow to fast, and depending on the needs of the specific network operator. Limits in reactive power provision imposed by wind power technology can be compensated either by oversizing the converters and/or installing additional equipment like STATCOM devices. Extending reactive power provision down to zero active power would imply extra costs. A particular economic challenge is the provision of reactive power at MV level, where larger fluctuations in voltage can occur, leading to a higher need to oversize electrical components.

o For the newly proposed ancillary service Fast Reactive Current Injection (FRCI) (Faiella et al., 2013) during network faults (i.e. during fault-ride-through), it can be determined that the current wind turbine design includes the capability for a controlled fast reactive current response and that limitations depend on the wind turbine conversion technology and the grid requirements imposed. When extending the capability towards very fast provision of a controlled response, technical challenges include the development of accurate voltage sensing, recognition of fault types and appropriate tuning of controllers.

3.3.2.2. Photovoltaic power

Regarding the photovoltaic generation, there is less experience, but its capability of providing system services is demonstrated both in literature and in European projects. The ReserviceS project concluded that there is no major technical challenge for the provision of the system services. However, remotely controlled frequency support services based on upward active power reserves can be offered at reasonable costs only by large PV portfolios spread over wide regions. Frequency support services provided by individual systems will hardly be cost-competitive, even with future PV forecast improvements. Another barrier for the integration of PV in providing frequency control services is the contracting framework for active power services to TSOs. Currently, PV systems cannot meet the requirements, as reserve services are contracted for time periods that include night-time hours, when PV could provide upward reserve only if costly storage systems were added, or long before actual delivery, so that the forecast uncertainty increases significantly.

An additional barrier is the confidence level required today. Holding upward reserve service ready with a confidence level that is similar to the one of a conventional power plant implies that only portfolios covering large areas can offer upward reserve at acceptable and competitive costs.

On the other hand, voltage support may be offered by rather small PV systems. For this type of service,

aggregation of systems in portfolios does not bring any added value to the possibility to control them in a coordinated way. However, it must be considered that reactive power is most effective locally and that

2 Cluster: set of independent wind farms jointly managed by a special control system in a coordinated manner 3 For a more detailed information, see: https://www.nationalgrideso.com/balancing-services/reserve-services/fast-reserve?market-information

https://www.nationalgrideso.com/balancing-services/reserve-services/fast-reserve?market-information

https://www.nationalgrideso.com/balancing-services/reserve-services/fast-reserve?market-information


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reactive power provision on the distribution grid level to support voltage control on the transmission level might even be counterproductive (Paul Kreutzkamp et al., 2013).

In general terms, the potential enhancements of capabilities for PV should include; estimation of available power/forecasting, faster and reliable communication and control within the plant, control strategies for portfolios composed of numerous small and medium sized units, improving interoperability of different networks and enhancing compliance to a multitude of non-harmonised grid code requirements (Van Hulle et al., 2014).

As a summary, the implementation of enhanced capabilities and the deployment of the services, for both

photovoltaic and wind generation will involve additional costs. In both cases, the additional investment costs for enhanced provision are relatively low and, provided appropriate cost recovery and market mechanisms are in place, their deployment should be commercially feasible. Only for current small PV systems, the impact of required communication components would result in high additional investment costs. In general, both for wind and PV, operational expenditure costs, notably upward readiness cost, represent the highest costs to make frequency services available.

However, the enhanced capabilities should not be required if there is no need for them, as this would result in unnecessary additional cost. In general, frequency-related services can be provided by a portion of DER units and not all units need the capability. Utilising DER in voltage-related services depends on their location in the network and should be judged on a case by case basis (Van Hulle et al., 2014).

3.3.3. Energy storage systems

The main objective of this section is to carry out a brief analysis of the main characteristics of the batteries with regard to the provision of system services in the network, paying special attention to the barriers.

As explained in detail in (Julien Le Bault et al., 2017) the storage can be stationary or mobile (EVs). This division has sense due to the additional constraints that EVs impose to batteries rather than to the technology used in the EV and, hence, they will be described in section 3.3.4). Regarding the technology, different storage technologies can be found based on the way the electric energy is stored:

Mechanical: pumped-storage hydropower, CAES (compressed-air energy storage), LAES (liquid-air energy storage), flywheels.

Thermal: thermo-chemical, sensible thermal, latent thermal.

Chemical: hydrogen storage, SNG (storage of natural gas).

Electro-chemical or batteries (BESS): lithium-Ion battery, lead acid battery, NaS battery, redox flow battery.

Electrical: super-capacitors.

Out of these technologies, the only one which has been widely used in big sizes is the pumped-hydro energy storage (PHES). PHES can be controlled either through variable of fixed speed control. In the former, the pumping process occurs at a fixed speed (i.e. at the synchronous speed) which does not enable any frequency regulation. Most of the existing plants are operated with fixed-speed synchronous generators, but recently, variable speed units have emerged thanks to the use of doubly-fed induction generator or synchronous generators coupled with static frequency converters. PHES are able to ramp-up to full power between 30 s and 1 min and can reverse the mode (pump to generator or vice-versa) in about 30 seconds. Therefore, pumped hydro has overall very good capabilities in terms of frequency and voltage control. In the future, more and more PHES will be of the variable-speed type, which will improve their capabilities. Some of the system services are not applicable to them (e.g. low voltage ride through) due to their size and the fact that they are mostly connected on the transmission grid level. As an additional drawback, PHES are not suited to provide power quality improvement system services.

Among the various storage technologies, BESS appears to be one of the leading technologies. Batteries have

excellent performance in any domain (Figure 6) thanks to their long discharge time, their high ramping rate and the well-known capabilities of inverters for voltage control or frequency control, Low Voltage Ride


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Through (LVRT) capability, etc. It is important to note that the main difference between the technologies is mostly reflected in the costs and the maximum number of cycles, but not in their ability to provide system services. Actually, energy storage can provide thirteen fundamental electricity services (i. e. energy arbitrage, spin/non-spin reserve, frequency regulation, voltage support, resource adequacy, transmission congestion relief, transmission deferral, distribution deferral, time-of-use bill management, demand charge reduction, increased PV self-consumption, backup power) for three major stakeholder groups (i. e. customers, utilities and independent system operators/regional transmission organizations (ISO/RTOs) when deployed at the customer’s premises (behind the meter) (Garrett Fitzgerald et al., 2015).

Figure 6: Services that batteries can provide to three stakeholders (Garrett Fitzgerald et al., 2015).

Furthermore, according to (CIGRE WG C6.30 and WG C6.30, 2018) energy storage is a key component in providing flexibility and supporting renewable generation integration in the energy system. It can balance both centralized and distributed electricity generation, while also contributing to power system security. Energy storage will supplement demand response, flexible generation and provide another option in grid development. Energy storage can also contribute to the decarbonisation of other economic sectors and support the integration of higher shares of variable renewable energy in transport, buildings or industry. The contribution that energy storage can make to the energy system is becoming recognized in most countries around the world.

Extensive innovation and development of BESS has produced significant cost reductions and performance improvements. It is also predicted that there will be further rapid reductions in cost, since future developments in batteries should mostly affect (i.e. decrease) the cost and not so much the technology. That is why the qualitative mapping is very similar between current and future system services.

However, there are key features of the batteries that must be considered to ensure a safe and cost-effective provision of system services, i.e. the BESS evaluation requires a different approach to conventional generation assets. Among others, there are three main characteristics that determine the performance and the adequacy of the batteries for the provision of system services (CIGRE WG C6.30 and WG C6.30, 2018; Iker Marino, 2018).


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1. Limited capacity: this means that their capacity to provide power is limited to a certain duration which highly affects to the provision of several services. Consequently, the current business opportunities for BESS are related to services that allow to offer a limited duration and, at the same time, allow to manage the state of charge. These two conditions do not exist in many markets, which limits the participation opportunities for BESS.

2. Consumable, degradation: the useful life of BESS is determined not only by the passing of time but also by the use and the working conditions (charge/discharge power, depth of discharge, temperature, etc). Thus, every kWh provided by a BESS produces a certain capacity degradation and hence a reduction of the system useful life. This is an important aspect when analysing the feasibility of a BESS for a certain application and assessing the cost associated to the provision of the service. Some batteries, such as those belonging to the lithium-ion family, deteriorate quickly when they are charged to maximum capacity and then fully discharged. The capacity used for such storage technologies is therefore generally 60-80% of the total installed capacity. This should be factored into the sizing procedure (CIGRE WG C6.30 and WG C6.30, 2018). For example, in (Wankmüller et al., 2017) the authors found that reducing the cycling of the battery via introducing a penalty cost in the objective function of the energy arbitrage optimization model can improve the profitability over the life of the BESS.

3. Cost and performance: compromises need to be made between cost and performance during the battery selection process. The technology, chemistry and configuration of the batteries determine the suitability of the whole system to perform a specific use-case or combination of compatible use-cases reliably, for a specified number of cycles, over a specified period of time, and within specified environmental conditions (CIGRE WG C6.30 and WG C6.30, 2018).

Additionally, and from the point of view of the DSO, the following issues are of high importance (CIGRE WG C6.30 and WG C6.30, 2018):

Maintenance: the batteries may require maintenance, service, periodic refurbishment or replenishment, or other care. Many of today’s battery technologies are far more versatile, powerful, energy-dense and sophisticated than traditional lead-acid batteries. Newer battery technologies may require careful attention from the BESS owner to ensure long-term service reliability of the entire BESS. Such attention may include occasionally changing a filter or a pump, maintaining environmental conditions that are favourable to battery reliability, periodically resting the batteries, so that they can cool down or perform cell-balancing, understanding the ratings of the batteries sufficiently so that the BESS is operated in a way that helps keep the batteries healthy. Not only must the BESS be designed well to minimise disruption to the distribution system when such battery maintenance occurs, but the operation of the BESS in light of such maintenance requirements must be coordinated with the DSO. This coordination may also impact the overall performance of the distribution system.

The control system, which is one of the most important factors in successful BESS implementation, depends on two key considerations:

1. The application-specific requirements of BESS performance as experienced by the grid, which determine, among other things:

the operation modes that each component in the BESS system must perform; the speed of response that is required to perform each of the operation modes, or

to transition between operation modes; and, the rate at which control signals and data must be processed.

2. The degree to which the control systems at all levels are either integrated or modular, from the lowest-level Building Management System to the highest-level Distribution Management System or central office information system. This degree of integration determines:

the complexity of the overall control architecture; the extensiveness of the customisation, configuration, integration and verification

required for each sub-system; the types and quantities of data that must be exchanged between various

components in the system. “Who” implements the control systems and “how” they are implemented may be more important than “what” was implemented and “when” it was delivered. Control engineers and system integrators are more likely to develop high-quality and reliable BESS control systems when they have


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experience with all the following topics: power systems, power electronics, programmable logic controllers (PLCs), building management systems, supervisory control and data acquisition (SCADA), and communications protocols such as TCP/IP. If DSO personnel do not have such experience, then they will likely need to work with trustworthy consultants or third-party systems engineers to enhance their capability.

The boundaries of responsibility for the generation, transmission, distribution and consumption of electrical energy are well-established in many areas of the world. An asset, such as BESS in the distribution network, can push against those boundaries, or even transcend them in some cases. It is generally understood how the performance of the distribution network affects end-users, since the grid of the past was designed for unidirectional energy flows from a point of centralized generation to dispersed points of consumption. However, the points of consumption, once considered the end of the electrical energy chain, may now be dynamic, distributed, diverse, interconnected, intelligent and interactive co-generators within the distribution network. The result is that the stability and reliability of the distribution system now depend, in part, on multi-directional relationships with formerly traditional and unidirectional energy consumers. In this sense, from the perspective of a distribution network, BESS concentrated at the substation level can help manage the aggregate variability of consumption-side resources and loads in an economically favourable manner.

BESS sizing: The procedure for sizing BESS mainly depends on the operation of the BESS and varies from application to application. Generally, two criteria, namely the power rating of the system and the discharge time at rated power, are applied to identify the applications of a BESS. Based on this classification, three applications can be identified: energy management, power quality and bridging power. The sizing procedure is also directly related to the design of an energy storage management system (ESMS). Optimal BESS operation can reduce the size of storage capacity and storage power, thus reducing the capital expenditure. Depending on the case study, the sizing procedure will change. For example,

1. An autonomous system with intermittent power generation: due to the relation between the depth of discharge and the service life of the BESS, the battery deteriorates very quick (degradation) which makes necessary to oversize the BESS.

2. Primary frequency control: in order to sell its power reserve (both positive and negative) at any time, a BESS either has to be discharged if it has been charged beforehand to help maintain network frequency, or it has to be charged if it has been discharged beforehand. Buying and selling power on the intraday market is one way to charge and discharge a BESS. On some intraday markets, the physical trading of power occurs forty-five minutes after the financial trading. Thus, a time lag of forty-five minutes should also be factored into BESS sizing.

Apart from the general information on the installed capacity and the types pf technologies more deployed in each country (this information is developed and available in section 8.3.4), the DOE’s database gathers a list of 30 use cases which are applicable to each specific project (Department of Energy - USA, 2019). For the sake of simplicity, these use cases have been grouped into a higher-level category as follows (CIGRE WG C6.30 and WG C6.30, 2018):

Energy arbitrage: Electric bill management, electric bill management with renewables, electric energy time shift.

System services: Frequency regulation, load following (tertiary balancing), electric supply reserve capacity – spinning, electric supply reserve capacity-non-spinning, voltage support, black start, ramping, transmission support.

Balancing renewable energy: On-site renewable generation shifting, renewables capacity firming, renewables energy time shift.

Load levelling and peak demand: Demand response, distribution upgrade due to solar, distribution upgrade due to wind, transmission upgrades due to solar, transmission upgrades due to wind, transportable transmission/distribution upgrade deferral, stationary transmission/distribution upgrade deferral, transmission congestion relief, electric supply capacity, on-site power, EV charging.

Resiliency: Resiliency, grid-connected commercial (reliability & quality), grid-connected residential (reliability), microgrid capability.

Transportation services: Transportation services.


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As it can be seen in Figure 7, the Energy arbitrage and System services are the main distribution primary use-cases. In general, using storage to shift energy demand is a significant use case, both for reducing or levelling demand on the network and for maximising renewable energy use. Whilst the storage size is a design factor to be optimized, the information from the primary use cases suggests that all sizes are able to support all use-cases.

Figure 7: Storage installed capacity on distribution networks by primary use case (CIGRE WG C6.30 and WG C6.30, 2018)

Based on the analysis performed by the working group in (CIGRE WG C6.30 and WG C6.30, 2018), some main findings can be highlighted. In general, storage applications are useful across the whole electricity value chain and there is a high variety of business use cases with typical requirements for the configuration of each storage system. The battery storage technologies are ready for deployments from kW to MW ratios to create value from short to medium term, but, at the same time, the battery storage face considerable challenges.

The safe and reliable control of the battery is crucial for an economically viable operation. Specifically, one of the main challenges is the accuracy of the state of charge value. Another issue to be considered is the battery storage efficiency, since, so far, there is no standardized definition of it. To map all loses to one overall system efficiency value, all losses should be related to the expected average power of the planned battery application.

Finally, it must be considered the different treatment that storage has in the countries; while in some

countries the storage is considered as a generation subset, in other ones it is considered as special loads, which creates uncertainties about what services can be provided by and, also, what has to be paid for the operation of the batteries.

3.3.4. Electric vehicles

In the past few years the electric vehicles (EVs) market has witnessed a continuous and steady increase. Apart from the benefits of lower energy costs and less greenhouse gas emission, EVs are also considered a critical supplementary resource for building a sustainable energy system in a smart grid environment. In recent years, the application of aggregated EVs as energy sources to provide system services is under analysis (Islam et al., 2019).


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EVs are considered as a separate category from stationary storage because EVs have additional constraints, mainly due to the fact that the battery is not connected to the grid all the time and its primary use is driving. In spite of these issues, the battery technology is basically the same for both stationary and mobile applications (Julien Le Bault et al., 2017).

It must be noticed that only those EVs which can be connected to the grid, plug-in electric vehicles, are considered in this analysis. There are two main types of plug-in EVs:

Battery electric vehicles (BEV) which run only on electricity and their batteries are charged through the grid.

Plug-in hybrid electric vehicles (PHEV) which also have an ICE. These cars can switch to the ICE when the battery is depleted. The battery is charged by plugging it to the grid and by regenerative braking.

Note that both hybrid electric vehicles, where the battery is only charged by regenerative braking, and fuel cell electric vehicles are not considered since they are never plugged in to the electric grid and thus cannot provide services to the grid.

On the one hand, all EVs can technically provide grid-to-vehicle (G2V) services to the power system by modulating their charging power consumption pattern. Therefore, a coordinated EV charging behaviour will benefit the existing electricity infrastructure by accommodating additional demands, which is favourable to the entire electricity system during the charging period (Aziz and Huda, 2019). On the other hand, part of the EVs could also provide vehicle-to-grid (V2G) services to the grid by discharging power into the grid, similar to a stationary battery.

The mobile storage coming from the EVs have quite promising performances. In particular, by using the characteristics of a the EV as a power resource, several system services could be developed, including frequency regulation, voltage regulation, load levelling, congestion mitigation and power storage (Aziz and Huda, 2019).

Frequency regulation is considered able to achieve high economic benefit for EV owners due to the high participation price (Islam et al., 2019). EVs could provide a quick response for a not too long duration and this is why scores are higher for the primary control compared to the secondary control (Julien Le Bault et al., 2017).

Voltage control. EVs perform relatively well for the primary, secondary and tertiary voltage control thanks to the use of inverters (Julien Le Bault et al., 2017).

In general, the most suited applications for both frequency and voltage regulations, are those ones which require responses that are faster than a minute with durations of few minutes. EVs are also able to provide up and down regulation, avoiding dangerous peaks and drops (Julien Le Bault et al., 2017).

The integration of the EVs needs to be investigated from the perspectives of both the owner of the EV and the power system. The benefit of the EV’s owner (or aggregator) should be maximized through the identification of a set of optimal charging/discharging decisions and, on the other side, the EVs should be integrated into the smart grid for improving grid reliability and service quality. Focusing on this last issue, the integration can be realized in three different modes (Islam et al., 2019):

1. Base load mode: EVs are required to work as a regular generator to provide electricity to the grid. 2. Peak load mode: EVs need to provide additional electricity supply during peak periods. 3. Frequency regulation mode: EVs need to adjust the energy flow rate between the batteries and the

grid to reduce the difference between the load and the generation of the grid in such a way that the frequency of the grid can be tuned back from deviation on a real-time basis.

It has been pointed out that the cost due to the battery degradation is significant when EVs are used for base load and peak load purposes, due to the depth of discharging and long service time. However, in the frequency regulation mode, the battery will undergo shallow charging/discharging cycles with a short duration, so the cost with respect to battery degradation is very limited compared to the application of an


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energy storage device used to provide bulk energy. Furthermore, the frequency regulation mode requires that the sources providing regulation service possess a fast response capability (less than one minute) to either provide or consume the electricity in order to offset the unbalance between the generation and the load, which can be fulfilled by EVs. Therefore, the frequency regulation mode is considered a promising EV V2G application by many researchers (Islam et al., 2019).

Considering the limited size of an individual battery (kWs), multiple EVs need to be aggregated so that the total capacity is able to achieve the desired functionality in the frequency regulation mode. An intermediate aggregator between the grid and the EV owners is then needed to coordinate the aggregate behaviour of EVs for frequency regulation when they are connected to the grid. The cost effectiveness of such an aggregated frequency regulation service has been analysed in existing literature demonstrating that the frequency regulation is the most competitive EV application that can be utilized by the grid when the payment from the grid to the aggregator includes both a capacity reserved payment and an actual energy contribution payment (Islam et al., 2019).

