4.7 Article

An energy-efficient scheduling approach to improve the utilization of regenerative energy for metro systems

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2015.05.002

关键词

Metro systems; Scheduling approach; Regenerative braking; Energy consumption

资金

  1. Fundamental Research Funds for the Central Universities [2014YJS022]
  2. National Natural Science Foundation of China [71371027]
  3. State Key Laboratory of Rail Traffic Control and Safety [RCS2014ZT29]
  4. Beijing Laboratory of Urban Rail Transit
  5. Beijing Key Laboratory of Urban Rail Transit Automation and Control
  6. Beijing Mass Transit Railway Operation Corporation Limited
  7. Utah Transportation Center at Utah State University
  8. China Scholarship Council

向作者/读者索取更多资源

Regenerative braking is an energy recovery mechanism that converts the kinetic energy during braking into electricity, also known as regenerative energy. In general, most of the regenerative energy is transmitted backward along the pantograph and fed back into the overhead contact line. To reduce the trains' energy consumption, this paper develops a scheduling approach to coordinate the arrivals and departures of all trains located in the same electricity supply interval so that the energy regenerated from braking trains can be more effectively utilized to accelerate trains. Firstly, we formulate an integer programming model with real-world speed profiles to minimize the trains' energy consumption with dwell time control. Secondly, we design a genetic algorithm and an allocation algorithm to find a good solution. Finally, we present numerical examples based on the real-life operation data from the Beijing Metro Yizhuang Line in Beijing, China. The results show that the proposed scheduling approach can reduce energy consumption by 6.97% and save about 1,054,388 CNY (or 169,223 USD) each year in comparison with the current timetable. Compared to the cooperative scheduling (CS) approach, the proposed scheduling approach can improve the utilization of regenerative energy by 36.16% and reduce the total energy consumption by 4.28%. (C) 2015 Elsevier Ltd. All rights reserved.

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