Urban rail system is one of the most energy-consuming and highest costing public sectors in cities, and its energy efficiency has great potential to improve on the system level. The aim of this study is to introduce a novel method for identifying key energy-consuming parts based on univariate uncertain data pattern miner (U2P-miner) in order to improve the energy efficiency of urban rail system and to apply it in a real urban rail system. Firstly, an energy consumption association network model is constructed based on the operation energy consumption by analyzing the association among the energy use during operation. Secondly, a method for identifying critical nodes using U2P-miner algorithm is presented, which consider both topological and energy-consuming attributes of nodes. Finally, the proposed method is applied in Beijing Subway to help operator make better choices in energy efficiency improvement.


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    Title :

    A U2P-Miner-Based Method to Identify Critical Energy-Consuming Parts of Urban Rail Operation System


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Jia, Limin (editor) / Qin, Yong (editor) / Liu, Baoming (editor) / Liu, Zhigang (editor) / Diao, Lijun (editor) / An, Min (editor) / Wu, Mingtao (author) / Wang, Yanhui (author) / Lin, Shuai (author) / Hao, Boyan (author)

    Conference:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2019 ; Qingdao, China October 25, 2019 - October 27, 2019



    Publication date :

    2020-04-08


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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