Alexandre, Benoit, Emmanuel Alain Bernard

Antoine Ludovic

Fabrice

inestimable. Enfin Je Pense À Nicole

Sandrine, Thibault Yves Catherine

Sylvain, Laurent Thierry Olivier

François Jean-Christophe Patrick

Avant-Propos Christophe

Philippe

Jean Michel

Sandeep, Olivier, Bernard Romain Gilles

Rodolphe Yann

Thierry, Kamel, Gérard Avancées Cédric

Antoine Jacques

Karel Tom Sindhu

Christian Guillaume

Dien Hector Naila

Maxime Hoa Théo

Loann Matthieu Timothé

Brida Luis

Renaud Guillaume

Gauthier Olivier Samuel

Gabrielle

Clément Paul

Lucile Nicolas

Wilhem Aurore

Antonin Paul

Pierre, Hervé, Damien Gilles

Cyril

Patrick Bruno

Keywords: Mécanique lourde, câblage industriel, électronique, informatique industrielle, simulation temps

Avant-Propos

La lecture de cent-cinquante pages est somme toute prenante. Un déplacement à Grenoble au milieu d'épisodes de grèves l'est tout autant pour des personnes aux agendas si chargés. Messieurs Geconninck, Mayer, Edin, Henry, Terenti, Glatigny, Hadjsaid et Caire, ce fut donc un réel honneur de pouvoir confronter mes travaux à votre expérience tant scientifique qu'industrielle. Je vous en suis hautement reconnaissant. Je suis tout autant reconnaissant envers mes quatre encadrants, Messieurs Bediou, Glatigny, Hadjsaid et Caire pour la confiance et la grande liberté d'entreprendre qu'ils m'ont accordé durant ces trois années. Stéphane, je n'oublie pas les invitations croisées au Casset et sur le Vercors pour parler double-diode, stockage, VPP et j'en passe. Raphaël, je te remercie d'avoir misé sur moi il y a quatre ans, malgré un agenda déjà surchargé. Je garde en souvenir ces réunions en mouvement entre avion, navette aéroport, vélo sous la pluie vs. tram, qui exprimèrent bien mieux notre souhait d'aller de l'avant que des rapports d'avancement sans grand devenir. Merci. Je n'oublierai pas non plus les premiers mots de Monsieur Kaschny à mon égard lors mon arrivée chez Schneider Electric« Bienvenue parmi nous. Tu es là pour apprendre, profites-en et amusestoi ». Fraîchement diplômé, je me suis dit alors « Tout de même, c'est bon le Demand Response, je commence à connaître . . . ». Trois ans plus tard, mon immersion dans cet environnement industriel m'a énormément apporté et oui nettement, j'ai beaucoup appris. Merci ! Le quotidien n'a pas toujours été évident. Les Pyrénées se sont avérées compliqués à franchir. Nous nous sommes également convertis au Riesling avec plus ou moins de facilité. Au final « ce vin sec, vertical, [. . .] construit autour d'une belle vivacité que l'on apprécie du début jusqu'à la fin, [. . .] marqué par l'ampleur » décrit parfaitement les clients et avant tout collègues d'Electricité de Strasbourg Réseaux, que je me réjouis d'avoir pu côtoyer au sein du projet européen Dream. Inévitablement, j'associe Elisabeth à cette pensée, Grenobloise puis Strasbourgeoise d'adoption, qui s'est arrangée à merveille d'un positionnement au sein du projet plus que complexe. Le déploiement des équipements de Dream sur Strasbourg n'aurait pas pu être possible sans le soutien des collègues de Schneider Electric à commencer par Stéphane, Yves,

frequency Nadir (red surface), depending on the availability of primary reserves.

Comparison of the frequency Nadir with the first UFLS step at 49Hz (purple surface) [START_REF] Das | Primary reserve studies for high wind power penetrated systems[END_REF] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II.20 Evolution of system kinetic energy along the day in islanded network depending of PV production and inherited unit commitment of conventional generation units. Case A/B/C: different strategies of grid tariff, likely to modify the unit commitment strategies of power producers [START_REF] Cardozo | A statistical analysis of the frequency response in an isolated power system with an increasing share of photo-voltaic generation[END_REF] . . . . . . . . . II.21 Evolution of Power flow in Kuching Island faced with to 30% RES-E penetration [START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II.22 Effect of UFLS weakening due to by RES-E spreading on Kuching power system face to the reference incident (loss of the 0.48pu interconnection) [START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF] Assessment of load-shifting costs for either ESS or thermal storage . . . . . . . .

II.1

Typical inertia constants H i of synchronous machines [START_REF] Kothari | Power System Engineering, 2e[END_REF]] II. 2 FCR providing groups and units' minimum frequency accuracy and insensitivity requirement(Art 44 (1), [START_REF] Entso-E | Network code on electricity balancing[END_REF]) . . . . . . . . . . . . . . . . . . . . . II. 3 References numbers used in Figures II.9

General introduction

General Introduction

1 From Geopolitics to Smart Grid

Geopolitics incentives

The business perspectives of Smart Grid solutions presently under discussion among scientists and European industrial communities came initially from geopolitic incentives which appeared in the early 2000s. These incentives are split into two categories. The first category of incentives appears as a response to the need to secure national energy independence. The second category consist of environmentally-based incentives, which aim to mitigate climate change by limiting the Greenhouse Gas (GhG) emissions of the power or transportation industries.

Smart Grid

The Smart Grid can be defined as all new ICT technologies that would make power system assets communicant, with the final objective to support utilities in their evolution towards an evolved power system architecture, induced by the energy transition. The challenge of the utilities will be to rely on a roll-out of Smart Grid functions, to adapt their assets of power production, transmission, distribution, metering, storage and consumption in addition of solely investing in grid reinforcement and additional Reserve Capacities. Such modernization of power system assets is expected to contribute to maintain or even the improvement of the system resiliency as well as an economical delivery of electricity in a more and more complex environment. The power system would thus be operated in a more flexible way, allowing operational constraints such as the intermittence of Renewable Energy Resources (RES-E) to be handled more efficiently. Meantime, it should allow new uses of electricity such as the Electric Vehicle (EV). Progressively the real-time balance between production and consumption balance would move from a paradigm where the production is adapted to the demand towards a new paradigm where the demand has to be synchronized with the availability of the production instead. Becoming a real actor of the power system reliability, the consumer would become a "prosumer" [Smart Grid CRE, 2015].

The energy independence incentives have led to three major decisions. The first decision came from the utilities who decided to invest in Combined Cycle Gas Turbines (CCGT) over the past ten years. It aimed to improve the efficiency of their power assets and diversify their sources of supply, enjoying the emergence of a new route of importation of Liquefied Natural Gas (LNG) from the Middle-east, through shipping. The capacity of LNG exporting terminals of Ras Laffan (Qatar) rose by 250% from 2008 to 2011, to reach a level of nearly 80 Million Metric Tonne Per Annum (mmtpa) (1219 TWh) (Figure 1), while the technological progress of gas turbines enabled the utilities to reach levels of efficiency of 60% for the latest CCGT units.

It appeared thus as a great opportunity to reduce meantime the dependency of Europe towards the uncertain Russian gas and the GhG emission of power assets. ENGIE commissioned the first French CCGT in 2005 in Dunkerque at the benefit of Arcelor Mittal.

The second decision came from the US administration, that bet on the exploitation of shale gas to increase its national production of fossil fuels, in order to both reduce its energy dependency towards the OPEC countries and enable the US citizens to enjoy cheaper fossil fuels prices. This decision led to an excess of coal in the US, that was then exported to Europe at a price which halved from April 2011 to April 2015 (Figure 3).

The third political decision came from the European regulation entities, who have initiated a progressive commissioning of feed-in tariffs applied to the Renewable Energy Sources for Electricity (RES-E) connected to the European grid. This decision has been driven by both energy dependency and environmental issues. Starting from this decision, and in addition to a favourable technical learning curve of RES-E sources and the simplification of administrative RES-E deployment's procedures, the penetration of RES-E in Europe have started to rise significantly (Figure 2).

The field of environmental incentives have been completed by two additional decisions. Firstly, a compulsory phasing-out of high-pollutant European power units by January 1st, 2016 have been stated by the European Commission. Secondly, several European countries have decided to terminate their nuclear program at the mid-term benefit of RES-E due to Fukushima. The decision of the European Commission would induce the phasing-out of 4 -5GW of peak-load capacity among the 130GW of French power assets [START_REF] Rte | Generation adequacy report 2012[END_REF], while nuclear phase-out would prevent countries such as Germany to benefit from a cheap base-load capacity.

1. FROM GEOPOLITICS TO SMART GRID 2000[START_REF] Hodge | Distributed frequency relay -us patent 6[END_REF]2002200320042005200620072008

Bankruptcy of gas-fired assets

The consequence of these non-correlated successive decisions lead to a collapse of competitiveness of the European gas-fired assets confronted to RES-E and coal. RES-E have started to damage the profitability of gas-fired assets, by reducing their yearly operation rate due to the priority dispatch commitment of RES-E units on the market (principle of feed-in tariff). The US decision to exploit shale gas led then to a drop in coal prices worldwide from January 2011, while the Russian gas prices which feed European countries doubled from late 2009 to early 2012 (Figure 3). This fall of coal prices has been induced by a discardment of coal by the US industries at the benefit of shale gas, while the US did not export shale gas for both strategic reasons and the lack of LNG exporting terminals in the US. That led to a massive export of cheap coal to Europe, which reversed the competitiveness of coal-fired power plants compared to gas-fired assets. The coup de grâce came finally from the collapse of the CO 2 price on the European Trading System (ETS) that lightens even more the marginal cost of coal (Figure 4). ENGIE has clearly identified the annual or seasonal shutting down of three of its four French gas-fired units in mid 2013, as a consequence of coal competition [Les Echos, 2013]. Since October 2014, the successive and spectacular drops in crude oil price, the Russian gas price and even the LNG price in Japan have not been followed by the massive reopening of gas-fired assets in Europe, probably due to the existence of long-term gas delivery contracts that mitigates the volatility of the prices. Finally, the drop under 40e/MWh of the power prices on the European wholesale markets that occurred in 2015 due to an excess of power capacities make the reopening of these assets even more complicated.

Migration toward Distributed Energy Resources (DERs) assets

This new paradigm induces the apparition of new kind of unit commitment strategies driven by non-dispatchable Distributed Generation (DG). Such evolution would lead to several consequences for the power system such as:

the mid-term scarcity of bulk generation, which operates as base-load, would reduce the availability of conventional frequency-controlled reserves that are vital for the power system stability;

the phasing-out of dispatchable sources in countries where the power consumption is still increasing, is likely to directly alter the peak-load adequacy of the power system; the significant connection of DG assets on the distribution grid would induce a risk of congestion on these grids, impeding so far the overall objective of maximization of grid-coupling of any carbon-free assets;

the solutions proposed for handling the challenges quoted above, sometimes leads to the modulation of the level of generation of Distributed Energy Resources (DERs) assets to facilitate the operations of power transmission, power distribution or power trading. However a given modulation can induce contradictory results depending on the issue it solves. Consequently, a fourth challenge is to coordinate these needs to reach an adequate level of satisfaction at the scale of the power system; the last challenge is finally to build business models that are profitable enough to enable the contribution of DERs in the resolution of the challenges presented above.

Structure of the thesis

In response to such an evolving paradigm, a review of the main power market products is produced in Chapter I, in order to assess the business opportunities that would be handled by DER flexibility assets. Among these markets, the supply of frequency-controlled reserves has been identified as economically promising and technically challenging for the power system stability. Chapter II investigates thus in detail the processes operated by the System Operators to ensure the system stability. Chapter II identifies as well the obstacles that the deregulation of the power markets and the wide penetration of RES-E would present for the system stability.

Based on the outcomes of the two first chapters, the PhD work focussed then on the development of the Primary Support initiative, which is presented in Chapter III. Primary Support is an innovative process of firm supply of frequency-controlled reserves, that relies on a coordinated modulation of the level of load of DER assets. Chapter IV presents finally the initiatives of demonstration of Primary Support that have been performed since 2013 to promote the supply of frequency-controlled reserves from the control of DERs.

Publications 4 Axis of research and of inspiration of the present thesis

The list of publications presented in Section 3 has shown contributions in domains such as distributed VoltVAR Management and DER operation coordination, that are not mentioned in the structure of the thesis presented in Section 2. Such differences are justified by the editorial choices that have been taken to ensure the consistency of the present PhD thesis. Given that

European initiatives linked to this PhD work

This PhD work relies upon the involvement in three different European initiatives: the Instinct initiative of KIC InnoEnergy CC Sweden and both EvolvDSO and Dream FP7 projects funded by the European Commission (EC grant agreements n • 608732 and n • 609359).

MAIN CONTRIBUTIONS

the final opinion expressed in this PhD has been influenced by these parallel contributions, all of them are consequently summarized from Figure A.1 to Figure A.7 in Appendix A, including the contributions that will not be developed in the present PhD thesis.

Main contributions

Six main contributions of this work are listed below:

1. It identifies the either wholesale or ancillary services power products, whose delivery by DERs and especially by DR assets would be the most profitable (Section 2 in Ch I).

2. It popularizes the operational principles and reserves architectures, that guarantee the power system stability (Section 1 in Ch II).

3. It popularizes the sections of the Network Codes on Electricity Balancing and on Load-Frequency Control and Reserves [ENTSO-E, 2013c,d], that establish the operational rules in charge of guaranteeing the power system stability (Section 1 in Ch II).

4. It identifies the main challenges that both the power market deregulation and the large penetration of Distributed Generation (DG) would induce on the system stability and especially on the frequency containment defence plan (Section 2 in Ch II) .

5. It claims an innovative method of coordination of DER assets, that enables the involvement of DERs of different natures in the supply of Frequency Containment Reserve (FCR) at the benefit of the System Operators. Without coordination, most of DERs could not guarantee of 24/7 delivery of the same level of reserve, that justified the development of such advanced method (Section 3 in Ch III).

6. It demonstrates the previous concept with three main objectives. The first objective targets to test different architectures of DER controllers, adapted to different nature of DERs. Then this PhD work aims to validate the architecture of DER coordination. Finally it aims to obtain a final solution having a Technology Readiness Level (TRL) at least of five. The obtaining of such TRL aims to enhance the probability of adoption of the solution by the management of Schneider Electric (Chapter IV).

Glossary of Important Terms and Abbreviations

Adequacy: System's ability to meet consumers' total power demand and to satisfy their requirements as regards energy at all times, taking account of planned and reasonably expectable trips of system elements. The concept covers stationary conditions [START_REF] Energinet | System plan 2007[END_REF].

aFRR: Frequency Restoration Reserves that can be activated by an automatic control device [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF]. ⊲ Frequency Restoration Reserves.

Ancillary services: Joint name for various services to which TSOs require access in the operating phase in order to maintain the safe and stable operation of the electricity system [Energinet, GENERAL INTRODUCTION 2007].

Balance Responsible Party (BRP): A party that has a contract proving financial security and identifying balance responsibility with the Imbalance Settlement Responsible of the Market Balance Area entitling the party to operate in the market. This is the only role allowing a party to nominate energy on a wholesale level [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

Balancing Area: Areas of the power system where there is continuous regulation in order to maintain the frequency and a physical balance in relation to adjacent areas. In the Nordic area, the synchronous system and Western Denmark are separate balance areas [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

Balancing: All actions and processes, on all time-lines, through which TSOs ensure, in a continuous way, to maintain the system frequency within a predefined stability range as set

Sharing partners of scientific and industrial knowledges

This PhD work has been largely inspired by beneficial discussions that occurred with colleagues and customers of the following companies and institutions.

GENERAL INTRODUCTION

and costs nearly 20-30e.

REE (Red Eléctrica de España): TSO of Spain.

Reference Incident: Largest power system incident having a sensible probability of occurrence among a Synchronous Area, that induces a power imbalance that must be handled by the Frequency Containment Process. See wider definition box in Section 1.4.

REN (Redes Energéticas Nacionais): TSO of Portugal.

Replacement Reserves: Reserves used to restore/support the required level of FRR to be prepared for additional system imbalances. This category includes operating reserves with activation time from Time to Restore Frequency up to hours [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

RES-E: ⊲ Electrical Renewable Energies Sources.

Reserve Capacity: Sum of the FCR, FRR or RR that needs to be available to the TS0 to ensure a resilient operation of the power system [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

Reserve Providing Group: Aggregation of Power Generating Modules Demand Unit and/or Reserve Providing Units connected to more than one Connection Point fulfilling the requirements for FCR FRR or RR [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

Reserve Providing Unit: Single or an aggregation of Power Generating Modules and/or Demand Units connected to a common Connection Point fulfilling the requirements for FCR FRR or RR [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

RR: ⊲ Replacement Reserves. See Section 1.6. SA: ⊲ Synchronous Area.

RPI

Smart Grid: All new ICT technologies that would make power system assets communicant, with the final objective to enable power system actors to overcome the mutation of the conventional power system, that is induced by the energy transition [Smart Grid CRE, 2015]. See wider definition box in Section 1.1.

Spread: Widest amplitude of market price between a set of price data of one day, one season, one year, etc.

Standard Frequency Deviation: Absolute value of the Frequency Deviation that limits the Standard Frequency Range [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

Standard Frequency Range: Interval defined symmetrically around the Nominal Frequency of a Synchronous Area. The System Frequency is supposed to stay contained within this Standard Frequency Range in normal operation [START_REF] Entso-E | Entso-e definitions and acronyms[END_REF].

Statnett: TSO of Norway.

Steady State Frequency Deviation: Absolute value of Frequency Deviation that is observed after the occurrence of an imbalance once the System Frequency has been stabilized [ENTSO-E,

CHAPTER I

Opportunity of DER involvement in power markets

Chapter I

Opportunity of DER involvement in power markets

One large concern of the present thesis is to identify the power markets willing to make DER flexibility and especially Demand Response (DR) profitable. The final objective is to make DERs take par as much as possible to the energy transition. In this context, Section 1 reviews the different power markets wherein DERs flexibility would be involved. Section 2 then identifies the business opportunities to make DER flexibility profitable at mid-term among the set of markets listed in Section 1. Section 3 summarizes the analysis either gathered or performed on our own to identify priority markets.

Overall market review

The power market is composed of a wide variety of products, whose most common products are presented in Figure I.1. These products that aim to satisfy different needs of the utilities can be split into two main categories: the wholesale products first, presented in Section 1.1 and the ancillary services products, presented in Section 1.2.

Wholesale electricity markets

It can be distinguished first the power products that formalize the exchange between the energy buyers and sellers. These exchanges occur among a set of energy markets that can be defined as the wholesale markets 1 , and consist commonly of exchange from the power producers down to the power retailers. The wholesale markets address the trading of firm volumes of energy to be delivered during periods that have a predetermined length: 15 minutes (quarter bids), one hour (hourly bids) or several hours (block bids). This category of wholesale market can be split into two sub-categories, that are differentiated from one another depending on the time horizon From a period that lasts from five years ahead to two days ahead the delivery, the bids can be traded on open-access Long Term markets. These Long Term markets are actually risk hedging markets and do not consider the physical ability of the power system to deliver such power over the grid.

From the day-ahead down to 30 minutes before the delivery, energy bids can be exchanged over the open-access trading platform called the spot market. The spot market is split between the day-ahead spot market whose auction gate closes at mid-day in the day-ahead, the delivery and the intra-day spot market, where bids can be exchanged down to 30 minutes ahead of the delivery in real-time [Epex Spot SE, 2015a]. Epex Spot SE [2015a] is the power spot market operator that covers France, Germany, Austria and Switzerland. Nord Pool Spot [2015] covers of the Nordics and Baltics countries. The TSO which is in charge of the system operation in a given area of delivery can validate or reject the bids that have been exchanged on the spot market if it would result in situations of non-transmittable power on their grid. In some areas, the spot market is even split in different sub-markets depending on the area of delivery of the bid. Such areas are defined as bidding areas. Figure I.2 lists for instance the bidding area of the Nordics and Baltics. In such markets, the amount of power that is allowed for trading between different bidding areas are stated in advance by the TSOs. This enables automatic forbidding of the exchange of bids over a given power limit during the market clearing instead of after the clearing thanks to a reverse process of cancellation. According to such a principle, the areas of delivery of two different countries, operated by two different TSOs are usually considered as two different bidding areas. Lastly, power system actors are willing to trade bilateral bids in parallel to the open-access platforms of trading that have been previously presented. In such a case, neither the volumes Pool Spot, 2015] nor the prices of each bilateral transaction are published.

The principle of power procurement performed by each power retailer from more than one year ahead, down to the real time, in order to balance its portfolio of power is explained in detail by [START_REF] Kok | The PowerMatcher: Smart Coordination for the Smart Electricity Grid[END_REF]. Figure I.3 provides the resulting portfolio of power bids purchased and resold by a given retailer to match with the linear demand of the portfolio of grid users he has to balance.

The wholesale markets aforementioned address the trading of firm amount of energy to be injected in the power system: these are energy markets. In parallel, capacity market has also been introduced to guarantee either the power system adequacy or the access to inter-bidding area interconnections. RTE has for instance introduced such a mechanism of capacity trading in 2015 and Epex Spot will commission a public platform of Capacity Auction trading during 2016 [Epex Spot SE, 2015b]. The capacity mechanism obligates a retailer to purchase capacity auctions in proportion to the theoretical peak-load of its portfolio. These capacities can be purchased from power producers or from DER operators.

The access of inter-bidding area interconnections is then guaranteed by Market Coupling capacities [Epex Spot SE, 2015c], where one-hour-long auctions are exchanged every day. The introduction of such capacities can be seen as a way to dissociate the marginal cost of production that is traded on the spot market from the cost of using a given interconnection to export or import power between two bidding areas. The introduction of such products would perhaps enable the TSOs to finance new inter-bidding areas interconnections to allow power users to benefit of the lowest power price, regardless where this power is produced within the synchronous area i.e maximizing the market coupling across Europe.

Ancillary services products

The ancillary services constitute the second major category of power products that gather energy or capacity underlying that enables the utilities -and especially the System Operators -to ensure Figure I.3: Procurement and resale of different power products to get a resultant profile that complies with a linear evolution of the demand. Gray and white blocks: long-term ahead bids purchase. Red blocks: close to real-time bids purchase. Green blocks: close to real-time bids resale. [START_REF] Kok | The PowerMatcher: Smart Coordination for the Smart Electricity Grid[END_REF] the reliability of the power system. The most well known ancillary services are purchased by TSOs to ensure the system stability with regards to the occurrence of sudden power system disturbances (see Ch.II Section 1.2). These are in particular the Replacement Reserves (RR), the Frequency Restoration Reserves (FRR) and the Frequency Containment Reserves (FCR), which are each responsible for maintaining the system frequency, through adjusting generation output to the load variation or unbalance (see Ch.II Section 1.3). The underlying of the FCR (see Ch.II Section 1.4) is the injection or withdrawal of unpredictable amount of power within 15 seconds for brief amount of time at random periods of time (see Ch.II Section 4.3). The RR (see Ch.II Section 1.6) addresses the injection or withdrawal of a predetermined amount of power for a given amount of time at an exact time decided by the TSO 15 minutes in advance -not at a precise gate as for spot market products. Thus the FCR is a capacity product while the RR is an energy product quite similar to the interday quarter product. In this spirit, the FRR (see Ch.II Section 1.5) is at the mid-way point between the FCR and the RR.

Mid-way between the concerns of markets and system reliability, a variety of products aims to ensure the system adequacy at the peak load, thanks to either specific peak load energy bids, RR bids or capacity auctions. The call for each of these products differs depending on the TSO in charge of the system operation and can be ranked as either energy or capacity products. As examples, RTE relies up to 2018 only on the RR to deal with potential issues of peak load adequacy, while the first role of the RR is to contribute to the system balance. RTE launched hence in the past formalized products within the RR such as the Fast Tertiary Control (1000MW) and the Additional Tertiary Control (500MW) [START_REF] Cre | Consultation publique de la commission de régulation de l'énergie du 6 novembre 2012 sur les quatrièmes tarifs d'utilisation des réseaux publics d'électricité[END_REF], to secure peak load capacities despite the absence of a wide-scale capacity mechanism. RTE expects to secure the procurement of peak load capacity thanks to such large scale Capacity Auction to be used by 2017 only (mechanism launched in 2015). Meantime Svenska Kraftnät operates the Effektreserven to formalize on its own the procurement of peak load flexibilities and so lighten the role of the RR in such situation.

Last but not least, the System Operators have access to a variety of products capable of facilitating the grid operations -other than the previous products that address the system operations -, such as contributions to VoltVAR management, congestion management or even losses savings. The VoltVAR management is a function already formalized by TSOs. The other functions and again VoltVAR are products whose procurement is also foreseen by DSOs as new Smart Grid tools.

Business opportunities of DER flexibility

Following the review of power products that has been presented above, the present section aims to identify the business opportunity that each of these products would represent for DERs.

Both the industrial and scientific communities strongly believe in the opportunity that DER flexibility would represent to facilitate both the power grid and power system operations, but the questions of when? and how far? are still opened. A wide range of wholesale and ancillary services products would be concerned, at least in the long-term perspective: grid reinforcement deferral postponing, support to self-healing reconfiguration supporting, VoltVAR management, peak load management, intermittent RES-E balancing, frequency-controlled reserves supplying, etc. While most of these DER-based functions will be technically ready to penetrate the market by 2020, the key factor of the success of these functions will depend on the ability of the utilities to involve DERs in their business, on a profitable manner.

The analysis is dependent on a literature review and on specific Cost Benefit Analysis models developed for the needs of the present review. The review starts from the products traded on the less fluid markets up to the most fluid ones. The products related to grid operation reliability are addressed first, followed by the power system security & stability products (see definition in Preamble: the present review mainly performed in 2013 is not exhaustive. It targets the building of a personal opinion regarding the opportunity of profitability of DERs on the wholesale and ancillary services markets at the date of the review.

Grid losses savings

The shifting of load from peak period to off-peak period has been investigated in the literature as a source of cost saving for the System Operators, especially in distribution. The present section, based on the contributions of E-Cube [2013] and [START_REF] Nourai | Load leveling reduces t&d line losses[END_REF], assesses the added-value of DER flexibility in such use case. [START_REF] Nourai | Load leveling reduces t&d line losses[END_REF] claims for physical savings of 181-336MWh/yr per MW of flexibility, on a US network of low quality (12% of T&D technical losses against 6% in France [ErDF, 2009[START_REF] Rte | Portail clients rte: Pertes sur le réseau public de transport[END_REF]). The saving relies on the load-shifting from peak to off-peak periods, every day (Figure I.5 (b)). [START_REF] Nourai | Load leveling reduces t&d line losses[END_REF] consider only the resistive losses among the wires and not additional potential savings that would be performed within MV/LV substations depending on the size and number of transformers compared to the LV loads. A total grid cost saving of 12.2-20.2ke/MW DER /yr can be assessed (Table I.1). Both papers assess however a load-shifting over several hours from peak to off-peak that cannot be provided by any type of DR technologies. Thus grid losses savings opportunities are not able to generate sufficient value on their own to make this business model profitable. Moreover, the regulation is not favourable yet in several countries to enable the DSOs to perform energy trading for purposes like load shifting at their own benefit.

VoltVAR & congestion management

The value of DER flexibility on the distribution markets remains uncertain faced with a lack of industrial deployment feedback and effective large-scale needs of the DSOs. Such assessment concern especially the solutions that target VoltVAR or congestion management. Such solutions aim mainly to contain grid reinforcement costs, and eventually to contain grid operation cost. [START_REF] Gouin | Évaluation de l'impact du Smart Grid sur les pratiques de planification en cas d'insertion de production décentralisée et de charges flexibles[END_REF] supports this view, observing a contribution of DER flexibility on suburban distribution grid reinforcement costs. However such deployment can slightly increase the probability of outage occurrence on the grid, that challenges the reliability KPIs of the DSOs. [START_REF] Battegay | Valorisation des gisements de flexibilité dans les investissements smart grid[END_REF] also identifies a beneficial contribution of DER flexibility on suburban grid reinforcement costs. The authors moderate however their statement given the difficulties of application of such DER-related reinforcement policies. Indeed, suburban grid reinforcement works are usually performed in parallel of other street works such as the building of a new tramway line, before the occurrence of a distribution constraint. Hence, at such date no clear benchmark could be performed to compare the cost of grid reinforcement and of DER flexibility, and the option of grid reinforcement would remain the solution selected. [START_REF] Battegay | Benefits analysis of voltage regulation on mv networks investments[END_REF] observe finally that DERs' reactive power flexibility is capable of providing interesting VoltVAR support especially in rural area to avoid reinforcement when facing DG deployment. In these areas, the service of constraint management would be provided directly by the DER which had provoked the constraint, thanks to an adaptation of its pattern of power injection or withdrawal. Indeed, it would be too complicated to rely on an additional DER asset instead, such as a DR or an Energy Storage System (ESS) would have been deployed for such dedicated purpose. [2013] publishes a value of 20-70ke/MW/yr -without explaining how they got itderived from US distribution utilities publications, which have however the reputation to operate Finally DERs would be of interest for daily DSOs' operation and investment sparing. However, it seems that they have not been added to the industrial road map of the distribution utilities yet. Hence there is no business model of VoltVAR and congestion management, relying on DER flexibility that is profitable at the date of the review.

E-Cube

Frequency Containment Reserves (FCR)

The present review of DER business opportunities focusses then to the power system security & stability products, starting from the FCR. Figure I.6 provides thus the overall addressable market of FCR in Europe. Upward regulation prices last from 12e/MW/h in Denmark East to up to 42e/MW/h in Denmark West, i.e 100-350ke/MW/yr for a full time availability. These figures are especially high and can be claimed as being a clear business opportunities for the supply of FCR by DER flexibility. The question of effective needs for a contribution of DER in the supply of FCR is further addressed in Ch II. Section 2, while Chapter III provides a solution able to supply FCR based on a specific coordination of DERs.

Frequency Restoration Reserve (FRR)

The FRR business opportunities are slightly more complicated to assess given that the remuneration of FRR is usually composed of both capacity and energy components. Moreover the capacity component is a firm remuneration while the energy component is a remuneration provided by the TSO for the upward volumes of FRR injected into the grid but a charge to pay to the TSO for the downward volumes withdrawn from the grid.

Figures I.7 and I.8 display the distribution of prices of two weekly tenders for a delivery of automatic FRR (aFRR) in all of Germany in the first week of February and June 2015 respectively. It shows typical upward capacity prices of 2.5-8e/MW/hr. Per year it represents a remuneration of 22-70ke/MW/yr that appears to be a convenient remuneration for DERs. In the meantime, such capacity prices are of 16.96e/MW/hr in France i.e 148ke/MW/yr, but with complementary energy remuneration that is regulated (Table I.2).

Note: The German aFRR energy prices of Figures I.7 and I.8 appears as excessively expensive for both upward and downward reserves -prices of 6000e/MWh commonly occur -and have thus not been considered in the present partial review of FRR values.

Restoration Reserves (RR)

The RR is a Balancing Reserve that requires few requirements: the activation time is about 15 minutes, and it does not require specific geographic constraints of grid injection [START_REF] Entso-E | Network code on electricity balancing[END_REF]. For such a reason, the RR has been one of the first ancillary services to be opened to the competition of DR assets. It led to the early success -especially in France -of some start-ups such as Voltalis and Energy Pool, specialized in the supply of formalized RR products, partly remunerated at the capacity as the French Fast Tertiary control (1000MW) and the Additional Tertiary control (500MW) [START_REF] Cre | Consultation publique de la commission de régulation de l'énergie du 6 novembre 2012 sur les quatrièmes tarifs d'utilisation des réseaux publics d'électricité[END_REF].

Voltalis' business model relies on the commissioning of both monitoring hardware and steadystate relays in electric-heated domestic households. The hardware is deployed for free by the company. It enables the end user to keep its power consumption under surveillance and so performs energy saving [START_REF] Voltalis | Liquefied natural gas[END_REF]. In return, Voltalis is free to perform load shedding of the end users' heaters and boilers, and sell such flexibility on the RR.

Voltalis positions its business on a high rate of solicitation of the DR assets, at a cheap marginal cost of activation. [START_REF] Lebel | Household aggregators development for demand response in europe[END_REF] presented the opportunity to export the business model of Voltalis on the Swedish RR and assessed an opportunity of incomes of 8.9-12.3ke/MW/yr (Table I.3).

The model assumes a null marginal cost of activation and an activation of the asset winter-long. It leads to the annual shifting of 517-917MWh of load consumption per MW of space heating capacity i.e. an activation rate of 6-10% per year. The revenue are quite limited compared to the customer acquisition cost required to set up a DR portfolio of critical size of success. In France, Voltalis gambled on the commissioning of a green bonus of 16.3e/MWh at the benefit of the DR assets of less than 36kVA [CRE, 2014b], to increase its profitability. Considering the activation rate of 6-10% presented in [START_REF] Lebel | Household aggregators development for demand response in europe[END_REF], the bonus is able to raise the income of DR on the RR from 8.9-12.3ke/MW/yr to 17.3-27.7ke/MW/yr. Up to now, Voltalis claims a pool of residential DER close to 100MW [START_REF] Voltalis | Liquefied natural gas[END_REF], which can be considered as a success 2 .

Table I.3: Assessment of RR using domestic space heating DR Swedish RR 2005-2011 8.9-12.3 ke/MW/yr [START_REF] Lebel | Household aggregators development for demand response in europe[END_REF] At the opposite, Energy Pool focusses on the control of electro-intensive DR assets, which 2 Voltalis built however its success on a legal uncertainty that enabled it not to compensate the BRP for the balancing volumes shifted from the BRP portfolio to the TSO balancing portfolio. Voltalis benefited so of free primary energy contrary to Energy Pool which paid these volumes back to the DER assets owner engaged toward its BRP. The non-compensation by Voltalis toward the BRP of DR assets maintain a lawsuit between EDF and Voltalis since 2009 in France. commonly suffer a rather high marginal cost of activations but cheaper instrumentation cost. The company interfaces itself with the processes of its industrial customers through hardware or even only software gateways -Energy Pool Demand Response Management System (DRMS) is OpenADR-compliant [Energy Pool, 2014] -but compensates financially the DER owner at each activation of DERs. Energy Pool is one of the European Demand Response Leaders, having a portfolio of Industrial DER of 1.2GW [START_REF] Baud | Accélérer le demand response en france et améliorer la compétitivite des gros consommateurs[END_REF].

If both models could be considered as successful, their business model differs significantly: different instrumentation costs, different activation abilities, different access modes to the wholesale and ancillary services markets.

Peak load

The peak load challenges the adequacy of the power system while impacting the wholesale prices. The challenges of DER flexibility operators have consequently been to position themselves on both these business opportunities. The DER operators have started to do it quite early and it is an already well-established business for DER operators. The first reason for its success is the ease of delivery of the load shifting product: the aggregation of load is not dependent on the grid topology. Thus the operators can aggregate their flexibility on the scale of the bidding area, without knowing on each precise feeder the DER is connected -that can be required for the business model of VoltVAR management. Secondly, the customer acquisition is made easier thanks to the simplicity of the product. The added-value for the energy transition of the end-user's involvement is easy to explain, that facilitates its adhesion to the process, regardless the revenue the end-user can expect. Thirdly, the peak-shaving products have been one of the first products that have been opened to DER delivery, on the TSO-operated RR markets. Voltalis applied exactly these factors of success: the company's core business is the aggregation of domestic electric heaters and boilers, located all around the country; Voltalis axed its initial customer acquisition strategy in the environmental benefit that load shifting would procure to the society, by avoiding the black-start of pollutant fired power production assets at the peak load [START_REF] Voltalis | Liquefied natural gas[END_REF]; and the company got involved in the French RR since 2008 [START_REF] Voltalis | [END_REF]. Section 2.6.1 presents the opportunity of DER revenue based on an involvement on capacity markets or obligation mechanism. Section 2.6.2 assesses the effective value of the load-shifting process on the day-ahead spot markets in periods of peak loads.

Capacity auctions and markets

The value of the capacity auction depends on the geographic area. It goes from affective prices of 6.9ke/MW/yr observed on the Swedish Effektreserven market [START_REF] Lebel | Household aggregators development for demand response in europe[END_REF] to 60ke/MW/yr on the French capacity auction [E-Cube, 2013] (Table I .4). The assets of the Swedish Effektreserven market are composed of emergency margins that benefit from a complementary marginal cost of activation close to 200e/MWh for a common rate of activation of less than 10hr per year.

The capacity markets look well adapted for DER business and especially for DR assets having a low instrumentation cost -per MW of flexibility -despite expensive industrial costs. Electrointensive flexibilities look particularly adapted. Svenska Kraftnät targets thus call only for DR contribution on the Effektreserven by 2020. Energy Pool involves such electro-intensive DR flexibilities on the formalized reserves of the French RR.

Handling of the peak load by the day-ahead spot market

The occurrence of events of peak load is able to stress the power system. The most extreme events can even require the mobilization of specific assets of power production or Demand Response, whose contribution over the year is only dedicated to such purpose. As presented above, these assets are remunerated in some areas by capacity auctions or firm RR bids. In other locations however, part or all of these assets are remunerated only on the wholesale markets, while their marginal cost of activation can be much larger than 100e/MWh. Such a situation is consequently capable of inducing peak prices on the spot markets whose prices are set by the marginal cost of activation of the most expensive selected asset. The present section is dedicated to the analysis of the value that the peak-load is likely to represent on the day-ahead spot markets. It later assesses how DER flexibility would benefit from the intra-day spread. The assessments is based on a method of day-ahead spot data analytic, that has been developed for the present purpose. The entire description of this method including the detailed stages of construction and the signification of the eighteen different types of built data [D1] to [D18] is explained in Appendix B.

Among the datasets available, the data analytic assesses the annual revenue that can be obtained by a DER able to perform 3.5hr of load-shifting per day, either 365 days a year [D17] or only during the days of peak loads [D18]. The daily revenue is generated by the purchase of power during the 3.5 cheapest hours of the day and the selling back of the same amount of power during the 3.5 most expensive hours of the day (see App. B Sections 2 and 3). The days of peak loads are the days where the peak volume of the day reaches a value larger than 85% of the historic peak load [D8]. I.5 presents then the ratio of [D17]/[D18] in each bidding area, averaged over the years of available data. Ignoring the case of Eastern Denmark, it can be noticed that the periods of peak load capture from nearly 10% to 25% of the potential annual spread revenue, while nearly 10% of the annual turnover of the day-ahead spot market is traded during these peak-days (Table I.7).

