Preprints
https://doi.org/10.5194/wes-2023-176
https://doi.org/10.5194/wes-2023-176
02 Apr 2024
 | 02 Apr 2024
Status: this preprint is currently under review for the journal WES.

Probabilistic cost modeling as a basis for optimizing the inspection and maintenance of support structures in offshore wind farms

Muhammad Farhan, Ronald Schneider, Sebastian Thöns, and Max Gündel

Abstract. The operational management of offshore wind farms includes inspection and maintenance (I&M) of the turbine support structures. These activities are complex and influenced by numerous uncertain factors that affect their costs. The uncertainty in the I&M costs should be considered in decision and value of information analyses performed to optimize I&M regimes. In this paper, we present a probabilistic cost model for I&M activities in an offshore wind farm serviced by boats operating from a port base. The model is developed based on interviews with a wind farm operator, consultants, and operation and maintenance engineers, as well as on scientific literature. Various I&M methods are considered, and the model is evaluated to predict probabilistic I&M costs at different levels, i.e., wind farm, structural system, and structural component. A sensitivity analysis is performed to study the influence of the different model parameters on the overall I&M costs. Finally, the model is included in a numerical example in which the I&M regime for a steel frame subject to fatigue is optimized using risk-informed methods. The frame's characteristics are comparable to those of a jacket structure supporting an offshore wind turbine. In the example, we demonstrate that the I&M costs can be considered deterministically as expected values since they are included in the optimization on a linear basis.

Muhammad Farhan, Ronald Schneider, Sebastian Thöns, and Max Gündel

Status: open (until 30 Apr 2024)

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Muhammad Farhan, Ronald Schneider, Sebastian Thöns, and Max Gündel
Muhammad Farhan, Ronald Schneider, Sebastian Thöns, and Max Gündel

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Short summary
This paper formulates and applies a probabilistic cost model to support the operational management of offshore wind farms. It provides the decision-theoretical basis for the optimization of I&M regimes with an emphasis on integrating the probabilistic cost model into the decision analysis. The proposed probabilistic cost model is then applied in a numerical example and a value of information analysis is performed to quantify the cost effectiveness of the identified optimal I&M strategy.
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