In practice, the aggregated EVs could provide upward regulation by either decreasing the charging rate or increasing the discharging rate when the frequency drops because the load exceeds the generation and the grid issues a signal of regulation up. In the same way, the EVs could provide downward regulation by either increasing the charging rate or decreasing the discharging rate when necessary. One of the challenges to be solved by the aggregators when making decisions is that the control actions need to be dynamically updated together with the changing signals of the frequency regulation from the grid as well as the new EVs that are connected to the grid (Islam et al., 2019).

Finally, a strength of the EVs is the fact that the investment cost in the battery can be assigned to the primary use of the EV, driving, which makes EV a cheap resource to provide system services. In addition, EVs are advantageous because of their scarce use for transportation (estimated ~ 4% of the time). The remaining 96% of time could be potentially reserved for the system services provision, ensuring availability even during the peak hours (Julien Le Bault et al., 2017).

3.4. Qualitative analysis

This section tries to summarize which type of DER is more or less suitable for the provision of the different services required by power systems, based on the analyses by (Braun, 2006) and (Rehtanz et al., 2014).

Frequency control services: Notice that significant difference exist depending on the product considered such as aFRR, mFRR or RR, the feasibility of different resources would depend on the activation time, the activation mode and other characteristics (See CoordiNet Deliverable 1.3 for further details of products). In general, this control (based on active power) can be provided by almost all DER, although there are technologies, such as heat-driven4 CHP is limited, since they have to follow the required thermal profiles. On the contrary, electricity-driven CHPs as well as storage systems show good capabilities because of their high availability and flexibility. Intermittent RES systems, i.e. wind, PV and hydro power plants, as well as loads, can control their active power, but their availability is limited. Although frequency control comprises services of different reaction times (from seconds to minutes), all of them times can be covered by different DERs. Before balancing energy is technically fully available due to the activation times, rapid frequency changes are attenuated in the short-term due to the inertia of the rotating masses of generators in the conventional power plant fleet. The capability of counteracting frequency changes by absorbing or feeding kinetic energy is referred to as instantaneous reserve. The DERs, especially wind turbines large PV plants and battery storage capacities, can already be technically equipped to contribute to the instantaneous reserve. In this case, with an appropriate control of wind turbines, throttling of renewable energy systems, the use of rotating phase shifters, storage systems, or must-run power plants, instantaneous reserve can be provided. By implementing a frequency control in wind turbines, they would be able to provide instantaneous reserve by dumping rotational energy, being this option the most efficient alternative (Rehtanz et al., 2014). Alternative providers already

4 In a heat-driven CHP plant, the heat production is optimised, while electricity is only a sub-product. An electricity-driven CHP plant can vary the active power output according to the electricity needs, while the heat is only a sub-product which creates no restrictions to the whole unit.


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available in the flexibility markets include balancing energy pools, comprising biogas plants, emergency electricity generators and large-scale batteries, as well as particularly energy-intensive industrial companies with flexible loads. Other alternative providers which have the fundamental capability to provide balancing energy include remote-controlled wind turbines or photovoltaic systems, and smaller generation systems (e.g. small-scale CHP plants) and loads (e.g. connection of flexible electricity loads).

Voltage control, congestion management and optimisation of grid losses is mainly dependent on the reactive power control capability of the grid-coupling technology, but also on the active power control capability of the DER unit. Inverter and distributed generation (DG)-coupled storage units show a very good reactive power control capability. This capability is lower for DFIG-coupled units because they have a lower range of reactive power control. Finally, IG-coupled units have no reactive power control capability, but partly an active power control capability which gives them a capability of lower quality, but not for heat-driven CHP units. Due to the increasing transport distances and international power transit, the demand for reactive power in the transmission grid will increase significantly by 2030. With the increasing fluctuating feed-in of renewable energy and the increasing use of underground cables, the demand for regulating reactive power, and thus voltage, is growing to prevent violations of the permitted voltage range. The optimisation of voltage control by providing reactive power from decentralised generation systems at all distribution grid levels must be assessed.

Islanded operation requires the capability to control active power, reactive power, voltage and frequency. Active power control is not possible with heat-driven CHP plants. In contrast, electricity-driven CHP plants show very good active power control capabilities. These are less good in case of intermittent resources, i.e. PV systems, wind and hydro power plants, because they show a lower availability and primary source fluctuations. Anyhow, active power control is possible, particularly if integrated in virtual power plants. IG-coupled DG units do not have islanded operation capability because they cannot control reactive power and voltage. The other grid coupling technologies are capable to control reactive power and voltage, whereas the capability is lower in case of DFIG-coupled wind turbines. While DFIG-coupled and inverter-coupled DG units can define the frequency directly, SG-coupled units need a speed control. Distributed storage is mostly designed for islanded operation for uninterruptible power supplies. In contrast, loads can only support islanded operation by their active and reactive power control capabilities. DER are particularly suitable for islanded operation due to their load-near location.

Black Start needs the same control capabilities as islanded operation. In addition, it demands for a grid-independent system start. This is possible for the same DER units if the necessary storage support is assumed to be implemented and the inverters are assumed to be self-converting and not grid-converting.

In the SmartNet project (Julien Le Bault et al., 2017), a qualitative analysis regarding the capability to provide system services by different DERs was performed. The analysis was carried out for both the current and the expected situation by 2030, considering the evolution of technologies and requirements for the system services provision. Figure 8 shows the qualitative mapping at the 2030 horizon; the colour green indicates good technical capabilities, while red indicates no capabilities to provide the indicated system services. Some of the main conclusions drawn from this analysis are summarised in the next paragraph.

The best resources to provide frequency control services are the storage systems, which have high performances and less constraints with respect to other resources. CHPs and industrial shiftable loads show high performances due to the thermal storage system and the good monitoring and control (industrial processes). Wind turbines, photovoltaic, EVs and curtailable loads have lower performance for long-duration system services due to lower predictability. The shiftable loads (wet appliances) are more suitable for long-time horizon services, due to the latency of the response. Regarding TCLs, they can provide quite good capabilities from fast system services (FCR) to longer duration system services (FRR and even RR in some cases), which is linked to the thermal inertia. In general, loads are not well-suited for voltage control services as they do not provide the mechanisms to change their reactive power output.


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Figure 8: Capabilities of DERs to provide future system services (Julien Le Bault et al., 2017)


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4. Characterisation DER capabilities

This section aims to provide an analysis and characterization of the different flexibility types found within the applications and processes behind electricity consumption. This will prove useful in understanding where is to be expected significant contribution to system services. While section 3 discussed the different types of DER and their characteristics, this chapter aims to go a step further and characterize the processes involved in each of these DERs. In particular, the aim is to understand how energy is really consumed in order to make a solid hypothesis about whether that consumption is really available to provide ancillary services for DSOs and TSOs.

The analysis will be focused on the largest consumer categories, since these are the most likely to present latent flexibility within their consumption.

The analysis of any type of demand is a complex task, which requires a good structuring to be able to handle all the required information. In this report, the work is partially based on the DER categories defined in the SmartNet project (Mario Dzamarija et al., 2018):

Atomic loads, which include the loads with a fixed load profile and which can only provide flexibility by shifting their start time or by replacing the scheduled load profile with an alternative profile. Once started, atomic loads cannot be paused or interrupted. Many industrial processes and wet appliances fall within this category and are often also called shiftable loads.

Thermostatically-controlled loads (TCL) refer to electric loads linked to thermal needs, such as air conditioning systems, heat pumps, water heaters, electric heaters, etc.

Curtailable load, which include loads that can be curtailed without any rebound effect, such as lighting, etc.

Curtailable generation include the generation units that can only be flexible by reducing the production, i.e. RES systems, such as wind, PV and run-of-river hydro power.

Storage systems, which include both stationary systems (BESS and pumped hydro) and EVs.

The grouping of DER categories was very useful to simplify the aggregation, bidding and disaggregation process in SmarNet and has been very useful to quantify the demand response potential in CoordiNet, as shown in chapter 5.

Although less critical for the different types of generation units and storage systems, these categories facilitate the characterisation of electricity load on the consumption side. This way, industrial loads can be divided into process loads (the ones affecting the industrial activity as such) and non-process loads (such as space heating, lighting, etc.), and the process can be applied to different industrial sectors.

The objective of this approach is to understand how the energy is consumed in different sectors and, thus,

be able to evaluate the demand response potential for each of them.

Table 5 recalls the information in section 3.1 about the main types of consumers and their expected consumption/generation from 2017 to 2030 for the two selected scenarios. On the consumption side, it is worth highlighting that these few actors represent almost 85% of the projected load in 2030. This table summarizes the information from the consumer segments that will be used going forward, as well as the data regarding renewable generation and storage.


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Table 5: Summary of 2030 expected energies in two scenarios

A review of the main generic energy flowcharts and description of the industrial processes involved in the selected energy-intensive industries has been carried out.(Edelgard Gruber et al., 2008, Yeen Chan and Ravi Kantamaneni, 2015, Samuel Thomas, 2018 and “Static Sankey Diagram Full Sector Manufacturing (2014 MECS) Department of Energy,” n.d.)

Furthermore, the patterns for consumption in the residential and tertiary sector have also been reviewed. For that purpose, several papers regarding different ways and methods to classify demand and qualify/quantify demand response potential have been analysed. Particularly remarkable is the approach proposed by Pierluigi Siano in demand response and smart grids (Siano, 2014). It is based on a survey where a top-down approach on consumers’ categories is introduced and the main consumption process for each of them is described.

In order to analyse the different types of loads served in each type of consumer and, given the wide-variety of consumers considered, the loads were grouped into different clusters (process heating, motors, lighting, HVAC…), with the aim to deal with two main issues:

The lack of information and transparency. There is little literature on how precisely industrial processes consume energy and how ‘flexible’ these processes are. In general, industries are very wary of sharing this information and only gross estimates with a limited level of detail are provided. Therefore, information from EU and USA have been used.

The complexity. Given the large variety of industrial processes, applications and constraints, the large amount of process counts would make the complete enumeration exercise of the consumption processes an impossible task. Instead, a categorisation provides enough level of detail to perform a high-level analysis and allows deepening, if needed, within each category for each specific industry or actor.

Based on the available information, the wide-variety of electricity consumption purposes have been split in two main categories: Process and Non-process related. This first distinction is made as a consequence of the critical difference in terms of comfort and demand-response type. For instance, non-process load can be expected to be more prone to curtailment, whereas 24/7 industrial process load is expected to offer only very limited participation.

We discuss below the assembled electricity uses behind these two main categories, which will be used in our analysis further on.

2017 CAGR 15Y CAGR 10Y CAGR 5Y


TWh % % % % % TWh TWh

CONSUMPTION

Iron & Steel 115 -2.2% -3.6% -0.6% 0.5% 0.2% 123 118

Chemical and Petrochemical 184 -1.5% -1.8% 0.6% 1.2% 0.8% 215 204

Machinery 124 5.1% 0.8% 0.2% -0.2% -0.7% 121 113

Food, Beverages and Tobacco 118 2.5% 1.0% 0.9% -0.7% -1.2% 108 101

Paper, Pulp and Printing 117 -2.9% -4.4% -1.1% -0.7% -1.1% 107 102

Commercial and public services 837 4.4% 1.2% 0.0% 2.5% 1.3% 1153 989

Households 808 1.5% 0.0% -0.6% 0.4% -3.0% 851 544

Total analysed 2302 2676 2170

%age of Total 82% 85% 82%

RENEWABLE GENERATION & STORAGE

Wind 344 6% 6% 770 750

Solar 114 7% 8% 275 300

Storage 0 - - 38 20

Total analysed 458 1083 1070

%age of Total 16% 34% 40%

Expected CAGR to 2030 Consumption by 2030



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Process-related uses:

Heating: This relates to all electricity consumption designed to generate heat for a process purpose, such as conventional electric heating (boilers and induction), furnaces and ovens, dryers, kilns, etc.

Cooling: This category includes the process-related cooling and refrigeration such as refrigerating process. It is removal of heat, usually resulting in a lower temperature and/or phase change.

Motors: Those machines which are typically 24/7 and generate spin with torque, such as pumps & compressors, fans & blowers, cranes, conveyors, etc.

Process-specific: Lastly, there are some processes which do not fall in the previous ones and are intimately linked to a specific process, such as electrolysis, electric arc furnaces and so on.

Non-process-related uses:

HVAC: Within the non process-related, the main category is the heat-ventilation and air-conditioning (HVAC).

Lighting: The studied category is the use of electricity for lighting purpose.

Other: Lastly, there is a difference between the explained consumption and the total consumption. This difference is assigned to the category “other”, although it will not be used for the analysis. This includes for instance the use of office equipment (e.g. computers), appliances, etc.

Table 6 presents some examples of final uses of electricity within these categories, and this the three main consumption sectors considered (industry, household and tertiary) for illustration purposes:

CONSUMPTION SECTOR CLUSTER HOUSEHOLD TERTIARY INDUSTRY

HEATING space and water heating heating

Furnace/ kilns/ ovens/ dryers / steam boilers

COOLING food preservation commercial refrigeration cooling & refrigeration

MOTORS pumps / fans / blowers / compressors / motors

pumps / fans / blowers / compressors / motors

PROCESS-SPECIFIC

Washing, cleaning, cooking Washing, cleaning, cooking Electrolysis, electric-arc-

furnaces, etc.

HVAC space and water heating, air conditioning and ventilation

space and water heating, air conditioning and ventilation

space and water heating, air conditioning and ventilation

LIGHTNING lighting Street and office lighting Street, factory and office lighting

OTHER TV, audio, computers TV, audio, computers TV, audio, computers

Table 6: Process examples in selected consumer segments

Large industrial consumers are typically those who enjoy the most favourable position to deliver demand response due to their energy-markets expertise (sometimes acquired by direct participation for their own procurement arrangements). However, methodological perspective, the same characterization of clusters can prove useful for defining consumption in tertiary and household sectors as illustrated in Table 6.

Figure 9 presents the characterisation of consumption in the tertiary sector whereas Figure 10 below presents analogous analysis on the household sector. The information from the main industries, tertiary sector and households is grouped into the clusters presented above and summarised in Table 7.


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Figure 9: Breakdown of the Tertiary sector consumption for EU (Paolo Bertoldi and Bogdan Atanasiu, 2009)

Figure 10: Breakdown of Households sector consumption for EU (Paolo Bertoldi and Bogdan Atanasiu, 2009)

By applying the shares of consumption per cluster to each main consumption segment (main industries,

tertiary sector and households) presented in Figure 9 and Figure 10 to the expected consumption from each segment in the 2030 scenario, the share of electricity consumption per type of consumer and cluster can be calculated, as shown in Table 7.


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This will be useful as the consumption flexibility is expected to be a function of the nature and purpose of the consumption itself, as will be explained further below. Therefore, no attempt is made to analyse the flexibility within the industrial or tertiary or household sector as a whole; instead, a bottom-up approach is used to examine the actual suitability and likelihood of providing real flexibility within each of the processes which are performed behind the meter of each of these segments.

Table 7: Estimated consumptions by use in the main sectors (own elaboration)

Applying the coefficients in Table 7 to the estimated consumption from different sectors and industries in 2030 presented in Table 5, the estimated consumption in energy terms per process type and sector / industry are obtained. This estimation is complemented by an analysis of the participation from renewable generation and energy storage. For renewable generators, it is assumed that there is a large amount of energy from renewable assets which are either technologically old or coming from subsidized schemes which are not fit to provide the required flexibility by DSOs or TSOs. Instead, only the increase in energy between 2017 and 2030 is considered to be flexible, which implicitly assumes that all new built capacity is technologically capable of offering system services and, most importantly, all such capacity is in full or aligned with market-parity, i.e. there is no energy-based incentive bias in their economic dispatch decision, such as feed-in-tariffs or feed-in-premiums. These premiums not only distort the dispatch decisions of these assets; in doing so, these assets might have an incentive to produce even at negative prices, thereby causing further grid issues.

The results from this exercise are presented in the Table 8 and Figure 11 for both Scenarios 1 and 2. This

table presents the estimated 2030 consumption and generation (from main consumers / renewable generators) in a different ways splitting the consumption first in process and non-process related and furthermore, within each category, into the main categories of consumption. This provides a view into the expected use of electricity in 2030 by the actual use of that electricity; i.e. to produce heat or cooling, for spinning motors, for HVAC convenience, lighting, etc.

This first step into quantifying the total amount of energy coming/ending in different segments and processes is necessary to further develop the analysis and estimate the actual response capacity from the system as a whole. Next chapter will describe and propose a methodology to estimate the amount of response resource behind each of these segments.

Heat Cooling Motors Process HVAC Light Others

% % % % % % %

Iron & Steel 35% 0% 40% 10% 10% 5% 0%

Chemical and Petrochemical 5% 5% 60% 15% 15% 0% 0%

Machinery 5% 30% 55% 0% 5% 5% 0%

Food, Beverages and Tobacco 5% 30% 55% 0% 5% 5% 0%

Paper, Pulp and Printing 5% 0% 85% 0% 5% 5% 0%

Commercial and public services 5% 5% 5% 5% 40% 15% 25%

Households 15% 5% 0% 5% 60% 10% 5%

source: DG Energy 2012 data, contrasted with 2014 data from U.S. Department of Energy and Our New Energy own analysis

PROCESS NON PROCESS


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Table 8: Estimated consumptions in two different scenarios for 2030 by the main types of consumers

Figure 11: Composition of consumption in 2030 in main process clusters

Heat Cooling Motors Process HVAC Light Others Generation

TWh TWh TWh TWh TWh TWh TWh TWh

Scenario 1

Iron & Steel 43 0 49 12 12 6 0

Chemical and Petrochemical 11 11 129 32 32 0 0

Machinery 6 36 66 0 6 6 0

Food, Beverages and Tobacco 5 32 59 0 5 5 0

Paper, Pulp and Printing 5 0 91 0 5 5 0

Commercial and public services 58 58 58 58 461 173 288

Households 128 43 0 43 510 85 43

Wind 426

Solar 161

Batteries 38

TOTAL 256 179 452 145 1033 281 331

Scenario 2

Iron & Steel 41 0 47 12 12 6 0

Chemical and Petrochemical 10 10 122 31 31 0 0

Machinery 6 34 62 0 6 6 0

Food, Beverages and Tobacco 5 30 55 0 5 5 0

Paper, Pulp and Printing 5 0 86 0 5 5 0

Commercial and public services 49 49 49 49 396 148 247

Households 82 27 0 27 326 54 27

Wind 406

Solar 186

Batteries 20

TOTAL 198 151 423 119 780 224 275

PROCESS NON PROCESS


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5. Quantification of feasible flexibility potential from DERs

This chapter quantifies the feasible potential of demand response from DERs in order to identify and quantitatively assess what can be expected from each and every market participant, and to test the capabilities from selected DERs during demonstration experiences.

In order to characterise the flexibility embedded, in the particular operation from certain assets, the nature of such operations needs to be understood, which is the main objective of this chapter.

