At present, with the rapid development of urban rail transit, the energy consumption of the urban rail transit system has become a hot spot for many scholars. In order to effectively reduce the traction energy consumption of the urban rail transit system and improve the utilization of regenerative braking energy, this paper proposes a collaborative optimization strategy for multi-train operation curve. Firstly, this paper builds the simulation model of multi-train operation for urban rail power supply, it uses the improved Rosenbrock algorithm to calculate and solve, and analyzes the energy flow and utilization of the system energy. On this basis, it establishes the optimization model, proposes a collaborative optimization strategy for multi-train operation curve under the different operational scenarios by using the particle swarm optimization for the optimization solution. Finally, based on the actual line and train data of Beijing Metro Batong Line, the effectiveness verification of the optimization strategy under multiple scenarios is realized.


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    Titel :

    Collaborative Optimization Design of Multi-train Operation Curve Based on Utilization of Regenerative Braking Energy in Urban Rail Transit


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liang, Jianying (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Qin, Yong (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Song, Meiyu (Autor:in) / Wu, Xiaobo (Autor:in) / Jin, Taimu (Autor:in) / Liu, Yuyan (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Erscheinungsdatum :

    2022-02-19


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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