• DocumentCode
    3470901
  • Title

    Power transmission network vulnerable region identifying based on complex network theory

  • Author

    Zhao, Hongshan ; Zhang, Chao ; Ren, Hui

  • Author_Institution
    Dept. of Electr. Eng., North China Electr. Power Univ., Baoding
  • fYear
    2008
  • fDate
    6-9 April 2008
  • Firstpage
    1082
  • Lastpage
    1085
  • Abstract
    Complex network theory is applied to study the inherent vulnerability of power transmission grid under cascading failures. It introduces the complex analysis model and some basic conceptions of network characteristic parameters and its algorithm to calculating network efficiency, then it applies proposed algorithm to analyze the complex characteristics of power grid while occurring the cascading failures triggered by link failures, and qualitatively analyzes the resistible ability of power grid in case change of topological structure. Taking advantage of qualitative simulating results, we may determine the vulnerable regions which affect the performance of power transmission network.
  • Keywords
    power grids; transmission networks; cascading failures; complex analysis model; complex network theory; inherent power grid vulnerability; network efficiency; power transmission grid; topological structure; vulnerable power transmission network regions; Algorithm design and analysis; Complex networks; Failure analysis; Large-scale systems; Power grids; Power system dynamics; Power system faults; Power system protection; Power system simulation; Power transmission; Cascading failures; Complex network theory; Power transmission grid; Topological analysis; Vulnerable regions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
  • Conference_Location
    Nanjuing
  • Print_ISBN
    978-7-900714-13-8
  • Electronic_ISBN
    978-7-900714-13-8
  • Type

    conf

  • DOI
    10.1109/DRPT.2008.4523568
  • Filename
    4523568