• DocumentCode
    1558575
  • Title

    Stator Insulation Degradation Test Uses ASD Switching Frequency

  • Author

    Kueck, John D. ; Haynes, Howard D. ; Staunton, Robert H.

  • Volume
    22
  • Issue
    1
  • fYear
    2002
  • Firstpage
    7
  • Lastpage
    11
  • Abstract
    Two sequential self-organizing hierarchical neural network (SHNN) models are utilized to estimate power system voltage stability. The first SHNN determines whether the power system is dynamically stable or not. The second one is used for the dynamically stable system to estimate the voltage magnitudes at all PQ buses. Tests results at different loading conditions for two test systems, WSCC nine-bus system and New England 39-bus system, are reported.
  • Keywords
    control system analysis computing; power system analysis computing; power system control; power system dynamic stability; self-organising feature maps; PQ bus voltage magnitudes; computer simulation; control simulation; dynamic stability; loading conditions; power system voltage stability estimation; sequential self-organizing hierarchical neural network models; Degradation; Insulation testing; Power system dynamics; Power system modeling; Power system stability; Stators; Switching frequency; System testing; Variable speed drives; Voltage;
  • fLanguage
    English
  • Journal_Title
    Power Engineering Review, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1724
  • Type

    jour

  • DOI
    10.1109/39.975659
  • Filename
    975659