On-Line Parameters Identification for Excitation System Based on Small Population-Based Particle Swarm Optimization

Abstract:

Parameters identification of excitation system 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 excitation system 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 BPA-FV practical model and the PMU data are adopted. The simulation results of the model obtained by SPPSO have been compared with that of the model obtained by other approach in literature and our reformulations. The SPPSO algorithm shows better performance on the convergence as well as computation time and effort.

• Periodical: Applied Mechanics and Materials (Volumes 291-294)
• Pages: 2159-2163
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.291-294.2159
• Online since: February 2013
• Authors: Li Fang Lu, Huan Qi
• Keywords: Excitation System, Parameter Identification, PMU Data, SPPSO

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