The upcoming paradigm shift of transportation electrification will crucially change the spatial-temporal power demand profile imposed on our power grid. This paper proposes aggregated macroscopic traffic models that can be scalable to metropolitan scale real-time applications. Moreover, the prime focus lies on first-principle-based models that can properly capture the spatial-temporal evolution of traffic jams. This paper develops unified modeling frameworks for coupled traffic and power infrastructure, that capture the major cross-interactions between vehicular traffic flow and the power grid. The proposed models can then be used for long-time development of the power grid to facilitate possible traffic scenarios, energy trading, and short-time control to implement power grid response actions to traffic incidents.


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    Titel :

    Spatial-Temporal EV Charging Demand Model Considering Generic Second-Order Traffic Flows


    Beteiligte:
    Ross, Megan (Autor:in) / Du, Liang (Autor:in) / Seibold, Benjamin (Autor:in)


    Erscheinungsdatum :

    21.06.2021


    Format / Umfang :

    2676555 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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