Prediction of Insulator's Equivalent Salt Deposit Density in Power System

Abstract

The equivalent salt deposit density (ESDD) of insulator in power system is the main basis of defining pollution classes and mapping pollution areas. However, The meteorological factors on it is complex, using traditional methods is difficult to establish accurate mathematical model to express the relationship, In this paper, the gray theory and neural network model to reflect the changing trend of data series on the apparent effect, Gray neural network model used to predict the insulators ESDD under certain meteorological factors, and to design a neural network compensator correction on the predicted results. The simulation results show that the model has higher prediction accuracy, better than a simple gray neural network model, and have certain theoretical value and practical application value.