Original Articles
Xiuge Zhang, Ye Ren and Qizhou
Abstract
The parameters of synchronous generators are the basis of power system analysis and operating control. Parameters identification of synchronous generator plays a key role for the power system stability analysis. In this paper, a small population-based particle swarm optimization (SPPSO) approach is used to acquire synchronous generator on-line model quickly and accurately. In the proposed approaches, three operations are introduced to improve the performance of the algorithm, namely mutation operation, DE-acceleration operation and migration operation. Furthermore, the synchronous generator practical model and the PMU data are adopted. The simulation results of the model obtained by SPPSO have been compared with hybrid genetic algorithm and PSO. The SPPSO algorithm shows better performance on the convergence as well as computation time and effort.