Energy consumption optimization of train operation for railway systems: Algorithm development and real-world case study

被引:56
作者
Zhang, Huiru [1 ]
Jia, Limin [2 ,3 ]
Wang, Li [1 ,2 ]
Xu, Xinyue [2 ]
机构
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
[3] Beijing Engn Res Ctr Urban Traff Informat Intelli, Beijing 100044, Peoples R China
基金
中国国家自然科学基金;
关键词
Railway; Energy-efficient operation; Timetable; Particle swarm optimization; Bi-level optimization; EFFICIENT OPERATION; MINIMIZATION; TIME;
D O I
10.1016/j.jclepro.2019.01.023
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Traction energy is the main component of railway operation energy, and a timetable that predefines the running time of train operation can be used to determine the traction energy consumption. This study proposes a bi-level model that optimizes timetables to achieve the energy-saving control of railway systems. The upper level of the model ensures the relative stability of the timetable while maintaining railway safety constraints, which makes train operations more convenient for the railway sector as well as passengers; while the lower level of the model optimizes the arrival and departure time among intermediate stations to minimize the energy consumption of each train. Then, a unified iterative optimization algorithm combining particle swarm is developed to solve the model, and a timetable that ensures energy consumption optimizations is thus obtained. A case study using actual operation data from the Beijing-Shanghai high-speed railway is developed to illustrate the proposed method. Results show that the total energy consumption is reduced by more than 7.6%, and the average adjustment time for each distance interval is approximately 1 min, which maintains the stability of the original timetable. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1024 / 1037
页数:14
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