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supply of ancillary services in real-time
Gaspard Lebel
To cite this version:
DOCTEUR DE L’UNIVERSITÉ GRENOBLE ALPES
Spécialité : Génie Electrique
Arrêté ministériel : 7 août 2006
Présentée par
Gaspard LEBEL
Thèse dirigée par Raphaël CAIRE et codirigée par Nouredine HADJSAID
préparée au sein du G2ELab - laboratoire de Génie Électrique de
Grenoble
dans l'École Doctorale Électronique, Électrotechnique,
Automatique et Traitement du Signal
Coordination de GEDs pour la fourniture de
services systèmes temps réel.
Distributed Energy Resources coordination
toward the supply of ancillary services in
real-time.
Thèse soutenue publiquement le 26 avril 2016, devant le jury composé de :
M. Geert DECONINCK
Professeur, Katholieke Universiteit Leuven Président
M. Didier MAYER
Professeur, Mines PARISTECH Rapporteur
M. Hans EDIN
Maître de conférence, Kungliga Tekniska Högskolan Rapporteur
M. Sébastien HENRY
Directeur SI & Télécommunications, RTE Membre
M. Matthieu TERENTI
Délégué Grand Projet Territorial, Enedis Membre
M. Alain GLATIGNY
VP Innovation Smartgrid Utility, Schneider Electric Encadrant
M. Nouredine HADJSAID
Professeur, Université Grenoble Alpes Co-Directeur
La lecture de cent-cinquante pages est somme toute prenante. Un déplacement à Grenoble au mi-lieu 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 hon-neur 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 amuses-toi ». 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
col-lègues 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.
Christophe, Philippe, Michel, Jean, Jean-Yves, Benoît, Romain, Gilles, Sandeep, Olivier, Bernard, Rodolphe, Yann et Benoît.
Mes pensées vont ensuite aux équipes techniques du G2Elab, dont la disponibilité et les com-pétences feront pâlir tout personnage critique du service public qui osera s’y confronter. Pro-totypage rapide, Mécanique lourde, câblage industriel, électronique, informatique industrielle, simulation temps-réel : tout y est, pour permettre de grandes avancées. Cédric, Thierry, Kamel, Gérard, Florian, Antoine et Jacques, je me fais tout petit devant votre expertise.
Karel. Tom. Sindhu, Christian. Guillaume, Hector. Naila, Dien Hoa. Théo, Maxime, Matthieu. Timothé, Loann, Luis, Brida, Guillaume, Renaud, Olivier. Samuel, Gauthier. Gabrielle, Paul, Clément. Nicolas, Lucile. Aurore, Wilhem. Autant de nouveaux projets d’ouvertures étudiants lancés avec votre aide que de phrases, avec de belles réussites à la clef. Ce fut un plaisir de vous encadrer.
Mains invisibles des succès du laboratoire, je salue également la grande disponibilité du pôle administratif. Florence, Elise, Sylvianne, Valérie, Aurélie, Cathy, sans vous, nous ne ferions pas grand-chose.
Je salue également les équipes d’INPG Entreprise SA pour leur flexibilité aux côtés d’Elise face aux déplacements de dernières minutes, aux concours improbables et autres particularités dont je me suis fait champion – ce que n’étonnera guère amis et famille.
Parlant d’équipe, je me tourne maintenant vers la team Dokever, pour m’avoir fait prendre l’air et permis de jouer au docteur 4 ans avant de le devenir vraiment aujourd’hui. Parier sur un ingénieur pour diriger des médecins et quelques milliers de trailers ou cyclistes, il n’y avait que les Clooneys’ brothers pour oser! Je vous en remercie et espère rester le plus longtemps derrière vous avec le plus de chuchotements possibles en réunion de courses et PC. Claire, Marion,
Marjolaine, France, Florence, Théo, Fred, Antonin, Paul, Gilles, Pierre, Hervé, Damien, Cyril,
Bruno, Patrick chaque instant peu reposant passé à vos côtés est un plaisir.
Dans la continuité des amis, arrive maintenant la sphère grenobloise. Manue pour m’avoir converti au principe du sinus et pour ton accompagnement sans faille de la chute au renouveau, de Séville 3am à Athènes 6am en passant par Strasbourg, Milan, Eindhoven, Amsterdam et
Chamrousse alt 1721, 20◦ Ouest. Merci. Te pour tes chemises – et oui maintenant on peut parler
recette de topinambour qui plaira tant à Jean Louis. Audrey parce que tu ne manges pas que des graines. Rozenn parce que tu ne manges pas que des graines. Jérôme pour ta simplicité piquante. Cédric, parce que un jour on réussira à aller à l’Etendard ! Léo parce qu’avec tes deux mains, tu referais le monde. Arnaud, pour avoir lu les sms que je ne saurais te lire. Tes racines latines sont si précieuses. Amandine pour ce soutien mutuel précieux, alimentée par ton adresse légendaire. Clem parce qu’il me reste 12 ordis, 8 téléphones et 3 vélos à réparer – et je ne compte pas le camion poubelle LEGO Technic que ta sœur a très probablement cassé par jalousie en cet été 2003 – alors cela vaut bien des remerciements en avance. Fny pour être l’inspectrice gadget de demain: « Comment optimiser le procédé de guérison de dix tendinites du genoux droit avec un rouleau à pâtisserie, un four à pain, un bouquin de suédois, une sorbetière et plaque d’immatriculation coincé dans un virage ? Vous avez toute une vie. Question suivante ». Poline pour être dorénavant l’avenir du service public – à contrat privé, et pour ces folles soirées électriques place des Tilleuls dont je me souviendrais très longtemps. Clark pour avoir pris la responsabilité de Poline au quotidien, fort de tes années d’apprentissage empirique du Coco. Coco parce que ton audace artistique et technologique est grande et inimitable. Anaïs parce que si je devais parier sur quelqu’un, je n’hésiterai pas longtemps. Mathieu parce que Grand Prof tu seras. Olive et Cyril parce qu’il est difficile de mettre des mots sur tout ce que vous m’apportez. Peter pour tes leçons de management autour d’un Maria tout sec à Abisko. PB parce que tu as bien raison, je suis un vrai merdier! Bastien, pour cette motivation à toute épreuve. Yo parce que le rouge et le makestorming, c’est la vie. Sandy pour être une valeur sûre de l’accueil et de la simplicité. Macha, parce que qui sait, ta petite maison solaire sera peut-être ma mascotte de demain. Emeline pour penser à toi à chaque fois que je vois une pile. Thib pour ces petits pas de dance en soirée, synonymes de gaîté. Philémon, parce qu’après tes sondages dans les lacs népalais et dans l’Isère gelée, rien ne t’arrêtera. Ched pour être allergique
