Title :
Particle swarm optimization for multimachine power system stabilizer design
Author_Institution :
Electr. Eng. Dept., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
Abstract :
In this paper, a novel evolutionary algorithm based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. The proposed approach develops and employs 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 and loading conditions is tested and examined. Eigenvalue analysis and nonlinear simulation results show the effectiveness of the proposed PSOPSSs to damp out the electromechanical oscillations and work effectively over a wide range of loading conditions.
Keywords :
control system analysis; control system synthesis; damping; eigenvalues and eigenfunctions; evolutionary computation; optimal control; power system control; power system dynamic stability; robust control; PSS parameters optimal settings; control design; dynamic stability; eigenvalue-based objective functions; electromechanical modes damping; electromechanical oscillations; evolutionary algorithm; loading conditions; multimachine power system stabilizer design; nonlinear simulation; particle swarm optimization; robustness; Algorithm design and analysis; Damping; Design optimization; Evolutionary computation; Particle swarm optimization; Power system dynamics; Power system modeling; Power system simulation; Power system stability; Power systems;
Conference_Titel :
Power Engineering Society Summer Meeting, 2001
Conference_Location :
Vancouver, BC, Canada
Print_ISBN :
0-7803-7173-9
DOI :
10.1109/PESS.2001.970272