Location of electric vehicle charging stations: A perspective using the grey decision-making model
Location of electric vehicle charging stations: A perspective using the grey decision-making model
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DOI：
10.1016/j.energy.2019.02.015
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发表时间：
2019-04
期刊：
影响因子：
9
通讯作者：
Xianqiang Ren;Huiming Zhang;Ruohan Hu;Y. Qiu
中科院分区：
文献类型：
--
作者：
Xianqiang Ren;Huiming Zhang;Ruohan Hu;Y. Qiu
充电站的合理选址将促进新能源汽车产业的快速发展。本文首先建立了以社会总成本最小为目标的选址模型，并采用遗传算法进行求解。其次，从土地成本、建设成本、道路交通流量、电网条件和周边环境5个区位影响因素构建了评价指标体系。数值研究表明，灰色关联决策和灰靶理论应用于最优选址时，具有操作简单、对数据采集和处理要求低等优点。
the reasonable location of a charging station will promote the rapid development of the new energy automobile industry. This paper initially establishes the location model of minimizing the total social cost with the purpose of a genetic algorithm solution. Next, an evaluation index system is constructed based on five location influencing factors; land cost, construction costs, road traffic flow, power grid conditions and the surrounding environment. Numerical studies show that both grey incidence decision and grey target theory have the advantages of ease of operation, low requirement of data collection and processing when they are employed while selecting the optimal location.