à ses lunettes [Lozé et al., 2008] et ta science folle et rigoureuse (P.S. j’ai encore du foin pour
ton prochain lapin). Audrey parce que ça y est, Arnaud est reparti, on a du répit! Romain pour cette ponctualité faite montre suisse. Teddy pour ces sourires dans l’open space, debout sur tes béquilles. Laura, classe, rigueur et gaîté sont tes homonymes. Sam pour ton audace en toute simplicité. Nath, Nico et Isa pour votre entreprise de déstabilisation de votre com’ #YCC. Max pour ces après-midi en Peugeot 102, pré-Kyoto. Nico pour tes conseils décomplexés et ton agilité reconnue ! Benoit, les Lumières étaient à la fois philosophes, scientifiques, poètes, artistes. Tu en prends le chemin. Robin, Fif, Jason, Martin, parce que vous êtes beaucoup trop vous-mêmes ! Johanna pour avoir refusé de me garder en fond d’écran. Johanna, parce que sur le Roc échelle-1 je n’accepterai qu’un dossard dessiné à la main. Juliette, pour cette future entreprise de troc unidirectionnel et pour cette logistique du dernier kilomètre qui passe forcément par Meylan. Aurélie pour être nettement plus efficace que le reste de la troupe ! Basile, pour ton enthousiasme de Start-upper. Marco, grand frère des années skis. Marie pour cette insouciance retrouvée. On s’est donné rendez-vous dans dix ans entre château de sables, hippopotames et crocodiles. . . Johanna, Federica, Laura, Simone and Paolo to have made Erasmus come true. See you soon in Bucharest?
sur ces théâtres devenu tristement inaccessibles. Curiosité, ouverture culturelle et scientifique assurée. Je n’ai jamais été capable de répondre à la question mainte fois posée « Pourquoi veux-tu faire une thèse ? ». Intrinsèquement, une partie de la réponse se trouve là. Une autre partie, à La Source et à La Fontaine. A ma maman, pour nous avoir été la clef de voûte de cette enfance peu commune ; pour lui au fond, traverser les frontières fut un jeu, pour toi ce fut des choix. Merci. A mes frères et belles-sœurs pour cette organisation kolkhozienne en perte de vitesse, si souvent sujette aux revirements météos du patriarche.
En tout, vous êtes soixante à avoir contribués à ces sobres travaux de thèses par vos discussions de café, vos réflexions, vos retours et relectures, vos facilités administratives et vos travaux de prototypages. Si la mode – dans laquelle je m’inscris – est à l’entreprenariat, il ne faudrait tout de même pas oublier que seules des équipes constituées ont permis de bâtir de grandes avancées technologiques depuis la Révolution Industrielle. La recherche est collective.
Dans cette droite ligne, je me positionne certes naïvement mais fermement pour que les rancœurs au sein des équipes, entre les équipes et entre les institutions n’aient plus leur place dans la recherche publique soutenue par les contribuables français et européens. Enfin, j’espère à l’avenir ne plus plier devant la bureaucratie de la recherche européenne. Combien de lignes qui ne seront jamais relues avons-nous tous écrit ? Combien d’heures perdues à justifier de l’avancée de nos travaux, au lieu de les faire avancer concrètement? Pourquoi ne pas simplement évaluer cette avancée sur le nombre de communications scientifiques et industrielles, qui sont par nature directement évaluées par nos pairs ?
Avant-Propos. . . vii
Contents . . . xi
List of Figures . . . xiv
List of Tables . . . xix
General Introduction 1 1 From Geopolitics to Smart Grid . . . 1
1.1 Geopolitics incentives . . . 1
1.2 Bankruptcy of gas-fired assets . . . 3
1.3 Migration toward Distributed Energy Resources (DERs) assets . . . 3
2 Structure of the thesis . . . 5
3 Publications . . . 5
4 Axis of research and of inspiration of the present thesis . . . 6
5 Main contributions . . . 7
6 Glossary of Important Terms and Abbreviations . . . 7
I Opportunity of DER involvement in power markets 17 1 Overall market review . . . 17
1.1 Wholesale electricity markets . . . 17
1.2 Ancillary services products . . . 19
2 Business opportunities of DER flexibility . . . 21
2.1 Grid losses savings . . . 22
2.2 VoltVAR & congestion management . . . 23
2.3 Frequency Containment Reserves (FCR) . . . 24
2.4 Frequency Restoration Reserve (FRR) . . . 25
2.5 Restoration Reserves (RR) . . . 25
2.6 Peak load . . . 27
2.6.1 Capacity auctions and markets . . . 28
2.6.2 Handling of the peak load by the day-ahead spot market . . . . 28
2.7 Intra-day spot markets . . . 30
2.8 Day-ahead spot markets . . . 31
2.8.1 Day-ahead market data analytics . . . 32
2.8.3 Domestic space heating optimisation using day-ahead spot prices 38
2.9 Long-term wholesale markets . . . 43
2.10 Market coupling capacities . . . 43
2.11 Bilateral wholesale markets . . . 43
