Skip to main content

Timetabling with Regenerative Energy Maximization

  • Chapter
  • First Online:
Subway Energy-Efficient Management

Part of the book series: Uncertainty and Operations Research ((UOR))

  • 129 Accesses

Abstract

As mentioned in Chap. 1, regenerative braking is an energy recovery mechanism used in subway systems to recover the traction energy during braking into electricity. In order to maximize the regenerative energy utilization, Yang et al. [1] presented a timetable optimization 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. Based on the literature [1], this chapter aims to enhance the regenerative energy utilization by making minor adjustments of the dwell times to the current timetable while using the real-world speed profiles and keeping the cycle time and the number of trains unchanged. We mainly focus on the following three questions: (1) How to measure the regenerative energy using kinetic equations? (2) How to coordinate all trains located in the same electricity supply interval? (3) How to formulate the timetabling model with regenerative energy maximization?

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Yang X, Chen A, Li X, Ning B, Tang T (2015), An energy-efficient scheduling approach to improve the utilization of regenerative energy for metro systems, Transportation Research Part C: Emerging Technologies, 57: 13–29.

    Article  Google Scholar 

  2. Howlett PG, Pudney PJ (1995), Energy-efficient train control, Adv. Ind. Control. New York, NY, USA: Springer-Verlag.

    Google Scholar 

  3. Howlett PG (1996), Optimal strategies for the control of a train, Automatica, 32(4): 519–532.

    Article  Google Scholar 

  4. Yang X, Li X, Gao ZY, Wang H, Tang T (2013), A cooperative scheduling model for timetable optimization in subway systems, IEEE Transactions on Intelligent Transportation Systems, 14(1): 438–447.

    Article  Google Scholar 

  5. Narendra PM, Fukunaga K (1977), A branch and bound algorithm for feature subset selection, IEEE Transactions on computers, 9: 917–922.

    Article  Google Scholar 

  6. Roger A (1981), Newton-Kantorovitch algorithm applied to an electromagnetic inverse problem, IEEE Transactions on Antennas and Propagation, 29(2): 232–238.

    Article  Google Scholar 

  7. Yang X, Chen A, Gao ZY, Tang T (2019), An energy-efficient rescheduling approach under delay perturbations for subway systems, Transportmetrica B: Transport Dynamics, 7(1): 386–400.

    Google Scholar 

  8. Zhang L (2014), The operation data for the Beijing Metro Yizhuang Line, Technical Report, Beijing Mass Transit Railway Operation Corporation Limited (in Chinese).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiang Li .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Li, X., Yang, X. (2020). Timetabling with Regenerative Energy Maximization. In: Subway Energy-Efficient Management. Uncertainty and Operations Research. Springer, Singapore. https://doi.org/10.1007/978-981-15-7785-7_4

Download citation

Publish with us

Policies and ethics