Such observation leads to the first conclusion that a DER operator whose business model focusses on the delivery of load-shifting services on these occasional peak days (Table I.6) would miss out on 75% to 90% of the overall spread value. Furthermore, a second look at the annual incomes of each bidding area, specifically during the days of peak-load [D18] compared to the overall incomes [D17], highlights that bidding on the peak is an opportunity of specific situations for most of the countries studied. Winter 2010 data A annual revenue of 19ke/MW would have been expected this year 2010. It can be noticed that 7.5ke/MW over the revenue of 19ke/MW would have been captured during three days of peak-prices. A first morning peak price occurred on January 9th 8am, followed by a second peak on February 22nd, 8am as well. These 7.5ke/MW equal almost the additional income observed this year compared to the previous years (Figure B.10). Winter 2010, was a cold and dry in Scandinavia. Power demand was high and inelastic, hydro long-term potential was reduced, and last but not least, Swedish nuclear maintenance works faced delays, so that the nuclear feed-in power had been reduced by 40% that winter [START_REF] Nordreg | Nordreg memo to emg on the price peaks in the nps market[END_REF] Finally, if one unique bidding area would have to be selected to deploy a DER-based business model that is likely to play on the peak spread only, it would be Denmark East. A deployment in any other area would induce getting in business on unpredictable and non-structural extreme spreads, whose occurrence should be counted in years and not in days. Investment in such business model looks too hazardous and should be reserved to industrial processes, having an especially high activation cost, and a limited loads instrumentation and control cost.

The incomes of the peak-load days in the spot market should be considered by the investors as a variable part of remuneration i.e. an unpredictable bonus. The wish to target specifically the peak-load, should lead to an involvement into the capacity market and auction mechanisms, instead of the spot market. Indeed, the capacity market and auction mechanisms are designed to secure such investment in unpredictable peaks, in order to ensure the system adequacy.

Intra-day spot markets

It has to be noticed that the intra-day spot markets have not been assessed in the present PhD works. Due to time priority, a focus has been dedicated to the day-ahead spot markets which are more fluid and easier to analyse. Indeed, the day-ahead spot markets are settled at the marginal price of production of the last production unit called. Thus it has been considered that the review of the day-ahead markets enables to get a better vision of the opportunities for DERs. No data are consequently provided here for the intra-day spot market. However, it is strongly believed that the intra-day markets should be analysed. They would notably play an important role in the future as the needs for RES-E balancing is increasing. ENR Pool [2015] initiative can be quoted as a proof of concept of stochastic RES-E balancing using DERs. The start-up Sun'R Smart Energy [2015] developed other concepts of RES-E portfolio balancing and devotes presently its activities in such a promising field.

Day-ahead spot markets

The delivery of day-ahead wholesale market bids as a basic DER flexibility product is driven by two parameters. The first parameter of interest is the large turnover of such markets. The second parameter is the time delay available between the closure of the markets that occurs generally at mid-day in day-ahead and the period of real-time operation (Figure I.1). The large turnover affords volume stability and contained price volatility over the days. The time delay enables getting sufficient time to sale and prepare the delivery of parallel ancillary services products close to real time, using the same DER unit. Such a combination enables to build a robust and long-term baseline business in day-ahead, on the top of which, either more technical or more volatile products, that are definitely smart grid oriented, can be proposed to the system and grid operators.

The opportunity of DER involvement in the day-ahead market has been assessed thanks to two different analyses. The first analysis relies on the work of data mining and analytics that is presented in Appendix B. Its conclusions are presented in Section 2.8.1 and then applied on two use cases. Section 2.8.2 presents the first use case that performs intra-day load shifting on the day-ahead spot market using an Energy Storage System (ESS). Section 2.8.3 presents the second use case that performs load shifting up to three-days in advance using the thermal inertia of an electric heated household as a source of DR flexibility. In this second use case, the power is procured on theoretical three-days-ahead market that provides the prices three days in advance.

Day-ahead market data analytics

The second objective of the data analytics that are presented in Appendix B, has been the analysis of how far an involvement of DER flexibility on the day-ahead spot markets could generate a baseline revenue to the DER assets. The business model of DER assessed in the analysis relies on intra-day load-shifting, with a daily load-shifting event of either 1hr or 3.5hr. The process of load-shifting can be either a DR process such as electric heater shifting or a process that relies on an ESS. The model does not consider restriction of neither minimum nor maximum delay between the charge or discharge event. Moreover, the periods of charge and discharge can be split into several sub-charge and sub-discharge periods per day on the condition that they respect the maximum cumulated length of 1hr or 3.5hr per day. Figures B.9 and B.10 (App. B Section 4) presents the annual revenues [D17] that would be obtained by a daily shift of load consumption from the 3.5hr most expensive hours of the day to the 3.5hr least expensive hours, on the day-ahead spot markets of each bidding area of the Nordics, Baltics and France. It results over the five last years to an annual revenue of 30-45ke/MW/yr in the Baltics and in France, 20-35ke/MW/yr in Denmark, 25ke/MW/yr in Finland, ≈15ke/MW/yr in Sweden and less than 10ke/MW/yr in Norway. The final profit would then depend on the operation cost of the technology of load-shifting selected.

As seen in Section 2.6.2, only 10-25% of the load-shifting revenue is generated during the days of peak load (≥ 85% of the peak load [D8] 3 ), which represents nearly 10% of the annual turnover of the day-ahead spot market, regardless of the bidding area. Meanwhile,Figures B.11,B.12 and B.13 shows that 80% of the annual turnover4 is traded in a range of level of load of [50%; 85%] ±2% of the peak load (sets of green rectangles representing each 10% of the day-ahead market turnover in the bidding area studied). Finally peak load events are observed in winter only, while levels of load [50%; 85%] of the peak load occur all year round (Figure B.8). As such, aggregators should focus on the control of DERs that can be operated all the year-long to 3-12: Counter of days of the year having a daily spread 3.5 is larger than 40€/MWh. Average be able to handle a wide part of the annual load-shifting value.

Aggregators could also benchmark their decision of investment by looking at the annual occurrence of days having a daily spread 3.5hr larger than thresholds of either 20e/MWh or 40e/MWh. It would enable them to assess their annual rate of solicitation depending on the marginal cost of activation of the DER assets of their portfolio.

Such rates of solicitation (in days per year) are summarized in Tables I.8 and I.9, whilst the monotonic daily spreads 3.5hr of the year 2011-2014 are presented in Figures B.14 andB.15. It can be noticed that the daily spread stays larger than 20e/MWh over one third of the year and larger than 40e/MWh over one month, except in Sweden and Norway. At the end, a clear correlation can be observed between the annual income and the annual number of years having a daily spread of at least 20e/MWh. Figure I.10 illustrates graphically such outcomes, using the Swedish, Finnish, Danish and French examples: keeping a sufficient daily spread all throughout the year is necessary to generate interesting revenue at the end of the year.

The roadmap should give investment priority to DERs which have a reduced marginal cost of activation, and that are likely to be activated all along the year to handle a significant part of the annual load-shifting potential on the day-ahead spot markets. Selecting a value of 20e/MWh as a targeted marginal cost of DER load-shifting activation would be a relevant rough size, that would enable the contribution of DERs at least half of the year in half of the countries benchmarked. Finally, if a decision of investment would have to be done on short term, focussing on wholesale market spread business, the bidding areas to address in order of priority would be France, Eastern Denmark and the Baltics. France would afford a mean revenue of /!\ different Y scale Figure I.10: Illustration of descent daily spread 3.5hr shape and annual spread revenue (curves building method presented in App. B, Section 2) 45ke/MW/year. The situation of the Baltics is likely to evolve toward a lower ratio of spread. Indeed, the deployment of the Baltic Energy Market Interconnection Plan (BEMIP) [European Commission, 2015] would increase the market coupling between the Nordics and the Baltics, hence smoothing the Baltics spread.

Speculation on the day-ahead spot prices using a Tesla Powerwall ESS

The sector of ESS faced large movements in 2015, especially in the domestic storage field. Several manufacturers announced the commercialisation of small size batteries capable of being connected to domestic applications. After the 7kWh Powerwall of Tesla [Tesla Motors, 2015] and the 2.5kWh system of Mercedes-Benz [M'Bida, 2015[START_REF] Schneider Electric | Ecoblade. www.schneider-electric.com/ecoblade[END_REF] announced in December 2015 the commercialization for the end of 2016 of its Ecoblade, a system of multibatteries connected in racks as in server towers. Thus, a model has been created during this PhD work to assess the profitability for a domestic end user to get involved in the business of day-ahead spot market load-shifting, after having invested in such domestic ESS (Figure I.11). The model assumes the investment in a 7kWh/2kW Powerwall [Tesla Motors, 2015], at ≈2800ewithout DC/AC inverters. The access to the spot market is enabled by the subscription of each individual ESS owner into a pool of aggregation, large enough to enable the trading on either EpexSpot or Nord Pool Spot of 0.1MWh per hour of operation. In respect with the outcomes of Section 2.8.1, each ESS achieves one deep cycle of charge/discharge per day. The daily charge duration as well as the discharge duration last 3.5hr per day, in order to use the full capacity of the Powerwall. The cycles of charge and discharge can be interrupted during the day in order to purchase power during the four cheapest hours of the day, and sell it back during the four most expensive hours of the day. The charge and discharge are performed at a power level of 2kW per Powerwall during the three cheapest and three most expensive hours of the day. The charge and discharge are performed at a power level of 1kW only per Powerwall during the fourth cheapest and most expensive hours of the day. The model created, assesses an efficiency of 3×95% for each of the three steps of conversion AC/DC -DC/DC -DC/AC (Figure I.12). The efficiency of the DC/DC conversion match with the official communication of Tesla Motors [2015]. The efficiency of the AC/DC and DC/AC conversions are slightly lower than the maximum efficiency declared on inverters data-sheet (97.5% for the ConextRL from Schneider Electric [2016]).

The daily income that can be expected for the Powerwall, depending on the mean price of power purchase P purchased and the mean price of power resale P sold is defined by the Equations I.1 and I.2. The equations consider the loss of revenue that depends on the efficiency of each step of power conversion. Finally, Equation I. The Baltics are the second most interesting bidding areas, followed by Denmark and Finland. At the opposite, Norway and Sweden appear as countries devoid of any interest for such a business based on the spread. In an echo of Section 2.6.2, the 37 most profitable days of operation (10% of contribution) generates at most one third of the maximum revenue that can be reached with daily operation (100% of contribution), regardless of the bidding area. It confirms the assessment of Section 2.6.2: contributing to the peak-load resolution thanks to an involvement on the energy wholesale markets does not appear as a key business.

At the end, it can be concluded that a business model that would participate only on the dayahead spread is not capable of generating enough revenue to make ESS profitable. An ESS would generate at most 35ke/MWh/yr in France, that is equivalent to a revenue of 70e/yr for one Powerwall, that costs ≈2800e without considering the cost of the DC/AC inverter. Its time of return is too long to justify such investment for the present purpose of study, regardless of its lifetime and the financial discount rate considered.

The next Section 2.8.3 investigates an alternative way to benefit from such daily spread using the inertia of a cottage as a source of thermal storage, wherein load-shifting can be performed.

Domestic space heating optimisation using day-ahead spot prices

Specific simulation study have been performed during this PhD work [START_REF] Lebel | Cost benefit analysis of households energy boxes deployment in europe: impact of the spot prices[END_REF] to get additional assessments regarding the involvement of DR in the day-ahead spot market. The study aimed to assess the profitability of replacing a conventional thermostat in electric heated households by a Smart Thermostat, also called Energy Boxes. It assumed that such replacement is a prerequisite for a domestic end user to take the entire advantage of being involved in Real Figure I.15 presents the deterministic model that has been built to perform such a Cost Benefit Analysis of investment in Energy Box hardware. First, the model considers a theoretical household located in Malmö (Southern Sweden) having standard thermal characteristic (λ, τ ). This is the same household as the one modelled in [START_REF] Lebel | Household aggregators development for demand response in europe[END_REF] to perform the Cost Benefit Analysis of domestic household involvement in the Swedish RR (see Section 2.5). Such households face the real hourly outside weather of Malmö which is modelled thanks to a dataset of historic hourly outside weather from Malmö. The dataset has been provided by the Swedish Meteorological and Hydrological Institute [SMHI, 2015]. Secondly, the heating system controller embeds functionalities of either energy or cost-optimization. The controller defines the heat load profiles of the 72 coming hours depending on both weather and tariff forecast. Two tariffs have been proposed: either a fixed price, that is the mean winter day-ahead spot price, or the hourly day-ahead spot price. The day-ahead spot prices data have been collected on Nord Pool Spot [2015] and Epex Spot SE [2015a] open data platforms. For an accommodation that is not equipped with a central thermostat, the investment would be larger, but additional energy savings would be expected. Hence the profitability of the Energy Box would be mainly more induced by the improvement of the energy efficiency of the accommodation than by the present business case.

The computation made for France with different climate references shows that the colder does not mean the better in terms of load-shifting potential. Indeed, the maximum heat load of the household is too limited during really cold periods to enable the turning-off of the heaters during the peak prices that occur in cold conditions. As an example, it can be mentioned the historic French peak-load that occurred in February 2012 due to a week-long high pressure conditions that induced particular cold weather. The model shows thus better incomes for the theoretical household simulated as located in Grenoble than for one located in the Vercors.

In summary, this study has shown that the profitability for the end-user of Real Time Price tariffs adoption is highly dependent of the national power market context. At the end, the present kind of DR would be profitable in Denmark and the Baltics... even if it has not been checked if Baltic households are equipped with electric heaters, as it is the case for part of the The business margins generated per household are however limited to a magnitude of 25-75e/yr/household i.e DR incomes of 4.1-12.5ke/MW/yr in the best located areas (the households modelled have a heating load of 6kW). It would address therefore a niche market, composed of early-adopters only, given that a wide market penetration would require significant customer acquisition costs (100-200e/customer [E-Cube, 2011]), that is likely to willing to jeopardize the profitability of the DR service, challenging thus its penetration.

It would address therefore a niche market, composed of early-adopters only. Indeed a wider market penetration would require larger customer acquisition costs (100-200e/customer [START_REF]Les modèles d'affaires "agrégateur d'effacement diffus" quelle soutenabilité en france?[END_REF]) to convince as well technology-friendly dwellers to get involved. This rising of the customer acquisition cost is likely to jeopardize the profitability of the DR service, challenging thus its penetration. On the contrary, a wide market penetration would not induce a reduction of the gross profit per household (previously assessed at 25-75e/yr/household), given that most of the load-shiffing revenue is generated out of peak periods as it has been shown in Section 2.8.1.

Long-term wholesale markets

Long term markets have been assessed as of no interest. Long term markets are risk hedging products, aiming initially to smooth prices of less flexible conventional assets, without any consideration of system operation constraints. The involvement of flexible DER capacities on such markets looks much less adapted than on the short-term spot markets, detailed in the previous sections.

Market coupling capacities

Market coupling capacities have been assessed as devoid of interest as well. Indeed, the underlying of market coupling capacities address physical capacities in power lines and cannot be replaced by DER capacities consisting of on-site production, storage or demand response assets.

Bilateral wholesale markets

The bilateral contracts stay out of the scope of analysis given that they trade the same underlying as the long term and spot markets. The main difference is that the prices and the volumes are not published. The assessments stated on the long term and spot markets in the previous Sections 2.7, 2.8 & 2.9 remain true for the bilateral products of equivalent underlying.

Scenario of DER flexibility assets sharing

Table I.10 summarizes the opportunity that each power product is able to constitute for DER flexibility operations. One can notice a diversity of remuneration depending on the product. This is somehow correlated to either the solicitation of the DERs or the complexity of supply of each product. The last parameter evaluated is the liquidity of each market, i.e. the ease of Table I market entrance for each new actor. Table I.10 has been built based on a given set of assumptions -that could be challenged. Over the exact figures that are displayed, the added-value of Table I.10 is to highlight specific points per country. The European market is not uniform depending on the country; the national markets are not uniform depending on the bidding area. It appears essential to keep this idea in mind despite it opposes the trend of coupling of the European power markets.

Table I.10 gathers the values of DER flexibility that have been listed from Section 2.1 to Section 2.8.

For ease of comparison, the revenues are assessed in ke/MW/yr, while the table contains both energy and capacity products. This is of prime importance to benchmark both the marginal cost of energy supply per technology of DER and the energy rate of solicitation of each power product before getting involved in the supply of a given power product based on DER flexibility operation.

Overall, it can be noticed that the profitability of DER flexibility on the power markets stays too contained to enable DER flexibility operators to focus on the supply of one unique power product. In such a context, a way to be explored to reach a profitable model would be to engage a given DER for the delivery of multiple smart grid functions, either in parallel or one after the other. Such an approach is motivated by the diversity of DER solicitations that grid and system operations can require. Period, delay, length, minimum, mean and maximum occurrences of activation per day can vary significantly depending on the services supplied. Overall, the idea is that basic power products that are easy to supply such as the RR or day-ahead spot bids would provide a basic remuneration on the top of which advanced smart grid functions would be introduced. It appears as a promising way to speed-up the grid penetration of such advanced functions, by making grid-oriented DER investment more profitable. Such multiplicity of products supplied from the same pool of DER is facilitated by the different gates closure of each product, that lead from quarterly firm agreement to intra-day call for activation.

In regards to such a philosophy, Figure I.19 presents a set of scenarios of combined supply of power products, with the priority of supply sorted from left to right. An informal range of remuneration is listed below each product and summed for each scenario of products combination. The range of remuneration provided are voluntary wide for two reasons. Firstly, Table I.10 has highlighted a significant geographical disparity of remuneration. Secondly, the review of the business opportunities of DER flexibility have been assessed per main kind of product taken independently of one another. Thus the global study performed in Section 2, is not strong enough to accurately assess the missing revenue that would be induced by a combined supply of several products. Indeed the supply of a main product in priority is likely to reduce the availability of the DER for the delivery of the complementary products, reducing hence its revenue. On the other end, the activation in a specific situation of a given DER is likely to induce synergies of delivery of several products in the meantime, at the same cost but with multiple remunerations. As an example, the shifting of a given DER for VoltVAR concern is likely to induce physical losses saving as well, given that voltage constraints commonly occur on highly-loaded grids. Then if the local peak load is synchronized with the national peak -that is actually not always true in distribution -, such load-shifting is capable of becoming eligible to peak load shifting remuneration. In parallel, such a local load-shifting will provide savings on DSO's energy procurement cost for grid losses compensation.

Another concern deals with the guarantee of the level of revenue of DER flexibility in the context of a wide penetration of these sources of flexibility. On the one side, the depth of the market of ancillary services is limited and would smooth the revenue of each DER flexibility asset depending on the market penetration. On the other side, the market opportunities remain large. Considering the huge turnover that occurs on the wholesale market, it can be assessed that DER flexibility would not impact in a significant manner the daily spread out of these peak days, regardless the importance of DER asset penetration. Thus, the inter-DER competition in the wholesale market would not be so challenging on DER profitability.

Table I.11 provides elementary investment and marginal activation costs of three technologies of DER flexibilities, leading either on chemical storage or domestic space heating flexibilities (thermal storage). These costs enable the scenario of DER flexibility operation to be benchmarked.

It can be noticed that a business model of a pure-player of DER flexibility operator does not look so promising. First, the opportunity of chemical storage looks irrelevant in largely interconnected power systems at present6 . Even if some success stories focussing on domestic space heating flexibilities such as Voltalis exist, their future is not guaranteed either. In parallel, industrial flexibilities operators such as Energy Pool, Smart Grid Energy or Actility operate promising assets. However they suffer from significant marginal costs of activation that forbid them to access to most of the markets. Their business model remains profitable mainly on the ancillary services that target system stability & adequacy services. And most of these markets Then an involvement in the services targeting the grids reliability looks interesting knowing the troubles DSOs would face in a close future with respect to large DG penetration. The price DSOs would be willing to pay for services that enable grid investment postponing would probably rise. Nonetheless, these markets that have a low liquidity have not really grown as initially expected and DSOs are still reluctant to push for the industrialisation of these Smart Grid functions.

Finally, the supply of reserves that have a high level of requirements could be an interesting market for DER flexibility. The FRR and the FCR, that target the real-time power system stability are examples of such advanced reserves. Unfortunately, the supply of FRR using DER flexibility constitutes another challenge that has not been addressed in depth in the present PhD works. It is strongly believed that DER-based solutions for FRR delivery should be looked at closely by innovators, while FRR stays up to now in the shadow of system stability concerns and solutions that targets FCR. At the opposite, the opportunity of supply of FCR based on a coordination of DER flexibility will be the focus of the three last chapters of the present thesis. Out of the business opportunities, Chapter II will emphasize the technical needs of supplying such products based on DER flexibility. Chapter III will focus on an innovative way to supply FCR: the Primary Support initiative. Chapter IV presents finally the initiatives of demonstration that has been performed to promote the supply of frequency-controlled reserves from the demand side.

Conclusion of Chapter I

A profusion of Smart Grid demonstration projects have highlighted the benefit that the operation of flexible DERs would procure to the utilities for power system operations. Unfortunately the profitability of these business models of DER flexibility operation at the benefit of the System Operators is still pending. As of now, these unknowns are heightened by a contained use of Smart Grid technologies by the utilities. Innovation teams were set in motion, in response to the fear expressed by the utilities to see their operations being jeopardized by the wide penetration of Distributed Generation. However, the sale of these new Smart Grid technologies did not rise yet, the commercial feed-back is missing and the uncertainties of profitability remain.

In such a context, the initial PhD work aimed to review the main wholesale and ancillary services markets and benchmark the business opportunities that the supply of several services based on the same DER flexibility asset would constitute (Figure I.19). In contrast to received ideas, the generation of revenues on the day-ahead spot markets would first require the involvement of DER assets that have a contained marginal cost of load shifting (≈ 20e/MWh), able thus to get involved all year long. Then an involvement only during the days of peak loads is not able to generate significant revenues. Finally, the profitability of DER flexibility on the spot market is largely dependent on the bidding area of involvement. If a decision of investment would have to be done on short term, focusing on wholesale market spread business, the bidding areas to address in order of priority would be France, Eastern Denmark and the Baltics.

On the side of the ancillary services, the supply of DER flexibility to guarantee the power system adequacy appears as the most reliable business model for DER operators. The call for effective flexibility activation is exceptional -some hours a year -and the revenue of the service could constitute an interesting revenue for industrial assets owners. In addition, the frequency controlled reserves are well remunerated power products, for which part of the allocated capacity is solicited almost permanently, while the volume left is almost never used. The supply of such frequency controlled reserves -and foremost of Frequency Containment Reserves (FCR) -appears thus as promising products to be supplied by distributed flexibility assets. Such opinion is driven by: the business opportunity of these products, that has been identified in the present chapter; the evolving challenges of power system stability expected in the future and that would have to be solved by evolved FCR supplying assets, as explained in Chapter II; the technical challenge presented by the delivery of such frequency controlled reserves using DER assets, and that has been solved in the present PhD works, as presented in Chapters III and IV.

CHAPTER II

Theory and Challenges of Frequency Stability

Chapter II

Theory and challenges of frequency stability

Chapter I highlighted the opportunity offered by DER flexibility assets to contribute to the stability of the power system. In such a context, the present chapter focusses particularly on the process operated by the System Operators to ensure the stability of the power system (Section 1). The challenges that System Operators would probably face with in the coming years to guarantee the performance of stability of the power system are then presented (Section 2).

Section 1 details the operational principle of the real-time load-frequency control processes. Section 1.1 presents how the system frequency deviates depending on power load imbalance. Section 1.2 details the importance of these processes to avoid blackouts, whose can have significant impacts on the economy of countries -0.6-1% of the GDP is lost annually due to power outages in the USA [START_REF] Bruch | Energy risks -the dangers of power cuts and blackouts[END_REF]. Section 1.3 presents then the system response chronology to any disturbance affecting the stability of the system. Sections 1.4 to 1.7 afford an explanation of the upcoming European Network Code.

Section 2 presents the challenges that System Operators would face in the coming years regarding frequency stability of the network. Section 2.1 focusses on the availability of conventional FCR providing units. Section 2.2 addresses the degradation of the system frequency quality, likely to induce large FCR sollicitation. The issues induced by a degradation of the system inertia are presented in Section 2.3. Section 2.4 details finally why the conventional emergency process of UFLS would face troubles of robustness.

1 Principle of power system balancing

Power system balance & frequency deviation

It is commonly stated in the literature that electrical power can barely be stored. This means that any power imbalance between power production and consumption induces a disturbance for the "traditional" power system -the situation would be potentially worse for micro-grids -, causing naturally a deviation of the power system frequency. As detailed subsequently (Section [START_REF] Andersson | Dynamics and Control of Electric Power Systems[END_REF] 1.2.2), a too large deviation of the system frequency (±5%) can induce a global breakdown of the entire power system i.e. a blackout. Such an event is caused by the loss of synchronism of the power generators that will not be further detailed in this thesis.

The evolution of the frequency deviation can be understood by looking at the electro-mechanical process of power conversion that occurs in a power plant. Figure II.1 displays a simplified representation of a power plant. In this model, the primary source of energy P set m is converted into a mechanical power P m thanks to the turbine T . The mechanical power P m is transmitted through a shaft to the generator G, that converts this mechanical power into an electrical power P e . The electrical power P e is injected to the power network, and is finally consumed away from the power plant by a given electrical load, that consumes a power P load . This simplified representation neglects the mechanical, the magnetic and the electrical losses. Hence, in steady state operation it is assumed :

P set m = P m = P e = P load (II.1)
The equation of motion of the machine to which the transmission shaft is connected is defined by equation (II.2):

J d 2 θ dt 2 = T m -T e (II.2)
where J is the total moment of inertia of the rotating mass (in kg.m 2 )

T m is the mechanical torque associated to the mechanical power P m (in N.m)

T e is the electrical torque associated to the electrical power P e (in N.m) θ is the angular position of the rotor (in rad)

The moment of inertia J represents the mass repartition around the rotation axis. For a rotor 1. PRINCIPLE OF POWER SYSTEM BALANCING or any shaft that has a cylindrical shape, J can be calculated thanks to equation (II.3):

J = 1 2 M r 2 (II.3)
where M is the mass of the shaft (in kg) r is the radius of the shaft (in m)

Considering now that the rotor speed is constant ahead the occurrence of a disturbance, it can be assumed that the rotor speed ω r remains constant and equals with the power system's synchronous speed ω sm [START_REF] Kothari | Power System Engineering, 2e[END_REF]:

ω sm = ω r = dθ dt (II.4)
Hence, the equation of motion can be expressed as function of the power values by multiplying the equation (II.2) by the rotor speed ω r :

Jω r d 2 θ dt 2 = ω r × (T m -T e ) (II.5) <=> Jω sm d 2 θ dt 2 = P m -P e (II.6)
where P m is the mechanical power supplied by the turbine (in W ) P e is the electrical power produced by the generator (in W )

Given that dθ dt = ω sm and ω sm = 2πf , the variation of the power system frequency depending on the mechanical power injected P m and the level of load P e can be expressed by the equation (II.9), starting from equation (II.6):

J × (2πf ) × d(2πf ) dt = P m -P e (II.7) <=> J × 4π 2 × f × df dt = P m -P e (II.8) <=> df dt = 1 4π 2 J × 1 f × (P m -P e ) (II.9)
where f is the system frequency (in Hz) 1.00 Synchronous motor with load varying from 1.0 to 5.0 and higher for heavy flywheels 2.00

It becomes finally easy to assess how fast the system frequency f will deviate from its steadystate value f 0 following a sudden imbalance ∆P = (P m -P e ). The imbalance can be induced by either a mechanical incident on the power plant itself impacting P m or by an non-expected variation of load consumption P load (= P e as stated in equation (II.1)). The equation (II.10) describes finally the maximum Rate of Change of Frequency (ROCOF) that is likely to be observed in the system, ahead of the reaction of both the turbines governors and the natural smoothing phenomena such as the self regulation of load:

df dt = 1 4π 2 Jf 0 × ∆P (II.10)
The use of the moment of inertia J in the network stability computation is however restricting given that this is an absolute value that depends on the size of the system. Thus, the use of J compromises the use of per unit data. Consequently the notion of the constant of inertia H i per generator i has been introduced in the literature, as defined in equation (II.11):

H i = 1 2 J i ω 2 0 × 1 S Bi (II.11)
where

H i is the constant of inertia of the generator considered (in M W s/MVA ≈ s) J i is the moment of inertia of the rotor of generator considered (in kg.m 2 ) ω 0 is the nominal angular frequency (ω 0 = 2πf 0 ) (in rad/s)
S Bi is the rated power of generator considered (in MVA)

Table II.1 provides typical constants of inertia H i depending on the technology of power plant considered.

PRINCIPLE OF POWER SYSTEM BALANCING

Using H i and S Bi constants, the scale-up at the power system level becomes easily doable by introducing a total constant of inertia that represents the entire power system, as defined in the equation (II.12):

H = i H i S Bi i S Bi (II.12)
where H is the total constant of inertia of the power system modeled (in M W s/MVA ≈ s)

The overall constant of inertial H can be expressed as well as function of the nominal frequency, starting from equation (II.11):

H = J × (2π) 2 × f 2 0 2 × 1 S (II.13) <=> 1 4π 2 Jf 0 = f 0 2.H.S B (II.14)
Finally, the injection of the second term of equation (II.14) in equation II.10 enables to express the power system initial ROCOF as function of the constant of inertia H and the rated power S B , as proposed in equation (II.15):

df dt = f 0 2.H.S B × ∆P (II.15)
In some situations, System Operators publish directly either the kinetic energy KE of their network or of their power plants KE i . This kinetic energy is expressed either in Joules (J) or in MWs. The kinetic energy KE i of a synchronous machine i operated at its nominal frequency f 0 is obtained by multiplying the constant of inertia of the machine H i by its rated power S Bi (equation (II.16)):

KE i = H i × S Bi (II.16)
The initial ROCOF df dt introduced by the equations (II.10) and (II.15) can then be expressed using the constant of inertia of the system H or its kinetic energy KE:

df dt = f 0 2.KE × ∆P (II.17)
Illustration of system inertia weight on the power system maximum ROCOF EirGrid [2011] publishes the kinetic energy KE of the synchronous area of Ireland (IRE: 25GWs). According to equation (II.17), the largest ROCOF that could be observed following the loss of the largest power unit of the area (450MW) consequently equals to 0.45Hz/s:

df dt = 50Hz 2 × 25000M W s × 450M W = 0.45Hz/s (II.18)
Meantime, according to equation (II.15), the loss of the interconnection on the 282M V A system of Kuching Island in Asia [START_REF] Aik | A general-order system frequency response model incorporating load shedding: analytic modeling and applications[END_REF][START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF] induces an imbalance of 0.48pu on a system having a constant of inertia of 3s (see Section 2.4). It results a ROCOF of 4.0Hz/s.

df dt = 50Hz 2 × 282M V A × 3s 282M V A × 0.48pu = 4.0Hz/s (II.19)
It shows how fast UFLS relays must trip the loads in islanding context to prevent the disconnection of generators at 47.5Hz.

As a last means of comparison, the 2003 Italian blackout has been initiated by an imbalance of more than 7GW, induced by the disconnection of Italy from the Continental Europe (CE) synchronous area, on an Italian system consuming initially 27.4GW [ENTSO-E, 2004a]. Such an imbalance is much larger than the reference incident (see Section 1.4) assumed in CE, led to a ROCOF of 0.3Hz only, showing how important can be the inertia of a power system for its stability.

System reliability & blackout

Jeopardize of system reliability

One core mission of System Operators is to provide reliable electric service to their grid users, 24 hours a day. The system reliability can be damaged by two main kinds of events. The first kind relates to network components tripping due to components' fault or natural and climate events that are likely to interrupt the power supply in parts of the network (exogenous events). The second kinds relates to power and load imbalances among a given synchronous area (endogenous events). Such imbalances are capable of inducing frequency deviation down to the disconnection from the network of both power producers and consumers. Sometimes, transmission lines tripping can induce the split of a given synchronous area into several smaller sub-synchronous areas (Figure II.2). Suddenly, each of these sub-synchronous areas become in situation of imbalance due to the loss of the interconnection. In such situations, the first kind of event (network components tripping) induces the second one (imbalances), which is precisely the most critical one for the system stability due to disturbance propagation.

Blackout

A blakout can be defined as a wide-scale event which leads to the loss of a significant part of the transmission network, and deprives the System Operator of vital power units involved in the maintain of the system stability. Even if such blackout stays fortunately exceptional, it can have major impacts on the affected economies. The occurrence of blackouts varies widely from one area to another, depending notably on the network's characteristic, such as the investments made by the System Operators in their network. [START_REF] Ockert | Load control receiver with line under voltage and line under frequency detection and load shedding -us patent 7[END_REF]. However, the outage of 2006 did not lead to the total interruption of the power supply in the areas concerned, hence the blackout has been avoided. In both cases, the outages were induced by the cascaded tripping of transmission lines following the tripping of a first transmission line due to either a natural event (tree flash-over on a Swiss 380 kV line in 2003) or a human mistake (inter-TSO misunderstanding on cross-bordering line capacity in 2006).

Western

Estimation of blackout cost [Bruch and Hunter, 2012]

Allianz Global Corporate & Specialty (AGCS) provided estimations of blackout occurrences and inherited costs for their US customers [START_REF] Bruch | Energy risks -the dangers of power cuts and blackouts[END_REF]. The company states a cost of US$15,000 per 30 minutes cut and US$94,000 for an 8 hours cut for its medium and large industrial customers. The [START_REF] Bruch | Energy risks -the dangers of power cuts and blackouts[END_REF] for the country between US$104 and US$164 billion, i.e. nearly 0.6-1% of GDP.

Cost analysis of historic blackout scenarios

The largest blackout that USA faced in August 13, 2003, affected 50 millions of people in Northwest USA and Canada. It led to an economic loss of US$6 billions, i.e. 0.2% of the GDP of the affected population. Most of the 62GW tripped were reconnected within two days [START_REF] Elcon | The economic impacts of the august 2003 blackout[END_REF].

System security, stability & reliability

The efficiency of the power system reaction to such sudden imbalances first is characterized by its ability to keep the customer connected in the seconds following the incident: this is the System Security [START_REF] Kundur | Definition and classification of power system stability[END_REF]. This efficiency is then characterized by its ability to regain a state of operating equilibrium without oscillations in the minutes following the physical disturbance, so that the entire system remains secure: this is the System Stability [START_REF] Kundur | Definition and classification of power system stability[END_REF]. Beyond these notions of Security and Stability, the System Reliability denotes finally the ability of the system to supply an adequate electric service continuously, with few localized interruptions over an extended time period. As a result, the System Reliability is commonly assessed as a function of time-averaged performance, while both Security and Stability are assessed under a particular set of conditions [START_REF] Kundur | Definition and classification of power system stability[END_REF].

The reliable response of the power system to these disturbances is enabled by the operation of four main processes, under the responsibility of the System Operator. These processes are described in Section 1.3.

Balancing reserves activation in response to a frequency deviation event

TSOs have commonly four different processes of load regulation at their disposal. Part of these processes are dedicated to the maintaining of the power and load balance -the so-called frequency regulation. Others are involved both in frequency regulation and in other services, such as power line congestion management, power line disconnection for maintenance purpose, etc. Considering the focus of this thesis, the following sections present only the usage of these processes for the system frequency regulation.

As introduced in Section 1.1, the system frequency deviates when facing a system imbalance. Physically, an inequality between the mechanical power generated and the electrical load consumed causes a change in the grid frequency. In other words, any marginal unit of electrical load connected to the grid at a given point of time becomes instantaneously supplied by electrical power converted from the kinetic energy of generators' rotors. It induces a slowing down of the rotor of the generators, which result in a fall of the grid frequency. Thus both the rotational speed of the generators and the grid frequency decrease continuously as long as the system has not been brought back to a balanced situation by modifying the set point of given production or consumption assets. The load-frequency control processes implemented by the TSOs are consequently designed to deal with this physical behaviour of the system frequency.

In a normal situation it relies on three successive processes :

The Frequency Containment Process (FCP) aims first to stop the frequency deviation by bringing the system back in balance, seconds after an incident. To do so, the TSO activates the so-called Frequency Containment Reserve (FCR). Given that the frequency continues to deviate as long as the system has not been brought back to a balanced situation, the system frequency still differs from its normal value despite the activation of the FCP and the frequency stabilisation.

The role to bring the frequency back to its normal value i.e. 50Hz in Europe, in minutes Finally the TSO can activate the Replacement Reserve (RR) to release the aFRR and mFRR in the 15 minutes following the incident. At the end, the RR is released when a given Balance Responsible Party (BRP) has updated its unit commitment plan in the same magnitude as the initial incident. It can be noticed that the FCR is progressively released along the restoration of the frequency. This is the key characteristic of the FCR, whose principle of operation is presented in Section 1.4. Figure II.5 presents a situation where FCR has been activated fast enough and with an appropriate magnitude.

In extreme situations however, it can happen that the injection of FCR does not manage to stabilize the frequency fast enough. This would induce a frequency drop at values lower than the frequency limit that is physically acceptable by the generators. This would cause the disconnection from the grid of all of these generators i.e. the occurrence of a blackout (see Section 1.2.2). The limit of spontaneous generators disconnection is defined at 47.5Hz by the European Network Code (Art 8. [START_REF] Entso-E | Network code for requirements for grid connection applicable to all generators[END_REF]). In order to prevent such emergency situation, a fourth process has been introduced by the System Operators:

The Under Frequency Load Shedding (UFLS) process is a mechanism that enables the TSO to shed large amount of load in the event of a significant frequency drop. It relies on the automatic shedding of entire primary substation feeders, one after the other at predetermined frequency thresholds. It has the final objective to restore the system balance before the system frequency reaches the critical limit of 47.5Hz, leading to a blackout. In Europe, this Last but not least, a passive process of load regulation contributes naturally to the maintaining of the power and load balance:

The self-regulation of load describes the natural dependence of motors' consumption to the system frequency. Thanks to this dependence, the power consumption of the motors that are connected to the power system load will reduce with the frequency drop, contributing so to reduce the power and load imbalance.

Sections 1.4 to 1.7 detail the operational processes and associated rules the suppliers of FCR, FRR, RR and UFLS/LFDD flexibilities must comply with. Section 1.8 details finally the physical principle of self-regulation of loads. , 2012, 2013c,d, 2015a].

source: http://networkcodes.entsoe.eu/

Frequency Containment Process

The Frequency Containment Process refers to the activation of Frequency Containment Reserves (FCR) at the scale of an entire synchronous area (Figure II.6), in response to a sudden disturbance which may occur on the power system. As noticed in

Reference Incident

The Reference Incident refers to the maximum instantaneous power deviation that can occur between generation and demand in a synchronous area. The value of the Reference Incident can be different for a positive and a negative imbalance. For instance the positive Reference Incident of the synchronous area CE shall be the absolute value of the largest imbalance that may result from an instantaneous change of active power of one or two Power Generating Modules or one or two HVDC Interconnectors connected to the same electrical node. The negative Reference Incident shall be the maximum instantaneous loss of active power consumption due to the tripping of one or two Connections Points (Art 43(4a), [START_REF] Entso-E | Network code on electricity balancing[END_REF]). ENTSO-E [2013d] states that these FCR sources can be composed without distinction of Power Generating Modules and/or Demand Units. To perform the frequency regulation, each Power Generating Module and Demand Unit that is involved in the Frequency Containment Process, acts autonomously. That means that each of these units is equipped with a governor that measures the system frequency and adapts in almost real-time its power injection or withdrawal depending on the frequency measured on site. Table II.2 summarizes the minimum frequency accuracy and dead-band the governor systems must comply with.

