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

DOI

10.2991/978-94-6463-835-6_23How to use a DOI?

Keywords

Onshore wind power project; Risk evaluation; Fault tree; Bayesian network modeling

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.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jingyi Huang
AU  - Yi Wang
PY  - 2025
DA  - 2025/09/17
TI  - Risk Assessment and Prognosis of Onshore Wind Power Projects Utilizing Fault Tree Analysis and Bayesian Network Methodology
BT  - Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025)
PB  - Atlantis Press
SP  - 212
EP  - 225
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-835-6_23
DO  - 10.2991/978-94-6463-835-6_23
ID  - Huang2025
ER  -