• DocumentCode
    2929714
  • Title

    Multi-Uncertainty Evaluation of Failure Probability of Sensitive Equipment Due to Voltage Sag

  • Author

    Liao Xue-Jing ; Sun Xiao-Lu ; Xu Pei-Dong ; Xiao Xian-Yong

  • Author_Institution
    Deyang Electr. Power Bur., Sichuan Province Electr. Power Co., Deyang, China
  • fYear
    2011
  • fDate
    25-28 March 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Serious problem for failure probability evaluation of equipment due to voltage sag is the uncertainties and mathematical expression of influencing factors. The uncertainties contained in voltage sag, equipment voltage tolerance and possible operation state are researched. The intension and extension uncertainties of influencing factors are used to distinguish their property. Stochastic and fuzzy variables are introduced to express intension and extension uncertainties. The mathematical models of influencing factors are established using stochastic and fuzzy models and a multi-uncertainty evaluation model is proposed also. In this method, maximum entropy principle is used to extract the probability distribution of voltage sag intensity and the determination principle of membership function of fuzzy safety event is used to determine the multi-uncertainty evaluation model. As a case study, personal computer is simulated. The simulation results show that this method is correct and viable and it can be easily used in other fields.
  • Keywords
    fuzzy systems; power supply quality; power system faults; stochastic processes; equipment voltage tolerance; failure probability; fuzzy variables; membership function; multi-uncertainty evaluation; probability distribution; sensitive equipment; stochastic variables; voltage sag intensity; Entropy; Mathematical model; Microcomputers; Safety; Stochastic processes; Uncertainty; Voltage fluctuations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
  • Conference_Location
    Wuhan
  • ISSN
    2157-4839
  • Print_ISBN
    978-1-4244-6253-7
  • Type

    conf

  • DOI
    10.1109/APPEEC.2011.5748530
  • Filename
    5748530