DocumentCode :
823964
Title :
Optimal design of power-system stabilizers using particle swarm optimization
Author :
Abido, M.A.
Author_Institution :
Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
Volume :
17
Issue :
3
fYear :
2002
fDate :
9/1/2002 12:00:00 AM
Firstpage :
406
Lastpage :
413
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 a particle-swarm-optimization (PSO) technique to search for optimal settings of PSS parameters. Two eigenvalue-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 and 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 is demonstrated.
Keywords :
control system analysis; control system synthesis; damping; eigenvalues and eigenfunctions; evolutionary computation; optimal control; optimisation; power system control; power system dynamic stability; robust control; PSS parameters setting; control design; dynamic stability; eigenvalue analysis; eigenvalue-based objective functions; electromechanical modes damping; evolutionary algorithm-based approach; loading conditions; multimachine power systems; multimachine power-system stabilizers; nonlinear simulation; power system stabilizer design optimisation; robustness; Algorithm design and analysis; Analytical models; Damping; Eigenvalues and eigenfunctions; Evolutionary computation; Particle swarm optimization; Power system analysis computing; Power system simulation; Robustness; System testing;
fLanguage :
English
Journal_Title :
Energy Conversion, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8969
Type :
jour
DOI :
10.1109/TEC.2002.801992
Filename :
1033970
Link To Document :
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