The high penetration of renewable energies (RE) in power systems is increasing the volatile production on the generation side and the presence of distributed energy resources (DER) over the territory. On the other hand, Virtual Power Plants (VPPs) are an aggregation of DER managed as a single entity to promote flexibility services to power systems. Therefore, VPPs are a valid approach to cope with the arising challenges in the power system related to RE penetration. This report defines the concept of a utility-scale VPP, as a tool to stabilize the grid and increase the flexibility capacity in power systems. For this purpose, the report places special emphasis in the use cases that can be developed with a utility-scale VPP. Nevertheless, implementing a utility-scale VPP is a complex procedure, as VPP solutions are highly customizable depending on the scope and the conditions of each project. For this reason, this report analyses the main factors that must be taken into account when implementing a VPP solution. The report concludes that the two most critical factors that define the viability of a VPP project are, first, the energy market design and regulatory framework and second, the technical requirements. These two must always align with the scope of the project and the use cases intended to be developed. Further, other minor factors, including a cost estimate for a VPP solution, are also considered in the report. / Den höga penetrationen av förnybara energier i kraftsystem ökar den flyktiga produktionen på produktionssidan och närvaron av distribuerade energiresurser över territoriet. Å andra sidan är virtuella kraftverk en sammanställning av distribuerade energiresurser som hanteras som en enda enhet för att främja flexibilitetstjänster till kraftsystem. Därför är virtuella kraftverk: er en giltig strategi för att hantera de uppkomna utmaningarna i kraftsystemet relaterat till förnybara energier genomslag. I denna rapport definieras konceptet med en virtuella kraftverk verktygsskala som ett verktyg för att stabilisera nätet och öka flexibilitetskapaciteten i kraftsystem. För detta ändamål lägger rapporten särskild tonvikt på användningsfall som kan utvecklas med en virtuella kraftverk-nytta. Trots det är implementering av en virtuella kraftverknyckelskala en komplex procedur, eftersom virtuella kraftverk-lösningar är mycket anpassningsbara beroende på omfattning och villkor för varje projekt. Av denna anledning analyserar denna rapport de viktigaste faktorerna som måste beaktas vid implementering av en VPP-lösning. Rapporten drar slutsatsen att de två mest kritiska faktorerna som definierar ett virtuella kraftverk projekts livskraft är, dels energimarknadens utformning och regelverk och för det andra de tekniska kraven. Dessa två måste alltid anpassa sig till projektets omfattning och användningsfall som är avsedda att utvecklas. Vidare beaktas även andra mindre faktorer, inklusive en kostnadsuppskattning för en virtuella kraftverk lösning, i rapporten.

Historically, electricity supply was heavily centralized and was provided by conventional thermal power plants such as coal-fired, gas, or nuclear power plants. The share of conventional power generation is being increasingly replaced by power generation from renewable sources. In Europe, the share of electricity generation from fossil fuels fell from 49% in 2011 to 37% in 2020, whereas the share from renewables increased from 22% to 38% during the same timeframe. Renewable generation is expected to rise by 10% annually to almost triple the current renewable capacity by 2030. The accelerating adoption of renewables changes the character of the electricity infrastructure from a centralized energy supply to a highly decentralized one, such that generation is moving closer to the point of demand. This change brings numerous challenges with it. This work focuses on challenges in operational planning of distributed energy resources from the perspective of so-called aggregators that are increasingly participating in energy markets. Aggregators combine different energy resources, i.e., electricity producers and consumers, and operate them as a distributed power plant. However, the planning of the energy resources is still coordinated collectively in a centralized manner by the