3 Scenario of DER flexibility assets sharing . . . 43
4 Conclusion of Chapter I . . . 47
II Theory and challenges of frequency stability 51 1 Principle of power system balancing . . . 51
1.1 Power system balance & frequency deviation . . . 51
1.2 System reliability & blackout . . . 56
1.2.1 Jeopardize of system reliability . . . 56
1.2.2 Blackout . . . 57
1.2.3 System security, stability & reliability . . . 58
1.3 Balancing reserves activation in response to a frequency deviation event . 59 1.4 Frequency Containment Process . . . 62
1.5 Frequency Restoration Process . . . 66
1.6 Replacement Reserve Process . . . 68
1.7 Under Frequency Load Shedding (UFLS / LFDD) . . . 69
1.8 Contribution of self-regulation of load to power system stability . . . 71
2 Challenges of the frequency containment defence plan . . . 72
2.1 Degradation of conventional FCR providing units’ availability . . . 73
2.1.1 Periodic non-availability of conventional generation . . . 73
2.1.2 Loss of business interest in FCR supply . . . 74
2.2 Degradation of the frequency quality inducing larger FCR solicitation . . 77
2.3 Degradation of the system inertia . . . 78
2.4 Degradation of UFLS scheme efficiency . . . 80
3 Conclusion of Chapter II . . . 84
III Innovation Concept of Primary Support 89 1 Primary Support: a response to the challenges of system stability . . . 89
2 State of the art of distributed frequency control . . . 91
3 Concept of Primary Support . . . 94
3.1 Multi-layers process . . . 94
3.2 Targeted DERs - layer 0 . . . 94
3.3 Real-time process - layer 1 . . . 96
3.4 Coordination of the distributed thresholds and slopes - layer 2 . . . 99
3.4.1 Operational parameters . . . 100
3.4.2 Operational flow of data . . . 106
3.4.3 Threshold & slope computation algorithm . . . 107
3.4.4 Definition of the slope of the DERs controlled in ON/OFF mode 113 3.5 Cooperation between two different coordination platforms - layer 3 . . . . 113
4 Value Proposition of Primary Support . . . 118
4.1 Robustness . . . 118
4.2 Adaptability to topology-dependent architecture for regulated operation . 118 4.3 DER modulation acceptance by DER owners . . . 119
5 Conclusion of Chapter III . . . 124
IV Field Demonstration and Validation of Primary Support 129 1 Validation of DERs real-time modulation (Layers 0 & 1) . . . 129
1.1 ON/OFF DER’s response on a lab micro-grid . . . 129
1.1.1 Field Test . . . 130
1.1.2 Protocol of tests . . . 131
1.1.3 Illustration of frequency stabilization in steady-state operation . 131 1.1.4 Validation of the agent-based platform time-response . . . 132
1.1.5 Validation of the droop curve conformity . . . 132
1.2 ON/OFF DER’s response on a interconnected system . . . 133
1.2.1 Field Test . . . 134
1.2.2 Protocol of tests . . . 135
1.2.3 Validation of ON/OFF DERs time-response . . . 135
1.3 Variable-speed DER’s response on a interconnected system . . . 138
1.3.1 Field Test . . . 138
1.3.2 Protocol of tests . . . 140
1.3.3 Validation of the HVAC cubicle time-response . . . 141
1.3.4 Validation of the droop curve conformity . . . 143
2 Deployment of pre-industrial coordination platform (Layer 2) . . . 145
2.1 Architecture of the coordination platform of demonstration . . . 145
2.2 HMI of visualisation of the resultant offer and demand power-frequency characteristics . . . 147
3 Deployment of a scale-1 Primary Support infrastructure . . . 148
3.1 Schneider Electric - Grenoble . . . 149
3.2 G2Elab - Grenoble . . . 149
3.3 ICCS - Athens . . . 150
3.4 SEA - Milano Malpensa . . . 150
4 Conclusion of Chapter IV . . . 152
General Conclusion 157 Appendix A Axes of research addressed during the PhD work 165 Appendix B Method of Day-ahead spot market data analytics 171 1 Data Harvesting . . . 171
2 Data Processing . . . 172
3 Analytics Produced . . . 173
2 Dataset of common FCR prices in Europe . . . 192
Appendix D Patent Review 195
Appendix E HMI screen-shot of the coordination platform of demonstration 203
Résumé étendu & opinion 211
Bibliography 225
List of Figures
1 Evolution the LNG exporting capacities of Qatar(data: Wikipedia [2015]) . . . 2
2 Penetration of Wind (left) and PV (right) in Europe over the 10 past years (in
GW) [EWEA, 2016, GWEC, 2016, IEA, 2016] . . . 3
3 Evolution of the raw materials prices since 1984 (data: Index mundi [2015]) . . . 4
4 Evolution of the carbon spot price on the European Trading System (ETS) [The
Economist, 2013] . . . 4
I.1 Summary over the time of markets and main physical limitations of the power
industry . . . 18
I.2 Localisation of the 15 Nordics and Baltics Nord Pool Spot bidding areas [Nord
Pool Spot, 2015] . . . 19
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. [Kok, 2013] . . . 20
I.4 Review of capacity mechanism penetration in Europe(data: UFE [2014]) . . . 20
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
[Nourai et al., 2008] . . . 22
I.6 Estimation of annual procurement and cost of FCR supply in Europe. ( data:
appendix C.5) . . . 24
I.7 Distribution of the weekly FRR capacity prices in Germany - February 2-8th
I.8 Distribution of the weekly FRR capacity prices in Germany - June 8-14th 2015 (data: Regelleistung [2015] ). . . 27
I.9 Decomposition of spread revenue captured during days of peak-load over the
year 2010 in Finland . . . 31
I.10 Illustration of descent daily spread 3.5hr shape and annual spread revenue (curves
building method presented in App. B, Section 2) . . . 34
I.11 Structure of the Cost Benefit Analysis performed to assess the profitability of
