Abstract
Distribution of the contamination on insulators is often irregular, which threatens the reliability of outdoor insulation. This work aimed to study the influence of pollution distribution, humidity and dry band location with various scenarioes on flashover characteristic of insulators. Flashover tests of cup-pin glass polluted insulators were conducted. Findings indicated the difference between the flashover performances of insulators under different pollution distribution. The flashover characteristics like voltage and current are greatly affected by salt deposit density (SDD), distribution modes, and distribution area. The relation between U50 and SDD has positive power function with more contrast in distribution. Insulators with more regular distribution have lowest flashover voltage and highest critical leakage current. Different distribution modes lead to the change of the conductivity of the contamination layer and the uneven distribution of the current density, which is the main cause that the characteristics of pollution flashover are directly related to the pollution modes.
| Original language | English |
|---|---|
| Title of host publication | 2020 IEEE Student Conference on Research and Development, SCOReD 2020 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 319-324 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728193175 |
| DOIs | |
| State | Published - 27 Sep 2020 |
| Event | 2020 IEEE Student Conference on Research and Development, SCOReD 2020 - Virtual, Johor, Malaysia Duration: 27 Sep 2020 → 28 Sep 2020 |
Publication series
| Name | 2020 IEEE Student Conference on Research and Development, SCOReD 2020 |
|---|
Conference
| Conference | 2020 IEEE Student Conference on Research and Development, SCOReD 2020 |
|---|---|
| Country/Territory | Malaysia |
| City | Virtual, Johor |
| Period | 27/09/20 → 28/09/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- FEM model
- flashover
- polluted insulators pollution distribution
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
- Electrical and Electronic Engineering
- Media Technology
- Waste Management and Disposal
- Control and Optimization
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