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General Information
    • ISSN: 1793-8236 (Online)
    • Abbreviated Title Int. J. Eng. Technol.
    • Frequency:  Quarterly 
    • DOI: 10.7763/IJET
    • APC: 500 USD
    • Managing Editor: Ms. Isa Yuan 
    • Abstracting/ Indexing:  CNKI,  Google Scholar, Crossref, EBSCO  etc.
    • E-mail: ijet_Editor@126.com
IJET 2010 Vol.2(6): 558-563
doi: 10.7763/IJET.2010.V2.181

PSO Algorithm-Based Optimal Tuning of PSS for Damping Improvement of Power Systems

A. Jalilvand 1 , M. Daviran Keshavarzi 2

  • 1 Electrical Engineering Department, Zanjan University, Zanjan, Iran .M. Daviran Keshavarzi., was with
  • 2 Electrical Engineering Department, Zanjan University, Zanjan, Iran

Abstract

In this paper a method based on the Particle Swarm Optimization (PSO) algorithm is presented for tuning Power System Stabilizer (PSS) parameters. In the proposed method, based on the optimization of a suitable objective function, optimal values for PSS controlling parameters including lead-lag compensator time constants as well as the controller gain are calculated. The employed objective function is the damping ratio of eigenvalues corresponding to system critical modes obtained from the analysis of the linearized model of system around the operating point. Controllable and critical modes of the system are identified using modal controllability and observability criteria. The proposed algorithm is applied to a single machine power system and for various operating conditions. Simulation results prove the capability of the proposed algorithm in damping improvement of power system.

Keywords

  • controllability
  • observability
  • particle swarmoptimization
  • power system stabilizer
  • root locus
181-T295

How to Cite

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A. Jalilvand and M. Daviran Keshavarzi, "PSO Algorithm-Based Optimal Tuning of PSS for Damping Improvement of Power Systems," International Journal of Engineering and Technology, vol. 2, no. 6, pp. 558-563, 2010. https://doi.org/ 10.7763/IJET.2010.V2.181

Copyright & License

Copyright © 2010 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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