aggregator. This work aims to develop a framework to schedule energy resources from the perspective of an aggregator to cover a large variety of technical assets and to simultaneously consider market interactions such as bid acceptance and rejection possibilities. The inevitable and accelerating proliferation of renewable energy resources brings with it -- as a consequence of its intermittency -- a growing need in control reserve and storage technologies. Hence, a focus is placed on control reserve, energy storage, and integrated scheduling and bidding, as well as their trade-offs, to answer the following research questions: 1) What is the current state of control reserve formulations and how can they be improved? Specifically regarding reserve under consideration of limitations with respect to the rate of change of power output, maximum power output, and energy capacity. 2) What are the effects of using different control reserve formulations? 3) Which trade-offs exist in the operation of storage plants in a market environment? 4) Is it possible to derive a rigorous, tractable mathematical model to simultaneously determine scheduling and bidding decisions? 5) Which trade-offs exist between scheduling and bidding decisions and what are their effects? 6) To what extent is it possible to solve energy resource scheduling models faster while retaining sufficiently high solution quality? / In der Vergangenheit war die Stromerzeugung stark zentralisiert und wurde durch konventionelle Kraftwerke wie Kohle-, Gas- oder Kernkraftwerke bereitgestellt. Der Anteil der konventionellen Stromerzeugung wird zunehmend durch die Stromerzeugung aus erneuerbaren Quellen ersetzt. In Europa sank der Anteil der Stromerzeugung aus fossilen Brennstoffen von 49% im Jahr 2011 auf 37% im Jahr 2020, während der Anteil der erneuerbaren Energien im gleichen Zeitraum von 22% auf 38% anstieg. Es wird erwartet, dass die Stromerzeugung aus erneuerbaren Energien jährlich um 10 % steigt und sich die derzeitige Kapazität bis 2030 fast verdreifacht. Die zunehmende Einführung erneuerbarer Energien verändert den Charakter der Elektrizitätsinfrastruktur von einer zentralisierten zu einer stark dezentralisierten Energieversorgung, so dass die Erzeugung näher an den Ort des Bedarfs rückt. Dieser Wandel bringt zahlreiche Herausforderungen mit sich. Diese Arbeit konzentriert sich auf die Herausforderungen bei der Betriebsplanung dezentraler Energieanlagen aus der Perspektive sogenannter Aggregatoren, die zunehmend an den Energiemärkten teilnehmen. Aggregatoren fassen verschiedene Energieanlagen, d.h. Stromerzeuger und -verbraucher, zusammen und betreiben sie als dezentrales Kraftwerk. Die Planung der Energieressourcen wird jedoch weiterhin zentral durch den Aggregator koordiniert. Diese Arbeit zielt darauf ab, ein Framework für die Planung von Energieressourcen aus der Sicht eines Aggregators zu entwickeln, um eine große Vielfalt an technischen Anlagen abzudecken und gleichzeitig Marktinteraktionen wie Gebotsannahme- und Ablehnungsmöglichkeiten zu berücksichtigen. Der unvermeidliche und zunehmende Ausbau von erneuerbaren Energieressourcen bringt -- als Folge ihrer Unstetigkeit -- einen wachsenden Bedarf an Regelleistung- und Speichertechnologien mit sich. Daher liegt der Schwerpunkt auf Regelleistung, Energiespeicherung und integrierter Anlagen- und Gebotsplanung sowie deren Trade-offs, um die folgenden Forschungsfragen zu beantworten: 1) Was ist der aktuelle Stand von Regelleistungsmodellen und wie können diese verbessert werden? Insbesondere im Hinblick auf Regelleistung unter Berücksichtigung von Einschränkungen hinsichtlich der Änderungsrate der Leistungsabgabe, der maximalen Leistungsabgabe und der Energiekapazität. 2) Welche Auswirkungen hat die Verwendung unterschiedlicher Regelleistungsmodelle? 3) Welche Zielkonflikte bestehen beim Betrieb von Speicheranlagen in einem Marktumfeld? 4) Ist es möglich, ein rigoroses, praktikables mathematisches Modell zur gleichzeitigen Bestimmung von Anlagen- und Gebotsplanung aufzustellen? 5) Welche Zielkonflikte bestehen zwischen Anlagen- und Gebotsplanung und welche Auswirkungen haben sie? 6) Inwieweit ist es möglich, Modelle zur Planung von Energieressourcen schneller zu lösen und dabei eine ausreichend hohe Lösungsqualität beizubehalten?

