• DocumentCode
    791713
  • Title

    Coordination control of ULTC transformer and STATCOM based on an artificial neural network

  • Author

    Kim, Gwang Won ; Lee, Kwang Y.

  • Author_Institution
    Sch. of Electr. Eng., Univ. of Ulsan, South Korea
  • Volume
    20
  • Issue
    2
  • fYear
    2005
  • fDate
    5/1/2005 12:00:00 AM
  • Firstpage
    580
  • Lastpage
    586
  • Abstract
    This paper presents an artificial neural network (ANN)-based coordination control scheme for under load tap changing (ULTC) transformer and STATCOM. The objective of the coordination controller is to minimize both the amount of tap changes of the transformer and STATCOM output while maintaining an acceptable voltage magnitude at the substation bus. The coordination controller is designed to substitute for a classical ULTC mechanism by utilizing active and reactive powers, tap position, and STATCOM output. A competitive ANN is used as a classifier for tap positions and trained by a proposed iterative condensed nearest neighbor (ICNN) rule.
  • Keywords
    control system synthesis; neurocontrollers; on load tap changers; reactive power; static VAr compensators; substations; voltage control; STATCOM; ULTC transformer coordination control; active power; artificial neural network; iterative condensed nearest neighbor rule; reactive power; substation bus; under load tap changing; voltage regulation; Artificial neural networks; Automatic voltage control; Capacitors; Flexible AC transmission systems; Nearest neighbor searches; Neural networks; Power electronics; Reactive power control; Substations; Voltage control; Artificial neural network (ANN); STATCOM; ULTC transformer; condensed nearest neighbor rule; coordination control; voltage regulation;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2005.846205
  • Filename
    1425548