Abstract:
High voltage insulators form an essential part of the high voltage electric power transmission systems. Any failure in the satisfactory performance of high voltage insulators will result in considerable loss of capital because there are numerous industries that depend upon the availability of an uninterrupted power supply. The importance of the research on insulator pollution has been increased considerably with the rise of the voltage of the transmission lines. In order to determine the flashover behavior of polluted high voltage insulators and to determine the physical mechanisms that govern this phenomenon, the researchers have established many types of modeling.
Artificial intelligent techniques can be used and are being used to estimate the critical flashover voltage (FOV) for polluted insulators, using experimental measurements carried out in an insulator test station and a mathematical model based on the characteristics of the insulator like : diameter, height, creepage distance, form factor , equivalent salt deposit density etc.
In this project work Fuzzy logic technique and Artificial Neural Network technique have been used to make the models of the outdoor insulators: glass, porcelain and composite. These models have four element input vectors. These four elements include surrounding pressure, salt deposit density, creepage distance and maximum diameter of insulators. A comparison between the results of the two types of the models is also done and has been seen that ANN models give results much nearer to experimental values. Then these models have been simulated at some new input values other- than the experimental ones. So prediction of flashover voltage has been done by using these models.
