Improved particle swarm optimization with disturbance term for multi-machine power system stabilizer design

Mahdiyeh Eslami, Hussain Shareef, Azah Mohamed, Mohammad Khajehzadeh

Research output: Contribution to journalArticlepeer-review

Abstract

Power system stabilizers (PSSs) are the most well-known and effective tools to damp power system oscillation caused by disturbances. To gain a good transient response, the design methodology of the PSS is quite important. The tuning of the PSS parameters for a multi-machine power system is usually formulated as an objective function with constraints consisting of the damping factor and damping ratio. The present paper, discusses a novel hybrid optimization technique to solve this kind of problem. A modified velocity updating formula of the particle swarm optimization (PSO) algorithm is declared. The addition of the disturbance term based on existing structure effectively mends the defects. The convergence of the improved algorithm is analyzed. Maximizations of the damping factor and the damping ratio of power system modes are taken as the goals or two objective functions, when designing the PSS parameters. The New England 16-unit 68-bus standard power system, under various system configurations and operation conditions, is employed to illustrate the performance of the proposed method. Eigenvalue analysis and nonlinear time domain simulation results demonstrate the effectiveness of the proposed algorithm. The results are very encouraging and suggest that the proposed PSO with the disturbance term (PSO-DT) algorithm is very efficient in damping low frequency oscillations and improving the stability of the power system. Simulation results demonstrated that the improved algorithm has a better performance than the standard one.

Original languageEnglish
Pages (from-to)5768-5779
Number of pages12
JournalJournal of Applied Sciences Research
Volume6
Issue number12
Publication statusPublished - Dec 2010
Externally publishedYes

Keywords

  • Disturbance term
  • Multi-objective optimization
  • PSS design
  • Particle swarm optimization

ASJC Scopus subject areas

  • General

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