Tesla Powerwall involvement on the day-ahead spot markets . . . 36
I.12 Model used to characterize the AC-to-AC efficiency of the load shifting process
using an ESS . . . 37
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) . . . 37
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: ηAC/DC =
2 × 95%, ηDC/DC = 95%) . . . 39
I.15 Structure of the Cost Benefit Analysis performed to assess the profitability of
Energy Boxes involvement on the day-ahead spot markets . . . 40
I.16 Benchmark of energy boxes hardware in terms of price and compliance with the
business case of domestic space heating optimisation . . . 41
I.17 Benchmark of the power bill savings induced by the implementation of the
cost-optimized heating process (process B-1 in Figure I.15), compared with Energy Box investment cost assumptions in the Nordic and Baltic countries (same out-door reference temperature from Malmö). . . 42
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. . . 42
I.19 Scenarios of DERs flexibility sharing for revenue multiplication . . . 46
II.1 Simplified representation of a generator connected to a unique load [Andersson,
2012] . . . 52
II.2 Splitting of the Continental Europe synchronous area into three areas,
asyn-chronous one another following the German disturbance of November 4, 2006
[ENTSO-E, 2006] . . . 57
II.3 Summary of outages occurrences and duration across the world (both limited
outages and blackouts) [Bruch and Hunter, 2012] . . . 58
II.4 Load tripping repartition across Europe following the disturbance of November
4, 2006 [ENTSO-E, 2006] . . . 59
II.5 Illustration of the activation of balancing reserves following an over-load
distur-bance, depending on the frequency variation . . . 60
II.6 Presentation of the Synchronous Areas of ENTSO-E (data: ENTSO-E [2013a,e]) . . 61
II.7 Presentation of the ENTSO-E LFC Areas and LFC blocks (data: ENTSO-E [2013a,e]) 61
II.9 Definition of the FCR power-frequency characteristic (data: Art 44, ENTSO-E
[2013e]) . . . 64
II.10 Characteristic Time of FCR(data: Art 44,45, ENTSO-E [2013e]) . . . 65
II.11 Characteristic Time of FRR(data: Art 46,47, ENTSO-E [2013e]) . . . 68
II.12 Implementation range for LFDD plan [ENTSO-E, 2015b] . . . 70
II.13 Evolution of the asynchronous machine’s operation point faced with slight vari-ations of the power system frequency . . . 71
II.14 Annual occurrence of negative residual load in West Denmark (in % of the time. 10%=876hrs a year)(data: Energinet [2015]) . . . 74
II.15 Levelized Cost of Electricity (LCOE) - 2015 - 3% to 10% discount rate [IEA, 2015] 75 II.16 Evolution of frequency deviation in the Northern Europe Synchronous Area over the 15 last years [ENTSO-E, 2013e] . . . 77
II.17 Daily occurrence of high frequency deviation in Northern Europe Synchronous area in 2009-2010 [ENTSO-E, 2013e] . . . 78
II.18 Decrease of system inertia with increase in wind penetration replacing conven-tional generations [Das et al., 2015] . . . 79
II.19 Effect of the increase in wind penetration (replacing conventional generators) on 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) [Das et al., 2015] . . . 79
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 [Cardozo et al., 2015] . . . 81
II.21 Evolution of Power flow in Kuching Island faced with to 30% RES-E penetration [Lebel et al., 2015c] . . . 82
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) [Lebel et al., 2015c] . . . 82
II.23 Vertical grid load flow from Tennet Germany transmission network down to the distribution grids - July 2015(data: Tennet [2015]) . . . 83
III.1 Suitable frequency range of operation of Primary Support . . . 91
III.2 IEC61850-7-420 compliant architecture of PrimarySupport . . . 95
III.3 Kind of loads compliant with Primary Support . . . 96
III.4 Characteristic of FWHZ function embedded into IEC61850-7-420-compliant DERs 97 III.5 Targeted step-by-step droop curve involving ON/OFF-driven DERs . . . 100
III.6 Data model used in Primary Support IEC61850-compliant . . . 103
III.7 Sequences of data exchange between the PrimarySupport coordination agent and a DER controller . . . 108
III.8 Thresholds & slopes coordination algorithm used by Primary Support . . . 109
III.10 Principle of operation of the Layer 3 in Primary Support . . . 115
III.11 Topology-related system-scale architecture . . . 120
III.12 Mean Frequency Deviation Dispersion . . . 121
III.13 Common daily occurrence of load modulation events, as a function of the fre-quency threshold applied . . . 121
III.14 Combination of FCR-N and FCR-D claimed by Jomaux and De Jaeger [2015] . 123 III.15 Frequency deviation distribution for various penetration of FCR-D [Jomaux and De Jaeger, 2015] . . . 123
III.16 Common duration of load modulation events, as a function of the frequency threshold applied . . . 124
III.17 Simplified operational process of Primary Support . . . 125
IV.1 Presentation of the agent-based platform and the field test . . . 130
IV.2 Scheme of principle and real energy box developed . . . 130
IV.3 Test of the agent-based platform in steady-state operation . . . 131
IV.4 Micro-grid response to a major outage, with and without frequency regulation . 132 IV.5 Characterisation of the obtained droop curve compared to the droop expected . 133 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 . . . 135
IV.8 Prototype of ON/OFF demonstration suitcase . . . 136
IV.9 ON/OFF industrial DER controllers response to a sudden frequency drop . . . 137
