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A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system
Liu, Hongjie1,2,3; Tang, Tao1,2; Guo XW(郭希旺)3,4,5; Xia, Xisheng6
Department工业控制网络与系统研究室
Source PublicationADVANCES IN MECHANICAL ENGINEERING
ISSN1687-8140
2018
Volume10Issue:9Pages:1-13
Indexed BySCI
WOS IDWOS:000445224400001
Contribution Rank4
Funding OrganizationNational 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
KeywordRegenerative energy utilization timetable optimization headway time dwell time artificial bee colony
AbstractMaximizing 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.
Language英语
WOS SubjectThermodynamics ; Engineering, Mechanical
WOS KeywordBRAKING ENERGY ; PERFORMANCE ; STRATEGIES ; MANAGEMENT ; FLOW
WOS Research AreaThermodynamics ; Engineering
Funding ProjectNational 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
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Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/22819
Collection工业控制网络与系统研究室
Affiliation1.State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
2.School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China
3.Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA
4.Key Laboratory of Network Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Liaoning, China
5.Computer and Communication Engineering College, Liaoning Shihua University, Fushun, China
6.Research and Development Center, Traffic Control Technology Co., Ltd., Beijing, China
Recommended Citation
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.
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