Differential Evolution and Fuzzy-Logic-Based Predictive Algorithm for V2G Charging Stations

This work proposes a differential evolution algorithm to control vehicle-to-grid (V2G) system based on photovoltaic generation and energy cost curves, constraints associated with the power converters’ operation, battery charging strategy, initial budgets. The is designed trade off batteries’ state of charge profits gained from selling grid. To achieve this balance, fuzzy controller employed acts forecasts electricity, within prediction windows 120 min, adapting rate or discharging. Simulation results show that for different curves budgets, target reached at end time horizon. By evaluating proposed scheme under scenarios, algorithm’s performance proven be suitable future practical deployment.