An Improved Dynamic Multi-Arcs Modeling Approach for Pollution Flashover of Silicone Rubber Insulator

This article presents a dynamic modeling approach to analyze pollution flashover of silicone rubber insulators. Pre-flashover conditions can be used to represent analytical formulations for different stages of dry band arcing activities on the surface of polluted insulator. In this article, effects of dust deposit as nonsoluble deposit density (NSDD) are investigated on the dynamic behavior of partial arcs on the surface of insulators by means of a proposed multi-arcs modeling approach. It is shown that analytical formulations of dynamic resistance of surface pollution can be used to analyze different modes of arcing as unstable and stable. Real data of leakage current (LC) and flashover voltage (FOV) of polluted insulator are used to make correlation with analytical multi-arcs formulations. The proposed analytical multi-arcs model is based on an artificial neural network (ANN) which is able to predict the LC and FOV of the insulator in real-time monitoring. In addition, effects of pollution resistance as variable surface conduction and thickness of pollution layer are investigated on LC and FOV of the insulators. It is shown that the proposed multi-arcs representation has a closer correlation with real testing data in comparison to previous single-arc and multi-arcs models.