Prediction of AC Breakdown Voltage of Different Electrode Configuration Using Artificial Neural Networks

Abstract

The study focuses on the application of Artificial Neural Networks (ANNs) to model and predict the AC breakdown voltage in gas-insulated systems for different electrode configurations. Gas-insulated systems play a crucial role in the transmission and distribution of electrical energy, and understanding the breakdown characteristics is essential for designing reliable and efficient systems. The research investigates how different electrode configurations impact the AC breakdown voltage in gas-insulated environments. Traditional methods for studying AC breakdown involve complex theoretical models and extensive experimentation. The use of ANN offers an innovative approach to predict breakdown voltages by learning complex relationships from available data.