Previsão e Otimização de Flexibilidade Energética em Comunidades de Energias Renováveis

flexREC aims to develop multi-objective algorithms to manage the charging/discharging of electric vehicles parked in large buildings in a transactive energy context in communities so that the integration of renewable energy is optimized. The project intends to answer four main research questions: • How can EVs be used for providing energy flexibility services for large buildings while simultaneously guaranteeing their autonomy and mobility requirements and compliance with actual regulation? • How can the objectives and preferences of different stakeholders, such as buildings, EV users, the electrical grid and society be ensured when aiming at the optimum integration of PV using EVs as a flexibility resource? • Which algorithms can be used to manage EVs in order to ensure the optimum integration of PV, while ensuring coordination with other flexibility resources, such as batteries or Demand Response? • How can artificial intelligence methodologies be used to improve the prediction accuracy of EV requirements at the building level and flexibility at the community level to ensure optimized EV management? • Which methods can be implemented to ensure the aggregation and coordination of EVs’ flexibility for the optimization of the community in a transactive energy context? This project goes beyond the state-of-the-art by: • Implementing a V2B methodology that considers the economic relationship between different entities (the building owner and EV users) with innovative incentive schemes based on the parking period; • Ensuring the management of the V2B system without requiring difficult data to be monitored or estimated by the user; • Ensuring simultaneously the requirements and objectives of buildings and EV users; • Using artificial intelligence to predict EV users’ requirements for several EVs parked in large buildings and collaborative learning to forecast flexibility at the community level; • Ensuring the aggregation of buildings with the coordination of EVs as a flexible resource at the community level; • Implementing transactive energy techniques for community optimization.