Risk analysis in energy projects using Bayesian networks: A systematic review

• Published in: Energy strategy reviews 2023-05, Vol.47, p.101097, Article 101097
• Main Authors: Gerber Machado, Pedro, de Oliveira Ribeiro, Celma, Oller do Nascimento, Claudio Augusto
• Format: Article
• Language: English
• Subjects: Bayesian networks; Energy systems; Risk analysis; Systematic review
• ISSN: 2211-467X; 2211-467X
• DOI: 10.1016/j.esr.2023.101097

This systematic review summarizes the use of Bayesian networks in assessing risk in the energy sector based on peer-reviewed publications. The interest in risk analysis of the energy sector has increased with the number of energy resources and energy demand due to the need to supply energy with minimized interruptions and avoid hidden costs related to maintenance and recovery from accidents. A Bayesian network is a powerful tool that harmonizes information and expert judgment to evaluate the probability of different scenarios and events, making them helpful in assessing risk in the energy sector. However, their use in other energy systems development, such as oil refineries, nuclear power plants and biodiesel plants, has not been analyzed in a review. A systematic review has identified and appraised studies with Bayesian network applications in energy production, use and distribution for their scope, modeling aspects and use. The review shows that the applications of Bayesian networks in the energy sector can be improved regarding modeling choices, and recommendations for future works are drawn to aid the standardization of modeling practices. •Bayesian networks (BN) application is extraordinarily case-specific.•BN applications in the energy sector is focus on nuclear power and oil related accidents.•Merging BN with other methods is possible and desirable.•Model validation is overlooked and underreported by authors.•More transparency is needed when using experts' judgment.