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Bayesian network model for accessing safety and security of offshore wind farms

: Ramírez-Agudelo, Oscar Hernán; Köpke, Corinna; Sill Torres, Frank

Volltext ()

Baraldi, P.:
30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference, ESREL/PSAM 2020. E-Proceedings. Online resource : 01 - 06 November 2020, Venice, Italy
Singapore: Research Publishing, 2020
ISBN: 978-981-14-8593-0
8 S.
European Safety and Reliability Conference (ESREL) <30, 2020, Online>
Probabilistic Safety Assessment and Management Conference (PSAM) <15, 2020, Online>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer EMI ()
offshore wind farms; safety; security; Bayesian network

The offshore wind industry experiences a rising importance for the worldwide energy production, which is accompanied by increasing amount of wind turbines and Offshore Wind Farms (OWFs). However, due to its harsh environment and its role for energy provision, OWFs are confronted with several threats that are impacting its safety and security. Consequently, decision making at design as well as run time plays an important role for providing safe and secure operation in OWFs. We propose in this work the application of a Bayesian Network (BN) for a high-level representation of the safety and security state of an OWF. The developed BN-model is based on the safety and security goals and related functions defined in Köpke et al. (2019). The derived model enables a user to analyze the overall importance of high impact functions, like compliance, environmental protection, supply reliability or accident prevention. Obtained results indicate that the proposed BN-model enables decision makers to explore cross-system interrelations, and thus, to define requirements for implementations on lower design levels.