5.1. Methodology

On the consumption side, electricity (and energy in general) is mainly consumed to be transformed into other sorts of energy to satisfy a purpose in a given process. Henceforth, the concept of process discomfort, which means the cumulative stress in a given operation derived as a consequence of the flexibility provision to the grid, will be often used. From a flexibility characterisation approach, two types of processes can be distinguished:

Continuous processes, which represents an ongoing and rarely interrupted streamlined process. Ideally, it could be approximated to a 24-hours/day and 7 days/week consumption, in a high degree of steadiness. For example, lights and closed-circuit TV in a logistic centre, pumps and fans in a blast furnace or a refinery, electrolysis, phantom loading from transformers, mobile network antennas, data processing centres, etc. are included in this category. However, only few processes are absolutely continuous and, hence, not flexible. An approximation is made and some processes are considered as continuous when they really are not. For instance, HVAC is not strictly continuous, however, given the high degree of up-time, can be closely approximated to a continuous process. Continuous processes, from a flexibility point of view, are interesting as they typically represent an important portion of the base-load consumption in Europe. Their flexibility provision methods can be categorised as follows:

o Modulation: The best example is the flexibility available in TCLs, which are basically those loads that can be easily modulated by changing a setpoint parameter. Thereby, TCLs can offer flexibility to the grid causing a minimum discomfort to the process.

o Curtailment: When the underlying process is not critical and/or the impact of electrical consumption can be mitigated in one way or another, the flexibility could be provided by curtailing the consumption in a short time period. Only small curtailment rates can be approximated, since their impact needs to be ‘absorbed’ by the process with little or no rebound effect. It must be noted that large curtailment rates represent a hardship halt to the processes, thereby causing significant operational discomfort. For example, many European countries use the curtailment option as the only source of demand-side flexibility accepted by grid operators. The majority of modern curtailable loads are excellent for the provision of very fast balancing services, although they also have significant limitations. For instance, some loads may have limited possibilities to increase their consumption (or the achievable benefit is not attractive enough for the consumer).

Batch processes: In contrast to the continuous ones, the batch processes take place in a non-continuous manner, either for logistical reasons (e. g. loading/unloading is needed), process requirements or actual need for such process. Examples in this category include wet appliances, cooking, some chemical processing, electric arc furnaces, etc.

The typical and inherent provision of flexibility from this sort of processes is derived from a delay or advancement in the schedule of a given batch, hence, there is a load shifting action (e. g. delaying by X minutes the batch of a 110 MW electric arc furnace in the secondary metallurgy). In general, when the shifting times are small, the process disomfort rate is rather low.


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In summary, the following categories of flexibility available from distributed energy resources have been defined:

Load modulation: From quasi 24 hours/7 days continuous processes.

Load curtailment: From non-critical continuous processes.

Load shifting: From batch processes with the ability to shift the time of consumption.

Next sections focus on the different segments of DERs, especially differentiating between the generation

and consumption side.

5.2. Generation

Generation technologies are generally assumed to provide certain degree of flexibility to the grid. In this regard, some remote and/or insular systems can be still found to rely solely on distributed conventional generators. These can include gas and oil-fired engines and combined cycles, as well as small hydropower plants.

Conventional generators typically transform dynamic energy into electricity by means of spinning generators (alternators). This generation method offers numerous advantages to provide flexibility to the grid in various ways, depending on the technology of the asset itself. Basically, the first electric grids were built based on the idea that generators would be the sole responsible to offer most of the flexibility required by the grids.

The above-mentioned consideration was modified with the penetration of intermittent renewable energy resources, whose availability depends on the renewable resource at every single moment, and, thus, their scheduling and management capabilities are much lower than those of conventional generators. Until recently, the provision of flexibility from renewable resources was considered ineffective because the curtailment was the only available option and the actual resource/load at any given time was unknown, since large communication infrastructure was required. Nowadays, the participation from variable renewable energy resources is not only approved as feasible, but in some cases, it is imposed by the grid codes, proving that renewable generation deployment can also be part of the solution.

Energy storage: The game-changing technology of the next two decades will certainly be the energy storage. It will be available in different ways and places, such as stand-alone, utility-scale storage units connected to the high-voltage network, coupled to renewable energy systems (typically solar PV) and in homes by means of the introduction of electric vehicles and adoption of vehicle-to-grid technologies.

5.3. Industry

From the dataset of pan-European industries as represented by Eurostat and shown in Figure 4, only a subset of them will be analysed in order to balance accuracy of the results provided and the required time and effort.

Thus, the consumption patterns from five energy-intensive industries (i.e. iron & steel, chemical and petrochemical, machinery, food-beverages & tobacco and pulp & paper) plus the tertiary and household sectors have been analysed. These sectors amount altogether the 82-85% of forecasted consumption by 2030. Furthermore, the consumption by different processes has been analysed for each of these sectors.

As it was indicated previously, the flexibility available in the different consumption processes can follow several patterns:

Load modulation: From quasi 24/7 continuous processes

Load curtailment: From non-critical continuous processes

Load shifting: From batch processes with the ability to shift the time of consumption.


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On the other hand, and as it was already defined and developed in section 4, the clusters have been categorised as follows:

Process-related clusters: o Heating o Cooling o Motors o Process specific

Non process related clusters: o HVAC o Lighting o Others

Lastly, the flexibility patterns need to be mapped in order to characterise the flexibility potential from each

cluster of consumption. Some findings are briefly described below:

Heating and cooling: From previous definitions (see section 4), the heating and cooling activities seem to be ‘typical’ load modulation candidates. Specifically, these loads are called Thermostatically-Controlled Loads, since they rely on the flexibility of the temperature set-point, to advance or delay the energy consumption for heating (or cooling), thereby using thermostatic inertia of the system and its tolerance as a source of flexibility. Due to the thermal mass that is intrinsic to the TCLs (and in particular, to heat-pump-based technologies), there is flexibility that can be offered for different purposes. The suitable system services that can be offered by TCL will heavily depend on the thermal mass and the utilization of the TCL. In the most simplistic way, TCLs can be considered as a pure resistance used for transforming the electricity to heat (although some of them, e.g. HVAC, make use of compressors, but they are not equipped of any control allowing a reactive power regulation). Therefore, it is envisioned that TCLs are not suitable for providing system services related to reactive power. The system services related to provision of active power in the time range of seconds to hours are likely to be the most in the capability spectrum of TCLs.

Motors: These activities represent the electrical consumption from automation (e. g. conveyor belts, pushers, mills, etc.), spinning machines (e. g. blowers, fans compressors, etc.) and other categories such as cranes, crashers, etc. Their flexibility provision follows a load modulation kind, as they present a very high uptime (refineries and chemical industry, metallurgy and mineral processing). Two main reasons make necessary to differentiate these loads from the previous ones:

o The participation of these engines to the overall process is typically on a secondary row, which renders them as ‘accessory’ processes, which means that, a given delay or malfunction in any of these, would yield fatal consequences to the operation. Therefore, the discomfort rate from the use of this flexibility is highly sensible. However, and precisely because of their secondary role, these processes can represent a curtailable load in certain applications, such as in the quarrying business or highly automatized factories (e. g. the automobile manufacturing).

o The number of assets actually involved in these processes is much larger than those involved in the heating/cooling. Consequently, the management of the overall system is relatively complex, and their aggregation, activation and response verification arrangements can be rather costly compared to the benefits. An additional barrier is the lack of knowledge from the users and owners of these resources about the shedding possibilities.

Process specific: This is a particularly difficult segment of processes, as they can differ largely among industries and, hence, do not fall particularly in any of the above categories for a particular reason. In order to illustrate this variety, two electrical applications included here are described below:

o The chlorine production industry: In the membrane process route, the use of electricity represents a specific process itself. This is a process running 24 hours/7 days, as the current running through the membranes is monitored to be as steady as possible to avoid the effect of bending the membranes, which could derive in a malfunction/breaking of these very costly pieces. Electrolysers can be approximated as a modulable load.


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o The secondary metallurgy: The consumption from electric arc furnaces represents a specific process. The electric arc is used to generate current within the scrap causing heat that melts the scrap. These furnaces are to be regarded as shiftable loads.

HVAC: This non-process category is very similar to the TCL discussed above for the process heat and cooling. However, there is further system flexibility and tolerance and less discomfort rate in this category, as it is not a critical function. Thereby, it is estimated that a higher share of flexible load is available from HVAC than from heating/cooling processes.

Lighting: Provided that on a 2030 scenario there is a high penetration of LED lighting, the fast and continuous controllability of modern LEDs makes them a good example of curtailable loads, especially given their extreme fast response, large amount of assets and lack of rebound effect.

Others: Other uses of electricity are so variate that an argument to determine their characterisation or degree of flexibility cannot be easily found. Therefore, these additional uses of electricity will not be considered within the pool of potentially interesting sources of flexibility.

In view of the explained above, Table 9 approximates each cluster of consumption to the specific flexibility patterns providing also the expected degree of flexibility:

Modulation Curtailment Shifting

Heating & Cooling TCL model with a

moderate degree of flexibility

n/a Low degree of flexibility

is assumed

Motors

(or modulable load)

Low degree of flexibility

Limited application in some industrial

processes and non-core applications.


n/a

Process specific

In some industrial processes (e.g. chlorine

production)

Moderate degree of flexibility.


In some industrial processes (e.g. electric

arc furnaces)

Moderate degree of flexibility

HVAC Moderate degree of

flexibility n/a n/a

Lighting High degree of

flexibility n/a n/a

Table 9: Suitability for the provision of different flexibility methods from different clusters

5.4. Tertiary and household sectors

The tertiary and household sectors are described together below, since both their level of energy consumption and their intrinsic flexibility characteristics are very similar. As it has already been mentioned in this report, these sectors are characterized by presenting the lowest degree of available and reliable information. Their management capacity should be exploited, as they have big potential for energy savings. This potential should be based on the improvement of energy use habits and/or the introduction of energy efficiency systems, and especially through the development of demand response programs and the adoption of a market design and regulatory environment which incentivise the expansion of the role of flexibility aggregators.


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In these sectors, the non-processes related clusters (HVAC and lighting) are the most relevant ones. Depending on the type of installation, the type and use of energy, the consumption varies considerably. It must be noted the great number of variables affecting the consumption in these sectors; climatology, habits of each environment (e. g socioeconomic characteristics of the holder, opening and closing hours of shops, opening and closing hours of the company, etc.), logistic set-up, etc. are variables that considerably affect consumption. Therefore, the proposed values have to be considered just as a reference value.

The values differ significantly within the service sector, where the use of energy can be very different. For example, in offices, the consumption is mainly due to computer equipment, lighting and air-conditioning system, whereas in sport centres, a large part of the energy is used to heat the water in swimming pools and space heating, etc.

Henceforth, in order to quantify the consumption from these sectors, the concept of wet appliances (i.e. non-interruptible, atomic loads, such as washing-machine, dishwasher and dryer) is used. For system services, such as frequency and voltage support, the control of the flexibility resources has to be fast and automatic and this is currently impractical for the aforementioned loads. In the future, with the absence of market barriers and with the increase in appliance automation, flexible domestic appliances may be useful to help balance the power system. It should be noted that the cheapest energy and the only one that really does not pollute and is not detrimental to the system is the one which is not used. Therefore, it will be essential to raise the awareness of the users that certain habits involve an unnecessary consumption of energy. Moreover, designers and constructors must be aware that a building equipped with automated and thermally-insulated elements will need lower energy consumption.

5.5. Quantitative Analysis

In the literature review performed, only a few attempts to quantify the demand response potential from the consumption side have been found and these estimates vary largely across scenarios and papers. For instance, the report (DG Energy, 2016) evaluates the potential response from distribution-connected assets and it is considered that there is a maximum theoretical potential of up to 28% of the peak load, versus a 6% in the business as usual scenario. Moreover, a limited number of models have tried to provide quantitative support in characterising and qualifying the load curves from consumers and/or their processes. The main objective of these models was to derive demand response potential, but only a relative success was achieved. These wide ranges exemplify the difficulty in assessing properly and efficiently the actual level of availability DER resources.

The analysis performed in (McKenna et al., 2018) discussing the importance of modelling DERs properly deserves special attention. In this paper, the main flaws in five selected numerical approaches are discussed aiming to model and quantify the amount of flexibility in residential load profiles. It also argues the importance of considering the discomfort of demand response throughout the demand-response study, from modelling to policy-making. This consideration is further supported by the experience from some professionals based on their attempts to enable flexibility from different large energy-intensive industrial players. Furthermore, the responses to the questionnaires (as will be shown in chapter 6 and section 8.5), served as a first benchmark for developing the quantification: Participation to demand-response programs has to be seen in the light of the cost/reward for the participant, where the cost bit is mainly affected by the discomfort it creates to the participant. Hence, reward sensitivity and discomfort factors are important elements to consider.

Considering the above, the classification of consumption processes from section 4 proves to be increasingly useful, as it allows for distinguishing between core and non-core processes, which should feature a degree of correlation with the degree of discomfort from participation to demand response programs. Given that the European experience in demand response is rather limited and recent, the experience from the US (Doug Hurley et al., 2013), where demand response programs count with over a decade of existence, was also reviewed.


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Another very interesting point raised by the authors in (Earle et al., 2009) is the definition of the Load Duration Curve, which illustrates the rather limited requirement of extreme response resources. In their example, only 1% of the hours amounted to 11% of the peak-load. This is especially interesting because, as argued in their paper, small amounts of demand response are cheaper, more effective and reliable sources than greater and greater amounts of it, mainly because of the above-mentioned discomfort factor. An index of the Loss of Load Expectation (LOLE) measures the expected number of loss of load within a year and cited as a target standing at 2.4 hours per year (i.e. a given appliance should be expected to contribute 2.4 hours per year on average as a response to the system).

Empirical data from the US suggests that demand response can contribute to shed about 2-10% of each region’s annual peak demand. Saving the existing differences between systems and market design, the conclusion is that demand response has the capacity to meaningfully contribute to the operation of the system. Moreover, its actual deployment could be achieved by a number of ways, such as direct or indirect programs, energy or capacity payments (directly or via aggregators), etc.

At this point, it is important to remind the important difference between resources and reserves:

- Demand response resource refers to how much actual capacity to respond can be found in DERs, provided that an economically acceptable proposal is in place.

- The reserve is the amount of resource that is economically viable in a given scenario where policies and market design are given.

Therefore:

- The amount of resource is independent of the actual policy status but varies according to electrification, penetration of electro-mobility, deployment of micro CHPs and heat-pumps, etc.

- The amount of reserves is conditional to the same factors as the resources, but there are additional factors which are specific to a market design situation in a given point of time and market. As a result, the amount of reserves is naturally lower or equal to the amount of resource in a given moment and geographic scope.

Attempting to quantify the amount of DR reserves is therefore a highly complex exercise, as well as futile in a 2030 scenario. Numerous changes will impact the market design, industry documents, regulations and other elements. Instead, the remainder of this chapter tries to discuss the potential quantification of demand response resources, which depends exclusively on factors already discussed above and on the two scenarios provided. In order to quantify those resources, a scoring methodology based on the main factors influencing the expected adoption of demand response has been followed, namely:

- Suitability: More response from those resources which are better suited to perform the response required is expected. For example, keeping all the remainder conditions stable, more response from flexible battery storage systems is expected than from core industrial process. The analysis shown in Figure 8, capabilities of DERs to provide future system services, have also been taken into consideration.

- Comfort: More response from resources whose participation produce the least discomfort should be expected, since that serves two purposes; it lowers the requirement for economic incentive and eases the process overall (i.e. the less discomfort it creates as a deviation from a given base-line, the easier it should be to accept and implement it). Furthermore, an intuitive link between a low degree of discomfort and a low degree of required economic incentive to activate flexible resources can be established, as this can be interpreted as reduced system efforts, lower rebound effect or process rescheduling.

- Industry Size: More response from industries / processes which represent more volume in the system shall also be expected, as they shall provide a larger array of opportunities to respond.


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- Granularity: The scope of this analysis covers large energy-intensive industries as well as households, sitting at the extremes of the size per single DER. However, there is one more factor that explains the actual size of the DER, besides the industry size, which is the level of granularity in that segment. This could be understood as the number of actual DERs which fall within a given segment. For instance, the petrochemical industry is characterised for grouping only few very large sites; however, the food and beverages industry presents a much larger number of sites which operate independently. This is relevant because the larger the number of DERs, the larger the population of potential respondents, therefore higher probability to find a subject within that segment which will actually respond to an opportunity or programme.

Next tables, from Table 10 to Table 13, score each of the processes according to these factors with a grade between 1 and 4, being 1 the least prone to offer demand response and 4 the most adequate for participating in demand response. This is a rather subjective exercise, so, these scores should be considered just as a proposal that could be used as a basis for discussion and testing during the test pilots in CoordiNet.

The proposed evaluation of these factors is as follows:

- Suitability:

Table 10: Proposed scoring of DERs according to their suitability

- Comfort:

Table 11: Proposed scoring of DERs according to their level of comfort

Heat Cooling Motors Process HVAC Light Generation

SUITABILITY

Iron & Steel 2.0 2.0 1.0 3.0 3.0 4.0

Chemical and Petrochemical 2.0 2.0 2.0 3.0 3.0 4.0

Machinery 2.0 3.0 2.0 2.0 3.0 4.0

Food, Beverages and Tobacco 3.0 3.0 3.0 2.0 3.0 4.0

Paper, Pulp and Printing 3.0 3.0 4.0 2.0 3.0 4.0

Commercial and public services 2.0 2.0 2.0 2.0 3.0 4.0

Households 2.0 2.0 2.0 2.0 3.0 4.0

Wind 4.0

Solar 4.0

Batteries 2.0

PROCESS NON PROCESS


COMFORT

Iron & Steel 1.0 1.0 1.0 2.0 3.0 3.0


Machinery 2.0 2.0 1.0 2.0 3.0 3.0




Households 2.0 2.0 2.0 2.0 3.0 3.0

Wind 4.0

Solar 4.0

Batteries 4.0

PROCESS NON PROCESS


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- Size:

Table 12: Proposed scoring of DERs according to their size

- Granularity:

Table 13: Proposed scoring of DERs according to their granularity

The next logical step in this scoring exercise is to weight each of these factors to get a comparable result amongst different potential flexibility providers. With that aim, a simple weighted average with self-proposed coefficients has been calculated (the proposed formula is a normalization of the score between zero and one rather than the weighted average). Those coefficients are subjective and subject to review and calibration based on future experiences and inputs. Given the scoring mechanism followed, a scoring formula that will yield a result in the [0,1] range by assigning weights to the various aspects scored above is proposed. The resulting formula can be seen below:

𝑆𝑐𝑜𝑟𝑒 =30% 𝑆𝑢𝑖𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦 + 30% 𝐶𝑜𝑚𝑓𝑜𝑟𝑡 + 20% 𝑆𝑖𝑧𝑒 + 20% 𝐺𝑟𝑎𝑛𝑢𝑙𝑎𝑟𝑖𝑡𝑦 − 1

3

This formula allocates the heaviest weight on the suitability and comfort, which are intuitively the major drivers for techno-economic feasibility of participation to system services. In a second level, the remaining weight is distributed between size and granularity, which are expected to have some degree of influence. Therefore, heavier weights have been applied on those parameters considered as main-drivers which should have a larger impact in a first approach, rounding up with those that may play a residual role.


SIZE

Iron & Steel 1.2 0.0 1.6 0.4 0.4 0.0


Machinery 0.0 1.2 2.0 0.0 0.0 0.0




Households 4.0 1.2 0.0 1.2 4.0 2.8

Wind 4.0

Solar 4.0

Batteries 1.2

NON PROCESSPROCESS


GRANULARITY

Iron & Steel 1.0 1.0 1.0 1.0 1.0 1.0


Machinery 2.0 2.0 2.0 2.0 2.0 2.0




Households 4.0 4.0 4.0 4.0 4.0 4.0

Wind 3.0

Solar 4.0

Batteries 4.0

PROCESS NON PROCESS


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After applying the proposed formula to the matrices from Table 10 to Table 13, the obtained results for the analysed DERs are shown and scored in Table 14:

Table 14: Total score of DERs according to their proposed weighting formula

The exercise explained above results in a quantitative qualification of the DER ability to perform system

services. Based on these ability values, the below figures are treemap diagrams where the size of each rectangle represents the cumulated score from Table 14. Figure 12 representation is done by industry whereas Figure 13 is done by process

Both Figure 12 and Figure 13 represent a qualification approach, but they are not supposed to represent the

amount of flexibility or response from these segments / processes. These figures may provide a characterisation basis for future developments which could be performed during the demo activities foreseen in CoordiNet.

