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Estimating the optimal number and locations of electric vehicle charging stations: the application of multi-criteria p-median methodology

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  • Aleksandar Janjić
  • Lazar Velimirović
  • Jelena Velimirović
  • Petar Vranić

Abstract

Recent developments related to the widespread utilization of electric vehicles (EV) have required the building of sound and reliable public charging networks. In the literature, this task has usually been approached by optimizing the spatial distribution of a predefined number of stations, based on a number of selection criteria. Our study provides a new multi-criteria approach to the optimization of both charging station numbers and locations. The optimization procedure is based on the fulfilment of the following criteria: EV installation costs, walking distances to the charging station locations, location safety, access to parking, and power distribution network capacity. The novel methodology used for the analysis is the p-median based modified with an iterative approach and distances weighted with the Analytic Hierarchy Process (AHP) approach. The optimal number and site selection methodology of charging stations are verified based on a case study of the city of Niš (Serbia).

Suggested Citation

  • Aleksandar Janjić & Lazar Velimirović & Jelena Velimirović & Petar Vranić, 2021. "Estimating the optimal number and locations of electric vehicle charging stations: the application of multi-criteria p-median methodology," Transportation Planning and Technology, Taylor & Francis Journals, vol. 44(8), pages 827-842, November.
    • Handle: RePEc:taf:transp:v:44:y:2021:i:8:p:827-842
    DOI: 10.1080/03081060.2021.1992177
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    Cited by:

    1. Yang, Xiong & Peng, Zhenhan & Wang, Pinxi & Zhuge, Chengxiang, 2023. "Seasonal variance in electric vehicle charging demand and its impacts on infrastructure deployment: A big data approach," Energy, Elsevier, vol. 280(C).

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