Combinatorial Optimal Location Design of Charging Stations based on Multi-agent Simulation

Hideaki Uchida, H. Fujii, S. Yoshimura
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引用次数: 1

Abstract

In recent years, the introduction of electric vehicles (EVs) has become increasingly desirable from an environmental perspective. However, it is important to develop suitable charging equipment and infrastructure, as EVs tend to have shorter cruising distances than gasoline-powered vehicles. Various data-driven methods have been proposed for the placement of charging stations (CSs). To date, however, there have been few simulation-driven approaches that can take account of the microscale interactions among vehicles. Therefore, in this paper, we propose an efficient placement method based on multi-agent traffic simulations with an improved scoring function. In addition, as the number of CSs increase in proportion to the spread of EVs, we solve a multiple location design problem formulated as a combinatorial optimization technique. Numerical experiments were conducted on a realistic network in the central part of Wakayama Prefecture in Japan, and it was shown that the proposed method could improve the performance indicator of CS placement compared with the conventional method. Furthermore, the scenario of multiple CS installations at one time demonstrated that good combinations could be obtained.
基于多智能体仿真的充电站组合优化选址设计
近年来,从环保的角度来看,电动汽车的引入越来越受欢迎。然而,开发合适的充电设备和基础设施是很重要的,因为电动汽车的巡航距离往往比汽油动力汽车短。人们提出了各种数据驱动的充电站(CSs)布置方法。然而,到目前为止,很少有模拟驱动的方法可以考虑到车辆之间的微观相互作用。因此,在本文中,我们提出了一种基于多智能体流量模拟的高效放置方法,并改进了评分函数。此外,当CSs的数量与电动汽车的扩散成比例增加时,我们解决了一个用组合优化技术表述的多位置设计问题。在日本和歌山县中部的一个现实网络上进行了数值实验,结果表明,与传统方法相比,该方法可以提高CS放置的性能指标。此外,同时安装多个CS的场景表明,可以获得良好的组合。
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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