• DocumentCode
    1098682
  • Title

    Power System Risk Assessment Using a Hybrid Method of Fuzzy Set and Monte Carlo Simulation

  • Author

    Li, Wenyuan ; Zhou, Jiaqi ; Xie, Kaigui ; Xiong, Xiaofu

  • Author_Institution
    British Columbia Transm. Corp., Vancouver
  • Volume
    23
  • Issue
    2
  • fYear
    2008
  • fDate
    5/1/2008 12:00:00 AM
  • Firstpage
    336
  • Lastpage
    343
  • Abstract
    This paper presents fuzzy-probabilistic modeling techniques for system component outage parameters and load curves. The fuzzy membership functions of system component outage parameters are developed using statistical records, whereas the system load is modeled using a combined fuzzy and probabilistic representation. Based on the fuzzy-probabilistic models, a hybrid method of fuzzy set and Monte Carlo simulation for power system risk assessment is proposed to capture both randomness and fuzziness of loads and component outage parameters. An actual example using a regional system at the British Columbia Transmission Corpoation is given to demonstrate the application of the presented fuzzy-probabilistic models for system parameters and new system risk evaluation method.
  • Keywords
    Monte Carlo methods; fuzzy set theory; power system reliability; risk management; British Columbia Transmission Corpoation; Monte Carlo simulation; fuzzy membership functions; fuzzy set theory; fuzzy-probabilistic modeling techniques; hybrid method; load curves; power system risk assessment; probabilistic representation; statistical records; system component outage parameters; system risk evaluation method; Fuzzy model; Monte Carlo simulation; power systems; reliability; risk evaluation;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2008.919201
  • Filename
    4470565