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Optimal locations of electric public charging stations using real world vehicle travel patterns

机译:使用实际车辆行驶模式的电动公共充电站的最佳位置

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摘要

We propose an optimization model based on vehicle travel patterns to capture public charging demand and select the locations of public charging stations to maximize the amount of vehicle-miles-traveled (VMT) being electrified. The formulated model is applied to Beijing, China as a case study using vehicle trajectory data of 11,880 taxis over a period of three weeks. The mathematical problem is formulated in GAMS modeling environment and Cplex optimizer is used to find the optimal solutions. Formulating mathematical model properly, input data transformation, and Cplex option adjustment are considered for accommodating large-scale data. We show that, compared to the 40 existing public charging stations, the 40 optimal ones selected by the model can increase electrified fleet VMT by 59% and 88% for slow and fast charging, respectively. Charging demand for the taxi fleet concentrates in the inner city. When the total number of charging stations increase, the locations of the optimal stations expand outward from the inner city. While more charging stations increase the electrified fleet VMT, the marginal gain diminishes quicldy regardless of charging speed. (C) 2015 Elsevier Ltd. All rights reserved.
机译:我们提出了一种基于车辆行驶模式的优化模型,以捕获公共充电需求,并选择公共充电站的位置,以使正在行驶的车辆行驶里程(VMT)最大化。该模型以三个星期内11,880辆出租车的车辆轨迹数据为例,应用于中国北京。在GAMS建模环境中阐述了数学问题,并使用Cplex优化器找到了最佳解决方案。为了容纳大规模数据,考虑了正确地建立数学模型,输入数据转换和Cplex选项调整。我们表明,与现有的40个公共充电站相比,该模型选择的40个最佳充电站可以分别对慢速和快速充电的电动车队VMT分别增加59%和88%。出租车车队的充电需求集中在市中心。当充电站总数增加时,最佳充电站的位置将从内城区向外扩展。当更多的充电站增加了电动车队的VMT时,无论充电速度如何,边际收益都会减少。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Transportation Research》 |2015年第12期|165-176|共12页
  • 作者单位

    Koc Univ, Dept Ind Engn, TR-34450 Istanbul, Turkey|Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA;

    Purdue Univ, Sch Ind Engn, W Lafayette, IN 47907 USA|Purdue Univ, Div Environm & Ecol Engn, W Lafayette, IN 47907 USA;

    Koc Univ, Dept Ind Engn, TR-34450 Istanbul, Turkey;

    Univ Michigan, Sch Nat Resources & Environm, Ann Arbor, MI 48109 USA|Univ Michigan, Dept Civil & Environm Engn, Ann Arbor, MI 48109 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Optimization; Electric vehicles; Vehicle trajectory; Charging infrastructure planning;

    机译:优化;电动汽车;车辆轨迹;充电基础设施规划;

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