Highlights Propose a multi-period two-stage stochastic linear programming model. A hybrid decomposition algorithm is developed to solve the mathematical model. Impact of power demand uncertainty and flow rate on system performance are examined. Several managerial insights are made based on our computational studies.

    Abstract This study proposes a novel formulation for designing and managing electric vehicle charging stations, considering both long-term planning decisions and short-term operational decisions over a pre-specified planning horizon and under stochastic power demand. To solve this challenging problem, we propose a hybrid algorithm that combines Sample Average Approximation with an enhanced Progressive Hedging Algorithm. A case study, based on the road network around Washington, D.C., is presented to visualize and validate the modeling results. Results indicate that the electric vehicle power demand are satisfied primarily via the grid and Vehicle-to-Grid when energy cost is low and solar power is unavailable.


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    Titel :

    Modeling electric vehicle charging station expansion with an integration of renewable energy and Vehicle-to-Grid sources


    Beteiligte:


    Erscheinungsdatum :

    2019-06-11


    Format / Umfang :

    29 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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