Driving a gasoline-powered vehicle is a major polluting factor that degrades the environment. In order to reduce our dependency on gasoline and its related environmental effects, the plug-in electric vehicles (PEVs) are being recommended as an alternative to the conventional gasoline vehicles. As the PEVs start to enter the consumer market, a clear emphasis should be placed on the supporting infrastructure such as the charging stations in order to reduce the range anxiety and the time required to charge the battery. This infrastructure is critical for market acceptance and future growth of PEVs. Using a graphic weighting method this paper estimates the number of charging station needed at different locations, varied by the charging characteristics commonly referred to as level of charging. The objective is to maximize service to the charging demand while meeting the budget constraint. By means of integrated GIS modeling and mathematical optimization on a GIS platform, the promising initial results of the study indicate that the proposed model is able to make reasonable selections based on the given criteria in a given socioeconomic environment.


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    Titel :

    Optimum Location Identification of Plug-In Electric Vehicle Charging Stations Based on Graphic Weighting


    Beteiligte:
    Yi, Ping (Autor:in) / Kandukuri, Yudhveer (Autor:in)

    Kongress:

    The Twelfth COTA International Conference of Transportation Professionals ; 2012 ; Beijing, China


    Erschienen in:

    CICTP 2012 ; 3435-3440


    Erscheinungsdatum :

    23.07.2012




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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