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.
A U2P-Miner-Based Method to Identify Critical Energy-Consuming Parts of Urban Rail Operation System
Lect. Notes Electrical Eng.
International Conference on Electrical and Information Technologies for Rail Transportation ; 2019 ; Qingdao, China October 25, 2019 - October 27, 2019
Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019 ; Chapter : 24 ; 245-255
2020-04-08
11 pages
Article/Chapter (Book)
Electronic Resource
English
Urban rail operation system , Energy efficiency , Network model , Critical part identification , Univariate uncertain data pattern miner Engineering , Transportation Technology and Traffic Engineering , Computational Intelligence , Control and Systems Theory , Information Systems Applications (incl. Internet)
A U2P-Miner-Based Method to Identify Critical Energy-Consuming Parts of Urban Rail Operation System
British Library Conference Proceedings | 2020
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