Model parameter identification of excitation system based on a genetic algorithm techniques

Excitation system is one of the key elements affecting the dynamic performance of electric power systems. Therefore, accurate Excitation models are of great importance in the simulation and the investigation of the power system transient phenomena. In this paper, a nonlinear identification method for the excitation system (EXS) of Mianhuatan power plant in China is presented. Two different identification methods, i.e., genetic algorithm and prediction error method (PEM) are used and compared. In the genetic algorithm, a block-diagram for the EXS is suggested at first. In the investigated excitation system, measurement was performed at no-load operation condition to obtain step response used for the identification of the parameters for the model. The simulation results and the comparison show the good accuracy of both methods. Although the model based on parameter obtained by the genetic algorithm shows a better fit when its output response is compared with that obtained with the prediction error method.