• DocumentCode
    3252310
  • Title

    Application of Bayesian Networks for maintenance and risk modelling

  • Author

    Sand, Kjell ; Aupied, Jean ; Spruyt, Florent

  • Author_Institution
    Energy Syst. Dept., SINTEF Energy Res., Trondheim, Norway
  • fYear
    2010
  • fDate
    14-17 June 2010
  • Firstpage
    530
  • Lastpage
    535
  • Abstract
    In an ageing electricity distribution infrastructure as found in many countries, measuring the impact of maintenance is becoming increasingly important. A realistic maintenance impact model will permit to improve existing maintenance strategies. This paper addresses this issue from a risk management perspective. The first part gives a short review of some of the existing mathematical models that are developed to assess the effect of the maintenance on component reliability. The second part presents the possibility of applying Bayesian Networks to model maintenance strategies´ impact on utility risk. A practical example dealing with power transformer tap-changers is presented. Experience shows that the approach have the capacity of providing decision makers with a holistic overview of the problem they are facing as well as with quantitative model results.
  • Keywords
    Bayes methods; decision making; maintenance engineering; power distribution planning; power distribution reliability; risk analysis; Bayesian networks; component reliability; decision making; electricity distribution infrastructure ageing; maintenance impact modelling; maintenance strategies; risk management; Aging; Asset management; Bayesian methods; Electric variables measurement; Energy measurement; Maintenance; Mathematical model; Portfolios; Power transformers; Risk management; Bayesian Networks maintenance; asset management; modelling; on-load-tap-changers reliability; risk;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5720-5
  • Type

    conf

  • DOI
    10.1109/PMAPS.2010.5528936
  • Filename
    5528936