Citation

Salem AA, Abd-Rahman R, Ishak MTB, Lau KY, Abdul-Malek Z, Al-ameri S, Al-Gailani SA, Ghoneim SSM. Ain Shams Eng. J. 2023; 14(12): e102249.

Copyright

(Copyright © 2023, Ain Shams University, Publisher Elsevier Publishing)

DOI

10.1016/j.asej.2023.102249

PMID

unavailable

Abstract

The aim of this work is to model the influence of uneven contamination distribution under various humidity on the pollution flashover voltage of 11 kV porcelain insulator disc. Four scenarios of contamination distribution were proposed to test the sample under various severities of contamination simulated by salt deposit density (SDD). Seriesflashover experiments on contaminated insulators were performed under various conditions. The voltage of flashover under clean condition was appointed as a reference value for analyzing the effect of pollution. Based on the percentage value of breakdown voltage of the contaminated insulator to the clean insulator, the conditions of the tested sample are classified into three categories namely normal (55-60%), caution (45-54 %) and severe (35-44%). In the experimental tests, the uneven contamination area dimension was taken into consideration. An artificial neural network (ANN), derived from experiment results was used as a tool to predict the flashover voltage. The ANN method is built with five inputs related to the geometry of the sample and pollution factors while the flashover voltage was set as the model's output. The results showed that the distribution of pollutants according to the presented scenario has a significant impact on the performance of the flashover voltage. In addition, the error value between the experiment outcomes and the prediction system appeared to be less than 6%. This suggests that the proposed ANN model can be an effective tool in forecasting the insulators' flashover voltage under test.

Language: en

Keywords

Artificial neural networks; Distribution; Flashover voltage; Polluted insulators; Pollution scenario