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.
| Original language | English |
|---|---|
| Pages (from-to) | 406-413 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Energy Conversion |
| Volume | 17 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 2002 |
Bibliographical note
Funding Information:Manuscript received August 9, 2000; revised December 4, 2001. This work was supported by King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. M. A. Abido is with the Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia (e-mail: [email protected]). Publisher Item Identifier 10.1109/TEC.2002.801992.
Keywords
- Dynamic stability
- PSS design
- Particle swarm optimization
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering