• DocumentCode
    2327869
  • Title

    Transient stability study using artificial neural networks models of generator, excitation system, governor

  • Author

    Qian, Ai ; Shande, Shen ; Shouzhen, Zhu

  • Author_Institution
    Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
  • Volume
    2
  • fYear
    1998
  • fDate
    18-21 Aug 1998
  • Firstpage
    1331
  • Abstract
    In this paper, the power system models established by artificial neural networks (ANNs) including generator, excitation system and governor are presented. Meanwhile, the three parts of the generation unit are connected together as a detail model. Furthermore, the detail model is written into power system network equations and the power system transient process is calculated using them. The calculation results demonstrate that artificial neural network models can give a precise description of a generator´s transient processes
  • Keywords
    control system analysis computing; electric generators; electric machine analysis computing; exciters; machine theory; neural nets; power system analysis computing; power system transient stability; artificial neural networks; computer simulation; excitation system; generator; governor; network equations; power system models; power system transient process; Artificial neural networks; Character generation; Equations; Neurons; Power generation; Power system analysis computing; Power system modeling; Power system stability; Power system transients; Recurrent neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-4754-4
  • Type

    conf

  • DOI
    10.1109/ICPST.1998.729302
  • Filename
    729302