• DocumentCode
    2241354
  • Title

    Design and implementation of power system stabilizers based on evolutionary algorithms

  • Author

    Sheetekela, Severus ; Folly, Komla ; Malik, Om P.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Cape Town, Cape Town, South Africa
  • fYear
    2009
  • fDate
    23-25 Sept. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper discusses the design and implementation of power system stabilizers based on newly introduced evolutionary algorithms, namely the population- based incremental learning (PBIL) and the breeder genetic algorithm (BGA) with adaptive mutation. The designed PSSs were implemented on a power system experimental setup and the experimental results are presented in this paper. A conventional power system stabilizer (CPSS) was also designed and implemented for comparison purposes. In total three PSSs were designed and implemented, and their performance compared. It was found that CPSS gives the worst performance and BGA-PSS performs better than the PBIL-PSS for the specific case described in this paper, with the electrical power used as the input to the PSS.
  • Keywords
    evolutionary computation; genetic algorithms; power system stability; breeder genetic algorithm; evolutionary algorithms; population-based incremental learning algorithm; power system stabilizers; Africa; Algorithm design and analysis; Cities and towns; Damping; Evolutionary computation; Frequency; Genetic algorithms; Genetic mutations; Optimal control; Power systems; BGA; PBIL; automatic voltage regulators; genetic algorithm; premature convergence; real — time; stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AFRICON, 2009. AFRICON '09.
  • Conference_Location
    Nairobi
  • Print_ISBN
    978-1-4244-3918-8
  • Electronic_ISBN
    978-1-4244-3919-5
  • Type

    conf

  • DOI
    10.1109/AFRCON.2009.5308124
  • Filename
    5308124