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An Energy Efficient Train Dispatch and Control Integrated Method in Urban Rail Transit

Author

Listed:
  • Bing Bu

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Guoying Qin

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Ling Li

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Guojie Li

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

Abstract

With the rapid development of urban rail transit, the energy consumption of trains is increasing dramatically. The shortage of electrical energy is becoming more and more serious. In this paper, a novel method is proposed to better use regenerative braking energy for energy saving. A ‘time slot and energy grid’ model is set up to analyze the utilization of regenerative energy among trains. Based on this model, an energy efficient strategy that integrates train dispatch with train control is designed. The running time of trains in sections, the dwell time of trains at stations and the headway can be adjusted to find the global optimal solution for energy saving. The operational data of Beijing Changping subway line and Beijing Yizhuang subway line are used in simulation to illustrate the effectiveness of the proposed method in different scenarios. Simulation results show that our approach can significantly improve the utilization of regenerative braking energy and minimize the energy consumption in different scenarios when compared with the existing method.

Suggested Citation

  • Bing Bu & Guoying Qin & Ling Li & Guojie Li, 2018. "An Energy Efficient Train Dispatch and Control Integrated Method in Urban Rail Transit," Energies, MDPI, vol. 11(5), pages 1-23, May.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1248-:d:146256
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    References listed on IDEAS

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    2. Phil Howlett, 2000. "The Optimal Control of a Train," Annals of Operations Research, Springer, vol. 98(1), pages 65-87, December.
    3. Liao, Gwo-Ching, 2011. "A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power," Energy, Elsevier, vol. 36(2), pages 1018-1029.
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    Cited by:

    1. Nena Apostolidou & Nick Papanikolaou, 2018. "Energy Saving Estimation of Athens Trolleybuses Considering Regenerative Braking and Improved Control Scheme," Resources, MDPI, vol. 7(3), pages 1-18, July.
    2. Franciszek Restel & Szymon Mateusz Haładyn, 2022. "The Railway Timetable Evaluation Method in Terms of Operational Robustness against Overloads of the Power Supply System," Energies, MDPI, vol. 15(17), pages 1-17, September.
    3. Artur Kierzkowski & Szymon Haładyn, 2022. "Method for Reconfiguring Train Schedules Taking into Account the Global Reduction of Railway Energy Consumption," Energies, MDPI, vol. 15(5), pages 1-18, March.
    4. Zhou, Wenliang & Huang, Yu & Deng, Lianbo & Qin, Jin, 2023. "Collaborative optimization of energy-efficient train schedule and train circulation plan for urban rail," Energy, Elsevier, vol. 263(PA).

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