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Resumo(s)
Este trabalho propõe uma metodologia para integrar os veículos elétricos (VE’s) como
sistemas de armazenamento de energia local numa Comunidade de Energia Renovável
(CER). O objetivo é otimizar a gestão local de energia, minimizando o desgaste das baterias
através da aplicação de algoritmos inteligentes de carregamento e maximizando o retorno
financeiro dos participantes. Para isso, utilizam-se técnicas de valorização energética e
aumenta-se a utilização da energia gerada, reduzindo a injeção na rede e aumentando a
eficiência tanto do ponto de vista energético como do financeiro.
A gestão da energia é realizada de forma descentralizada, com a participação ativa
dos membros da CER. O sistema recolhe dados sobre consumo, geração e ligação dos
VE’s aos carregadores em intervalos de 15 minutos. A partir destes dados, aplicam-se
algoritmos de inteligência artificial para prever consumos, geração e disponibilidade dos
VE’s, permitindo um planeamento otimizado da utilização da energia na comunidade.
Os resultados demonstram uma redução significativa na fatura elétrica, variando entre
53% e 90%, consoante o participante. Além disso, foi avaliada a viabilidade económica
considerando o custo de degradação das baterias. No caso de estudo analisado, a utilização
dos VE’s como armazenamento local ainda não se revela financeiramente viável. No
entanto, são identificadas condições que podem tornar esta metodologia economicamente
viável no futuro.
This work proposes a methodology to integrate electric vehicles (EVs) as local energy storage systems within a Renewable Energy Community (REC). The goal is to optimize local energy management by minimizing battery degradation through the application of intelligent charging algorithms and maximizing the financial return for participants. To achieve this, energy valorization techniques are employed, and the use of generated energy is increased, reducing grid injection and enhancing efficiency from both an energy and financial perspective. Energy management is carried out in a decentralized manner, with the active partici- pation of REC members. The system collects data on consumption, generation, and the connection of EVs to chargers at 15-minute intervals. Based on this data, artificial intel- ligence algorithms are applied to forecast consumption, generation, and EV availability, enabling optimized energy planning within the community. The results show a significant reduction in electricity costs, ranging between 53% and 90%, depending on the participant. Additionally, the economic feasibility of the methodology was assessed, considering the cost of battery degradation. In the analyzed case study, the use of EVs as local storage is not yet financially viable. However, conditions that could make this methodology economically feasible in the future have been identified.
This work proposes a methodology to integrate electric vehicles (EVs) as local energy storage systems within a Renewable Energy Community (REC). The goal is to optimize local energy management by minimizing battery degradation through the application of intelligent charging algorithms and maximizing the financial return for participants. To achieve this, energy valorization techniques are employed, and the use of generated energy is increased, reducing grid injection and enhancing efficiency from both an energy and financial perspective. Energy management is carried out in a decentralized manner, with the active partici- pation of REC members. The system collects data on consumption, generation, and the connection of EVs to chargers at 15-minute intervals. Based on this data, artificial intel- ligence algorithms are applied to forecast consumption, generation, and EV availability, enabling optimized energy planning within the community. The results show a significant reduction in electricity costs, ranging between 53% and 90%, depending on the participant. Additionally, the economic feasibility of the methodology was assessed, considering the cost of battery degradation. In the analyzed case study, the use of EVs as local storage is not yet financially viable. However, conditions that could make this methodology economically feasible in the future have been identified.
Descrição
Palavras-chave
Comunidade de Energia Renovável Previsão Séries Temporais Gestão de sistemas de armazenamento
