An Energy Saving Optimization Strategy for Metro Power Supply Considering Randomness of Stop Delay

被引：0

作者：

Yang, Shaobing ^{[1
]}

Zhang, Zheng ^{[1
]}

Ye, Jingjing ^{[1
]}

Wu, Mingli ^{[1
]}

Zhou, Jinghua ^{[2
]}

机构：

[1] Beijing Jiaotong University, Beijing,100044, China

[2] North China University of Technology, Beijing,100144, China

来源：

Journal of Railway Engineering Society | 2021年 / 38卷 / 07期

关键词：

Energy conversion - Regenerative braking - Scheduling - Energy utilization - Light rail transit - Energy conservation;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Research purposes: By adjusting the train timetable of metro reasonably, the utilization rate of regenerative braking energy can be improved, which is of great significance to the energy saving and consumption reduction of the metro. This paper studies the statistical characteristics of stop delay time, builds a mathematical model to describe the random characteristics of stop delay time based on the measured data, and introduces it into the simulation analysis of traction power supply network. Therefore the optimization strategy of energy saving timetable based on the random simulation is realized. Research conclusions:(1) Stop time is a key parameter of train timetable and plays a decisive role in operation optimization. The difference between the actual and scheduled value will significantly affect the energy saving effect. In this paper, a practical probabilistic model is proposed to describe the stop time, which can accurately reflect the deviation of operation time and improve the effectiveness of train timetable optimization. (2) The traditional energy saving objective function is usually based on the total energy consumption of substation, so it is difficult to evaluate the effect of regenerative braking energy absorbed by adjacent trains. In this paper, the energy conversion rate is designed and applied to the optimization of energy saving strategy, which has advantages in optimal degree and operability. (3) A dynamic description method of train timetable based on the probabilistic model of stop time is proposed. The optimization scheme and detailed steps of energy saving strategy are designed by means of genetic algorithm. The effectiveness of the proposed optimization strategy is verified by the simulation calculation and actual measurement analysis on actual metro line. (4) This paper provides ideas and methods for the optimization of energy saving operation for metro trains, and has a good application prospect in energy consumption management and operation diagram optimization of metro. © 2021, Editorial Department of Journal of Railway Engineering Society. All right reserved.

引用

页码：94 / 99