• DocumentCode
    3478226
  • Title

    A reinforcement learning approach to STATCOM controller

  • Author

    Guo, H.X. ; Liu, Y.Q. ; Wu, J. ; Yang, J.M.

  • Author_Institution
    Electr. Power Coll., South China Univ. of Technol., China
  • Volume
    2
  • fYear
    2004
  • fDate
    5-8 April 2004
  • Firstpage
    638
  • Abstract
    The advanced static synchronous compensator (STATCOM) is a device that can provide reactive support to bus voltage. A novel control scheme based on reinforcement learning algorithm for the STATCOM is presented in this paper. Design of STATCOM controller presented does not depend on structure and parameters of power system. The adaptive heuristic critic algorithm is adopted in this paper and the parameter of the controller are updating by given reinforcement signal of system. Only local information is required. A simulation example of single-machine infinite power system is given, and the result shows the effectiveness on maintaining voltage and preventing voltage collapse.
  • Keywords
    learning (artificial intelligence); power system control; power system dynamic stability; power system simulation; static VAr compensators; STATCOM controller; adaptive heuristic critic algorithm; bus voltage; reinforcement learning algorithm; reinforcement signal; single-machine infinite power system; static synchronous compensator; voltage collapse prevention; voltage stability; Automatic voltage control; Control systems; Learning; Power system dynamics; Power system modeling; Power system reliability; Power system simulation; Power system stability; Power system transients; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation, Restructuring and Power Technologies, 2004. (DRPT 2004). Proceedings of the 2004 IEEE International Conference on
  • Print_ISBN
    0-7803-8237-4
  • Type

    conf

  • DOI
    10.1109/DRPT.2004.1338061
  • Filename
    1338061