Title :
Optimal des´ign of Power System Stabilizers Using Particle Swarm Opt´imization
Author_Institution :
King Fahd University of Petroleum and Minerals, Saudi Arabia
fDate :
7/1/2002 12:00:00 AM
Abstract :
In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. The proposed approach employs the particle swarm optimization (PSO) technique to search for optimal settings of PSS parameters. Two elgenvalue-based objective functions to enhance system damping of electromechanical modes are considered. The robustness of the proposed approach to the initial guess is demonstrated. The performance of the proposed PSO-based PSS (PSOPSS) under different disturbances, loading conditions, and system configurations is tested and examined for different multimachine power systems. Eigenvalue analysis and nonlinear simulation results show the effectiveness of the proposed PSOPSSs to damp out the local as well as the interarea modes of oscillations and work effectively over a wide range of loading conditions and system configurations. In addition, the potential and superiority of the proposed approach over the conventional approaches are demonstrated.
Keywords :
Algorithm design and analysis; Damping; Eigenvalues and eigenfunctions; Evolutionary computation; Particle swarm optimization; Power system analysis computing; Power system simulation; Power systems; Robustness; System testing; PSS design; dynamic stability; particle swarm optimization;
Journal_Title :
Power Engineering Review, IEEE
DOI :
10.1109/MPER.2002.4312374