Figure 12:Treemap of cumulated score on the demand side by consumer segment


SCORE

Iron & Steel 0.1 0.0 0.0 0.3 0.4 0.4


Machinery 0.2 0.4 0.2 0.2 0.4 0.5




Households 0.6 0.4 0.3 0.4 0.8 0.8

Wind 0.9

Solar 1.0

Batteries 0.6

PROCESS NON PROCESS


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Figure 13: Treemap of cumulated score on the demand side by related process

5.6. Additional considerations

As general conclusions, at this point, it can be stated that, in most processes and sectors, there are possibilities for flexibility provision from demand response. Demand response can take different forms depending on consumer volumes and consumption patterns. For example, industrial customers or large commercial customers may reorganize their productions or operations to shift their consumption to lower-price hours. However, there are still many barriers to achieve the development and engagement of smaller scale consumers into demand-response programs. Some of these identified barriers are detailed below:

Regulatory and market barriers: These barriers seem to be the main obstacles to the development of commercially-viable aggregation applications, e.g. establishing clear rules for the technical validation of flexible demand response transactions.

Lack of information from the users' point of view: Customers, especially smaller ones, are not aware of the importance, interest and suitability of participating in demand response initiatives. More transparent information on the subject is needed to be provided by policy makers, regulators, authorities and electricity companies.

Consumption habits: The flexibility potential from consumers is highly dependent on the electrical appliances or devices they have, but also on their habits and, more generally, on their individual preferences.

Social and ethics responsibility: the work shifts could be changed in order to work only during the least congested and cheapest hours, even if this implies night shifts.

Discomfort: For households and commercial and public services, demand response can be achieved by different means, e.g. shifting the use of heating or air conditioning to the non-maximum price hours, delaying the use of washing machines or charging/discharging the electric vehicles according to the hourly prices. However, one of the most important issue to be considered is the willingness from consumers to suffer certain degree of discomfort.

Economic incentives: Attracting small consumers to participate in a demand response programme requires appropriate price signals and tools that are accessible, easy to use and maintained. Demand response will be developed on a large scale when consumers see real value in these services and are therefore willing to get involved in exchange for certain benefits (e. g. discounts, premiums, etc.). These benefits must compensate for the effort to change habits or a certain loss of comfort, as well as to recover investment costs in automation and communications.

Lack of penetration of demand response aggregation as a service: In markets like the UK, the figure of the aggregator is more developed, but they are almost all bankrupt, or bought by large electric companies. The regulation does not 'support' in any way the figure of the independent aggregator yet to avoid the concentration of flexibility on the part of the incumbents.


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6. Stakeholder interviews

In order to be able to acquire, analyze and rely on real and current data, a questionnaire (see annex 8.4) was prepared to understand the willingness of different industries and relevant stakeholders (such as demand response associations or specialists, policy makers, etc) to participate in the provision of ancillary services by means of flexibility. In addition, the questionnaire was also tailored to analyse the barriers and the reasons that may induce companies to join the different demand response services.

Part of the introduction of the questionnaire, was based on the definition of the different products in the CoordiNet deliverables D1.1 (Leandro Lind and José Pablo Chaves Ávila, 2019) and D1.3 (Annelies Delnooz et al., 2019).

The questionnaire was submitted to a total of 19 survey prospects, including: wind, solar and storage associations, associations of different industrial sectors (chemical and aluminium), large industries of different sectors (automotive, steel, chemical, polymer, automotive), multinationals in the communications sector, multinationals in the water and waste sectors, as well as multinationals in the renewable energy sector. Out of the 19 prospective surveys, seven5 completed forms have been received. The participants who have responded to the questionnaire belong to the following segments or industries:

Iron and Steel

Automotive manufacturing

Renewable generation

The European Association for Storage of Energy

Water utility

Manufactured off-site buildings

The full set of answers is shared below in annex 8.5; below, we reproduce a summary of the most relevant answers:

Among the profiles of the interviewees, the automotive sector pointed out that, since the entry of the electric vehicles, they have stopped behaving like a normal industrial factory and they have now a more significant impact on the power system.

Regarding the current participation in the provision of grid services under the current schemes (FCR, FRR and RR), the respondent from the steel industry already participates in the FRC and RR reserves. Another participant replied that energy storage systems typically provide FCR, FRR and RR, depending on whether these services are offered in the market and are open to the participation of storage devices. Storage also offers new system services, such as enhanced frequency response in the UK and system services such as DS3 (EIRGRID Group, n.d.) in Ireland.

Some of the barriers faced by respondents are that the period of subscription is too long for an industry that has low visibility beyond a period of 3 to 6 months, with a remuneration scheme that is usually lower that the remuneration for participating on the balancing and intraday markets, as well as operational (industrial) constraints. Other barriers mentioned in the answers include the following:

Not all Member States tender grid services on the market.

The lack of long-term contracts for system services reduces the long-term investment certainty for storage facilities.

Prequalification, tendering, or availability requirements may prevent storage operators from ‘stacking’ multiple services on one storage device, e.g. providing FCR but also arbitrage, black start, etc.

5 Due to the lack of replies received, the conclusions are not entirely representative.


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Regarding the issue of sustainability and its financing, in general there are no sustainable targets set among the interviewees, apart from the development of as better as possible manufacturing and recycling processes and products. Only in the case of the water supply company, there is a target to have zero net emissions by 2021.

One of the issues on which all respondents agree is that the price of energy affects them significantly. Therefore, the economic incentive from participation to system services would be most welcome measure, as long as discomfort is kept to a controlled minimum.

As for the replies by consumers, their consumption profile is usually quite concentrated in the following categories, which are process loads: Heating/furnaces/dryers/ovens, cooling & refrigeration, pumps/fans/blowers/compressors and process specific (electrochemical, motors, robots, conveyor belts, etc).

On the contrary, the sector dedicated to the manufactured off-site buildings concentrates its consumption in the following clusters, considered non-process loads: HVAC, Lighting, etc.

Rather often, large, energy-intensive industries have or consider having on-site generation solutions. The water utility considered cogeneration and solar PV, while the manufactured off-site buildings thought of solar thermal and solar PV. Their general objective is to be self-sufficient and reduce the demand of electricity from the grid, thanks to a better thermal insulation and on-site generation of electricity for the homes.

With regard to the question of whether the respondents could have flexibility in changing the power consumption profile, almost all (except for the renewable and the utility of water) could have some flexibility. The automobile sector did not send either affirmative or negative responses, so no conclusions can be drawn for them.

When asked about whether these companies could assume a limited number of supply interruptions, only 4 answers were received, out of which only the manufactured off-site buildings could assume them.

In the case of those that are generators, the steel and storage sectors do provide grid services. In the first case, they provide frequency control with fixed remuneration, and, in the second case, FCR, FRR and RR. One of the barriers that the interviewees name for not providing this service is the current legislation. Most of the interviewees also indicate that they are willing to participate in grid services directly or indirectly via upstream aggregators.

For potential future developments, they all agree that they see opportunities to incorporate energy storage technology. All of them (apart from the steel sector) also agree that they see opportunities to incorporate electric mobility solutions. In addition, they all indicate that energy storage will be a crucial parameter for the implementation of demand response and will definitely facilitate every related process.

With regard to the sort of flexibility that the interviewed companies could bring to the grid, almost all of them could bring some or several of the following types: FCR, FRR, RR, voltage control and congestion management. On the other hand, almost everyone agrees (with the exception of storage) that it would be difficult for them to provide black start or inertial response.

The participants in this questionnaire share the view that their participation could occur both directly and indirectly through the ascending aggregators.

To conclude, the main factors that would help interviewees to consider participating in demand response programs are:

Legislative framework.

Remuneration high enough to encourage participants.

Decrease in price for energy storage systems.

Preferential access to the grid capacity to connect renewable generators and storage systems.


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7. Conclusions

This deliverable aimed to characterise and present the potential flexibility from DERs in a way that would allow to quantify its quantification from various market participants in a European scenario in 2030. From

a methodology perspective, a bottom-up approach was followed, focusing on quantifying resources rather than in reserves, as reserves require making additional hypothesis on the degree of economic satisfaction and quantifying in economic terms the discomfort produced by a given response or activation.

Although a wide spectrum of energy consumption in EU was covered, including an industry-level view for

energy-intensive industries, the results highlight the importance of engaging the household and the tertiary sector, as these sectors present a high degree of non-core electricity consumption which, besides representing the largest block of consumption, is a very good candidate for response aggregation. To illustrate this point, about 35 % of the expected response potential identified by the methodology described in this deliverable lies in the tertiary sector and 20-30 % in the household sector (depending on different scenarios).

We analysed the main processes from the largest consumers amounting to almost 85% of consumption, and quantifying the expected consumption by sector, industry and process under two scenarios in for 2030. For instance, it is worth highlighting on the industrial consumption side, the potential response from the different use of motors in all their forms (compressors, fans, conveyors, etc) amounts to 60 % of the consumption and about 60 % of the potential response from the industrial sector.

In this report, the choice of process clustering into process and non-process and further decomposition allowed to define the main DER characteristics and suitability to perform system services which will serve as inputs to ideate a range of transaction models. As a result, the capabilities of DERs to provide future system services was discussed as follows:

Frequency control services: In general, this control (based on active power) can be provided by almost all DER. Renewable generators, such as wind turbines, large PV plants and battery storage capacities, can already be technically equipped to contribute to the instantaneous reserve. By implementing a frequency control in wind turbines, they would be able to provide instantaneous reserve by dumping rotational energy, being this option the most efficient alternative (Rehtanz et al., 2014). Alternative providers already available in the flexibility markets include balancing energy pools comprising biogas plants, emergency electricity generators and large-scale batteries, as well as particularly energy-intensive industries, tertiary sector and households as discussed in section 5. Depending on the product under consideration fast and automatic response are required and therefore only some specific technologies can meet these requirements.

Voltage control, congestion management and optimisation of grid losses is mainly dependent on the reactive power control capability of the grid-coupling technology, but also on the active power control capability of the DER unit. Inverters and distributed generation-coupled storage units show a very good reactive power control capability. Due to the increasing transport distances and international power transit, the demand for reactive power in the transmission grid will increase significantly by 2030.

Islanded operation requires the capability to control active power, reactive power, voltage and frequency within the system itself. Active power control is not possible with conventional technologies (e.g. CHP plants and/or small combustion engines). Active power control is possible, particularly if integrated in virtual power plants. Distributed storage is mostly designed for islanded operation for uninterruptible power supplies. In contrast, consumption loads can only support islanded operation by their active and reactive power control capabilities.

Black Start needs the same control capabilities as islanded operation. In addition, it demands for a grid-independent system start. This is possible for the same DER units if the necessary storage support is assumed to be implemented and the inverters are assumed to be self-converting and not grid-converting.


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As for distributed renewable generators, the analysis anticipates a valuable contribution from wind and solar photovoltaic assets, but only from market-parity assets, i.e. those revenues depend solely on market revenues without the interfering from subsidies, capacity payments, etc.

All in all, the different consumption processes in the main consumer segments were analysed and scored according to four different criteria, namely: suitability, comfort, size and granularity. On the generation side, it was assumed that all newly built capacity from 2017 onwards, which are expected to represent about 25 % of generation in 2030, will be able to provide ancillary services. Based on the scoring methodology proposed herein, an overall scoring formula in the range 0 to 1 (where 0 represents the lesser expected participation to demand response and 1 the maximum) was introduced to provide a simple numeric estimate of the participation from these different actors and processes to system services. DERs showing a score close to 1 (wind and solar generation assets and HVAC / lighting in the tertiary and household sectors) presented the most promising potential especially due to their size and granularity.

Table 15: Total score of DERs according to their proposed weighting formula

From the data, analysis and interviews, it is clear that all actors in the electricity value chain (also on the consumption side) are attentive to changes in technology, business models and regulations. Most players are aware that they have a role to play. Indeed, we found that energy intensive consumers (household / tertiary-segment) would consider having on-site generation solution, if they were proven to be a good investment.

However, the most repeated main barriers for leveraging this dormant flexibility were identified in the literature review and corroborated in the interviews summarised in chapter 6. We summarize them below along with the main identified route of action to cope with each of these:

- Regulatory / legislative framework: On the consumption side, the great majority of players are non-

market experts, thereby lacking the insights, processes and systems to face increasingly complex regulations and costs linked to requirements to comply. The development of the role of flexibility aggregators seem to provide a first approach to a solution to some of the most common and individual issues listed above. Aggregators could play the role of market experts which maximize AS revenue for DERs; aggregators could use portfolio effects to minimize the actual count of activations of DER flexibility; furthermore, aggregators could exploit the synergies from the portfolio effect of wide range of DERs. Facilitate the role / business model for aggregators to limit the number of activations, i.e. reduce / limit the degree of discomfort from participation to these markets

- Market design and remuneration: Current subscription periods for system services are deemed too long and smallest size for participating too high by most prominent demand response potential participants. Furthermore, demand response programmes require appropriate price signals which provide the right benefits that compensate DERs for their loss of comfort, as well as to recover investment costs in automation and communications. As per previous point, fostering the development of aggregators should prove useful in coping with these issues as removes most of the burden from the shoulders of the DERs themselves, placing a capable market expert in front of the market.


SCORE

Iron & Steel 0.1 0.0 0.0 0.3 0.4 0.4


Machinery 0.2 0.4 0.2 0.2 0.4 0.5




Households 0.6 0.4 0.3 0.4 0.8 0.8

Wind 0.9

Solar 1.0

Batteries 0.6

PROCESS NON PROCESS


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8. Annexes

8.1. Analysis of Selected EU Projects

Here we present a detailed analysis of a selection of EU projects relevant to this topic.

8.1.1. Remodece Project

The overall objective of the REMODECE project (“REMODECE Project,” n.d.) is to contribute to an increased understanding of the energy consumption in the EU-25+2 households for the different types of equipment, including the consumers’ behaviour and comfort levels, and to identify demand trends. This project evaluates the potential electricity savings that exist in the residential sector in Europe, and that can already be implemented by existing means, like the use of very efficient appliances or the elimination/mitigation of standby consumption.

The availability of high-quality data is an essential condition for the definition of policy recommendations to influence through a combination of measures the energy efficiency of the equipment to be sold in the EU-25+2 in the next decade, as well as to influence the user behaviour in the selection and operation of that equipment. In this scope, the main objectives of this survey are:

Contribute to an increased understanding of the energy consumption in the EU-25+2 households for the different types of equipment, including the consumers’ behaviour and comfort levels;

Identify demand trends; Evaluate the potential electricity savings that can already be implemented by existing means, like

the use of very efficient appliances or the elimination/mitigation of standby consumption; Analyse the market transformation for different types of equipment; Make policy recommendations for each type of equipment

From this project was resulted a set of policy recommendations for each type of equipment in the residential sector, which can lead to a successful market transformation and the provision of cost-effective energy and carbon savings, addressing both conventional appliances and new fast-growing loads.

The REMODECE project was supported within the Intelligent Energy for Europe Programme of the European community (contract no. EIE/05/124/S12.419657). The kick-off meeting was in January 2006 and the project finished at September of 2008.

8.1.2. GIFT project

GIFT (“Objectives | Gift H2020,” n.d.) is an innovative project that aims to decarbonise the energy mix of European islands. European islands have to abide by the law of their countries that push toward a greener energy mix to comply with the European and international agreements. GIFT is willing to develop innovative systems to allow islands to integrate vast amount of renewables. Through the development of multiple innovative solutions, such as a virtual power system, energy management systems for harbours, factories, homes, better prediction of supply and demand and visualisation of those data through a GIS platform, and innovative storage systems allowing synergy between electrical, heating and transportation networks. GIFT will increase the penetration rate of renewable energy sources into the islands’ grid, reducing their needs for diesel generation and thus decreasing the greenhouse gases emissions directly related to it. For 4 years, the partners will develop and demonstrate the solutions in two lighthouse islands, in Hinnøya, Norway’s largest island and the small island of Procida in Italy and study the replicability of the solution in a Greek and Italian island at the minimum, respectively Evia and Favignana.

Expected Impacts


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Developing renewable energy systems-based systems (including heating and cooling and storage) that are cheaper than diesel generation;

Highly integrated and digitalised smart grids based on high flexibility services from distributed generation, demand response and synergy between electrical, heating and transport networks;

Significant reduction of fossil fuel consumption; Large-scale replication on the same island and on other islands with similar problems; Enhance autonomy for islands that are grid connected with the mainland (existing diesel

generators shall be used primarily as security back-up in the long term); Reduction of CO2 emissions; Improvement of air quality; Renewable energies sector enhancement by encouraging investors and creation of jobs; Socio-economic impacts and green tourism

The start of this project was in January 2017 and the expected end is December 2019.

8.1.3. NatConsumers project

The NATCONSUMERS project (“NATural Language Energy for Promoting CONSUMER Sustainable Behaviour | NATCONSUMERS Project | H2020-EC | CORDIS | European Commission,” n.d.) aims to define different types of energy consumers in the EU and design tailored actions that will lead them to use less energy. Residential energy consumption represents 28% of all EU energy consumption. If commercial buildings are also considered, this percentage increases to 40%, which is equal to 36% of EU CO2 emissions. Changing the consumer behaviour provides an opportunity for considerable energy savings in residential buildings. The key goal of the NATCONSUMERS project is to develop an advanced and integral user-centred framework for the implementation of efficient energy feedback programmes in the domestic area. The approach relies on establishing the complete characteristics of the EU energy consumer, and then designing specific personalised actions, based on the use of natural language and emotional contents, tailored to each of the consumer pattern. In this context, the provision of feedback to consumers has resulted in promising results, achieving savings in the range of 5% to 20%.

The duration of the project was from May 2015 to June 2017.

8.1.4. IndustRE project

Innovative Business Models for Market Uptake of Renewable Electricity unlocking the potential for flexibility in the Industrial Electricity Use.

IndustRE (“IndustRE - Integration of renewable energy through flexible industrial demand,” n.d.) has

identified the flexibility potential of the industrial electricity demand as an opportunity that - through innovative business models - can facilitate further growth and integration of variable renewable energy, while reducing the industrial electricity costs. In this project the electricity intensive industry in Europe works closely with the renewable energy sector in order to find common ground and create win-win situations.

These business models:

Create win-win situations for the involved parties; Support the further deployment of variable renewable energy without dependence on support

schemes; Bring benefits for the power system and the environment; Can be applied in the current market and regulatory framework of the target countries

The overall objective of the project is to use the potential for flexibility in energy intensive industries to facilitate further market uptake of variable renewable electricity, through innovative business models and


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regulatory improvements. In order to achieve this, the work has been structured around the following objectives:

Present suitable business models and facilitate their adoption; Formulate policy recommendations; Quantify the potential benefits for the power system; Move industry and variable renewable energy plant operators into action

The project activities are relevant for all industries in Europe, especially the chemicals, non-ferrous metals, cold storage, steel, and water treatment sectors. These five sectors with 302 TWh/year represent about 10% of the electricity consumption in Europe.

The project work is applicable to all European countries, with particular attention to Belgium, France, Germany, Italy, Spain and the UK. These countries have traditionally had important industrial production and together they represent more than 65% of the EU population and almost 80% of all the installed wind and PV capacity. These figures allow us to balance between a manageable effort of working with 6 target countries and still having an important impact on a European level.

The duration of the project was from January 2015 to December 2017.

8.1.5. GOFLEX project

The GOFLEX project (“GOFLEX - Project,” 2017) innovates, integrates, further develops and demonstrates electricity smart-grid technologies. It aims to enable the cost-effective use of demand response in distribution grids, increase the grids’ available adaptation capacity and support an increasing share of electricity generated from renewable energy sources.

The GOFLEX smart grid technologies deliver flexibility solutions that are both general (across different loads

and devices) and operational (solving specific local grid problems).

GOFLEX supports an active use of distributed sources of load flexibility to provide services for grid operators, balance electricity demand and supply, and optimise energy consumption and production at the local level of electricity trading and distribution systems.

