• DocumentCode
    3260208
  • Title

    Neural network excitation control system for transient stability analysis of power system

  • Author

    Lachman, T. ; Mohamad, T.R.

  • Author_Institution
    Fac. of Eng., Archit. & Built Environ., UCSI Univ., Kuala Lumpur, Malaysia
  • fYear
    2009
  • fDate
    23-26 Jan. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents artificial neural network (ANN) based controller model to simulate the automatic voltage regulator (AVR) response for the transient stability analysis. Two different models are simulated considering single machine connected to an infinite bus (SMIB) to check the response of NN behaviour with conventional controller. Based on simulation results, it is found that NN controller gives better response by removing oscillations, while the both conventional AVR controllers show ripple and oscillations before reaching the steady state condition. The development of a neural network based software controller to simulate the automatic voltage regulator behavior for improving transient stability of power system.
  • Keywords
    neurocontrollers; power system control; power system transient stability; voltage control; voltage regulators; AVR controllers; artificial neural network; automatic voltage regulator; infinite bus; neural network excitation control system; power system; transient stability analysis; Control systems; Neural networks; Power system analysis computing; Power system control; Power system simulation; Power system stability; Power system transients; Power systems; Stability analysis; Transient analysis; ANN; Control System; Power System; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2009 - 2009 IEEE Region 10 Conference
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-4546-2
  • Electronic_ISBN
    978-1-4244-4547-9
  • Type

    conf

  • DOI
    10.1109/TENCON.2009.5396242
  • Filename
    5396242