• DocumentCode
    1994513
  • Title

    Power system load dynamic characteristics identification based on Elman neural network

  • Author

    Liao, Bin ; Ma, Rui

  • Author_Institution
    Inst. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
  • fYear
    2011
  • fDate
    16-18 Sept. 2011
  • Firstpage
    4010
  • Lastpage
    4013
  • Abstract
    This paper analyzed and expounded the defects in the BP neural network is used to identify dynamic characteristics of power system load, this article introduces one kind has the function of dynamic feedback in Elman neural network load model, and this model has simple structure, convenient, few parameters, application of dynamic characteristics described and comprehensive load identification, so this article discusses the application of Elman neural network identification the dynamic characteristic of electrical load, and analyses identification process problems should be paid attentioned .The application shows that the identification method is useful and practical.
  • Keywords
    load (electric); neural nets; power engineering computing; power system simulation; BP neural network; Elman neural network; dynamic feedback; power system load dynamic characteristics identification; Analytical models; Heuristic algorithms; Load modeling; Neurons; Power system dynamics; Power system stability; Training; Elman neural network; load dynamic characteristics; power system; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2011 International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4244-8162-0
  • Type

    conf

  • DOI
    10.1109/ICECENG.2011.6058050
  • Filename
    6058050