An energy-efficient scheduling and speed control approach for metro rail operations

被引:246
作者
Li, Xiang [1 ]
Lo, Hong K. [2 ]
机构
[1] Beijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
[2] Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Metro rail system; Energy-efficient operation; Timetable; Speed profile; Net energy consumption; TRAIN; DESIGN; OPTIMIZATION;
D O I
10.1016/j.trb.2014.03.006
中图分类号
F [经济];
学科分类号
02 ;
摘要
Due to increasing environmental concerns and energy prices, what is very important but has not been given due consideration is the energy efficiency of metro rail systems. Train energy-efficient operation consists of timetable optimization and speed control. The former synchronizes the accelerating and braking actions of trains to maximize the utilization of regenerative energy, and the latter controls the train driving strategy to minimize the tractive energy consumption under the timetable constraints. To achieve a better performance on the net energy consumption, i.e., the difference between the tractive energy consumption and the utilization of regenerative energy, this paper formulates an integrated energy-efficient operation model to jointly optimize the timetable and speed profile. We design a genetic algorithm to solve the model and present some numerical experiments based on the actual operation data of Beijing Metro Yizhuang Line of China. It is shown that a larger headway leads to smaller energy saving rate, and the maximum energy saving rate achieved is around 25% when we use the minimum allowable headway of 90 s. In addition, compared with the two-step approach optimizing the timetable and speed profile separately, the integrated approach can reduce the net energy consumption around 20%. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:73 / 89
页数:17
相关论文
共 33 条
[1]   Energy-efficient train control: From local convexity to global optimization and uniqueness [J].
Albrecht, Amie R. ;
Howlett, Phil G. ;
Pudney, Peter J. ;
Vu, Xuan .
AUTOMATICA, 2013, 49 (10) :3072-3078
[2]   SOLUTION OF THE PROBLEM OF THE ENERGETICALLY OPTIMAL-CONTROL OF THE MOTION OF A TRAIN BY THE MAXIMUM PRINCIPLE [J].
ASNIS, IA ;
DMITRUK, AV ;
OSMOLOVSKII, NP .
USSR COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS, 1985, 25 (06) :37-44
[3]   Transit-network design methodology for actual-size road networks [J].
Bagloee, Saeed Asadi ;
Ceder, Avishai .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2011, 45 (10) :1787-1804
[4]  
Benjamin B., 1989, 4 INT HEAVY HAUL RAI, P369
[5]  
Bocharnikov Y.V., 2010, IET Conf. Railw. Tract. Syst, P32, DOI [10.1049/ic.2010.0038, DOI 10.1049/IC.2010.0038]
[6]   Optimising train movements through coast control using genetic algorithms [J].
Chang, CS ;
Sim, SS .
IEE PROCEEDINGS-ELECTRIC POWER APPLICATIONS, 1997, 144 (01) :65-73
[7]   Optimizing the demand captured by a railway system with a regular timetable [J].
Cordone, Roberto ;
Redaelli, Francesco .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2011, 45 (02) :430-446
[8]  
[丁勇 Ding Yong], 2011, [交通运输系统工程与信息, Journal of Transporation Systems Engineering & Information Technology], V11, P96
[9]   Energy Savings in Metropolitan Railway Substations Through Regenerative Energy Recovery and Optimal Design of ATO Speed Profiles [J].
Dominguez, Maria ;
Fernandez-Cardador, Antonio ;
Cucala, Asuncion P. ;
Pecharroman, Ramon R. .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2012, 9 (03) :496-504
[10]  
Fournier D., 2012, 18 INT C PRINC PRACT, P7