Simulation of energy-efficient operation for metro trains: A discrete event-driven method based on multi-agent theory

被引:2
作者
Yang, Xingxing [1 ]
Li, Yang [2 ]
Guo, Xin [2 ]
Ding, Meiling [2 ]
Yang, Jingxuan [2 ]
机构
[1] Suzhou Univ, Sch Math & Stat, Suzhou, Anhui, Peoples R China
[2] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol Co, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-agent theory; Discrete-event driven; Train operation simulation; Train energy-saving operation; Adaptive large neighborhood search  algorithm; TIMETABLE OPTIMIZATION; TRAFFIC FLOW; MODEL; STRATEGIES; TRACK;
D O I
10.1016/j.physa.2022.128325
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Along with the rapid development of urban rail transit systems, the increase in operating mileage is the direct result of the enormous energy consumption. Among them, the energy consumption of train traction operation is close to half of the total energy consumption, leading to a gradual increase in operation cost. Based on the discrete event-driven method of multi-agent simulation, this paper simulates the process of the train operation with four function modules. Ingenuity, trains with onboard equipment would store braking regenerative energy and then transmit regenerative energy to other traction trains in the same power supply section. Moreover, the evaluation method of renewable energy utilization efficiency also is proposed with different operation schemes to calculate train operation energy consumption. Further, an adaptive large neighborhood search algorithm is designed to improve computational efficiency for real-time applications. Lastly, the operation of the Beijing Metro Yizhuang line is utilized as a case study to evaluate the simulation model and algorithm. The results show that the simulation method can reasonably simulate the process of train operation according to the actual situation. By optimizing the train operation time and dwell time of different onboard power storage equipment scenarios, the traction energy consumption can be reduced by 3.95% and up to 17.71%, which has a remarkable effect on energy saving.(c) 2022 Published by Elsevier B.V.
引用
收藏
页数:23
相关论文
共 40 条
[1]   Energy-Efficient Control Method for Subway Train in Section with Long Heavy Down Grade [J].
Bai Y. ;
Zhou Y. ;
Qiu Y. ;
Jia W. ;
Mao B. .
Zhongguo Tiedao Kexue/China Railway Science, 2018, 39 (01) :108-115
[2]  
Cai J., 2011, HIGH SPEED RAILW TEC, V02, P4
[3]  
Chen Y., 2014, COMPUT APPL, V34, P1521
[4]  
China Urban Rail Transit Association, 2021, STAT ANAL REPORT URB
[5]  
Ding Y., 2011, TRANSP SYST ENG INFO, V11, P96
[6]  
Fournier David., 2012, The 18th International Conference on Principles and Practice of Constraint Programming, P7
[7]  
Hao J., 2020, RES ENERGY SAVING OP
[8]   Simulation-optimization framework for train rescheduling in rapid rail transit [J].
Hassannayebi, Erfan ;
Sajedinejad, Arman ;
Kardannia, Ali ;
Shakibayifar, Masoud ;
Jafari, Hossein ;
Mansouri, Ehsan .
TRANSPORTMETRICA B-TRANSPORT DYNAMICS, 2021, 9 (01) :343-375
[9]  
[侯忠生 Hou Zhongsheng], 2014, [北京交通大学学报. 自然科学版, Journal of Beijing Jiaotong University], V38, P29
[10]   Optimal driving strategies for a train on a track with continuously varying gradient [J].
Howlett, PG ;
Cheng, J .
JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY SERIES B-APPLIED MATHEMATICS, 1997, 38 :388-410