Impact of Non-Gaussian Winds on Blade Loading and Fatigue of Floating Offshore Wind Turbines

This study introduces a novel methodology for estimating loading and fatigue damage in the blades of wind turbines, emphasizing non-Gaussian wind conditions’ impact. By calculating blade loading and fatigue using higher statistical moments of the irregular winds, the study demonstrates the significance of non-Gaussian effects on loading and fatigue predictions. A two-step methodology is developed to synthesize non-Gaussian wind processes, integrating the TurbSim (version 1.5) and Hermite moment model transformation methods. These wind time histories are then utilized in a fully coupled simulation of a floating wind turbine, integrating with a blade beam model. Preliminary analysis of wind thrust and the blade root bending moment indicates non-Gaussian effects on aerodynamic loading. Further analysis of fatigue reveals that fatigue hot spots vary along the blade surface, depending on short-term wind conditions and long-term wind distribution, with total fatigue life estimated by summing the fatigue damage at each potential hot spot. The probability density function of long-term wind process is estimated by fitting the Weibull distribution to measured buoy data. The results show that variations in long-term wind speed distributions lead to an average fatigue life difference of about 1.3 years (16%). The Gaussian wind model overestimates fatigue life by roughly 1.5 years (18%) compared to the non-Gaussian model. This highlights the importance of considering both long-term wind distributions and short-term wind characteristics for accurate fatigue assessment. The findings provide valuable insights for the design and operation of floating offshore wind turbines.

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Institutions

Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-09-01
DOI
https://doi.org/10.3390/jmse13091686
Citations
1
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
4.99

Funders

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article

Impact of Non-Gaussian Winds on Blade Loading and Fatigue of Floating Offshore Wind Turbines

Shanran Tang, Bert Sweetman, Shu Dai
1 citations
Journal of Marine Science and Engineering
Wind Energy Research and Development
4.99
article

Impact of Non-Gaussian Winds on Blade Loading and Fatigue of Floating Offshore Wind Turbines

Shanran Tang, Bert Sweetman, Shu Dai
article en
1 citations

Abstract

This study introduces a novel methodology for estimating loading and fatigue damage in the blades of wind turbines, emphasizing non-Gaussian wind conditions’ impact. By calculating blade loading and fatigue using higher statistical moments of the irregular winds, the study demonstrates the significance of non-Gaussian effects on loading and fatigue predictions. A two-step methodology is developed to synthesize non-Gaussian wind processes, integrating the TurbSim (version 1.5) and Hermite moment model transformation methods. These wind time histories are then utilized in a fully coupled simulation of a floating wind turbine, integrating with a blade beam model. Preliminary analysis of wind thrust and the blade root bending moment indicates non-Gaussian effects on aerodynamic loading. Further analysis of fatigue reveals that fatigue hot spots vary along the blade surface, depending on short-term wind conditions and long-term wind distribution, with total fatigue life estimated by summing the fatigue damage at each potential hot spot. The probability density function of long-term wind process is estimated by fitting the Weibull distribution to measured buoy data. The results show that variations in long-term wind speed distributions lead to an average fatigue life difference of about 1.3 years (16%). The Gaussian wind model overestimates fatigue life by roughly 1.5 years (18%) compared to the non-Gaussian model. This highlights the importance of considering both long-term wind distributions and short-term wind characteristics for accurate fatigue assessment. The findings provide valuable insights for the design and operation of floating offshore wind turbines.

Journal of Marine Science and EngineeringVol. 13(9)
Guangzhou Maritime College (CN), Texas A&M University (US)
Newcastle University, East China University of Science and Technology
Openalex Percentile: Top 5%
Wind Energy Research and Development
4.99
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