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Bayesian network application for the risk assessment of existing energy production units

Author

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  • Sýkora, Miroslav
  • Marková, Jana
  • Diamantidis, Dimitris

Abstract

The assessment of existing infrastructures in the energy sector is of great economic significance worldwide. Fossil power stations are reaching their design service life and rational decisions concerning extensions of service life, maintenance and replacements of devices should be based on updated information of the actual conditions of the energy devices and their components, and on cost-benefit analysis using risk analysis and probabilistic optimisation procedures.

Suggested Citation

  • Sýkora, Miroslav & Marková, Jana & Diamantidis, Dimitris, 2018. "Bayesian network application for the risk assessment of existing energy production units," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 312-320.
    • Handle: RePEc:eee:reensy:v:169:y:2018:i:c:p:312-320
    DOI: 10.1016/j.ress.2017.09.006
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    References listed on IDEAS

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    1. Maes, Marc A. & Faber, Michael H., 2006. "Bayesian framework for managing preferences in decision-making," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 556-569.
    2. Youyuan Wang & Senlian Gong & Stanislaw Grzybowski, 2011. "Reliability Evaluation Method for Oil–Paper Insulation in Power Transformers," Energies, MDPI, vol. 4(9), pages 1-14, September.
    3. Kim, Man Cheol & Seong, Poong Hyun, 2006. "A computational method for probabilistic safety assessment of I&C systems and human operators in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 580-593.
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    Cited by:

    1. Zhou, Jing & Liu, Yu & Liang, Decui & Tang, Maochun, 2023. "A new risk analysis approach to seek best production action during new product introduction," International Journal of Production Economics, Elsevier, vol. 262(C).
    2. Pan, Xing & Zuo, Dujun & Zhang, Wenjin & Hu, Lunhu & Wang, Huixiong & Jiang, Jing, 2021. "Research on Human Error Risk Evaluation Using Extended Bayesian Networks with Hybrid Data," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    3. Zhou, Daoqing & He, Jingjing & Du, Yi-Mu & Sun, C.P. & Guan, Xuefei, 2021. "Probabilistic information fusion with point, moment and interval data in reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    4. Wu, Xingguang & Huang, Huirong & Xie, Jianyu & Lu, Meixing & Wang, Shaobo & Li, Wang & Huang, Yixuan & Yu, Weichao & Sun, Xiaobo, 2023. "A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    5. Quintanar-Gago, David A. & Nelson, Pamela F. & Díaz-Sánchez, à ngeles & Boldrick, Michael S., 2021. "Assessment of steam turbine blade failure and damage mechanisms using a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    6. Wang, Fan & Li, Heng & Dong, Chao & Ding, Lieyun, 2019. "Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 191(C).

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