基于社会物理信息系统的异质电动汽车充电优化策略

Charging Optimization Strategy of Heterogeneous Electric Vehicles Based on Cyber-Physical-Social Systems

本文指出随着电动汽车的快速发展,电动汽车对电网的影响及其在电力系统调度和需求侧响应方面的潜力非常值得关注;具有异质电动汽车的智能电网已经成为社会-物理-信息系统(CPSS)。本文根据异质电动汽车充电数据和行为分析,建立了基于改进的多目标粒子群算法的充电优化模型。仿真结果表明,该模型能够综合考虑电网负载能力和电动汽车用户充电需要,以充电站利润最大化、减小电网波动为目标,有效地实现了电动汽车用户、充电站和电网的充放电需求。

This paper points out that with the rapid development of electric vehicles(EVs),the impact of electric vehicles on the grid and their potential in power system scheduling and demand-side response are of great concern;a smart grid with heterogeneous electric vehicles has become a Cyber-Physical-Social System(CPSS).Based on heterogeneous EV charging data and behavior analysis,a charging optimization model based on improved multi-objective particle swarm optimization(PSO)algorithm is established in this paper.The simulation results show that the model can comprehensively consider the load capacity of the power grid and the charging needs of EV users,and effectively realize the charging and discharging needs of EV users,charging stations and the power grid,with the goal of maximizing the profit of charging stations and reducing the fluctuations of the power grid.