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Research on the Energy Management Strategy of a Hybrid Energy Storage Type Railway Power Conditioner System

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  • Ying Wang

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    Laboratory of Opto-Technology and Intelligent Control Ministry of Education, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Ya Guo

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Xiaoqiang Chen

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    Laboratory of Opto-Technology and Intelligent Control Ministry of Education, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Yunpeng Zhang

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Dong Jin

    (China Railway Lanzhou Bureau Group Co., Ltd., Lanzhou 730000, China)

  • Jing Xie

    (Xi’an Rail Transit Group Co., Ltd., Operation Branch, Xi’an 710000, China)

Abstract

High-speed railways generate a large amount of regenerative braking energy during operation but this energy is not utilized efficiently. In order to realize the recycling of regenerative braking energy of high-speed railways, the hybrid energy storage type railway power conditioner (RPC) system is proposed. The working principle and the control strategy of the system are studied. The energy management strategy consisting of a hybrid energy storage system charging and discharging strategy and variational modal decomposition (VMD) power allocation strategy is proposed. Three system operation modes are proposed: the power of the hybrid energy storage system is decomposed by VMD and an interrelationship number is proposed to determine the lithium battery and supercapacitor power. The hardware-in-the-loop test experiments are conducted by the StarSim power electronics small-step real-time simulator from Modeling Tech and the validation analysis is carried out on MATLAB/Simulink with the actual measurement data of a traction substation on the Lanzhou–Xinjiang line. The results verify that the proposed strategy can effectively recycle the regenerative braking energy, realize the peak-shaving effect on the load, and reduce the energy consumption of the train.

Suggested Citation

  • Ying Wang & Ya Guo & Xiaoqiang Chen & Yunpeng Zhang & Dong Jin & Jing Xie, 2023. "Research on the Energy Management Strategy of a Hybrid Energy Storage Type Railway Power Conditioner System," Energies, MDPI, vol. 16(15), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5759-:d:1208819
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    References listed on IDEAS

    as
    1. Wang, Xin & Luo, Yingbing & Qin, Bin & Guo, Lingzhong, 2022. "Power dynamic allocation strategy for urban rail hybrid energy storage system based on iterative learning control," Energy, Elsevier, vol. 245(C).
    2. Luis A. M. Barros & António P. Martins & José Gabriel Pinto, 2023. "Balancing the Active Power of a Railway Traction Power Substation with an sp-RPC," Energies, MDPI, vol. 16(7), pages 1-22, March.
    3. 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.
    4. Zhuang Xiao & Pengfei Sun & Qingyuan Wang & Yuqing Zhu & Xiaoyun Feng, 2018. "Integrated Optimization of Speed Profiles and Power Split for a Tram with Hybrid Energy Storage Systems on a Signalized Route," Energies, MDPI, vol. 11(3), pages 1-21, February.
    5. Jing Teng & Longkai Li & Yajun Jiang & Ruifeng Shi, 2022. "A Review of Clean Energy Exploitation for Railway Transportation Systems and Its Enlightenment to China," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    6. Francesco Cutrignelli & Gianmarco Saponaro & Michele Stefanizzi & Marco Torresi & Sergio Mario Camporeale, 2023. "Study of the Effects of Regenerative Braking System on a Hybrid Diagnostic Train," Energies, MDPI, vol. 16(2), pages 1-18, January.
    7. Yuanli Liu & Minwu Chen & Shaofeng Lu & Yinyu Chen & Qunzhan Li, 2018. "Optimized Sizing and Scheduling of Hybrid Energy Storage Systems for High-Speed Railway Traction Substations," Energies, MDPI, vol. 11(9), pages 1-29, August.
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