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  4. Development of a risk analysis model for the installation of offshore wind farms
 
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2023
Conference Paper
Title

Development of a risk analysis model for the installation of offshore wind farms

Abstract
The installation of offshore wind farms represents a major driver of offshore wind energy costs due to the high level of associated risks. Substantial cost reduction potential can be realized if these risks are effectively identified and controlled, preventing project delays and financial damages. Therefore, we propose a new method to identify, analyse and evaluate installation risks for use in project planning. This paper provides an in-depth walkthrough of the steps involved in the development of a simulation-based quantitative risk analysis model. At the example of a turbine installation case study, project plan-related risks are identified and quantified by conducting a literature review and expert interviews. The corresponding risk likelihoods and consequences are modelled with probability distributions to simulate their impact on total project duration. Using Monte Carlo simulation, the distribution of results is statistically evaluated to derive the expected project delay caused by the analysed risks as well as reference values for optimistic and pessimistic scenarios. Regarding the underlying model assumptions, the most significant risks (e.g. supply chain failure) are identified and examined in a sensitivity analysis. The developed model can serve as a basis for developing more reliable schedule estimations and contribute to minimizing installation delays and costs.
Author(s)
Munoz, N. Garcia
Fraunhofer-Institut für Windenergiesysteme IWES  
Lange, A. K.
Hamburg University of Technology
Kaczenski, Jonas  
Fraunhofer-Institut für Windenergiesysteme IWES  
Wiggert, Marcel
Fraunhofer-Institut für Windenergiesysteme IWES  
Mainwork
Journal of Physics Conference Series
Conference
20th Deep Sea Offshore Wind R and D Conference, DeepWind 2023
Open Access
DOI
10.1088/1742-6596/2626/1/012042
Additional link
Full text
Language
English
Fraunhofer-Institut für Windenergiesysteme IWES  
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