This paper presents concisely one of the main topics of a research project, concerning the sustainable linking between smart traffic systems and smart grids by an efficient energy management – deployed in Germany. Therefore, an evolutionary neural etwork modification algorithm is developed to predict the power demand of Battery Overhead Line Buses (BOB), which were regarded as moving energy storages. This knowledge allows a flexible usage of these battery capacities e.g. to harmonize the general catenary grid load.


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    Titel :

    Predicting Power Demand in Urban Transportation Systems using an Evolutionary Neural Network


    Beteiligte:
    Weisbach, Michele (Autor:in) / Herklotz, Kay (Autor:in) / Fechtner, Heiko (Autor:in) / Spaeth, Utz (Autor:in) / Gipp, Bela (Autor:in) / Schmuelling, Benedikt (Autor:in)


    Erscheinungsdatum :

    15.06.2022


    Format / Umfang :

    3124246 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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