• DocumentCode
    3357925
  • Title

    Notice of Retraction
    Reliability Analysis of transformer Based on FTA And Mente Carlo Method

  • Author

    Liu Shuping ; Han Zhengqing

  • Author_Institution
    Sch. of Electr. Eng., Southwest Jiaotong Univ., Chengdu
  • fYear
    2009
  • fDate
    27-31 March 2009
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Notice of Retraction

    After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

    We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

    The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

    Considering the fact that transformer is void of reliability data, fault tree analysis (FTA) and Monte Carlo algorithm are combined in this paper to analyze the reliability of transformer. Fault trees are built. By using the fault tree, Mente carlo is applied to quantitatively analyze the model. Then the reliability index and cell importance parameter help to find out the weak link of the system. Combination of the above two methods offers a practical method for the reliability analysis of transformer.
  • Keywords
    Monte Carlo methods; fault trees; power system reliability; power transformers; FTA; Monte Carlo method; fault tree analysis; power system reliability analysis; transformer; Algorithm design and analysis; Computational modeling; Failure analysis; Fault trees; Oil insulation; Power system reliability; Power system simulation; Power transformer insulation; Sampling methods; US Department of Transportation;
  • 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
  • Type

    conf

  • DOI
    10.1109/APPEEC.2009.4918645
  • Filename
    4918645