Building on existing, already validated technologies for capturing and exploiting distributed energy consumption and production flexibility, the project develops solutions providing more flexibility for automatic trading of general, localised, device-specific energy as well as flexibility for trading aggregate prosumer energy.

The generalised demand-response services developed in the framework of the project are based on

transparent aggregation of distributed, heterogeneous resources to offer virtual-power-plant and virtual-storage capabilities. The sources of load flexibility include thermal (heating/cooling) and electric (electric vehicles charging/discharging) storages. A backbone data-services platform offers short-term predictions of energy demand/generation, and flexibility in order to support effective data-driven decisions for various stakeholders. Smart-grid technologies, such as increased observability and congestion management, contribute to the platform. The project plans to demonstrate the benefits of the integrated GOFLEX solution in three use-cases, covering a diverse range of structural and operational distribution grid conditions in three European countries.

The period of execution of this project is scheduled for November 2016 to October 2019.


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8.1.6. Flexiciency project

The objective of FLEXICIENCY project (“Energy services demonstrations of demand response, FLEXibility and energy effICIENCY based on metering data | FLEXICIENCY Project | H2020-EC | CORDIS | European Commission,” n.d.) is to demonstrate that the deployment of novel services in the electricity retail markets (ranging from advanced monitoring to local energy control and flexibility services) can be accelerated thanks to an open European Market Place for standardized interactions among all the electricity stakeholders and opening up the energy market also to new players at EU level.

Four major distributor system operators (DSOs): ENEL Distribuzione (Italy), Endesa Distribucion (Spain), ERDF (France) and Vattenfall Distribution (Sweden) with smart metering infrastructure in place, representing the majority of smart meters installed in Europe, are running a set of four complementary large-scale demonstrations with real customers, covering one or several new services related to advanced monitoring, local energy control and flexibility exploitation and valuation. Relevant meter data will be made available by the DSOs in a non-discriminatory way close to real time, in order to enable the emergence of new energy services. Advanced interoperable platforms for making available metering data to all the interested players, either new or existing ones, will be enhanced and run in the project building on open standards.

The project is assessing economic models of these new services. Based on the five demonstrations, the

dissemination activities will support the preparation of the market place exploitation strategies, as well as the promotion of the use cases tested during the demonstration activities.

The duration of the project was estimated was from February 2015 to January 2019.

8.1.7. Pentagon project

The Pentagon project (“Unlocking European grid local flexibility trough augmented energy conversion capabilities at district-level | PENTAGON Project | H2020-EC | CORDIS | European Commission,” n.d.) is a 3-years with deliver date in November 2019, research and innovation project that will investigate the potential of wider deployment of energy conversion technologies and strategies at district-level, with the aim to foster flexibility in the low-voltage and medium-voltage grid. The rationale that underlies Pentagon approach is that multi-vector smart districts can be the key enablers of future smart grids, provided their flexibility capabilities are augmented with adequate energy conversion technologies. To this end, Pentagon will deliver two key technology assets: a highly efficient power-to-gas installation sized for coupling with typical district heating plants and a multi-vector multi-scale district energy management platform for the combined monitoring and management of all district energy carriers.

The power-to-gas technology will achieve a 15 to 25% energy gain compared to state-of-the-art performances. The multi-vector multi-scale district energy management platform will achieve 15 to 20% more flexibility at district-level, allowing for a 25% increase of renewable penetration, by leveraging building and district power to heat conversion capabilities. These impacts will be thoroughly assessed through an iterative validation and demonstration roadmap that will start with lab-scale individual component testing, continue with a focused deployment in district-scale experimental facilities, and conclude with a wider simulation-based assessment at distribution grid level that will rely on a real smart district from a project partner. Based on the results of the validation and demonstration, Pentagon will be able to implement an exploitation roadmap aimed both at (a) preparing the commercialization of the results (5-years post-project horizon) and (b) the definition and targeted dissemination of innovative local energy aggregation business models, leveraging a 200+ member stakeholder community and connections between PENTAGON and relevant market design standardization initiatives.

8.1.8. MAGNITUDE project

In the framework of the achievement of the EU Climate and Energy packages for the decarbonisation of the energy sectors, the integration of variable renewable energy sources will put at stake the stability and provision security of the electricity system: there is a growing need for flexibility provision to ensure a reliable and stable electric system.


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MAGNITUDE project (“MAGNITUDE - Project,” n.d.) addresses the challenge to rise flexibility in electricity systems, by increasing the synergies between electricity, heating/cooling and gas networks and associated systems. MAGNITUDE will bring technical solutions, market design and business models, to be integrated on ongoing policy discussions.

MAGNITUDE will define technological and operational means for maximising flexibility provision to the electricity network. It will identify the regulatory framework to bring such flexibility service to the energy markets and will provide enhanced market designs and related business mechanisms.

MAGNITUDE is built upon 7 real life case studies of multi energy systems, located in different European

countries, under different regulatory and geopolitical environments and with different technological development levels. It will:

Simulate the multi energy systems in the case studies and optimise their operation strategies maximising the provision of specific flexibility services

From existing regulations, propose improved market designs, and integrate them in a market simulation platform for evaluating its performance among the case study countries

Quantify the benefit of pooling flexibilities from decentralized multi energy systems for energy markets through an aggregation platform.

MAGNITUDE results will define policy strategies and recommendations in a pan-European perspective. Achievements will be spread among stakeholders to raise awareness and foster higher collaboration among the electricity, heating and gas sectors to achieve the common goal of a less carbon intensive, yet reliable energy system.

It started in October 2017 and the project will be finished in March 2021.

8.1.9. SmartNet project

We consider necessary to make a special mention to this project called SmartNet. As the reader will see, this project is mentioned recurrently throughout the project as it could be said that CoordiNet is a follow-up of the SmarNet project. Therefore, many SmarNet's references and data may have been used as a starting point of this document.

SmartNet (“SmartNet - Integrating renewable energy in transmission networks,” n.d.) aims at providing architectures for optimized interaction between TSOs and DSOs in managing the exchange of information for monitoring and for the acquisition of system services (reserve and balancing, voltage regulation, congestion management) both at national level and in a cross-border context. Local needs for system services in distribution systems are supposed to co-exist with system needs for balancing and congestion management. Resources located in distribution systems, like demand side management and distributed generation, are supposed to participate to the provision of system services both locally and for the system in the context of competitive system services markets.

Through an in-depth and a simulation in a lab-environment, answers are sought for to the following

questions:

which system services could be provided from distribution to the whole system (via transmission), which optimized modalities could be adopted for managing the network at the TSO-DSO interface

and what monitoring and control signals could be exchanged to carry out a coordinated action, how the architectures of the real time markets (in particular the balancing markets) could be

consequently revised, what information has to be exchanged and how (ICT) for the coordination on the distribution-

transmission border, starting from monitoring aspects, to guarantee observability and control of distributed generation, flexible demand and storage systems,

which implications could the above issues have on the on-going market coupling process, that is going to be extended to real time markets in the next years, according to the draft Network Code on Electricity Balancing by ENTSO-E.


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Different TSO-DSO interaction modalities are compared with reference to three selected national cases (Italian, Danish, Spanish) also supposing the possibility of a cross-border exchange of balancing services. Physical pilots are developed for the same national cases. The impacts of SmartNet include:

deployment of solutions for improving flexibility and capacity of European electricity grids at high voltage levels to integrate both renewable and other new electricity producers and users;

demonstrating advanced grid technologies and system architectures and enhancing the competitiveness of European industries;

devising new architecture and business models and disseminating most effective architecture and models across Europe;

demonstrating the infrastructures, processes and information management to encourage active participation of actors from the demand-side and new players (such as aggregators) in energy markets.

The duration of the project was from January 2016 to June 2019.

8.2. Selected industry details

Here we present a detailed analysis of a selection of energy-intensive industries as well as tertiary and residential sectors.

8.2.1. Iron and Steel

After China, the EU is the world's second largest steel producer, with almost 10% of world crude steel production in 2018. EU Crude steel production is concentrated in a relatively limited number of Member States. Nine Member States (Germany, Italy, France, Spain, United Kingdom, Poland, Belgium, Austria, and the Netherlands) accounted for 81% of the total EU production in 2018 (“EUROFER - European Steel in Figures,” 2019). For iron and steel sector, it is estimated that production will increase, as it is assumed that EU steel makers will remain competitive in terms of overall costs and quality, through a continuous process of investments and restructuring, in spite of increases in energy prices and raw materials, labour and regulatory costs. Given the limitations of emerging energy efficiency technologies in the steel industry, the energy intensity of the sector is expected to improve only marginally until 2030, increasing energy consumption between 2011 and 2030.

8.2.2. Chemical and Petrochemical

Analysing energy consumption within the chemical sector and its different subsectors, we must pay special attention to those subsectors that have a higher energy intensity6:

Petrochemicals (C20.1): 47% (Energy intensive);

Basic inorganic (C20.1; C20.5): 25% (Energy intensive);

Polymers (C20.1; C20.6): 12% (Non-energy intensive)

Specialty chemicals (C20.2; C20.3): 8% (Non-energy intensive);

Consumer chemicals (C20.4): 2% (Non-energy intensive);

Pharmaceutical products (C21): 6% (Non-energy intensive).

With respect to the chemical and pharmaceutical sector in the EU will increase in 2030 to satisfy the expected global demand for products. The sector has continuously progressed its energy intensity trend considering its historical trend since 1990. However, the index of energy intensity improvement has slowed down significantly since 2000, reflecting a limited potential for further improvement. As a result, the sector's energy consumption is expected to increase in accordance with the expected increase in production.

6 Classification according to NACE (Statistical classification of economic activities in the European Community). For more information, see (“Glossary - NACE,” n.d.)


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8.2.3. Machinery

The machinery sector is divided among 4 NACE divisions:

Manufacture of fabricated metal products, except machinery and equipment (C25);

Manufacture of computer, electronic and optical products (C26);

Manufacture of electrical equipment (C27);

Manufacture of machinery and equipment not elsewhere classified (C28).

When compared to other manufacturing sectors, the machinery sector is less energy-intensive. The sector needs constant change in its production process to respond to changing consumer demands and technological trends. As a result, energy consumption is linked to the manufacturing demands of product specifications. It is expected that the sector will continue its strong downward trend in energy intensity in the long term, which will translate into a trend of relatively flat energy consumption as production continues to grow.

8.3. Analysis of barriers to market participation and needs

In the present annex, the main barriers for storage participation in electricity markets are analysed. Regulation, including that affecting markets’ design, is changing fast and Distributed Energy Resources (DERs), including storage, tend to be considered relevant flexibility providers in power systems. In this sense, latest EU policy is revised. To end, some good practices to overcome the main barriers are presented, both from EU and USA.

8.3.1. Barriers

The lack of power system flexibility can hinder the accomplishment of the renewable energy goals, as well as the power system’s reliability. Electricity storage has, however, played a minor role in the power sector so far. Network storage is, today, based on pumped hydro but, still, it represents a small percentage of the total installed power, e.g., in Germany and France around a 5%. The main barriers existing up to now for the development of storage installations in the network can be grouped in two aspects: the capital cost of technologies; and the rules governing the electricity markets, which need to be revised to value flexibility and allow the various technologies compete with equal opportunities (Olsthoorn et al., 2018).

The latter has been addressed through the Clean Energy for All Europeans package, which is described more in detail below. However, the absence hitherto of a common regulatory approach has led to differences in how Member States treat storage in the energy system. Investors have encountered the following key obstacles to private sector investments (Milionis et al., 2019):

Grid fees: in several countries (Austria, Germany, Finland…), owners of storage have to pay grid fees twice, both as producers and consumers. The new electricity market directive does not permit double charging under some circumstances: “for stored electricity remaining within their premises or when providing flexibility services to system operators”.

Combining revenues from different services: the Directive on common rules for the internal market in electricity (Official Journal of the European Union, 2019a) states that customers owning a storage facility “are allowed to provide several services simultaneously, if technically feasible”. The directive applies to customers who store electricity generated within their premises, sell self-generated electricity or participate in flexibility schemes, provided that these activities do not constitute their primary commercial or professional activity. The directive does not address the case of companies who provide such services as their main activity.

Ownership of energy storage facilities: until the new rules are adopted and ownership rights

clarified, legal uncertainty is conducive for neither private companies nor regulated grid operators to invest in energy storage facilities.

Combining electricity with other forms of energy: cross-sector energy solutions were not regulated by EU legislation until December 2018. This lack of regulation made it more difficult to define a positive business case for some such combinations.


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All four obstacles above are regulatory, however the second obstacle is directly related to the electricity market.

Most of these barriers appear again in (Storage Working Group EUROBAT, 2016), where the main legislative barriers in Europe are presented, all of them referred to the situation before the Clean Energy for All Europeans package was approved in May 2019. EUROBAT7 proposes some solutions to these barriers:

Definition of storage: the biggest barrier to storage was the lack of attention paid in legislation to storage itself. There is no common regulatory approach to energy storage, so every Member State takes own decisions, in some cases, preventing the use of storage system. The lack of definition makes that it is sometimes considered as generator and falls under network codes as such. EUROBAT proposes that storage should be considered as a fourth component of the electricity system, after generation, transmission and distribution.

Ownership of energy storage systems: according to EUROBAT, Transmission and Distribution System Operators (TSOs and DSOs) should be granted the ability to own and control storage systems. At the same time, balance providers should be allowed to participate in balancing markets and sell their services to system operators.

Double grid fees and taxation: it is a consequence of the lack of definition. Because of differences

among member states, it could be possible that a storage is set up in one state with favourable rules to provide cross-border services to another state with less favourable rules. According to EUROBAT, the principle of cost causality should be established and, as storage represents no burden for the grid, double grid tariffs fees should be eliminated for stored electricity. Direct taxation on storage should be avoided. A negative example is that of the Self Consumption Decree from 2015 in Spain (this was later amended by new regulatory texts in 2018 and 2019):

o It imposes double grid fees on storage systems connected to the grid. o The electricity self-produced and stored with PV plus storage systems is taxed directly, even

if the electricity is not fed into the grid. o Owners of plants under 100kW cannot sell electricity but feed the surplus electricity into

the grid for free.

Curtailment and balancing responsibilities: energy storage can avoid wasting energy produced by Renewable Energy Sources (RES) because of curtailment. According to EUROBAT, grid constraints that naturally prevent Renewable Energy (RE) from having priority dispatch could be addressed through the deployment of storage. In addition, financial compensation for curtailed energy represents a disincentive for renewable producers to install storage, and in EUROBAT’s opinion this does not promote the market-based approach for RE.

System services and the value of energy storage: key barriers for system services are the unequally balanced market and the underestimation of the value of ancillary and flexibility services. EUROBAT supports to develop an appropriate regulatory framework for aggregators to allow them to participate in the market competing with established providers; to create business cases for storage systems by recognising the value of the services offered by them; and to provide compensation for these balancing services. The International Energy Agency (IEA) suggests providing compensation based on value of reliability, power quality, energy security and efficiency gains.

Electricity pricing: EUROBAT thinks that if electricity prices reflected scarcity, this would represent an important market signal for demand response and storage solutions. In addition, having transmission costs integrated into the final cost of electricity would allow a fair market-based selection of the most efficient solution.

Regarding market participation two aspects are mainly important (Sakti et al., 2018):

Removing barriers for energy storage to participate in different markets and services that already exist.

Introduce new services that better address the issues arising from an increasing distributed and variable energy production.

In the case of USA, while different Independent System Operators (ISO) and Regional Transmission Organizations (RTO) allow for the participation of energy storage at different levels, there are frequent instances where batteries are unable to or do not participate in electricity markets. It is expected that this

7 Association of European Automotive and Industrial Battery Manufacturers (“EUROBAT homepage,” n.d.)


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will change with FERC Order 841's, which mandates that energy storage resources be allowed fully participate in capacity as well as other markets.

It is to see how EU rules, in the case of Europe, or Federal rules, in the case of USA, are then translated into state-level regulations and rolled out within each (Member) State.

8.3.2. Policy

By the end of May 2019, EU agreed a comprehensive update of its energy policy framework seeking a transition to a cleaner energy and a lower environmental impact society model. The new energy rulebook, called the Clean energy for all Europeans package consist of eight legislative acts, which should be transposed into national law in 1-2 years’ time by EU countries (European Commission web site, 2019).

In accordance to (Constantinescu, 2019), the Renewable Energy Directive revision included in the package (Official Journal of the European Union, 2018), presents the following main topics:

For 2030, it establishes a binding EU target of a share of at least 32% of renewable energy.

It empowers consumers, including energy communities, and self-consumption: o Right to self-consume and store energy. o Non-discriminatory grid fees and charges.

It seeks a coherence in support schemes across Europe.

Revised renewable targets in transport: focus on advanced biofuels and fuels from non-biological origin.

DSOs are obliged to assess, at least every four years, the potential for district heating or cooling systems to provide services such as demand response and storing of excess electricity from renewable sources.

The Electricity Market Directive, (Official Journal of the European Union, 2019a), refers to storage in several ways, some of the aspects that may have an impact on storage are the following (Constantinescu, 2019):

Energy storage definition accommodates the different storage technologies. For the first time, storage of electricity is defined: it means “deferring the final use of electricity to a later moment than when it was generated or the conversion of electrical energy into a form of energy which can be stored, the storing of that energy, and the subsequent reconversion of that energy back into electrical energy or use as another energy carrier”.

Citizen energy communities constitute a new type of entity. Their rights and obligations should be in accordance with the roles that they undertake, such as, final customers, producers, suppliers or distribution system operators. Electricity sharing enables members to be supplied with electricity from generating installations within the community without being in direct physical proximity to them and without being behind a single metering point. Where electricity is shared, the sharing should not affect the collection of network charges, tariffs, and levies related to energy flows (Official Journal of the European Union, 2019a).

Regulatory authorities should facilitate cross-border access for suppliers of electricity from different energy sources, as well as for new providers of generation, energy storage and demand response.

DSOs should procure, among other services, storage.

DSOs and TSOs should consider storage for network planning.

In general, DSOs and TSOs cannot own, develop, manage or operate energy storage facilities. Under some circumstances they are allowed: when facilities are fully integrated network components; when other parties cannot deliver storage services at a reasonable cost and in timely manner; when the facilities are not used to buy or sell electricity in the energy markets but to operate the system; and when the regulatory authority has assessed the necessity and has granted its approval (Official Journal of the European Union, 2019a).

Access: Member States shall ensure that active customers that own an energy storage facility: (a) have the right to a grid connection within a reasonable time after the request, provided that all necessary conditions, such as balancing responsibility and adequate metering, are fulfilled; (b) are not subject to any double charges, including network charges, for stored electricity remaining within


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their premises or when providing flexibility services to system operators; (c) are not subject to disproportionate licensing requirements or fees; (d) are allowed to provide several services simultaneously, if technically feasible. In addition, regulatory authorities should facilitate access to the network for new generation capacity and energy storage facilities, in particular removing barriers that could prevent access for new market entrants and of electricity from renewable sources (Official Journal of the European Union, 2019a).

Market participation (general): all customer groups (industrial, commercial and households) should have access to the electricity markets to trade their flexibility and self-generated electricity. Customers should be allowed to make full use of the advantages of aggregation of production and supply over larger regions and benefit from cross-border competition. State Members should implement transparent and fair rules to allow independent aggregators to fulfil their roles as intermediaries and to ensure that the final customer adequately benefits from their activities. Products should be defined on all electricity markets, including system services and capacity markets, so as to encourage the participation of demand response (Official Journal of the European Union, 2019a).

Balancing: TSOs shall procure balancing services subject to the participation of all qualified electricity undertakings and market participants, including market participants offering energy from renewable sources, market participants engaged in demand response, operators of energy storage facilities and market participants engaged in aggregation (Official Journal of the European Union, 2019a).