IV.10 ON/OFF industrial DER controllers response to a sudden frequency recovery . 137 IV.11 On-site generic architecture of an HVAC system and picture of the equivalent system built within PREDIS platform . . . 138
IV.12 Power conversion process from the HVAC-emulator cubicle down to the final resistive loads . . . 140
IV.13 Power-response of the HVAC unit to a monthly-event observed in Continental Europe (March 2015) . . . 142
IV.14 Power-response of the HVAC unit to a decade-event (2003 Italian Black-out) . . 142
IV.15 ICT and physical path from Hz modification up to new T otW value observation 143 IV.16 Validation of delivery of the slope Wgra by the HVAC cubicle . . . 143
IV.17 Architecture of the demonstration coordination platform of Primary Support . . 146
IV.18 Interface of visualisation of the resultant offer and curves . . . 148
IV.19 Map of the DER controllers of Primary Support deployed among Dream facilities 149 IV.20 Architecture of the airport lighting modulation system to the deployed at Milano Malpensa for Primary Support purpose . . . 150
IV.21 [Left] Overview of the parking lighting of Milano Malpensa Airport to be involved in Primary Support . . . 151
IV.22 [Right] Overview of the parking lighting of Milano Malpensa Airport to be in-volved in Primary Support . . . 151
A.2 Research axis on Real-Time-Price tariff for households . . . 166
A.3 Research axis on Business Use Cases for DER integration . . . 167
A.4 Research axis on LV4MV . . . 167
A.5 Research axis on DLVM . . . 168
A.6 Research axis on Primary Support . . . 169
A.7 Research axis on Second Ice . . . 169
B.1 Illustration of data analytic strengthening along the steps of data computation . 172 B.2 Example of [D1] data content . . . 174
B.3 Example of [D2] data content . . . 174
B.4 Example of [D5], [D10] and [D14] data content . . . 175
B.5 Example of [D11], [D12], [D15] and [D16] content . . . 177
B.6 Illustration of [D10] (grey points), [D13] (green rectangles) and [D14] content (gradation of green points depending on the period of averaging) . . . 178
B.7 Example of [D17] and [D18] content . . . 178
B.8 Observation of the periods of extreme loads among the network load [D1] in the 18 bidding areas. Limits of extreme loads: ]50%; 85%[ of [D8] . Year 2010 or more recent. . . 180
B.9 Annual revenue of the daily spread 3.5hr gathered 365 days a year [D17] or during peak-days only [D18] in Norway, Denmark and France . . . 181
B.10 Annual revenue of the daily spread 3.5hr gathered 365 days a year [D17] or during peak-days only [D18] in Sweden, Finland, Latvia, Lithuania and Estonia 182 B.11 Spot turnover repartition [D13], 1MW-steps price elasticity [D10] and Gliding price elasticity average [D14] in Norway . . . 183
B.12 Spot turnover repartition [D13], 1MW-steps price elasticity [D10] and Gliding price elasticity average [D14] in France and Sweden . . . 184
B.13 Spot turnover repartition [D13], 1MW-steps price elasticity [D10] and Gliding price elasticity average [D14] in Norway . . . 185
B.14 Descending daily spread 1hr [D11] and 3.5hr [D12] in Sweden, Denmark and France. Average 2011-2014 . . . 186
B.15 Descending daily spread 1hr [D11] and 3.5hr [D12] in Sweden, Finland, Latvia, Lithuania and Estonia. Average 2011-2014 . . . 187
B.16 Descending daily spread 1hr [D15] and 3.5hr [D16] at peak in Norway, Denmark and France. Average 2011-2014 . . . 188
B.17 Descending daily spread 1hr [D15] and 3.5hr [D16] at peak in Sweden, Finland, Latvia, Lithuania and Estonia. Average 2011-2014 . . . 189
C.1 Distribution of the FCR prices in UK compared with the mean FCR price(data: [National Grid, 2015]) . . . 192
D.3 Patent review - Key words "Demand Response " 1/5 . . . 198
D.4 Patent review - Key words "Demand Response " 2/5 . . . 199
D.5 Patent review - Key words "Demand Response " 3/5 . . . 200
D.6 Patent review - Key words "Demand Response " 4/5 . . . 201
D.7 Patent review - Key words "Demand Response " 5/5 . . . 202
E.1 Map of synoptics: path to the different platform’s functions . . . 203
E.2 Path of declaration of a new DER into the pool of Primary Support . . . 204
E.3 Path of modification of DER parameters and view of the effective contribution . 205 E.4 Path of modification of demand bids . . . 206
E.5 Path of modification of the market clearing and clearing visualisation algorithms 207 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 [Lebel et al., 2015c] . . . 213
IV.7 Principe de l’analyse coûts-bénéfices réalisée pour estimer la rentabilité du stock-age chimique intraday sur les marchés spot . . . 215
IV.8 Exemple de GEDs compatibles avec les spécifications de Primary Support . . . 217
IV.9 Procédé opérationnel simplifié de Primary Support . . . 218
IV.10 Exemple d’architecture de déploiement de Primary Support selon la topologie du réseau . . . 219
IV.11 Illustration des enjeux de standardisation des protocoles de communication des GEDs . . . 221
List of Tables
I.1 Assessment of Grid losses cost saving opportunities using DER . . . 23I.2 FRR regulated remuneration in France and Denmark . . . 25
I.3 Assessment of RR using domestic space heating DR . . . 26
I.4 Assessment of Capacity Auction opportunities using DER . . . 28
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] . . . 29
I.6 Mean number of peak days per year . . . 29
I.7 Spot volumes range (in % of the peak load, wherein the top 10% of the day-ahead spot turnover is traded) . . . 30
I.9 Number of days of the year having a daily spread 3.5hr larger than 40e/MWh.
