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This paper studies siting and sizing of plug-in electric vehicle (PEV) fast-charging stations on coupled transportation and power networks. We develop a closed-form model for PEV fast-charging stations' service abilities, which considers heterogeneous PEV driving ranges and charging demands. We utilize a modified capacitated flow refueling location model based on subpaths (CFRLM_SP) to explicitly capture time-varying PEV charging demands on the transportation network under driving range constraints. We explore extra constraints of the CFRLM_SP to enhance model accuracy and computational efficiency. We then propose a stochastic mixed-integer second-order cone programming model for PEV fast-charging station planning. The model considers the transportation network constraints of CFRLM_SP and the power network constraints with ac power flow. Numerical experiments are conducted to illustrate the effectiveness of the proposed method.
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Zhang et al. (2017) studied this question.
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