Risk Assessment and Prognosis of Onshore Wind Power Projects Utilizing Fault Tree Analysis and Bayesian Network Methodology

Jingyi Huang () and Yi Wang ()
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Jingyi Huang: North China Electric Power University (Baoding)
Yi Wang: North China Electric Power University (Baoding)

A chapter in Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025), 2025, pp 212-225 from Springer

Abstract: Abstract As the energy mix evolves, the share of wind power is increasing. Presently, the risk assessment of onshore wind projects predominantly relies on expert judgment. To enhance this process, our study commences with a clear definition of project objectives, followed by an analysis of risk sources and events. We systematically map these elements into a Bayesian network utilizing a fault tree model. By integrating fuzzy expert evaluations, we develop a comprehensive risk assessment model and perform a sensitivity analysis. Case studies demonstrate that the risk factors identified by our model align closely with real-world scenarios, providing robust references for the management of onshore wind projects.

Keywords: Onshore wind power project; Risk evaluation; Fault tree; Bayesian network modeling (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-835-6_23

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DOI: 10.2991/978-94-6463-835-6_23

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