• DocumentCode
    1361585
  • Title

    Operational reliability assessment of power systems considering condition-dependent failure rate

  • Author

    Sun, Yue ; Wang, Peng ; Cheng, Lin ; Liu, Hongying

  • Author_Institution
    Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
  • Volume
    4
  • Issue
    1
  • fYear
    2010
  • fDate
    1/1/2010 12:00:00 AM
  • Firstpage
    60
  • Lastpage
    72
  • Abstract
    Failure rate of a system component is usually assumed to be constant in conventional reliability evaluation of power systems. It has been realised from the real-time operation that a component will experience more failures during heavy loading condition than those during light loading condition, which means that the failure rate of a component in real-time operation is not constant and varies with loading condition. In order to evaluate system operational reliability related to load condition, the factors affected condition-dependent failure rate (CDFR) are investigated and a basic CDFR model is proposed in this study. In predictive operational reliability study, equipment loading condition for a given load period is determined using AC power flow based on the corresponding load level with considering load uncertainty. A four-state model has been proposed to represent a system component. The equations for determining the probability of each state for the four-state model have been derived. A technique based on these equations and models has been developed to evaluate operational and annual reliability indices of components, load points and system. The IEEE-RTS has been analysed to illustrate the proposed models and technique.
  • Keywords
    load (electric); power system management; power system measurement; power system reliability; AC power flow; condition-dependent failure rate; equipment loading condition; four-state model; load points; load uncertainty; operational reliability assessment; power systems; reliability indices; system component;
  • fLanguage
    English
  • Journal_Title
    Generation, Transmission & Distribution, IET
  • Publisher
    iet
  • ISSN
    1751-8687
  • Type

    jour

  • DOI
    10.1049/iet-gtd.2009.0006
  • Filename
    5357361