IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1946-d765966.html
   My bibliography  Save this article

Method for Reconfiguring Train Schedules Taking into Account the Global Reduction of Railway Energy Consumption

Author

Listed:
  • Artur Kierzkowski

    (Department of Technical Systems Operation and Maintenance, Faculty of Mechanical Engineering, Wrocław University of Science and Technology, 50-370 Wrocław, Poland)

  • Szymon Haładyn

    (Department of Technical Systems Operation and Maintenance, Faculty of Mechanical Engineering, Wrocław University of Science and Technology, 50-370 Wrocław, Poland)

Abstract

The paper aims to propose a method of reconfiguring the train timetable, taking into account minimising the globally consumed energy for traction purposes. This is a very important issue in the context of rising electricity prices, alarming climate changes and the “Fit for 55” policy introduced in Europe. Each unit of energy saved contributes to improving the state of the planet and reducing the negative human impact on it. In this paper, the authors propose a model that, when applied, will reconfigure the timetable in terms of energy intensity and, as a result, reduce the impact of railways on the burden on the environment. It is proposed to introduce an interdependence between trajectories of electrical train movement. This interdependence is to take place so that it is possible to efficiently transfer the energy recovered during the braking of one train to another train, moving on the same section of the railway line and at the same time (i.e., without using energy storage devices). The paper provides a physical background to the considerations—discussing the movement of electric trains in the context of their energy intensity and the possibility of energy recovery; presenting the possibility of interconnecting trains in such a way that the energy from a train that is being braked can be efficiently used by a train that is being accelerated; presenting a method for making the linkages between trains (in the form of an original algorithm resulting from the application of the Delphi method) and implementing them in the timetable. The timetable for the application of the method is real and was obtained from the railway operator in Poland, as a mathematical–physical model describing the trajectory and energy consumption of the original, after which the proposed timetable was verified by running simulations and comparing the energy consumption of the original and the proposed timetable. It turned out that it is possible to achieve a global total energy demand reduction of up to 398 MWh/year. This proves the validity of using the proposed algorithm at the timetabling stage and extending its implementation to the entire network. Furthermore the authors also recognise the tendency of the algorithm to return repeatable solutions, which has the side effect of creating a cyclic timetable. Its implementation in Poland has proved impossible for many years. The application of the proposed method could change this unfavourable situation.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1946-:d:765966
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1946/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/5/1946/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Pengling & Goverde, Rob M.P., 2017. "Multi-train trajectory optimization for energy efficiency and delay recovery on single-track railway lines," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 340-361.
    2. Pablo Arboleya & Islam El-Sayed & Bassam Mohamed & Clement Mayet, 2019. "Modeling, Simulationand Analysis of On-Board Hybrid Energy Storage Systems for Railway Applications," Energies, MDPI, vol. 12(11), pages 1-21, June.
    3. Giuliano Cipolletta & Antonio Delle Femine & Daniele Gallo & Mario Luiso & Carmine Landi, 2021. "Design of a Stationary Energy Recovery System in Rail Transport," Energies, MDPI, vol. 14(9), pages 1-16, April.
    4. Cheng Gong & Shiwen Zhang & Feng Zhang & Jianguo Jiang & Xinheng Wang, 2014. "An Integrated Energy-Efficient Operation Methodology for Metro Systems Based on a Real Case of Shanghai Metro Line One," Energies, MDPI, vol. 7(11), pages 1-25, November.
    5. Mihaela Popescu & Alexandru Bitoleanu, 2019. "A Review of the Energy Efficiency Improvement in DC Railway Systems," Energies, MDPI, vol. 12(6), pages 1-25, March.
    6. Donato Morea & Stefano Elia & Chiara Boccaletti & Pasquale Buonadonna, 2021. "Improvement of Energy Savings in Electric Railways Using Coasting Technique," Energies, MDPI, vol. 14(23), pages 1-15, December.
    7. Xuan Lin & Qingyuan Wang & Pengling Wang & Pengfei Sun & Xiaoyun Feng, 2017. "The Energy-Efficient Operation Problem of a Freight Train Considering Long-Distance Steep Downhill Sections," Energies, MDPI, vol. 10(6), pages 1-26, June.
    8. Longda Wang & Xingcheng Wang & Kaiwei Liu & Zhao Sheng, 2019. "Multi-Objective Hybrid Optimization Algorithm Using a Comprehensive Learning Strategy for Automatic Train Operation," Energies, MDPI, vol. 12(10), pages 1-33, May.
    9. Qiwei Lu & Bangbang He & Mingzhe Wu & Zhichun Zhang & Jiantao Luo & Yankui Zhang & Runkai He & Kunyu Wang, 2018. "Establishment and Analysis of Energy Consumption Model of Heavy-Haul Train on Large Long Slope," Energies, MDPI, vol. 11(4), pages 1-20, April.
    10. Petru Valentin Radu & Adam Szelag & Marcin Steczek, 2019. "On-Board Energy Storage Devices with Supercapacitors for Metro Trains—Case Study Analysis of Application Effectiveness," Energies, MDPI, vol. 12(7), pages 1-22, April.
