Electrical railways are vital users of the State Grid. Load modeling for electrified railways is the precondition for regional power grid planning and economic dispatch. This paper primarily analyzed the probability distribution characteristics of the field-measured traction loads in three typical traction substations (TSSs) of electrified railways, including the high-speed railway TSS, the hub-Tss, and the TSS for a long-ramp heavy haul railway (HHR). The probability density curves (PDCs) have the characteristics of skew, multiple peaks, and long tails. Moreover, it studied a probability modeling method for dynamic traction loads with a mixed skew normal density function (MSNDF). The parameters were identified using the least square method. Few case studies were conducted to verify the effectiveness of the modeling method. The results show that the proposed methods can effectively restore the distribution and characteristics of the dynamic traction loads in electrified railways.


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    Titel :

    Measurement-Based Probability Distribution Characteristics and Modeling Methods of Traction Loads in Electrified Railways


    Beteiligte:
    Wang, Ke (Autor:in) / Zhang, Caiyuan (Autor:in) / Ai, Lei (Autor:in) / Hu, Haitao (Autor:in)


    Erscheinungsdatum :

    01.04.2023


    Format / Umfang :

    958736 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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