Electric vehicle charging schedule considering shared charging pile based on Generalized Nash Game

Abstract Electric vehicle (EV) will not only effectively promote the popularization of charging facilities, but also reduce the dependence on fuel vehicles. However, large-scale charging behaviours of EVs will bring new challenges to match between charging facilities and EVs. Due to the limited capacity of the centralized charging stations, it is difficult to meet the charging demands of EVs in certain areas, especially during the peak load periods. To solve the insufficiency of charging capacity caused by the mismatch between charging stations and EV charging loads, this paper proposes a hierarchical scheduling model of EVs considering shared charging piles. The upper scheduling model determines the charging time of EVs based on the charging demands. The lower scheduling model coordinates charging stations and shared charging piles to determine the charging locations of EVs. The sharing scheme of private charging piles is determined by sharing capacity model based on the generalized Nash game. The quantum particle swarm algorithm with the dynamic feedback mechanism is adopted for a better convergence of the solving process of the hierarchical scheduling model. The simulation results on IEEE 33-node system are conducted to validate the effectiveness of the proposed model and solution algorithm, which show the extensive potential applications in EV scheduling.