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

• Autor(a) principal: António Sérgio Barbosa Faria
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/121802
• topic: Ciências da engenharia e tecnologias; Engineering and technology

The 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.