Highlights Large-scale charging station planning for electric buses. Optimize the planning jointly under the transportation system and power grid. A spatial-temporal model decides the sites of facilities for multiple stages. Equivalently transform the model into a mixed-integer second-order cone programming. Implement a case study of the real-world transportation network in Shenzhen, China.

    Abstract With the applications of electric buses (e-buses), potential solutions to problems related to infrastructures for charging e-buses are emerging. This study particularly focused on large-scale fast charging-station planning for e-buses in the public transportation electrification process, according to the characteristics of e-bus operation and plug-in fast charging mode. We conducted an interdisciplinary study to optimize planning jointly under the transportation system and power grid. In addition to capturing the spatiality of the e-bus charging service network, we further considered temporality in order to conduct long-term planning in view of the continuously growing e-bus charging demand. A spatial-temporal model, which determines the sites and sizes of e-bus charging stations, was proposed and the strategies for multistage infrastructure planning were put forward. The model was equivalently transformed into a mixed-integer second-order cone programming with high computational efficiency. The model and the multistage planning strategies were justified through a series of numerical experiments. A case study of Shenzhen, China was implemented and the robustness of the model to plan changes was studied.


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    Title :

    Multistage large-scale charging station planning for electric buses considering transportation network and power grid


    Contributors:
    Lin, Yuping (author) / Zhang, Kai (author) / Shen, Zuo-Jun Max (author) / Ye, Bin (author) / Miao, Lixin (author)


    Publication date :

    2019-08-10


    Size :

    21 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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