The stationary supercapacitor energy storage systems (SCESS) in urban rail transit systems can effectively recover the regenerative braking energy of the trains and reduce the fluctuation of the traction network voltage. Generally, the charge/discharge states of SCESS is determined by the voltage of the traction network; however, in actual operation, the fluctuation of the no-load voltage of the substation may result in unexpected working states of SCESS, such as barely charge/discharge. Therefore, a dynamic threshold adjustment strategy based on no-load voltage identification is proposed in this paper: the output characteristic equation of substation is fitted in real-time with the recorded substation currents and voltages, and the present value of no-load voltage is predicted by the neural network, based on which the charge and discharge thresholds of the SCESS are adjusted dynamically. Through the proposed identification method, the variation trend of the no-load voltage of Liyuan Substation in Beijing Metro Batong Line in the whole day is analyzed. Besides, simulation results show that with the proposed dynamic threshold adjustment strategy, the SCESS is charged and discharged more effectively, and the energy saving effect is significantly improved.


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    Titel :

    Dynamic Threshold Adjustment Strategy of Supercapacitor Energy Storage System based on No-load Voltage Identification in Urban Rail Transit


    Beteiligte:
    Zhu, Feiqin (Autor:in) / Yang, Zhongping (Autor:in) / Lin, Fei (Autor:in) / Xin, Yue (Autor:in)


    Erscheinungsdatum :

    01.05.2019


    Format / Umfang :

    370713 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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