• DocumentCode
    1737441
  • Title

    Two separate continually online trained neurocontrollers for excitation and turbine control of a turbogenerator

  • Author

    Venayagamoorthy, Ganesh K. ; Harley, Ronald G.

  • Author_Institution
    Dept. of Electron. Eng., ML Sultan Technikon, Durban, South Africa
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1263
  • Abstract
    This paper presents the design of two separate continually online trained (GOT) artificial neural network (ANN) controllers for excitation and turbine control of a turbogenerator connected to the infinite bus through a transmission line. These neurocontrollers augment/replace the conventional automatic voltage regulator and the turbine governor of a generator. A third COT ANN is used to identify the complex nonlinear dynamics of the power system. Results are presented to show that the two COT ANN controllers can control turbogenerators under steady state as well as transient conditions and thus allow turbogenerators to operate more closely to their steady state stability limits
  • Keywords
    learning (artificial intelligence); machine control; neurocontrollers; nonlinear dynamical systems; turbines; turbogenerators; artificial neural network controllers; automatic voltage regulator; continually online trained neurocontrollers; excitation; steady state; transient conditions; transmission line; turbine control; turbogenerator; Artificial neural networks; Automatic control; Neurocontrollers; Power system dynamics; Power system stability; Power system transients; Power transmission lines; Steady-state; Turbines; Turbogenerators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
  • Conference_Location
    Rome
  • ISSN
    0197-2618
  • Print_ISBN
    0-7803-6401-5
  • Type

    conf

  • DOI
    10.1109/IAS.2000.882046
  • Filename
    882046