Hydropower in Sweden is a powerful and efficient source of energy due to its flexibility, usually used to balance the Swedish power system. With the transition of power system into more intermittent power sources, the role of hydro-power as producers will become more important. Thus the optimal scheduling of hydropower units, with other assets, holds an important place in electric power systems, which is significantly investigated as a research issue. This thesis presents an optimization model that aims at maximizing the income of that producer. The model is implemented on a virtual power plant trading in both day-ahead and mFRR balancing markets in the SE2 bidding zone in Sweden. The virtual power plant comprises hydo-power plants located on the Swedish river Skellefteälven, a wind power unit, and a storage unit. This system participates in electricity market as a single entity in order to optimize the use of energy resources. As feature, uncertainty in electricity market price, wind power production and in active-time duration in the mFRR energy market are modeled in order to formulate a so-called stochastic adaptive robust optimization model. The latter is solved using a column-and-constraint generation algorithm, solved by GAMS and Matlab. A bid curve analysis is performed showing the optimal strategy in case of low/high price scenario and the level of conservativeness. After that, a revenue assessment is carried out which in turn leads to an investigation of the interaction between the three assets and the impact of the storage facility in the revenue. Results demonstrate the advantage of the battery in increasing profit in some cases and its flexibility in the use of storing energy and selling it to the markets at suitable times, e.g., it saves energy from the wind in hours of comparatively low prices, while it sells it in hours of comparatively high prices. Finally, an assessment on variation of imbalance costs is held with and without battery, comparing how such virtual power plants reduce the imbalance costs. / Vattenkraften i Sverige är en kraftfull och effektiv energikälla tack vare sin flexibilitet, används vanligtvis för att balansera det svenska kraftsystemet. I och med att kraftsystemet övergår till mer intermittenta energikällor kommer vattenkraftens roll som producent att bli viktigare. Den optimala schemaläggningen av vattenkraftsenheter har därför tillsammans med andra tillgångar en viktig plats i elkraftsystemen, vilket är en viktig forskningsfråga. I denna avhandling presenteras en optimeringsmodell som syftar till att maximera inkomsten för den producenten. Modellen implementeras på ett virtuellt kraftverk som handlar på både day-ahead- och mFRR-balanseringsmarknader i budzonen SE2 i Sverige. Det virtuella kraftverket består av vattenkraftverk belägna vid den svenska Skellefteälven, en vindkraftsenhet och en lagringsenhet. Systemet deltar på elmarknaden som en enda enhet för att optimera användningen av energiresurser. Som en funktion kan osäkerheten i elmarknadspriset, vindkraftsproduktionen och den aktiva tiden i kraftverket användas. mFRR-marknaden modelleras för att formulera en så kallad stokastisk adaptiv robust optimeringsmodell. Den sistnämnda löses med hjälp av en kolumn-och-bindningsgenerering algoritm, som löses med GAMS och Matlab. En analys av budkurvan utförs och visar att optimala strategin vid scenarier med lågt/hög pris och nivån av försiktighet. Efter därefter görs en intäktsbedömning som i sin tur leder till en undersökning av interaktionen mellan de tre tillgångarna och lagringsanläggningens inverkan på intäkterna.Resultaten visar att batteriet i vissa fall är en fördel när det gäller att öka vinsten och att dess flexibilitet när det gäller att lagra energi och sälja den på marknaden vid lämpliga tidpunkter, Det sparar t.ex. energi från vinden under timmar med jämförelsevis låga priser, medan det säljer den. när priserna är jämförelsevis höga. Slutligen görs en bedömning av variationen i obalansen. med och utan batteri, där man jämför hur sådana virtuella kraftverk minskar kostnaderna för obalans.

