Research on multi‐train energy saving optimization based on cooperative multi‐objective particle swarm optimization algorithm

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...

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Bibliographic Details
Published in:International journal of energy research Vol. 45; no. 2; pp. 2644 - 2667
Main Authors: Zhang, Yong, Zuo, Tingting, Zhu, Muhan, Huang, Cheng, Li, Jun, Xu, Zhiliang
Format: Journal Article
Language:English
Published: Chichester, UK John Wiley & Sons, Inc 01.02.2021
Subjects:
Algorithms
Collaboration
cooperative multi‐objective PSO
cooperative multi‐train
Energy
Energy conservation
Energy consumption
multi‐objective PSO
Optimization
Particle swarm optimization
rail transport
train energy‐saving
ISSN:0363-907X, 1099-114X
Online Access:Get full text
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Summary: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%. The methods of regenerative braking energy utilization based on stop time, departure interval adjustment and speed curve adjustment are studied in this paper. Establish multrain‐train energy‐saving optimization model and carry out simulations based on the data of Guangzhou Metro Line 7. The simulation result shows that the optimized train greatly improves the utilization efficiency of regenerative braking energy and reduces the net traction energy consumption.
Bibliography:Funding information
National Key R&D Program of China, Grant/Award Number: 2016YFB1200402
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0363-907X
1099-114X
DOI:10.1002/er.5958