A Two-Stage Energy Management Strategy for Electric Vehicle Supercharging Stations Based on Model Predictive Control

Charging stations equipped with energy storage systems can reduce the peak load and improve the operational economic benefits. However, the charging load of electric vehicles (EVs) has random fluctuations, posing challenges to the energy management strategies of energy storage systems. To address this issue, a model predictive control (MPC)-based energy management strategy for EV supercharging stations is proposed. In the day-ahead phase, the objective function is to minimize the cost of the charging station throughout the day, and a day-ahead scheduling plan is developed. In the real-time phase, a load deviation band is established based on the day-ahead plan, and a real-time energy management strategy for the energy storage system is proposed. The effectiveness of the strategy is illustrated by comparing the strategy proposed in this paper with the logical threshold strategy using a supercharging station in Beijing as an example.