[pt] A perspectiva de queda nos preços dos sistemas fotovoltaicos e sistemas de armazenamento de energia elétrica em baterias trouxe a possibilidade de maior viabilidade econômica de projetos envolvendo recursos energéticos distribuídos. No Brasil, a Resolução Normativa 482/2012 regulamentou a micro e mini geração distribuída, estimulando, portanto, a integração desses recursos nas redes de distribuição. Com a promulgação da Lei brasileira 14.300/2022, os projetos de micro e mini geração distribuída foram impactados, uma vez que o sistema de compensação de energia elétrica passou a ser parcial, o que demanda agregar valor aos modelos de negócios baseados em geração distribuída. Este trabalho propõe um modelo de Programação Linear Inteira Mista estocástico com o objetivo de avaliar a viabilidade econômica de usinas virtuais compostas por diferentes configurações de recursos energéticos distribuídos, envolvendo baterias e painéis fotovoltaicos. Para atingir esse propósito, o modelo busca dimensionar o contrato de energia anual ótimo, fornecendo também a operação diária das baterias. Além de levar em consideração os aspectos da Lei 14.300/2022, o modelo incorpora a prática de arbitragem tarifária. Colaborando, assim, com estudos que analisam os impactos regulatórios sobre empreendimentos envolvendo baterias e painéis fotovoltaicos no contexto brasileiro. Com o intuito de abordar o tema de maneira ampla, o modelo proposto foi implementado para recursos energéticos distribuídos organizados como usina virtual, contendo: (i) um sistema fotovoltaico; (ii) um sistema de armazenamento de energia em baterias; (iii) um sistema híbrido (composto por um sistema fotovoltaico e um sistema de armazenamento de energia em baterias); e (iv) o estudo de caso da distribuidora de energia elétrica brasileira Energisa Tocantins. Em todas as aplicações, analisou-se a viabilidade econômica da usina virtual para as tarifas da Energisa Tocantins e outras 34 distribuidoras brasileiras, representando pelo menos uma distribuidora por estado brasileiro. Além disso, foram feitas comparações em relação à data de início de operação da usina virtual, evidenciando o impacto da Lei 14.300/2022 na viabilidade econômica das usinas virtuais analisadas, mostrando, assim, o impacto da referida lei nos projetos de geração distribuída no Brasil. No estudo de caso da distribuidora de energia elétrica brasileira Energisa Tocantins, foi realizada uma análise adicional contemplando aspectos da rede de distribuição da própria Energisa Tocantins, onde os recursos energéticos distribuídos estão alocados. Nessa análise adicional, foram avaliadas as perdas elétricas e seus custos, bem como o perfil de tensão para dois casos de operação das baterias e para o caso base, que seria o caso sem recursos energéticos distribuídos na rede de distribuição Energisa Tocantins. Os resultados evidenciaram que a implementação da Lei 14.300/2022 reduziu a atratividade de projetos envolvendo geração distribuída. No entanto, em sua maioria, considerando os parâmetros adotados deste estudo, esses projetos ainda se mostram viáveis economicamente. Levando em consideração as perdas elétricas e o perfil de tensão, a integração de recursos energéticos distribuídos na rede de distribuição pode trazer benefícios elétricos e redução de custos, dependendo da operação dos recursos energéticos distribuídos, demonstrando sua capacidade de fornecer serviços ancilares ao sistema elétrico. Além disso, os sistemas fotovoltaicos ainda apresentam maior competitividade se comparados com os sistemas híbridos ou os sistemas de armazenamento de energia em baterias, proporcionando retornos financeiros mais atrativos. Por fim, as diferentes amplitudes tarifárias influenciam diretamente na viabilidade de projetos de geração distribuída envolvendo sistemas de armazenamento de energia, já que quanto maior a amplitude tarifária, maior será a arbitragem tarifária que tais sistemas podem proporcionar. / [en] The prospect of declining prices in photovoltaic systems and battery energy storage systems has brought about the possibility of greater economic viability for projects involving distributed energy resources. In Brazil, Regulatory Resolution 482/2012 regulated micro and mini distributed generation, thereby encouraging the integration of these resources into distribution networks. With the enactment of Brazilian Law 14.300/2022, projects involving micro and mini distributed generation were impacted, as the net metering system for electricity became partial, demanding the addition of value to distributed generation-based business models. This work proposes a stochastic Mixed Integer Linear Programming model aimed at evaluating the economic feasibility of virtual power plants composed of different configurations of distributed energy resources, involving batteries and photovoltaic panels. To achieve this purpose, the