Estimation of the Pollution Critical Level on the Surface of Glass Insulators Based on Leakage Current

Electrical insulators are components used to promote electrical isolation and mechanical support for conductors in transmission lines belonging to the electric power systems (EPS). The performance of glass insulators is compromised mainly in the face of high pollution level, causing the amplitude of the leakage current to increase and the formation of superficial discharges. In this work, a methodology for estimating the surface pollution critical level of glass insulators using leakage current parameters and artificial intelligence algorithms is proposed. For this purpose, glass insulators were tested in the laboratory to simulate different levels of pollution, in order to record leakage current, voltage signals and environmental variables (e.g., humidity and temperature). The pollution level was simulated by depositing the pollution solution on the insulators, where each solution was differentiated based on the level of equivalent salt deposit density (ESDD). In the tests, the level of ESDD responsible for causing surface discharges was also recorded, as this phenomenon occurs at high levels of pollution. Pollution modeling was performed using forecasting algorithms such as multilayer perceptron (MLP) and support vectors regression (SVR). Based on the application of the best performance model and using criteria that indicate the occurrence of surface discharges, it was possible to estimate the critical level of pollution in the glass insulators string for 69 kV systems.