Identification of dynamic parameters of a fourth-order Synchronous generator nonlinear model using Particle Swarm Optimization algorithm

In recent years, Synchronous generator parameters identification has been taken into consideration in many studies. This article presents an approach for parameters identification of the nonlinear fourth-order dynamic model of a synchronous generator. Past researches have shown that some perturbations can easily be applied to a working generator. This leads us to a proper choice of input and outputs needed for identification. By applying step perturbation to the field voltage, as input, generator outputs including electrical power, rotor speed and stator current are measured and parameter of the generator has been estimated by making comparison between the estimated model outputs and the measured ones, using Particle Swarm Optimization (PSO). The result of the simulation shows how efficient this method is.