Metodologia para gerenciamento de sistemas de armazenamento com baterias e operação flexível em tempo real para suporte a instalações com geração distribuída - Farias, Héricles Eduardo Oliveira (2021)
This dissertation presents a management methodology applied to battery energy storage systems connected to electric vehicle charging stations supported by distributed generation. The study is divided in three main parts: The first part consists of a planning process for vehicle recharge, taking into account only scheduled consumers. In this step the meta heurisitic Evolutionary Particle Swarm Optimization (EPSO) along with the Monte Carlo process are used. The scheduling also considers both the recharge station and the grid interests. The second step refers to the optimized dispatch of the battery bank based on the information provided by the previous step. In this step, the optimization takes into account factors such as battery degradation and costs reduction. A multi-criteria optimization model was used to solve this problem. Finally, the last step considers the operation for both scheduled and non scheduled users in real time. In this step the daily operation of the recharge station is calculated, based on the defined strategies and considering the arrival of new users to the station. At daily operation, load and cash flow processes are used, based on rule based approaches. For validation, the case study takes into account different factors such as: charging types, user comfort, station and grid interests, among others. The results presented a good operation of the charging station. Both the scheduling and the dispatch optimization processes showed benefits to the station without compromising the grid or the battery bank operation. With the proposed scheduling, the recharge station has a better distribution of its own load in the following day, and improves the coordination of the distributed resources dispatch. With the optimization of the battery bank dispatch, the recharge station can: reduce the operational costs related to energy purchase from the grid; reduce the battery degradation; and maximize the self consumption of distributed generation.