Sebastian Torres Franco, Ivan Camilo Durán Tovar, Mónica Marcela Suárez Pradilla, Agustin Marulanda Guerra
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This article presents a heuristic methodology for urban transportation networks, that considers the deployment of the charging stations for coverage purposes, and the fulfilment of user preferences and constraints as two separated processes. In this methodology, a Reallocation Algorithm is formulated to prioritize the selection of Locations of Interest, and to reduce the number of stations with overlapping covering areas. The methodology results are compared to those drawn from a Greedy Algorithm based on a multipath consideration, in an extensive metropolitan transportation network. 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引用次数: 2
摘要
Sebastian Torres Franco,哥伦比亚哥伦比亚大学电气工程系Julio Garavito,哥伦比亚波哥大。电子邮件:sebastian.torres@escuelaing.edu.co摘要公共充电基础设施的缺乏一直是阻碍传统汽车向电动汽车技术转型的主要障碍之一。为了加快这一技术转型,有必要制定最佳充电站选址策略,以提高用户信心,并将投资成本保持在可接受的水平内。然而,现有的这方面的工作通常基于多径考虑或多目标函数,这导致城市交通网络的计算工作量很大。本文提出了一种适用于城市交通网络的启发式方法,将充电站的部署和用户偏好和约束的实现视为两个独立的过程。在该方法中,制定了重新定位算法,以优先选择感兴趣的位置,并减少覆盖区域重叠的站点数量。在广泛的大都市交通网络中,将该方法的结果与基于多径考虑的贪婪算法得出的结果进行了比较。结果表明,所提出的方法显著减少了解决定位问题所需的计算时间,此外,允许获得与考虑k 1⁄4 2和k 1⁄4 3偏差路径时获得的结果相似的结果。
Electric vehicle charging stations’ location in urban transportation networks: A heuristic methodology
The lack of public charging infrastructure has been one of the main barriers preventing the technological transition from traditional vehicles to electric vehicles. To accelerate this technological transition, it is necessary to elaborate optimal charging station location strategies to increase the user confidence, and maintain investment costs within acceptable levels. However, the existing works for this purpose are often based on multipath considerations or multi-objective functions, that result in taxing computational efforts for urban transportation networks. This article presents a heuristic methodology for urban transportation networks, that considers the deployment of the charging stations for coverage purposes, and the fulfilment of user preferences and constraints as two separated processes. In this methodology, a Reallocation Algorithm is formulated to prioritize the selection of Locations of Interest, and to reduce the number of stations with overlapping covering areas. The methodology results are compared to those drawn from a Greedy Algorithm based on a multipath consideration, in an extensive metropolitan transportation network. The results show that the proposed methodology significantly reduce the computational time required for solving the location problem, and furthermore, allows for similar results to those obtained when considering k = 2 and k = 3 deviation paths.