This frequency-dependent power deviation is predefined by a power-frequency characteristiccommonly called droop curve -, that can be specific for each unit. In Europe, the Network Code decrees that the overall characteristic of FCR activation in a synchronous area shall reflect a monotonic variation of the FCR activation as a function of the frequency deviation (Art 33, Art 44 (6), [START_REF] Entso-E | Network code on electricity balancing[END_REF]). A schematic representation of a power-frequency characteristic is presented in Figure II.9. Figure II.9 provides as well the characteristic of the expected FCR delivery at the scale of each synchronous area.

Figure II.10 describes finally the main characteristic times that any FCR supplying unit has to respect, depending on the synchronous areas where the unit is connected to the grid. The FCR is characterized by short delays of activation of the reserves, which are of 5s only in the synchronous areas of Northern Europe (NE) and Ireland (IRE), and 15s in Continental Europe (CE). The assets that supply the FCR must be able to guarantee the delivery of the entire contractual reserves during more than 30 minutes.

It can be noticed that the unions of TSOs of each synchronous area -the so-called Regional Group -have decreed regulations which are usually more restrictive than the ENTSO-E Network Code. For example, ENTSO-E defines a FCR Full Activation Time of 30s, regardless of the synchronous area, while most of the TSOs has defined shorter delays. 200mHz Art19, [1] 20mHz

A-D2.1, [6] 16.7 GB 600MW+* / 350MW- [START_REF] Ockert | Load control receiver with line under voltage and line under frequency detection and load shedding -us patent 7[END_REF] 500mHz Art19, [1] 25mHz (assumed from [6])

1.25

*1050MW+ instead from 2019 2.19 IRE 300MW [9] 500mHz Art19,[1] 0.34 NE FCR N 600MW [3] 100mHz [3] 20mHz (assu- med from [6]) 7.5 FCR D 1000MW [3] 400mHz [3] 2.5
A description of references [1] to [START_REF]IV.10 Exemple d'architecture de déploiement de Primary Support selon la topologie du réseau[END_REF] is provided in Table II 15s if ∆P 1.5GW (∆P/1000)s else App F, [2], [6] 30min full time equivalent Art 45( 6), [1] 120min Art 45( 6), [1]

NE

FCR N n/a 120-180s [3] 30min full time 120min FCR D 50% 5s [3] 100% 30s [3] equivalent Art 45( 6), [1] Art 45( 6), [1] GB n/a FCDM : 2s.

[7] other: 10s

Art44, [1] FCDM : 30min.

[7] other: n/a

Art44, [1] n/a

IRE 5s [5] 15s [5] 90s [5]
n/a a description of references [1] to [START_REF]IV.10 Exemple d'architecture de déploiement de Primary Support selon la topologie du réseau[END_REF] is provided in Table II Exchange & sharing of FCR TSOs can purchase FCR produced in others adjacents LFC Areas, LFC Blocks and even synchronous areas. [START_REF] Entso-E | Network code on electricity balancing[END_REF] specifies even in details the rules applied to the area CE: An LFC Block can export to its adjacent LFC Blocks a volume of FCR limited to at most 30% of its Initial FCR Capacity, in a limit of 100MW.

Meanwhile, an LFC Block can import at most 70% of its Initial FCR Capacity from its adjacent LFC Blocks. An operational security limit of its adjacent LFC blocks can however limit its exchanges. According to this rule, the block Germany + DK West could for instance outsource almost 70% of its supply of FCR, if all of its adjacent LFC Blocks agree to import as much capacity as they legally can. Exchange of FCR among different LFC Areas of the same LFC Block is possible as well but should avoid the occurrence of internal congestions and guaranty a sufficient delivery of FCR in case of network splitting (Art 50). The exchange of FCR between different synchronous areas can be performed as well if it is agreed by all of the TSOs of the synchronous areas concerned. Finally, ENTSO-E [2013d] allows even the sharing of FCR between the two different synchronous areas of GB and IRE (Art 60( 1)).

The propagation of frequency deviation over HVDC links

The exchange or the sharing of FCR across synchronous areas borders are complex processes, given that the FCR is activated by the FCR sources, based on the frequency deviation measured on-site. Thus the activation of FCR by a given FCR source, at the benefit of a TSO located in another synchronous area can only be done by propagating the frequency deviation across the synchronous areas boundary, which can be risky for the system. This propagation is done by assigning a bi-directional droop curve to one or several HVDC interconnectors. This droop curve is the resultant droop curve of all of the oriented FCR Exchange and Sharing bids contracted between two synchronous areas. The FRR activation will then be impacted as well by the presence of FCR Exchange and Sharing contracts.

Frequency Restoration Process

The Frequency Restoration Process refers to the activation of Frequency Restoration Reserve (FRR) by a TSO to regulate toward zero a given frequency deviation that has been induced by an incident which occurred on the network it is in charge of -i.e. its LFC area of operation.

As hinted above, the FRR activation is not shared at the scale of the whole synchronous area like the FCR, but stays under the responsability of a given TSO. The area of operation of a In Continental Europe (CE), the notion of Frequency Restoration Range is not used. Instead, the TSO has to compensate toward zero the imbalance that occurred in the LFC block it is in charge of, within the Time to Restore Frequency.

Figure II.5 illustrates the impact of FRR activation on the power system balance and frequency, following an over-load imbalance. While the FCR activation enabled the system balancing, the activation of FRR introduces an expected imbalance in the opposite direction of the initial disturbance's trajectory, in order to speed the generators up and make the system frequency rise in the meantime. Given that the FCR is released with the system frequency rise, the TSO has to increase progressively the volume of FRR activated in parallel of the FCR release to maintain the expected imbalance. As soon as the system frequency has reached back the nominal system frequency, the FCR is totally released and the volume of FRR that has been activated equals the volume of FCR which was activated at the beginning of the Frequency Restoration Process. ENTSO-E [2013d] (Art 34(1a)) decrees that the FCR has to be fully released within the Time to Restore Frequency (values available in Figure II.11).

The FRR can be split in two sub-reserves. The first one is automatic: the aFRR. The second one is manually activated: the mFRR. The ratio of aFRR and mFRR available per LFC Block is left to the discretion of the TSO in charge of the Frequency Restoration Process (Art 46(2c), [START_REF] Entso-E | Network code on electricity balancing[END_REF]). Moreover the TSO can rely only on aFRR or only mFRR.

The physical activation of FRR on the site of each FRR sources is performed by an automatic controller or an operator, according to a set-point that is calculated by the TSO at the scale of the LFC Area (Figure II.7). This set-point is the same for all of the FRR supplying units of the area. It varies from -1 to +1, representing respectively a full activation of the negative or positive FRR capacities of the unit. Art 47(1d) [1] aFRR France: 133s or 800s [START_REF]IV.10 Exemple d'architecture de déploiement de Primary Support selon la topologie du réseau[END_REF] 15min activation delay of aFRR is at most of 30s for the four ENTSO-E's synchronous area (Art 47(1d), [START_REF] Entso-E | Network code on electricity balancing[END_REF]). The aFRR Full Activation Time should be at most equal to the Time to Restore frequency (Art 46(2c), ENTSO-E [2013d]), i.e comprised of 10 to 20 minutes, depending on the synchronous area. Some TSO has defined more restrictive conditions depending on the imbalance magnitude. For instance RTE has defined a Full Activation Time of 800s, that can be reduced to 133s if the imbalance observed in its LFC block is larger than 1800MW [START_REF] Rte | Modalités de délestage entre rte et les distributeurs[END_REF].

In the synchronous areas of GB and IRE, the capacities used for the FCR are actually mostly used as well as FRR base-load, due to the relatively small size of these synchronous areas. The reserves change name while the system frequency rises with the activation of FRR over-load (8.3.2, ENTSO-E [2013e]).

Replacement Reserve Process

The Replacement Reserve Process refers to the activation of Replacement Reserve (RR) by a TSO, to replace and/or support the activated FRR, according to the chronology presented in Section 1.3 (Figure II.5). The Reserve Replacement Process is operated by manual modification of the level of load of the RR assets. The set-points of each asset are defined independently of each other by the TSO at the scale of the LFC Area. In GB and IRE, the RR replaces meantime the FCR and the FRR. The RR is traded on a power market platform usually operated by the No more details on these quite well-known reserves, having furthermore long delays of activation (≈15min) will be provided in this thesis. If needed, [START_REF] Lebel | Household aggregators development for demand response in europe[END_REF] and ENTSO-E [2013a,d,e] provide further details on the RR.

Under Frequency Load Shedding (UFLS / LFDD)

As introduced in Section 1.3, the Under Frequency Load Shedding scheme (UFLS) is a mechanism that enables the TSO to shed a large amount of load when faced with a significant frequency drop event. It relies on the automatic shedding of entire primary substation feeders, one after the other when the system frequency goes below predetermined frequency thresholds. It has the final objective to restore the system balance before the system frequency reaches the common generators disconnection threshold of 47.5Hz Given that primary substations are usually operated by the DSOs, the implementation of this UFLS scheme is outsourced by the TSO to the DSOs or to any demand facilities that are directly connected to the transmission grid (Art 20.1a, [START_REF] Entso-E | Network code on demand connection[END_REF]). The characteristics of the demand disconnection plan are defined by the TSO in coordination with the other TSOs of the synchronous area.

The UFLS / LFDD remains an emergency process, that induces load customer interruption due to the blind shedding of a wide number of customers connected below a given Medium Voltage (MV) feeder. Moreover, a common fear of System Operators is the penetration of Distributed Generation (DG) down these MV feeders. Such DGs are likely to engender an effect on system stability that is the opposite of the theoretical expectations. The challenge of UFLS evolution in the future is addressed in Section 2.4.

Contribution of self-regulation of load to power system stability

The loads that are connected to the power system can be split in two main categories of loads.

As a first category, the resistive loads gather all of the loads that have a resistive behaviour, such as boilers, electric heaters, ovens, dryers. The power consumption of such kind of loads is expressed by the equation (II.20), inherited from the famous Ohm's law :

P = U 2 R (II.20)
where P is the power consumption of the load (in W)

R is the resistance of the load (in Ω)

U is the power system voltage (in V)

Hence, the variation of the power consumption depends mainly on the power system voltage. On the contrary there is no direct relation between the power consumption and the system frequency. In addition, despite the voltage can vary when the power system faces imbalances, the presence of On-Load Tap Changer (OLTC) in primary substations partly dissociates the effect of wide-scale voltage variations on end-users load located on the distribution grids.

As a second category, the rotating loads gather all of the loads that are composed of a motor i.e. a rotating machine. In the industry and tertiary sectors, a wide part of the rotating machines are asynchronous machines, whose Torque-Rotational speed characteristics suffer of a speed offset when the system frequency deviate from its nominal frequency, as illustrated in Figure II.13. Considering a linear resistive characteristic of the mechanical shaft that is connected to the machine, it results a shifting of motor's operation towards both a lower rotational speed and torque (Figure II.13). Given the power consumption of the machine equals the product between the torque and the rotational speed (losses neglected), the reduction of the system frequency induces a direct reduction of the power consumption of the machine. Conversely, the power consumption increases when the system frequency rises. Such direct relation between the system frequency and the power consumption is named the self-regulation of load.

ENTSO-E [2004b] assesses a variation of the overall load consumption of 1%/Hz at the scale of the synchronous area of Continental Europe (CE) thanks to such self-regulation of load.

Considering a base-load of 150GW in CE, the self-regulation of load counts for a contribution of 150GW × 0.01 × 180mHz = 270M W in the frequency range of contribution of the FCR. At a peak-load of 300GW, it count for 300GW × 0.01 × 180mHz = 540M W .

Hence, the self-regulation of load represents a additional contribution from

270M W 3000M W = 9% to 540M W 3000M W = 18% of the FCR.
As a result, this passive process of load regulation provides a significant contribution to the power system stability.

Difference between self-regulation supply and FCR supply

It has been seen that the effective contribution of the self-regulation of load is on the whole proportional to the real-time level of load of the synchronous area. Hence, its effective contribution is not guaranteed 24/7. As a preamble of Chapter III, Section 2 in Ch III will show that quite a lot of solutions have been proposed in the literature to enlarge the portfolio of loads able to contribute to the self-regulation of load by modifying their default behaviour faced with frequency variation. Without coordination, the persistence of a dependence between the level of consumption of the load and its contribution to the system self-regulation brakes the contribution of all of these solutions to the supply of FCR, that must respect the supply of a linear power-frequency characteristic 24/7. Faced with such issue, the Primary Support concept claimed in Section 3 in Ch III is a distinguishing solution.

Challenges of the frequency containment defence plan

The undergoing deregulation of the power markets associated with the large development of Distributed Generation (DG) is likely to induce notable challenges with respect to the processes of load-frequency regulation. The whole chain of processes could be affected such as the procurement of FCR, the rising solicitation of FCR, the lowering of the system inertia and the degradation of the efficiency of the UFLS emergency scheme. The following Sections 2.1 to 2.4 provide highlights on the detailed causes and potential consequences on system stability.

Degradation of conventional FCR providing units' availability

Periodic non-availability of conventional generation

The Frequency Containment Processes (FCP) currently in operation in Europe, continue to rely only on the contribution of large-scale conventional generation. The involvement of either bulk or distributed load modulation is still largely anecdotal, despite the recommendations of ENTSO-E to go in this direction. Such position would be formalized soon with the approval by the EC of the Network Code on Load-frequency control and reserves [ENTSO-E, 2013a]. The acceptance of load modulation assets among the pool of FCR supplying units, would probably not constitute a significant enough decision to renew the historic pool of FCR assets. Without specific incentives, the FCP would continue to rely mainly on the contribution of conventional generation flexibility.

Sunny Sunday in Germany

Each new record of RES-E peak production is related in several press articles, as a piece of blue sky among the set of articles saddened by the failure of worldwide climate change mitigation policies. For the power system actors however, such articles highlight something else: How the supply of FCR or FRR could remain guaranteed at midday, while the production of ramp up and source: http://cleantechnica.com down bulk generation units have already been divided by two and operate at their minimum rating power? If the situation is still under control at the moment, it could change in the future and force the TSO to find new sources of FCR and FRR within their border to maintain the network robustness.

Meantime, conventional bulk generation is facing the competition of RES-E, connected to both the transmission and distribution grids. In the tiniest areas, it now occurs during periods of the day where the residual load, i.e. the difference between the net load minus the stochastic RES-E generation is negative. Figure II.14 highlights the evolution over the last years of the phenomenon in both bidding areas of Denmark. DK West faced this issue 10% of the time in 2013, while DK East is not concerned yet. This means that during these periods a given network would be self-sufficient while turning off temporarily its conventional generation units. Furthermore, it means that in the context of no power exportation ability due to interconnection congestion or in a situation of micro-grid for example, either conventional generation would have been turned-off or RES-E curtailed, in the absence of DR or ESS.

However turning-off conventional generation would obstruct the delivery of FCR, jeopardizing the system stability. Consequently, System Operators would have as unique choice to curtail RES-E and keep bulk generation running, while the stochastic RES-E such as photovoltaic and wind power would have a much cheaper marginal cost. Despite being based on already old data, Figure II.15 enables the marginal cost of each technology to be quickly assessed by summing up the fuel and carbon costs of each of these technologies. Such over-cost of generation should then be billed as a system security cost.

Loss of business interest in FCR supply

Inspired from the Levelized Cost of Electricity (LCOE) presented in Figure II.15, a second concern adresses the profitability that bulk generation units can expect from the supply of FCR services instead of being involved on the wholesale markets.

A small case study has been launched during this PhD work to assess such a risk. It aimed first to assess the cost of providing 1MWh bid on the wholesale market or 1MW 1hr-long bid on the FCR markets. The idea has then been to compare these costs with the income that could be expected from each market. The case study assumes that:

The wholesale income range corresponds to the mean pondered day-ahead wholesale spot prices observed by [START_REF] Lebel | Cost benefit analysis of households energy boxes deployment in europe: impact of the spot prices[END_REF] Last but not least, it is assumed that a power unit of 1MW has to sell 0.5MWh on the wholesale market to then be able to trade 0.5MW/hr of FCR. This reason comes from the obligation for the FCR supplier to provide both up and down service of ±0.5M W per MW of capacity, that requires an operation of the power unit at 0.5MW of load per MW of capacity in normal frequency situation. The results displayed in Table II.6 show that only nuclear would be competitive for the supply of FCR out of peak spot prices period. But on the other hand, it would have been much more profitable for nuclear operators to sell all of their capacity on the wholesale market. Meanwhile, the supply of FCR would become profitable for gas-fired units -especially gas turbines -during these peak prices given that it induces significant fuel cost savings in units that have a low investment costs (wholesale prices ≥ 70e/MWh for CCGT and ≥ 100e/MWh for gas turbines, assuming an FCR price of 30e/MW/h). Despite the lack of data regarding hydro, it can be assessed that hydro power is an interesting supplier of FCR, thanks to the water saving Such conclusion highlights that a disinterest is possible amongst the historical producers for FCR in any area where the FCR market is open to competition such as in Germany and in the Nordics. In France, bulk generation operators would be welcome to outsource their supply of FCR -rules pending for January 2016 -if they found cheaper suppliers. Moreover, the supply of FCR induces an additional mechanical solicitation of the turbines and rotating machines that are not welcome by the producers (see SEA Energia's witness in Section 3.4).

CHALLENGES OF THE FREQUENCY CONTAINMENT DEFENCE PLAN

Process in 2013.

Nordics experience larger FCR prices during night

The opened data provided by [START_REF] Energinet | Energinet portal: Download of market data[END_REF] enable the access to the hourly evolution of FCR prices in both the bidding areas of DK Westconnected to synchronous area CE -and DK East -connected to synchronous area NE. It can be observed that FCR prices in DK East are up to three times more expensive during night (0 to 7am) than during the day. This seems to be in- duced by the specific unit commitment scheme the delivery of FCR imposes to power producers, as assessed as well by [START_REF] Farrokhseresht | Economic impact of wind integration on primary frequency response[END_REF]. On the contrary, the periods of negative residual load (Figure II.14), that occurs during nights of high wind production did not impact up to now the FCR prices, compared to the nights of low wind production.

Degradation of the frequency quality inducing larger FCR solicitation

Over fifteen years, the occurrence of frequency deviation disturbances larger than 100mHz has been multiplied by ten in the Northern Europe synchronous area (NE). It reaches a trend of frequency excursion out of this bandwidth 2.5% of the time in 2011 (Figure II.16). Figure II.17 provides one part of the explanation of this trend: most frequency excursions occur around full clock, that matches for each producer with the switch from one unit commitment plan to the next one. The deviations are even larger at 7:00, and 20:00 and 21:00 where the HVDC flows change significantly between the Northern Europe (NE) and Continental Europe (CE) synchronous areas [START_REF] Entso-E | Network code on electricity balancing[END_REF]. It corresponds to a discontinuity of the production plan that is induced by the trading of one-hour long power bids on the market, while most of the load consumption follows a continuous path. A second explanation could come from the penetration of intermittent RES-E that complicates the balance forecast.

Degradation of the system inertia

One of the oldest contributions assessing the impact of large RES-E interconnected to the power system came from [START_REF] Holttinen | The impact of large scale wind power production on the Nordic electricity system[END_REF] and [START_REF] Holttinen | Design and operation of power systems with large amounts of wind power[END_REF] with a focus on wind generation. At that time, power electronics were not commonly used in wind turbines architectures and the main concern of [START_REF] Holttinen | The impact of large scale wind power production on the Nordic electricity system[END_REF] was dedicated to the impact of sudden variations of wind power production on the system security. The author's fear was to observe in the future sudden imbalance events at the scale of a synchronous area that would be larger than the reference incident for which the FCR is sized. [START_REF] Holttinen | The impact of large scale wind power production on the Nordic electricity system[END_REF] concluded that the spatial variation of wind from turbine to turbine and from wind plant to wind plant lightens the effect of wind variation on the power output variation. As a result, wide wind power penetration would not require a modification of size of the FCR. The same effect would be expected for photovoltaic (PV) cloud effects at a regional scale, since the clouds' formation and movement is driven by the wind speed and is a slow phenomenon compared to time challenges of power system security.

As suggested above, [START_REF] Holttinen | Design and operation of power systems with large amounts of wind power[END_REF] did not fully assess however the impact that power electronics penetration among RES-E technologies would induce. There is currently a rising feeling of certainty among the power system actors regarding how the system security will evolve with the penetration of these technologies. The concerns address first PV installations connected to the grid through DC/AC inverters. It concerns then new wind turbines that embed a AC/DC/AC architecture instead of a conventional switch gear to maximize their power production. Having these architectures, these RES-E technologies are not seen any more by the grid as rotating machines. Consequently they do not contribute to the system inertia. As a result, experts foresee that the phasing out of bulk generation units and their replacement by such power electronic based RES-E will induce a reduction of the system inertia. [START_REF] Das | Primary reserve studies for high wind power penetrated systems[END_REF] investigated such concerns by performing simulations on one part of PEGASE system model [START_REF] Villella | Pegase pan-european test-beds for testing of algorithms on very large scale power systems[END_REF], which represents the power system of western Denmark (DK West). In their model DK West is devoid of interconnection with the rest of Europe. It results a 5140 MW grid, initially composed of 970MW of CCGT, 10MW of hydro and 4160MW of steam generator. In the simulations, the steam is progressively replaced by DC-connected wind turbines for a wind penetration rising from 0% to 80%. The simulation highlights finally a halving of the system inertia with a wind penetration of 40% (Figure II.18). [START_REF] Das | Primary reserve studies for high wind power penetrated systems[END_REF] analysed then the impact that wind penetration has on system frequency drop following the disconnection of 400MW of generation, assumed as a reference incident. The authors took the amount of primary reserve -i.e. FCR -available, as a second input parameter.

In the literature the lowest system frequency value reached following an incident is named the frequency Nadir. The impact of both the wind penetration and the availability of FCR resources on the frequency Nadir is presented in II.5 for Europe). This threshold is represented by a flat purple area set at the value of 49Hz. Each time the frequency Nadir goes under 49Hz, grid users interruption are induced. That challenges both the system reliability and the Key Performance Indicators (KPIs) of the System Operators. Figures II.18 and II.19 highlight that the higher the wind penetration, the lower the system inertia and the lower the frequency Nadir. And the lower the frequency Nadir, the poorer the System Operator's KPIs.

Moreover Figure II.19 shows that from a given limit of inertia, the Rate of Change of Frequency (ROCOF) becomes too large to enable a reliable operation of the FCR. This underlines that conventional FCR is not fast enough to prevent UFLS relays tripping (see contractual delays of activation of ≈ 5-15s in Figure II.10). Therefore, it appears a need to speed up the FCR activation. [START_REF] Das | Primary reserve studies for high wind power penetrated systems[END_REF] investigated a first palliative that relies on the supply of faster FCR provided from wind turbines. This on-site supply aims to increase the admissible wind penetration rate. The authors claim a significant improvement, enabling earnings of 13 to 28 points on the admissible wind penetration rate. However these improvements are not free of cost: respectively 20% and 40% of the wind production would have to be pre-curtailed to ensure a stable power system. This counters the objective of full grid coupling of carbon-free power production assets. [START_REF] Cardozo | A statistical analysis of the frequency response in an isolated power system with an increasing share of photo-voltaic generation[END_REF] highlighted finally another challenge of system inertia degradation due to RES-E. The authors studied the case of PV on the islanded networks of EDF SEI. Their conclusions show that PV penetration is capable of strongly modifying the unit commitment of coal and fuel-fired assets. Hence it modifies the amount of the kinetic energy that is available on the network along the day (Figure II.20). As a direct consequence, it modifies the power system inertia. The authors showed that a lack of inertia increases the risk of UFLS activation from 0 to 70%, when passing from a PV penetration rate of 30% to 70% [passing from 6hr to 19-27hr of UFLS activation per year]. However, the conclusion is not so simple. In some periods, the number of partly-loaded units committed enable the maintain of the system reliability despite large RES-E injection. Indeed, such partly-loaded units are capable of supplying FCR, while supplying kinetic energy to the system. In some other hours, the kinetic energy of the system collapses (Figure II.20), and UFLS activation occurs. [START_REF] Cardozo | A statistical analysis of the frequency response in an isolated power system with an increasing share of photo-voltaic generation[END_REF] claims finally that allowing PV curtailment in some precise situations would enable a limitation of the risk of instability. Additionally, it would limit the number of costly start-ups and shut-downs of conventional units, while the curtailment would induce less than 1% of loss of PV production per year. It appears as a both cost and system efficient logic.

Degradation of UFLS scheme efficiency

Section 1.7 presented the principle of operation of UFLS: the blind and automatic shedding of entire primary substation feeders, one after the other at predetermined frequency thresholds, starting from 49Hz, to prevent the system collapse in case of exceptional events.

Members of the power system community have recently expressed some doubts regarding the guarantee of efficiency of such a process, faced with a wide connection of Distributed Generation (DG) within the distribution network. Their fear relies on the observation that these DG would be connected at MV feeders that are controlled by UFLS relays within the primary substations. Figure II.20: Evolution of system kinetic energy along the day in islanded network depending of PV production and inherited unit commitment of conventional generation units. Case A/B/C: different strategies of grid tariff, likely to modify the unit commitment strategies of power producers [START_REF] Cardozo | A statistical analysis of the frequency response in an isolated power system with an increasing share of photo-voltaic generation[END_REF] As a result, the effectiveness of the disconnection of these feeders would be reduced compared to the situation without DG. Three different situations would occur:

Legend:

P DG : production of the DG located at a given MV feeder subjected to UFLS. P load : local load located along such MV feeder.

P DG < P load

The MV feeder still imports power from the transmission network. Its shedding stays beneficial for the system balance, but its efficiency can be lower than expected, especially if the UFLS sizing method used the historic sizing rule that relies on fixed reference load, such as the third Thursday of January, used in France (Section 1.7).

P DG = P load

The MV feeder approaches a state of self power-load balance. Its shedding is absolutely useless for the system balance while it damage the System Operator's KPI due to the interruption induced.

P DG > P load

The MV feeder has a negative vertical load i.e. it is exporting power to the transmission network. Hence, it contributes in a positive way to the restoration of the system balance, following a disturbance. Its shedding would be dangerous for the system security.

Finally, the lower the system size, the worse the impact. Moreover this issue of DG tripping has to be considered seriously in small power systems such as islanded systems. In addition, DG penetration is growing much faster in such small systems thanks to a much more favourable [START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF] Figure II.22: Effect of UFLS weakening due to by RES-E spreading on Kuching power system face to the reference incident (loss of the 0.48pu interconnection) [START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF] grid parity cost of these assets compared to the assets deployed in large interconnected systems.

To illustrate such concerns, simulations have been performed during this PhD work on a semiislanded network, representing the 218MVA system of the Asian island of Kuching [START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF]. Kuching has the particularity of being connected to the mainland through one unique interconnection that affords a cheaper power than the local generation using fossil fuel (Figure II.21). [START_REF] Aik | A general-order system frequency response model incorporating load shedding: analytic modeling and applications[END_REF] proposed an optimization of the UFLS scheme that enables the maximisation of the use of the interconnection while keeping the local network safe from blackout in case of the tripping of such interconnection following a fault. The model used reproduced accurately the results of [START_REF] Aik | A general-order system frequency response model incorporating load shedding: analytic modeling and applications[END_REF] by applying his model. The model outcomes conclude that such an UFLS scheme does not remain resilient if the DG penetration is larger than 20%, reducing the effectiveness of the UFLS scheme of the same magniture. Figure II.22 presents the simulation results with scenarios of 0%, 10% or 30% penetration of RES-E. The present issue has been assessed as well by De Boeck and Van Hertem [2015], who proposed three methodologies that are likely to handle this issue of UFLS weakening. The authors proposed first to introduce a simple tripping conditioned to the current direction. The second option is to modify the tripping priority of the feeders depending on a combination of the hour of the day and of the installed PV capacity of the feeder. The last option is finally to pre-coordinate the tripping to handle as best as possible the PV power injected close to real-time, thanks to a ranking of feeder tripping efficiency. This "Smart" approach requires however a replacement of the actual UFLS relays by new ones embedding ICT to enable the coordination.

The risk of UFLS degradation is less challenging on the large interconnected system. However, the situation could evolve in the future. [START_REF] Tennet | Network transparency -vertical grid load[END_REF] publishes for instance the net vertical grid load2 that flows from its transmission network down to the distribution grids in Germany.

Figure II.23 shows that such a vertical grid load can become negative in summer time periods.

During these periods, it means that most of the power is injected by DG on MV feeders down primary substations and not by historic bulk generation assets. Irremediably, it means that part of the UFLS-equipped MV feeders have a negative vertical load -i.e. P DG > P load . Therefore the degradation of UFLS efficiency would concern both islanded and interconnected systems at mid term.

Experimentation of industrial load involvement in FCR supply in France

The French regulator (CRE) introduced in June 2014 an experiment for the involvement of industrial load for the supply of up to 40MW of FCR [CRE, 2014a]

Conclusion of Chapter II

The System Operators commonly rely on four reserve means to guarantee the reliability of their power systems. ENTSO-E renamed in the last years theses reserves as the FCR, the FRR, the RR and finally the LFDD, in replacement of the former Primary, Secondary, Tertiary and UFLS reserves. Among them, the FCR and the LFDD are the unique autonomous and real-time reserves, that ensure the stability of the power systems. The FCR is the conventional mean of regulation of the system frequency. Historically, the FCR is supplied by bulk generation units. These assets must initiate the modulation of their level of load within the 15 seconds after a disturbance occurred. The magnitude of such an injection of FCR is proportional to the frequency deviation observed. Such an injection is predefined according to linear powerfrequency characteristic. Conversely, the LFDD is an emergency reserve that leads to step-bystep blind shedding of primary substation feeders, as soon as the system frequency drops by more than 1Hz. Any activation of LFDD relays induces an interruption in the supply of end-users, that deteriorates the Key Performance Indicators (KPIs) of the System Operators concerned.

The challenge of the System Operators is thus to have a sufficient and a fast-enough amount of FCR at their disposal to keep the frequency Nadir higher than the first frequency threshold of tripping of the LFDD.

Hence, the present chapter has presented the four main challenges the System Operators will face to ensure the procurement of a sufficient amount of fast-enough FCR, faced with evolving power system paradigms. First of all, a lack of availability of conventional FCR resources would occur. Firstly, such a lack would be induced by a lack of competitiveness of the FCR markets for these assets compared to the revenue they could earn on the wholesale markets. Secondly, such lack would be induced by the periodic non-availability of bulk generation assets 3. CONCLUSION OF CHAPTER II in periods of negative residual loads. The second concern addresses the degradation of frequency quality. Such degradation is provoked by the discontinuity of the unit commitment plan around the clock limit from one bidding hour to the other, while the demand is continuous. Such a degradation becomes a risk for the system stability while it constitutes an additional obstacle to the involvement of suppliers of FCR, that fears a larger solicitation and an over-ageing of their assets. The third concern addresses the degradation of system inertia. Such a degradation is engendered by both the penetration of power electronics interfaces in the newest RES-E technologies and the phasing-out of bulk generation assets. Last but not least, the spreading of DG down the primary substations is capable of dampening the effective impact of the activation of LFDD's relays on the power system balance. Therefore it would degrade the efficiency of the LFDD at the power system scale.

In light of these statements and in regards to the opportunity of spreading of DER flexibilities, this PhD work endeavours to develop an architecture that enables the supply of FCR, thanks to a coordinated modulation of DERs. In addition the architecture targets activation delays shorter than the delays presented allowed by ENTSO-E. This concept entitled Primary Support is presented in Chapter III.

CHAPTER III

Innovation Concept of Primary Support

Chapter III

Innovation Concept of Primary Support

The present chapter presents Primary Support, a concept of coordinated modulation of the level of loads of DERs, capable of supplying both FCR and UFLS/LFDD reserves. Primary Support has been thought of as an answer to the coming challenges of frequency stability summarized in the previous Chapter II (Section 2).

Section 1 details how Primary Support addresses these challenges. Section 2 benchmarks the innovative nature of Primary Support within the existing literature, reviewing both scientific publications and patents. The concept and operational processes of Primary Support are then presented in Section 3. Section 4 summarizes finally the value proposition of Primary Support.

1 Primary Support: a response to the challenges of system stability

Chapter 2 highlighted four main types of challenges to be addressed in the future by System Operators in order to guarantee the system stability with regards to frequency deviation events.

Primary Support concept has been developed and validated precisely to answer to these predetermined challenges. The genesis of the operational specifications of Primary Support is detailed in Table III.1. It relies on the identification of functional specifications that address these challenges. These functional specifications have then been converted into the operational specifications that are at the core of Primary Support.

Fulfilling the operational specifications results in the definition of an architecture of coordinated modulation of DERs. The detailed concept is presented in Section 3. It aims to supply FCR based on DER assets in order to replace or supplement the historic contribution of bulk generation units. Depending on the load processes controlled by Primary Support, shorter FCR activation delay would be expected compared to the current FCR providing units, that would provide a first answer to the reduction of system inertia. In addition, Primary Support relies on DER assets which are connected at LV feeders. Hence, Primary Support could be used as an

Challenges

Functional specifications

Operational specifications

Lack of availability of conventional FCR resources

Degradation of frequency quality

Degradation of system inertia

Degradation of UFLS efficiency

adaptive emergency load-shedding scheme, that would remain robust despite the penetration of DG at MV and LV feeders and compensate the lack of efficiency of the UFLS. Primary Support would therefore provide frequency-controlled reserves that are compliant with the FCR rules, while providing as well reserves which are operational between the frequency range of activation of the UFLS and FCR, as pre-UFLS reserve (Figure III.1).

The review of the existing literature, completed by a review of patents confirmed the innovative nature of the concept which has continuously evolved since 2013. The closest patents and the publications that go in the direction of Primary Support are presented in Section 2. The principle of the distribution of frequency regulation means is a service not so new. The first applications focussed on fully autonomous systems, devoid of any communication channel. The application relied on down-the-meters tripping relays. Somehow, it aimed at doing within the LV network what System Operators already do on the MV network with the UFLS tripping relays (Section 1.7). [START_REF] Besore | Smart plug with internal condition-based demand response capability -us patent 8[END_REF] and [START_REF] Fleck | Under frequency/under voltage detection in a demand response unit -us patent[END_REF] proposed a controller, interposed between a utility's network and a load, acting autonomously based on predefined threshold. Based on a similar principle, [START_REF] Koritarov | Frequency based electric vehicle charge controller system and method for implementing demand response and regulation services to power grid using frequency detection -us patent app[END_REF] wished to modulate EV charging cycles, depending on the network frequency, [START_REF] Cannon | Thermostat device with line under frequency detection and load shedding capability -us patent 7[END_REF] embedded the process into a thermostat and [START_REF] Hammerstrom | Pacific northwest gridwise TM testbed demonstration projects; part ii. grid friendly TM appliance project[END_REF] introduced the shedding of dryer and water heaters faced with emergency situations. [START_REF] Ockert | Load control receiver with line under voltage and line under frequency detection and load shedding -us patent 7[END_REF] brought an innovation in the process introducing a delay before the load-shedding, likely to play the role of a hysteresis. [START_REF] Qhihat | Underfrequency load shedding device based on household network -cn patent 202[END_REF] proposed a load shedding system to face frequency deviation, as a way of protecting the electrical devices, without specific concerns regarding system stability. Most of the patents quoted above implement a reversible process with automatic load re-connection when the load rise back above the frequency threshold. Such a reversibility differs significantly from the UFLS relays that require a manual reactivation of the loads. Some applications rely on wide numbers of frequency-controlled relays responding at the same frequency threshold to emulate the behaviour of one unique UFLS step. On the contrary some other applications rely on the random assignment of thresholds among the portfolio of relays commissioned. Using such a scheme, [START_REF] Molina-Garcia | Decentralized demand-side contribution to primary frequency control[END_REF] target to obtain a linear droop. To obtain it, the authors assess that the random assignment of threshold would induce a linear distribution of the frequency thresholds, at the condition that a portfolio of aggregation is large enough. Actually these applications are more emergency systems close to the UFLS than FCRcompliant applications.

Nonetheless, apart from their strict contribution to a UFLS scheme, the introduction of a linear droop as proposed by [START_REF] Molina-Garcia | Decentralized demand-side contribution to primary frequency control[END_REF] enables the creation of an effect of selfregulation of loads. Such an application can be interesting for the control of resistive loads whose power consumption remains independent of the network frequency unlike the rotating machines. As stated in Section 1.8 in Ch II, [START_REF] Entso-E | Operation handbook policy -appendix 1 load-frequency control and performance[END_REF]ENTSO-E [ , 2009] ] assume already as input the natural self-regulation of loads that occurs on the transmission network of Continental Europe (CE) to establish a resilient defence plan in case of sudden imbalance. Hence the application proposed by [START_REF] Molina-Garcia | Decentralized demand-side contribution to primary frequency control[END_REF] would enable to increase this ratio of self-regulation of loads and therefore improve the system security.

However such autonomous systems are static. Hence their contribution to the system stability is not constant through time, given that the power consumption of the portfolio of the loads controlled varies along the day and the season. Therefore [START_REF] Zhao | Optimal load control via frequency measurement and neighborhood area communication[END_REF] introduced an ingenious neighbourhood communication between the load controllers of a given area. Each load controller calculates its load reduction target, broadcasts its target to the other load controllers, and adapts its effective contribution depending on the feed-back it received. Such a process enables the guarantee of a constant contribution at the scale of portfolio of coordination. However [START_REF] Zhao | Optimal load control via frequency measurement and neighborhood area communication[END_REF] rely only on distributed peer-to-peer communication, that do not enable the System Operator to send specific feed-back. Despite a first guarantee of reserve availability, the System Operator does not have any control yet to modify the amount of reserves called.

However introducing a way of monitoring the availability of reserve would not be an innovation by itself for the final application targeted. For example, [START_REF] Black | System and method for estimating demand response in electric power systems -us patent app[END_REF] already introduced the notion of estimation of the available flexibilities among a portfolio of loads, based on data exchange between loads controllers and a coordination agent. In a centralized way, some applications introduced the ability of remotely updating the threshold embedded in the load controller thanks to a communication channel connected to a Network Operations Center (NOC) [START_REF] Hodge | Distributed frequency relay -us patent 6[END_REF]. It remains mainly a hardware-based application, that neither focusses on frequency control nor provides specific logic of threshold programming to reach predetermined objectives.

Additional contributions targeted then the introduction of a coordination of DERs for the supply of ancillary services products that are closer to the FCR. [START_REF] Yuen | The provision of frequency control reserves from multiple microgrids[END_REF] introduced a decentralized control system setup, wherein each DG unit -possibly compensated by ESSapplies a power-frequency droop equivalent to the droop currently applied by bulk generation assets. Such power-frequency droop would approach the standard FWHZ function claimed by IEC 61850-7-420 [2015] (Figure III.4). An aggregating agent is then introduced by the authors to scale-up each marginal contribution to a significant-enough size. In the absence of ESS units, it would however force a pre-curtailment of wind power and PV injection to enable the supply of upward FCR regulation. Based on the notion of aggregation, mainly driven by commercial purposes, their approach is finally not so different from the supply of FCR by large-scale wind turbines as already proposed by several contributions such as [START_REF] Erlich | Primary frequency control by wind turbines[END_REF] or [START_REF] Das | Primary reserve studies for high wind power penetrated systems[END_REF].

