Learning-Assisted Energy Optimization of Electric Vehicle Fleets in Renewable-Rich Microgrids
In this paper, we propose a learning-enabled framework to support the energy management of EV fleets operating in renewable-rich microgrids. The framework leverages a combination of Reinforcement Learning, Model Predictive Control, and Probabilistic Renewable Forecasting to optimize the charging schedules of EVs and th...