PDF《基于充电设备利用率的电动汽车充电路径多目标优化调度》

第47 卷第4期电力系统保护与控制 Vol.

47 No.4 2019年2月16日Power System Protection and Control Feb. 16,

2019 DOI: 10.7667/PSPC180279 基于充电设备利用率的电动汽车充电路径多目标优化调度 周天沛 1,2 ,孙伟2(1.徐州工业职业技术学院机电学院,江苏 徐州 221140;

2.中国矿业大学信控学院,江苏 徐州 221008) 摘要:由于电动汽车车主选择充电站具有较大的随机性,使得各充电站的利用率存在较大的差异,从而造成整个 电网的负荷失衡,影响配电网的稳定性和安全性.针对上述问题,将行驶路程最近、时间最短、充电站时间利用 率偏差最小和功率利用率偏差最小作为优化目标,建立了电动汽车充电路径多目标优化调度模型.在对该模型进 行求解的过程中,提出了基于细菌趋化的改进粒子群算法进行求解.仿真结果表明,采用该算法后,电动汽车车 主可以根据区域内充电站的利用率情况有目的选择充电站,实现均衡化充电站利用率的目的. 关键词:电动汽车;

充电路径;

多目标优化;

充电设备利用率;

细菌趋化 PSO 算法 Multi-objective optimal scheduling of electric vehicles for charging route based on utilization rate of charging device ZHOU Tianpei1,

2 , SUN Wei2 (1. School of Mechatronic Engineering, Xuzhou College of Industrial and Technology, Xuzhou 221140, China;

2. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221008, China) Abstract: The utilization of every charging station varies greatly because the Electric Vehicle (EV) owners have great randomicity for choosing charging station, which causes the load imbalance of the whole power grid and affects the stability and security of the power grid. In view of the problem, minimum driving distance, minimum time and minimum deviation of time utilization rate and power utilization rate for charging station as optimization objectives, multi-objective optimal scheduling model of EVs for charging route is built. An improved Particle Swarm Optimization Algorithm based on Bacterial Chemotaxis (PSOBC) is proposed in order to solve the model. The simulation results show that the EV owners can purposefully choose charging stations according to the utilization of the charging stations in the area after adopting the proposed algorithm, which realizes the purpose of utilization equalization for charging stations. This work is supported by Industry-Academy-Research Cooperation Project of Jiangsu Province (No. BY2016026-01) and Natural Science Research Project in Universities of Jiangsu Province (No. 16KJB480006). Key words: electric vehicle (EV);

charging route;

multi-objective optimization;

utilization efficiency of charging device;

particle swarm optimization based on bacterial chemotaxis (PSOBC)

0 引言 由于电动汽车具有环保和节能的优点,受到了 各国政府的大力扶持和推广[1] .但是由于受到车载 蓄电池容量的限制,大部分电动汽车的行驶里程不 超过

200 km, 因此电动汽车为了避免电量不足影响 正常出行,需要到充电站为其补充电能,因此充电 站的建设是作为电动汽车能够实现产业化和商业化 基金项目:江苏省产学研合作计划项目资助(BY2016026-01);

江苏省高校自然科学研究面上项目资助(16KJB480006) 的重要条件之一[2] .截至

2013 年底,全世界建成

8 000 座充电站、

32 万个充电桩, 其中我国建成

723 座充电站、2.8 万个充电桩.预计到