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Peak Shaving Strategy in the Context of the Charging Process of a Battery Energy Storage System in the Railway Microgrid

Author

Listed:
  • Piotr Obrycki

    (Office of Research, Development and Aid Financing, PGE Energetyka Kolejowa S.A., 63/67 Hoża St, 00-681 Warsaw, Poland)

  • Krzysztof Perlicki

    (Institute of Telecommunications, Faculty of Electronics and Information Technology, Warsaw University of Technology, 15/19 Nowowiejska St, 00-665 Warsaw, Poland)

  • Marek Stawowy

    (Department of Air Transport Engineering and Teleinformatics, Faculty of Transport, Warsaw University of Technology, 75 Koszykowa St, 00-662 Warsaw, Poland)

Abstract

Peak shaving is one of the key mechanisms implemented in technically advanced power grids, including rail networks, to reduce the demand for costly power generation during peak hours. Energy storage systems are commonly used for this purpose. This article presents an analysis of peak load reduction using energy storage considering the specifics of the energy operation of the railway network. Two methods of peak shaving are proposed: a variable threshold value and a constant threshold value. The choice of one of them depends on the relationship between the frequency of occurrence of peak loads on the railway line and the charging time of the energy storage system. An innovative predictive analysis of the temporal characteristics of the railway line load was carried out to determine the likelihood of a peak load occurring during the charging of the energy storage system. The Poisson distribution and Long Short-Term Memory method were used to accomplish this task. The first experiment in Poland on peak shaving using a large-scale energy storage system is presented. It was also one of the first high-power installations of this type in the world to directly cooperate with a 3 kV DC traction network.

Suggested Citation

  • Piotr Obrycki & Krzysztof Perlicki & Marek Stawowy, 2025. "Peak Shaving Strategy in the Context of the Charging Process of a Battery Energy Storage System in the Railway Microgrid," Energies, MDPI, vol. 18(11), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2674-:d:1661639
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    References listed on IDEAS

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    1. Marek Stawowy & Adam Rosiński & Mirosław Siergiejczyk & Krzysztof Perlicki, 2021. "Quality and Reliability-Exploitation Modeling of Power Supply Systems," Energies, MDPI, vol. 14(9), pages 1-16, May.
    2. Shirazi, Elham & Jadid, Shahram, 2017. "Cost reduction and peak shaving through domestic load shifting and DERs," Energy, Elsevier, vol. 124(C), pages 146-159.
    3. Reihani, Ehsan & Motalleb, Mahdi & Ghorbani, Reza & Saad Saoud, Lyes, 2016. "Load peak shaving and power smoothing of a distribution grid with high renewable energy penetration," Renewable Energy, Elsevier, vol. 86(C), pages 1372-1379.
    4. Chua, Kein Huat & Lim, Yun Seng & Morris, Stella, 2017. "A novel fuzzy control algorithm for reducing the peak demands using energy storage system," Energy, Elsevier, vol. 122(C), pages 265-273.
    5. Md Masud Rana & Mohamed Atef & Md Rasel Sarkar & Moslem Uddin & GM Shafiullah, 2022. "A Review on Peak Load Shaving in Microgrid—Potential Benefits, Challenges, and Future Trend," Energies, MDPI, vol. 15(6), pages 1-17, March.
    6. Mobarak Abumohsen & Amani Yousef Owda & Majdi Owda, 2023. "Electrical Load Forecasting Using LSTM, GRU, and RNN Algorithms," Energies, MDPI, vol. 16(5), pages 1-31, February.
    7. Md Masud Rana & Akhlaqur Rahman & Moslem Uddin & Md Rasel Sarkar & Sk. A. Shezan & Md. Fatin Ishraque & S M Sajjad Hossain Rafin & Mohamed Atef, 2022. "A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data," Energies, MDPI, vol. 15(1), pages 1-16, January.
    8. Neves, Sónia Almeida & Marques, António Cardoso & Fuinhas, José Alberto, 2018. "On the drivers of peak electricity demand: What is the role played by battery electric cars?," Energy, Elsevier, vol. 159(C), pages 905-915.
    9. Gotham, Douglas & Muthuraman, Kumar & Preckel, Paul & Rardin, Ronald & Ruangpattana, Suriya, 2009. "A load factor based mean-variance analysis for fuel diversification," Energy Economics, Elsevier, vol. 31(2), pages 249-256, March.
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