System services: TSOs will ensure, among other things, the availability for all necessary system services, including those provided by demand response and energy storage facilities (Official Journal of the European Union, 2019a).

Regarding the Electricity Market Design regulation (Official Journal of the European Union, 2019b, p. 943), these are some of the aspects that may have an impact on storage facilities (Constantinescu, 2019):

Balancing: all market participants shall aim for system balance and have a financial responsibility related to it.

Day-ahead and intraday: the imbalance settlement every 15 minutes and bid size not above 1MW.

Price caps: no maximum (or under the value of lost load), no minimum (or minus 2000 €).

Priority dispatching: only for small RE generators (less than 400kW or 200kW for plants commissioned from 2026) and demonstration projects. Member States may also provide priority dispatch to high efficiency Combined Heat and Power (CHP) plants under 400kW. Plants commissioned before 4/7/2019 subject to priority dispatch shall continue to benefit from it, while they are not substantially modified.

Curtailment or re-dispatching: The resources that are re-dispatched shall be selected from among generating facilities, energy storage or demand response using market-based mechanisms and shall be financially compensated. Electricity re-dispatched from that produced from RES or high-efficiency cogeneration will not exceed 5% of the annually produced electricity in these installations (if RE and high efficiency CHP do not exceed 50% of the annual gross final consumption of electricity in the Member State).

Bidding zone: its borders shall be based on long term, structural congestions in the transmission network.

Network congestion: it must be addressed with non-discriminatory market-based solutions.

Grid fees: they should reflect actual costs. They should be non-discriminatory (including storage), not distance-related, customer profile could impact the fees (including storage), procured storage services would be included in the system operators cost base, recommendation on the structure of fees shall be made by the Agency for the Cooperation of Energy Regulators (ACER).

Regional TSO cooperation: by performing functions of regional relevance.

EU DSO entity: DSOs shall cooperate at Union level through the EU DSO entity, in order to promote the completion and functioning of the internal market for electricity, and to promote optimal management and a coordinated operation of distribution and transmission systems.

Network codes: The Commission may adopt delegated acts, such as network codes on the basis of text proposals developed by the ENTSO for Electricity, or, by the EU DSO entity and ACER.

Furthermore, the UK has one the most advanced market regulations in the electricity sector in Europe. Regarding energy storage, these are some of the regulatory and market developments in the field (Bird&Bird, 2018):


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Ofgem and the UK government issued in July 2017 the Smart Systems and Flexibility Plan, which sets out the proposed approach for integrating flexible and smart technologies into the UK energy system. It addresses the role of energy storage in the electricity market and makes proposals to deal with the commercial and regulatory barriers that may prevent the further development of energy storage.

Ofgem released a guidance in December 2017 seeking to clarify existing requirements that generators must satisfy under the Renewables Obligation (RO) and Feed-In Tariffs (FIT) schemes, if storage is co-located with generation accredited under these schemes. The draft proposes no change to the schemes' requirements and support under the schemes will remain solely available for eligible electricity.

Revenue streams: battery storage revenue streams may include a mixture of frequency response, capacity market payments, TRIAD revenue and power supply payments. The challenge is to construct installations that can take advantage of multiple revenue streams and can demonstrate returns against capital expenditure to secure funding.

In the USA, the ancillary market is a reference. The first step towards its creation was Order 890 of the FERC of 2007, which required considering non-generation units as service providers for the grid and having them fully participating in the energy market. In 2011, with Order 755, FERC acknowledged the added value of fast-response storage systems for frequency control, but also recognised that system services were not adequately compensated, creating a scheme based on two terms: capacity payment and performance payment. In 2013, Order 784 clarified accounting rules for storage participation (Storage Working Group EUROBAT, 2016). In 2018, Order 841 removes barriers for the participation and efficient remuneration of energy storage resources in wholesale electricity markets (Sakti et al., 2018). The latter is the most direct ruling yet to allow for an efficient participation of energy storage in US wholesale electricity markets.

8.3.3. Good practices

The new rules in both EU and USA represent a step forward, while it remains to be seen how they will be applied in their regions before deciding whether they are positive enough for storage or whether they require further improvements. There are some interesting examples of storage market participation in Europe:

Sonnen virtual battery, Germany (sonnen, 2018): it consists of thousands of residential energy storage systems installed across the country used, normally, to manage the house consumption. However, they can also independently arrange themselves into a large-scale virtual battery when fluctuations arise in the power grid. Since each battery will have a different state of charge, a number of individual batteries are aggregated into blocks starting at 1 MW, which are then made available to the energy market. The virtual battery was qualified for participation in the TenneT’s primary operating reserve market, after performing the following test: first, discharge one MW, wait 30 seconds, and recharge 1 MW from the grid. Sonnen has around 30 000 battery systems in Europe with capacity between 5-15 kWh.

Social Energy, UK : it uses artificial intelligence techniques to educate an algorithm, which assesses and manages individual home solar and storage systems (every five minutes) (L. Stoker, 2019a). It is fully compliant with National Grid’s dynamic frequency response service (“About - Social Energy,” n.d.).

DER control, National Grid, UK (L. Stoker, 2019b): National Grid, UK’s TSO, has a Distributed Resource Desk in its control room. The desk enables to issue instructions to owners and operators of distributed energy resources (DERs), including battery storage operators, quicker than before. It enables smaller market players to participate much faster. Batteries entered the Balancing Mechanism (BM) market in 2018, via a virtual power plant. The TSO control room receives bids and offers from generators daily, detailing their power capacities, time frames and prices. These bids are accepted or rejected in order to manage the network at the least possible cost. In its 24 first hours of operation, the number of bids and offers of DER systems (energy) accepted by TSO doubled.

Terna, Italy (Storage Working Group EUROBAT, 2016): Regarding ownership, a partial exception to the unclear ownership rights is Italy. Here, the transmission operator Terna installed two grid-connected battery storage pilot projects (2011, 2012). The Italian government supported Terna’s project and allowed TSOs and DSOs to build and operate storage systems under certain conditions. Network access rules for energy storage have been defined in Italy.


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In (Sakti et al., 2018), a comprehensive review of rules that govern storage across various U.S. wholesale electricity markets is presented. A general conclusion of the analysis is that there is still potential to extract greater value from advanced storage assets through market reforms. Order 841 allows system operators to design these new markets. A wide range of market rules are currently applied to energy storage:

California Independent System Operator (CAISO): energy storage resources generally participate as non-generator resources (NGR), pumped storage hydro units, or as one of CAISO’s two demand response resources. CAISO’s Regulation Energy Management (REM) programme NGRs to bid into the day-ahead regulation markets based on the characteristics of the technology, taking into account the State of Charge (SOC) of the battery. They have developed market products for flexible ramping (able to ramp quickly in response to variable energy resources), very suitable for storage (Sakti et al., 2018). In 2013, a storage procurement target was established for the utilities operating in the State: utilities have to procure 1325MW of non-pumped hydro-storage capacity by 2020. In the Assembly bill No. 2514 of the State of California, a precise definition of storage is provided clearly defining its attributions, services, characteristics and purposes (Storage Working Group EUROBAT, 2016).

Electricity Reliability Council of Texas (ERCOT): under the wholesale storage load model, it allows for the participation of storage in the energy and system services markets with a separate fast responding regulation service (FRRS) tailored for faster acting resources.

Independent System Operator New England (ISO-NE): it has three resource types for energy storage participation, with two of them based on whether the storage unit is charging or discharging, and another one for demand response. Within ISO-NE, registration as an Alternative Technology Regulation Resource (ATRR) enables energy storage resources with varying performance capabilities to participate in the regulation market.

Midcontinent Independent System Operator (MISO): Stored Energy Resources (SERs), developed specifically for short term storage can only participate in the provision of regulating reserves. They have developed market products for flexible ramping (able to ramp quickly in response to variable energy resources), very suitable for storage but, in this case, storage is illegible.

New York Independent System Operator (NYISO): energy storage participation can be in the form of either Energy Limited Resources (ELRs), Limited Energy Storage Resources (LESRs), Demand Side System services Program (DSASP), and Special Case Resource (SCR).

Pennsylvania-New Jersey-Maryland Interconnection (PJM): Capacity Storage Resource (CSR) and Energy Storage Resource (ESR) allow for the participation of energy storage in its wholesale markets.

While all of the Independent System Operators (ISO) and Regional Transmission Organizations (RTO) analysed in (Sakti et al., 2018) allow advanced energy storage participation in their system services markets, only five of them currently allow storage to participate in their energy market. Meanwhile, storage participation in capacity markets is very limited.

Another conclusion from the analysis in (Sakti et al., 2018) is that market rules and mechanisms can have a real impact on the economics of energy storage. Some examples are presented:

FERC Order No. 825 more than doubled de potential revenues that can be realized from energy

storage arbitrage for a given location and time period within MISO due to the use of higher time resolution prices in market settlements.

PJM and ISO-NE have introduced fast regulation schemes that are better-suited to efficiently compensate faster responding resources such as battery energy storage systems or flywheels. Specially in the PJM market, their RegD scheme helps remunerate energy storage assets more appropriately.

In ISO NE, market rules have been revised to improve market participation for battery storage (Christopher Parent, 2018):

It can participate in the Capacity Market as supply.

It can participate in the Energy Market as dispatchable supply and dispatchable demand: o Eligible to set price as supply and demand. o Receive the nodal Locational Marginal Price (LMP) for its supply and demand. o Eligible for uplift payments (Net Commitment Period Compensation) as supply and demand.


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It can participate in the Forward Reserve Market and will be counted as Ten-Minute Spinning Reserve in real-time.

It can participate in the Regulation Market: o It can manage its state of charge using the energy-neutral signal. o Any capability not taken in the regulation market can be offered into the energy market.

“Available energy” and “available storage” will now be remotely metered in real time, which allows: o The resource to manage its state of charge (combined with bids/offers). o The ISO to calculate dispatch limits for use in real-time markets and reserve capability.

The ISO can determine a single “net” dispatch instruction (it avoids conflicting dispatch instructions).

It applies current cost-allocation treatment for pumped storage hydro to battery storage (when resources are consuming power from the grid).

Some of the US market reforms required to better capture the storage benefits could be the following (Sakti et al., 2018):

In the longer-term, for capacity markets, the duration thresholds need to be revisited for storage since most storage technologies are limited in their ability to operate for longer durations, which also is a function of their state-of charge.

In the case of day-ahead markets, the ability to economically schedule storage assets based on their states of charge and cycle life, and then allowing bid revisions closer to real time.

in the shorter-term, for ancillary-services’ markets, policy measures that remove barriers that impede storage from participating as well as allowed for payments for performance reflecting the accuracy and speed of response will be needed.

8.3.4. Volume of batteries

The global installed battery storage is growing, including both demonstration and commercial applications, specifically, this chapter provides an overview of the current situation in Europe. The main source of information used for the analysis is the database available on the DOE global energy storage database (Department of Energy - USA, 2019). The report (CIGRE WG C6.30 and WG C6.30, 2018) evaluates the international experience with battery storage at distribution systems and provides information of some of the main projects based on storage technologies. This evaluation is made using the data available on the DOE database which is publicly available and contains information about energy storage projects. The database is maintained by the U. S. DOE Office of Electricity Delivery and Energy Reliability and companies are encouraged to contribute to its updating. However, although there is a process to ensure the accuracy of the data, there are several limitations that should be considered:

The database is dependent on the updating entered by the users.

Although the database includes the status of the project (e. g. operational, contracted, etc.), this information is not included in this analysis, since this issue may not always be up to date.

Not all smaller installations (particularly behind the meter8) are likely to be included, although there could be projects including a set of batteries for which only the total capacity is indicated.

The focus of this database is battery storages connected at distribution level, but it must be considered that the grid interconnection level is not provided for all the projects and that the definitions of transmission and distribution are not consistent worldwide.

Some additional assumptions: batteries above 6 MW, off-grid installations and battery installations at renewable and conventional power plants are excluded since they are probably not connected at distribution level.

Next, some figures show the analysis performed using the data available on the DOE’s website, specifically for the European countries 9.

8 It is a renewable energy system designed and built for a single facility. The location of the system is on the owner’s property, not on the side of the electric grid/utility 9 The database includes information for the following European countries: Austria, Belgium, Bosnia Herzegovina, Bulgaria, Croatia,

Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, United Kingdom


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Figure 14: Storage capacity by country (own elaboration with data from (Department of Energy - USA, 2019).

The term Other countries aggregates installations from Romania, Netherlands, Sweden, Finland, Denmark and Hungary, since the installed capacity in these countries is less than ~ 50 MW. Countries like Spain, Italy, Germany, Switzerland and France have big installations of open-loop pumped hydro storage, which place these countries on the top of the score.

In order to analyse which technologies are the most installed ones, Figure 15 shows the capacity both by country and by technology. For the sake of simplicity, the hydro power technology and those technologies with installed capacity < 1 MW have been removed from the figure, since there are more than 12 different types of technologies reflected in the report (CIGRE WG C6.30 and WG C6.30, 2018) with an installed capacity < 1 MW.


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Figure 15: Battery storage capacity in MW by technology (own elaboration with data from (Department of Energy - USA, 2019).

As it can be seen, the majority of battery storage is from Lithium-ion batteries. The following technologies are the heat thermal storage and Sodium-sulfur battery, but far below the Lithium-ion technology. In Italy, the most deployed technology is the Sodium-sulfur technology and both in Spain and in France is the heat thermal storage.

Some of the main issues driven by the report (CIGRE WG C6.30 and WG C6.30, 2018) for energy storage in the most European active countries are summarized below:

Germany is in the process of an ambitious energy transition to replace fossil fuel and nuclear energy

with renewables and to reduce energy consumption. Although in the short term no much storage is expected to be required, the energy storage systems are being considered as an integral part of the overall transition, playing a fundamental role in addressing the large-scale renewable integration. As well as research funding, there are initiatives in place to support the deployment of storage. The country has significant solar PV installations on residential rooftops and the self-consumption is growing through the use of storage. The regulatory and legal status of storage in Germany is as an electricity consumer. However, there are some exemptions in place with regard to the payment of network tariffs and the renewable energy levy, as long as the electricity withdrawn is re-fed into the same network. Electricity stored is subject to electricity tax (however, an amendment requiring its exemption has been proposed). Regulation currently presents some barriers to the participation


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in balancing markets, although some changes have been proposed to open the market such as exemptions from the minimum bid size for secondary and tertiary balancing market.

Italy: Battery storage is considered to be a major opportunity in Italy, since it is one way to address the system balancing challenges related to the high renewable penetration, mainly in the south of the country, and the high peak demand, mainly in the north. In Italy, contrary to the majority of European countries, the transmission and distribution networks are allowed to own and operate storage facilities. The last regulatory framework introduced rules for the connection of storage, clarifying the network services which can be provided by the storage, including the voltage and frequency control. However, the main barrier to further deployment of storage is the remuneration for these services.

Spain. Although currently there are no subsidies to green production, the RES is increasing as a consequence of their cost reduction and improved competitiveness. Hydropower is a consolidated technology in Spain, but its share in the energy mix will progressively be reduced in comparison to other RES with greater potential. CHP facilities are also very present, however, due to its dependency on industry its development slowed down as a consequence of the big recession. In 2010, solar thermal power installed in Spain accounted for the 60% of the worldwide capacity. Given the high stability of thermal operation associated with thermal energy storage, its development in scenarios with high penetration of RES is expected to be promoted. Wind capacity is the RES with the largest installed capacity in Spain. In view of this generation mix, the energy storage systems need to be considered an integral part of the system (Bailera and Lisbona, 2018). Additionally, the Royal Decrees 15/2018 (Spanish Government, 2018) and 244/2019 (Spanish Government, 2019) approved the administrative, technical and economic conditions for energy self-consumption that will promote self-consumption in residential and industrial communities (“Spain’s new rules for self-consumption come into force - PV magazine international,” n.d.). The promotion of the energy storage will allow a greater integration of renewables, the prevention of unwanted dumping of clean energy during valley hours and the provision of more security to the electricity system (“Energy storage | Red Eléctrica de España,” n.d.).

United Kingdom: There are no specific storage targets, however it is considered to be a key technology by facilitating the deployment of distributed renewables and increasing system flexibility. Regulatory and legal status of storage results in storage not being able to fairly compete with generation, since the generator obligations and charging treatment apply despite the differences. However, in July 2017 the regulator (Ofgem) launched a set of actions to address policy and regulatory barriers to storage deployment. The storage in UK is set to increase, in spite of the barriers. The Enhanced Frequency Response (EFR)10 service has driven a tremendous interest in storage. This service has been developed to help improve the management of the system frequency pre-fault, with the speed of frequency required being well suited to battery storage. In 2017 the country put millions of pounds into research and development initiatives, including the creation of a battery institute (“The Faraday Institution – Powering Britain’s Battery Revolution,” n.d.).

Beyond Europe countries, the worldwide top countries in operational storage capacity on distribution networks are China, the United States and Japan, in fact, these countries are far above the rest of the countries. China and United States are the world leaders in storage research and development.

There has been a rapid storage development in China in the last few years. From having no grid-connected energy storage projects at the end of 2010, it is reported that by the end of 2015 China had 105 MW of operational storage (all of them are not registered in the DOE database). China has the largest installed solar and wind capacity, with targets to have 100 GW of solar and 200 GW of wind installed by 2020. The rapid expansion in renewables has led to high curtailments rates and the storage is seen as a technology which can help to address this issue. Some of the main barriers are the lack of economic mechanisms and the low electricity price. China has significant storage manufacturing capabilities, with over 100 Lithium-ion battery manufacturers, which are primarily focused on grid scale energy storage and electric vehicles and, as production increases, storage prices are expected to decrease.

10 Enhanced frequency response (EFR) is a dynamic service where the active power changes proportionally in response to changes in

system frequency. This service is aimed at improving the management of system frequency pre-fault to maintain system frequency closer to 50Hz. EFR is open to both balancing and non-balancing mechanisms providers who could meet the technical requirements


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In Japan, the storage is considered to be a high priority technology to address the energy challenges following the Fukushima nuclear incident in 2011 which led to the country suspending 50 of its nuclear power stations. The subsequent dependency on imported fossil fuels resulted in concerns around energy security, a rise in energy costs and an increase in greenhouse gas emissions. The 2014 Strategic Energy Plan highlighted the importance of storage to assist acceleration of renewable energy. In 2012 the Government set up the Storage Battery Strategy Project to develop and implement integrated strategic policies for battery storage, including the aim of Japanese companies acquiring around half of the world’s storage battery market share by 2020 (35% large scale storage, 25% residential/industrial, 40% vehicle use). The strong government support for storage has resulted in significant annual subsidies since 2012. Japan is considered to be a world-leader in sodium-sulphur batteries. It is forecast that Japan will be one of the largest energy storage markets.

The Department of Energy of the United States has been supporting research of the technology since the

1970s after the US oil fuel crisis and the storage is considered within the energy industry as an important technology for maintaining a robust and resilient system. Apart from the work developed by the DOE, the federal stimulus launched in 2009 had a significant positive impact on the growth of the industry, through the funding of the Smart Grid Investment Grant program and the Smart Grid Demonstration Project. With these incentives already expired, currently it is the Energy Storage Technology Advancement Partnership (ESTAP) the main source of funding for demonstration projects. Regulation changes in recent years has also helped to increase the deployment of storage, in particular for the provision of system services. One of the main barriers in the country is the regulatory issues and discrepancies in market rules across the large number of markets in the country. Within the industry, the storage is considered to be critical to achieve the sustainable energy goal.

8.4. Questionnaire

The following reproduces a copy of the questionnaire sent to the various counterparties.

