• DocumentCode
    2641877
  • Title

    Adaptive critic designs based coupled neurocontrollers for a static compensator

  • Author

    Mohagheghi, Salman ; Venayagamoorthy, Ganesh K. ; Harley, Ronald G.

  • Author_Institution
    Intelligent Power Infrastructure Consortium (IPIC) in the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, 30332-0250 USA
  • fYear
    2006
  • fDate
    4-6 Oct. 2006
  • Firstpage
    470
  • Lastpage
    475
  • Abstract
    A novel nonlinear optimal neurocontroller for a static compensator (STATCOM) connected to a power system, using artificial neural networks, is presented in this paper. The heuristic dynamic programming (HDP) method, a member of the adaptive critic designs (ACD) family, is used for the design of the STATCOM neurocontroller. The proposed controller is a nonlinear optimal controller that provides coupled control for the line voltage and the dc link voltage regulation loops of the STATCOM. An action dependent approach is used, in which the controller is independent of a model of the network. Moreover, a proportional-integrator approach allows the neurocontroller to deal with the actual signals rather than the deviations. Simulation results are provided to show that the proposed ACD based neurocontroller is more effective in controlling the STATCOM compared to finely tuned conventional PI controllers.
  • Keywords
    Artificial neural networks; Automatic voltage control; Couplings; Dynamic programming; Neurocontrollers; Optimal control; Power system dynamics; Power systems; STATCOM; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
  • Conference_Location
    Munich, Germany
  • Print_ISBN
    0-7803-9797-5
  • Electronic_ISBN
    0-7803-9797-5
  • Type

    conf

  • DOI
    10.1109/CACSD-CCA-ISIC.2006.4776691
  • Filename
    4776691