Finally, if a notable patent addressing economic optimization would have to be quoted, it would be the one of [START_REF] Tyagi | Method and system for demand response in a distribution network -us patent 8[END_REF], who introduced a decision process where the marginal cost of each bid is weighted by its effectiveness on the system. Such an approach would become valuable for load frequency control processes if it enables the consideration in the optimization process of the position of each FCR providing unit within the LV network in regards with the position of the UFLS relays at the primary substation.

At the end, the review of the documents quoted above, in parallel of the review of 86 patents that are detailed in Appendix D (page 195) leads to the identification of three main kinds of contributions: smart-less tripping relays adapted for static frequency stability defence plan ; aggregation platforms that assess the potential of flexibility through a monitoring of loads and ; aggregation platforms designed for system scale-up of local droop. However, none1 of the solutions propose the delivery of an accurate power-frequency characteristic, controlled over the time, adaptable depending on both the power system needs and flexibility resources availability, and involving DERs that are not able to provide by themselves a droop that acts continuously on a wide-enough frequency range. As mentioned in Section 1, this is precisely the target of the Primary Support concept. The detailed concept of Primary Support is presented in Section 3.

Supply of FCR by distributed ESS

A lithium-ion battery of 2MW/1.3MWh has been connected to a 20kV feeder operated by Enedis (ex-ErDF), for the need of the [START_REF] Venteea | Venteea project[END_REF] demonstration project. The system which is coordinated by a Programmable Logic Controller (PLC) produced by Schneider Electric [2015a] (Modicon M340), targets the supply of a dozen of services to the utilities [START_REF] Colin | The venteea 2 mw / 1.3 mwh battery system: An industrial pilot to demonstrate multi-service operation of storage in distribution grids[END_REF], including the supply of FCR. In their demonstration model, [START_REF] Amamra | Day-ahead primary power reserve planning and day-d primary frequency control of a li-ion battery[END_REF] target to perform full time FCR supply while providing parallel services when the State of Charge (SoC) of the battery is contained in a [20;80%] range to guarantee the continuity of supply of FCR.

In parallel, National Grid -the British TSO -has published in September 2015 a call for tender for the procurement of 200MW of ESS capacity. The assets must have a FCR full activation time of at most 1s and a Maximum FCR full activation period of 1hr (see Figure II.10 in page 65). It is reminded that the present FCR need for FCR in the synchronous area of Great Britain (GB) is of 600MW (FigureII.9 in Figure 64). [START_REF] Deign | Uk's 200 mw grid storage tender flooded by battery bid interest[END_REF] announced the tender "resulted in 68 project submissions totalling 1.3GW . Of all the submissions, 888 MW were for battery projects and the remainder included alternative technologies, such as flywheels and diesel-battery hybrid plants". The motivation of National Grid is "to offset losses in spinning reserve as all of the UK's coal-fired plants are due to be closed over the next 10 years", expressing thus the same fears as it has been developed in Section 2.1 in Ch II.

The unknowns -activation time, battery ageing, remuneration, etc. -that used to remain around the involvement of batteries in the supply of FCR seem to have been resolved. The distributed involvement of large battery assets (≥ 1M W ) could be THE revolution of system stability by 2020 and become a significant part of the State of the art of distributed frequency control.

Primary Support is a solution that introduces a coordination for the modulation of the level of injection/withdrawal of a pool of flexible DERs. The frequency range of operation targeted by the solution would encroach upon either the FCR or the UFLS range (Figure III.1). By doing so, the solution enables first the supply of FCR (see challenges in Table III.1). It could then pre-empt partly the blind tripping of UFLS relays in case of major frequency excursions. Thus it could avoid the affecting of vital loads and avoid the disconnection of the Distributed Generators (DG) whose availability is essential at any time for the system stability. It involves sites that are potentially composed of one unique load controlled in ON/OFF (All-or-Nothing mode). Each of these loads could not comply independently with the operational rules of the ancillary services targeted, which justifies such aggregation of ON/OFF behaviours.

Multi-layers process

The robustness of the solution relies on a multi-layer process where the DERs (layer 0) are controlled and coordinated by two successive upper layers. While doing so, the action of load modulation itself (layer 1), which is performed in real-time, is split from the action of coordination of the modulation events (layer 2) of the loads which is performed ahead of real-time. Close to real-time (≤ 15min), this action of coordination enables the determination of how each DER must behave in order to reproduce the supply at the system scale of the expected ancillary service such as the FCR. A last layer (layer 3) can eventually be introduced to allow a resilient scale-up of the solution for the supply of several MW. Figure III.2 presents such a multi-layers structure, from the DERs themselves (layer 0) up to the potential market interface (layer 3). Sections 3.2 to 3.4 describe the expectations of Primary Support from layers 0 to 2. The early developments of layer 3, which has not been fully deployed are presented in Section 3.5.

Targeted DERs -layer 0

Primary Support targets by priority the supply of upward frequency-controlled reserves involved in the prevention of under-frequency events. The architecture of the solution remains however fully compliant with the supply of downward reserves that are required to handle over-frequency events. This priority is driven by three main reasons. First of all, under-frequency events are usually more critical for the system stability than over-frequency ones. Secondly, the supply of upward reserves is more challenging for bulk generation units than the supply of downward reserves. The supply of upward reserves imposes actually the producers to limit their sales on the wholesale markets, contrary to the downward reserves. Lastly, the price that System Operators are willing to pay for upward reserves is larger than the price paid for downward reserves (see Section 2.1.2), notably due to the two previous reasons.

For such an objective of upward reserves supply, the most adapted DERs are the distributed loads, so-called Demand Response (DR) units. Primary Support focusses therefore mainly on the coordination of DR. For the same reason as for bulk generation, the involvement of Distributed Generation (DG) for the supply of upward reserves is not so adapted, despite several initiatives that go in this direction have been claimed. It requires actually a pre-curtailment of the DG production to be able to later increase the power production following a frequency drop. The contribution of carbon-free DG for such an upward reserve supply would even go so far in opposition with the final objective of the maximization of both the grid and market coupling of such assets.

On the contrary, the involvement of carbon-free DG for the supply of downward reserve would be an interesting idea to explore. Indeed, it would not require any pre-curtailment. Therefore, it would not impact so much both the grid and market coupling of such units, thanks to the scarcity of frequency deviation events (see statistics in Section 4.3). Last but not least, it has to be noticed that the supply of downward reserve can be done anyway using DR units which are energized only in periods of over-frequency, and left off otherwise. Such reasons justify why Primary Support has been thought of as well for the supply of downward reserves obtained from any kind of DERs. However it has to be noticed that the present thesis does not treat in-depth this downward side of delivery.

Given these operational constraints of FCR supply, Primary Support targets then the involvement of distributed assets that can be re-energized as fast as they have been shed. The expected shedding time is at most 10s, knowing that the shorter the delay, the better for both the system Primary Support is capable of controlling either domestic loads, tertiary loads or even some industrial loads of contained size. Figure III.3 represents the kinds of loads considered as compliant. In the domestic sector, a focus is dedicated on the thermal loads such as domestic heaters and boilers. In the tertiary sector, the control of HVAC systems looks like a great opportunity, taking the control of variable speed motors of compressors during periods of contained length.

The control of Uninterrupted Power Supply (UPS) during even shorter period appears as a third great opportunity. The modulation of Electric Vehicle (EV) charging depending on the system frequency is a great challenge for the future. However, such a challenge is conditioned to a sufficient market penetration of EVs. Finally, a last challenging application is the control of public lighting through voltage modulation. Lighting control for frequency regulation purpose is an exciting application, given that lighting has been assumed from the emergence of the Demand Response as a vital and uninterruptible load. Actually the objective of both UPS and public lighting involvement in FCR supply has been targeted following the monitoring of the system frequency each second over six weeks, whose results are reported in Section 4.3. In addition to publishing this dataset, the Section 4.3 details why the involvement of such unusual loads for Smart Grid purposes is consistent.

In the present applications, UPS and EVs are considered as DR and not as ESS assets: no power re-injection on the grid is assessed. Moreover, ESS technologies themselves have been considered as relatively out of the scope of Primary Support from the beginning of this PhD work. Such a decision is mainly based on cost -there were no "Giga-Factories" built in 2013, as claimed by Tesla. In addition, the involvement ESS dedicated to the supply of FCR, has not been assessed as a deep research challenge, considering the significant flexibility of operation of ESS.

Real-time process -layer 1

The real-time process is the first operational layer of Primary Support. It relies on a DER controller that acts autonomously and which decides on its own to modulate up or down the DER it controls depending on the evolution of the system frequency. The modulation of the level of load depending on the frequency follows a predetermined characteristic displayed in 96 ), the process of re-energization of the DER is not reversible any more in term of power-frequency pattern (dotted lines). Indeed, the slope of re-energization is expressed in term of power recovery per unit of time and not per unit of frequency. Hence, the pattern of the power recovery on the power-frequency chart differs from one event to the next one depending on the frequency evolution during each period of recovery.

Figures III.4 (a) and (b) present a FWHZ power-frequency characteristic adapted for DG modulation, with a frequency Nadir larger than the nominal frequency (i.e. 50Hz in Europe). This characteristic drives a reduction of the level of generation of DG faced with over-frequency event.

A similar characteristic, that relies on inverse direction is used as well in Primary Support for the modulation of DR assets.

For the purpose of Primary Support, the frequency is measured on-site by the DER controller thanks to a power meter having precise frequency measurement capability (0.01Hz -Table II.2). This local frequency measurement enables the speed-up of the load modulation decision. Indeed the action is not slowed down by remote communication delays.

The power-frequency characteristic followed by the DERs involved in Primary Support relies on a data model defined by the Frequency-Watt mode logical node (FWHZ) of IEC 61850-7-420 [2015]. IEC 61850-7-420 [2015] is the international standard that structures the basic functional behaviours of DERs. At mid-term, the deployment of a concept natively compliant with the IEC61850 processes would make it easier to replicate and scale-up. This native compliance will require to make the communication services of Primary Support compliant with the future IEC 61850 -8-2 [2016].

The use of the FWHZ function enables the involvement of DER assets that can be modulated either linearly or on-threshold depending on the frequency deviation. The involvement of loads that can be controlled only with ON/OFF positions thanks to steady-state relays, solely requires the definition of a W gra slope large enough to induce the shedding of the whole load within the range of accuracy of the frequency measurement device. The method of calculation of Wgra for such loads controlled on-threshold is detailed in Section 3.4.4. The reader is however reminded that the initial spirit of Primary Support is to enable the contribution of DERs controlled in ON/OFF to ancillary services that require a linear regulation at the system-scale thanks to a coordination of DERs' modulation thresholds. The FCR is an example of such ancillary service. However the use of FWHZ increases the portfolio of addressable DERs likely to get aggregated by the coordination platforms of Primary Support (layer 2 -see Section 3.4). Such increase of the portfolio of addressable DERs is of importance to reach a critical size of aggregation in an easier manner.

As identified in the state of the art (Section 2), the basic shedding of distributed loads at predetermined thresholds remains close to what has been done for decades to indirectly enhance the behaviour of self-regulation of loads of the power system faced with a deep frequency drop. The real innovation of Primary Support comes from the logic of updating both the threshold HzStr and the slope W gra of each DER. Such a logic enables the supply of a FCR-compliant product thanks to an aggregation of the behaviour of each of the DERs of a given portfolio. The operational process of real-time coordination of the threshold HzStr and slope W gra of each DER is presented in Section 3.4.2. Such a process is actually coordinated by an upper layer, detailed in Section 3.4.

IEC 61850

IEC 61850 is a standard for the design of power utility automation. The initial works on IEC 61850 were initiated by EPRI and IEEE in 1988 before they merged their efforts with the Technical Committee 57 (TC57) of the International Electrotechnical Commission (IEC) in 1997.

IEC 61850 has been developed to enable a wide interoperability between the control systems employed to monitor and control the electric power components, regardless of the equipment manufacturers. IEC 61850 features two major blocks of information: the definition of operational functions (data modelling) and the mapping of communication processes (data transfer).

The data modelling enables the standardization of the internal behaviour of each category of network components, thanks to the definition of their operational functions defined as Logical Nodes. The standards of data transfer aim to provide a fast and reliable mechanism of transferring event data over the entire substation networks, using multicast, broadcast services, etc. The current mappings in the standard are composed of MMS (Manufacturing Message Specification), GOOSE (Generic Object Oriented Substation Event), SMV (Sampled Measured Values) and soon, Web Services. These protocols can run over TCP/IP networks or substation LANs, using high speed switched Ethernet to obtain a response time below four milliseconds, that is necessary for protective relaying.

While IEC61850 focussed initially on electrical substations, there are related standards that emerged to characterize the DERs. IEC 61850-7-420 [2015] states a variety of logical nodes associated to DERs' behaviours, while IEC 61850-8-2 [2016] maps new communication services, specifically designed for devices like DERs.

IEC 61850-8-2 [2016] introduces the use of XMPP, mapped on a MMS service -as for IEC 61850-8-1 [2011] -and encoded on a XML scheme.

Coordination of the distributed thresholds and slopes -layer 2

Each coordination server of Primary Support hosts a platform which operates the process of coordination of the behaviours of each DER. Such coordination platforms belong to the layer 2 of Primary Support (Figure III.2). The coordination platforms are independent of one another. Each of these are in charge of coordinating their own portfolio of DERs, in order to satisfy a set of demands.

The first role of a coordination platform is to gather both the operation and business data that are required to calculate the real-time parameters (HzStr, W gra, etc.) of each DER of the portfolio of aggregation. The second role of the platform is to determine in advance the parameters that each DER controller has to apply in real-time. The computation of these parameters occurs minutes ahead of the operational time. An update of these parameters during As previously claimed, the objective of such step of coordination is to provide at the power system scale, any kind of resultant power-frequency characteristic. Such power-frequency characteristic can be either linear (FCR pattern), composed of stairs (UFLS pattern) or a mix of both. Moreover the DERs involved can be driven either through power steps (ON/OFF command) or through a modulation of power that varies linearly depending on the system frequency.

Figure III.5 illustrates the basic principle of assignment of thresholds HzStr d , applied to a set of DERs d, driven exclusively by ON/OFF commands and that lead to the supply of a linear power-frequency characteristic which complies with the requirement of FCR. The key idea behind the building of such a resultant curve looking like a stair, is to extend each piled block of dispatchable power in parallel of the frequency axis up to cross the power-frequency characteristic to be supplied (blue-dash line).

Section 3.4.1 presents first the input and output data of the algorithm of threshold coordination. Section 3.4.2 presents then the flow of data among the different layers that enables a resilient coordination of thresholds in operation while Section 3.4.3 presents the algorithm of threshold coordination that has been developed. Section 3.4.4 explains finally how the conditions of contribution of each DER controlled in ON/OFF mode have to be pre-configured in the DER owners interface of Primary Support.

Operational parameters

The deployment of Primary Support requires the definition of 26 parameters per DER. 20 parameters among these 26 are directly used to compute the threshold coordination algorithm. These 26 parameters are split into four categories which enable the characterization of either the global behaviour of the DER, the real-time behaviour of the DER or the willingness of DER owners to get their DER involved in the frequency regulation process. The fourth category concerns parameters used only internally for a correct computation of the algorithm.

The parameters that characterize both the global and the real-time behaviour of each DER correspond to standard parameters defined in different logical nodes -i.e. sections -of the IEC61850. These are the logical nodes FWHZ, MMXU, DRAT and LLN0. In standardization terminology, the parameters used are named data object. The use of standard parameters enables both the DER operators and ancillary service providers to operate their process with all the adaptability that can be required. The opportunity is especially to enable the DER operators to operate several smart grid functions from the same DER, one after the other or even in parallel.

Parameters of global DER behavior (IEC81650-7-420)

Four first parameters that belong to the Frequency-Watt mode (F W HZ) logical node, characterize the global behaviour of the DER are presented below:

W CtlHzEna enables the FWHZ mode to be activated, tested only or inhibited ;

ActDlT mms introduces a delay between the crossing of the threshold HzStr and the start of the load modulation; ClcN xtT mms defines the length of each calculation interval. Hence, it determines how often the power data exchange occurs between the DER controller and the coordination platform;

HysEna enables the operation of the FWHZ mode with or without hysteresis.

These four parameters remain commonly fixed throughout time. These are four of the six parameters that are not used as inputs of the threshold coordination algorithm. They are sent to the DER at their initialization only and not continuously in real-time (Flow 0 in Figure III.7).

Real-time input -output DER parameters (IEC81650-7-420)

As presented in Section 3. M inW out and M axW out describe DER generator ratings (logical node DRAT ). They respectively inform of the lower and upper limit of power consumption (for DR) or production (for DG) beyond which the DER cannot operate. For ease of operation, M axW out can be pre-defined as the nominal power of the DER; T otW informs of the real-time participation level the DER (logical node M M XU ). The effective upward flexibility of a given DR unit is then calculated by subtracting M inW out from T otW . In the same way, the downward flexibility can be obtained by subtracting

T otW from M axW out. The opposite operations would be performed to assess the upward and downward flexibility of a DG unit.

The two last output parameters are system and state monitoring-only parameters. These are the two last of the six parameters that are not used as inputs of the threshold coordination algorithm:

Hz provides the real-time system frequency value, measured on-site (logical node M M XU ). Such a value is theoretically useless for the process of load coordination. However, the monitoring of this value remains interesting for purposes of vulgarization in demonstration periods;

Health describes the coordination platform of the state of operation of the DER (normal, critical, etc.) (logical node LLN 0).

Two DER input parameters enable the remote definition from the coordination platform of how each DER must behave in regards to a frequency deviation (logical node F W HZ) (Figure III.4):

HzStr defines the frequency threshold below which the DER starts to be modulated (upward regulation context); W gra defines the power-frequency slope at which the power modulation occurs (in p.u. / Hz).

These two DER input parameters are then completed by two additional parameters if and only if the DER is operated using hysteresis (HysEna = 1):

HzStop defines the frequency above which the process of power recovery initiates following a power modulation event;

HzStopW gra defines finally the speed at which the power recovery occurs (in p.u. / minute).

The exact data model of these thirteen IEC61850 parameters used for the operation of Primary Support is illustrated in Figure III.6. Table III.2 provides the definition of these parameters, that enables the perfect characterization of the real-time behaviour of each DER in operation.

The thirteen parameters left are either used to define the willingness of each DER owner to get its DER involved in the frequency control process or is used for internal computation issues. They are summarized in Table III.3.

Market-related DER parameters

One added-value of Primary Support is to enable each DER owner to define its willingness to contribute to the frequency control process. Such willingness is defined by six parameters associated to a given DER, that are taken as inputs of the threshold coordination algorithm:

W graM in and W graM ax enable the slope W gra of power modulation to be limited. The definition of such values have to be chosen by the DER owner depending on the physical ability of the DER to deeply modulate its power consumption; F min and F max limit the frequency range of operation within which the DER owner accepts the modulation of its DER. F min and F max are chosen by the DER owner depending on both the number of load modulation events and the cumulative length of modulation per hour he considers as acceptable. Statistics of modulation are provided in Section 4.3; EnergyP rice and CapacityP rice represent respectively the energy and capacity prices the DER owner would like to be compensated for the activation of its DER for frequency control purposes.

Internal parameters used by the threshold coordination algorithm

The threshold coordination algorithm takes as input a unique two-dimensional matrix composed of 20 columns and as many lines as the sum of both the DER offers and the demands bids to be satisfied. Two first parameters aim to identify clearly each bid:

T ype is used to determine if each bid filled is a DER offer or a demand bid; idCEM S aims then to associate a unique index to each offer or demand bid. Such uniqueness of the index is of great importance for the correct computation of the algorithm. Two given offer and demand bids can however have the same index idCEM S given that they have a different T ype value.

Two parameters are then introduced to take into account the ICT channel that connects each DER to the coordination platform. Each DER controller is indeed connected to the coordination Starting limit of power recovery following a frequency regulation event in hysteresis mode (= HzStr if HysEna=0).

Starting limit of the frequency regulation (threshold or beginning of slope). platform through either an XMPP server or an HTTPS webservice. The challenge for the threshold coordination is that the coordination platform cannot initiate the communication with any DER controller connected through an HTTPS webservice. On the contrary, the initiation of the communication with the XMPP-connected DERs is possible from the coordination platform. Hence the threshold coordination algorithm has to compute only the XMPP-connected DERs and the HTTPS-connected DERs whose communication link has been initiated from the DER controller side. Otherwise the DERs connected through a presently closed HTTPS link could not get informed of any expected modification of behaviour. As a result:

IsXM P P enables the differentiation of either the XMPP or HTTPS channel used by a given DER;

IsRequester enables the declaration of the present opening of the HTTPS channel. A fifth parameter is then required to enable the selection of the portfolio of defined bids at the merit order:

Intern parameters used by the algortihm of

BidP rice corresponds to the resultant bid price of a given DER, having a threshold HzStr. BidP rice is calculated thanks to the equation III.2 (page 111).

Two last parameters enable the identification of the contribution of a given DER in the resultant power-frequency characteristic built by the threshold coordination algorithm (see illustration in Figure IV.18 on page 148). These are more visualisation and monitoring-oriented parameters than parameters that are vital for the operation:

P minCum defines the lower power bound of contribution on the resultant power-frequency characteristic;

P maxCum defines the upper power bound. DERs while it considers the threshold and slope of the non-reachable DERs as a predefined frequency controlled contribution. Thus, it is not possible to update a DER behaviour that cannot be physically implemented due to the inability to inform the DER of the new behaviour it should respect (see Section 3.4.3).

At the DER side, each message containing the {M inW out, M axW out, T otW } dataset is sent with a periodicity of ClcN xtT mms (in milliseconds). A spontaneous message can be sent by some of the DERs as well, each time its effective power consumption T otW varies by more than a predetermined share. However such a share is not a standard parameter and is implemented directly in the operational script of the DER controller (layer 1). However, such a sending of spontaneous message has not been described in the IEC61850. This is characteristic that has been specifically designed for the operational purposes of Primary Support.

As a result the periodicity of the clearing can lead from a dozen of seconds to a quarter of an hour, depending on the stability of the power output of each DER and of the periodicity ClcN xtT mms chosen for each DER. The algorithm takes as an input one unique 2D matrix. The matrix is composed of 20 columns and as many lines as the sum of both the number of DER offer bids and the number of demand bids filled in the coordination platform. Table III.4 displays the order in which the 20 parameters presented in Section 3.4.1 must be filled in the input matrix. For ease of operation, the output matrix has exactly the same size and specification as the input matrix. The column ranking presented in Table III.4 remains valid as well for the output matrix.

Threshold & slope computation algorithm

The algorithm is split into two main parts, firstly aiming at conditioning the offer and demand bids, before proceeding to the bids clearing itself i.e. the assignment of a new {HzStr; W gra} pair to each of the reachable DERs. These two main parts are identified by the two grey dark frames in Figure III.8.

Flexible Resources Operation

/ IU ! " # $ % & ' & & ( ) * # )) # $ $ $ +, " - $ +, ".- () ) ,) ,) ( ( # ( ) () ) # $ ' ' ) / )) * # )) / )) 0 ! 1 (( ( 2 2 2 " $ )
Figure III.7: Sequences of data exchange between the PrimarySupport coordination agent and a DER controller

Offer & Demand bids conditioning

The process of bids conditioning aims at identifying the offer bids of the reachable DERs, the offer bids of the non-reachable DERs and finally the demand bids.

The identification of these three kinds of bids, enables the building on the one side of the resultant demand (pthDemand(f )) to be supplied ∀ f ∈ [47.5Hz; 50hz] and on the other side the initial resultant offer (of f erAssigned(f )). pthDemand is built by summing all of the powerfrequency characteristics associated to each demand bid, regardless of their prices. The initial of f erAssigned is built by summing the power-frequency characteristics of the non-reachable DERs that are already in operation.

These resultant curves express the derivative of power dP per sub-frequency interval df either required (demand) or provided (offer) at the scale of the aggregation portfolio. The algorithm assumes a sub-frequency interval of df = 10mHz, in accordance with the accuracy of frequency measurement devices required by ENTSO-E [2013d] (Table II.2). These curves are consequently expressed in W/0.01Hz.

Update of HzStr; W gra pairs of each reachable DERs

The clearing of the pool of reachable DER bids is performed through a set of sub-clearings whose aim is to match the offer and the demand within each sub-frequency range. Each subfrequency range has a width of df = 10mHz. Each sub-clearing is performed starting from the sub-frequency range that is the closest to the normal frequency of 50Hz i.e. [49.99; 50.00Hz] down to the limit of generators disconnection at 47.5Hz i.e. [47.50; 47.51Hz].

Each sub-clearing is preceeded by the extraction from the pool of available DER offer bids, of the bids that are defined on the entire sub-frequency interval of clearing. Then, the DERs selection is performed during the sub-clearing only among this list of defined bids. Such a condition of definition is expressed by the equation III.1:

F min d ≤ [f -0.005; f + 0.005] ≤ F max d (III.1)
where f is the center of the frequency interval wherein the subclearing occurs (in Hz)

[F min d ; F max d ]
is the suitable frequency range of contribution of a given DER d (in Hz)

Then, the selection of a given bid among the set of defined offer bids that have been previously extracted, is performed in merit order. The offer bids are selected one after the other starting from the bid that has the cheapest BidP rice(f ) at the frequency of clearing f . The BidP rice of each defined DER depending on its frequency threshold HzStr is calculated based on the equation III.2, which uses the function of probability of activation P act displayed in Figure III.9.

           HzStr d = f + 0.005 W gra d = T otW d -M inW out d HzStr d -max(47.5Hz; F min d ) W graM in d ≤ W gra d ≤ W graM ax d (III.3)
where f is the center of the frequency interval wherein the subclearing occurs (in Hz), while the others parameters are real-time and market related parameters of the DER d, presented in Section 3.4.1.

Each sub-clearing of mean frequency f selects then as many DER offer bids as required until satisfying the resultant demand. Such logic of bids selection matches with the equation III.4:

d ∈ {DER selected} W gra d ≥ pthDemand(f ) -of f erAssigned(f ) (III.4)
where f is the center of the frequency interval wherein the subclearing occurs (in Hz)

{DER selected} is the list of DER offers selected during the subclearing centered at f W gra d is the slope of the DER of index d listed in {DER selected} (in W/0.01Hz) pthDemand is the ideal resultant demand to be satisfied at the subclearing at f (in W/0.01Hz) of f erAssigned is the resultant offer already assigned ahead the subclearing at f (in W/0.01Hz)

The last step of each sub-clearing aims finally to update of f erAssigned, by adding to it all of the DER offers that have been assigned following the present sub-clearing centered in f . Such a step enables the keeping up-to-date of the resultant offer already assigned. Such up-to-date resultant offer is later reused as base-load contribution at the following sub-clearings to assign additional DER offers if required by equation III.

of f erAssigned(f )+ = W gra d ∀f ∈ [HzInf d ; HzStr d ] ∀d ∈ {DER selected} (III.6)
Finally, it can be noticed that this algorithm of coordination enables the call for the contribution of DERs in the limit of the needs of the demand. At the end, in case of an excess of offer compared to the demand, the most expensive DER bids are not called for contribution and are kept in reserve to prevent a potential lack of DER flexibility along the time of operations. Hence, the resultant offer is lower than the maximal potential of the pool of DERs. Such a gathering of back-up flexibilities guarantees the delivery of a droop that complies with the specific demand.

The thresholds HzStr d of all of the DERs d kept in back-up, equal the lower limit of generators disconnection i.e. 47.5Hz.

Definition of the slope of the DERs controlled in ON/OFF mode

The drive of loads in ON/OFF mode remains easy to do using the FWHZ data objects. It only requires the definition of a slope Wgra (in % of MaxWout /Hz) that leads to the shedding of the entire DER flexibility (T otW out -M inW out) within the standard accuracy of frequency measurement df (equation III.7):

W gra = 100 × T otW -M inW out M axW out × 1 df (III.7)
This relation can be simplified considering the inequality of equation III.8:

T otW out -M inW out ≤ M axW out (III.8) <=> W gra = 100 × T otW -M inW out M axW out × 1 df ≤ 100 × M axW out M axW out × 1 df (III.9) <=> W gra ≤ 100 df (III.10)
Finally, the definition of a slope W gra = 10000 in the CE synchronous area -where df = 0.01Hz (Table II.2) -enables the characterization of the delivery of flexibility using the ON/OFF mode (equation III.11):

W gra ≤ 100 0.01 = 10000 (III.11) Such W gra slope of 10000 can be used in NE as well, while a slope of 6667 is sufficient in GB and IRE where df = 0.015Hz.

However the coordination algorithm (layer 2) performs the clearing through successive subclearing steps of 10mHz width. Hence, it is advised to rely on the values W graM in = W graM ax = 10000 to operate a DER in ON/OFF mode, regardless of the synchronous area of operation. Such a definition of W graM in and W graM ax would guarantee an accurate delivery at the system scale, of the resultant power-frequency characteristic.

Cooperation between two different coordination platforms -layer 3

PrimarySupport has been designed as a system able to be deployed either within one unique coordination platform of large scale or around a multiplicity of reduced scale coordination platforms, easy to replicate one another. While a wide-scale platform would be cloud-oriented, the use of a multiplicity of small platforms would for instance enable to rely on aggregation portfolios that are in adequacy with the grid topology as presented in Section 4.2.

On the one hand, the use of a reduced-scale portfolio enables the provision of a resilient service at the system scale. Indeed, if one coordination platform crashes or gets in trouble, only a reduced amount of vital reserves will not be supplied. The loss of such a unit of aggregation could be included in power flow simulations as a probable network incident for which the power system must remain safe (N-1 rule). Such computation exercise would for instance provide an idea of the suitable maximum size of aggregation portfolio. RTE's preliminary rules of FCR delivery from DR units requires an accurate delivery 99% of the time. The constitution of 100 different aggregation portfolios, with a probability of failure lower than 1/100 would for instance enable the fulfilment of such a criteria 24/7, in terms of software and ICT risk.

On the other hand, the use of too-reduced portfolio of aggregation independent one from another would not be efficient. Indeed it would require to keep too large amount of reserves in back-up compared to the portfolio's size, to guarantee an accurate and resilient delivery of FCR per coordination platform.

Therefore, the introduction of one upper layer of coordination wherein back-up bids would be shared among coordination platforms looks interesting. Such a layer would enable that one back-up offer would be operated by a coordination platform in situation of excess of reserve at the benefit of another coordination platform that misses back-up. In such a situation, the DER controller (G2Elab_A in This upper Layer 3could be coordinated by an upper authority or an automated ICT agent in charge of operating a dedicated pool. It could either be self-regulated thanks to peer-to-peer trading and agreements among several coordination platforms (blue link looped in the layer 3 in Figure III.2 on page 95). Such peer-to-peer trading of back-up reserves has been tested in an off-grid context at G2Elab but did not lead to wide demonstration results. At the moment, such peer-to-peer link is not implemented in the Primary Support application of Struxureware Flexible Resources Operation platform (see Section 2) and no data model has been defined yet for such real-time sharing of back-up reserves.

Future improvements

The concept of Primary Support would evolve in the future, by either the implementation of additional functionalities or by the modification of the algorithm of thresholds and slopes clearing. Five directions of improvement are listed below:

It can be observed that the algorithm currently addresses only the supply of upward frequencycontrolled reserves to handle frequency drop events. As previously announced in Section 3.2, an extension of the present algorithm to address downward regulation would be easily achieved as well.

The algorithm presented considers both the FCR and UFLS demand as non-elastic bids. As a result, the demand is satisfied regardless of the bid price of the offer bids selected to match In such a case, the algorithm maximizes the slope of delivery -i.e. W gra d = W graM ax d -and summed only the activated flexibility to the resultant curve of f erAssigned. However the DER owner cannot refuse such partial activation. Hence, a complementary clearing rule could be to enable the DER owner to accept or not the delivery of such a partial bid, as proposed in the initial claims of Primary Support [START_REF] Lebel | Distributed and coordinated demand response for the supply of frequency containment reserve (fcr)[END_REF].

A previous algorithm assumes the filling of both offer and demand bids whose prices were defined as a function of the frequency of assignment / delivery. It was a way to better assume the DER interruption that a DER owner was likely to accept. Such a product proposed in the initial claims of Primary Support [START_REF] Lebel | Distributed and coordinated demand response for the supply of frequency containment reserve (fcr)[END_REF], has however been considered as too different from conventional power products. Hence it has not been implemented in operational scripts.

Since the resultant demand is usually a linear function while the resultant offer is composed of piled blocks, tolerance limits could be introduced in the algorithm, to guarantee that both curves of resultant demand and offers remain close enough one another. The introduction of such tolerance limits follows the spirit of the implementation range that has been introduced by ENTSO-E [2015b] for the delivery of LFDD (Figure II.12). The aggregation of small-size offers compared to the resultant demand is however supposed to make this discontinuity of offers negligible when compared to the system scale demand.

The standardization of the function of peer-to-peer trading of flexibility between the two different coordination platforms (Section 3.5), could be natively implemented in the system.

To prevent a risk of lack of offer within the time of operation, the algorithm of coordination could introduce a ratio of non-affected bids to be kept in reserve. The peer-to-peer exchange of bids during the time of operation would thus focus on the exchange of these non-affected bids. Such repartition would enable to split the business issue of bid sourcing from the operational issue of real-time delivery of flexibilities.

The opportunity of standardization

The spreading of the IEC 61850 -8-2 [2016] standard, using XMPP to connect DERs is a promising opportunity for the supply of energy and capacity services to either wholesale actors or System Operators. By purchasing ancillary services provided by DERs, System Operators tip actually over an area astride regulated systems -the distribution and transmission grids as a natural monopoly -and deregulated systems open to the market. To communicate with these DERs, the utilities have to go over the public power meter and so go out of their private ICT network (blue dotted lines in the figure below) over their own proxy. As such, they would tackle a wide variety of protocols that compromises their effective ability to control in real-time these DERs, facing proxies and native port closure of the private ICT networks (orange dotted lines) wherein the DERs are connected. As illustrated in the figure below, the emergence of a future dominant protocol that requires only output flow, like XMPP is a great chance to breakdown complexity towards DERs connectivity. Beyond the only issue of connectivity compliance claimed by the IEC 61850 -8-2 [2016], the use of standard function claimed by IEC 61850-7-420 [2015] appears as a business opportunity. Firstly, it would cost-kill the effort of DERs integration. Secondly, such a standardization would ease the involvement of a given DER into power market successively or even meantime, given that the capabilities of each DERs would be better known in advance according to the standard. Doing so, the critical size of a DER required to pay-back its integration cost, would be significantly reduced.

Primary Support has been designed having in mind such opportunities. In such a spirit of reserve sharing, a DER could provide both VoltVAR and FCR support. Indeed, the coordination ability of Primary Support enables the guarantee of a constant supply of FCR reserves at the scale of a pool of DERs, despite the local disturbance of level of load induced by the VoltVAR support at the scale of one DER.

The added values claimed by Primary Support are mainly its robustness, its adaptability of architecture and its contained impact on the DER processes, ensuring its easier acceptance by the DER owners. These three characteristics are detailed in the three subsequent Sections.

Robustness

The present section summarizes the specificities of Primary Support architecture that ensure the robustness of the solution:

The architecture of system monitoring: the coordination platform gathers the power consumption of each load directly monitored by each DER controller. The frequency monitoring is then performed only by the DER controllers.

The coordination of the solution behaviour: the coordination platform self decides ahead of the operational time the behaviour of all the DERs of the portfolio of aggregation, in case of frequency deviation events.

The distribution of the decision process: Each DER controller decides finally autonomously to shed and re-energize the DERs it controls, thanks to an on-site frequency monitoring, in order to comply with the specific frequency behaviour of each DER that has been defined ahead of the operational time by the coordination platform.

The replicability of the solution: Each set of {coordination platform + DER controllers + coordinated DERs} is replicable autonomously. It enables the building of several pools of reasonable size whose individual failure would not jeopardize the system stability.

It is reminded that the real-time processes i.e. the up and down modulation of the level of load -are performed by the DER controllers only, in a distributed manner. The coordination platform performs only periodic or event processes. As detailed above, this distribution of the real-time processes among the agents is a key factor of robustness of the solution. Neither the communication delay nor even a minutes-long loss of communication channel can stop the supply of these distributed frequency-controlled reserves, since the DER controllers interpret the shedding and reconnection order only from an on-site monitoring of the system frequency.

Adaptability to topology-dependent architecture for regulated operation

The reader is reminded that the efficiency of the UFLS scheme is capable of becoming particularly challenging in highly constrained power systems, such as in islanding grids (Section 2.4). In such a situation, Primary Support can be deployed locally at the scale of a primary substation or even at the scale of a secondary substation, in accordance with the normal scheme of operation of the distribution grid. Hence, it enables the deployment of a topology-dependent architecture, that would control in priority the DERs connected to MV feeders not involved in the UFLS scheme. Doing so, Primary Support and the UFLS would rely on a different pool of loads, without jeopardizing the UFLS activation.

Beyond its interest for the weak grid stability, the deployment of topology-related architecture is a way to reuse the utilities' components already deployed in the grids, such as the connected power meters and secondary substation RTUs. The technologies of smart meters2 embed already: a solid-state relay able to shed domestic thermal loads; frequency measurement ability with a 10mHz accuracy; a communication channel toward a data concentrator located in the secondary substation, such as Power Line Communication (PLC).

A simple update of the smart meters firmware would be enough to convert it into a distributed DER controller compliant with the layer 1 of Primary Support (see Section 3.3). The addition of a market clearing script into the secondary substation would then enable the distributed deployment of the layer 2 (see Section 3.4). Finally, an either peer-to-peer communication between secondary substations or a link with a DSO-operated bids trading platform would ensure the layer 3 (see Section 3.5).

Such architecture would be well adapted for a DSO or an integrated utility that would like to operate the service of FCR supply itself. Figure III.11 provides an illustration of such topologyrelated architecture, where the coordination platform is embedded in the substation's RTU. Correlated or not-correlated with the grid's topology: such adaptability of the architecture of deployment of Primary Support is assessed as a valuable opportunity for the System Operators.

DER modulation acceptance by DER owners

One significant hardship toward Smart Grid penetration relates to the willingness of DER owners to get their DER involved in the delivery of any power product that relies on a modulation of the level of load of the DER. The lack of familiarity of the DER owners with these uncommon products appears as a first reason of this difficulty. The second reason comes from the fear of the DER owners regarding the impact that the modulation of load could have on their businessas-usual process.

Thus, a set of frequency measurements has been gathered from the Continental Europe (CE) synchronous area, to assess the impact that an involvement of a given DER in the supply of FCR would have on its business-as-usual process, depending on the frequency threshold HzStr respected by the DER. While RTE [2015a] publishes open frequency measurement data from October 2014 with a 10-second sampling, complementary measurements have been performed over 40 days to get data with 1-second sampling and an accuracy of 10mHz. Having data available based on faster sampling is important to assess accurately the number of load modulation The 1-second frequency dataset has then been introduced in a model in order to characterize the impact that Primary Support would have on the DER depending on its threshold HzStr.

