The popularity of electric vehicles has led to an increase in the use of electric vehicles for commuting to work, requiring company charging stations to predict electric vehicle charging loads to aid advance planning. This paper takes into account the method of predicting EV load influenced by the travel characteristics of various types of EVs in a company. A probabilistic model of travel characteristics based on different types of EVs is established and a Monte Carlo simulation method is used to propose a company EV charging load prediction model. Taking a city as an example, the load of electric vehicles of a company in that place is predicted to provide more reliable data support for the planning of electric vehicle charging stations of the company.


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    Titel :

    Electric vehicle charging station load forecasting for companies based on travel characteristics


    Beteiligte:
    Shakir Md Saat, Mohd (Herausgeber:in) / Bin Ibne Reaz, Mamun (Herausgeber:in) / Ma, Hengke (Autor:in) / Liu, Tianyu (Autor:in)

    Kongress:

    Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023) ; 2023 ; Kuala Lumpur, Malaysia


    Erschienen in:

    Proc. SPIE ; 12788 ; 127884W


    Erscheinungsdatum :

    25.09.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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