With the development of charging technologies, the auto industry has envisioned the ability to recharge plug-in electric vehicles (PEV) at speeds comparable to traditional gas refueling. These ultrafast charging stations (UFCSs) could exert disruptive influences on the power grid. This article proposes a graph-computing-based cascading failure evolution (G-CFE) analysis to predict potential cascading failures induced by UFCS on power transmission systems. Fundamentally different from the existing cascading analysis tools, which are based on dc power flow or require a long-computation time, the proposed method greatly improves accuracy by using ac power flow, while guaranteeing the analyzing speed with graph parallel computing techniques. In addition, G-CFE can accurately capture the stochastic PEV charging patterns with Monte-Carlo simulation. Finally, G-CFE can be easily scaled to various network configurations through a graph-based scheme. The proposed method is validated on a provincial transmission system in China.


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    Titel :

    Online Prediction for Transmission Cascading Outages Induced by Ultrafast PEV Charging


    Beteiligte:
    Mao, Daijiafan (Autor:in) / Yuan, Chen (Autor:in) / Gao, Ziran (Autor:in) / Wang, Jiankang (Autor:in) / Zhao, Ruili (Autor:in)


    Erscheinungsdatum :

    01.12.2019


    Format / Umfang :

    4008061 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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