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Research on multi‐train energy saving optimization based on cooperative multi‐objective particle swarm optimization algorithm
Author(s) -
Zhang Yong,
Zuo Tingting,
Zhu Muhan,
Huang Cheng,
Li Jun,
Xu Zhiliang
Publication year - 2021
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.5958
Subject(s) - train , particle swarm optimization , energy consumption , energy (signal processing) , computer science , mathematical optimization , line (geometry) , interval (graph theory) , engineering , simulation , algorithm , mathematics , geometry , cartography , combinatorics , electrical engineering , geography , statistics
Summary An energy saving optimization method of multi‐train collaboration is studied. According to the different scenarios of two and three trains, the corresponding overlapping time calculation model was established respectively. Minimizing the total energy consumption, a multi‐train collaborative energy consumption optimization model is established. The cooperative multi‐objective PSO algorithm was used to solve the model from the aspects of optimizing stop time and departure interval as well as the train speed curve. Finally, the energy optimization of the whole line of multi‐train during the morning rush hour were carried out by the actual data of Guangzhou metro line 7. The results show that the optimization model can greatly improve the utilization efficiency of regenerative energy and save energy consumption of the whole line by 11.74%.