潘含芝, 于艾清, 王育飞, 等. 均衡不同主体利益的电动汽车充电站选址定容[J]. 现代电力, 2023, 40(6): 995-1004. DOI:10.19725/j.cnki.1007-2322.2022.0114
引用本文: 潘含芝, 于艾清, 王育飞, 等. 均衡不同主体利益的电动汽车充电站选址定容[J]. 现代电力, 2023, 40(6): 995-1004.DOI:10.19725/j.cnki.1007-2322.2022.0114
PAN Hanzhi, YU Aiqing, WANG Yufei, et al. Site Selection and Capacity Determination of EV Charging Station to Balance Interests of Different Entities[J]. Modern Electric Power, 2023, 40(6): 995-1004. DOI:10.19725/j.cnki.1007-2322.2022.0114
Citation: PAN Hanzhi, YU Aiqing, WANG Yufei, et al. Site Selection and Capacity Determination of EV Charging Station to Balance Interests of Different Entities[J].Modern Electric Power, 2023, 40(6): 995-1004.DOI:10.19725/j.cnki.1007-2322.2022.0114

均衡不同主体利益的电动汽车充电站选址定容

Site Selection and Capacity Determination of EV Charging Station to Balance Interests of Different Entities

  • 摘要:针对电动汽车充电站选址定容问题,提出了一种多场景下计及配电网、充电站和用户多主体经济利益模型。首先通过对比配电网在正常运行环境和极端天气条件下的运行经济性与负荷损失成本,对电动汽车充电站进行预选址;其次以充电站预选方案以及节假日、工作日交通流量分布差异为基础,综合考虑充电站与用户端经济性对充电站站址容量进行优化;采用粒子群算法以及Voronoi图联合增加局部寻优效果,进一步优化电动汽车充电站选址定容结果。最后利用某地区的实际算例进行仿真分析,结果验证了所提电动汽车充电站规划方案的可行性和有效性。

    Abstract:In allusion to the site selection and capacity determination of the electric vehicle (abbr. EV) charging station, a multi-agent economic benefit model for distribution network, charging station and users under multi-scenarios was proposed. Firstly, by means of comparing the operation economy and load loss cost of distribution network under normal operating environment and under extreme weather conditions, the site pre-selection of the site for EV charging station was performed. Secondly, taking the preselected scheme of the charging station and the traffic flow distribution difference on holidays and working days as the basis and overall considering the economy of the charging station and the economy at the user side, the site and the capacity of the charging station were optimized. The local optimization effect was enhanced by joint utilizing particle swarm optimization and Voronoi diagram, so the result of site selection and capacity determination of EV charging station were further optimized. Finally, based on an actual computing example of a certain region the simulation analysis was conducted. Simulation results show that the proposed planning scheme of EV charging station is feasible and effective.

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