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.


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    Title :

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


    Contributors:
    Jingzi Tan (author) / Wei-Hua Lin (author)


    Publication date :

    2014-10-01


    Size :

    927052 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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