8.4.1. Objective and instruction of the Questionnaire This questionnaire aims to gather information about feasible potential of Distributed Energy Resources (DER), including distributed generators, demand response and storage, in order to be able to identify untapped potential and define the main characteristics of the best DER candidates for market products to be tested. It is conducted as part of Task 1.4 “DER Modelling” of the CoordiNet project funded by the European Union’s Horizon2020, Grant Aggrement Number (824414) and topic (LC-SC3-ES-5-2018-2020 TSO – DSO – Consumer: Large-scale demonstrations of innovative grid services through demand response, storage and small-scale (RES) generation) research and innovation program and will feed into Deliverable 1.4.

Your organisation has been selected as a candidate to participate in the questionnaire following our initial research on the qualification of your electricity consumption and expected potential flexibility available.

All of the data of the questionnaire is relevant and limited to the purposes of the CoordiNet project, and the data collected is anonymized. More information on the data protection is provided in Chapter 3 of this document.

The questionnaire shall be duly filled in and returned via e-mail to [email protected] by 08/07/2019

For any enquiries, please contact [email protected]

8.4.2. Introduction

8.4.2.1. Abbreviations and acronyms

aFRR automatic Frequency Restoration Reserves

mailto:[email protected]



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CCGT Combined Cycle Gas Turbines

DER Distributed Energy Resources

DRES Distributed renewable energy sources

DSO Distribution System Operator

FAT Full Activation Time

FCR Frequency Containment Reserves

FSP Flexibility Service Provider

HV High Voltage

HVAC Short for heating, ventilation, and air conditioning. The system is used to provide heating and cooling services to buildings

LV Low Voltage

mFRR manual Frequency Restoration Reserves

MV Medium Voltage

OCGT Open Cycle Gas Turbine

RoCoF Rate of Change of Frequency

RR Replacement Reserves

SO System Operator

TSO Transmission System Operator

VAR Volt-Ampere Reactive

8.4.2.2. About the CoordiNet project

The CoordiNet project (www.coordinet-project.eu) or “Large-scale TSO-DSO-Consumer demonstrations of innovative network services through demand response, storage and small-scale distributed generation” aims at demonstrating how Distribution System Operators (DSO) and Transmission System Operators (TSO) 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 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 for the demonstration sites to pave the way for the interoperable development of a pan-European market that will allow all market participants to provide energy services and open 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 DER. Running from January 2019 to June 2022, the CoordiNet project brings together 23 partners and 10 Linked Third Parties from 10 European countries consisting of academia, TSOs, DSOs, industry, aggregators, service providers and municipalities.

http://www.coordinet-project.eu/


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8.4.3. Definitions

In the context of the CoordiNet project, the followings are the concepts and definitions used in this questionnaire.

8.4.3.1. Flexibility

Flexibility can be defined as the possibility of modifying generation and/or consumption patterns in reaction to an external signal (price or activation signals) to contribute to the power system stability or portfolio management in a cost-effective manner. Flexibility can also be seen as the characteristic that makes it possible for generation or consumption resources to supply services defined by grid operators to manage the network.

8.4.3.2. Distributed Energy Resources (DER)

DER is a concept used to encompass the multiple types of end-users connected to the distribution grid, capable of providing energy and/or services to the grid by mobilizing the flexibility they have available. The CoordiNet project makes the distinction between four types of DER: distributed generation, demand response, energy storage systems and electric vehicles, at all voltage levels of the distribution grid.

8.4.3.3. Grid services

Grid Services are services provided to TSOs and DSOs to keep the operation of the grid within acceptable limits for security of supply and are delivered mainly by third parties. The grid services considered in the CoordiNet Project are balancing (frequency control), congestion management, voltage control, inertial response, black start and controlled islanding.

8.4.4. Products for grid services

Products for grid services can be grouped into standard products and specific products. In this questionnaire, the focus is on standard products, which is defined as “harmonized products for the exchange of grid service(s) with common characteristics across Europe (i.e. shared by all TSOs or by all DSOs or by all TSOs and DSOs)”. See CoordiNet Deliverable 1.3 (Annelies Delnooz et al., 2019) for a more detailed information.

8.4.4.1. Definition of product characteristics

The characteristics of products and their definitions are presented in Table 1. The first six characteristics are also represented in Figure 1.

Table 1: Definition of product characteristics

Characteristic Definition Source

Preparation period The period between the request by the SO and the start of the ramping period.

Adapted from (European Commission, 2017)

Ramping period The period during which the input and/or output of power will be increased or decreased until the requested amount is reached.

Adapted from (ENTSO-E, 2018a)

Full activation time The period between the activation request by the SO and the

corresponding full delivery of the concerned product. Adapted from (European Commission, 2017)

Minimum/maximum quantity

The power (or change in power) which is offered, and which will be reached at the end of the full activation time. The minimum quantity represents the minimum amount of power for one bid. The maximum quantity represents the maximum amount of power for one bid.

Adapted from (ENTSO-E, 2018a)

Minimum/maximum duration of delivery period

The minimum/maximum length of the period of delivery during which the service provider delivers the full requested change of



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power in-feed to, or the full requested change of withdrawals from the system.

Deactivation period The period for ramping from full delivery to a set point, or from full withdrawal back to a set point.


Granularity The smallest increment in volume of a bid. Adapted from (ENTSO-E, 2018a)

Validity period The period when the bid offered by the FSP can be activated, where all the characteristics of the product are respected. The validity period is defined by a start and end time11.


Mode of activation The mode of activation of bids, i.e. manual or automatic. Automatic activation is done automatically during the validity period, whereas a manual activation is done at the request of the SO.


Availability price Price for keeping the flexibility available (mostly expressed in € /MW/hour of availability)

Activation price Price for the flexibility actually delivered (mostly expressed in € MWh)

Divisibility The possibility for a system operator to use only part of the bids offered by the service provider, either in terms of power activation or time duration. A distinction is made between divisible and indivisible bids.


Locational information included

This attribute determines whether certain locational information needs to be included in the bid (e.g. identification of Load Frequency Control (LFC) area, congested area...)

Recovery period Minimum duration between the end of deactivation period and the following activation.


Aggregation allowed This attribute determines whether a grouped offering of power by covering several units via an aggregator is allowed.

Symmetric/asymmetric product

This attribute determines whether only symmetric products or also asymmetric products are allowed. For a symmetric product upward regulation volume and downward regulation volume has to be equal.

Adapted from (ENTSO-E, 2018b)

Figure 1: Representation of product characteristics (source: (ENTSO-E, 2018c)

8.4.4.2. Attributes of products by service

8.4.4.2.1. Balancing (Frequency control)

Balancing entails all actions and processes, on all timelines, through which TSOs ensure, in a continuous way, the maintenance of system frequency within a predefined stability range and compliance with the amount of reserves needed with respect to the required quality. European TSOs use different reserve products to balance the system or to restore its frequency if necessary. Specifically, and in this order:

11 The validity period thus reflects the time period where the FSP could provide the product through its bid and should therefore be at least the full delivery period of the bid.


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8.4.4.2.2. Frequency Containment Reserves (FCR)

FCR means the active power reserves available to contain system frequency after the occurrence of an imbalance. FCR is a fast-acting capacity which can increase/decrease power output in a very short time period. It is therefore important for short-term balance of power production and consumption. Its goal is to stabilize the frequency within a couple of seconds. A summary of product attributes and values are shown in Table 2 below.

Table 2: Attributes of the FCR product

Attribute Value

Preparation period n/a12

Ramping period Defined in terms and conditions for FSPs13

Full activation time < 30 seconds

Minimum quantity 1 MW or 0.1 MW14

Maximum quantity Defined in terms and conditions for FSPs

Deactivation period n/a15

Granularity 0.01 MW or 0.001 MW

Minimum duration of delivery period 30 seconds

Maximum duration of delivery period Up to 15 minutes

Validity period 4 hours (ENTSO-E, 2018d)

Mode of activation Automatic

Activation price Possible

Availability price Yes

Divisibility Divisible and indivisible bids are allowed

Location LFC area

Recovery period n/a (continuous activation within validity period)

Aggregation allowed Yes

Symmetric / asymmetric product No symmetry required

8.4.4.2.3. Frequency Restoration Reserves (FRR)

FRR are the active power reserves available to restore system frequency to the nominal frequency and, for a synchronous area consisting of more than one LFC area, to restore power balance to the scheduled value. A distinction is made between Automatic Frequency Restoration Reserves (aFRR) and Manual Frequency Restoration Reserves (mFRR). A summary of product attributes and values are shown in the tables below (.

12 The product needs to be available continuously within the validity period 13 The sum of the ramping period and preparation period cannot be greater than the full activation time 14 The minimum guideline set within the FCR cooperation is 1 MW (ENTSO-E, 2018d). Within the CoordiNet lower min quantities will however also be considered where appropriate 15 The product needs to be available continuously within the validity period


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Table 3: Attributes of the FRR product

Attribute Value

Preparation period Defined in terms and conditions for FSPs16

Ramping period Defined in terms and conditions for FSPs

Full activation time Current value: 15 minutes

Future value: max 5 minutes (ENTSO-E, 2018e)17

Minimum quantity 1 MW or 0.1 MW

Maximum quantity Defined in terms and conditions for FSPs18

Deactivation period ≤ full activation time (ENTSO-E, 2018e)


Minimum duration of delivery period n/a19

Maximum duration of delivery period 15 minutes

Validity period 15 minutes20 (ENTSO-E, 2018e)

Mode of activation Automatic (ENTSO-E, 2018e)

Activation price Yes

Availability price Possible, dependent on the procurement process


Location LFC area

Recovery period Defined in terms and conditions for FSPs



Table 4: Attributes of the mFRR product

Attribute Value



Full activation time Current value: 15 minutes

Future value: 12.5 minutes (ENTSO-E, 2018a)



Deactivation period Defined in terms and conditions for FSPs


Minimum duration of delivery period

Defined in terms and conditions for FSPs23

Maximum duration of delivery period

Defined in terms and conditions for FSPs

Validity period 15 minutes (ENTSO-E, 2018a)

Mode of activation Manual



16 The sum of the ramping period and preparation period cannot be greater than the full activation time 17 A subcategory for FRR defined as Fast FRR (up and down), which can be provided within a time period of 1 min, is currently implemented by IPTO. This type of reserve has been formulated in order to commit at least one hydro unit. 18 A maximum quantity of 9,999 MW is set within (ENTSO-E, 2018b) 19 Each balancing energy product bid can be activated and deactivated at any moment within the validity period (ENTSO-E, 2018e) 20 The first validity period of each day shall begin right after 00:00 CET. The validity periods shall be consecutive and not overlapping 21 The sum of the ramping period and preparation period cannot be greater than the full activation time 22 A maximum quantity of 9,999 MW is set within (ENTSO-E, 2018a) 23 A min duration of 5 minutes is set within (ENTSO-E, 2018a)


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Location At least the smallest of LFC area or bidding zone (ENTSO-E, 2018a)



Symmetric / asymmetric product

No symmetry required

8.4.4.2.4. Replacement Reserves (RR)

According to the system operation guideline “RR means the active power reserves available to restore or support the required level of FRR to be prepared for additional system imbalances, including generation reserves (European Commission, 2017b). RR are needed to restore system balances when FRR was not able to do so (it is therefore only necessary in case of large imbalances). In addition, it allows FRR units to prepare again for a potential next short-term imbalance intervention and to free up their resources.

Table 5: Attributes of the RR product

Attribute Value



Full activation time 30 minutes (ENTSO-E, 2018a)





Minimum duration of delivery period 15 minutes (ENTSO-E, 2018a)

Maximum duration of delivery period Current value: 4h

Future value: 60 minutes26 (ENTSO-E, 2018a)

Validity period Defined in terms and conditions for FSPs

Mode of activation Scheduled with manual activation




Location At least the smallest of LFC area or bidding zone.




8.4.4.3. Congestion Management

Network congestion occurs because the hosting capacity of a given grid is limited by the inherent characteristics of physical assets (i.e. lines, cables, transformers). Congestion is a condition where one or more constraints (thermal limits, voltage limits, stability limits) restrict the physical power flow through

24 The sum of the ramping period and preparation period cannot be greater than the full activation time 25 In case of a divisible bid, no maximum is requested, while in case of an indivisible bid national rules shall be implemented (ENTSO-E, 2018a) 26 The maximum delivery period depends on the number of daily gates. The RR-Platform will start with 24 daily gates (one optimization which will cover 60min balancing duration) and maximum delivery period of 60 min. For example, in case of moving the RR-Platform to 48 gates, the maximum delivery period will be 30 min (for 96 daily gates, maximum delivery period will be 15min).


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the network. The service of congestion management refers to the process of mitigating grid congestion issues by avoiding the crossover of network capacity.

For the provision of congestion management services two products are considered.

Congestion management Short Term (ST): This is an energy-based product procured for congestion management services at an energy price (most likely to be procured closer to delivery given the fact that it is energy based). This product copes with sporadic constraints.

Table 6: Attributes of the congestion management product ST

Attribute Value



Full activation time Defined in terms and conditions for FSPs28

Minimum quantity 0.1 MW (ETPA, 2019) or 1 MW

Maximum quantity N.A.


Granularity 0.1 or 0.01 MW

Minimum duration of delivery period Defined in terms and conditions for FSPs29

Maximum duration of delivery period Defined in terms and conditions for FSPs





Location Included in the bid30




Congestion management Long Term (LT): This is a capacity-based product procured for congestion management services at a certain Availability price which is then activated when the service is needed and called upon by the relevant system operator. This product is defined to cope with structural constraints.

Table 7: Attributes of the congestion management product LT

Attribute Value



Full activation time Defined in terms and conditions for FSPs32

Minimum quantity 0.1 MW (ETPA, 2019) or 1 MW

Maximum quantity N.A.


27 The sum of the ramping period and preparation period cannot be greater than the full activation time 28 A full activation time of 12.5 minutes could be considered in line with the mFRR product, so that the possibility to trade both products on the same market can be considered 29 Typical durations considered range from 15 min up to multiple hours 30 At least the smallest granularity relevant from grid operation perspective 31 The sum of the ramping period and preparation period cannot be greater than the full activation time. 32 A full activation time of 12.5 minutes could be considered in line with the mFRR product, so that the possibility to trade both products on the same market can be considered.


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Granularity 0.1 or 0.01 MW

Minimum duration of delivery period Defined in terms and conditions for FSPs33



Activation price Possible, dependent on the procurement process



Location Included in the bid34




8.4.4.4. Voltage Control

Voltage control is used to facilitate the transfer of active power in an economic, efficient and safe manner across the power system. Voltage is a localized property of the power system and as such it is essential that it does not exceed a certain level locally to maintain the health of grid assets. For the voltage control service two products were identified:

8.4.4.4.1. Steady State Reactive Power

This product aims at providing means to control voltage under normal operation of the system. The product keeps the voltage profile within the safe range. Its provision takes place by injecting or absorbing reactive power according to a voltage set point (measured at the injection point) set by the system operator. Only units that are able to be controlled for the provision of reactive power in function of grid voltage will be able to participate.

Table 8: Attributes of the Steady State Reactive Power product

Attribute Value

Preparation period N/A

Ramping period N/A

Full activation time Less than 0,1 second

Minimum quantity 0.1 MVAr (Elia, 2018)

Maximum quantity Within technical limits of the installation (incl. all available capacities capable of being coordinated at connection point) (Elia, 2018)

Deactivation period N/A (constant activation)

Minimum duration of delivery period N/A (constant activation)

Maximum duration of delivery period N/A (constant activation)

Validity period Defined in terms and conditions for FSPs (Elia, 2018)

Mode of activation Automatic (reactive setpoint) (Elia, 2018)

Activation price Possible, dependent on the procurement process (€/MVARh) – price should reflect, at the very least, incremental active energy losses due to the provision) (Elia, 2018)


Divisibility Not allowed

Location POC (Point of connection)35

Recovery period N/A (constant activation)

Aggregation allowed Yes (at connection point level)

33 Typical durations considered range from 15 min up to multiple hours. 34 At least the smallest granularity relevant from grid operation perspective 35 At connection point level (at transmission level and distribution level for the TSO and DSO, respectively) (Elia, 2018)


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Symmetric / asymmetric product No symmetry required (injection or absorption of reactive power can be provided separately) (Elia, 2018)

8.4.4.4.2. Dynamic Reactive Power

This product aims at providing means to control voltage under system disturbance. The dynamic reactive power product consists of a punctual regulation of reactive power injection or absorption requested by the system operator. Participation is open to all technologies capable of following the request within specified time scales. In this regard, non-synchronous generators, static compensators and static VAR compensators among others can participate provided they are controlled carefully to support voltage recovery.

Table 9: Attributes of the Dynamic Reactive Power product

Attribute Value

Preparation period N/A

Ramping period N/A

Full activation time Defined in terms and conditions for FSPs (typical values range between 2 – 5 minutes

Minimum quantity 0.1 MVAr (Elia, 2018)

Maximum quantity Within technical limits of the installation (incl. all available capacities capable of being coordinated at connection point) (Elia, 2018)

Deactivation period N/A

Minimum duration of delivery period Defined in terms and conditions for FSPs (Elia, 2018)

Maximum duration of delivery period Defined in terms and conditions for FSPs (Elia, 2018)36

Validity period Defined in terms and conditions for FSPs (Elia, 2018)

Mode of activation Manual (Elia, 2018)

Activation price

Possible, dependent on the procurement process (€/MVARh) – price should reflect, at the very least, incremental active energy losses due to the provision) (Elia, 2018)


Divisibility Allowed

Location POC (Point of connection)37

Recovery period N/A

Aggregation allowed Yes (at connection point level)

Symmetric / asymmetric product No symmetry required (injection or absorption of reactive power can be provided separately) (Elia, 2018)

8.4.4.4.3. Inertial Response

Inertial response is provided to the system by the rotating parts of synchronous machines. Electricity generation technologies connected to the power system employing power electronic converters are electrically decoupled from the grid and, thus, do not naturally contribute to system (physical) inertia. Adequate levels of system (physical) inertia allows operators to maintain a stable frequency. The (physical) inertial response supplied by large rotating masses "buys" time for the system operator to take action. In case of a disturbance or power imbalance, system operators with low (physical) inertia in their system would have less time to react due to a higher rate of change of frequency. Due to its importance, system operators are exploring options for maintaining system inertia levels to achieve higher penetration of intermittent renewable energy sources. Given the peculiar service to be provided by the product, specific technical requirements are applicable.

36 For instance, in Belgium the average activation period of the centralized voltage control (manual activation) is 10 hours 37 At connection point level (at transmission level and distribution level for the TSO and DSO, respectively) (Elia, 2018)


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Table 10: Attributes of the inertial response product

Attribute Value

Minimum quantity Relative to the kinetic energy embedded in rotating masses of a synchronous unit (generators, some loads, primarily motors)38 (Mancarella et al., 2017)

Minimum duration of delivery period 15 seconds (EIRGRID and SONI, 2017)

Maximum duration of delivery period 45 seconds (EIRGRID and SONI, 2017)

Mode of activation Automatic (Inherent response/natural response) (Mancarella et al., 2017)

Availability price Yes in €/MW/h (where MW refers to nominal capacity)

8.4.4.4.4. Black Start

Black start refers to the capability of a grid connected unit (traditionally generation units) to start up without an external power supply, called upon as a means of restoring supplies following a major failure on all or part of the network. A Black Start service is procured in different zones and locational information is needed to ensure the system can always be restored. The nature of the product leads to low competition. The current Black Start provider portfolio is mostly made up of coal stations, OCGT and CCGT gas stations, diesel generators and hydro stations. With a market-based approach the intention is to attract other providers and technologies to provide black start services.

