2,018 research outputs found

    Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

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    Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

    A chance-constrained approach for electric vehicle aggregator participation in the reserve market

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    As recorrentes preocupações ambientais têm levado a que se verifiquem alterações nos sistemas de energia, sendo que a aposta em sistemas distribuídos é já uma realidade, contudo a aposta em energia renovável está, normalmente, associada a intermitência no que diz respeito ao aproveitamento de energia proveniente do sol, vento, ondas, etc. Assim, neste paradigma, surgem os veículos elétricos que fazem parte do sistema e têm boas perspetivas de verem a sua penetração a aumentar exponencialmente num futuro próximo, pelo que devem ser estudadas novas formas de relação entre este recurso e os agentes de mercado. Neste momento, já é possível carregar e descarregar os veículos elétricos, o que, auxiliado pelas decisões e algoritmos corretos, pode contribuir com um apoio fundamental para a rede de energia tratar de forma simplificada congestionamentos e variações nos valores nominais de tensão e frequência. Tudo isto, está dependente da disponibilidade do proprietário do veículo para fornecer este tipo de serviço e que estados mínimos de carga sejam assegurados para as viagens diárias. Geralmente, os operadores da rede elétrica gerem elevados níveis de geração e carga, pelo que surge a necessidade do conceito de agregador de veículos elétricos, que terá a função de juntar vários veículos elétricos para assim corresponder de forma mais eficaz e com capacidade de oferta conforme as necessidades da rede.Neste trabalho, pretende-se otimizar o lucro do agregador, que poderá estar sujeito a penalidades em caso de falha no fornecimento de reserva a subir ou a descer, não colocando de parte a fiabilidade no fornecimento do serviço ao mercado de reserva. Deste modo, são utilizadas técnicas de otimização estocástica que pretendem modelar incertezas de uma pequena frota de veículos elétricos como disponibilidade para fornecer o serviço e perfis de consumo. A técnica de otimização chance-constrained, mais precisamente as relaxações Big-M e McCormick, são aplicadas a fim de analisar o risco da oferta que o agregador deve submeter em mercado.Para situações de mercado real, mais precisamente o FCR-N na Dinamarca, são explorados diversos cenários para diferentes níveis de risco submetidos em mercado, diferentes probabilidades de o veículo estar conectado à redeThe recurring environmental concerns have led to changes in energy systems, and the investment in distributed systems is in progress, however, the investment in renewable energy is usually associated with intermittent with regard to the use of energy from the sun, wind, waves, etc. Thus, within this scope, electric vehicles that are part of the system rises and stand good chances of seeing their penetration increase significantly in the near future, so new forms of relationship between this resource and the market agents should be addressed. At this point, it is already possible to charge and discharge electric vehicles, which, aided by correct decisions and algorithms, can contribute with a fundamental support for the energy network to deal in a simplified way with congestion and fluctuations in voltage and frequency. It all depends on the willingness of the vehicle owner to provide this type of service and that minimum states of charge are ensured for the daily trips. In general, electricity grid operators manage high power generation and load capacities, so there is a demand for the concept of electric vehicle aggregator, which will have the function to bring together several electric vehicles to correspond more effectively and with supply capacity according to the requirements of the grid.The aim of this work is to optimise the profit of the aggregator, which may be subject to penalties in the event of a failure in the provision of reserve upward or downward, regardless of the reliability in the provision of the service to the reserve market. Therefore, stochastic optimization techniques are used to model uncertainties of a small fleet of electric vehicles as availability to provide the service and consumption profiles. The optimization technique chance-constrained, namely Big-M and McCormick the relaxation methods, are applied in order to analyze the risk the aggregator must submit in the market. For real market cases, specifically the FCR-N in Denmark, several scenarios are analyzed for different levels of risk submitted in the market, different probabilities of the vehicle being connected to the grid

    Virtual power plants with electric vehicles

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    The benefits of integrating aggregated Electric Vehicles (EV) within the Virtual Power Plant (VPP) concept, are addressed. Two types of EV aggregators are identified: i) Electric Vehicle Residential Aggregator (EVRA), which is responsible for the management of dispersed and clustered EVs in a residential area and ii) Electric Vehicle Commercial Aggregator (EVCA), which is responsible for the management of EVs clustered in a single car park. A case study of a workplace EVCA is presented, providing an insight on its operation and service capabilities
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