Abstract
Safe and reliable delivery of power through transmission lines mainly depends on the quality condition of the high voltage insulators. In the last few decades, demand in polymeric insulator has been dramatically increased due to their advanced performance in comparison to ceramic and glass insulators. This paper discusses the application of Artificial Neural Network (ANN) to predict the flashover parameters of polymeric insulators under the impact of weather and environment conditions. The training data for ANN were obtained from experimental tests executed in the climate chamber with the implementation of high voltage stress. The parameters predicted in this paper are arc-inception voltage, flashover voltage and surface resistance. A promising application of the ANN model proposed in this paper is the effective prediction of the flashover parameters of polymeric insulators affecting by extreme temperature, humidity and pollution level. These results will also enhance our understanding of the flashover process in outdoor polymeric insulators.
| Original language | English |
|---|---|
| Title of host publication | 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus) |
| Publisher | IEEE |
| Pages | 2868-2873 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781665404761 |
| ISBN (Print) | 9781665446426 |
| DOIs | |
| Publication status | Published - 9 Apr 2021 |
Keywords
- surface resistance
- training data
- artificial neural networks
- high-voltage techniques
- flashover
- insulators
- polymers
- flashover behaviour
- high voltage
- neural network
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Safety, Risk, Reliability and Quality
- Instrumentation
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Hardware and Architecture
- Computer Networks and Communications
