Optimal Urban EV Charging Station Site Selection and Capacity Determination Considering Comprehensive Benefits of Vehicle-Station-Grid

iEnergy Pub Date : 2024-09-01 DOI:10.23919/IEN.2024.0021
Hongwei Li;Yufeng Song;Jiuding Tan;Yi Cui;Shuaibing Li;Yongqiang Kang;Haiying Dong
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Abstract

This paper presents an optimization model for the location and capacity of electric vehicle (EV) charging stations. The model takes the multiple factors of the “vehicle-station-grid” system into account. Then, ArcScene is used to couple the road and power grid models and ensure that the coupling system is strictly under the goal of minimizing the total social cost, which includes the operator cost, user charging cost, and power grid loss. An immune particle swarm optimization algorithm (IPSOA) is proposed in this paper to obtain the optimal coupling strategy. The simulation results show that the algorithm has good convergence and performs well in solving multi-modal problems. It also balances the interests of users, operators, and the power grid. Compared with other schemes, the grid loss cost is reduced by 11.1% and 17.8%, and the total social cost decreases by 9.96% and 3.22%.
考虑车-站-网综合效益的最佳城市电动汽车充电站选址和容量确定
本文介绍了电动汽车(EV)充电站位置和容量的优化模型。该模型考虑了 "车-站-网 "系统的多种因素。然后,利用 ArcScene 将道路和电网模型耦合,确保耦合系统严格遵循社会总成本最小化的目标,其中包括运营商成本、用户充电成本和电网损耗。本文提出了一种免疫粒子群优化算法(IPSOA)来获得最优耦合策略。仿真结果表明,该算法具有良好的收敛性,在解决多模式问题时表现出色。它还兼顾了用户、运营商和电网的利益。与其他方案相比,电网损耗成本分别降低了 11.1% 和 17.8%,社会总成本分别降低了 9.96% 和 3.22%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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