The model targets to assess the daily number of load modulation episodes -like a reversible ON/OFF switch manipulation -, the daily cumulative duration of load modulation, the maxium and finally the mean duration of each load modulation event. have been obtained using the statistical relation that links the average of a dataset, its standard deviation and its maximum value fulfilled by 95% of the data (equation III.12):

M ax HzStr = d HzStr + 1.96 × σ HzStr ;

(III.12) where d HzStr is the mean duration of the modulation events having a threshold HzStr σ HzStr is the standard deviation duration of these events M ax HzStr is the maximum duration of these events, fulfilled by 95% of the events

It can be noticed that the under-frequency events observed, last ≈ 20seconds while the overfrequency events are even shorter: ≈ 10seconds. 95% of these under-frequency events last less than 2minutes, and even less than 1minute for the over-frequency events. However, these statistics concern only the supply of FCR in normal operation, given no major outage occurred during These statistics conclude the present section by calling again for a compliant contribution of DER in the supply of FCR, preferably out of a given bandwidth center at 50Hz, width of ±50mHz or even only ±35mHz.

Conclusion of Chapter III

The present chapter has presented the developed Primary Support concept. Primary Support is a concept of coordinated modulation of DERs, capable of supplying both FCR and LFDD reserves, without inducing an undesirable interruption of the DERs' power supply. It has been designed to answer to the upcoming challenges of frequency stability that have been summarized in Chapter II.

Primary Support relies on a four-layers process, composed first of a multiplicity of DERs (layer 0) and of DER controllers (layer 1), at least one coordination platform (layer 2) and finally one trading platform to share reserves of flexibilities among different coordination platforms (layer 3). Such multi-layer architecture enables the splitting of the operations of DER modulation that occurs in real-time, from the operations of coordination of the behaviour of each DER that occurs ahead of real-time. Such coordination of the DERs enables the obtaining of an aggregated behaviour of the entire pool of DERs, that complies with the operational specifications of either the FCR or the LFDD. The constitution of the portfolio of aggregation can be performed by considering either market concerns or power system operation concerns. The DERs can thus be aggregated according to either their power retailer or their localisation in the grid topology.

To do so, the operations of coordination start by sending ( in Figure III.17) the level of In parallel, the DER owners of each DER firstly define the frequency range wherein they allow the modulation of their DERs. Secondly they set both the energy and capacity prices they want to be compensated for the involvement of their assets. The coordination platform determines ( ) then the frequency threshold and slope of modulation of each DER (Figure III.4 on page 97). Such a coordination relies on an algorithm which considers on the one side the parameters that characterize both the willingness and effectiveness of contribution of each DER, and on the other side the resultant FCR and LFDD demands that have to be supplied by the pool of DERs. The operations of coordination end by sending ( ) the operational frequency threshold and slope of each DER to each DER controller.

The real-time operations are then driven autonomously and independently of one another by each DER controller. To do so, each DER controller monitors on-site the system frequency and modulates the level of load or of generation of the DERs it controls according to the predetermined power-frequency slope of modulation, starting from the predetermined frequency threshold ( ) . Moreover, the characterization of the process of modulation of the level of loads of each DER relies on the standard Frequency-Watt mode (FWHZ) logical node, defined by the IEC 61850-7-420 [2015] in order to guarantee the interoperability of the DER and maximize the opportunity of supply of several services based on the same DER.

The statistics of frequency deviation that have been performed, enable the possibility of involvement of a wide diversity of DERs such as domestic heaters and tap boilers, HVAC systems for tertiary building, pumping applications, Uninterrupted Power Supply (UPS), Elec-tric Vehicles (EVs) or even public lighting facilities. The willingness of the DER processes to get interrupted would then determine their frequency range of modulation, considering that two main bandwidths of frequency operation can be differentiated, split one another by a ±50mHz limit. On the one side, the involvement of a DER for FCR delivery in a range [49.95;49.98Hz] ∩ [50.02; 50.05Hz] would significantly impact the business-as-usual process of the DERs, with modulation from 20min up to 5hr per day. It would thus be adapted only for the DER that can dispose of large buffer such as tap boilers or EVs charging. On the contrary the involvement of a DER for either LFDD or FCR delivery based on a threshold lower than < 49.95Hz or greater than > 50.05Hz would induce a modulation of the level of load during less than 6min per day. Such a frequency range of operation would be adapted to UPS or public lighting facilities.

The next arguments toward a wide adoption of Primary Support by Smart Grid actors will come from the outcomes of the demonstrations which have been performed in the framework of the present PhD work. These outcomes are presented in Chapter IV.

Field Test

Figure IV.1 presents the architecture of the field test used to emulate a micro-grid. On the power supply side, the micro-grid relies on a 4kVA synchronous machine, operated as an alternator. This demo synchronous machine, behaves at a reduced scale as a typical conventional thermal unit connected to the French power system [EDF, 1986]. The machine is not equipped with an excitation control. On the demand side, five resistive loads are connected to the grid and are controlled by the energy boxes. Figure IV.2 presents the energy boxes used (layer 1). They have been specifically developed for the demonstration purposes, in order to embed a sub-layer of real-time control of the solid-state relay, hosted by an Arduino [START_REF] Uno | Arduino & genuino products : Arduino uno & genuino uno[END_REF]

Protocol of tests

The demonstration aimed to prove the ability of the agent-based distributed platform to provide a support to the grid with the same accuracy as a bulk generation unit can do. The use of a reduced scale power system fed by one generator has however imposed an adaptation of the protocol of tests. Indeed, it has not been possible to reproduce a blackout on the micro grid, given that the machine always remains able to stabilize the frequency at a lower value, regardless of the amount of load suddenly connected to the grid in a limit of the nominal capacity of 4kVA of the machine.

Three kinds of tests have consequently been performed. The first ones aimed simply at showing the agent-based platform's ability to regulate the micro grid's frequency in steady-state situations. The second ones aimed at testing the energy boxes' time response when faced with a sudden frequency drop, while the third ones aimed at validating the respect of the droop line predefined. The results of these three sets of tests are presented from Sections 1.1.3 to 1.1.5.

Illustration of frequency stabilization in steady-state operation

The validation of the concept in steady state operation was not planned initially, for two reasons. Firstly, the electric wave provided by the 4kVA generator can vary naturally by ±80mHz due to the machine's imperfections and the lack of inertia of the micro grid. Secondly, the natural slope of the micro grid's droop curve is comprised in a range of [1; 2mHz/W ] [START_REF] Kuypers | Development of a multi-agent system for primary frequency control[END_REF]. This natural deviation is due to the absence of closed-loop excitation control on the machine. It induces voltage drops while the micro-grid is loaded and so a damping of the load consumption. Thus the impact of a 25W load-shedding on the grid frequency cannot be really analysed and used to assess the platform robustness. It has finally been decided to perform some tests with a reduced droop curve of 1.35mHz/W. The evolution over the time of both the system frequency and the consumption level of the dispatchable loads curves are presented in Figure IV.3, as well as the evolution of the frequency deviations dispersion with or without regulation. The figures show the energy boxes' relays act fast enough to reduce the bandwidth of natural frequency deviations, hence benefiting to the system stability. Indeed, the dispersion of the frequency is reduced when the regulation is activated (red curves in Figure IV.3). The results illustrate that the energy boxes effectively handle the frequency droop faster than the natural system behaviour. First, the frequency drop's depth ∆F d is reduced by 20% with the frequency regulation, while the rebound ∆R d remains at the same magnitude. Then, the mean delay ∆T d of occurrence of the frequency Nadir lasts from 1046ms to 872ms, i.e. is reduced by 17%. Both observations prove that the DER controllers act fast enough even on such lowinertia system. Finally it validates the added-value that the controls of dispatchable DERs through ON/OFF relays may have for the system stability, compared to the control of variable speed loads. The response time of ON/OFF relays is much shorter than for variable speed loads (see Section 1.3.3).

Validation of the droop curve conformity

The conformity towards the expected droop curve has been assessed by modifying slowly the micro grid frequency, by acting on the synchronous machine speed. Eight cycles of frequency decreasing and rising have been performed over 12min. This proportion of 15.8% of out of bounds values can be considered as an acceptable rate. Moreover, none of these out of bounds values have been engendered by the periodic updates of the frequency thresholds, which have been performed by the coordination agent every 60 seconds during these tests. These deviations could be explained first by the high steady-state instability of the micro-grid (Figure IV.3). The presence of reactive power on the phases to which the dispatchable loads have been connected may also damage part of the frequency measurement performed due to proof-of-concept equipment. Finally, six different lab-made frequency measurement devices have been used in the demonstration, based on Arduino Uno devices. Their quality and the absence of time synchronisation of the different devices that have been used for load driving and for monitoring the system reaction may explain as well part of the deviation. However, all of these assumptions regarding the origin of measurement problems do not explain why errors of more than 50mHz have been monitored. No explanation of these large deviations have been identified yet.

ON/OFF DER's response on a interconnected system

The second physical validation of Primary Support aimed to assess the behaviour of an industrial ON/OFF DER controller, on an interconnected power system. The response of a pool of DER controller has been assessed using a Power Hardware In the Pool (PHIL) test bench. The outcomes are presented below, following the description of the field test and of the protocol of tests. describes the architecture of this test bench. It is composed of an RT-lab c digital real-time simulator that drives a power amplifier. Then, analog devices such as scale-1 DERs can be connected to the power amplifier. The real-time simulator enables to simulate any kind of scenarios by loading Simulink c files. The power amplifier is then able to play physically each of these scenarios. Current sensors are finally associated to the power amplifier to provide a feedback to the real-time simulator of the effective current consumptions of the analog devices that have been connected to the power amplifier. Thanks to this architecture, the power system that is simulated is impacted by the real-time behaviour of the analog devices. Last but not least, a current coefficient can be applied on the current measurements. This enables to modify the scale of simulations. According to such logic, the PHIL can either execute a specific event or reproduce power system architectures of any size, from micro-grids up to large-scale interconnected grids.

This test bench has been firstly used to test and validate the behaviour of ON/OFF DER controllers, that have been built using industrial power components provided by Schneider Electric. Figure IV.7 displays the architecture of these ON/OFF DER controllers. Figure IV.8 presents one of the three ON/OFF demonstration suitcases that has been built by Schneider Electric for the needs of demonstration. Out of the power protection components, the cubicle is composed of three main kinds of components: one sub-power meter, one Power Logic Controller (PLC) and two or three steady-states relays -depending on the suitcase version -that turn the loads ON or OFF independently one another. For the specific needs of the coordination between the layers 1 and 2 of Primary Support, an ICT gateway has been added and hosted in a Raspberry PI (RPI). The PLC communicates with the power meter and the ICT gateway using a Modbus RTU protocol. The PLC is the unique master device, the others are Modbus slaves. The steady-state relays are driven by a 0/5V analog signal that comes from the PLC. The power meter provides to the PLC the informations of power consumption of each of the loads, as well Figure IV.7: Architecture of the ON/OFF demo kit to the deployed within Schneider Electric show-room as the power system frequency. The set of {M inW out; T otW ; M axW out} and {HzStr; W gra} parameters are exchanged between the DER controller and the coordination platform through the ICT gateway.

Protocol of tests

The test implemented on these industrial ON/OFF DER controllers aimed essentially to assess the time response of controllers. Indeed, the introduction of communications between the components of frequency monitoring and load driving is a source of response delay. This delay had to be evaluated and compared with the results that have been obtained using the all-in-one energy boxes (Section 1.1).

The mean time-response of the suitcases has been assessed by connecting the three independent suitcases to the power amplifier. On the whole, eight loads where connected and controlled by three independent PLC. The power amplifier played a scenario of sudden frequency variations of ±1Hz with a period 40s. 26 events of sudden frequency drop and 26 events of sudden frequency recovery were played the one after the other. The frequency evolved between 49.05Hz and 50.05Hz. Each of the eight loads had nearly the same power consumption. They were coordinated to provide an aggregated linear power-frequency characteristic between 49.8Hz and 49.98Hz. Given the frequency step magnitude of ±1Hz, it was expected that the eight loads were disconnected and reconnected simultaneously. Seven of the eight loads were resistive loads. The eighth load is a fan. The behaviour of the suitcases during these events is presented in next Section 1.2.3.

Validation of ON/OFF DERs time-response

Figure IV.9 presents the evolution of the overall power consumption of the test bench depending on the system frequency prior and after each of the 26 events of frequency drop. Three main levels of power consumption can be observed in Figures IV.9 and IV.10. Each of these levels correspond to the simultaneous disconnection of all of the two or three loads that are controlled by the same PLC. Given that two suitcases control three loads while the third suitcase controls only two loads, the power consumption of one of the three suitcase is lower. Hence, depending on the chronology of disconnection of the three suitcases, the power consumption of each of the main three main level observed, can differ.

Nonetheless, the main conclusions of these test remains the same despite of these slight variations of power consumption:

The delay of disconnection of 100% of the loads is close to 5s with the present suitcase architecture. Despite 5s is a value that complies with the European Grid codes -except for the FCDM power product in GB synchronous area - Figure IV.11: On-site generic architecture of an HVAC system and picture of the equivalent system built within PREDIS platform

Variable-speed DER's response on a interconnected system

The third physical validation of Primary Support aimed to assess the behaviour of an industrial rotating machine, on an interconnected power system. The outcomes of the demonstration are presented following the same logic as in the previous section: the field test is described first, ahead of the description of the protocol of tests. The section ends with the validation of both the time-response and the droop conformity of the variable speed drive controller.

Field Test

This set of tests has been performed again on Grenoble INP's PREDIS platform. A specific industrial cubicle has been built for this purpose, using components provided by Schneider Electric. This cubicle aims to reproduce an architecture of control-command of one or several conventional variable speed loads that can be found in the industry, such as a compressor of an HVAC system or a pump. Figure IV.11 displays the generic architecture of an HVAC system usually deployed in tertiary buildings. This architecture has been used as a reference for the design of the final cubicle, whose picture is displayed as well in Figure IV.11.

Out of the power protection components, the cubicle is composed of three main kinds of components: one sub-power meter, one Power Logic Controller (PLC) and at least one variable speed drive. The cubicle can be composed of as many variable speed drives as the number of variable speed loads to be controlled independently one-another. The variable speed drives supply the flexible loads at a local frequency that depends on the drives' set-points. For the specific needs of the coordination between the layers 1 and 2 of Primary Support, an ICT gateway has been added and hosted in a Raspberry PI (RPI). The four components, including the gateway communicate on-site by Modbus. The PLC is the unique master device, the others are Modbus slaves. In the generic architecture, the power meter aims to provide sub-metering data of the entire HVAC process. The variable speed drives control the rotational speed of both the HVAC compressors and fans to optimize the thermal flow according to concerns of high power efficiency. The PLC defines finally the set points f drive of the variable speed drives, according to a set of temperature, air quality or presence sensors spread among the building. f drive is the frequency of the electrical wave generated by the variable speed drives to feed the loads they control. The information of power consumption of the drive T otW is provided by the drive in answer to a Modbus request of the PLC.

For the purpose of Primary Support, the PLC operates as well the FWHZ function. It is reminded that FWHZ [IEC 61850-7-420, 2015] characterizes the local power-frequency characteristic i.e. it characterizes how does the modulation of the level of load occur depending on the variation of the system frequency. The modulation of the level of load -i.e. the modification of f drive -which is imposed by FWHZ, has the priority on the business-as-usual process of thermal flow optimization. The information of system frequency is provided on-site by the power meter, while the {HzStr; W gra} parameters of the DER controller's power-frequency characteristic are transmitted from the coordination platform to the DER controller through the ICT gateway. The flows of data requested by the PLC to operate FWHZ are presented in red in Figure IV.11 along the communication bus. The ICT gateway is hosted by a RPI -i.e. a computerwhich uses an RS485/USB converter to perform a Modbus-RTU/webservice-TCP conversion on a Python script.

Physically, the modulation of load is controlled by a variation of the frequency f drive at the side of the variable speed and not by a direct control of the power consumption T otW . The task of determination of the correlation T otW = f ct(f drive ) belongs to the script embedded into the PLC.

In PREDIS, the cubicle drives a 4kW asynchronous machine that behaves like an HVAC compressor or a pump. The mechanical torque to be supplied by the asynchronous machine is passed by the connection of a DC machine to the shaft of the asynchronous machine. The DC machine itself is the source of supply of a DC sub-grid, to which are connected resistive loads. The mechanical torque -and so the power consumption of the variable speed drive -depends on the amount of resistive loads connected. This process of power conversion deployed for the need of the demonstration is displayed in Figure IV.12. The correlation between the power consumption of the loads T otW and the drive's frequency f drive corresponds to a polynomial function of order 2. This correlation is demonstrated by the successive equations IV.1 to IV.5, that use the parameters of Figure IV.12: By simplifying the input equations thanks to the assumptions:

         T otW = U 2 e R load + δP U e = E mcc -U Ld -U r E mcc = k × φ × Ω (IV.1)
δP ≈ 0 U r = R mcc × I mcc ≈ 0 U Ld = Ld × dI mcc dt = 0 in steady-state operation
It leads to the equation IV.2:

   T otW = U 2 e R load U e = k × φ × Ω (IV.2)
i.e. :

T otW = (k × φ × Ω) 2 R load (IV.3) T otW = (k × φ × ( 2π p × f drive )) 2 R load (IV.4) T otW = 2π × k × φ p × √ R load 2 × f 2 drive (IV.5)

Protocol of tests

The tests implemented on the HVAC cubicle aimed to assess the response of the 4kVA asynchronous machine to frequency deviation disturbances. Achieving these tests requires the reproduction of the scenario of frequency drop that would not occur by the simple connection of the cubicle to the power system of Continental Europe, due to the extremely low probability of occurrence of these events. Based on this assessment, there are two ways left to simulate such disturbances : either connect the cubicle to a real-time simulator, with a frequency moving in real time according to predefined set of data as it has been presented in Section 1.2; or replace the cubicle's power meter by a second RPI that returns the given set of frequency data in response to the Modbus initiated from the PLC.

The method chosen and presently presented is the second one that emulates the power meter. It has been chosen for its easiness of deployment, which does not require a modification of the grid point of connection of the cubicle in PREDIS. In this method, the RPI is in charge of the monitoring of the power-response of the HVAC unit faced with the variation of frequency. The

Validation of the HVAC cubicle time-response

As presented in Section 1.3.2, each of the Hz and T otW data of the points {Hz, T otW } have been saved with the same time-stamp. However, the response of the HVAC unit to a given variation of frequency can be observed at the RPI side, only after the effective variation of the level of load of the HVAC unit, as presented in Figure IV.15. The RPI faces therefore a delay ∆T which is the sum of three sub-delays: a first ICT delay ∆T ICT 1 due to the emulation and monitoring of the scenario ; a second ICT delay ∆T ICT 2 due to the control of the variable speed drive following a request for frequency surveillance and a third physical delay ∆T P ower induced by the power process of modulation of the load.

In the context of FCR supply, the commitment of a given FCR supplying unit is to get a cumulative delay from the real time occurrence of the frequency deviation (Start icon ), up to On the one side, such a total delay is compliant with the supply of FCR. The effective delay is even shorter given that ∆T includes two Modbus messages that are out of the committed path from the start to stop icons. Moreover the Python script operated by the RPI is much less optimized and slower than the script that runs a power-meter. Figures IV.13 On the other side, the present operational process of variable speed load modulation coordinated by a PLC using Modbus link is finally not an instantaneous process, and must be considered as such. The RPI received for instance a frequency request only once every 2 seconds and it has not been managed to reduce this time interval in operation.

Validation of the droop curve conformity

The set of {Hz, T otW } points saved by the RPI have then been exploited to assess the conformity of the power-frequency droop of the HVAC demonstration unit with a contractual droop W gra.

The operational droop has been assessed after having removed the time offset that occurred during the monitoring of each Hz and T otW point. On the script-side, the droop has been implemented as a linear function of the rotational speed, thus neglecting the theoretical second order of the relation T otW = f ct(f drive ). On the monthly event (b), the limit of modulation of the droop has been defined as in equation IV.6:

   f drive = 1500rpm ≡ F ≥ 49.98Hz f drive = 600rpm ≡ F ≤ 49.8Hz (IV.6)
It leads to the supply of a power-frequency droop of 914W/Hz i.e. 22.9

%M axW out Hz on the variable speed drive of 4kW (M axW out = 4kW ), with a good coefficient of regression (0.94). Figure IV.16 (b) clearly dissociates the two different behaviours of the HVAC: the upper range of non-modulation and the range of power modulation. However the third behaviour i.e. the inferior range of non-modulation has not been observed due to too-contained frequency deviation.

On the decade-event (a), a droop of the same nature as for the monthly-event (b) has been implemented but on a wider range of frequency, limited by the conditions of equation IV.7:

   f drive = 1500rpm ≡ F ≥ 49.98Hz f drive = 600rpm ≡ F ≤ 48Hz (IV.7)
It leads to the supply of a power-frequency droop of 94W/Hz i.e. 2.3

%M axW out Hz

on the variable speed drive of 4kW (M axW out = 4kW ), with an even better coefficient of regression (0.98). During this outage simulation, only the two behaviours of the HVAC associated with the range of power modulation and inferior range of non-modulation, can be observed in Figure IV.16 (b), due to a lack of frequency data historic available before the occurrence of the outage.

Figure IV.16 (a) displays in green a droop trend characterized as a polynomial function of order 2. It can be noticed that such an approximation improves the coefficient of determination R 2 of the approached droop, as it was expected considering the theoretical order of the correlation T otW = f ct(f drive ). Such improvement of the coefficient is however of less than 1% and it can be assessed that the linear approximation is sufficient for the present process.

In the present case, the linearisation of the non-linear correlation went well which is a good outcome for Primary Support. It does not guarantee however that it will remain true in any process. It highlights as such a potential challenge for any industrial deployment of Primary Support on variable speed drivers. Despite the fact that the link with the coordination platform which has been standardized thanks to the use of FWHZ, the characterisation of the transfer function that links the slope W gra with the parameter of control of the drive f drive will have to be tested & validated individually for each process.

Deployment of pre-industrial coordination platform (Layer 2)

The coordination of the individual behaviour of each DER is one of the two main innovations claimed by Primary Support, with the distribution of the decision of load modulation. The validation of the philosophy of coordination put forward during the conception of Primary Support (see Ch III Section 3.4), went through the development of such a kind of coordination platform that uses software and telecommunication tools that comply with the requirements of industry. The first commitment of this step of development was to deploy the telecommunication infrastructure that enables the exchange of data between the DER controllers (layer 1) and the coordination platform (layer 2). The second commitment was to host the algorithm of market clearing that has been presented in Section 3.4.3, within the coordination platform and operate it to effectively test the coordination of the DER.

Architecture of the coordination platform of demonstration

Figure IV.17 presents the entire architecture of the coordination platform developed for the purpose of the testing and validation. Four main tools are implemented beside the central market and operation database, that stores all of the 24 parameters per offer or demand bid that are required to operate Primary Support (see Section 3.4.1). These four tools provide either functions of telecommunication (Telecom interface), computation (Market clearing and Clearing visualisation algorithm) or Human Machine Interface (HMI).

The HMI is composed of three main components. The first one aims to declare FCR or UFLS demand bids (see synoptic's details in A set of arrows have been drawn between the different components of architecture that are represented in Figure IV.17. These arrows represent flows of data that occur between the different components of the platform. The arrows are plotted in four different colors depending on the nature of the event that induces their exchange:

The grey arrows represents the flow of data induced by the HMI. Such flows could first occur on-event, following a modification of the behaviour of a DER by its owner. Otherwise such flows occur following the modification/creation/suppression of a FCR or UFLS demand bid by a customer. Both these kinds of flows are presented by the grey arrows plotted on the right upper corner of Figure IV.17. On the other side, the continuous visualisation of the resultant offer and demand curves induces the download from the database of the data that are required for the building of these resultant curves by the algorithm of clearing visualisation. In the demo testing, such downloads occur every two or ten seconds. In scale-1 operation, such an interval could be adapted to an effective need to be determined with the saving of the clearing outcomes and the emission of the message of behaviour update at the destination of the reachable DERs that belong to the portfolio of aggregation. The reachable DERs are all the DERs connected by an XMPP channel and the DERs that are controlled by the DER controller which had emitted the HTTPS message handled by the coordination platform. Figure IV.17 does not currently present accurately the green and red flows of data that would occur following the handling of an XMPP message. In such a case, neither green nor red communication would occur with the HTTPS plug-in. Instead, the two green arrows that used to be received and emitted by the HTTPS plug-in would be linked with the XMPP plug-in.

The red dotted arrow represent the flow of data that enables finally the provision of the real-time value of system frequency to the visual interface of clearing output. Such real-time value is updated each time a message of a DER controller has been handled;

The messages that are exchanged through both HTTPS and XMPP plug-ins are written in a JSON semantics. However, the conditioning of the keys and data does not comply with the standard defined by IEC 61850 -8-2 [2016], that claims for the use of an XML conditioning

{ ′ LogicalN ode ′ : ′ G2ELAB_C_3 ′ , ′ DRAT 1$SP $M axW out$setM ag.i ′ : 1000.0, ′ DRAT 1$SP $M inW out$setM ag.i ′ : 0.0, ′ M M XU $M X$T otW $mag.i ′ : 910.0, ′ M M XU $M X$T otW $t ′ : 1448971039, ′ M M XU $M X$Hz$mag.f ′ : 49.1 }
Answer to the request by the coordination platform { "LogicalN ame" : "G2ELAB_C_3", "F W HZ1$SP $HzStr$setM ag.f " : "49.18", "F W HZ1$SP $HzStop$setM ag.f " : "0.0", "F W HZ1$SP $W gra$setM ag.f " : "10000.0", "F W HZ1$SP $HzStopW gra$setM ag.f " : "0.0" } instead of JSON. Such a choice has been taken for easiness of deployment and compliance with the different field tests of Dream [2013]. However the keys' names that have been used remain in compliance with the standard names defined by IEC 61850-7-420 [2015] ed.2 (Figure III.6 and Table III.2). Table IV.1 presents the effective call and reply JSON semantics that are used between the DER controller and the coordination platform. The clearing is performed such as the resulting offer is at least equal to the aggregated demand. Thus the values of the green resulting offer curve are supposed to be larger than the value of the blue demand curve;

HMI of visualisation of the resultant offer and demand power-frequency characteristics

Both green and blue curves can unfortunately cross each-other in the case of a lack of offers to meet the resulting demand;

The linear demand to be supplied in the interval [48.5Hz;50Hz] is supplied thanks to the contributions of DERs that are modulated either in slope or ON/OFF mode. The resulting offer curve looks like a stair whose limits between two steps do not have the same downgrade. Such

Schneider Electric -Grenoble

One ON/OFF load controller that has been deployed in the innovation show-room of Schneider Electric. This is one of the three easy to move demo-kit suitcases that have been developed by Schneider Electric for the demonstration needs of Dream. The suitcase and its architecture have already been presented in Section 1.2 (Figures IV.7 and IV.8).

G2Elab -Grenoble

The field test of G2Elab is composed of two sets of DERs : a set of loads connected to a Power Hardware In the Loop (PHIL) test bench, presented in Section 1.2 and the HVAC emulation unit, presented in Section 1.3.

In the present scale-1 demonstration, the HVAC emulation unit was coordinated by the remote coordination platform located in Lyon, and the cubicle got its power meter reconnected to the PLC -that was not the case during the tests presented Section 1.3. The set of loads connected to the PHIL test bench are a mix of two kinds of physical loads and one kind of virtual loads, that are all ON/OFF-controlled. The first kind of physical loads as well as the virtual loads have the same architecture as the energy boxes presented in Section 1.1. Up to three three-phases or nine single-phase resistive loads can be physically connected on the test bench and directly driven by the RT-lab c digital real-time simulator, depending on the system frequency that is computed in real-time by the Simulink c script. The coordination of these set of loads is enabled by a Java Virtual Machine (JVM), that is interfaced with RT-lab c . It enables the coordination

ICCS -Athens

The third ON/OFF load controller, developed by Schneider Electric (Section 1.2) has been deployed during a short period among ICCS facilities, for perspective of vulgarisation as it has been done within Schneider Electric innovation show-room.

SEA -Milano Malpensa

SEA is willing to involve a wide range of lighting loads on Milano Malpensa Airport in the operational process of Primary Support. As presented in Figure IV.20, the modulation of the level of loads would have been performed by a modulation of the voltage level that feeds the lighting sources involved. The lighting loads concerned are first LED lamps that light streets and car parks. The second kind of lighting loads are apron lighting towers that light other car parks and aircraft facilities on both the cargo city area and satellite A of the main terminal. Figures IV.21 & IV.22 displays the map of the lighting facilities able to be controlled.

"SEA is interested in Primary Support to replace the gas and steam turbine operated by SEA Energia in the supplying of primary frequency regulation required by the Italian TSO. We aim to avoid thermal and mechanic stress on the turbines, prolonging so their life-time." SEA Environment team. The works of demonstration performed to test and validate the efficiency and the robustness of Primary Support led to the development of a pre-industrial coordination platform able to coordinate the behaviour of a pool of DERs. The coordination platform is hosted by a cloud server physically located in Lyon. Three different DER controllers, located in two different locations in Grenoble, have been connected to the coordination platform. These controllers drive either variable speed loads or resistive loads controlled in ON/OFF mode. Unfortunately, the connection to the platform of the industrial lighting loads of Milano Malpensa airport have not been performed by the end of this PhD work, due to an issue of grid connection agreement with the airport authorities.

The tests of operation of the real-time process have shown an accurate fulfilling of the powerfrequency characteristic for the different cubicles deployed. These tests have then highlighted a variability of the delays of modulation of the level of load from less than 1 second to more than 5 seconds, depending on the architecture of the cubicles. The faster response time has been obtained by the ON/OFF load, tripped by a relay controlled by the DER controller through a serial bus. The slower response time has then been obtained by the variable speed load controlled through Modbus set-points, where the electro-mechanical delays have been added to the delay of connectivity. All of the cubicles enabled nonetheless a modulation in less than 10 seconds that validates the commitment of Full Activation Time of the FCR in Europe.

In terms of connectivity, the communication between the coordination platform and the DER controllers has been achieved through an either XMPP or HTTPS communication channel. On the one side, the use of HTTPS makes the connectivity of the DER easier by not requiring the opening of the port 5222 for out-stream flows of data ; on the other side, it induces an additional computational complexity for the algorithm in charge of the coordination of the slope and threshold of each DER of the pool. Indeed, the use of an HTTPS webservice does not allow the sending of data to the DER controllers at the initiative of the coordination agent. Consequently for each computation, the algorithm is able to update the behaviour of all of the XMPP-connected DER controllers. But meantime it can only update the behaviour of one unique HTTPS-connected DER controller: the latest one which had been in contact with the coordination platform. XMPP -which is promoted by the IEC 61850 -8-2 [2016] -should thus be used by preference each time it does not require a too complicated process of opening of the port 5222.

Ahead the generalisation of XMPP, robustness studies should consequently be performed to assess how does the penetration rate of XMPP connectivity at the expense of HTTPS, improve the accuracy of the resultant offer power-frequency characteristic compared with the targeted demand characteristic. Moreover the impact of the load variability over the time of the DERs that compose the pool of aggregation would have to be assessed as well. It is effectively expected that a portfolio of DERs whose available flexibility varies a lot over the time would increase the number of required algorithm computation per interval of time, inducing additional computation complexity. The risk of obtaining a resultant power-frequency characteristic out of a pre-determined implementation range, should be assessed accurately. However such scenario was not carried out at the end of this PhD.

General Conclusion

General Conclusion

Twenty four years after Rio92, six years after COP15 in Copenhagen and several months after COP21 in Paris, the international community duly notes the need for a new energy paradigm. Such an energy transition would induce the migration from an energy mix driven by conventional bulk generation assets to a new paradigm relying on partly distributed RES-E assets. As a direct consequence, the amount of conventional capacities naturally available would decrease, while the constraints on the distribution networks would rise.

The principle of aggregation of Distributed Energy Resources (DERs) emerged in previous years, with the objective to propose new solutions to handle such issues. The DER aggregation enables the coordination of the behaviour of each of the DER controlled. In doing so, it becomes possible to reproduce the behaviour of a bulk generation asset. Hence, these technologies of aggregation of DERs are commonly called Virtual Power Plants (VPP).

Review of business opportunities of DER flexibility operation

In such a context, the first drive of this PhD work has been the identification and the promotion of the technologies of VPPs, likely to contribute positively to this new paradigm. Performed thanks to the sponsorship from the manufacturer Schneider Electric, this industrial PhD targets then the development of solutions that remain easy to deploy in compliance with the existing market and power operation rules. Moreover, these technologies would likely be profitable without the support from public policies. Such a choice is motivated by the wish not to see the business model of VPPs being jeopardized by the modification over time of such public policies as it occurred for photovoltaic energy in France in 2011.

The review of business opportunities of VPP is commenced with an analysis of both the elasticity and volatility of the day-ahead spot markets (Figures A.1 and A.2 on page 166). This analysis relies on the elaboration of a methodology of data mining and analytics of three million dayahead spot market data points. The data of all the bidding areas of the Nordics, the Baltics and of France have been computed from 2001 to 2014. One premier objective was to assess the opportunity of supplying peak load reserve based on DER load-shifting, being remunerated by the spot market. Indeed, the peak load adequacy is directly challenged by the phasing-out of bulk generation units due to either a lack of competitiveness or the introduction from 2016 of the European directive n • 2010/75/U E on pollutant assets phasing-out. Hence, the contribution of DER flexibility to the peak load adequacy appeared as interesting. Moreover the choice of being remunerated by the spot market only reduces the exposition to public policies. A second objective of such an analysis was to identify the period of the year and the time of day where DER load-shifting would be the most profitable and beneficial for the power system. The business model studied relies on the operation of intra-day load-shifting, that enables the purchase of energy during the cheapest hours of the day and their resale during the most expensive hours of the day, benefiting from the prices' spread.

Unfortunately, the analytics have highlighted that an involvement of DER flexibility for the supply of load-shifting only during the days of peak loads would not constitute a sufficient source of revenue. The revenues from load-shifting can be expected from the day-ahead spot market during the 10% of the time that has the largest network load, are not significantly larger than the potential revenues outside of the peak load. Hence, the peak load adequacy remains an opportunity of the capacity market and not of the energy market. The supply of peak load reserve is interesting only in the case of a complementary remuneration of the assets with a capacity price, associated with an exceptional activation request (some hours a year). In these conditions, it would constitute a profitable model for industrial assets.

In regards to the second objective of analysis, the volatility and elasticity of the spot prices remain contained. The generation of revenues on the day-ahead spot markets would require the involvement of DER flexibility assets that have a really contained marginal cost of load shifting (≈ 20e/MWh). Indeed, such a marginal cost would enable the operation of intra-day loadshifting all year long, hence increasing significantly the annual revenue. Finally, the profitability of DER flexibility on the spot market is largely dependent on the bidding area of involvement. If a decision of investment would have to be done on short term, focussing on wholesale market spread business, the bidding areas to address in order of priority would be France, Eastern Denmark and the Baltics. France would afford a mean revenue of 45ke/MW/year.

Based on these conclusions, the involvement of DER flexibilities on the day-ahead spot market could be envisaged as a source of preliminary revenue, prior to the involvement of these assets on the delivery of more advanced power products, such as frequency regulation services. A gross revenue of 10-30ke/MW/yr would be expected, nevertheless the final income remains largely dependent on the bidding area and potentially volatile depending on the year.

The review of business opportunities of VPP focussed then on the concerns of power system stability. Such stability is impacted by four concerns, capable of endangering the procurement of sufficient amount of fast-enough FCR. First of all, a lack of availability of conventional FCR and FRR resources would occur. Such a lack would be induced by either a deficit of competitiveness of the FCR markets for these assets compared to the revenue they could earn on the wholesale markets, or the periodic non-availability of bulk generation assets in periods of negative residual loads. The second concern addresses the degradation of frequency quality induced by the discontinuity of the units commitment around the clock from one bidding hour to the other, while the demand is continuous. Such a degradation becomes a risk for the system stability while it constitutes an additional obstacle to the involvement of FCR suppliers, that would fear a larger solicitation and an over-ageing of their assets. FRR assets would be concerned to a lesser extent. The third concern addresses the degradation of system inertia, that is engendered by both the penetration of power electronics interfaces in newest RES-E technologies and the phasing-out of bulk generation assets. Finally, the large scale development of Distributed Generation downstream the primary substations is likely to alter the effective activation of LFDD's relays, degrading as such the efficiency of the LFDD at the power system scale.

Faced with such a list of concerns, the question of the maintaining of the power system stability has been considered as central during the PhD work. The challenge of FCR supply involving DER flexibility appears achievable, using an innovative methodology of DER coordination. The remuneration of the FCR would be adequate depending on the process of FCR supply selected. Last but not least, such a contribution is likely to contribute to a rising need of the System Operators. Hence a specific process of coordinated modulation of DERs, named Primary Support has been developed.

Specifications of Primary Support

A pragmatic approach of development has been adopted driven by cost-oriented drivers. The first driver of Primary Support targets the use of the same DER asset for the supply of several wholesale and ancillary services in parallel or sequentially, considering especially the supply of both FCR and LFDD reserves. The sharing of the same asset for the supply of several services enables the multiplication of the sources of revenues, and therefore the chance of setting-up a profitable business model. In addition, in doing so, the critical size of a DER required to payback the DER integration cost would be significantly reduced. The monitoring of the frequency of the Continental Europe synchronous area has been performed over 40 days with 1-second sampling and an accuracy of measurement of 10mHz. It shows that the supply of FCR in 80% of the contractual range of delivery would induce less than 20 minutes of load modulation per day. Hence, a given DER would be able to perform a baseline operation of intra-day load-shifting to benefit of the spot price spread. In parallel, the DER could supply FCR all the day round, in proportion with its hourly consumption, without impeding the baseline process of intra-day load-shifting. Such a case illustrates the complementarity that can be found in the delivery of power products.

However the coordination of delivery of several power products could induce complexities of operation depending on both the nature of each product and the buyer of the DER flexibility. Faced with such an issue, an interesting proposition has been promoted within the European project EvolvDSO, to rely on the use of standard business use cases that structured the call of DER flexibility at the benefit of either the producers, the TSOs, the DSOs or the retailers. This PhD work has contributed to the final redaction and validation of the EvolvDSO business use cases that structure the DER integration in the distribution grids (Figure A.3 on page 167).

Beyond the standardization of the DER business use cases, the standardization of the operational functions and of the communication services of DERs is of great importance. It appears as a promising opportunity toward the inter-operability of DERs and power system components. It would ease the business of DER flexibility operation by first cost-killing the effort of integration of DERs. This is then an achievement of prior importance to enable the coordinated contribution of a given DER to several services, as previously claimed. Hence, the embedding of a native IEC61850 compliancy constituted a second major driver of Primary Support. It has to be noticed that standardization is becoming a significant concern of the utilities as well, despite it requiring a deep update of their present infrastructures of power system operation. Faced with such challenges, my thoughts go to Mr. Guise and Ulian for their -unattractive but of importance -contributions to the works of the IEC61850, at the benefit of the entire power system community.

