Electric vehicle charging stations emplacement using genetic algorithms and agent-based simulation
Electric vehicle charging stations emplacement using genetic algorithms and agent-based simulation
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DOI：
10.1016/j.eswa.2022.116739
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发表时间：
2022-03-08
影响因子：
8.5
通讯作者：
Julian, Vicente
中科院分区：
文献类型：
--
作者：
Jordan, Jaume;Palanca, Javier;Julian, Vicente
电动汽车在城市环境中的日益明显的融合是一个不可否认的变化。电动汽车以更高的自主性和更低的价格出现在市场上，这促进了车队的逐步变化。然而，电动汽车带来了需要提供足够的充电站分布在整个城市，使车辆的自主性不是问题。这项工作介绍了如何使用遗传算法，分析一个城市的开放数据源，提出最合适的位置，这些站。该建议是一系列实验的输入，这些实验模拟了沿着城市放置这些站的影响，以衡量遗传算法提出的解决方案的好处。为此，围绕舰队模拟器构建了基于代理的模拟基础设施。
The increasingly evident incorporation of the electric vehicle in urban environments is an already undeniable change. Electric vehicles are appearing on the market with more autonomy and lower prices, which is facilitating the progressive change of the vehicle fleet. However, the electric vehicle brings with it the need to provide enough charging stations distributed throughout the city, so that the autonomy of the vehicle is not a problem. This work presents how a genetic algorithm that analyzes the open data sources of a city is used to propose the most suitable locations for these stations. This proposal is the input for a series of experiments that simulate the impact that has the placement of these stations along the city, in order to measure the benefits of the solution proposed by the genetic algorithm. To do this, an agent-based simulation infrastructure was built around a fleet simulator.