Estimating the major replacement rates in next-generation offshore wind turbines using structured expert elicitation. Issue 1 (1st November 2022)

• Record Type: Journal Article
• Authors: Jenkins, Brian; Belton, Ian; Carroll, James; McMillan, David
• Is Part Of: Journal of physics. Volume 2362: Issue 1(2022)
• Publication Date: 2022-11-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2362/1/012020
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract : With offshore wind turbines continuing to increase in size and move further offshore and into harsher environments, the complexity of carrying out the major replacement of large components is expected to pose a significant challenge for future offshore wind farms. However, the rate of major replacement operations that will be required in these next generation offshore wind turbines is currently unknown. Using a structured expert elicitation method, based on the Classical Model and implemented using EFSA guidance for the practical application of structured expert elicitation, major replacement rates of large components (generator, gearbox, and rotor) were systematically estimated for four next generation offshore wind turbine configurations, based on the knowledge of six wind energy experts. The results presented in this paper are based on an equal-weighting aggregation approach. The major replacement rate values found using this approach are presented and compared between different turbine configurations. Based on these results, it is expected that a larger number of major replacement operations are more likely to be required in medium-speed turbine configurations, in comparison to direct- drive, and in floating turbines, in comparison to fixed-foundation turbines.