• DocumentCode
    635979
  • Title

    Adaptive rule-base fuzzy power system stabilizer for a multi-machine system

  • Author

    Hussein, T. ; Shamekh, A.

  • Author_Institution
    Electr. & Electron. Eng. Dept., Univ. of Benghazi, Benghazi, Libya
  • fYear
    2013
  • fDate
    25-28 June 2013
  • Firstpage
    1514
  • Lastpage
    1519
  • Abstract
    A new type of power system stabilizer based on fuzzy set theory is proposed to improve the dynamic performance of a multi-machine power system. To have good damping characteristics over a wide range of operating conditions, speed deviation and it is derivative of a machine are chosen as the input signals to the fuzzy stabilizer on that particular machine. The paper proposes Adaptation to Rule bases of the designed Fuzzy logic Power System Stabilizer (ARFPSS) to damp inter-area modes of oscillation. The proposed technique is derived as a direct fuzzy logic power system stabilizer. However, the integration steps are restricted to be in the linear area to avoid the problems that may result when the solution becomes saturated. The article shows that ARFPSS is more efficient than the Conventional Power System stabilizers (CPSS´s) due to its ability to cope with oscillations at different operating points and different fault locations. A bench mark simulation problem of a 4-machine 2-area power system is exploited to demonstrate the performance of the proposed controller compared with standard techniques.
  • Keywords
    adaptive control; feedback; fuzzy control; fuzzy set theory; genetic algorithms; integration; nonlinear control systems; power system stability; 4-machine 2-area power system; ARFPSS technique; CPSS; adaptive rule-base; conventional power system stabilizer; damping characteristics; fuzzy power system stabilizer; fuzzy set theory; integration steps; machine derivative; multimachine system; nonlinear system; speed deviation; Fuzzy logic; Generators; Mathematical model; Oscillators; Power system stability; Rotors; Vectors; Adaptive control; Direct integration algorithm; Fuzzy logic control; Power system stabilizer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control & Automation (MED), 2013 21st Mediterranean Conference on
  • Conference_Location
    Chania
  • Print_ISBN
    978-1-4799-0995-7
  • Type

    conf

  • DOI
    10.1109/MED.2013.6608922
  • Filename
    6608922