The charging demand of electric vehicles is closely related to residents’ travel behavior, this paper proposes a charging demand prediction method based on the travel behavior of electric vehicle users. By studying the probability distribution of temporal and spatial characteristics in travel behavior, constructing a charging decision model for electric vehicle users, use Monte Carlo method to simulate the travel activities of each electric car in one day, get the charging demand of the whole city. Take Nanjing as an example to verify the model, this method can effectively predict the temporal and spatial distribution of charging demand, and can provide a basis for subsequent site selection of charging facilities.


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    Titel :

    Electric Vehicle Charging Demand Forecast Based on Residents’ Travel Data


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Wuhong (Herausgeber:in) / Wu, Jianping (Herausgeber:in) / Jiang, Xiaobei (Herausgeber:in) / Li, Ruimin (Herausgeber:in) / Zhang, Haodong (Herausgeber:in) / Jin, Zhule (Autor:in) / Xu, Yongneng (Autor:in) / Li, Zheng (Autor:in)

    Kongress:

    International Conference on Green Intelligent Transportation System and Safety ; 2021 November 19, 2021 - November 21, 2021



    Erscheinungsdatum :

    28.10.2022


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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