A Graphical Game Approach to Electrical Vehicle Charging Scheduling: Correlated Equilibrium and Latency Minimization

Abstract

Electric vehicles (EVs) are becoming increasingly popular, but the frequent charging and large charging latency remain major obstacles to the EV industry. This article focuses on the charging scheduling of on-the-move EVs in a transportation network to minimize EVs' charging latency, including driving time to charging stations (CSs), wait time and charging time. We formulate this charging scheduling problem as a graphical game to characterize the strong couplings of charging latency among neighboring EV players. Specially, we investigate correlated equilibrium (CE) to describe the joint strategies of EV players, which is expected to further reduce the charging latency of EVs compared with Nash equilibrium (NE). It is shown that CE always exists in a finite game, and can be found by linear programming tools. In addition, we propose a method of wait time prediction, which can improve the prediction accuracy by combining the data of deterministic EV arrivals and the stochastic property of potential EV arrivals. Simulation studies are used to examine the performance of the proposed game-based approach, the efficiency of CE, the preciseness of our proposed wait time prediction method, the impacts of CS deployment on EVs' charging latency, etc. We can draw a conclusion that our method has apparent advantages in situations where the locations of EV players are in dense manners.