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
Link To Document :
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