With the move of electric vehicle (EV) initiatives in many countries, there is a growing demand for fast-charging stations for recharging EVs. In this paper, we consider the problem of siting these EV charging stations in a transportation network with demand uncertainty. The demand for service considered is the passing flows in the network, i.e., the drive-by customers. We started with formulating the problem as a deterministic flow capturing location-allocation problem and then extended it into a stochastic model. Our results show that the stochastic model more realistically capture the actual coverage of the demand. We also developed a backup flow capturing model for providing secondary or multiple facilities coverage to ensure stability in service coverage and reduce the “range anxiety.” Test cases with different flow composition and cost parameters are examined.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A stochastic flow capturing location and allocation model for siting electric vehicle charging stations


    Beteiligte:
    Jingzi Tan (Autor:in) / Wei-Hua Lin (Autor:in)


    Erscheinungsdatum :

    01.10.2014


    Format / Umfang :

    927052 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Optimal siting and sizing of electric vehicle charging stations

    Jia, Long / Hu, Zechun / Song, Yonghua et al. | IEEE | 2012


    Managing electric current allocation of electric vehicle charging stations

    BAXTER DAVID / HAGENMAIER JR CARL F / TORMEY MILTON T et al. | Europäisches Patentamt | 2015

    Freier Zugriff

    Optimal Sizing and Siting of Electric Vehicle Charging Stations in Distribution Networks With Robust Optimizing Model

    Barhagh, Sahar Seyyedeh / Mohammadi-Ivatloo, Behnam / Abapour, Mehdi et al. | IEEE | 2024