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On-Board Energy Storage Devices with Supercapacitors for Metro Trains—Case Study Analysis of Application Effectiveness

Author

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  • Petru Valentin Radu

    (Electric Traction Division, Power Engineering Institute, Warsaw University of Technology, Koszykowa Street 75, 00-662 Warsaw, Poland)

  • Adam Szelag

    (Electric Traction Division, Power Engineering Institute, Warsaw University of Technology, Koszykowa Street 75, 00-662 Warsaw, Poland)

  • Marcin Steczek

    (Electric Traction Division, Power Engineering Institute, Warsaw University of Technology, Koszykowa Street 75, 00-662 Warsaw, Poland)

Abstract

This paper presents an analysis on using an on-board energy storage device (ESD) for enhancing braking energy re-use in electrified railway transportation. A simulation model was developed in the programming language C++ to help with the sizing of the ESD. The simulation model based on the mathematical description has been proposed for a train equipped with on-board ESD for analysis of effectiveness of its application. A case study was carried out for a metro line taking into consideration train characteristics, track alignment, line velocity limits and a running time table. This case study was used to assess the energy savings and perform a cost-benefit analysis for different sizes of the on-board ESD by applying the proposed approach. It was shown that when additional environmental benefits (reduction of CO 2 emissions) are considered, this may significantly improve effectiveness of the investments due to CO 2 European Emission allowances.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1291-:d:219912
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    References listed on IDEAS

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    1. Bin Wang & Zhongping Yang & Fei Lin & Wei Zhao, 2014. "An Improved Genetic Algorithm for Optimal Stationary Energy Storage System Locating and Sizing," Energies, MDPI, vol. 7(10), pages 1-25, October.
    2. Rupp, A. & Baier, H. & Mertiny, P. & Secanell, M., 2016. "Analysis of a flywheel energy storage system for light rail transit," Energy, Elsevier, vol. 107(C), pages 625-638.
    3. 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.
    4. Huan Xia & Huaixin Chen & Zhongping Yang & Fei Lin & Bin Wang, 2015. "Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm," Energies, MDPI, vol. 8(10), pages 1-23, October.
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    Citations

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    Cited by:

    1. Agata Pomykala & Adam Szelag, 2022. "Reduction of Power Consumption and CO 2 Emissions as a Result of Putting into Service High-Speed Trains: Polish Case," Energies, MDPI, vol. 15(12), pages 1-24, June.
    2. 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.
    3. 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).
    4. Petru Valentin Radu & Miroslaw Lewandowski & Adam Szelag, 2020. "On-Board and Wayside Energy Storage Devices Applications in Urban Transport Systems—Case Study Analysis for Power Applications," Energies, MDPI, vol. 13(8), pages 1-29, April.
    5. Hassan Mohammadi Pirouz & Amin Hajizadeh, 2020. "A Highly Reliable Propulsion System with Onboard Uninterruptible Power Supply for Train Application: Topology and Control," Sustainability, MDPI, vol. 12(10), pages 1-30, May.
    6. Petru Valentin Radu & Miroslaw Lewandowski & Adam Szelag & Marcin Steczek, 2022. "Short-Circuit Fault Current Modeling of a DC Light Rail System with a Wayside Energy Storage Device," Energies, MDPI, vol. 15(10), pages 1-24, May.
    7. 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.
    8. 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.
    9. 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.
    10. 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.

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