Energy-saving operation approaches for urban rail transit systems

Ziyou GAO, Lixing YANG

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Front. Eng ›› 2019, Vol. 6 ›› Issue (2) : 139-151. DOI: 10.1007/s42524-019-0030-7
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Energy-saving operation approaches for urban rail transit systems

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Abstract

With the accelerated urbanization in China, passenger demand has dramatically increased in large cities, and traffic congestion has become serious in recent years. Developing public urban rail transit systems is an indispensable approach to overcome these problems. However, the high energy consumption of daily operations is an emerging issue due to increased rail transit networks and passenger demands. Thus, reducing the energy consumption and operational cost by using advanced optimization methodologies is an urgent task for operation managers. This work systematically introduces energy-saving approaches for urban rail transit systems in three aspects, namely, train speed profile optimization, utilization of regenerative energy, and integrated optimization of train timetable and speed profile. Future research directions in this field are also proposed to meet increasing passenger demands and network-based urban rail transit systems.

Keywords

urban rail transit / energy saving / speed profile optimization / regenerative energy / train timetable

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Ziyou GAO, Lixing YANG. Energy-saving operation approaches for urban rail transit systems. Front. Eng, 2019, 6(2): 139‒151 https://doi.org/10.1007/s42524-019-0030-7

References

[1]
Allegre A L, Bouscayrol A, Delarue P, Barrade P, Chattot E, El-Fassi S (2010). Energy storage system with supercapacitor for an innovative subway. IEEE Transactions on Industrial Electronics, 57(12): 4001–4012
CrossRef Google scholar
[2]
Chang C S, Sim S S (1997). Optimizing train movements through coast control using genetic algorithms. IEE Proceedings-Electric Power Applications, 144(1): 65–73
CrossRef Google scholar
[3]
Gu Q, Tang T, Cao F, Song Y D (2014). Energy-efficient train operation in urban rail transit using real-time traffic information. IEEE Transactions on Intelligent Transportation Systems, 15(3): 1216–1233
CrossRef Google scholar
[4]
Howlett P G, Milroy I P, Pudney P J (1994). Energy-efficient train control. Control Engineering Practice, 2(2): 193–200
CrossRef Google scholar
[5]
Huang Y R, Yang L X, Tang T, Gao Z Y, Cao F, Li K P (2018). Train speed profile optimization with on-board energy storage devices: A dynamic programming based approach. Computers & Industrial Engineering, 126: 149–164
CrossRef Google scholar
[6]
Ichikawa K (1968). Application of optimization theory for bounded state variable problems to the operation of train. Bulletin of the JSME, 11(47): 857–865
CrossRef Google scholar
[7]
Ke B R, Chen M C, Lin C L (2009). Block-layout design using MAX–MIN ant system for saving energy on mass rapid transit systems. IEEE Transactions on Intelligent Transportation Systems, 10(2): 226–235
CrossRef Google scholar
[8]
Ke B R, Lin C L, Yang C C (2012). Optimization of train energy-efficient operation for mass rapid transit systems. IET Intelligent Transport Systems, 6(1): 58–66
CrossRef Google scholar
[9]
Li X, Lo H (2014). An energy-efficient scheduling and speed control approach for metro rail operations. Transportation Research Part B: Methodological, 64: 73–89
CrossRef Google scholar
[10]
Liu P, Yang L X, Gao Z Y, Huang Y R, Li S K, Gao Y (2018). Energy-efficient train timetable optimization in the subway system with energy storage devices. IEEE Transactions on Intelligent Transportation Systems, 19(12): 3947–3963
CrossRef Google scholar
[11]
Liu R, Golovitcher I M (2003). Energy-efficient operation of rail vehicles. Transportation Research Part A: Policy and Practice, 37(10): 917–932
CrossRef Google scholar
[12]
Ma C Y, Ding Y, Du P, Mao B H (2010). Study on coast control of train movement for saving energy based-on genetic algorithm. Railway Computer Application, 19(6): 4–8
[13]
Rao Z (2006). Train Traction Calculation. Beijing: China Railway Press
[14]
Wang Y (2016). Calculation of Train Operations in Urban Metro Systems. Beijing: Science Press
[15]
Yang L X, Li K P, Gao Z Y, Li X (2012). Optimizing trains movement on a railway network. Omega, 40(5): 619–633
CrossRef Google scholar
[16]
Yang X (2016). Research on train timetable optimization for energy-saving operations in urban rail transit. Dissertation for the Doctoral Degree. Beijing: Beijing Jiaotong University
[17]
Yang X, Li X, Gao Z Y, Wang H W, Tang T (2013). A cooperative scheduling model for timetable optimization in subway systems. IEEE Transactions on Intelligent Transportation Systems, 14(1): 438–447
CrossRef Google scholar
[18]
Yin J T, Yang L X, Tang T, Gao Z Y, Ran B (2017). Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches. Transportation Research Part B: Methodological, 97: 182–213
CrossRef Google scholar
[19]
Zhao L (2014). Research on metro timetable optimization model and algorithm based on regenerative braking. Dissertation for the Master Degree. Beijing: Beijing Jiaotong University
[20]
Zhao S (2014). Research and simulation of urban rail transit super capacitor energy storage system. Dissertation for the Master Degree. Changsha: Central South University of Forestry and Technology

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