Characteristics of Partial Discharge of Typical Defects in Converter Transformer Under Operation

Converter transformers, operating in complex electric fields for extended periods, are prone to insulation degradation. To investigate partial discharge (PD) characteristics caused by internal insulation deterioration, this study developed an AC/DC PD simulation platform replicating real-world operating conditions. Four typical insulation defects—turn-to-turn, spacer block, electrostatic ring, and tap changer—were modeled, with experiments conducted in a 35 kV transformer tank using pure AC and composite AC/DC voltages (1:1, 1:3, 1:5, 1:7 ratios). The 48 Phase-Resolved Partial Discharge (PRPD) spectra were processed through image cropping, grayscale conversion, and dimension standardization, with 84% training and 16% testing datasets. Convolutional neural networks (CNNs) achieved an overall classification accuracy of 93.7% on the test set. Field validation using ±400 kV real-world converters confirmed the network’s precision in PD pattern recognition, providing technical support for insulation condition diagnosis and fault prediction in converter transformers.

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Publication Details

Journal
Energies
Published
2026-10-16
DOI
https://doi.org/10.3390/en19204905
Primary Topic
High voltage insulation and dielectric phenomena
Type
article
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article

Characteristics of Partial Discharge of Typical Defects in Converter Transformer Under Operation

Minghe Chi, Yiming Hu, Yunpeng Tang, Hong Liu et al.
Energies
High voltage insulation and dielectric phenomena
article

Characteristics of Partial Discharge of Typical Defects in Converter Transformer Under Operation

Minghe Chi, Yiming Hu, Yunpeng Tang, Hong Liu, Hua Yu, Jian Liu
article en

Abstract

Converter transformers, operating in complex electric fields for extended periods, are prone to insulation degradation. To investigate partial discharge (PD) characteristics caused by internal insulation deterioration, this study developed an AC/DC PD simulation platform replicating real-world operating conditions. Four typical insulation defects—turn-to-turn, spacer block, electrostatic ring, and tap changer—were modeled, with experiments conducted in a 35 kV transformer tank using pure AC and composite AC/DC voltages (1:1, 1:3, 1:5, 1:7 ratios). The 48 Phase-Resolved Partial Discharge (PRPD) spectra were processed through image cropping, grayscale conversion, and dimension standardization, with 84% training and 16% testing datasets. Convolutional neural networks (CNNs) achieved an overall classification accuracy of 93.7% on the test set. Field validation using ±400 kV real-world converters confirmed the network’s precision in PD pattern recognition, providing technical support for insulation condition diagnosis and fault prediction in converter transformers.

EnergiesVol. 19(20)
Harbin University of Science and Technology (CN), State Grid Corporation of China (China) (CN), State Grid Shanxi Electric Power Company Electric Power Research Institute
Industry, innovation and infrastructure, Affordable and clean energy
Openalex Percentile: Top 28%
High voltage insulation and dielectric phenomena
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