model seeks to size the optimal annual energy contract, also providing the daily operation of the batteries. In addition to considering the aspects of Law 14.300/2022, the model incorporates tariff arbitrage practice, thus contributing to studies analyzing regulatory impacts on ventures involving batteries and photovoltaic panels in the Brazilian context. In order to comprehensively address the topic, the proposed model was implemented for distributed energy resources organized as virtual power plant, containing: (i) a photovoltaic system; (ii) a battery energy storage system; (iii) a hybrid system (composed of a photovoltaic system and a battery energy storage system); and (iv) the case study of the Brazilian electric utility Energisa Tocantins. In all applications, the economic viability of the virtual power plant was analyzed for the tariffs of Energisa Tocantins and 34 other Brazilian distributors, representing at least one distributor per Brazilian state. Additionally, comparisons were made regarding the start date of operation of the virtual power plant, highlighting the impact of Law 14.300/2022 on the economic viability of the analyzed virtual power plants, thus demonstrating the impact of said law on distributed generation projects in Brazil. In the case study of the Brazilian electric utility Energisa Tocantins, an additional analysis was conducted considering aspects of Energisa Tocantins distribution network, where distributed energy resources are allocated. In this additional analysis, electrical losses and their costs, as well as voltage profiles for two battery operation scenarios and the base case (i.e., the case without distributed energy resources in the Energisa Tocantins distribution network) were evaluated. The results showed that the implementation of Law 14.300/2022 reduced the attractiveness of projects involving distributed generation. However, for the most part, considering the parameters adopted in this study, these projects still demonstrate economic viability. Taking into account electrical losses and voltage profiles, the integration of distributed energy resources into the distribution network can bring electrical benefits and cost reductions, depending on the operation of the distributed energy resources, demonstrating their ability to provide ancillary services to the electrical system. Furthermore, photovoltaic systems still exhibit greater competitiveness when compared to hybrid systems or battery energy storage systems, providing more attractive financial returns. Finally, different tariff amplitudes directly influence the viability of distributed generation projects involving energy storage systems, as the greater the tariff amplitude, the greater the tariff arbitrage that such systems can provide.

La raréfaction des sources de production conventionnelles et leurs émissions nocives ont favorisé l’essor notable de la production renouvelable, plus durable et mieux répartie géographiquement. Toutefois, son intégration au système électrique est problématique. En effet, la production renouvelable est peu prédictible et issue de sources majoritairement incontrôlables, ce qui compromet la stabilité du réseau, la viabilité économique des producteurs et rend nécessaire la définition de solutions adaptées pour leur participation au marché de l’électricité. Dans ce contexte, le projet scientifique Winpower propose de relier par un réseau à courant continu les ressources de plusieurs acteurs possédant respectivement des fermes éoliennes offshore (acteurs EnR) et des centrales de stockage de masse (acteurs CSM). Cette configuration impose aux acteurs d’assurer conjointement la gestion du réseau électrique.Nous supposons que les acteurs participent au marché comme une entité unique : cette hypothèse permet aux acteurs EnR de tirer profit de la flexibilité des ressources contrôlables pour minimiser le risque de pénalités sur le marché de l’électricité, aux acteurs CSM de valoriser leurs ressources auprès des acteurs EnR et/ou auprès du marché et à la coalition de faciliter la gestion des déséquilibres sur le réseau électrique, en agrégeant les ressources disponibles. Dans ce cadre, notre travail s’attaque à la problématique de la participation au marché EPEX SPOT Day-Ahead de la coalition comme une centrale électrique virtuelle ou CVPP (Cooperative Virtual Power Plant). Nous proposons une architecture de pilotage multi-acteurs basée sur les systèmes multi-agents (SMA) : elle permet d’allier les objectifs et contraintes locaux des acteurs et les objectifs globaux de la coalition.Nous formalisons alors l’agrégation et la planification de l’utilisation des ressources comme un processus décisionnel de Markov (MDP), un modèle formel adapté à la décision séquentielle en environnement incertain, pour déterminer la séquence d’actions sur les ressources contrôlables qui maximise l’espérance des revenus