Table 11: Attributes of the black start product

Attribute Value



Full activation time 2-4-6h

Minimum quantity Defined in terms and conditions for FSPs

Maximum quantity n/a

Deactivation period n/a

Minimum duration of delivery period Defined in terms and conditions for FSPs


Mode of activation Automatic

Activation price Possible, dependent on the procurement process


Divisibility Not allowed

Location Locational information included in the bid to define black start control zones

8.4.4.4.5. Control Islanding

Control islanding is often considered as the final stage of power system defence plans. In case of detection of events that may lead to a disturbance, signals are send for the formation of the pre-selected islands in order to: 1) create a balance between the load and generation before the isolation from the system and 2) isolate the island from the system. Specific products for this service are not defined at this stage, as during the operation of the island, the services needed could be the same at least as balancing and voltage control.

8.4.5. Data Protection

The CoordiNet project is committed to respecting and protecting questionnaire participants’ personal data under the framework of Regulation (EU) No 2018/1725. The information the data subject supplies on this

38 This is relative to the nominal capacity of the unit 39 In any case, the sum of the ramping period and preparation period cannot be greater than the full activation time.


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questionnaire will be held by and used solely for the purposes of the CoordiNet project. By submitting the filled-in questionnaire, the data subject gives consent to the processing of the data which is anonymized. Sensitive data, which are collected with consent of the data subject, are irrecoverably deleted with the end of the CoordiNet project. All other data are stored for one year after the project for project auditing purposes and to permit post-project support. To exercise his/her rights, the data subject can contact [email protected].

8.4.6. Questionnaire - Document

8.4.6.1. Your Segment

Please briefly describe typical electricity consumption within your industry and provide details of your company that could make your case special or different (if at all) to the best of your knowledge.

Is your company or industry a net generator or a net consumer?

8.4.6.2. Current Situation

Does your company/industry typically participate in grid services (see 2.4.2) under the current schemes i.e. primary, secondary and tertiary reserves?

If yes, where, how, how much?

If yes, describe the main objectives

If yes, describe the main barriers

Does your company/industry have sustainability targets, or is it being (or planning to be) financed by green bonds or by any other financial instruments linked to efficiency or sustainability targets?

If yes, where, how much, for when?

If yes, do these targets include participation in smart-grids and/or demand-response programs?

How sensitive is your company/ industry to energy pricing?



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8.4.6.3. For Consumer(s)

Could you split your current typical yearly power consumption amongst the following categories? (if possible in MWh or % of consumption)

PROCESS

- Heating/furnaces/dryers/ovens, etc. - Cooling & refrigeration

- Pumps/fans/blowers/compressors - Process specific (electrochemical, motors, robots, conveyor belts, etc)

NON PROCESS

- HVAC

- Lighting

- Others

PROCESS

NON PROCESS

Does your company/industry typically adopt on-site generation solutions?

If so, which one, where, how and how much?

If yes, what is the main purpose and dimensioning of these on-site generation solutions?

Does your company/industry have some technical flexibility to change the profile of power consumption associated to some specific uses or processes (i.e. moving consumption from one hour to other)?


If yes, short commentary on main objectives and barriers

Could your company/industry be technically able to assume a limited number of interruptions of supply and /or reductions of maximum energy demand during short period of time (i.e. some minutes for air conditioning)?



Could your company/industry be technically able to provide flexibilities on power consumption for thermal processes, backed


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by thermal energy storage systems (i.e. some minutes for water heaters)?



For Generator(s)

Do you provide grid services? (See 2.3 for definition for grid services)

If yes, what type of grid services. What are the settlement rules?

If no, why? Are you technically able to provide grid services? Which sort of flexibility could you provide to the grid?

What are the main barriers in order to participate in the provision of grid services?

Do you expect to participate in grid services directly or indirectly via upstream aggregators?

8.4.6.4. Potential Future Developments

Do you see opportunities in the incorporation of energy storage technology?

Do you see opportunities in the incorporation of electric mobility solutions?

If yes, where, how and how much (if possible in MWh or % of consumption)?

Do you think your company/industry’s participation in demand-response programs


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would be affected by the adoption of energy storage?

Which sort of flexibility could your company/industry provide to the grid? (see tables in 2.4.2)

Which sort of flexibility could ABSOLUTELY NOT your company/industry provide to the grid?

(see tables in 2.4.2)

Which revenue/return analysis would you perform to assess your potential participation in demand response programs?

Do you expect your participation to take place directly or indirectly via upstream aggregators?

What would be the best and main enablers for you to consider participating in demand response programs?


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8.5. Replies received on the questionnaire

In order to keep the privacy of the respondents, we present below the summary of their answers in an anonymous form.

Respondent 1 is a corporate active in the field of investment and operation of renewable generation

Respondent 2 is a corporate active in the field of steel manufacturing

Respondent 3 is a corporate active in the field of car manufacturing

Respondent 4 is a European association in the field of energy storage

Respondent 5 is a corporate active in the field of water utility

Respondent 6 is a corporate active in the field of smart homes and micro-grids

Respondent 7 is a corporate active in the field of investment and operation of renewable generation


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QUESTIONS Respondent 1 Respondent 2 Respondent 3 Respondent 4 Respondent 5 Respondent 6 Respondent 7

1.1. Your Segment

Please briefly describe typical electricity consumption within your industry and provide details of your company that could make your case special or different (if at all) to the best of your knowledge.

The consumption of the company includes the consumption of the headquarter offices and the consumption in the plants. The plants (hydro, solar, wind) during the hours and days of operation cover their self-consumptions and during the rest of the period they consume mainly as MV customers.

Electric arc furnace mill for steel production. High intensive power consumer with a electrical consumption, difficulties to predict long time in advance the consumption for a given hour.

Autmotive industry, car manufacturer. The consumption of the industry has been in the past the same of any manufacturing industry. Due to penetration of EV, automotive industry has now a huge impact in the electricity system. Car manufacturers could in the coming future offer at least the services: 2.4.2.1, 2.4.2.2, 2.4.2.3 and 2.4.2.6

Not applicable. Respondent 6: Energy Efficient modular housing for sustainable communities, manufactured off-site, incorporating passive and active features such as PV solar and storage, superior insulation, and smart controls. Monetisable benefits justify the investment and help address fuel poverty concerns

Respondent 7 activity is mainly renewable generation.

Is your company or industry a net generator or a net consumer?

The company is primarily an energy producer (RES energy producer). However, we do have consumptions in both headquarters and plant units.

Net consumer Both. Respondent 4 represents the energy storage sector. Since the round-trip efficiency of most energy storage systems is below 100%, storage is technicaly a net consumer of electricity.

Net consumer Respondent 6 target is to manufacture Near Zero Energy Buildings. European Standard 2010/31/UE Mandatory from 2020 for new buildings. Zero balance of Energy.

Generation


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QUESTIONS Respondent 1 Respondent 2 Respondent 3 Respondent 4 Respondent 5 Respondent 6 Respondent 7

1.2. Current Situation

Does your company/industry typically participate in grid services (see 2.4.2) under the current schemes i.e. primary, secondary and tertiary reserves?

No, it does not since all our plants are under the FiT scheme. However, this would be a possibility for the plants whose PPA is ending in the coming years and they will be entering the market reformed by the framework of the target model.

Primary and tertiary

At the moment it is at the pilot phase, but it is going to be actively participating in the coming 2-3 years.

Energy storage systems commonly provide FCR, FRR, and RR, depending on whether these services are tendered on the market and open to participation of storage devices. Storage also provides new ancillary services such as enhanced frequency response in the UK and DS3 system services in Ireland.

NO No Yes, wind farms

· If yes, where, how, how much?

A souple of MW on R1 Several MW on R3

Not yet. The first of the services that will be offered are voltage control & congestion management. Then depending on the car pool also Frequency control. Islanding might not be profitability attractive enough.

Tertiary reserve in Spain

· If yes, describe the main objectives

Valorize the flexibility offered

To provide a service to compensate frequency


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by low production planning periods

· If yes, describe the main barriers

Period of subscription is too long for an industry that has low visibility on Q+2, remuneration and constraints are usually elss interesting than being really reactive on balancing or intraday markets.

POLITICAL: RES generation, E-Mobility development and deployment, Flexibility market design and implementation, City adaptation ECONOMICAL: Investments in Smart Grid, Business models, Price for flexibility (KWh/effort) SOCIAL: Level of acceptance (Flexibility sources, Remote control, Privacy and cybersecurity); Accessibility (Car sharing, DR program, EV adoption, Level of energy independence, DR involvement) TECHNOLOGICAL: Smart Grid infrastructure (ICT networks, Type of chargers, Interfaces to energy markets); Standardization level of communication,

Not all Member States tender grid services on the market. Where market-based tendering exists, storage in some Member States is prevented from providing grid services or heavily de-rated. This renders the business case for storage very difficult. Another barrier is the lack of long-term contracts for system services, which reduces the long-term investment certainty for storage facilities. A further barrier is that prequalification, tendering, or availability requirements may prevent storage operators from ‘stacking’ multiple services on one storage device, e.g. providing FCR but

For having capacity for tertiary reserve it is necessary to work under nominal power, which is a capacity loss. Barriers are mainly economic.


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interfaces & protocols; Processes for inclusion of decentralized assets ENVIROMENTAL: Environmental policies for CO2 and restrictions in cities, Pollution level LEGAL: Regulations and incentives for provision to TSO and DSO, Regulation for integration of EV in the electricity markets, Privacy and security regulations

also arbitrage, black start, etc.

Does your company/industry have sustainability targets, or is it being (or planning to be) financed by green bonds or by any other financial instruments linked to efficiency or sustainability targets?

The company places high importance in sustainability and tries to implement it in all its activities. Being a clean energy producer (RES), the promotion of sustainability is a key driver. There is no exterior financing, all actions are financed by the company itself. One

No target fixed at the moment.

I don’t know. The energy storage industry does not have common sustainability targets, but is increasingly focused on developing better manufacturing and recycling processes, particularly for batteries.

Yes. Respondent 7 is leading the transition towards a sustainable energy model through investments in renewable energy, smart grids, large-scale energy storage and digital transformation, offering the most advanced products and services to our customers.


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of the latest actions is the concept of the Sustainable Plant Program, in the content of which all sustainable best practices in our plants all over the world and communicated in order to be applied universally. New best practices are fincanced and supported.

· If yes, where, how much, for when?

0 net emissions 2021

See links above

· If yes, do these targets include participation in smart-grids and/or demand-response programs?

NO See links above

How sensitive is your company/ industry to energy pricing?

All of the company’s plants are in the FiT scheme and therefore they are not affected by pricing. The only plants that will be affected are a wind plant in Evoia whose PPA is finishing in a couple of years and the

Very sensitive Not yet sensitive but will be. The highest of the barriers is the poor compensation for offering ancillary services.

Variable pricing, locational pricing, and scarcity pricing would incentivize investments in flexibility technologies.

Is sensitive, but the most of the times electricity costs are transferred to our customers

Very sensitive in the generation side

Very sensitive. Direct impact on revenues.


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wind plants in Crete which will receive a lower price after the completetion of the island’s interconnection with the mainland.

1.3. For Consumer(s)

Could you split your current typical yearly power consumption amongst the following categories? (if possible in MWh or % of consumption)

PROCESS

- Heating/furnaces/dryers/ovens, etc.

10% 80% N/A

- Cooling & refrigeration

15% N/A

- Pumps/fans/blowers/compressors

5% 10% 100%

- Process specific (electrochemical, motors, robots, conveyor belts, etc)

30%

NON PROCESS

- HVAC 20% 8%

- Lighting 15% 13%

- Others 5% 10% 60%


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Does your company/industry typically adopt on-site generation solutions?

The plants cover their self-consumptions during operation.

Power plant can be installed in case process gas can be valorized. only safety generators.

Energy storage systems are commonly co-located with renewables or thermal generation.

YES Yes

· If so, which one, where, how and how much?

COGENERATION & SFV IN ROOFTOPS

Solar Thermal and Solar PV with Li-ion storage technology, integrated in the roof of the houses, or built within solar carparks. - Solar PV 3,5 kWp per house on average - Energy Storage system 13,5 kWh capacity

· If yes, what is the main purpose and dimensioning of these on-site generation solutions?

SELFCONSUMTION Reduce the demand of electricity from the grid, thanks to superior thermal insulation and on-site generation of electricity for the homes. Up to 83% Electrical heating demand reduction due high efficiency building insulation compared to a standard house. On-site generation


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from PV installation of 2,784 kWh/year on average, which combined with storage can achieve autoconsumtion levels of up to 75% Ultimately, reductions of up to 80% can be achieved in the energy bills of the households.

Does your company/industry have some technical flexibility to change the profile of power consumption associated to some specific uses or processes (i.e. moving consumption from one hour to other)?

At the moment no, but it could be implemented with the proper technical upgardes.

Yes Decrease consumption for a given period of time with some constraints on the duration, the delay from information to activation

Yes, the main purpose of energy storage is to separate the generation and final consumption of energy, both geographically and over time.

NO Yes


10MW Use of energy storage by means of Li-ion batteries (domestic individual units, or larger centralized batteries for communities managed as a private smart grid) Batteries can also be connected in P2P networks in


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order to optimally exchange and trade energy among users in the community.

· If yes, short commentary on main objectives and barriers

Main objective is to offer homes which are more affordable to run in the long term, by reducing the energy bills for the users. Our ambition is to make housing more affordable to buy and to cheaper to live in.

Could your company/industry be technically able to assume a limited number of interruptions of supply and /or reductions of maximum energy demand during short period of time (i.e. some minutes for air conditioning)?

At the moment no, but it could be implemented with the proper technical upgardes.

Not assessed at the moment,increase of power consumption for fans is possible and already done.

NO Yes


Respondent 6 feature energy storage, typically of 13,5 kWh per domestic unit. This allows the houses to become


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independent from the grid at times of grid outages, or to reduce the demand form the grid when there is power limitations.


Respondent 6 user reliability of supply, as the solar PV with storage can work in island mode for some hours, which is especially relevant in countries or areas where the grid is unstable or unreliable.

Could your company/industry be technically able to provide flexibilities on power consumption for thermal processes, backed by thermal energy storage systems (i.e. some minutes for water heaters)?

No. N/A NO Yes


Respondent 6 feature solar thermal panels and 150l water thank which is powered from the solar PV system


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4.4. For Generator(s)

Do you provide grid services? (See 2.3 for definition for grid services)

No we do not. Theoretically Frequency control

Energy storage systems commonly provide FCR, FRR, and RR, depending on whether these services are tendered on the market and open to participation of storage devices. Storage also provides new ancillary services such as enhanced frequency response in the UK and DS3 system services in Ireland.

N/A

Currently not. In larger developments, Respondent 6 might in the future design private networks where large solar plants and centralized storage will be connected, and the technology will allow to provide some grid services.

Reactive power/cos phi control, Tertiary reserve, firming.

· If yes, what type of grid services. What are the settlement rules?

Fixed remuneration Reactive power/ cos phi: With the reactive power capacity of the turbines, the Wind Farm is able to follow a setpoint in the Point of interconnection. Depends on the characteristics of the connection point ( Scc, Capacity, etc)


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Active Power control: Congestion management. The WF is able to control the active power ( reduce/increase) at the POI within the limits of the available power.

· If no, why? Are you technically able to provide grid services? Which sort of flexibility could you provide to the grid?

Energy storage devices, due to their fast reaction times and flexibility, are well suited to providing different grid services at various timescales.

Yes, Respondent 6 technology is able to provide grid services such as flexibility of demand relying on chemical Li-ion storage, and even controlled islanding.

What are the main barriers in order to participate in the provision of grid services?

The current legislation.

Some markets are not open to stand-alone energy storage devices providing grid services. Also, technical requirements may be overly cautious, e.g. requiring longer activation periods than technically necessary to respond to most frequency events, which puts energy storage at a disadvantage

N/A Not economically feasible, so far.


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compared to generation technologies.

Do you expect to participate in grid services directly or indirectly via upstream aggregators?

We would be interested to act as aggregator for RES units.

Currently indirect, if harmonization makes it easier to cover a European scope then why not directly

Energy storage can participate both directly in grid services (front-of-meter storage devices) and via aggregators (behind-the-meter storage).

N/A Possibly yes as long as the business model allows to do this in a competitive economic way.

Yes

4.5. Potential Future Developments

Do you see opportunities in the incorporation of energy storage technology?

The company already owns a storage system for the provision of frequency control in another country. If the legislation allows, the already acquired knowledge will be implemented in similar projects in Greece. EV chargers already installed at the company’s headquarters.

Reduction of gird costs combined with safety generation replacing diesel generators

Yes. Yes. Storage is the essential to integrate RES And can provide a wide range of services from ultra-fast responding synthetic inertia to longer-duration balancing.

YES Yes Yes, for active power reserve services, energy shifting and black start, etc.


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Do you see opportunities in the incorporation of electric mobility solutions?

Yes we do and we already investigate the possible solutions.

No

Yes.

Vehicle to grid solutions should be further investigated.

YES Yes

· If yes, where, how and how much (if possible in MWh or % of consumption)?

We are not ready yet to provide accurate numbers but we are exploring both fleet management and V2G opportunities.

Our R1 remuneration is already impacted by storage development,

For us it is not about the consumption, it is about the new services that we can offer.

NOT EVALUATED In addition to local/centralized storage static systems, the use of the storage in Electric Vehicles (EVs) will be connected with the grid to exchange electricity between EVs and Respondent 6.

Do you think your company/industry’s participation in demand-response programs would be affected by the adoption of energy storage?

Yes energy storage will be a crucial parameter for the implementation of demand-response and will definitely facilitate every related process.

Our EV are the energy storage units. We need them to offer DR programs.

Energy storage and demand response are not always distinctly separate. For instance, some consider demand response to include thermal storage devices such as hot water heaters. Therefore, it’s not so easy to differentiate between pure energy storage and demand response.

YES

Yes Yes


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Which sort of flexibility could your company/industry provide to the grid? (see tables in 2.4.2)

It highly depends on the technology. If RES units are combined with storage or upgraded (for example inverter technology for provision of ancillary services) they could provide most of the flexibility types. (storage alone)

Theoretically mFRR, RR

The first of the services that will be offered are voltage control & congestion management. Then depending on the car pool also Frequency control. Islanding might not be profitability attractive enough.

Depending on the storage technology, storage can provide FCR, FRR, RR, congestion management, voltage control, reactive power, inertial response, black start, and intentional islanding. Storage can also provide new ancillary services (e.g. enhanced frequency response, synchronous inertia response, fast frequency response, ramping margin, etc). Moreover, storage can also be used to defer or avoid transmission and distribution grid investments and provide customer energy management services such as end-user peak shaving.

N/A Balancing (frequency and voltage control), congestion demand, and controlled islanding

Balancing, congestion management, Voltage control.

Which sort of flexibility could ABSOLUTELY NOT your

Depending on the technology (RES + storage or storage stand-alone) we

As it is designed Black start is difficult to foresee. Inertial response

Not sure about it. At this stage, energy storage technologies for weekly and

N/A Intertial response and black start


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company/industry provide to the grid?

would be able to provide all grid services.

seasonal balancing are not mature enough to provide such services cost-effectively.

Which revenue/return analysis would you perform to assess your potential participation in demand response programs?

The IRR will be the main KPI to assess a new implementation.

Revenue vs variable cost and loss of production

Not sure about it.

We would make an incremental capital investment return analysis that should hit our minimum company IRR targets.


Do you expect your participation to take place directly or indirectly via upstream aggregators?

We expect to be the aggregator.

both It could be both directly done with an aggregator, or we could directly become the aggregator.

Both, depending on whether storage is installed behind or in front of the meter.

N/A Both alternatives are open right now

Yes

What would be the best and main enablers for you to consider participating in demand response programs?

The most important is the legislative framework. In addition, the remuneration needs to be high enough in order to provide incentive for participation to the end users.

remuneration Not relevant. Price storage systems

Participating in demand-response programs should be an economic activity with returns which are balanced with the level of risks. We would expect to have advantages from the DNO/TSOs for such participating, for example preferential access to the grid capacity to connect RREE generators and storage systems



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9. References

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der modelling - coordinet project

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