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Optimal location of EV charging stations in a neighborhood considering a multi-objective approach

机译：考虑到多目标方法的邻居EV充电站的最佳位置

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摘要

Despite the environmental and economic benefits of Electric Vehicles (EVs), distribution network operators will need to understand the location where the charging infrastructure will be placed to ensure EV users' needs are met. In this sense, this work proposes a methodology to define the optimal location of EV semi-fast charging stations (CS) at a neighborhood level, through a multi-objective approach. It applies a hierarchical clustering method to define CS service zones, considering both technical and mobility aspects. Besides, it considers uncertainties related to the EV load profile to determine the CS capacity, based on the user's charging behavior. A Pareto Frontier method is deployed to support the decision-making process on CS optimal location, considering utility and EV users' preferences. The results indicate that the best CS locations for mid-term EV penetration can also fit into long-term planning, with higher EV charging demand. Thus, these locations would be good candidates for the power utility to make initial investments, regarding both planning horizons. A real distribution system case is used to demonstrate the applicability of the results.
机译：尽管电动车的环境和经济效益（EVS），配送网络运营商需要了解收费基础设施将放置以确保EV用户需求的位置。从这个意义上讲，通过多目标方法提出了一种方法来定义邻域级的EV半快充电站（CS）的最佳位置。它应用分层聚类方法来定义CS服务区域，考虑到技术和移动性方面。此外，它考虑了与EV负载配置文件相关的不确定性，以根据用户的计费行为来确定CS容量。部署了Pareto前沿方法，以支持CS最佳位置的决策过程，考虑实用程序和EV用户的首选项。结果表明，用于中期EV渗透的最佳CS位置也可以符合长期规划，具有更高的EV充电需求。因此，这些位置将是用于初始投资的能力效用的良好候选者，这是一个规划视野。使用实际分配系统壳体来证明结果的适用性。

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