Integration of plug-in electric vehicles (PEVs) with distributed renewable power sources will reduce PEVs’ well-to-wheels greenhouse gas emissions, promote renewable power adoption, and defer power system investments. This paper proposes a multidisciplinary approach to jointly plan PEV charging stations and distributed photovoltaic (PV) power plants on a coupled transportation and power network. We formulate a two-stage stochastic programming model to determine the sites and sizes of: 1) PEV charging stations and 2) PV power plants. This proposed method incorporates comprehensive models of: 1) transportation networks with explicit PEV driving range constraints; 2) PEV charging stations with probabilistic quality of service constraints; 3) PV power generation with reactive power control; and 4) alternating current distribution power flow. The formulation results in a mixed-integer second-order cone program. We then design a generalized Benders decomposition algorithm to efficiently solve it. Numerical experiments show that investing in distributed PV power plants with PEV charging stations has multiple benefits, e.g., reducing social costs, promoting renewable power integration, and alleviating power congestion. The benefits become more prominent when utilizing PV generation with reactive power control, which can also help to enhance power supply quality.


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    Title :

    Joint PEV Charging Network and Distributed PV Generation Planning Based on Accelerated Generalized Benders Decomposition


    Contributors:
    Zhang, Hongcai (author) / Moura, Scott J. (author) / Hu, Zechun (author) / Qi, Wei (author) / Song, Yonghua (author)


    Publication date :

    2018-09-01


    Size :

    2212292 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English