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Fault-Tolerant Control in a Peak-Power Reduction System of a Traction Substation with Multi-String Battery Energy Storage System

Author

Listed:
  • Marcin Szott

    (Institute of Automatic Control, Electronics and Electrical Engineering, University of Zielona Góra, St Prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland)

  • Marcin Jarnut

    (Institute of Automatic Control, Electronics and Electrical Engineering, University of Zielona Góra, St Prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland)

  • Jacek Kaniewski

    (Institute of Automatic Control, Electronics and Electrical Engineering, University of Zielona Góra, St Prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland)

  • Łukasz Pilimon

    (Institute of Automatic Control, Electronics and Electrical Engineering, University of Zielona Góra, St Prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland)

  • Szymon Wermiński

    (Institute of Automatic Control, Electronics and Electrical Engineering, University of Zielona Góra, St Prof. Z. Szafrana 2, 65-516 Zielona Góra, Poland)

Abstract

This paper introduces the concept of fault-tolerant control (FTC) of a multi-string battery energy storage system (BESS) in the dynamic reduction system of a traction substation load (DROPT). The major task of such a system is to reduce the maximum demand for contracted peak power, averaged for 15 min. The proposed concept, based on a multi-task control algorithm, takes into account: a three-threshold power limitation of the traction substation, two-level reduction of available power of a BESS and a multi-string structure of a BESS. It ensures the continuity of the maximum peak power demand at the contracted level even in the case of damage or disconnection of at least one chain of cells of the battery energy storage (BES) or at least one converter of the power conversion system (PCS). The proposed control strategy has been tested in a model of the system for dynamic reduction of traction substation load with a rated power of 5.5 MW. Two different BESS implementations have been proposed and several possible cases of failure of operations have been investigated. The simulation results have shown that the implementation of a multi-string BESS and an appropriate control algorithm (FTC) may allow for maintenance of the major assumption of DROPT, which is demanded power reduction (from 3.1 MW to 0.75 MW), even with a reduction of the BESS available power by at least 25% and more in the even in fault cases.

Suggested Citation

  • Marcin Szott & Marcin Jarnut & Jacek Kaniewski & Łukasz Pilimon & Szymon Wermiński, 2021. "Fault-Tolerant Control in a Peak-Power Reduction System of a Traction Substation with Multi-String Battery Energy Storage System," Energies, MDPI, vol. 14(15), pages 1-23, July.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:15:p:4565-:d:603305
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    1. Mao-Chia Huang & Cheng-Hsien Yang & Chien-Chih Chiang & Sheng-Cheng Chiu & Yun-Feng Chen & Cong-You Lin & Lu-Yu Wang & Yen-Liang Li & Chang-Chung Yang & Wen-Sheng Chang, 2018. "Influence of High Loading on the Performance of Natural Graphite-Based Al Secondary Batteries," Energies, MDPI, vol. 11(10), pages 1-12, October.
    2. Fei Lin & Xuyang Li & Yajie Zhao & Zhongping Yang, 2016. "Control Strategies with Dynamic Threshold Adjustment for Supercapacitor Energy Storage System Considering the Train and Substation Characteristics in Urban Rail Transit," Energies, MDPI, vol. 9(4), pages 1-18, March.
    3. Qing Gu & Tao Tang & Fang Cao & Hamid Reza Karimi & Yongduan Song, 2013. "Peak Power Demand and Energy Consumption Reduction Strategies for Trains under Moving Block Signalling System," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-11, November.
    4. Li Chen & Yuqi Tong & Zuomin Dong, 2020. "Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems," Energies, MDPI, vol. 13(7), pages 1-19, April.
    5. Hyeongig Kim & Jae-Haeng Heo & Jong-Young Park & Yong Tae Yoon, 2017. "Impact of Battery Energy Storage System Operation Strategy on Power System: An Urban Railway Load Case under a Time-of-Use Tariff," Energies, MDPI, vol. 10(1), pages 1-15, January.
    6. Shuai Su & Tao Tang & Yihui Wang, 2016. "Evaluation of Strategies to Reducing Traction Energy Consumption of Metro Systems Using an Optimal Train Control Simulation Model," Energies, MDPI, vol. 9(2), pages 1-19, February.
    7. Wei, Zhongbao & Zhao, Jiyun & Ji, Dongxu & Tseng, King Jet, 2017. "A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model," Applied Energy, Elsevier, vol. 204(C), pages 1264-1274.
    8. Kyoung-min Kwon & Jaeho Choi, 2019. "Single-Phase 13-Level Power Conditioning System for Peak Power Reduction of a High-Speed Railway Substation," Energies, MDPI, vol. 12(23), pages 1-26, November.
    9. Marcin Szott & Szymon Wermiński & Marcin Jarnut & Jacek Kaniewski & Grzegorz Benysek, 2021. "Battery Energy Storage System for Emergency Supply and Improved Reliability of Power Networks," Energies, MDPI, vol. 14(3), pages 1-21, January.
    10. Regina Lamedica & Alessandro Ruvio & Laura Palagi & Nicola Mortelliti, 2020. "Optimal Siting and Sizing of Wayside Energy Storage Systems in a D.C. Railway Line," Energies, MDPI, vol. 13(23), pages 1-22, November.
    11. 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.
    12. Yu-Shan Cheng & Yi-Hua Liu & Holger C. Hesse & Maik Naumann & Cong Nam Truong & Andreas Jossen, 2018. "A PSO-Optimized Fuzzy Logic Control-Based Charging Method for Individual Household Battery Storage Systems within a Community," Energies, MDPI, vol. 11(2), pages 1-18, February.
    13. Yu Miao & Patrick Hynan & Annette von Jouanne & Alexandre Yokochi, 2019. "Current Li-Ion Battery Technologies in Electric Vehicles and Opportunities for Advancements," Energies, MDPI, vol. 12(6), pages 1-20, March.
    14. Peter Haidl & Armin Buchroithner & Bernhard Schweighofer & Michael Bader & Hannes Wegleiter, 2019. "Lifetime Analysis of Energy Storage Systems for Sustainable Transportation," Sustainability, MDPI, vol. 11(23), pages 1-21, November.
    15. 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.
    16. 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.
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    2. Nikita Dmitrievich Senchilo & Denis Anatolievich Ustinov, 2021. "Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption," Energies, MDPI, vol. 14(21), pages 1-25, October.

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