The third driver toward the development of Primary Support targets the definition of operational specifications in compliance with the Network Code of ENTSO-E. The compliancy with such codes, likely to be adopted by the European TSOs enable the building of Primary Support on a robust framework. Of course, such network codes would not 100% comply with specific situations such as islanded grids. Nonetheless, the initial objectives and priorities of the PhD led to the decision not to assess in depth the capability of Primary Support to improve the stability of such specific grids, compared to the contribution of business-as-usual FCR suppliers.

With respect to the three drivers presented above, Primary Support has been designed as likely to supply both FCR and LFDD reserves, without inducing an undesirable interruption of the DERs' power supply (Figure A.6 on page 169). Primary Support relies on a multi-layer process, composed first of a multiplicity of DERs and of DER controllers, at least one coordination platform and possibly one trading platform to share reserves of flexibilities among different coordination platforms. Such an architecture enables the splitting of the operations of DERs modulation that occurs in real-time, from the operations of coordination of the behaviour of each DER that occurs ahead of real-time. In real-time, the modulation of the level of load of each DER is driven autonomously and independently of one another by each DER controller. The modulation depends on the system frequency measured on-site, in respect with a powerfrequency droop. The power-frequency droop is characterized by a standard pair of slope and frequency threshold, defined by the IEC 61850-7-420 [2015]. The use of the data model of the IEC 61850-7-420 [2015] guarantees the interoperability of the DER and maximizes the opportunity of supply of several services based on the same DER. The slope and frequency threshold are pre-determined ahead of the operational time by the coordination platform. The computation of the slope and threshold depends on the effective flexibility of the DER and the willingness of the DER owner to get its asset involved in the process of frequency regulation. Such a coordination of the DERs enables the obtaining of an aggregated behaviour of the entire pool of DERs, that complies with the operational specifications of either the FCR or the LFDD. The consideration in the period close to real-time of the effective flexibility of each DER as the input of the slope and threshold algorithm enables the guarantee of the effective delivery of the reserve. In opposition, most of the existing systems randomly assign a frequency threshold to a pool of interruptible loads, without monitoring their consumption among the day. Hence, they constitute frequency-controlled loads but their reserve is proportional to the load consumption of the pool of interruptible loads at the time of operation. As a result they behave as suppliers of a system of self-regulation of loads and as firm FCR suppliers.

In Primary Support, the constitution of the portfolio of aggregation can be performed by considering either market or power system operation concerns. Thus, each DER can be aggregated according to either its power retailer or its localisation on the grid. Primary Support is capable of involving a wide diversity of DERs such as domestic heaters and tap boilers, HVAC systems for tertiary buildings, pumping applications, Uninterrupted Power Supplies (UPS), Electric Vehicles (EVs) or even public lighting facilities. The willingness of a DER process to get interrupted would determine its frequency range of modulation, considering that two main bands of frequency operation can be differentiated. On the one side, the involvement of a DER for FCR delivery in a first range of [49.95;49.98Hz] ∩ [50.02; 50.05Hz] would significantly impact the business-as-usual process of the DER. In Continental Europe, the daily duration of modulation can last from 20min up to 5hr, depending on the threshold assigned. The involvement in such a range would be adapted only for the DERs that can dispose of large buffer like tap boilers or EVs charging. On the contrary the involvement of a DER for either LFDD or FCR delivery based on a threshold lower than < 49.95Hz or greater than > 50.05Hz would induce a modulation of the level of load during less than 6min per day. Such a frequency range of operation would thus be adapted to UPS or public lighting facilities.

The concept of Primary Support has been implemented and validated during this PhD work. A dedicated cloud-based coordination platform has been implemented. In parallel, specific cubicles have been built to test and validate different architectures of DER controllers. These cubicles control DERs in accordance with a behaviour that has been predetermined by the coordination platform, with respect to the operational principle of Primary Support. The cubicles' architectures that have been tested enable the control of DER in ON/OFF mode or in slope mode. It enables on the one side the control of electric heaters, tap boilers, UPS, EVs or LED lamps. On the other side, it enables the control of variable speed drives. The control of loads through voltage regulation applicable to public lighting infrastructure, constitutes a third kind of architecture that still has to be tested. All of the tests of deployment were successful. The entire architecture of both behaviour coordination and load control is presently in operation.

Future of Primary Support

The conclusions carried out during the prospective works of this PhD enable clarification of the business potential of DER flexibility. Later on, the test and validation works enable the confirmation of the operational possibility of coordinating the DERs relying on the Virtual Power Plant (VPP) architecture. The coordination of DER flexibility can be both profitable for the aggregator and beneficial for the System Operator. In addition, the architecture of advanced control that has been tested appears relevant.

Nonetheless, the market penetration of the solutions of distributed delivery of ancillary services would be faced with hardships. The first concern is that the ICT architectures selected would need to remain cyber-secure in all conditions, given the criticality of the delivery of some of these ancillary services such as the FCR. Hence, the improvement of the cyber-security of Primary

Data Processing

Successive steps of data sorting, filtering and computing have been performed to produce value analysis, based on the simple datasets of network load and price previously extracted. Table B.2 presents the eighteen types of data that have been built to perform the business value analysis of DER modulation. Each of these eighteen types of data are presented in Section 3, and illustrated on the [D2] gathers the day-ahead spot price of each bidding area. It corresponds to the "Elspot" product which in trade in Nord Pool Spot [2015] , and to "EPEXSPOT AUCTION" in Epex [START_REF] Spot | Market data day-ahead auction[END_REF].

Collection of data: 1 data/hour/year/series. 1 series/bidding area A device which includes a frequency measurement module, able to shed and restore the load if the frequency drops goes respectively under and over a predefined frequency threshold.

High

Close to MX2011010064 (review n°24). Potentially constraintfull, but not a real TSO connected device that is our value.

US6314378 (B1) -Distributed frequency relay Clc global llc [us]

A system based on distributed relays whose frequency thresholds can be remotely updated.

High

This patent is really emphasized on the programmable characteristic of the relays, to assign the frequency threshold, that is close to Primary Support scope. However, there is no aspect regarding on how these thresholds are calculated or coordinated. A system that finally allows a utility manager to control the production plan of an on-site energy storage (=not owned by the utility). The utility can choose to feed the customer with its own production unit or with the customer's energy storage system. The customer just send its consumption plan, and the utility seems to optimize for the interest of both actors the storage system usage.

Gen electric [us]

A smart plug placed between the wall plug and the household appliance. A plug with measurement capability, wireless communication protocol and a local memory to store thresholds. Then turn the load off depending on the constraint.

High

Quite close to some hardware systems we thought at for Primary Support. However the coordination is decentralized at the appliance size, down meter located, without ICT links with the DSO/TSO. 27 JP2011062075 (A) -Method and system for DR in power distribution network

Gen electric

A DRMS for DSO issues: select the loads located on the specific node where the load flow must be reduced. Try to mimize the load modification compared with the initial flow, to solve only the physical issues.

High

The system allows to select a node where to shed power and to optimize the combination of loads to shed. The optimization targets to minimize the cost and/or the total power shedded, without affecting any critical loads. The systems receive load shedding amount from the utility or the DSO. There is no notion of frequency neither voltage threshold.

The system includes a method to control the effective activation of the command, in order to potentially update the shedding plan quickly. Severals method to estimate the load shedding capacity are claimed in the patent request. Hardware modules are claimed as well for data transmission and shedding request.

28 KR20090126104 (A) -Method and system for DR of electric power

Snu r&db foundation [kr]

A DRMS designed for peak-shaving. Network Links between a power provider, a power consumer (demander) and a power market. Malheureusement, la ruée vers le gaz de schiste en Amérique du Nord a conduit a un surplus de charbon sur les marchés de matières premières et à un effondrement des cours du charbon y compris en Europe. Pendant ce temps et contre toute attente, le prix de la tonne de carbone sur le marché européen (ETS) s'est effondré. Faible coût de combustible et faible taxes environnementales: il n'en fallut pas moins pour redonner une seconde jeunesse au charbon, venant concurrencer de plein fouet les nouveaux moyens de production au gaz. En parallèle, des capacités significatives d'énergies renouvelables ont été raccordées au réseau européen, avec un tarif de rachat garanti et une priorité d'injection sur le réseau aux dépens des moyens de productions conventionnels (nucléaire, gaz, charbon, etc.). Cette conjoncture a directement impacté la rentabilité des centrales à gaz et mené les grands énergéticiens européens dans une crise majeure. En mars 2014, dix de ces plus importants énergéticiens se sont regroupés au sein du groupe Magritte, pour faire front commun devant Bruxelles. A l'offensive, Gérard Mestrallet, PDG d'Engie, appela à l'instauration d'un mécanisme de capacité pour soutenir la rentabilité des centrales à gaz, indispensables à la sureté du système électrique européen en période de pointe, concédant toutefois la nécessité de migrer vers un mix énergétique bas carbone.

La transition énergétique, partant d'un mix bâtit autour de centrales électriques conventionnelles de fortes puissances, vers des moyens de production renouvelables, partiellement distribués ne fait dès lors plus de doute. Un tel changement n'est toutefois pas neutre pour la sureté du système électrique et la conduite du réseau. A titre d'exemples, les capacités de production garanties sont amenées à diminuer, de manière concomitante à l'apparition de contraintes sur les réseaux électriques. Dans un tel contexte, le rôle du Smart Grid est d'apporter une réponse à ces problématiques en devenir, via le déploiement de nouveaux modèles d'affaires, reposant sur une libéralisation des marchés de l'énergie et le déploiement des Technologies de l'Information et de la Communication (TIC) au sein des composants du réseau électrique. Ce déploiement est attendu de la centrale électrique jusqu'aux charges électriques situées en aval du compteur électrique du client final, en passant par les infrastructures de transport et de distribution de l'électricité.

La stabilité du réseau électrique est amenée à être impactée par quatre sujets majeurs, à même de mettre en danger la livraison d'un volume suffisant de réserve primaire (appelée FCR) dans un temps suffisamment bref. Tout d'abord, la disponibilité des moyens de fourniture conventionnels de réserve primaire (FCR) et secondaire (FRR) pourrait faire défaut, impactée par la faible rentabilité que ces fournisseurs peuvent attendre de ces marchés de réserves, en comparaison des gains qu'ils peuvent espérer obtenir sur les marchés de gros. Par ailleurs, ces moyens de fourniture de réserve sont à même de rester arrêté et donc indisponible durant les périodes de charge résiduelle négative du système électrique. La perte de qualité de la fréquence du réseau constitue une seconde préoccupation. Cette dégradation est induite par la discontinuité des programmes de production des centrales électriques, qui est à même de varier brusquement d'une heure à l'autre selon les volumes vendus sur les marchés alors que la demande est continue dans le temps. Une telle dégradation devient un risque pour la stabilité du réseau, tout en constituant un obstacle supplémentaire à la participation des centrales électriques à la fourniture de réserve primaire, qui craignent dès lors une plus grande sollicitation et donc un vieillissement prématuré de leurs moyens de production. Les fournisseurs de réserve secondaire sont concernés également, mais dans une moindre mesure. La troisième préoccupation concerne la perte d'inertie du système électrique, qui est induite d'une part par l'ajout d'une interface d'électronique de puissance dans la chaine de conversion électromécanique des dernières technologies d'énergies renouvelables (photovoltaïque bien sûr mais également éolien), et d'autre part par la fermeture des moyens de production conventionnels. Finalement, la pénétration de GEDs sur les réseaux de distribution, en aval des postes sources est à même de réduire l'efficacité du plan de protection du système électrique -schéma UFLS-face à l'occurrence de creux de fréquence significatifs au-delà de 1 Hz. En effet, l'UFLS repose sur le délestage de départs entier au niveau du poste source, sur la base de la puissance estimée dans chaque départ, estimation qui historiquement ne prend pas en compte l'injection de puissance par des GEDs sur ces départs -En Europe, le déploiement à venir du nouveau schéma LFDD en lieu et place de l'UFLS devrait toutefois réduire ce risque - (Figure IV.6).

La sécurisation de la pointe électrique est quant à elle directement mise en danger par la fermeture de moyens de production centralisés, due d'une part à la perte de compétitivité de ces centrales précédemment évoquées mais aussi d'autre part à l'entrée en vigueur au Figure IV.6: Evolution des flux de puissances dans un réseau semi-insulaire avec un fort taux d'énergies renouvelables, altérant l'efficacité de l'UFLS [START_REF] Lebel | Distributed and coordinated demand response for frequency-controlled reserve supply[END_REF] d'approvisionnement, la pointe électrique est en mesure d'induire des pics de prix sur les marchés de gros, dont l'anticipation reste complexe.

Le déploiement de GEDs est ensuite à même d'induire des contraintes de conduite des réseaux pour les Gestionnaires de Réseaux de Distribution (GRDs), en modifiant les flux de puissance pour lesquels les réseaux ont été historiquement planifiés i.e. dimensionnés. Des excursions de tension sont attendues en particulier dans les réseaux Basse Tension (BT), sur lesquels se concentrent 80% des demandes de raccordement de GEDs, alors même que ces réseaux restent à ce jour largement dépourvus de tout système de contrôle-commande.

Dans le même temps, le déploiement de GEDs met au jour des conflits d'usage de la flexibilité qu'ils sont en mesure d'offrir à différents acteurs du système électrique. Alors que les aggrégateurs de GEDs vendaient historiquement leur flexibilité sur le mécanisme d'ajustement (réserve tertiaire RR) opéré par les Gestionnaires de Réseaux de Transport (GRTs), la dérégulation des marchés de l'énergie a progressivement permis la commercialisation de telles flexibilités sur les marchés de gros également. Les GRDs se demandent ainsi dorénavant à quel point la sollicitation de GEDs pour de nouveaux usages est à même d'induire de nouvelles contraintes sur leur réseaux. A l'inverse, le recours à de telles flexibilités apparait comme un outil d'aide à la conduite des réseaux de distribution, sur lesquels les GRDs espèrent pouvoir compter dans les années à venir.

Résumé des initiatives de recherches & conclusions principales

Les thèmes abordés aux paragraphes précédents correspondent en réalité à un ensemble de préoccupations pour lesquels des solutions pourraient être apportés à l'aide de procédés de coordination de GEDs 2 . Ces travaux de thèses se sont donc préalablement attachés à évaluer le potentiel effectif de tels procédés de coordination de GEDs à contribuer à la résolution de chacun de ces enjeux. Cette évaluation s'est fondée sur une approche pragmatique, centrée autour de deux principaux postulats, motivés par des objectifs de rationalisation des coûts. Le premier postulat repose sur l'objectif de pouvoir réutiliser la même GED pour la soumission d'offres sur plusieurs marchés, qu'il s'agissent de marchés de gros ou de marchés de services systèmes. Les périodes de livraison de chaque offre peuvent alors être simultanées ou successives selon la nature du sous-jacent des offres. Le second postulat parie sur l'absence de déploiement généralisé des technologies du Smart Grid dans les réseaux électriques, au bénéfice de politiques de déploiements ciblés topologiquement, en réponse à des problèmes spécifiques à haute valeur ajoutée locale.

Le principe de réutilisation de la même GED pour des usages différents impose par conséquent de réfléchir à une politique de coordination de la livraison de chaque produit, sans conflit d'usages entre les différents acteurs du réseau. Une opportunité encourageante, dont l'adoption par l'ensemble des acteurs du Smart Grid et d'une grande valeur collective, serait d'axer les différents modèles d'affaires conformément à des Business Use Cases standardisés. Le recours à de tels Business Use Cases permettrait de clarifier les conditions d'utilisation des offres de flexibilités au bénéfice du GRT, du GRD, du fournisseur ou encore des aggrégateurs d'énergie. La philosophie d'une telle stratégie de coordination opérationnelle, à ce jour largement insufflée par les GRDs, serait de coordonner l'ensemble de la chaîne de valeurs et de coûts induites par la pénétration de GEDs dans les réseaux. Le premier maillon consisterait à appréhender l'impact que l'activation d'une offre de flexibilité par un acteur est à même d'avoir sur un autre acteur -ce que l'on appelle à ce jour la certification d'une GED -, avant d'évaluer en parallèle le bénéfice qu'une telle GED peut apporter aux GRTs et GRDs dans un contexte de gestion de contraintes. En dernier lieu, l'échange de flexibilité sur des plateformes de marchés dédiées permettraient aux opérateurs de réseaux de disposer de réserves opérationnelles à même de faciliter les opérations de conduite et de maintenance des réseaux. Dans un tel contexte, cette thèse s'est attaché à contribuer à la rédaction d'un certain nombre de ces Business Use Cases, dans le cadre du projet européen EvolvDSO.

La capacité de la flexibilité de la demande à apporter une réponse à la problématique de sécurité d'approvisionnement de la pointe électrique, a ensuite été évalué grâce au développement d'un modèle d'analyse de données. Ce modèle fut appliqué aux volumes et prix sur des marchés spot day-ahead des pays baltes, scandinaves (Nord Pool Spot) et de la France (Epex Spot). Les sorties de modèle ont finalement mis en lumière que l'élasticité des prix sur les marchés restent contenues et que le spread intraday -i.e. la différence de prix entre l'heure la plus chère et l'heure la moins chère de la journée -est relativement réduit, sauf au cours de quelques évènements extrêmes dont l'occurrence se compte en années. Par conséquent, l'investissement dans des GEDs, de stockage notamment, dans le seul but de fournir de la flexibilité en puissance uniquement les jours de pointe de consommation n'est pas en mesure de constituer un modèle d'affaire rentable, si celui est financé uniquement sur le spread intraday (Figure IV.7). Une rémunération de la capacité s'avère dans ce cas nécessaire, et est alors en mesure de convenir à des procédés de flexibilité de charges électriques industrielles, type réserves rapides et complémentaires (cas Français) ou Effektreserven (cas Suédois). Contrairement aux idées reçues, de si contenus niveaux de volatilité et d'élasticité des prix de gros, sont à même de doucher les espoirs des pro-Smart Grid de voir à ce jour la demande s'adapter aux prévisions de production des énergies renouvelables intermittentes, grâce à de simples signaux de prix. La création de valeur sur les marchés Spot day-ahead nécessite dès lors de compter sur des GEDs ayant des coûts marginaux de stockage ou de report de consommation de l'ordre de 20e/MWh, permettant ainsi la soumission d'offres de flexibilité compétitive sur les marchés tout au long de l'année. Enfin, les sorties de modèles ont mis en exergue une très grande variabilité de l'opportunité de revenu sur les marchés Spot d'un pays à l'autre et même d'une zone de prix à l'autre.

Profitability Assessment Business model definition

! " # $ %

Dans de telles conditions de coût marginaux d'activation, la commercialisation de flexibilité sur les marchés de gros peut toutefois rester pertinente afin de générer un revenu de base. Des revenus de 10-30ke/MW/an peuvent être espérés en fonction de la zone géographique et des années. Cette base sera ensuite abondée via l'engagement sur des marchés de services systèmes techniquement plus pointus afin d'aboutir à un modèle d'affaire combiné rentable. Ces services systèmes peuvent comprendre la fourniture de réserve de puissance pour le réglage du plan de tension dans les réseaux de distribution ou le maintien de la fréquence du système électrique.

Dans une thématique plus proche de la conduite des réseaux, les enjeux de gestion du plan de tension dans la distribution devraient être réglés via des outils distribués, au plus près des zones de déviation en tension et reposer sur le moins d'investissement en matériel possible. De plus, la méthode de contrôle déployée se devraient d'être la plus simple possible, clairement pragmatique et requérant le moins d'intégration de systèmes possibles. Cette position peut-être discordante et va à l'encontre des travaux de recherche contemporains sur l'estimation d'état qui visent à la conception d'outils de planification opérationnelle, déployés à grande échelle sur les réseaux. Néanmoins, cette conviction repose sur le constat que les GRDs ont jusqu'à maintenant été confrontés à bien moins de contraintes réseaux que ce qu'il a été imaginé par le passé. De ce fait, les stratégies grande échelle, qui parient sur le déploiement complet des technologies Smart Grid s'avèrent ne pas être compétitives à ce jour, comparées aux stratégies historiques qui reposent essentiellement sur des travaux de renforcements du réseau. Le renoncement du régulateur allemand d'imposer le déploiement de compteurs communicants à l'instar des Linky français, est l'illustration du refus actuel des acteurs du système électrique de modifier en profondeur leurs procédés opérationnels. De la même manière, les principaux équipementiers possèdent d'ores et déjà dans leur catalogue des transformateurs Moyenne Tension / Basse Tension (MT/BT) avec régleur en charge, en anticipation des problèmes de tension auxquelles les GRDs devraient être confrontés. Mais aucune commande n'a à ce jour été passé par les GRDs français en dehors d'initiatives de recherche... Révélateur de l'humeur actuelle des équipementiers électriques, quasiment aucun de ces nouveaux transformateurs et pas plus de cellules MT n'ont été présentés sur les stands lors l'édition 2015 de European Utility Week. Dans le même temps, le salon faisait la part belle à une multitude de nouveaux acteurs -non consolidés-de la Smart Home et de l'internet des objets. Face à un tel constat, une approche élémentaire pour la gestion du plan de tension BT serait de se reposer sur une infrastructure de capteurs de tension communicants, géolocalisables et plug&play, de manière à améliorer l'observabilité de ces réseaux historiquement dépourvus de tout système de mesure (cf. plaquette de l'initiative DLVM en Figure A.5, page 168). Au-delà d'une phase initiale de diagnostique, de tels capteurs peu chers pourraient ainsi être maintenus en quelques points du réseau, connus pour leur propension à affronter des excursions de tensions. Ces données de tension pourraient alors être utilisées afin de définir une amplitude de déviation en tension admissible au niveau de chaque poste de distribution et sur la base de laquelle le plan de tension MT pourrait être ajusté périodiquement -par exemple à l'échelle du quart d'heure -en jouant sur la prise du régleur en charge au poste source et sur d'éventuels bancs de capacités.

Ces travaux de thèse se sont enfin attachés à apporter une réponse à la problématique de dégradation de la stabilité du système électrique, évoquée aux paragraphes précédents. La réponse imaginée repose sur la conception d'un procédé de modulation coordonnée du niveau de puissance d'un ensemble de GEDs. L'élaboration puis la démonstration en conditions réelles de ce Primary Support repose sur une architecture logicielle et décisionnelle multi-couches, composée aux premiers niveaux d'un ensemble de GEDs et de contrôleurs de GEDs, coordonnés au niveau supérieur par au moins un plateforme de coordination. En dernier lieu, le déploiement d'une plateforme de marché facultative serait en mesure d'automatiser un procédé de partage de GEDs d'appoints d'une plateforme de coordination à l'autre, afin de pallier au déficit de flexibilité temporaire de l'une des plateformes. Le recours à une telle architecture permet de séparer les opérations de modulation du niveau de charge de chaque GED, qui sont réalisées en temps réel, des opérations de coordination du comportement de chacune de ces GEDs, qui peuvent avoir lieu en amont du temps réel, par exemple dans l'heure ou le quart d'heure précédent. En temps réel, la modulation du niveau de charge de chaque GED est pilotée de manière autonome et indépendamment d'une GED à l'autre par chaque contrôleur de GED, en fonction d'une mesure de fréquence du réseau réalisée sur site ( à la Figure IV.9), afin de suivre une caractéristique puissance-fréquence pré-déterminée.

Cette caractéristique est définie par une pente de modulation et un seuil initial de fréquence en-deçà duquel la modulation de charge débute ( ). Ce seuil et cette pente sont définis par un standard international: l'IEC 61850-7-420 [2015], ce qui garantie l'interopérabilité des GEDs et maximise les chances de pouvoir fournir plusieurs services systèmes ou de gros à partir du pilotage de la même GED. La détermination de cette caractéristique puissance-fréquence a lieu au cours de la phase de coordination du comportement de chacune des GEDs, en amont du temps réel et est réalisée par la plateforme de coordination dont dépend la GED. En complément de l'initiative de fourniture de réserves primaire (FCR) et d'urgence (LFDD), la coordination de GEDs est à même de permettre également la fourniture de réserve secondaire (FRR), comme imaginé par l'initiative Second Ice, brèvement développée au cours de cette thèse. Néanmoins, la fourniture d'une telle réserve repose sur une activation simultanée en moins de 30 secondes de l'ensemble des moyens de réserve, décidée de manière centralisée depuis le centre de conduite du GRT, et indépendamment de conditions de réseau prédéfinies. L'activation de réserve secondaire à partir d'un pool distribué de GEDs est ainsi en mesure de comprendre des difficultés opérationnelles notoires.

Perspectives futures de coordination de GEDs au services des acteurs du système électrique

L'horizon de temps de cette thèse a correspondu à celui des principaux démonstrateurs Smart Grid déployés afin de valider la faisabilité technologique du Smart Grid et de tester différents modèles d'affaires. En France, le projet Greenlys a fournit des enseignements significatifs sur le comportement des utilisateurs du réseau électrique. En premier lieu, le coût d'acquisition client visant à convaincre une part de ces utilisateurs de devenir des exploitants de GEDs -via notamment le déploiement en aval-compteur d'un contrôleur énergétique permettant le contrôle à distance d'un chauffe-eau ou radiateurs électriques domestiques -se sont révélés bien plus élevés qu'imaginé. Un tel constat est en mesure de profondément remettre en question le potentiel de fourniture de services systèmes et d'énergie de gros à partir de sources de flexibilité de la demande dans l'habitat et les bâtiments tertiaires. Rêvé par une large part des communautés scientifiques et industrielles, le développement à large échelle de l'effacement diffus -appelé également Demand Response -au bénéfice de la transition vers les Smart Grids ne se produira probablement jamais. Durant la même période, la croissance du véhicule électrique, sensée apporter de nouvelles flexibilités sur les réseaux, a été bien moindre qu'espérée. Malgré le constat plutôt pessimiste dressé précédemment, l'espoir de voir le Smart Grid aller de l'avant reste réel, tiré par les avancées spectaculaires du solaire photovoltaïque. Les coûts marginaux des centrales solaires en plein champ atteignent dorénavant des coûts proches de 50e/MWh au Moyen Orient, alors qu'un prix plancher de 70e/MWh a été atteint pour la première fois en France en 2015. Le photovoltaïque est devenu moins coûteux que l'éolien terrestre (70-90e/MWh), alors que les unités de production nucléaires en construction ou en rénovation affiche des coûts marginaux au-delà de 110e/MWh à l'image du tarif de rachat négocié par EDF avec le gouvernement britannique pour les futures centrales EPR de Hinkley Point.

Cette réduction des coûts du photovoltaïque induit deux conséquences majeures. D'un côté, elle est en mesure de consolider durablement l'industrie du solaire et d'accélérer le déploiement de nouvelles centrales, dont la rentabilité n'est dès lors plus dépendante des politiques publiques de soutien aux énergies vertes, qui se sont montrées volatiles par le passé. D'un autre côté, la différence de coûts marginaux entre le photovoltaïque d'une part et le nouveau nucléaire de l'autre sont en mesure de fournir un coût d'opportunité en faveur du décalage de charges de Le photovoltaïque et le stockage sont donc tous deux en mesure de fournir un nouveau souffle à l'innovation dans le Smart Grid, au bénéfice des acteurs du système électrique à horizon 2020, alors même que 2016 va marquer la fin d'un grand nombre de projets de recherches français et européens. Enfin, pour revenir aux problèmes de stabilité des réseaux électriques qui ont animés cette thèse, le recours à une coordination distribuée de GEDs tels que le photovoltaïque, le stockage stationnaire et on l'espère le véhicule électrique semble constituer un chemin fiable à même de fournir une réponse en rupture aux problèmes de fermetures de centrales conventionnelles, dès lors remplacées par des sources d'énergies renouvelables raccordées aux réseaux via une interface d'électronique de puissance. Par ailleurs et en guise de conclusion finale, ces architectures de fourniture distribuée de services systèmes telles que Primary Support devraient être parfaitement adaptées aux problématiques d'électrification verte des pays du G77, en proposant des outils de stabilité compatibles avec des réseaux électriques à faible inertie.

  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II.23 Vertical grid load flow from Tennet Germany transmission network down to the distribution grids -July 2015 (data: Tennet [2015]) . . . . . . . . . . . . . . . . . . III.1 Suitable frequency range of operation of Primary Support . . . . . . . . . . . . III.2 IEC61850-7-420 compliant architecture of PrimarySupport . . . . . . . . . . . . III.3 Kind of loads compliant with Primary Support . . . . . . . . . . . . . . . . . . . III.4 Characteristic of FWHZ function embedded into IEC61850-7-420-compliant DERs III.5 Targeted step-by-step droop curve involving ON/OFF-driven DERs . . . . . . . III.6 Data model used in Primary Support IEC61850-compliant . . . . . . . . . . . . III.7 Sequences of data exchange between the PrimarySupport coordination agent and a DER controller . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.8 Thresholds & slopes coordination algorithm used by Primary Support . . . . . . III.9 Probability P act of activation of FWHZ function for a given DER depending on its threshold HzStr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvi LIST OF FIGURES III.10 Principle of operation of the Layer 3 in Primary Support . . . . . . . . . . . . . III.11 Topology-related system-scale architecture . . . . . . . . . . . . . . . . . . . . . III.12 Mean Frequency Deviation Dispersion . . . . . . . . . . . . . . . . . . . . . . . . III.13 Common daily occurrence of load modulation events, as a function of the frequency threshold applied . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.14 Combination of FCR-N and FCR-D claimed by Jomaux and De Jaeger [2015] . III.15 Frequency deviation distribution for various penetration of FCR-D [Jomaux and De Jaeger, 2015] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.16 Common duration of load modulation events, as a function of the frequency threshold applied . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.17 Simplified operational process of Primary Support . . . . . . . . . . . . . . . . . IV.1 Presentation of the agent-based platform and the field test . . . . . . . . . . . . IV.2 Scheme of principle and real energy box developed . . . . . . . . . . . . . . . . . IV.3 Test of the agent-based platform in steady-state operation . . . . . . . . . . . . IV.4 Micro-grid response to a major outage, with and without frequency regulation .IV.5 Characterisation of the obtained droop curve compared to the droop expected . IV.6 Architecture of the Power Hardware In the Loop simulation test bench at PREDIS134 IV.7 Architecture of the ON/OFF demo kit to the deployed within Schneider Electric show-room . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV.8 Prototype of ON/OFF demonstration suitcase . . . . . . . . . . . . . . . . . . . IV.9 ON/OFF industrial DER controllers response to a sudden frequency drop . . . IV.10 ON/OFF industrial DER controllers response to a sudden frequency recovery . IV.11 On-site generic architecture of an HVAC system and picture of the equivalent system built within PREDIS platform . . . . . . . . . . . . . . . . . . . . . . . . IV.12 Power conversion process from the HVAC-emulator cubicle down to the final resistive loads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV.13 Power-response of the HVAC unit to a monthly-event observed in Continental Europe (March 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV.14 Power-response of the HVAC unit to a decade-event (2003 Italian Black-out) . . IV.15 ICT and physical path from Hz modification up to new T otW value observation IV.16 Validation of delivery of the slope Wgra by the HVAC cubicle . . . . . . . . . . IV.17 Architecture of the demonstration coordination platform of Primary Support . . IV.18 Interface of visualisation of the resultant offer and curves . . . . . . . . . . . . . IV.19 Map of the DER controllers of Primary Support deployed among Dream facilities IV.20 Architecture of the airport lighting modulation system to the deployed at Milano Malpensa for Primary Support purpose . . . . . . . . . . . . . . . . . . . . . . . IV.21 [Left] Overview of the parking lighting of Milano Malpensa Airport to be involved in Primary Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV.22 [Right] Overview of the parking lighting of Milano Malpensa Airport to be involved in Primary Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A.1 Research axis on Spot market volatility analysis . . . . . . . . . . . . . . . . . . xvii losses cost saving opportunities using DER . . . . . . . . . . I.2 FRR regulated remuneration in France and Denmark . . . . . . . . . . . . . . . I.3 Assessment of RR using domestic space heating DR . . . . . . . . . . . . . . . . I.4 Assessment of Capacity Auction opportunities using DER . . . . . . . . . . . . I.5 Mean 2001-2014 ratio of the Annual Spread 3.5hr income of peak-days compared to off-peak-days. Peak-day limit: 85% of the historic peak load [D8] . . . . . . . I.6 Mean number of peak days per year . . . . . . . . . . . . . . . . . . . . . . . . . I.7 Spot volumes range (in % of the peak load, wherein the top 10% of the day-ahead spot turnover is traded) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I.8 Number of days of the year having a daily spread 3.5hr larger than 20e/MWh. Average 2011-2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . of the year having a daily spread 3.5hr larger than 40e/MWh. Average 2011-2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I.10 Summary of the sources of revenue of DER flexibility depending on the countries I.11

  , II.10 and II.11 . . . . . . . . . . . . . . II.4 Frequency Restoration Range applied by synchrounous area . . . . . . . . . . . II.5 Automatic Low Frequency Demand Disconnection scheme characteristics (Art 14, ENTSO-E [2015a]) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II.6 Estimation of the FCR and wholesale marginal cost and incomes depending on the technology used for 1MW of installed capacity . . . . . . . . . . . . . . . . . III.1 From frequency stability challenges to the functional and operational specifications of Primary Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.2 IEC61850-7-420 parameters to be defined for the use of the Frequency-watt mode FWHZ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.3 Non native IEC61850-7-420 parameters involved in the threshold coordination algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.4 Columns order of the 20 parameters introduced as inputs of the threshold & slope coordination algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III.5 Frequency dispersion occurrence in Continental Europe [Filip, 2011] . . . . . . . IV.1 Semantic of the JSON messages exchanged between the DER controllers and the coordination platform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Figure 1 :

 1 Figure 1: Evolution the LNG exporting capacities of Qatar (data: Wikipedia [2015])

Figure 2 :

 2 Figure 2: Penetration of Wind (left) and PV (right) in Europe over the 10 past years (in GW) [EWEA, 2016[START_REF] Gwec | Global wind statistics 2015[END_REF], IEA, 2016]

Figure 3 :Figure 4 :

 34 Figure 3: Evolution of the raw materials prices since 1984 (data: Index mundi [2015])

  forth in [Article 19 Frequency Quality Target Parameters] of [ENTSO-E, 2013d], and to comply with the amount of reserves needed per Frequency Containment Process, Frequency Restoration Process and Reserve Replacement Process with respect to the required quality, as set forth in [Chapter 6 Frequency Containment Reserves, Chapter 7 Frequency Restorations Reserves and Chapter 8 Replacement Reserves] of [ENTSO-E, 2013d]. [ENTSO-E, 2014b].

  : ⊲ Raspberry PI. RTE (Réseau de Transport d'Electricité): TSO of France.

Figure I. 1 :

 1 Figure I.1: Summary over the time of markets and main physical limitations of the power industry

1 .

 1 Figure I.2: Localisation of the 15 Nordics and Baltics Nord Pool Spot bidding areas [Nord PoolSpot, 2015]

Figure

  Figure I.5: (a) Estimation of the total losses in MV/LV transformers depending on the LV load consumed and on the transformer size (data: Schneider Electric [1996]) (b) Illustration of load-shifting from peak to off-peak time to reduces T&D losses[START_REF] Nourai | Load leveling reduces t&d line losses[END_REF]

  Figure I.5 (a) illustrates such challenge of losses reduction in transformer. E-Cube [2013] assesses then the complementary revenue that 1000hrs of load shifting per year would induce on the energy procurement costs of the System Operators. The cost saving is assessed at 1.2ke/MW/yr only. This amount of cost saving has been assessed by E-Cube

Figure I. 6 :

 6 Figure I.6: Estimation of annual procurement and cost of FCR supply in Europe. ( data: appendix C.5)

Figure I. 7 :

 7 Figure I.7: Distribution of the weekly FRR capacity prices in Germany -February 2-8 th 2015 (data: Regelleistung [2015])

Figure I. 8 :

 8 Figure I.8: Distribution of the weekly FRR capacity prices in Germany -June 8-14 th 2015 (data: Regelleistung [2015] )

Figures B. 9

 9 Figures B.9 and B.10 -(App. B Section 4) summarize the annual revenues [D17] and [D18] obtained in each bidding area of the Nordics, Baltics and France. TableI.5 presents then the ratio of [D17]/[D18] in each bidding area, averaged over the years of available data. Ignoring the case of Eastern Denmark, it can be noticed that the periods of peak load capture from nearly 10% to 25% of the potential annual spread revenue, while nearly 10% of the annual turnover of the day-ahead spot market is traded during these peak-days (TableI.7).

  illustrate especially this assessment. Annual spread income of Finland, Sweden and Northern Norway (Trondheim) would have doubled and the annual spread incomes of Denmark East would have increased by 50%, compared to previous years. A decomposition of the daily spread incomes over the year is proposed for Finland in Figure I.9 [b], while the cumulative sum of these daily incomes is displayed in Figure I.9 [c]. The day-ahead prices and volumes are finally plotted as well in Figures I.9[a] & [d].

  . It was enough to generate the three most extreme peak prices that ever occured from 2001 to 2014 in Finland (the third peak occured in December 17th 2009 at 5pm and its inherited spread incomes are visible in Figure I.9 [b] in grey).

Figure 3 -

 3 Figure 3-28: Decomposition of spread revenue captures over the year 2010 in Finland Figure I.9: Decomposition of spread revenue captured during days of peak-load over the year 2010 in Finland

2 .

 2 Figure I.14: Benchmark of the annual revenue of domestic ESS involvement in the day-ahead spot markets in the Nordics, Baltics and France. (Conversion efficiency: η AC/DC = 2 × 95%, η DC/DC = 95%)

Figure I. 16 :

 16 Figure I.16: Benchmark of energy boxes hardware in terms of price and compliance with the business case of domestic space heating optimisation

  Figures I.17 and I.18 present finally the potential cost savings induced by the new heating strategy (Optimization program B and power procurement at the day-ahead hourly spot price -tariff 1 -in Figure I.15) and compared these savings with the mean investment and operation costs required to replace the hardware. Such mean costs have been assessed by benchmarking the investment and installation costs of the hardware presently available on the market (Figure I.16).The ICT and maintenance costs have been neglected. A six-years lifetime has been considered for the hardware. Hence a mean annual cost of 25-50e/household have been considered. Such a range of cost is plotted in grey in the background of Figures I.17 and I.18, that enables the realisation of the Cost Benefit Analysis, directly on the Figures. The results are only valid for the accommodations already equipped with a central thermostat. For an accommodation that is not equipped with a central thermostat, the investment would be larger, but additional energy savings would be expected. Hence the profitability of the Energy Box would be mainly more induced by the improvement of the energy efficiency of the accommodation than by the present business case.

