Review on Migration Discharge Characteristics and Detection Methods of Conductive Particles in Transformer Oil

During the long-term operation of transformers, conductive impurity particles within the transformer oil can significantly degrade its dielectric strength, potentially leading to transformer failures and causing substantial economic losses and adverse social impacts. To comprehensively understand the influence of conductive particles on the discharge characteristics of transformer oil, this paper systematically reviews the progress of relevant research. First, the theoretical framework of force models for conductive particles in transformer oil is introduced, and the effects of voltage type, amplitude, temperature, and flow rate on the motion state, velocity, bridging speed, and landing distance of conductive particles are summarized. Subsequently, the discharge types of transformer oil containing conductive particles are elaborated, and the mechanisms by which factors such as the number of conductive particles and voltage type affect the breakdown voltage are analyzed. The physical mechanisms through which conductive particles induce discharges in transformer oil are also outlined. Finally, methods for the detection and identification of particles in transformer oil are systematically reviewed, with a comparison of the applicability and advantages of different techniques, and future research directions are discussed. This review aims to provide theoretical references and practical guidance for the structural optimization and operational maintenance of transformers.

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Institutions

Publication Details

Journal
IEEE Transactions on Dielectrics and Electrical Insulation
Published
2025-06-18
DOI
https://doi.org/10.1109/tdei.2025.3581173
Citations
1
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
0.73

Funders

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Review on Migration Discharge Characteristics and Detection Methods of Conductive Particles in Transformer Oil

Kai Zhou, Yefei Xu, Senhong Yang, Yuan Li et al.
1 citations
IEEE Transactions on Dielectrics and Electrical Insulation
Power Transformer Diagnostics and Insulation
0.73
article

Review on Migration Discharge Characteristics and Detection Methods of Conductive Particles in Transformer Oil

Kai Zhou, Yefei Xu, Senhong Yang, Yuan Li, Ranran Li, Chenjie Zhang, Shangchen Ji
article en
1 citations

Abstract

During the long-term operation of transformers, conductive impurity particles within the transformer oil can significantly degrade its dielectric strength, potentially leading to transformer failures and causing substantial economic losses and adverse social impacts. To comprehensively understand the influence of conductive particles on the discharge characteristics of transformer oil, this paper systematically reviews the progress of relevant research. First, the theoretical framework of force models for conductive particles in transformer oil is introduced, and the effects of voltage type, amplitude, temperature, and flow rate on the motion state, velocity, bridging speed, and landing distance of conductive particles are summarized. Subsequently, the discharge types of transformer oil containing conductive particles are elaborated, and the mechanisms by which factors such as the number of conductive particles and voltage type affect the breakdown voltage are analyzed. The physical mechanisms through which conductive particles induce discharges in transformer oil are also outlined. Finally, methods for the detection and identification of particles in transformer oil are systematically reviewed, with a comparison of the applicability and advantages of different techniques, and future research directions are discussed. This review aims to provide theoretical references and practical guidance for the structural optimization and operational maintenance of transformers.

IEEE Transactions on Dielectrics and Electrical InsulationVol. 32(5)
Sichuan University (CN), Tsinghua Sichuan Energy Internet Research Institute (CN), Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 27%
Power Transformer Diagnostics and Insulation
0.73
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