    11. 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.
    12. Adrián Fernández-Rodríguez & Antonio Fernández-Cardador & Asunción P. Cucala & Maria Carmen Falvo, 2019. "Energy Efficiency and Integration of Urban Electrical Transport Systems: EVs and Metro-Trains of Two Real European Lines," Energies, MDPI, vol. 12(3), pages 1-20, January.
    13. Agostinho Rocha & Armando Araújo & Adriano Carvalho & João Sepulveda, 2018. "A New Approach for Real Time Train Energy Efficiency Optimization," Energies, MDPI, vol. 11(10), pages 1-21, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mateusz Zając, 2022. "The Analysis of Selected Factors Improving the Cargo Susceptibility to Modal Shift," Energies, MDPI, vol. 15(23), pages 1-16, November.
    2. Artur Kierzkowski & Agnieszka A. Tubis, 2023. "Transportation Systems Modeling, Simulation and Analysis with Reference to Energy Supplying," Energies, MDPI, vol. 16(8), pages 1-6, April.
    3. Tomasz Smal & Joanna Wieprow, 2023. "Energy Security in the Context of Global Energy Crisis: Economic and Financial Conditions," Energies, MDPI, vol. 16(4), pages 1-12, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Szymon Haładyn, 2021. "The Problem of Train Scheduling in the Context of the Load on the Power Supply Infrastructure. A Case Study," Energies, MDPI, vol. 14(16), pages 1-19, August.
    3. Guang Yang & Feng Zhang & Cheng Gong & Shiwen Zhang, 2019. "Application of a Deep Deterministic Policy Gradient Algorithm for Energy-Aimed Timetable Rescheduling Problem," Energies, MDPI, vol. 12(18), pages 1-19, September.
    4. Mihaela Popescu, 2022. "Energy Efficiency in Electric Transportation Systems," Energies, MDPI, vol. 15(21), pages 1-5, November.
    5. Sahil Bhagat & Jacopo Bongiorno & Andrea Mariscotti, 2023. "Influence of Infrastructure and Operating Conditions on Energy Performance of DC Transit Systems," Energies, MDPI, vol. 16(10), pages 1-26, May.
    6. Piotr Gołębiowski & Marianna Jacyna & Andrzej Stańczak, 2021. "The Assessment of Energy Efficiency versus Planning of Rail Freight Traffic: A Case Study on the Example of Poland," Energies, MDPI, vol. 14(18), pages 1-18, September.
    7. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2018. "The two-train separation problem on non-level track—driving strategies that minimize total required tractive energy subject to prescribed section clearance times," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 135-167.
    8. Ivan Radaš & Ivan Župan & Viktor Šunde & Željko Ban, 2021. "Route Profile Dependent Tram Regenerative Braking Algorithm with Reduced Impact on the Supply Network," Energies, MDPI, vol. 14(9), pages 1-22, April.
    9. Mihaela Popescu & Alexandru Bitoleanu & Mihaita Linca & Constantin Vlad Suru, 2021. "Improving Power Quality by a Four-Wire Shunt Active Power Filter: A Case Study," Energies, MDPI, vol. 14(7), pages 1-20, April.
    10. Lukáš Dvořáček & Martin Horák & Jaroslav Knápek, 2022. "Simulation of Electric Vehicle Charging Points Based on Efficient Use of Chargers and Using Recuperated Braking Energy from Trains," Energies, MDPI, vol. 15(2), pages 1-28, January.
    11. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2016. "The key principles of optimal train control—Part 1: Formulation of the model, strategies of optimal type, evolutionary lines, location of optimal switching points," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 482-508.
    12. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    13. Aleksandra Kuzior & Marek Staszek, 2021. "Energy Management in the Railway Industry: A Case Study of Rail Freight Carrier in Poland," Energies, MDPI, vol. 14(21), pages 1-21, October.
    14. Ziyu Wu & Chunhai Gao & Tao Tang, 2021. "An Optimal Train Speed Profile Planning Method for Induction Motor Traction System," Energies, MDPI, vol. 14(16), pages 1-14, August.
    15. Oleg Bazaluk & Valerii Havrysh & Mykhailo Fedorchuk & Vitalii Nitsenko, 2021. "Energy Assessment of Sorghum Cultivation in Southern Ukraine," Agriculture, MDPI, vol. 11(8), pages 1-22, July.
    16. Marcin Steczek & Piotr Chudzik & Adam Szeląg, 2020. "Application of a Non-carrier-Based Modulation for Current Harmonics Spectrum Control during Regenerative Braking of the Electric Vehicle," Energies, MDPI, vol. 13(24), pages 1-21, December.
    17. Fei Lin & Shihui Liu & Zhihong Yang & Yingying Zhao & Zhongping Yang & Hu Sun, 2016. "Multi-Train Energy Saving for Maximum Usage of Regenerative Energy by Dwell Time Optimization in Urban Rail Transit Using Genetic Algorithm," Energies, MDPI, vol. 9(3), pages 1-21, March.
    18. Zhan, Shuguang & Wang, Pengling & Wong, S.C. & Lo, S.M., 2022. "Energy-efficient high-speed train rescheduling during a major disruption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    19. Andreas Bärmann & Alexander Martin & Oskar Schneider, 2017. "A comparison of performance metrics for balancing the power consumption of trains in a railway network by slight timetable adaptation," Public Transport, Springer, vol. 9(1), pages 95-113, July.
    20. Jefimowski, Włodzimierz & Szeląg, Adam & Steczek, Marcin & Nikitenko, Anatolii, 2020. "Vanadium redox flow battery parameters optimization in a transportation microgrid: A case study," Energy, Elsevier, vol. 195(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1946-:d:765966. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.