  Figures I.17 and I.18 present finally the potential cost savings induced by the new heating strategy (Optimization program B and power procurement at the day-ahead hourly spot price -tariff 1 -in Figure I.15) and compared these savings with the mean investment and operation costs required to replace the hardware. Such mean costs have been assessed by benchmarking the investment and installation costs of the hardware presently available on the market (Figure I.16).The ICT and maintenance costs have been neglected. A six-years lifetime has been considered for the hardware. Hence a mean annual cost of 25-50e/household have been considered. Such a range of cost is plotted in grey in the background of Figures I.17 and I.18, that enables the realisation of the Cost Benefit Analysis, directly on the Figures. The results are only valid for the accommodations already equipped with a central thermostat. For an accommodation that is not equipped with a central thermostat, the investment would be larger, but additional energy savings would be expected. Hence the profitability of the Energy Box would be mainly more induced by the improvement of the energy efficiency of the accommodation than by the present business case.

Figure I. 17 :

 17 Figure I.17: Benchmark of the power bill savings induced by the implementation of the costoptimized heating process (process B-1 in Figure I.15), compared with Energy Box investment cost assumptions in the Nordic and Baltic countries (same outdoor reference temperature from Malmö).

Figure I. 18 :

 18 Figure I.18: Difference of power bill savings induced by the implementation of the cost-optimized heating process (process B-1 in Figure I.15), with three different sets of outside temperature and French market data.

Figure I. 19 :

 19 Figure I.19: Scenarios of DERs flexibility sharing for revenue multiplication

Figure II. 1 :

 1 Figure II.1: Simplified representation of a generator connected to a unique load[START_REF] Andersson | Dynamics and Control of Electric Power Systems[END_REF]

Figure 4 :

 4 Figure 4: Schematic map of UCTE area split into three areas Figure II.2: Splitting of the Continental Europe synchronous area into three areas, asynchronous one another following the German disturbance ofNovember 4, 2006[START_REF] Entso-E | Final report system disturbance on 4 november 2006[END_REF]

  Europe faced one major power outage over the last fifteen years that can be qualified as blackout. It affected the whole of Italy in 2003 [ENTSO-E, 2004a], representing a load shedding of 27GW. A second major outage occurred in 2006 and impacted part of western European countries [ENTSO-E, 2006], from Germany and Hungary in the east up to Portugal in the west. It represented a load shedding of 18GW (Figure II.

Figure 7 :

 7 Figure 7: Map of load and pumps shedding by TSOs Figure II.4: Load tripping repartition across Europe following the disturbance ofNovember 4, 2006[START_REF] Entso-E | Final report system disturbance on 4 november 2006[END_REF]

Figure

  Figure II.5: Illustration of the activation of balancing reserves following an over-load disturbance, depending on the frequency variation

Figure

  Figure II.5 illustrates this process of step-by-step activation and release of balancing reserves.It can be noticed that the FCR is progressively released along the restoration of the frequency. This is the key characteristic of the FCR, whose principle of operation is presented in Section 1.4. Figure II.5 presents a situation where FCR has been activated fast enough and with an appropriate magnitude.

Figure II. 6 :Figure

 6 Figure II.6: Presentation of the Synchronous Areas of ENTSO-E (data: ENTSO-E [2013a,e])

  Figure II.5, the FCR is the first level of balancing reserves to be activated in a such situation. It aims to stabilize the frequency after the disturbance at a steady-state value within a permissible Maximum Steady-State Frequency Deviation (Figure II.8), thanks to a simultaneous action of all of the FCR sources, regardless of their location among the entire synchronous area. The bandwidths of the Maximum Steady-State Frequency Deviation that are admissible in Europe are presented in Figure II.9.

Figure II. 8 :

 8 Figure II.8: Frequency Quality Defining Parameters [ENTSO-E, 2013e]

Figure

  Figure II.11 defines the characteristic times that any FRR bids have to comply with. The

Figure 6 :

 6 Figure 6: The implementation range for LFDD plan Figure II.12: Implementation range for LFDD plan [ENTSO-E, 2015b]

  Figure II.14: Annual occurrence of negative residual load in West Denmark (in % of the time. 10%=876hrs a year) (data: Energinet [2015])

  from 2010 to 2014 in the Nordics and Baltics. The FCR income range is assessed from Figure I.6. The wholesale generation costs correspond to the LCOE of each technology (Figure II.15) The cost of FCR supply assumes 97.5% of fuel and carbon costs saving subtracted from the LCOE of each technology (Figure II.15), given that it can be roughly estimated from Figure II.16 that the FCR is fully activated at most 2.5% of the time.

Figure

  Figure II.15: Levelized Cost of Electricity (LCOE) -2015 -3% to 10% discount rate[IEA, 2015]

Figure 9 :

 9 Figure 9: Evolution of Frequency Deviations in NE Figure II.16: Evolution of frequency deviation in the Northern Europe Synchronous Area over the 15 last years [ENTSO-E, 2013e]

FCR

  bid prices (in €/MW/h) Time of the day (in hr) DK East FNR & FDR prices on Jan 7-8 th , 2015 FNR FDR source: Appendix C.3

Figure 11 :

 11 Figure 11: Daily occurrence of high average System Frequency Deviations in NE in 2009-2010 Figure II.17: Daily occurrence of high frequency deviation in Northern Europe Synchronous area in 2009-2010 [ENTSO-E, 2013e]

Figure

  Figure II.18: Decrease of system inertia with increase in wind penetration replacing conventional generations[START_REF] Das | Primary reserve studies for high wind power penetrated systems[END_REF]

  Figure II.19. The authors added on Figure II.19 the frequency threshold of disconnection of the first step of UFLS (purple surface) applied in the area of study i.e 49Hz (see Table

Figure

  Figure II.23: Vertical grid load flow from Tennet Germany transmission network down to the distribution grids -July 2015 (data: Tennet [2015])

Figure III. 1 :

 1 Figure III.1: Suitable frequency range of operation of Primary Support

  Figure III.2: IEC61850-7-420 compliant architecture of PrimarySupport

Figure III. 3 :

 3 Figure III.3: Kind of loads compliant with Primary Support

Figure III. 4 :

 4 Figure III.4: Characteristic of FWHZ function embedded into IEC61850-7-420-compliant DERs

  FigureIII.4. In both Figures III.4 (a) and (b), the green paths represent the maximum response that the DER is able to provide face to severe frequency deviation. The blue paths represent an intermediate response the DER has to provide following a frequency deviation up to the frequency value Fnadir. In its basic version devoid of hysteresis(Figure III.4 (a)), the modulation of the power consumption begins from a predetermined frequency threshold HzStr and follows a power-frequency slope W gra. The process is perfectly reversible between the periods where the DER is shed and re-energized. However, in the version with hysteresis(Figure III.4 (b)), the process of re-energization of the DER is not reversible any more in term of power-frequency pattern (dotted lines). Indeed, the slope of re-energization is expressed in term of power recovery per unit of time and not per unit of frequency. Hence, the pattern of the power recovery on the power-frequency chart differs from one event to the next one depending on the frequency evolution during each period of recovery.

  Figure III.5: Targeted step-by-step droop curve involving ON/OFF-driven DERs

  4.2 and illustrated by Figure III.7, the real-time operational process relies on the sending of four input parameters to each addressable DER, in response to the sending of five output data received from a given DER. The three first output parameters enable the monitoring of the effective flexibility of each DER (Figure III.4):

Figure III. 6 :

 6 Figure III.6: Data model used in Primary Support IEC61850-compliant

  power recovery following a frequency regulation event in hysteresis mode.Real-time operational setting of the Load Controller: PrimarySupport Coordination Server >> Load controller Client [write] Real-time state & monitoring of the Load Controller : Load controller Client >> PrimarySupport Coordination Server [read] Pre-operational setting of the Load Controller: PrimarySupport Coordination Server >> Load controller Client [write] Address & communication parameters: PrimarySupport Coordination Server <> Load controller Client [read]

  operation, 1…x: most critical value of the health attribute of all the domain logical nodes contained in the logical device state (inherited from DomainLN). Real-time network frequency. Enum validity of the measure (good | invalid | reserved | questionable). Enum validity of the measure (good | invalid | reserved | questionable). Timestamp of the measure (nb of seconds in GMT from 1/01/1970). Real-time Total active power consumed by the load controlled. Timestamp of the measure (nb of seconds in GMT from 1/01/1970).

  Thresholds Coordination N.B. As explained in Section 3.4.3, the threshold coordination algorithm is computed each time a DER controller sends an updated dataset to the coordination platform. The dataset is composed of the real-time parameters {M inW out, M axW out, T otW }. The communication is always initiated by the DER controller (see Section 3.4.2).

Figure III. 8

 8 Figure III.8 details the algorithm which enables the periodic coordination of the thresholds HzStr and slopes W gra of all of the reachable DERs of a given portfolio of aggregation. This algorithm introduced in previous Section 3.4.2 is represented by the large blue arrow in Figure III.7.

  Figure III.10) is charge of the control of one DER used as shared back-up (G2Elab_A_1 in Figure III.10) would communicate its real-time input and output parameters directly to the coordination platform that looks for back-up capacity (SmartPower Aggregator in Figure III.10), instead of remaining controlled by its usual coordination platform (energydreams Aggregator in Figure III.10).

  Figure III.13: Common daily occurrence of load modulation events, as a function of the frequency threshold applied

Figure

  Figure III.13 displays first the estimation of the number of load modulation episodes that would occur daily depending on the DER threshold HzStr. Figure III.13 displays then the daily cumulative duration of load modulation. The bars in black represent the threshold located in the FCR dead-bandwidth, while the bars in red are located within the frequency range of operation of the FCR in CE.

Figure 2 .Figure 8 .

 28 Figure 2. Combination of FCR-N and FCR-D

  Figure III.16: Common duration of load modulation events, as a function of the frequency threshold applied

Figure

  Figure III.17: Simplified operational process of Primary Support

Figure IV. 1 :Figure IV. 2 :Figure IV. 3 :

 123 Figure IV.1: Presentation of the agent-based platform and the field test

Figure IV. 4 :

 4 Figure IV.4: Micro-grid response to a major outage, with and without frequency regulation

  Figure IV.5: Characterisation of the obtained droop curve compared to the droop expected

Figure IV. 6 :

 6 Figure IV.6: Architecture of the Power Hardware In the Loop simulation test bench at PREDIS

  Figure IV.9 presents the evolution of the overall power consumption of the test bench depending on the system frequency prior and after each of the 26 events of frequency drop. Figure IV.10 presents then the equivalent power consumption prior and after each of the 26 events of frequency

1 .

 1 VALIDATION OF DERS REAL-TIME MODULATION (LAYERS 0 & 1)

Figure

  Figure IV.12: Power conversion process from the HVAC-emulator cubicle down to the final resistive loads

1 .

 1 VALIDATION OF DERS REAL-TIME MODULATION (LAYERS 0 & 1)

  RPI achieves this monitoring by handling the values of level of load T otW which are transmitted on Modbus by the PLC at the destination of the Modbus-RTU/Webservice-TCP gateway. It leads to the saving of set of {Hz, T otW } points, wherein each of the Hz and T otW data of the couple are saved at the same time-stamp.Two successive disturbances have been triggered. The first scenario is a set of 1-second sampling frequency data measured in CE synchronous area, wherein a frequency Nadir of 49.88Hz has been observed and recovered. This set of data is extracted from the 40 days of data monitored in 2015 within Schneider Electric show-room (seeSection 4.3), and corresponds somehow to an exceptional monthly-event. The second scenario is the sequence of events that lead to the Italian blackout in 2003 [ENTSO-E, 2004a], starting from the disconnection of the Italian power system from the rest of Continental Europe. Such an event can represent a decade or multi-decades event at the scale of a synchronous area.The power-response of the HVAC unit along the temporal sequence of incidents are represented by continuous black lines T otW (t) in Figure and Figure. The curve of frequency Hz(t) is plotted in red on the figures with an accurate linear scaling. Such scaling highlights a clear correlation between the curves of frequency and of the level of load. Nonetheless, a time-offset can be noticed between both curves, especially in Figure IV.14. Such offset is assessed inSection 1.3.3.

Figure

  Figure IV.13: Power-response of the HVAC unit to a monthly-event observed in Continental Europe (March 2015)

Figure

  Figure IV.15: ICT and physical path from Hz modification up to new T otW value observation

Figure

  Figure IV.16 plots the two operational droop obtained during the demo test. Each droop represents one of the two outages simulated.

  Figure E.4 in page 206). The second one enables the input of parameters that characterize the willingness of each DER owner to get its DER involved in the process of frequency regulation (see synoptic's details in Figure E.3 in page 205). The third component enables to plot the effective resultant offer that satisfies the resultant demand in time of operation at the scale of the portfolio of aggregation (see synoptic's details in Figure IV.18 in page 148).

Figure IV. 18 Figure D. 3 Figure D. 4 Figure

 1834 Figure IV.18

Figure

  Figure IV.18 displays the HMI of visualisation of the curves of resultant offer and demand, which are built at the scale of the portfolio of aggregation of the coordination platform. In Figure IV.18, the x-axis represents the frequency in hundredths of Hertz. The y-axis represents the cumulated regulating power in Watt. The aggregated demand is plotted in blue, while the aggregated offer is plotted in green. The graph displays as well in yellow the range of power contribution of the given DER that has been selected for the plot. The graph displays finally the value of the last frequency measurement that has been sent by a given DER controller at the destination of the coordination platform (red dotted arrow in Figure IV.17).

Figure

  Figure IV.18 illustrates the behaviour of the algorithm for the threshold and slope coordination:

Figure

  Figure IV.19: Map of the DER controllers of Primary Support deployed among Dream facilities

Figure

  Figure IV.20: Architecture of the airport lighting modulation system to the deployed at Milano Malpensa for Primary Support purpose

Figure

  Figure IV.21: [Left] Overview of the parking lighting of Milano Malpensa Airport to be involved in Primary Support

  Programmes (TSO, Producers, and DSO works) • Optimise network operations until market gate closure based on an operational planning schedule • Certify, manage the impact of flexibilities activated in Balancing and Flexibility Markets on the distribution network, and provide data for the settlement process • Operate the Distribution Constraints MarketContribution on Use CasesThe involvement of DERs on different power markets (wholesale, TSO-driven, etc.) is willing to induce unexpected constraints for the DSO. Hence, a coordination between power system actors is welcomed Business Use Cases Definition and Requirements[for DER integration]

Figure A. 3 :Figure A. 4 :

 34 Figure A.3: Research axis on Business Use Cases for DER integration

  Figure B.2 to Figure B.7. These illustrations have been produced using Finnish data. In TableB.2 the column of the left qualifies data that have been built based on network load heritage only; the column of the right qualify data that have been built based on price heritage only; finally the data in the middle have been computed thanks to a combined treatment of price and load data. Up to four successive steps of treatment have been required. The data are presented top-down depending on the heritage of data they are based on. It shows a convergence of the data toward the middle column over the successive steps of data manipulation. It describes the data empowerment through their successive treatment. The data surrounded with a red frame are the final data based on which business analyses have been performed to contribute to Section 2.8.1 (Chapter I, page 32).

Figure B. 1 Figure B. 2 :

 12 Figure B.1 illustrates graphically the principle of successive analytics reinforcement. From an initial cloud of {network load; price} points, extracted from fourteen years of hourly day-ahead spot data of Southern Sweden and Finland, it becomes possible to plot one smoothed curve of

Figure B. 3 :

 3 Figure B.3: Example of [D2] data content

Figure 3 -

 3 Figure 3-35: Spot turnover repartition [D13], 1MW-steps price elasticity [D10] and Gliding Price

Figure 3 -

 3 Figure 3-34: Spot turnover repartition [D13], 1MW-steps price elasticity [D10] and Gliding Price

Figure 3 -

 3 Figure 3-36: Spot turnover repartition [D13], 1MW-steps price elasticity [D10] and Gliding Price

Figure 3 -Figure 3 -

 33 Figure 3-39: Descending daily spread 1hr [D11] and 3.5hr [D12] in Sweden, Finland, Latvia, LithuFigure B.15: Descending daily spread 1hr [D11] and 3.5hr [D12] in Sweden, Finland, Latvia, Lithuania and Estonia. Average 2011-2014

Figure D. 7 :

 7 Figure D.7: Patent review -Key words "Demand Response " 5/5

Figure

  Figure IV.7: Principe de l'analyse coûts-bénéfices réalisée pour estimer la rentabilité du stockage chimique intraday sur les marchés spot

Figure IV. 8 :

 8 Figure IV.8: Exemple de GEDs compatibles avec les spécifications de Primary Support

Figure IV. 9 :Figure

 9 Figure IV.9: Procédé opérationnel simplifié de Primary Support

  En parallèle, la plupart des GEDs ont été et continueront à être déployés en aval du compteur électrique BT, échappant de fait au contrôle natifs des GRDs et GRTs. Cette absence de moyen de contrôle simple(Figure IV.11) risque de décourager les gestionnaires de réseaux d'avoir recours à la flexibilité offerte par les GEDs dans leurs opérations de conduite de réseau. La standardisation des fonctions réalisables par les GEDs et des protocoles de communication que ceux-ci embarquent de manière native est donc d'une importance capitale. La standardisation apparait comme donc une opportunité vers une interopérabilité entre les GEDs et les composants du système électrique. Celle-ci est à même de redonner vie à une partie des modèles d'affaires du Smart Grid tout d'abord en réduisant les coûts d'intégration logiciels et télécoms des GEDs, et en permettant ensuite la contribution d'une GED à la fourniture de différents services requis par différents acteurs du système électrique, et ceci simultanément ou un service après l'autre. De cette manière, la taille critique permettant d'amortir les coûts d'intégration d'une GED serait significativement réduite. Les efforts de standardisation deviennent à ce jour une réelle préoccupation pour les acteurs du système électrique, et ceci bien qu'un déploiement de ces fonctions standards va requérir une mise à jour des procédés de conduite des réseaux ou des générateurs d'énergies conventionnels et distribués. Devant un tel challenge, mes pensées vont à Messieurs Guise et Ulian pour leurs -ingrates mais riches -contributions aux travaux de l'IEC61850, au bénéfice de l'ensemble des acteurs du système électrique.

Figure

  Figure IV.11: Illustration des enjeux de standardisation des protocoles de communication des GEDs

  Definition of the FCR power-frequency characteristic (data: Art 44, ENTSO-E [2013e]) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II.10 Characteristic Time of FCR (data: Art 44,45, ENTSO-E [2013e]) . . . . . . . . . . . II.11 Characteristic Time of FRR (data: Art 46,47, ENTSO-E [2013e]) . . . . . . . . . . . II.12 Implementation range for LFDD plan [ENTSO-E, 2015b] . . . . . . . . . . . . . II.13 Evolution of the asynchronous machine's operation point faced with slight variations of the power system frequency . . . . . . . . . . . . . . . . . . . . . . . . II.14 Annual occurrence of negative residual load in West Denmark (in % of the time. 10%=876hrs a year) (data: Energinet [2015]) . . . . . . . . . . . . . . . . . . . . . II.15 Levelized Cost of Electricity (LCOE) -2015 -3% to 10% discount rate [IEA, 2015] II.16 Evolution of frequency deviation in the Northern Europe Synchronous Area over the 15 last years [ENTSO-E, 2013e] . . . . . . . . . . . . . . . . . . . . . . . . . II.17 Daily occurrence of high frequency deviation in Northern Europe Synchronous area in 2009-2010 [ENTSO-E, 2013e] . . . . . . . . . . . . . . . . . . . . . . . . II.18 Decrease of system inertia with increase in wind penetration replacing conventional generations [Das et al., 2015] . . . . . . . . . . . . . . . . . . . . . . . . . II.19 Effect of the increase in wind penetration (replacing conventional generators) on

Table I .

 I 1: Assessment of Grid losses cost saving opportunities using DER

	Physical losses	11-19 ke/MW/yr [Nourai et al., 2008]
	Energy procurement ---1.2 ke/MW/yr [E-Cube, 2013]
	Total grid savings	12.2-20.2 ke/MW/yr
	[2013], by assuming that the DSO purchases power at a mean price of 57.3e/MWh as assumed
	by ErDF in 2013 [CRE, 2012].

Table I .

 I 2: FRR regulated remuneration in France and Denmark

			France
	Capacity remuneration 16.96e/MW/hr [Lebel, 2012]
	Energy remuneration	9.76 e/MWh [Lebel, 2012]
			Denmark
	Capacity remuneration		no public data
	Energy remuneration	max(Elspot

price +13.4e/MWh ; RR price )

[START_REF] Energinet | Ancillary services to be delivered in denmark tender conditions[END_REF]

Table I . 4 :

 I4 Assessment of Capacity Auction opportunities using DER

	Swedish Effektreserven	6.9 ke/MW/yr [Lebel, 2012]
	French Capacity Auction 60 ke/MW/yr [E-Cube, 2013]

Table I .

 I 5: Mean 2001-2014 ratio of the Annual Spread 3.5hr income of peak-days compared to off-peak-days. Peak-day limit: 85% of the historic peak load[D8]

	Denmark DK West DK East	SE1	SE2	Sweden SE3	SE4	Sweden	Finland	France
	21%	33%	13%	9%	17%	10%	20%	14%	7%
			Norway
	Kristiansa nd	Trondhei m	Bergen	Oslo	Tromso	Norway	Estonia	Latvia	Lithuania
	9%	14%	9%	5%	7%	11%	11%	14%	25%

Table 3 - 9 :

 39 Mean 2001Mean -2014 ratio of the Annual Spread 3.5hr income of peak-days compared to off-

Table I . 6 :

 I6 Mean number of peak days per year

	Denmark DK West DK East	SE1	SE2	Sweden SE3	SE4	Sweden	Finland	France
	77	95	49	36	28	22	54	33	10
			Norway
	Kristiansa nd	Trondhei m	Bergen	Oslo	Tromso	Norway	Estonia	Latvia	Lithuania
	9	38	20	28	73	28	37	70	18

Table I .

 I 7: Spot volumes range (in % of the peak load, wherein the top 10% of the day-ahead spot turnover is traded)

	Denmark DK West DK East	SE1	SE2	Sweden SE3	SE4	Sweden	Finland	France
	84%	88%	84%	81%	83%	82%	87%	84%	79%
			Norway
	Kristiansa nd	Trondhei m	Bergen	Oslo	Tromso	Norway	Estonia	Latvia	Lithuania
	68%	84%	85%	83%	87%	82%	82%	85%	87%

Table 3 -

 3 10: Spot volumes range, wherein the top 10% of the day-ahead spot turnover is traded.

Table I .

 I 8: Number of days of the year having a daily spread 3.5hr larger than 20e/MWh. Average 2011-2014

	Denmark DK West DK East	SE1	SE2	Sweden SE3	SE4	Sweden	Finland	France
	175	192	49	49	63	87	64	135	314
			Norway
	Kristiansa nd	Trondhei m	Bergen	Oslo	Tromso	Norway	Estonia	Latvia	Lithuania
	17	39	19	20	31	17	177	294	259
	Table 3-11: Counter of days of the year having a daily spread 3.5 is larger than 20€/MWh. Average 2011-2014
	Table I.9: Number of days of the year having a daily spread 3.5hr larger than 40e/MWh.
	Average 2011-2014
	Denmark DK West DK East	SE1	SE2	Sweden SE3	SE4	Sweden	Finland	France
	28	36	9	9	11	13	11	33	70
			Norway
	Kristiansa nd	Trondhei m	Bergen	Oslo	Tromso	Norway	Estonia	Latvia	Lithuania
	5	8	5	7	7	5	38	151	106
	Table

  3 provides the daily revenue that can be expected for any ESS, expressed per MWh of storage capacity.Income ESS is the daily revenue to be generated by an ESS of a E cap capacity (in e/day)

				2. BUSINESS OPPORTUNITIES OF DER FLEXIBILITY
	Business model definition		Profitability Assessment
	70€/yr of revenue The business model has been tested on 11 bidding areas of the Nordics, Baltics and France. Only AC/DC Inverter ESS per Powerwall AC/DC =95% the least and the most interesting bidding areas have been tested for the countries composed
	Capacity: 7kWh Charging & Discharging power: 2kW Cycling efficiency: 95% Lifetime 2000 cycles Ends-up in Powerwall profitability, assessing a revenue 7 of more than two bidding areas such as Norway and Sweden. Three scenarios of solicitation, Purchase a Tesla's Powerwall battery for your home 1 of 2kW x 35k€/MW/yr 2800€ E charged = E cap E purchased E sold Interconnected in terms of percentage of days of activation per year have been tested: 10%, 30% and 100% of contribution, i.e. 37, 108 and 365 days of activity per year. The maximum income that can be expected annually is the sum of the days of operation that have a positive gross income -which Power System is actually not guaranteed due to the power conversion losses. Figure I.13 displays a typical E discharged distribution of the hours of charge or discharge of the ESS, illustrated with the data of Denmark
	DC/AC =95% West. Such a distribution does not differ so much depending on the bidding area. Two main DC/DC =95%
	Gather friends to get a capacity of 0.1MW to trade on the whole market periods of discharge can be observed either around midday or during the evening peak load, & # ' " 2 Figure I.12: Model used to characterize the AC-to-AC efficiency of the load shifting process using an ESS while most of the charge occurs during the night.
						!	#	" # $
	Observe the net annual income depending on the Figure I.14 provides finally the annual income that would have been expected per bidding area 6 annual rate of operation Become a day-ahead spot market 3 Distribution of battery charging and discharging hours -Denmark -West over the period 2001-2014. France appears as the country most able to generate the highest gross
	Adopt a strategy of performing one cycle of prosumer revenue, but requires a daily activation all the year long, to reach such a revenue. However, it can Bank each day the revenue 5 Charging Hours Discharging Hours induced by the daily Spread over 11 bidding areas. Trondheim 4 Lulea France be noticed that the revenue of France in the period 2010-2014 would have been reduced by ≈40% compared to the period 2005-2009.
	charge/discharge per day, width a depth of 7kWh.						Finland
	Charge the battery at 2kW, during the 3.5 cheapest hours of the day						Kristiansand	Malmo	Estonia Latvia
	Discharge the battery at 2kW,						DK West DK East	Lithuania
	during the 3.5 most expensive hours of the day						(	)	#
	The charging or discharging
	period can be composed of
	depending on the prices consecutives hours or not,	0	4	8	Hours of the day 12	16	20	24
	Hours of the day Figure I.13: Common periods of charge and discharge among the 24hr-day, for an optimal
	! " # $ % involvement on the day-ahead wholesale market (Denmark 2001-2014)
	Figure I.11: Structure of the Cost Benefit Analysis performed to assess the profitability of Tesla
	Powerwall involvement on the day-ahead spot markets where
	E cap is the storage capacity of the battery (in M W h)
	E purchased is the volume of electricity purchased to load the battery (in M W h)
	E sold is the volume of electricity sold at the battery discharge (in M W h)
	Income ESS =E sold × P sold -E purchased × P purchased P purchased is the mean price of the power purchased to load the battery (in e/M W h) (I.1) Income ESS =(η DC/DC × η DC/AC × E cap ) × P sold -( E cap η AC/DC P sold is the mean price at which the power discharged is sold (in e/M W h) ) × P purchased [in e/day] (I.2) η AC/DC is the efficiency of AC/DC conversion (in %)
	η DC/DC is the efficiency of DC/DC conversion (in %)
	η DC/AC is the efficiency of DC/AC conversion (in %)
	Income ESS/M W h = (η DC/DC ×η DC/AC )×P sold -( Income ESS/M W h is the daily revenue to be generated per MWh of ESS capacity (in e/M W h/day) 1 η AC/DC )×P purchased [in e/MWh/day] (I.3)

Day Ahead product (peak + off- peak) Intraday product Peak Load* Capacity Auction RR FRR (capacity price only) FCR VoltVAR mana- gement Congestion mana- gement Losses Saving

  .10: Summary of the sources of revenue of DER flexibility depending on the countries

						Capacity
	Energy
	contribution rate (in % of hrs per	Country
	year)
			Day-ahead agreement	Intra-day agreement	annual / quarterly agreement	annual / quarterly agreement	Day-ahead agreement	montly / weekly agreement	montly / weekly agreement
	30%	US						12.2 -20.2
	not documented US
	2.5%	DK East -FDR						52.5 -84
	10%	DK East -FNR						105 -193
	4%	France						148
	not documented UK						254
	8-15%	Germany						22 -70
	not documented France						148
	6-10%	Sweden					8.9 -12.3
		Sweden +
	6-10%	French distributed DR					17.3 -27.7
		bonus
	0% activation 33% allocation	Sweden Effektreserven				6.9
	0% activation 33% allocation	France				60
	8%	DK East			10
	1.4%	Lithuania			12
	0.8%	France			5 -10
	29%	France	30 -45
	29%	Baltics	30 -45
	29%	Denmark	20 -35
	29%	Finland	25
	29%	Sweden	12 -18
	29%	Norway	5 -15
	9%	France	12 -20
	9%	Baltics	12 -20
	9%	Denmark	10 -18
	9%	Finland	10 -15
	9%	Sweden	5 -10
	9%	Norway	<5
	Legend:	Values

in blue: calculated thanks to models that have been developped during this PhD work Values in black: obtained thanks to the literature review. The source of each of these values is presented in each Section 2.1 to 2.8 * The

  revenues of the day-ahead product are already included the specific revenue of the wholesale peak load. Thus, the revenue of the column Peak Load is relevant only is case of unique delivery of flexibility during Peak Load event.

	Suitable Revenue of DER assets (in k€/MW/yr)	Spot Market	Grid Operation Reliability
	Market liquidity
	Market gate closure		quarterly capacity agreement + day-ahead or intra-day call for activation
			20 -70

Bilateral wholesale contracts Power System Security & Stability

  TableII.1: Typical inertia constants H i of synchronous machines[START_REF] Kothari | Power System Engineering, 2e[END_REF]

	Type of machine		Inertia Constant H i
			(stored energy in MWs/MVA)
	Turbine generator
	Condensing	1.800rpm	6-9
		3.000rpm	4-7
	Non-condensing	3.000rpm	3-4
	Water wheel generator
	Slow-speed	< 200rpm	2-3
	High-speed	> 200rpm	2-4
	Synchronous condenser
	Large		1.25
	Small

Table II .

 II 2: FCR providing groups and units' minimum frequency accuracy and insensitivity requirement(Art 44(1),[START_REF] Entso-E | Network code on electricity balancing[END_REF])The Network Codes are a set of rules drafted by ENTSO-E under a mandate of the European Commission (EC). They aim to facilitate the har-

	Minimum accuracy of frequency measurement devices	CE,	GB,	10 mHz or
	used by the FCR providing units	IRE and NE	the industrial
				standard	if
				better
	Maximum combined effect of inherent frequency	CE		10 mHz
	response insensitivity and possible intentional	GB		15 mHz
	frequency response dead band of the governor of the	IRE		15 mHz
	FCR providing units or FCR providing groups.	NE		10 mHz

monisation, the integration and the efficiency of the European electricity market. Ten complementary codes are under development since 2011, to address the whole scope. The first of these ten networks codes, addressing Capacity Allocation and Congestion Management, has been adopted by EC on July 24, 2015. The concept of Primary Support claimed in this thesis (see Chapter III) is concerned with the Demand Connection Code, Electricity Balancing, Emergency and Restoration and especially the Load Frequency Control & Reserves code [ENTSO-E

  1. PRINCIPLE OF POWER SYSTEM BALANCINGTSO is named an LFC Area. For cost saving, the TSOs of a given synchronous area are allowed to regroup themselves within an entity named an LFC Block, at the scale of which the need for FRR is sized. Figure II.7 presents the architecture of LFC Blocks and LFC Areas across Europe. For operational ease, the TSOs of the same LFC Block can even delegate the activation of FRR to one of them: REE could then drive the FRR sources connected to REN's network(Figure II.7).In term of operation process, the TSO has to bring back the frequency within a predetermined bandwith -the Frequency Restoration Range(Figure II.8 and Table II.4 ) -within the Time to Restore Frequency(Figure II.11).

	Table II.4: Frequency Restoration Range applied by synchrounous area
	Frequency Restoration	CE	GB	IRE	NE
	Range	not used ±200 mHz ±200 mHz ±100 mHz

Table II

 II

	.5: Automatic Low Frequency Demand Disconnection scheme characteristics (Art 14,
	ENTSO-E [2015a])
	respect the following characteristics:
	Parameter	Values SA	Values	Values	Values	Measuring Unit
		Continental	SA	SA Great	SA
		Europe	Nordic	Britain	Ireland
	Demand disconnection	49	48.7 -	48.8	48.85	Hz
	starting mandatory level :		48.8
	Frequency
	Demand disconnection	5	5	5	6	% of the Total Load at
	starting mandatory level:					national level
	Demand to be
	disconnected
	Demand disconnection	48	48	48	48.5	Hz
	final mandatory level:
	Frequency
	Demand disconnection	45	30	50	60	% of the Total Load at
	final mandatory level:					national level
	Cumulative Demand to be
	disconnected
	Implementation range	±7	±10	±10	±7	% of the Total Load at
						national level, for a given
						Frequency
	Minimum number of steps	6	2	4	6	Number of steps
	to reach the final
	mandatory level
	Maximum Demand	10	15	10	12	% of the Total Load at
	disconnection for each					national level, for a given
	step					step

Table 1 :

 1 Automatic Low Frequency Demand Disconnection scheme characteristics

Table II . 6 :

 II6 Estimation of the FCR and wholesale marginal cost and incomes depending on the technology used for 1MW of installed capacity obtained by being involved in such service, that is closer to a capacity than an energy service. The behaviour of the French producer EDF confirms such a feeling: it maximizes the solicitation of hydro power for FCR supply. It enables first EDF to maximize its involvement of its nuclear units on the wholesale markets. It enables then EDF to spare water, and use hydro power on the wholesale market during high prices periods only.

		Income	Nuclear	Cost Gas CCGT	Gas Turbine
	Wholesale	30-60e/MWh	42e/MWh	82e/MWh	120 e/MWh
	FCR + 50% Wholesale	7.5-15e/MW/h + 15-30e/MWh	41e/MW/h 51e/MW/h 66 e/MW/h

  . Since 2015, RTE has been allowed to raise this amount up to 200MW without modification of the regulator statements. Even if only loads that are connected to the transmission system are eligible during the initial period of experiment, an extension to any load connected to the distribution grid is foreseen. Such extension follows the spirit of the Network Code and Load-Frequency Control and Reserves[ENTSO-E, 2013a]. CRE requests from RTE a feedback of the experiment by January 2016.These new FCR bids are not purchased directly by RTE but by any producer engaged towards RTE for the supply of FCR. Thus, these engaged producers are allowed to outsource the procurement of FCR they have to supply to the TSO. As of July 1st, 2014, RTE commited eight actors for the procurement and trading of FCR. Two of them are only power aggregators (Energypool, Actility) while the six other ows production assets (EDF, CNR, Engie, POWEO, ALPIQ AG and E.ON).

Table III .

 III 1: From frequency stability challenges to the functional and operational specifications of Primary Support

	-Need for the	-Need for FCR	-Need for FCR	-Need for FCR
	contribution of new	resources willing to be	resources having a	resources adapted to
	kind of reserves	activated more often to	shorter activation	islanded context, more
	-Make the FCR market economically as interesting as the	deal with the rising number of frequency deviation events	delay to handle high ROCOF	distributed among the networks
	other power markets
	-Involve Distributed	-Rely on DERs	-Rely on DERs whose	-Rely on DERs
	Energy Ressources	involved in	load modulation is	connected to the LV
	(DER) in the	interruptible processes	doable up and down	network
	Frequency		without delay neither
	Containment Process		recovery period, i.e. is
			reversible
	-Focus especially on		-Develop a process	-Rely on DERs
	Demand Response		where load modulation	activable on a wide
	(DR) contribution due		activation is not	frequency range down
	to business concerns		impacted by ICT	to the limit of UFLS
			delays	activation

Table III .

 III 2: IEC61850-7-420 parameters to be defined for the use of the Frequency-watt mode FWHZ

	Data Object name	Unit		Func-tional Con-straints	Data Attribut e	Type	Type's Attribut e name	Type's Attribute type	Com-mand Class Data	Key Example to address a given value involved in FWTH function:
	Function	string
	Platename	string
	Id primary
	support	string
	master
	Logical node of each load	string
			1:normal operation state, 2:blocked state, 3: normal
	WCtlHzEna	SPC	operation state, with results indicated as test result, 4:test with no impact on the process, 5: function is off.	ST	ctlNum INT8U		ctlNum: INT8U 0…254	SPC FWHZ1$ST$WCtlHzEna$ctlNum
			0: without hysteresis. 1: with hysteresis.					true: with
		SPG						hysteresis ; false: without
	HysEna			SP	setVal BOOLEAN		hysteresis	SPG FWHZ1$SP$HysEna$setVal
	ActDlTmms	ING	Time delay before FWHZ activation, in ms.	SP	setVal INT8U			SPG FWHZ1$SP$ActDlTmms$setVal
	ClcNxtTmms	ING		SP	setVal INT8U			SPG FWHZ1$SP$ClcNxtTmms$setVal
	Health	ENS (Health-Kind)		ST	stVal Enumerated		stVal: 0: .. ; 1: .. ; x: ..	ENS (Health-Kind) LLN0$ST$Health$stVal
		Hz		MX	mag AnalogueValue	f	FLOAT32	MV MMXU$MX$Hz$mag.f
								CODED Enum
								: good | invalid
								| reserved |
				MX	q	Quality		questionable	MV MMXU$MX$Hz$q
		s		MX	t	TimeStamp		INT32	MV MMXU$MX$Hz$t
		W		MX	mag AnalogueValue	i	INT32	MV MMXU$MX$TotW$mag.i
								CODED Enum
								: good | invalid
								| reserved |
				MX	q	Quality		questionable	MV MMXU$MX$TotW$q
		s		MX	t	TimeStamp		INT32	MV MMXU$MX$TotW$t
	MaxWout	W	Maximum total power that the load controlled is able to consume.	SP	setMag AnalogueValue	i	INT32	ASG FWHZ1$SP$MaxWout$setMag.i
	MinWout	W	Minimum total power that the load controlled is able to consume.	SP	setMag AnalogueValue	i	INT32	ASG FWHZ1$SP$MinWout$setMag.i
	HzStr	Hz		SP	setMag AnalogueValue	f	FLOAT32	ASG FWHZ1$SP$HzStr$setMag.f
	HzStop	Hz
				SP	setMag AnalogueValue	f	FLOAT32	ASG FWHZ1$SP$HzStop$setMag.f
		(%
	Wgra	Wmax)
		/Hz		SP	setMag AnalogueValue	f	FLOAT32	ASG FWHZ1$SP$Wgra$setMag.f
		(%
	HzStopWgra	Wmax)
		/min		SP	setMag AnalogueValue	f	FLOAT32	ASG FWHZ1$SP$HzStopWgra$setMag.f
	*SPC: Statistical Process Control
	*SPG: Single point setting CDC
	*ENS: Enumerated status CDC

Table III .

