Application of artificial neural network in predicting flashover behaviour of outdoor insulators under polluted conditions

Sajjad, Umer and Arshad, A and Ahmad, Jawad and Shoaib, Sultan; Shaposhnikov, S., ed. (2021) Application of artificial neural network in predicting flashover behaviour of outdoor insulators under polluted conditions. In: 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus). IEEE, SUN, pp. 2868-2873. ISBN 9781665404761

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    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.

    ORCID iDs

    Sajjad, Umer, Arshad, A ORCID logoORCID: https://orcid.org/0000-0001-8621-2773, Ahmad, Jawad and Shoaib, Sultan; Shaposhnikov, S.