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Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current

Author

Listed:
  • Guangya Zhu

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Shiyu Ma

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Shuai Yang

    (Dongfang Electric Machinery Co., Ltd., Deyang 618000, China)

  • Yue Zhang

    (Dongfang Electric Machinery Co., Ltd., Deyang 618000, China)

  • Bingyan Wang

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Kai Zhou

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

Abstract

Accurate diagnosis of the insulation condition of stator windings in pumped storage generator-motor units is crucial for ensuring the safe and stable operation of power systems. Time domain dielectric response testing is an effective method for rapidly diagnosing the insulation condition of capacitive devices, such as those in pumped storage generator-motors. To precisely identify the conductivity and relaxation process parameters of the insulating medium and accurately diagnose the insulation condition of the stator windings, this paper proposes a method for identifying the insulation dielectric response parameters of stator windings based on sparsity-enhanced dynamic mode decomposition of the depolarization current. First, the measured depolarization current time series is processed through dynamic mode decomposition (DMD). An iterative reweighted L1 (IRL1)-based method is proposed to formulate a reconstruction error minimization problem, which is solved using the ADMM algorithm. Based on the computed modal amplitudes, the dominant modes—representing the main insulation relaxation characteristics—are separated from spurious modes caused by noise. The parameters of the extended Debye model (EDM) are then calculated from the dominant modes, enabling precise identification of the relaxation characteristic parameters. Finally, the accuracy and feasibility of the proposed method are verified through a combination of simulation experiments and laboratory tests.

Suggested Citation

  • Guangya Zhu & Shiyu Ma & Shuai Yang & Yue Zhang & Bingyan Wang & Kai Zhou, 2025. "Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current," Energies, MDPI, vol. 18(13), pages 1-22, June.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3382-:d:1688893
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    References listed on IDEAS

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    1. Yang, Weijia & Yang, Jiandong, 2019. "Advantage of variable-speed pumped storage plants for mitigating wind power variations: Integrated modelling and performance assessment," Applied Energy, Elsevier, vol. 237(C), pages 720-732.
    2. Feng Yang & Lin Du & Lijun Yang & Chao Wei & Youyuan Wang & Liman Ran & Peng He, 2018. "A Parameterization Approach for the Dielectric Response Model of Oil Paper Insulation Using FDS Measurements," Energies, MDPI, vol. 11(3), pages 1-17, March.
    3. Yamei Li & Zhaowei Peng & Dangguo Xu & Shiyang Huang & Yanfeng Gao & Yuan Li, 2024. "Research on the Thermal Aging Characteristics of Crosslinked Polyethylene Cables Based on Polarization and Depolarization Current Measurement," Energies, MDPI, vol. 17(10), pages 1-14, May.
    4. Potrč, Sanja & Čuček, Lidija & Martin, Mariano & Kravanja, Zdravko, 2021. "Sustainable renewable energy supply networks optimization – The gradual transition to a renewable energy system within the European Union by 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
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