چكيده فارسي :
— The appropriate modeling of surge arrester and its equivalent circuit parameters are significant issues. To design a suitable lightning protection system, the surge arrester frequency-dependent model and its residual voltage should be defined. In this paper, particle swarm optimization with a grey wolf optimization algorithm (PSO-GWO) has been implemented as an optimization algorithm to adjust the parameters of the surge arrester dynamic model. According to the obtained results, the best relative error values for the injected transient current have been obtained by the Pinceti model. For lightning impulse current, the IEEE model has the best result and the lowest relative error values compared to the Fernandez and Pinceti models. In addition, to compare the efficiency of the PSO-GWO, the obtained results for 10kA, 8/20µs have been compared to the other optimization techniques results. The lowest error for the residual voltage amplitude of the surge arrester model has been achieved by PSO-GWO algorithm. Besides, the modified PSO had the best results compared to the genetic and the PSO techniques.
