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Energy-Saving Optimization Study of Train Timetable Based on Regenerative Braking Technology

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Proceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2023 (EITRT 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1137))

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Abstract

In this paper, we consider the effect of instantaneous power on the amount of regenerative braking energy recovery and divide a series of short time intervals to refine the calculation of energy consumption. Based on this, an optimization model with the objective of minimizing energy consumption is constructed, which uses the first station departure interval, inter-station travel time and station dwell time to describe the train timetable, and a running line adjustment algorithm is designed to ensure the arrival and departure intervals are reasonable. By using the hybrid genetic algorithm embedded with harmonic search, the case of a virtual line with 20 stations and 200 trips is solved and the results show that the method proposed in this paper can effectively reduce energy consumption.

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Acknowledgement

This work was supported by the National Natural Science Foundation of China (61603140).

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Authors and Affiliations

  1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, 510641, China

    Zheng Ya**g, Ma Zihan & ** Wenzhou

Authors
  1. Zheng Ya**g
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  2. Ma Zihan
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  3. ** Wenzhou
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Corresponding author

Correspondence to Ma Zihan .

Editor information

Editors and Affiliations

  1. Bei**g Jiaotong University, Bei**g, China

    Yong Qin

  2. Bei**g Jiaotong University, Bei**g, China

    Limin Jia

  3. Bei**g University of Civil Engineering and Architecture, Bei**g, China

    Jianwei Yang

  4. Bei**g Jiaotong University, Bei**g, China

    Lijun Diao

  5. Bei**g University of Civil Engineering and Architecture, Bei**g, China

    Dechen Yao

  6. University of Salford, Salford, UK

    Min An

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Ya**g, Z., Zihan, M., Wenzhou, J. (2024). Energy-Saving Optimization Study of Train Timetable Based on Regenerative Braking Technology. In: Qin, Y., Jia, L., Yang, J., Diao, L., Yao, D., An, M. (eds) Proceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2023. EITRT 2023. Lecture Notes in Electrical Engineering, vol 1137. Springer, Singapore. https://doi.org/10.1007/978-981-99-9311-6_37

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  • DOI: https://doi.org/10.1007/978-981-99-9311-6_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9310-9

  • Online ISBN: 978-981-99-9311-6

  • eBook Packages: EngineeringEngineering (R0)

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