• DocumentCode
    2387206
  • Title

    Improvement of order reduction approach for special modes in power system small signal stability analysis

  • Author

    Liu, Chang ; Wang, Kewen ; Cui, Wei ; Liu, Wei

  • Author_Institution
    Sch. of Electr. Eng., Zhengzhou Univ., Zhengzhou, China
  • fYear
    2012
  • fDate
    19-20 May 2012
  • Firstpage
    572
  • Lastpage
    575
  • Abstract
    Precise results of eigenvalues can be obtained in order reduction approach for special modes. To improve calculation efficiency, the order reduction approach is analyzed in this paper. In the process of order reduction, every set made up of retained state variables is shared by different modes, which reduces calculation amount. Based on real number expression of complex matrix, the expression of outer iteration is reformed. Factor table formed by the sequence elimination can be used to solve inverse matrix quickly. The function of parallel computation in Open Multi-Processing is introduced to accelerate calculation on multi-core computers. The improved effect of retained sets, sparse technique and parallel computation is tested and analyzed by a 105-machine system.
  • Keywords
    eigenvalues and eigenfunctions; matrix algebra; parallel processing; power engineering computing; power system stability; reduced order systems; eigenvalues; factor table; inverse matrix; multicore computers; open multiprocessing; order reduction; parallel computation; power system; sequence elimination; small signal stability analysis; Computers; Eigenvalues and eigenfunctions; Equations; Generators; Power system stability; Sparse matrices; Stability analysis; order reduction; parallel computation; power system; small signal stability; sparse technique;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2012 International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4673-0198-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2012.6223062
  • Filename
    6223062