Average 2011-2014 . . . 33
I.10 Summary of the sources of revenue of DER flexibility depending on the countries 44 I.11 Assessment of load-shifting costs for either ESS or thermal storage . . . 47
II.1 Typical inertia constants Hi of synchronous machines [Kothari and Nagrath, 2008] 54 II.2 FCR providing groups and units’ minimum frequency accuracy and insensitivity requirement(Art 44(1), ENTSO-E [2013d]) . . . 62
II.3 References numbers used in Figures II.9, II.10 and II.11 . . . 65
II.4 Frequency Restoration Range applied by synchrounous area . . . 67
II.5 Automatic Low Frequency Demand Disconnection scheme characteristics (Art 14, ENTSO-E [2015a]) . . . 70
II.6 Estimation of the FCR and wholesale marginal cost and incomes depending on the technology used for 1MW of installed capacity . . . 76
III.1 From frequency stability challenges to the functional and operational specifica-tions of Primary Support . . . 90
III.2 IEC61850-7-420 parameters to be defined for the use of the Frequency-watt mode FWHZ . . . 104
III.3 Non native IEC61850-7-420 parameters involved in the threshold coordination algorithm . . . 105
III.4 Columns order of the 20 parameters introduced as inputs of the threshold & slope coordination algorithm . . . 107
III.5 Frequency dispersion occurrence in Continental Europe [Filip, 2011] . . . 120
IV.1 Semantic of the JSON messages exchanged between the DER controllers and the coordination platform . . . 147
B.1 Period of market data acquisition per bidding area . . . 172
B.2 Representation of the data-heritage along the analytic levels . . . 173
B.3 Mapping of the Figures wherein [D1] to [D18] data are plotted . . . 174
B.4 Peak Load Value [D8] assumed for each bidding area (in MW) . . . 176
C.1 Characteristic UFLS schemes in CE . . . 191
C.2 Characteristic UFLS scheme in GB . . . 191
C.3 Characteristic UFLS scheme in IRE . . . 192
C.4 Characteristic UFLS scheme in NE . . . 192
1
From Geopolitics to Smart Grid
1.1 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].
0 10 20 30 40 50 60 70 80 90 A n n u al c ap ac it ty o f L N G ( in m m tp a) Years
Figure 1: Evolution the LNG exporting capacities of Qatar(data: Wikipedia [2015])
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 pro-gressive 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 depen-dency 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 de-ployment’s procedures, the penetration of RES-E in Europe have started to rise significantly (Figure 2).
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Rest of the World 5 7 8 11 13 18 26 37 56 84 113 144 176 201 241 291
Europe 13 17 23 29 34 41 48 57 65 75 85 95 107 117 129 142 Overall 17 24 31 39 48 59 74 94 121 159 198 238 283 318 370 432 0 50 100 150 200 250 300 350 400 450 500 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 C u m u la tiv e W in d p o w e r c a p a c ity ( in G W ) Years
Rest of the World Europe
7
Figure 2: Penetration of Wind (left) and PV (right) in Europe over the 10 past years (in GW) [EWEA, 2016, GWEC, 2016, IEA, 2016]
1.2 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 CO2 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.
1.3 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 conse-quences 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;
0 10 20 30 40 50 60 70 80
Feb 1984 Feb 1989 Feb 1994 Feb 1999 Feb 2004 Feb 2009 Feb 2014
P ri ce s (i n U S D /M W h ) Time
Evolution of Crude Oil, Coal and Natural Gas prices (in USD/MWh) Thermal coal (Australia)
Crude oil (average Dated Brent, West Texas, Dubai Fateh) Natural Gas in Louisiana
Natural Gas in Russia
Indonesian Liquified Natural Gas in Japan
Europe & China disappointing
growth
time-offset related to Oil/Gas indexation
Figure 3: Evolution of the raw materials prices since 1984(data: Index mundi [2015])
Figure 4: Evolution of the carbon spot price on the European Trading System (ETS) [The Economist, 2013]
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
con-gestion 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
mod-ulation 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
2
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.
3
Publications
This thesis has led to the following list of publications and communications:
Power Market Analysis
Gaspard Lebel, Raphaël Caire, Nouredine Hadjsaid, Stéphane Bediou and Alain Glatigny.
Cost benefit analysis of households energy boxes deployment in Europe: Impact of the spot
prices. In CIRED 23rd International Conference on Electricity Distribution. [Lebel et al.,
2015a].
DER Operation Coordination
Arnaud Ulian and Maria Sebastian. EvolvDSO Deliverable 2.1 – Business Use Cases
Defini-tion and Requirements v1.0. In http://www.evolvdso.eu/Home/Results [Ulian and Sebastian, 2014]
Gaspard Lebel. From fit&forget to #IoT driven distribution network: the importance of
standardization & decentralization In Increase Summer School 2015 lectures, Gent, Belgium,
July 15, 2015. [Lebel, 2015].
VoltVAR Management
Emmanuelle Vanet, Gaspard Lebel, Raphaël Caire, Nouredine Hadjsaid, Stéphane Bediou
and Alain Glatigny. LV4MV: a concept for optimal power flow management in
distribu-tion grids, using DER flexibility. In CIRED 23rd International Conference on Electricity
Distribution. [Vanet et al., 2015].
Emmanuelle Vanet, Gaspard Lebel, Raphaël Caire, Nouredine Hadjsaid, Mathieu Gabel
and Marc Lazarus. Flexibility activation optimization for constraints management in distribution grids, using DER flexibility through LV4MV. In CIRED Workshop 2016, Helsinki
Gaspard Lebel. DLVM: les capteurs de tension BT autonomes, geo-localisés et
commu-nicants. In Internet of Things (IoT) Final at concours innovation ErDF 2015 Réseaux
Electriques Intelligents
Power System Security: Assessments and Innovation Proposal
Gaspard Lebel, Karel Kuypers, Raphaël Caire, Nouredine Hadjsaid, Stéphane Bediou and
Alain Glatigny. Distributed and coordinated demand response for the supply of frequency
containment reserve (FCR). In CIRED 23rd International Conference on Electricity
Distri-bution. [Lebel et al., 2015b].
Gaspard Lebel, Karel Kuypers, Raphaël Caire, Nouredine Hadjsaid, Stéphane Bediou and
Alain Glatigny. Domestic Demand Response for Primary Control support. In Student Poster
Session of Cigré International Colloquium Lightning & Power Systems, Lyon 2014 [Lebel
et al., 2014b].
Gaspard Lebel, Da Wang, Raphaël Caire, Nouredine Hadjsaid, Stéphane Bediou and Alain
Glatigny. Distributed and coordinated demand response for frequency-controlled reserve supply. In PowerTech, 2015 IEEE Eindhoven, pages 1–5. [Lebel et al., 2015c].
Gaspard Lebel, Raphaël Caire, Nouredine Hadjsaid. Procédé de stabilisation d’un réseau
électrique par délestage de charges. In Institut National de la Propriété Intellectuelle (INPI),
FR Patent deposit N◦13/62664, December 16, 2013. [Lebel et al., 2013a].
