基于遗传算法的电动汽车充电站优化选址

Shuangshuang Chen, Yue Shi, Xingyu Chen, F. Qi
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引用次数: 22

摘要

本文研究了电动汽车充电站的最优选址问题。充电站作为电动汽车的重要基础设施之一,必须广泛部署,以满足日益增长的电动汽车需求。在本研究中,我们提出了一种兼顾经济性、容量、覆盖率和便利性的充电站定位方法。为解决充电站选址问题,首先建立充电站选址优化模型,使投资成本和运输成本最小化,同时满足容量、覆盖范围和便利性约束。然后,提出了一种改进的遗传算法(GA)来解决优化问题。仿真结果表明了该定位方法的有效性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal location of electric vehicle charging stations using genetic algorithm
In this paper, we investigate the optimal location of electric vehicle (EV) charging stations. As one of the crucial infrastructures of EV, electric charging stations must be widely deployed to meet the growing needs of EV. In this study, we propose a locating method of charging station when considering economics, capacity, coverage and convenience. In order to solve the locating problem, an optimization model for charging stations location is established first, which minimizes the investment cost and transportation cost, meanwhile, the constraints of capacity, coverage and convenience should be satisfied simultaneously. Then, an improved genetic algorithm (GA) is proposed to solve the optimization problem. The simulation results indicate that the proposed locating method is effective and practical.
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