Flashover Model of Insulator Based on Dynamic Variation of Pollution Layer Resistance—Part I
One of the primary threats to the reliable operation of power systems is the phenomenon of pollution flashover on insulators. Due to the intricate nature of the pollution flashover mechanism, existing flashover models face significant limitations in accurately analyzing the impact of critical factors such as environmental temperature, pollution layer wetting, and other variables on the resistance of the insulator’s pollution layer. This study aims to develop a dynamic pollution resistance model that accounts for the time-dependent variation of surface conductivity in polluted insulators. By incorporating the effects of leakage current evolution and moisture dynamics, the proposed model provides an improved predictive framework for pollution flashover under both AC and DC conditions. Experimental validation demonstrates that the model achieves high accuracy, with an average error of less than 5.2% compared to measured flashover voltages. The proposed model can be utilized to predict the flashover characteristics of contaminated insulators under both direct current (DC) and alternating current (AC) conditions.
Authors
- Yujun Guo (ORCID: https://orcid.org/0000-0003-3289-9471)
- Guangning Wu (ORCID: https://orcid.org/0000-0002-7920-6129)
- Zihao Wang (ORCID: https://orcid.org/0000-0002-3919-0396)
- Yutao Chen (ORCID: https://orcid.org/0000-0001-9366-7354)
- Xueqin Zhang (ORCID: https://orcid.org/0000-0003-3270-0899)
- Dalin Li (ORCID: https://orcid.org/0000-0002-6474-5998)
- Yang Yuan (ORCID: https://orcid.org/0000-0003-4022-0246)
- Chenguang Yang (ORCID: https://orcid.org/0000-0002-1342-5329)
Institutions
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- IEEE Transactions on Dielectrics and Electrical Insulation
- Published
- 2025-03-18
- DOI
- https://doi.org/10.1109/tdei.2025.3552059
- Citations
- 2
- Primary Topic
- Image Enhancement Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.55
Funders
- National Natural Science Foundation of China
- Sichuan Province Science and Technology Support Program