Gaspard Lebel, Raphaël Caire, Nouredine Hadjsaid. Procédé de stabilisation d’un réseau
électrique par délestage de charges. PCT Extension and additional claims. In European
Patent Office (EPO) , PCT Patent extension deposit PCT/EP2014/077815, December 15, 2014. [Lebel et al., 2014a].
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
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.
5
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).
6
Glossary of Important Terms and Abbreviations
Adequacy: System’s ability to meet consumers’ total power demand and to satisfy their
re-quirements as regards energy at all times, taking account of planned and reasonably expectable trips of system elements. The concept covers stationary conditions [Energinet, 2007].
aFRR: Frequency Restoration Reserves that can be activated by an automatic control device
[ENTSO-E, 2014b]. ⊲ Frequency Restoration Reserves.
Ancillary services: Joint name for various services to which TSOs require access in the
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 [ENTSO-E, 2014b].
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 [ENTSO-E, 2014b].
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 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].
Sharing partners of scientific and industrial knowledges
This PhD work has been largely inspired by beneficial discussions that occurred with col-leagues and customers of the following companies and institutions.
Balancing Capacity: The contracted ⊲ Reserve Capacity [ENTSO-E, 2014b]. Balancing Energy: Energy used by TSOs to perform Balancing [ENTSO-E, 2014b].
Balancing Market (BM): Entirety of institutional, commercial and operational arrangements
that establish market-based management of the function of Balancing within the framework of the European Network Codes [ENTSO-E, 2014b].
Balancing Service: Either or both ⊲ Balancing Capacity and ⊲ Balancing Energy
[ENTSO-E, 2014b].
BM: ⊲ Balancing Market.
BRP: ⊲ Balance Responsible Party.
Bulk Generation: Power plant of large capacity connected to the transmission grid.
CCGT: Combined Cycle Gas Turbines. Lastest generation of gas-fired power plant having an
efficiency ≥ 60% while conventional gas-fired power plants have an efficiency of ≤ 37%.
CE: ⊲ Synchronous Area
distri-bution system or HVDC system is connected to either a transmission system, offshore network, distribution system, including closed distribution systems, or HVDC system, as identified in the connection agreement [ENTSO-E, 2014b].
Demand Response (DR): Demand offered for the purposes of, but not restricted to, providing
Load-shifting at the benefit of the wholesale markets, Active or Reactive Power management, Voltage and Frequency regulation and System Reserve, at the benefit of the System Operators.
Demand Side Management (DSM): All the activities addressed to encourage customers
to modify patterns of electricity usage, including the timing and level of electricity demand. DSM covers the complete range of load shape objectives, including strategic conservation and load management, as well as strategic load growth. In system studies, the distinction is made between controllable DSM and uncontrollable DSM. Controllable DSM includes curtailment of interruptible loads and / or for emergency procedures such as voltage reductions and the anticipated effects of public appeals [ENTSO-E, 2014b]. To recap, Demand Side Management covers both Demand Response and Energy Efficiency processes.
Demand Side Response (DSR): Term used by ENTSO-E to designate ⊲ Demand Re-sponse.
DER: ⊲ Distributed Energy Resource. DG: ⊲ Distributed Generation.
Distributed Energy Resource (DER): Small-size power source connected to the distribution
grid. DER regroups Demand Response (DR), Distributed Generation (DG) or Energy Storage System (ESS) and is composed of assets like microCHP, wind-turbines, PV, back-up gensets, batteries, etc. DERs can be coordinated thanks to platform of operational aggregation called ⊲Virtual Power Plant (VPP).
Distributed Generation (DG): Generation plants connected to the distribution system
[ENTSO-E, 2014b], at either MV or LV voltage level.
Distribution System Operator (DSO): Natural or legal person responsible for operating,
ensuring the maintenance of and, if necessary, developing the distribution network in a given area and, where applicable, its interconnections with other networks and for ensuring the long-term ability of the network to meet reasonable demands for the distribution of electricity [ENTSO-E, 2014b].
DR: ⊲ Demand Response.
DSM: ⊲ Demand Side Management. DSO: ⊲ Distribution System Operator. DSR: ⊲ Demand Side Response.
EC: European Commission.
Electrical Renewable Energies Sources (RES-E): Set of green power technologies such as
as conventional generation and not RES-E
Energinet: TSO of Denmark.
Energy Storage System (ESS): Technologies of storage of power energy.
ENTSO-E: European Network of Transmission System Operators for Electricity as
established in the Regulation (EC) 714/2009 of the European Parliament and of the Council of 13 July 2009 on conditions for access to the network for cross-border exchanges in electricity and repealing Regulation (EC) 1228/2003[1].
ENTSO-E (European Network of Transmission System Operators for Electricity): Association
of European TSOs in charge of coordinating the development and the interconnection of each of the transmission systems of the European countries.
ESS: ⊲ Energy Storage System. EV: Electric Vehicle.
FCR: ⊲ Frequency Containment Reserves.
FCR Providing Group: ⊲ Reserve Providing Group. FCR Providing Unit: ⊲ Reserve Providing Unit.
Feed-in tariff : Policy mechanism designed to accelerate investment in renewable energy
tech-nologies. It commonly guarantees a priority feed-in of RES-E power on the network, at a guaranteed price at the expense of conventional generation.
FRR Providing Unit: ⊲ Reserve Providing Unit. FRR Providing Group: ⊲ Reserve Providing Group.
Frequency Containment Reserves (FCR): Operational Reserves activated to contain System
Frequency after the occurrence of an imbalance [ENTSO-E, 2014b]. See Sections 1.3 & 1.4.
Frequency Restoration Reserves (FRR): Active Power Reserves activated to restore System
Frequency to the Nominal Frequency and for Synchronous Area consisting of more than one LFC Area power balance to the scheduled value [ENTSO-E, 2014b].