 III 3: Non native IEC61850-7-420 parameters involved in the threshold coordination algorithm

	Data Object name	Unit	Func-tional Con-straints	Data Attri-bute	Type	Type's Attri-bute name	Type's Attribute type	Com-mand Data Class	Key Example to address a given value involved in FWTH function:
	WgraMin	(% Wmax)/Hz		AnalogueValue	f	FLOAT32
	WgraMax	(% Wmax)/Hz		AnalogueValue	f	FLOAT32
	Fmin	Hz		AnalogueValue	f	FLOAT32
	Fmax	Hz		AnalogueValue	f	FLOAT32
	EnergyPrice	€/MWh		AnalogueValue	f	FLOAT32
	CapacityPrice	€/MW/h		AnalogueValue	f	FLOAT32
	Type	ENS		BOOLEAN
	idCEMS	ING	1,2,3,…,11,12,…,21,22,…101,102,etc.	INT32
	IsXMPP	SPG	0: HTTPS-connected DER, 1: XMPP-connected DER.	BOOLEAN
	IsRequester	SPG	0: HTTPS-link closed, 1: HTTPS-link open (= accepted for threshold update during the coming algorithm computation).	BOOLEAN
	BidPrice	€/MW/h	Effective bid price.	AnalogueValue	f	FLOAT32
			Lower limit of power contribution on the resultant power-
	PminCum	W	frequency caracteristic at the scale of coordination server's	AnalogueValue	i	INT32
			portfolio.
			Upper limit of power contribution on the resultant power-
	PmaxCum	W	frequency caracteristic at the scale of coordination server's	AnalogueValue	i	INT32
			portfolio.
	*SPC: Statistical Process Control
	*SPG: Single point setting CDC
	*ENS: Enumerated status CDC

Displaying Parameters:

Thresholds coordination algorithm >> Displaying tool of PrimarySupport Coordination Server

	Data description
	DER owner willingness parameters: DER Owner >> PrimarySupport Coordination Server
	Minimum Power-frequency slope physically compliant with the
	DER.
	WgraMin=10000 for DERs controlled in ON/OFF.
	Maximum Power-frequency slope physically compliant with
	the DER.
	WgraMax=10000 for DERs controlled in ON/OFF.
	Lower admissible limit of load modulation.
	Higher admissible limit of load modulation.
	Marginal Energy Price of the either DER offer or FCR/UFLS
	Marginal Capacity Price of the either DER offer or FCR/UFLS
	demand.
	0: DER offer. 1: FCR/UFLS demand.

Table III .

 III 4: Columns order of the 20 parameters introduced as inputs of the threshold & slope coordination algorithm

	Column Number:	1	2	3	4	5	6	7	8	9	10
	Data name:	MinWout MaxWout TotW Fmin	Fmax	WgraMin WgraMax EnergyPrice CapacityPrice	IsXMPP
	Column Number:	11	12	13	14	15	16	17	18	19	20
	Data name:	BidPrice	HzStr HzStop Wgra HzStopWgra PminCum PmaxCum	idCEMS	Type	IsRequester

of the System Frequency over 40 days in Continental Europe (one-second data)

  Figure III.12 provides the frequency dispersion observed over 40 days of data which have been monitored per set of weeks from April to August 2015. It can be observed that the frequency remains contained within the FCR dead-bandwidth ]49.98; 50.02Hz[ 59% of the time, while no frequency excursion out of an extreme bandwidth [49.87; 50.09Hz] occurred. Finally the frequency excursions are lower than ±50mHz above 99.15% of the time. These statistics of frequency dispersion are confirmed as well by[START_REF] Filip | Load: Participation to auxiliary services[END_REF] in TableIII.5 (sampling however unknown).

							4. VALUE PROPOSITION OF PRIMARY SUPPORT
	P OFF (f)	f Frequency (in Hz) 50 Repartition Figure III.12: Mean Frequency Deviation Dispersion Load 1 … Load i … Load 3 Load 2 UFLS FCR Range of operation Fb Fa 49.85 49.9 49.95 50.05 50.1 Occurance (in %) Mean Frequency: 49.9989 Hz Fmin:49.87 Hz Fmax:50.09 Hz	50.15	Chart requencyHistogram
			!
			!	"
			Daily
	#	Number of events				No Modulation
			49.85	49.9	49.95	50	50.05	50.1	50.15
		Figure III.11: Topology-related system-scale architecture
	events that would be induced for a DER, given that Primary Support targets a reaction time of
	the DER much lower than 10 seconds.
	Table III.5: Frequency dispersion occurrence in Continental Europe [Filip, 2011]
	Bandwidth Occurrence within the bandwidth	±20mHz ±50mHz ±100mHz ±150mHz 66.58% 96.77% 99.88% 99.999998%
						120

number of load modulation events expected depending on the frequency threshold

	49.85	49.9	49.95	50	50.05	50.1	50.15
			Frequency Threshold HzStr (in Hz)

  Both the Figures III.12 and III.13 enable a clear differentiation between two main bandwidths of frequency operation. A centred bandwidth lays on[49.95; 49.98Hz] ∩ [50.02; 50.05Hz]. A second one lays on[47.5; 49.95[∩]50.05; 51.5Hz]. On the one side, the involvement of a DER for an FCR delivery in the range[49.95; 49.98Hz] ∩ [50.02; 50.05Hz] would induce significant impacts for the DER. A wide disturbance of its business-as-usual process can be expected due to significant daily load curtailment, associated with an over-ageing of its power components due to an excessive number of manipulation per day. 800 manipulations would so occur per day for HzStr = 49.98Hz, inducing a daily interruption of five hours. On the contrary, the involvement of a DER for either UFLS or FCR delivery based within the range [47.5; 49.95[∩]50.05; 51.5Hz] would statistically have almost no impact on its business-as-usual process. An upper average of 20 events of modulation per day, for a daily interruption of 6 minutes only could be expected for HzStr = 49.94Hz. Such an assessment leads to a claim for the emergence of two main categories of reserves. A first category would supply FCR in the bandwidth [49.95; 49.98Hz] ∩ [50.02; 50.05Hz]. A second category would cover the other FCR and UFLS needs i.e. [47.5; 49.95[∩]50.05; 50.2Hz].Each of these bandwidths would rely on the involvement of DERs of different natures. For example, ESS and electric heating modulation could get involved in the centred range[49.95; 49.98Hz] ∩ The authors place the limit between the FCR-N and FCR-D at ±150mHz. By now, the Nordics TSOs proceed actually in the opposite direction, applying a droop of ≈ 7.5GW/Hz within [49.9; 49.98] followed by a droop of only ≈ 2.5GW/Hz within[49.5; 49.9] [ENTSO-E, 2007].[START_REF] Jomaux | Frequency containment reserves with large deadband[END_REF] see such market organization as an opportunity to enhance the involvement of DER in the FCR, while keeping a resilient power system. The commissioning of larger FCR-D at the expense of the FCR-N leads however to a more diffuse distribution of the frequency deviation(Figure III.15).The last characteristics of DER modulation, likely to interest a DER owner are the maximum and mean duration of each modulation event, depending on the threshold HzStr assigned.

[50.02; 50.05Hz]. Public lighting and industrial processes could then contribute on the exceptional range [47.5; 49.95[∩]50.05; 50.2Hz]. Two sub-FCR reserves are actually already operated in some European countries such as in the Nordics, where the Frequency Normal Containment Reserves (FCR-N) are activated in priority at the vicinity of 50Hz before being completed by additional Frequency Disturbance Containment Reserves (FCR-D) for the case of larger frequency deviation. Based on this assessment of widely different solicitations of the FCR depending on its frequency range of operation, Jomaux and De Jaeger [2015] go even further, by claiming for the commissioning of an FCR-D which has a steeper slope than the FCR-N (Figure III.14). Figure III.16 presents the outcomes of the model launched for this analysis. The mean duration have been obtained by averaging the length of all of the load modulation events observed at each threshold HzStr = {49.85; 49.86; ...; 49.98} ∩ {50.02; ...50.14; 50.15}. The maximum durations 122 4. VALUE PROPOSITION OF PRIMARY SUPPORT

  and a sub-layer of frequency threshold coordination, performed by a Java agent hosted by a[START_REF] Raspberry | Raspberry pi 1 model b+ -datasheet[END_REF]. The accuracy of the monitoring script embedded into the Arduino Uno has been compared and validated with the measurement outcomes of a Chauvin[START_REF] Arnoux | Technical report[END_REF] model 8334, ahead of its operational validation. A coordination agent is finally hosted by an independent computer to perform the task of coordination of Primary Support (layer 2). The energy boxes agents and the coordination agent communicate with one another through a local Ethernet network.

	Limit of the micro-grid				Coordination
	25W	25W	25W			agent
	E-box	E-box	E-box	4kW Synchronous Machine	DC Machine
		x5	50V/230V		,	if mcc
	Power &				mechanical
	frequency monitoring	600W to 900W 3-phases baseload	if ms	transmission

Response of the test bench face to a sudden loading on the system

													∆
													∆
													∆
													∆
		50.1
		49.9 50											With Reg-ulation (ON)	Without Regula-tion (OFF)
	Frequency (in Hz)	49.6 49.7 49.8		∆F d OFF	∆F d ON ∆R d ON						Number of tests Frequency drop ∆Fd observed on the field test (in mHz) Mean Drop Max Drop Min Drop Standard Dev. Mean Rebound Rebound ∆Rd ob-Max Rebound served on the field Min Rebound test (in mHz) Standard Dev.	15 455 514 307 50 72 118 12 28	12 547 584 492 29 81 115 54 17
		49.5											Number of occurences
		49.4		∆R d OFF				∆T d ON ∆T OFF d					Frequency drop delay observed ∆Td (sam-pling period: 260ms)	785ms 1045ms 1310ms Mean Delay	11 3 1 872ms	2 8 2 1046ms
		2	3	4	5	6	7	8	9	10	11	12	13
								Time (in s)

  1. VALIDATION OF DERS REAL-TIME MODULATION(LAYERS 0 & 1)

		Webservice		layer 2
		TCP/IP
	Raspberry PI		TotW
	Power	HzStr Wgra	MaxWout MinWout	layer 1
	Meter			Programmable
	PM3250			Logic Controller
				M171
	Steady-
	state
	relay
	Loads
	layer 0

Table IV . 1 :

 IV1 Semantic of the JSON messages exchanged between the DER controllers and the coordination platform

	Request for threshold and slope
	emitted by a DER controller

Table 3 -

 3 5: Period of market data acquisition per bidding area

  List of Patents analysed from EspacenetThe present patent review aims to highlight the patents, likely to provide ancillary services as such Peak Shaving, Voltage and especially Frequency control to the utilities, thanks to an architecture of Virtual Power Plant (VPP). All of the patents that propose an architecture such focus on the price service without consideration of physical constraints are considered as Out of scope. and not conflictual for Primary Support.

	n°R espacenet / google patent eference	Author	Description	Potential Conflict	Analysis
				A load shedding system for poorly interconnected		Notion of centralization that is painfull for us.
	5	NZ197667 (A) -AC supply load shedding with frequency drop	South eastern elec board	grids in case of Frequency drop. Seems to include a sensor remain unclear. Is it embedded in each load central control unit. The location of the frequency	High ++	But actually the patent does not claims for a real time updating of the frequency threshold.
				controller or not?
	6	US7595567 (B1) -Thermostat device with line under frequency detection and load shedding capability	Cannon technologies cooper pow [us]
	Patent Review
		Legend of the Patent identified as having an initial "High" IP conflict:	High IP conflict to solve Patent still to be read. Relative IP conflict IP conflict finally depreciated without Patent content reading No IP conflict left after the Patent content reading
	n°R espacenet / google patent eference	Author	Description	Potential Conflict	Analysis
		Issues for the specific Primary Support patent. Key Word: "load shedding frequency"
				A two steps processes: 1°) DR potential computation		Chinese registration, no details available in
	1	CN101895121 (A) -Low-frequency and low-voltage load-multi-agent technology reducing control method based on	State grid electric nanjing nari corp power res;	from local scale, up to global scale thanks to an ABM structure. Definition of the DR local indexes and the real time measured state a local controller that trigger a breaker depending on coefficient at the global scale and data forwarding. 2°)	High ++	English. Usage of Google Translate. Finally not a so constraintfull process according to R.Caire
				A system to define a droop line for local signal		Not so constraintfull for Primary Support,
				generator. A second local system that defines local		since no claims regarding distributed data
	2	US2012041612 (A1) -Emergency frequency load shedding scheme	Electric power res inst [us]	shedding priorities depending on the signal generator Frequency (ROCOF), to get better result. No claims received . A system based on two parameters: the value of the frequency and the Rate Of Change Of	High ++	sharing. However still an interesting method for Under Frequency Load Shifting using the frequency value and the first derivate!
				regarding central coordination.
				A device which monitors the level of load and send		Quite large correlation, and potential overlap
			Haier group co	load-shedding orders to household appliances through		with the hardware. However, any notion of
		CN202285400 (U) -	ltd; qingdao haier	the household gateways, in case of threshold passing.		ancillary services, neither ICT link with the
	3	Underfrequency load shedding	intelligent home	The process seems to be more appliances oriented	High	TSO/DSO.
		device based on household network	appliances	than power system oriented. It claims for appliances
			technology co ltd	turning-off for the appliance satefy (ageing
		US2004190211 (A1) -Load		protection). An automatic load shedding system in case of under-		Only a document on a chinese website
	4	control receiver with line under voltage and line under frequency	Cannon technologies, inc	voltage, without utility neither customer intervention, based on voltage threshold. Potentially the same with	High	(soopat.com) which quotes the patent just above: US2012041612. (n°1)
		detection and load shedding		frequency.
		Figure D.1: Patent review -Key words "load shedding frequency"

  Issues for the Global VPP development and the specific Primary Support patent. Key Word: "Demand Response"

		n°R espacenet / google patent eference n°R eference espacenet / google patent	Author Author	Description Description		Potential Conflict Potential Conflict	Analysis Analysis
		34 70 71	EP2408082 (A1) -Integrated DR for energy utilization WO2010093345 (A1) -Method and system for reducing feeder circuit loss using DR KR20080072045 (A) -Fuel cell power plant diverting air in response to low demand	Siemens corp [us] Accenture global services ltd [ir] Utc power corp [us]	Down meters located, for facilities usage: Optimization algorithm to select the best combination of DR ressources regarding probable criteria of price and volume to respect an objective of cost. Assume marginal cost of usage of each device (foregone production costs, etc.). Tool to reduce feeder circuit losses due to DR. Close to US2012173030 (A1). A fuel cell system, not grid connected at all.	Low High/ Medium Low	No concern of frequency-related ancillary Out of scope. services. Out of scope.
		35 72 36 73	WO2012161993 (A2) -Bidirectional DR control US2009098427 (A1) -Fuel Cell Power Plant Diverting Air in Response to Low Demand EP2525462 (A2) -DRMS and method with VAR support KR20090053487 (A) -Method of demand paging for codes which requires real time response and terminal FR2920937 (A1) -Information	Siemens corp [us]; bruschi paul j [us]; suresh sindhu Gen electric [us] Samsung electronics co ltd [kr]	Optimization algorithm to select the best combination A fuel cell system, not grid connected at all. of DR ressource regarding probably price and volume to respect the cost objective. DRMS for VAR support -question of inductives Real time response aspects for IT. Out of power system's scope. devices.		Low Medium Medium Low	The algorithm seems to focus only on one side of the market (prod. Or cons.) and not do Out of scope. include ICT links neither hardware development and probably no ancillary services issues. Not a real issue for VPP. Maybe an hardship for the VAR part of the ancillary services, Out of scope. developed in Dream.
			i.e. real estate related information,				Green Charge Networks sells B2B end-users
		37 74	US2012245744 (A1) -Networked Power Management and DR broadcasting method for e.g. mobile telephone, involves interrogating database to verify existence of	Green charge networks llc Edet christophe [fr]	Seems to be a private DRMS down meters located, responding to price signals. Web portal for mobile phone. Out of power system's scope.		Medium Low	systems for load management / DR.. Do not seem so ready to reach the VPP side -> mainly down meter, responding to price Out of scope.
			response to information demand,				signal.
			CN102592246 (A) -System and and delivering response to terminal		A system to first estimate the DR potential coming
		38	method for estimating DR in if response exists	Gen electric [us]	from several DR providers before sending a relevant		Medium
	electric power systems WO2013039554 (A1) -A system and a method for optimization and management of DR and distribute energy resources NZ589983 (A) -Managing DR events in a power distribution network US2007107016 (A1) -Interactive Multiple Channel User Enrollment, Purchase Confirmation Transactional System with Fulfillment Response Feature for n°R 39 40 75 eference espacenet / google patent Author Narayam amit [us]; schwarz henry [us]; singh rajeev kumar [us]; bhat vijay srikrishna [us]; bahl abhishek [us] Gen electric [us] Angel albert j [us]; bienstock terry s [us]; leeper barry [us]; weiner gary a [us]; eisenberg Video On Demand Cable Systems lance [us] 76 JPH08191283 (A) -Method for FR2907992 (A1) -Interrupted content downloading session i.e. 84 demand and response to information, reception equipment, Victor company ICT patent. No link with Power System. DR request. A system to manage and optimized DR, using ICT and control equipment, in order to reduce the DR cost participation A DRMS for utility network + an inside household module. Consumers aggregation, DR opportunities estimation depending on the number of DR events and number of opportunities available. Business oriented Video on Demand system (VoD) and cable. Description Potential Conflict Low of japan video-on demand session, recovering method, for set-top box, involves recovering session when and reproducing device Thomson licensing sas [fr] VoD patent. NZ260222 (A) -Video-on-	Medium Medium Low Out of scope. Seems to be an only business oriented systems, not answer by itself to ancillary services supply request in other way than with price signals… Both up and down meters located, but no ancillary services aspects. Out of scope. Analysis Low Out of scope.
		all channels are available, in demand service transmits packets of		system.
	85	An energy box, providing energy price data to the Alcatel australia VoD patent. response to session recovery selected video signals in response Low		Out of scope.
		request from remote server to received control signals from		consumer who can then choose manually the price
		WO2009085610 (A2) -WO2004040425 (A2) -Highly subscribers		threshold for consuming or not power. The system		Down meters located. Reduce grid aspect: a
	86	41 77 FR2691233 (A1) -Domestic and Achieving energy DR using price signals and a load control transponder programmable mac architecture for handling protocols that require industrial steam generator with precision timing and demand very short response times immediate response -has intermediate chamber connected to Cogia [fr]	Aclara power line systems inc [us] Enikia llc [us] A patent about steam generator. No link with Power includes a bypass the utility can use to shed directly a minimum level of load without previous consumer agreement to maintain the security of supply. This minimum leve of load has been defined in advance by the consumer. MAC architecture patent. System. Low		Medium Low Out of scope. bypass system for emergency load-shedding. Only potentially Peak-shaving embedded service. Out of scope.
		42 storage tank during demand periods WO2008079210 (A1) -On-demand alerting and response system and method TWI251996 (B) -System, network demand in a multi-level repair 78 media recording software for planning repairs in response to method, and computer-readable only, and to boiler only when idling.	Swn comm inc [us] inc [us] I2 technologies	An alert sending system, based on several ways of device per contact. The system allows to define in actors depending on conditions. advance scenario to contact a selected number of Media aspects. data transmission and at least one communication		Medium Low	channels system patented interest in a context of VPP usage for Ancillary services supply. Communication Out of scope. An alert sending system, potentially of
	29	High Load restoration strategies using DR after outage on the grid Load restoration strategies using DR after outage on Gen electric [us] ABB research ltd JP2012135193 (A) -System and method for managing cold load pickup using DR FR2848055 (A1) -Data e.g. telephone number supply system for telephone network, has server to EP2575230 (A2) -Systems and 43 methods for integrating DR with service restoration in an electric distribution system [ch] the grid. Consider an outage area and an area that 44 US2012066686 (A1) -DR system incorporating a graphical processing unit Honeywell int inc [us] A graphical processing unit to connect a large number 79 transform demand of user into request and delivering unit to France telecom [fr] An application for Phone Utilities. Transform a demand into a request. of DR units… distribute message to user through remains power supplied. The system seems to provide High/ Medium Medium/ Low Ancillary services supply: peak shaving aspects, but no Voltage neither Frequency support The patent definitely adresses ancillary services : black-start solution, not in conflict Medium/ Low Probably down meters located and quite far from our concerns but global platform maybe Low Out of scope. behind.. Difficult to assess. with Primary Support. It can remain in CN102377182 (A) -Load shed DR request building system without Advanced desired media in response to power margins from power supplied area and open selectives loads' breakers in the outage area to make power restoration easier. 45 system for DR without AMI/AMR Gen electric [us] Metering Infrastructure. Usage of randomizing Medium/ Low No real ancillary services aspects. demand conflict with the self-healing use case system distribution routine. FR2838593 (A1) -Internet developed within Dream. Down meters located system: An household Energy protocol remote
	30	WO2011008775 (A2) -System for providing DR services 46 maintenance/administration/file Honeywell int inc [us] US2012029711 (A1) -GENERATOR DR BEHAVIOR Gen electric [us] Global system for DR services supply, both up and down meters located. Maybe only a smartless structure defining communication protocols… Management System, including a power meter and a High/ Medium Human Machine Interface. Addition of a local generator to reduce utility's power supply depending Medium/ Low Down meters located. Out of grid aspects. Seems to be both up and down meters located, but probably empty! 80 transfer having client connection responding server demands with Gouget michel [fr] Internet protocols issues. No link with Power System. Low Out of scope.
	31 32 33	CN101505070 (A) -Electronic smart meter enabling DR and method for DR first demand containing US2004034484 (A1) -Demand-response energy management system 47 EP2367254 (A1) -DR system for Ls ind systems co ltd [kr] Solomita michael v, ; ewald alan, ; hebert j. Daniell, ; knapp r. Benjamin, ; control of electric consumers Samsung A smart meters having a communication module and embedded breakers to control the load depending on signals, mostly price oriented on predetermined threshold. An EMS, based on a network of home energy boxes. Local data harvesting to allow the utility to adjust rates so as to increase energy savings. Message sending by the utility to the consumers to initiate energy saving. electronics co ltd [kr] protocol/limiting response Down meters located system: An household EMS, to High/ Medium High/ Medium optimize and send DR level to household appliances. repetition. Medium/ Low Down meters located. Out of grid aspects. down meters located. Out of grid aspects! Breakers embedded however JP2001319109 (A) -Demand Business oriented only transmission and supply response ICT links between consumers / utility, probably close to a VPP structure. However 48 EP2365600 (A2) -DR method, computer-readable medium and Samsung electronics co ltd Down meters located system: a load-shifting system for high power consumption household appliances , Medium/ Low Down meters located. Out of grid aspects. 81 system using as information terminal portable telephone with Washitani Mobile phone application. Low Out of scope. kazuhiko any notion of breakers neither automatic system [kr] with an attention on consumer inconvenience. mail function and internet ancillary services. connecting function mcgurk greg NZ592295 (A) -System and method for scheduling DR events in a network Gen electric [us] A DRMS: management of DR suppliers in a context of power network: 1) aggregate cluster 2) estimation of the final benefit 3) DR event scheduling. High/ Medium Close to HONEYWELL INT INC patent (US2012271473) (review n°22). 49 MX2010008264 (A) -Intelligent metering DR. Down meters located system: Household appliance WO0057645 (A1) -Selectively Leviton DRMS (light, load, meters, etc.). A connection with 82 caching video to improve on-DR Infolibria inc [us] VoD patent. Low Out of scope. manufacturing co Network Operation Center of other utility is available time [us] for real-time basis control of a building. GB2337912 (A) -Video on Daewoo
		83	demand system with adaptively	electronics co ltd			Low	Out of scope.
			controlled response stand-by time	[kr]

Figure D.3: Patent review -Key words "Demand Response " 1/5 Medium/ Low Down meters located. Out of grid aspects.

Figure D.4: Patent review -Key words "Demand Response " 2/5 Figure D.6: Patent review -Key words "Demand Response " 4/5

  1 er janvier 2016 de la directive européenne n • 2010/75/U E imposant la fermeture des unités industrielles les plus polluantes, centrales électriques comprises. Au delà du risque sur la sécurité

	Unique Interconnection	Top-down			Top-down
	subjected to tripping	power flow			& down-
	UFLS	0.48 pu			0.48 pu	only flows
	efficiency		~0.52 pu			~0.38 pu
				Reduction of UFLS load
				disconnection capacity
	Kuching		UFLS relays	Kuching		UFLS relays
	Island			Island
	RES-E penetration		1pu = 282MVA	30% RES-E penetration	0.14 pu	1pu = 282MVA

The present section does not consider however the trading platforms of pooling, that enable the producers to declare power bids with additional technical constraints like ramp-up, ramp-down or must-run delay. Such pools are still used in some locations to make the unit commitment of power assets closer to the physical limitation of the units.

BUSINESS OPPORTUNITIES OF DER FLEXIBILITY

values of peak load provided in TableB.[START_REF] Ockert | Load control receiver with line under voltage and line under frequency detection and load shedding -us patent 7[END_REF]

The market turnover considered is the product of the hourly volume times the hourly spot price

Not enough direct weather data from Grenoble were available. This is why Grenoble data have been converted from the set of Lans en Vercors data

This thesis has been mainly written during Autumn 2015. Given that ESS sector has evolved so quickly by this date, the present statement would probably become depreciated by 2020 in some conditions

In GB Generators must even remain connected

20s at 47Hz

"The vertical grid load is the corrected sum of all transfers from the transmission network in the TSO's control area via directly connected transformers and lines to distribution networks and end consumers." source: https://www.tennettso.de

STATE OF THE ART OF DISTRIBUTED FREQUENCY CONTROL

an initiative close to Primary Support and involving Schneider Electric USA seems to be in pipes (information from March

2015). This one cannot be referenced here due to Intellectual Properties issues.

CONCEPT OF PRIMARY SUPPORT Figure III.8: Thresholds & slopes coordination algorithm used by Primary Support

observed on Siemens' booth at Cired 2015

également appelé Réseau Electrique Intelligent (REI) par le ministère français de l'industrie

la dégradation du plan de protection induite par le déploiement de GEDs constitue toutefois un autre domaine pour lequel la coordination de GEDs n'est pas à même en soit de solutionner le problème

Operational flow of data

The process of operation is composed of two sub-processes: a one-shot initialization process followed by a continuous process operated in loop.

The initialization process enables the definition of the four parameters of global behaviour of each DER (W CtlHzEna, ActDlT mms, ClcN xtT mms and HysEna). Such a step can be performed either remotely on the DER controllers which are IEC61850-native or manually on-site for the non-native IEC61850 DER controllers. Thus, it is assumed that the DER controllers connected to a coordination platform of Primary Support using an HTTPS link cannot be configured remotely. Indeed, the communication needs to be initiated from the DER side to perform these updates, that compromises the modification of these parameters whenever the operator of the coordination platform wants. This step of initialization is represented by the arrow of label "0 -Initial WRITE" in Figure III.7.

The continuous process operated in loop aims then to keep up-to-date the operational behaviour of each DER. In other words, it aims at updating periodically the threshold HzStr and slope W gra of each DER in order to keep a behaviour that guarantees the delivery at the system scale of a resultant power-frequency characteristic that complies with a predetermined demand.

Such a continuous process first relies on a permanent monitoring of the coordination server to messages sent from DER controllers. The messages are handled by the coordination platform if and only if they contain at least the dataset {M inW out, M axW out, T otW } and have been sent by a DER controller which belongs to the portfolio of aggregation of the coordination platform. These messages are represented by the arrow of label "1 -Periodic REPORT" in Figure III.7.

Each reception of a compliant message induces then the immediate computation of the algorithm in charge of the coordination of the thresholds and slopes of the DERs of the portfolio. In power market terminology, such task is named the market clearing. The sub-task is presented by the large blue arrow labelled 2 -Algorithm computation in Figure III.7.

The clearing is immediately followed by the returning of the clearing outcomes to all of the DER controllers which are reachable. Such a returning of the updated FWHZ parameters is represented by the arrow labelled 3 -WRITE in Figure III.7 and constitutes the last sub-task of the loop. The DERs which are considered as reachable are all of the DERs driven by a DER controller which is connected to the coordination platform through an XMPP link. Last but not least, if the algorithm computation has been induced by the reception of a message sent by an HTTPS-connected DER controller, all of the DERs that are controlled by this DER controller are considered as reachable as well. Indeed in such a case, it can be stated that the HTTPS link that has just been initiated will remain open until the end of the algorithm computation i.e. the computation time remains quicker than the time-out of the HTTPS link previously-opened. According to the previous notion of reachable DERs, it must be clarified that the algorithm of threshold coordination updates only the threshold and slope of the reachable

CHAPTER IV

Field Deployment and Validation of Primary Support

Chapter IV

Field Demonstration and Validation of Primary Support

The present chapter details the activities performed to test and validate the concept of Primary Support, presented in Chapter III. The works performed in this direction aimed to validate the Primary Support concept in real conditions and identify operational issues that will have to be solved before thinking of scale-1 industrial deployment.

The first developments presented in Section 1, lead to the realisation of tests on micro-grid test bench and on physically simulated interconnected network, with the objective to assess the speed of operation of both the DER and their controllers i.e. the layers 0 and 1 of Primary Support.

A second part of developments presented in Section 2, leads to the commissioning of a preindustrialized coordination platform i.e. the layer 2 of Primary Support. The creation of such advanced platform enables to think at the connection of a quite significant numbers of DERs to Primary Support environment.

A third set of developments, presented in Section 3 supposed upon the deployment of the Primary Support concept in a critical industrial environment: the international airport of Milano Malpensa. Operational and legal difficulties that occurred on the airport operator side have however led to the cancellation of the demonstrations in this field test.

1 Validation of DERs real-time modulation (Layers 0 & 1)

ON/OFF DER's response on a lab micro-grid

The first physical validation of Primary Support has been performed on Grenoble INP's PREDIS platform [START_REF] Hadjsaid | Decentralized operating modes for electrical distribution systems with distributed energy resources[END_REF][START_REF] Hadjsaid | Integrated ict framework for distribution network with decentralized energy resources: Prototype, design and development[END_REF], by deploying energy boxes as DER controllers on a reduced scale power system. The response of the pool of DER controllers in both steady-state and disturbed situations have been assessed. The outcomes are presented below, following the description of the field test and of the protocol of tests. As soon as the PLC takes the decision of load shedding, both the transmission of the shedding order along the 0/5V analog bus and the effective shedding of the load are almost instantaneous. Indeed it is not possible to differentiate the specific shedding of each of the loads that are controlled by the same PLC with measurement sampling of 50ms. Only the fan can be identified more easily. In Figure IV.9, the frequency drop induces slight oscillations of the fan's motor, inducing slight variation of its power consumption. In Figure IV.10, its power consumption rises progressively while the screw speeds up.

Consequently the delay of response is induced by the sending of frequency value from the power meter to the PLC i.e. is induced by the Modbus delay. The use of Modbus complies with large-scale power system but is not doable in micro-grids. The effective frequency range of contribution of a given DER can be identified at the intersection between the green resulting offer curve and both the lower and upper bounds of the range of power contribution of the DER, plotted through a yellow shadow. The HzStr threshold of the DER corresponds to the x value of the intersection between the green resulting offer curve and the lower bound of the range of power contribution.

Last but not least, the height of each step of the resulting offer depends on the flexibility (T otW -M inW out) of each DER selected for contribution.

The Figures E.1 to E.5 provided in Appendix E, details all of the other synoptics of the coordination platform, that enables the input of the FCR and UFLS bids and the definition of the admissible behaviour of each DER of the portfolio of aggregation. A third concern addresses the potential competition for Primary Support from bulk generation assets in the delivery of FCR. Despite this PhD work claiming a theoretical lack of competitiveness of historic assets in the supply of FCR, the effective strategies of unit commitment of the utilities remain unclear and have not been deeply investigated during this PhD work. Indications have shown that producers appear reluctant to modulate up and down their power production in real-time, likely to induce an over-ageing of their assets. Nonetheless, no clear declaration from the utilities regarding their effective wish to outsource the supply of FCR has been observed in the literature. Faced with such unknowns, one positioning of Primary Support would be to address in priority off-grids and micro-grids systems. In such grids, the marginal cost parity of PV+ESS with bulk generation would be reached soon. The marginal cost of on-field PV reaches levels close to ≈50e/MWh in the Middle East and a minimum cost of 70e/MWh have been reached for the first time in France in 2015. In parallel, the marginal cost of gas turbines is larger than 100e/MWh [IEA, 2010]. In these conditions, and thanks to the cost reduction of ESS, the association PV+ESS would be competitive. Hence the phasing-out of bulk generation assets to the benefit of power electronic-connected RES-E such as PV would occur, challenging the system stability. Faced with such conditions, the architecture of supply of ancillary services such as Primary Support would be well adapted and ease to deploy.

Finally, the palliatives identified in response to the three concerns previously mentioned lead to the conclusion that Primary Support should continue beyond the end of this PhD thesis.

Gaspard Lebel

Appendices

Appendix A

Axes of research addressed during the PhD work

Assess the effective value that could be caught by DER operators by performing wholesale-prices driven peak-load management.

Idea Driver

• Analyze the day-ahead Spot market data of 10 different Nordics and Baltics price areas, over 14 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). • Plot Spot Price / Load characteristics • Compare these ones with Gross Product / Load characteristics • Identify the presence of niche or mass market for distributed load modulation for wholesale purpose.

Principle of Study

Aggregators focus historically on business model driven by peak-load management, promoted by the System Operators on dedicated ancillary services markets. So could wholesale market actually handle this issue instead? , over 14 years (2001-2014).

Spot Market volatility analysis

Principle of Study

European hourly metering commissioning affords incentives towards innovative power consumption strategies that are made doable by smart thermostat and energy boxes penetration.

DLVM

Un projet en construction:

Concours ERDF 2015

Method of Day-ahead spot market data analytics

The present section describes the method of data mining and data analytics that have been used to assess the profitability of DERs flexibility into the day-ahead spot markets. The assessments performed at Sections 2.6.2 and 2.8.1 rely on the presented method.

Data Harvesting

The data analytics performed address up to sixteen bidding areas spread over eight countries.

France, as well as the four Nordics (Denmark, Sweden, Norway, Finland) and the three Baltic (Estonia, Latvia, Lithuania) countries have been studied

The selection of the countries has been driven by two aspects: the wish to benchmark countries having different history of market deregulations and different energy mix and the ease of access to the data. The access to the data has finally been the most orienting aspect. Nord Pool Spot [2015] provided both the hourly prices and volumes exchanged on the Nordics and the Baltics. [RTE, 2015b] provided the data of the French consumption, used as volume data in the model. Epex Spot SE [2015a] provided the French price data.

The period of study led from up to 14 years depending on the bidding areas (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014), with a granularity of one hour. Pool Spot, 2013]. As a result part of the Norwegian data has not been computed not to distort the benchmark among the bidding areas.

At the end, almost three millions of data have been collected and computed. [D3] price elasticity per bidding area, for a representative period of four years. Morever, the volume axis is expressed in percentage of the peak load, that enables to compare two bidding areas of different size. The path that enables thee creation of these plots is represented by the red arrows in Table B.2.

Analytics Produced

The eighteen types of data are presented below from the index : 2001-2014, 2001-2005, 2006-2010 and 2011-2014.

Collection of data: 1 data/MW/series. 4 series/bidding area Coordination de GEDs pour la fourniture de services systèmes temps réels.

Résumé Dans le domaine de la production d'électricité, les politiques entreprises pour lutter contre le changement climatique reposent communément sur le remplacement des moyens de production fossiles et centralisés par de nouveaux moyens de type renouvelables. Ces énergies renouvelables sont en grande partie distribuées dans les réseaux moyenne et basse tension et sont le plus souvent intermittentes (énergies éolienne et photovoltaïque principalement). Les gestionnaires de réseaux s'attendent à ce que ce changement de paradigme induise des difficultés conséquentes dans leurs opérations. Les mondes de la recherche et de l'industrie se sont ainsi structurés depuis le milieu des années 2000 afin d'apporter une réponse aux problèmes anticipés. Cette réponse passe notamment par le déploiement de Technologies de l'Information et de la Communication (TIC) dans les réseaux électriques, des centres de contrôle jusqu'au sein même des moyens de production distribués. C'est ce que l'on appelle le Smart Grid. Parmi le champ des possibles du Smart Grid, ces travaux de thèse se sont en particulier attachés à apporter une réponse aux enjeux de stabilité en fréquence du système électrique. En effet, celle-ci est mise en danger par la réduction anticipée de l'inertie des systèmes électriques et la raréfaction des moyens de fourniture de réserve primaire (FCR), auxquels incombent le maintien de la fréquence en temps réel. En vue de suppléer les moyens de fourniture de réserve conventionnels et centralisés, il a ainsi été élaboré un concept de coordination de charges électriques délestables distribuées, qui se déconnectent et se reconnectent de manière autonome sur le réseau au gré des variations de fréquence mesurées sur site. Ces modulations de puissance répondent à un schéma préétabli qui dépend de la consommation électrique effective de chacune des charges. Ces travaux ont été complétés d'une étude technico-économique visant à réutiliser cette infrastructure de coordination de charges délestables pour la fourniture de services systèmes ou de produits de gros complémentaires. Ce travail de thèse réalisée au sein des équipes innovation de Schneider Electric et du Laboratoire de Génie Electrique de Grenoble (G2Elab), est en lien avec les projets Européens EvolvDSO et Dream, financés dans le cadre du programme FP7 de la Commission Européenne.

Mots clés Réseaux Electriques Intelligents (REI), Générateurs d'Energies Distribués (GEDs), Centrale

Virtuelle, Services Systèmes, Stabilité du Système Electrique, Réserve Primaire, Effacement Diffus.

Distributed Energy Resources coordination toward the supply of ancillary services in real-time Abstract The climate change mitigation policies in the power generation industry commonly rely on the replacement of bulk generation assets by Renewable Energy Resources (RES-E). Such RES-E are largely distributed on the medium and low voltage grids. Most of them are intermittent such as photovoltaic and wind power. System Operators foresee that such a new power system paradigm will induce significant complications in their operations. Hence, the research and industrial communities structured themselves from the mid-2000s to find solutions for these coming issues. The solutions rely notably on the deployment of Information and Communication Technology (ICT) in power systems assets, from the Network Operations Centers (NOCs) to Distributed Energy Resource (DERs) units. The aforementioned technologies are collectively described as the Smart Grid. Among the range of possibilities of the Smart Grid, this Ph.D work targets the development of a solution to handle the issue of frequency stability of the power system. Such stability is endangered by the combined loss of inertia of the power system and the phasing-out of conventional assets which were traditionally responsible for maintaining the frequency in real time through the supply of Frequency Containment Reserve (FCR). The concept developed relies on a process of coordinated modulation on the level of DER loads, which evolve depending on the system frequency measured in real time on-site. The strategy of modulation of each DER follows a pattern which is determined at the scale of the portfolio of aggregation of the DER, depending on the effective level of flexibility of the DER at normal frequency (i.e. 50Hz in Europe). This work is completed by a cost benefit analysis that assesses the opportunity of sharing the previous infrastructure of coordinated modulation of DERs for the supply of complementary ancillary services and wholesale products. This thesis was conducted within Schneider Electric's Innovation team and the Grenoble Electrical Engineering Laboratory (G2Elab