中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system

文献类型:期刊论文

作者Liu, Hongjie2,3,4; Tang, Tao2,3; Guo XW(郭希旺)1,4,6; Xia, Xisheng5
刊名ADVANCES IN MECHANICAL ENGINEERING
出版日期2018
卷号10期号:9页码:1-13
关键词Regenerative energy utilization timetable optimization headway time dwell time artificial bee colony
ISSN号1687-8140
产权排序4
英文摘要

Maximizing regenerative energy utilization in subway systems has become a hot research topic in recent years. By coordinating traction and braking trains in a substation, regenerative energy is optimally utilized and thus energy consumption from the substation can be reduced. This article proposes a timetable optimization problem to maximize regenerative energy utilization in a subway system with headway and dwell time control. We formulate its mathematical model, and some required constraints are considered in the model. To keep the operation time duration constant, the headway time between different trains can be different. An improved artificial bee colony algorithm is designed to solve the problem. Its main procedure and some related tasks are presented. Numerical experiments based on the data from a subway line in China are conducted, and improved artificial bee colony is compared with a genetic algorithm. Experimental results prove the correctness of the mathematical model and the effectiveness of improved artificial bee colony, which improves regenerative energy utilization for the experimental line and performs better than genetic algorithm.

WOS关键词BRAKING ENERGY ; PERFORMANCE ; STRATEGIES ; MANAGEMENT ; FLOW
资助项目National Key Research and Development Program of China[2018YFB1201501] ; Beijing municipal natural science foundation[L161008] ; Fundamental Research Funds for the Central Universities[2016JBZ004] ; TCT Funding Program[9907006510] ; Chinese Railway Certification Center funding program[1852ZJ1303] ; Beijing Laboratory of Urban Rail Transit ; China Scholarship Council
WOS研究方向Thermodynamics ; Engineering
语种英语
WOS记录号WOS:000445224400001
资助机构National Key Research and Development Program of China ; Beijing municipal natural science foundation ; Fundamental Research Funds for the Central Universities ; TCT Funding Program ; Chinese Railway Certification Center funding program ; Beijing Laboratory of Urban Rail Transit ; China Scholarship Council
源URL[http://ir.sia.cn/handle/173321/22819]  
专题沈阳自动化研究所_数字工厂研究室
通讯作者Liu, Hongjie; Guo XW(郭希旺)
作者单位1.Computer and Communication Engineering College, Liaoning Shihua University, Fushun, China
2.School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China
3.State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
4.Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA
5.Research and Development Center, Traffic Control Technology Co., Ltd., Beijing, China
6.Key Laboratory of Network Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Liaoning, China
推荐引用方式
GB/T 7714
Liu, Hongjie,Tang, Tao,Guo XW,et al. A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system[J]. ADVANCES IN MECHANICAL ENGINEERING,2018,10(9):1-13.
APA Liu, Hongjie,Tang, Tao,Guo XW,&Xia, Xisheng.(2018).A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system.ADVANCES IN MECHANICAL ENGINEERING,10(9),1-13.
MLA Liu, Hongjie,et al."A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system".ADVANCES IN MECHANICAL ENGINEERING 10.9(2018):1-13.

入库方式: OAI收割

来源:沈阳自动化研究所

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