Frequency Restoration Control Error: Control error for the FRP which is equal to the
ACE of a LFC Area or is equal to the Frequency Deviation where the LFC Area geographically corresponds to the Synchronous Area [ENTSO-E, 2014b].
FRR: ⊲ Frequency Restoration Reserves. GB: ⊲ Synchronous Area.
Green Bonus: Variation of the feed-in tariff, where RES-E producers sell their energy on the
wholesale markets at the market price and get a fix complementary remuneration in e/MWh from the authorities to promote investment in RES-E. Contrary to the feed-in tariff, the Green Bonus does not always guarantee a firm access to the grid to RES-E.
connection or really long distance in overhead connections, using the Direct Current (DC) instead of business-as-usual Alternative Current(AC).
HVAC: Acronym of "Heating, Ventilation and Air Conditioning". It gathers the technologies
of indoor building environmental comfort.
HVDC: ⊲ High Voltage Direct Current.
IEC: International Electrotechnical Commission. Committees in charge of the definition of
international standards and conformity assessment body for all fields of electrotechnology.
ICT: ⊲ Information and Communication Technologies.
Information and Communication Technologies (ICT): Gathers the technologies of
Infor-mation Technologies (IT) and of Telecommunication, that are involved in the building of the Smart Grid.
IRE: ⊲ Synchronous Area.
Key Performance Indicators (KPI): Set of indicators that evaluates the performance of
operation of System Operators.
KPI: ⊲ Key Performance Indicators.
LFC Area: Part of a Synchronous Area, operated by a TSO. European LFC Areas are displayed
in Figure II.7.
LFC Block: Aggregation of LFC Areas, that constitutes a wider area at the scale of which the
Frequency Restoration Process is operated by one unique TSO to enable a sharing of Frequency Restoration Reserves. Part of the European LFC Areas stays independent one another and constitutes so their own LFC Block. European LFC Blocks are displayed in Figure II.7.
LFDD ⊲ Load Frequency Demand Disconnection. LNG: Liquefied Natural Gas.
Load Frequency Demand Disconnection (LFDD): ⊲ Under Frequency Load Shedding
(UFLS).
LV: Low Voltage.
mFRR: ⊲ Frequency Restoration Reserves.
Modbus: Industrial protocol of data exchange between electronic devices. MV: Medium Voltage.
NE: ⊲ Synchronous Area. PV: Photovoltaic.
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 acti-vation time from Time to Restore Frequency up to hours [ENTSO-E, 2014b].
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 [ENTSO-E, 2014b].
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 [ENTSO-E, 2014b].
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 [ENTSO-E, 2014b].
RR: ⊲ Replacement Reserves. See Section 1.6. RPI: ⊲ Raspberry PI.
RTE (Réseau de Transport d’Electricité): TSO of France. SA: ⊲ Synchronous Area.
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 conven-tional 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 [ENTSO-E, 2014b].
Standard Frequency Range: Interval defined symmetrically around the Nominal Frequency
of a Synchronous Area. The System Frequency is supposed to stay contained within this Stan-dard Frequency Range in normal operation [ENTSO-E, 2014b].
Statnett: TSO of Norway.
Steady State Frequency Deviation: Absolute value of Frequency Deviation that is observed
2014b]. In other words, this is the System Frequency observed at the end of the Frequency Containment Process and prior the Frequency Restoration Process.
Svenska Kraftnät: TSO of Sweden.
Synchronous Area: Geographical area, composed of one or several LFC Areas interconnected
one another, wherein the System Frequency is the same all across the area in steady operational state. Thus all of the LFC Areas of the same Synchronous Areas are connected one another through at least one AC interconnection. Figure II.6 displays the four Synchronous Areas of Continental Europe (CE), Great Britain (GB), Ireland (IRE) and Northern Europe (NE), that composed the European power system.
System Security: Power system’s ability to handle sudden disturbances such as electrical
short circuits or the unexpected outage of system elements. The concept covers dynamic events [Energinet, 2007]. See Section 1.2.
Tennet: One of the four TSOs of Germany and unique TSO of the Netherland. Terna: TSO of Italy.
Time of Use (ToU): Tariff system where the energy price billed to the end-user is changing
depending on the hour of the day.
ToU: ⊲ Time Of Use.
Transmission System Operator (TSO): A natural or legal person responsible for operating,
ensuring the maintenance of and, if necessary, developing the transmission system in a given area and, where applicable, its interconnections with other systems, and for ensuring the long-term ability of the system to meet reasonable demands for the transmission of electricity [ENTSO-E, 2014b].
TSO: ⊲ Transmission System Operator.
Underlying: characteristic of a power product traded on the power wholesale or ancillary
services markets.
UFLS: ⊲ Under Frequency Load Shedding.
Under Frequency Load Shedding: Emergency mechanism which is automatically operated
by the DSOs face to large frequency deviation, out of the Maximum Instantaneous Frequency Deviation (See Figure II.8). It leads on a step-by-step blind shedding of the Primary Substation feeders.
Virtual Power Plant (VPP): System that integrates and coordinates several types of DERs
that can be seen from the power system side as one unique generation unit that behaves as a bulk generation unit.
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.
1
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.
1.1 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 markets1, 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
1
Market Coupling capacity RR FCR Spot market Day Ahead block / hourly product Intraday hourly product Intraday quarter product Energy Product Capacity Product Grid Operation Relialibity VoltVAR mgmt Congestion mgmt Losses Saving…
Long Term market Derivatives Futures / Forward Over the Counter (OTC) Power System Security & Stability
Wholesale Markets Ancillary Services Products for System Reliability
15min 1hr
12hr
Black-starting time for conventional thermal power units
Answering time of DR processes
Real Time
15s 5 years
Bilateral wholesale contracts
Reacting time of hydro power units 30s
Grid’s operations, less related to time horizon
< 10s 3-4hr FRR or 36hr Capacity Auction Peak Load Time Horizon
Figure I.1: Summary over the time of markets and main physical limitations of the power industry
when the trade occurs (Figure I.1).
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.
