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.
| Original language | English |
|---|---|
| Pages (from-to) | 53 |
| Number of pages | 1 |
| Journal | IEEE Power Engineering Review |
| Volume | 22 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2002 |
Keywords
- Algorithm design and analysis
- Damping
- Eigenvalues and eigenfunctions
- Evolutionary computation
- PSS design
- Particle swarm optimization
- Power system analysis computing
- Power system simulation
- Power systems
- Robustness
- System testing
- dynamic stability
- particle swarm optimization
ASJC Scopus subject areas
- Electrical and Electronic Engineering
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