New criteria for metal oxide surge arrester condition monitoring based on leakage current analysis: Considering non‐uniform pollution effect

Abstract

AbstractThe role of surge arresters is vital in power systems' protection against transient overvoltages, which can arise due to occurrences like lightning strikes or switching operations. Based on the performance of the surge arrester, assessing its condition is an essential requirement for early detection of any damage or deterioration. This article proposes innovative criteria based on the surge arresters’ leakage current analysis for the classification of uniform and non‐uniform pollution levels. The leakage current signal of clean, uniform, and non‐uniform polluted surge arresters has been examined under different contamination levels, humidity, and non‐uniformity degrees. Based on the experimental results analysis, a new criterion has been proposed for assessing the surge arrester condition, which has resulted from the fifth and first‐order harmonics ratio of resistive leakage current. Analysis of the proposed criterion demonstrates that this index has a significant correlation to the pollution level. The proposed criterion ability has been established based on random forest, support vector machine, decision tree algorithm, and multi‐layer perceptron in Python language. The obtained criterion based on experimental data in different conditions has been employed for classifier training, which can be applied in the power network for better condition monitoring of surge arresters ensuring fast and accurate outcomes.