Parameters' selection for metal oxide surge arresters models using genetic algorithm

The efficient representation of surge arrester's dynamic behavior by the appropriate equivalent circuit models improves the quality and reliability of the lightning performance studies; hence, the appropriate modeling of metal-oxide surge arresters and the determination of their parameters are significant issues. In the present work a genetic algorithm is developed, for the evaluation of the parameters of surge arrester's models. The developed genetic algorithm computes the optimum circuit model parameters, in order to minimize the error between the simulated peak residual voltage value and the one given by the manufacturer.