effectifs de la coalition. Toutefois, au moment de la planification des ressources de la coalition, l’état de la production renouvelable n’est pas connue et le MDP n’est pas résoluble en l’état : on parle de MDP partiellement observable (POMDP). Nous décomposons le POMDP en un MDP classique et un état d’information (la distribution de probabilités des erreurs de prévision de la production renouvelable) ; en extrayant cet état d’information de l’expression du POMDP, nous obtenons un MDP à état d’information (IS-MDP), pour la résolution duquel nous proposons une adaptation d’un algorithme de résolution classique des MDP, le Backwards Induction.Nous décrivons alors un cadre de simulation commun pour comparer dans les mêmes conditions nos propositions et quelques autres stratégies de participation au marché dont l’état de l’art dans la gestion des ressources renouvelables et contrôlables. Les résultats obtenus confortent l’hypothèse de la minimisation du risque associé à la production renouvelable, grâce à l’agrégation des ressources et confirment l’intérêt de la coopération des acteurs EnR et CSM dans leur participation au marché de l’électricité. Enfin, l’architecture proposée offre la possibilité de distribuer le processus de décision optimale entre les différents acteurs de la coalition : nous proposons quelques pistes de solution dans cette direction. / Renewable Energy Sources (RES) has grown remarkably in last few decades. Compared to conventional energy sources, renewable generation is more available, sustainable and environment-friendly - for example, there is no greenhouse gases emission during the energy generation. However, while electrical network stability requires production and consumption equality and the electricity market constrains producers to contract future production a priori and respect their furniture commitments or pay substantial penalties, RES are mainly uncontrollable and their behavior is difficult to forecast accurately. De facto, they jeopardize the stability of the physical network and renewable producers competitiveness in the market. The Winpower project aims to design realistic, robust and stable control strategies for offshore networks connecting to the main electricity system renewable sources and controllable storage devices owned by different autonomous actors. Each actor must embed its own local physical device control strategy but a global network management mechanism, jointly decided between connected actors, should be designed as well.We assume a market participation of the actors as an unique entity (the coalition of actors connected by the Winpower network) allowing the coalition to facilitate the network management through resources aggregation, renewable producers to take advantage of controllable sources flexibility to handle market penalties risks, as well as storage devices owners to leverage their resources on the market and/or with the management of renewable imbalances. This work tackles the market participation of the coalition as a Cooperative Virtual Power Plant. For this purpose, we describe a multi-agent architecture trough the definition of intelligent agents managing and operating actors resources and the description of these agents interactions; it allows the alliance of local constraints and objectives and the global network management objective.We formalize the aggregation and planning of resources utilization as a Markov Decision Process (MDP), a formal model suited for sequential decision making in uncertain environments. Its aim is to define the sequence of actions which maximize expected actual incomes of the market participation, while decisions over controllable resources have uncertain outcomes. However, market participation decision is prior to the actual operation when renewable generation still is uncertain. Thus, the Markov Decision Process is intractable as its state in each decision time-slot is not fully observable. To solve such a Partially Observable MDP (POMDP), we decompose it into a classical MDP and an information state (a probability distribution over renewable generation errors). The Information State MDP (IS-MDP) obtained is solved with an adaptation of the Backwards Induction, a classical MDP resolution algorithm.Then, we describe a common simulation framework to compare our proposed methodology to some other strategies, including the state of the art in renewable generation market participation. Simulations results validate the resources aggregation strategy and confirm that cooperation is beneficial to renewable producers and storage devices owners when they participate in electricity market. The proposed architecture is designed to allow the distribution of the decision making between the coalition’s actors, through the implementation of a suitable coordination mechanism. We propose some distribution methodologies, to this end.