• DocumentCode
    3362753
  • Title

    Transient Stability Analysis of Large-Scale Power Systems Based on Reduce Feature

  • Author

    Sun, Shuangxue ; Li, Chan ; Zai, Xiwei ; Yang, Xiaoguang ; Liu, Yingtong ; Zhou, Xiaoxia ; Fan, Youping

  • Author_Institution
    Fac. of Electr. Eng., Univ. of Wuhan, Wuhan
  • fYear
    2009
  • fDate
    27-31 March 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents an effective data analysis approach for character data compression from bi-direction. At the first step of the algorithm, basing on the theory of component analysis, the paper adopt a principal component analysis approach to reduce the dimension of data horizontally, then after comparison of existing clustering algorithms, put forward an immune clustering algorithm based on similarity measurement of principle component core for vertical reduction by using related mechanism of clone selection as well as immune network self-stabilization in organism natural immune system for reference. Finally, a pattern discrimination model based on a cerebellar model articulation controller neural network was developed. Simulation experiments on the data from the process control field proved the effectiveness of this algorithm.
  • Keywords
    data compression; fault diagnosis; large-scale systems; learning (artificial intelligence); neural nets; pattern clustering; power system analysis computing; power system transient stability; principal component analysis; cerebellar model articulation controller neural network; character data compression; clustering algorithm; component analysis theory; data analysis approach; immune clustering algorithm; large-scale power systems; pattern discrimination model; principal component analysis; transient stability analysis; Bidirectional control; Clustering algorithms; Data analysis; Data compression; Large-scale systems; Power system analysis computing; Power system stability; Power system transients; Stability analysis; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-2486-3
  • Electronic_ISBN
    978-1-4244-2487-0
  • Type

    conf

  • DOI
    10.1109/APPEEC.2009.4918943
  • Filename
    4918943