Mobility‐aware optimal trade planning and mean field game‐based decentralized charging control for large‐scale electric vehicles

Abstract

The uncertainty mobility characteristics of electric vehicles (EVs) are a key factor that influence the charging station trade income with the power grid. In this paper, a hierarchical energy management strategy is proposed for charging stations when large‐scale EVs are considered. The traveling and parking mobility characteristics of EVs are first extracted by analyzing historical real‐world traveling data. Then, a day‐ahead power trade planning strategy between the grid and charging station to maximize incomes is developed by solving a mixed‐integer linear programming problem. Furthermore, based on EV mobility characteristics, clusters are generated to classify different parking behaviors, where a mean field game‐based decentralized charging control scheme for individual EVs in each cluster is employed. The target of the proposed optimal charging controller is to guarantee the charging power tracking performance and the power demand of individual EV at the terminal time for subsequent travel. Finally, simulations on MATLAB/Simulink platform are conducted to show the effectiveness of the proposed hierarchical energy management strategy.