作者
Hao Liu, Jing Xun, Juanjuan Cai, Yafei Liu, Xuguang Wen
发表日期
2022/10/8
研讨会论文
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)
页码范围
499-504
出版商
IEEE
简介
Urban rail transit (URT) develops rapidly in modern cities, and its energy efficiency attracts extensive attention. The utilization of regenerative braking energy (RBE) is an important method for energy-efficient operation of URT. In order to make full use of RBE, this paper proposed a method to maximize RBE by train group matching with swarm intelligence algorithm. First, four cases of overlapping time are defined for train group matching. A train group can be formed with energy matching between trains and the moments when energy matching occurs in train groups are found out based on the actual timetable. Then, a dual-objective optimization model is formulated to maximize RBE and reduce the deviation of departure times for all train groups. Specifically, the train dwell time is adjusted to increase the overlapping time of train traction and braking, by which the RBE can be improved. A Particle Swarm Optimization …
引用总数
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H Liu, J Xun, J Cai, Y Liu, X Wen - 2022 IEEE 25th International Conference on Intelligent …, 2022