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Application of Bayesian networks for risk analysis of MV air insulated switch operation

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  • NordgÃ¥rd, D.E.
  • Sand, K.

Abstract

Electricity distribution companies regard risk-based approaches as a good philosophy to address their asset management challenges, and there is an increasing trend on developing methods to support decisions where different aspects of risks are taken into consideration. This paper describes a methodology for application of Bayesian networks for risk analysis in electricity distribution system maintenance management. The methodology is used on a case analysing safety risk related to operation of MV air insulated switches. The paper summarises some challenges and benefits of using Bayesian networks as a part of distribution system maintenance management.

Suggested Citation

  • NordgÃ¥rd, D.E. & Sand, K., 2010. "Application of Bayesian networks for risk analysis of MV air insulated switch operation," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1358-1366.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:12:p:1358-1366
    DOI: 10.1016/j.ress.2010.06.012
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    References listed on IDEAS

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    1. Jones, B. & Jenkinson, I. & Yang, Z. & Wang, J., 2010. "The use of Bayesian network modelling for maintenance planning in a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 267-277.
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    Cited by:

    1. Jiansong Wu & Weipeng Fang & Xing Tong & Shuaiqi Yuan & Weiqi Guo, 2019. "Bayesian analysis of school bus accidents: a case study of China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(3), pages 463-483, February.
    2. Catrinu, M.D. & Nordgård, D.E., 2011. "Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management," Reliability Engineering and System Safety, Elsevier, vol. 96(6), pages 663-670.
    3. Baoping Cai & Yonghong Liu & Zengkai Liu & Xiaojie Tian & Yanzhen Zhang & Renjie Ji, 2013. "Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1293-1311, July.
    4. Ali Namazian & Siamak Haji Yakhchali & Vahidreza Yousefi & Jolanta Tamošaitienė, 2019. "Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk," IJERPH, MDPI, vol. 16(24), pages 1-19, December.
    5. Edson Ruschel & Eduardo Alves Portela Santos & Eduardo de Freitas Rocha Loures, 2020. "Establishment of maintenance inspection intervals: an application of process mining techniques in manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 53-72, January.

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