Genetic Algorithm in evaluating insulation model parameters

In order to increase reliability of grids and also safety of power instruments, it is too important to distinguish their defects before a complete damage. Therefore insulation modeling of these instruments is noticed to recognize their insulation conditions and performance. In this paper, a simple RC model is used to model the power insulating instrument and PDC test results are used to determine the different parameters of this model. Among different methods evaluating the parameters, the methods of Exponential-curve-fitting and Genetic Algorithm (GA) are used. At last transformer insulation model of Neka1 power plant is presented and its parameters are evaluated according to PDC test results. Therefore the described methods are used to recognize the parameters and their results are compared with each other. This comparison shows ability of GA in recognizing insulation model parameters.