• DocumentCode
    87145
  • Title

    Mode matching pursuit for estimating dominant modes in bulk power grid

  • Author

    Tao Jiang ; Hongjie Jia ; Jinli Zhao ; Ledwich, Gerard ; Dan Wang ; Jinan Zhang ; Lulu Qiu

  • Author_Institution
    Key Lab. of Smart Grid of Minist. of Educ., Tianjin Univ., Tianjin, China
  • Volume
    8
  • Issue
    10
  • fYear
    2014
  • fDate
    Oct-14
  • Firstpage
    1677
  • Lastpage
    1686
  • Abstract
    This study presents a general approach to identify dominant oscillation modes in bulk power system by using wide-area measurement system. To automatically identify the dominant modes without artificial participation, spectral characteristic of power system oscillation mode is applied to distinguish electromechanical oscillation modes which are calculated by stochastic subspace method, and a proposed mode matching pursuit is adopted to discriminate the dominant modes from the trivial modes, then stepwise-refinement scheme is developed to remove outliers of the dominant modes and the highly accurate dominant modes of identification are obtained. The method is implemented on the dominant modes of China Southern Power Grid which is one of the largest AC/DC paralleling grids in the world. Simulation data and field-measurement data are used to demonstrate high accuracy and better robustness of the dominant modes identification approach.
  • Keywords
    AC-DC power convertors; iterative methods; oscillations; power grids; power system measurement; power system parameter estimation; power system stability; stochastic processes; AC-DC paralleling grids; bulk power grid; dominant oscillation mode identification; electromechanical oscillation mode; mode matching pursuit; power system oscillation mode; stepwise reflnement scheme; stochastic subspace method; wide area measurement system;
  • fLanguage
    English
  • Journal_Title
    Generation, Transmission & Distribution, IET
  • Publisher
    iet
  • ISSN
    1751-8687
  • Type

    jour

  • DOI
    10.1049/iet-gtd.2013.0730
  • Filename
    6910356