A Two-Stage Economic Optimization and Predictive Control for EV Microgrid

This paper focuses on a two-stage framework for economic optimization to maximize the profits of electric-vehicle (EV) microgrid. In the first stage, an economic optimization problem at the day-ahead time scale is solved to determine the power purchased from load serving entities (LSE), and make an optimal price decision (parking fee and charging fee) while considering with the EVs uncertainties. In the second stage, a real-time model predictive control strategy is proposed to meet the EVs requirement and minimize the operation cost. Through two-stage scheduling, EV microgrid can guarantee long-term safe and efficient operation, while ensuring maximum benefits. The simulation results show that the proposed method in this paper can provide reliable power supply to the EVs, increase the EV microgrid revenue and ensure the safe operation of the EV microgrid system.