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

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 capaciti...

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Main Authors: Guangya Zhu, Shiyu Ma, Shuai Yang, Yue Zhang, Bingyan Wang, Kai Zhou
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Energies
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Online Access:https://www.mdpi.com/1996-1073/18/13/3382
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author Guangya Zhu
Shiyu Ma
Shuai Yang
Yue Zhang
Bingyan Wang
Kai Zhou
author_facet Guangya Zhu
Shiyu Ma
Shuai Yang
Yue Zhang
Bingyan Wang
Kai Zhou
author_sort Guangya Zhu
collection DOAJ
description 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.
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institution Kabale University
issn 1996-1073
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publisher MDPI AG
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series Energies
spelling doaj-art-ccf8ca1256244b49b7d6353663419ed92025-08-20T03:49:55ZengMDPI AGEnergies1996-10732025-06-011813338210.3390/en18133382Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization CurrentGuangya Zhu0Shiyu Ma1Shuai Yang2Yue Zhang3Bingyan Wang4Kai Zhou5College of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaDongfang Electric Machinery Co., Ltd., Deyang 618000, ChinaDongfang Electric Machinery Co., Ltd., Deyang 618000, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaAccurate 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.https://www.mdpi.com/1996-1073/18/13/3382polarization/depolarization current methoddynamic mode decompositionADMM algorithmextended Debye modelpumped storage generator-motorwinding insulation
spellingShingle Guangya Zhu
Shiyu Ma
Shuai Yang
Yue Zhang
Bingyan Wang
Kai Zhou
Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current
Energies
polarization/depolarization current method
dynamic mode decomposition
ADMM algorithm
extended Debye model
pumped storage generator-motor
winding insulation
title Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current
title_full Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current
title_fullStr Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current
title_full_unstemmed Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current
title_short Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Current
title_sort identification of dielectric response parameters of pumped storage generator motor stator winding insulation based on sparsity enhanced dynamic decomposition of depolarization current
topic polarization/depolarization current method
dynamic mode decomposition
ADMM algorithm
extended Debye model
pumped storage generator-motor
winding insulation
url https://www.mdpi.com/1996-1073/18/13/3382
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