Modelo de precificação dinâmico para carregamento de veículos elétricos em estações de recarga rápida considerando previsões de operação e aspectos de mobilidade regional

• Ano de defesa: 2023
• Autor(a) principal: Silva, Leonardo Nogueira Fontoura da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia Elétrica; UFSM; Programa de Pós-Graduação em Engenharia Elétrica; Centro de Tecnologia
• Palavras-chave em Português: Veículos elétricos; Estações de recarga rápida; Modelo espaço-temporal; Precificação de recarga; Otimização estocástica; Microgrids; Electrical vehicles; Fast-charging stations; Spatial and temporal model; Charging price; Stochastic optimization; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufsm.br/handle/1/34346

Currently, the Electrical Vehicle (EV) market is in expansion. It occurs mainly due to government incentives for reducing greenhouse emissions and foreign energy independence. The growing perspectives from the EV market have been updated concerning the EV global cost reduction, boosted by battery cost decrease, range indexes increase, and the development of charging infrastructures. Thus, the charging events behavior discussions must be improved due to their relative impact on the system load curves, mainly influenced by the residential charging events. Another relevant aspect is the intercity charging infrastructure. However, due to the disruptive technology aspect, it needs to be better explored. For this charging concept, the path distance is sometimes more significant than the EV range, and the EV user must stop and recharge during the trip. Two main factors impact charging events along the roads and highways: the anxiety range of the user related to the EV state-of-charge and the charging time and cost. In this form, fast-charging station alternatives (higher than 50kW) are essential, reducing charging times' influence on the total travel time. This doctoral thesis aims to develop a dynamic price model for fast-charging stations composed of charger units and local integrations with battery energy storage systems and distributed generation in a Microgrid model. Then, the space-temporal traffic flow model developed estimates the fast-charging station operation and the respective load curves based on EV user behavior projections obtained using Monte Carlo Simulations. These outputs, combined with distributed generation forecasting, become inputs of a proposed Stochastic Mixed Integer Linear Programming to return the daily optimized operating costs and the storage system management. Finally, the relationship between operation and fixed costs with the local grid prices results in a charging hourly price model for the next 24 hours, focusing on the equilibrium between station profit and consumer impact, incentives to charging events distribution along the day, and queue reduction. The case study results show the viability of the model and discussions about the influence of factors like placing and sizing, EV user and charging station owner decisions on the calculated charging prices.