Power System Stabilizer Design for Multi-machine Power System Using Genetic Algorithm

Abinet Tesfaye, Dereje Shiferaw, J.H. Zhang, D.H. Zheng

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper uses genetic algorithm (GA) framework integrated with the classical Lyapunov’s parameter optimization method employing an Integral of Squared Error (ISE) criterion to optimally tune the parameters of the power system stabilizers (PSSs) for a multi-machine system, consisting of three machines and ten interconnected buses, which is taken from the national electric power grid of Ethiopia. The issue of optimally tuning the parameters of the PSS is converted into an optimization problem that is solved via the GA algorithm. Within the GA process, a potential solution–the PSS parameter setting–is coded as an individual, which is part of a population of such potential solutions randomly generated, and by applying the survival of the fitness principle based on each individual’s fitness with respect to the objective, a sound basis for finding the best individual, ie global optimum solution, is created. Simulation results are presented to show the effectiveness of the proposed approach, for various system loading conditions and other disturbances such as perturbation in mechanical torque inputs to the machines, and have been performed with satisfactory results with the design and integration of PSS to the power system investigated in this paper.
Original languageEnglish
Number of pages9
JournalInternational Journal of Science and Engineering Applications
Volume5
Issue number3
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Dynamic stability
  • Electromechanical oscillations
  • Genetic algorithm (GA)
  • Integral of Squared Error (ISE)
  • Lyapunov equation
  • Power systems
  • Power system stabilizers (PSSs)

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