Articles | Volume 9, issue 10
https://doi.org/10.5194/wes-9-1885-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-1885-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Oct 2024
Research article |
| 07 Oct 2024
| 07 Oct 2024
Probabilistic surrogate modeling of damage equivalent loads on onshore and offshore wind turbines using mixture density networks
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629HS Delft, the Netherlands
Richard Dwight
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629HS Delft, the Netherlands
Axelle Viré
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629HS Delft, the Netherlands
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Thematic area: Materials and operation | Topic: Fatigue
Data-driven surrogate model for wind turbine damage equivalent load
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Yu Cao, Ningyu Wu, Jigang Yang, Chao Chen, Ronghua Zhu, and Xugang Hua
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Wind Energ. Sci., 8, 1839–1852, https://doi.org/10.5194/wes-8-1839-2023, https://doi.org/10.5194/wes-8-1839-2023, 2023
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Analysis of long-term fatigue damage of four offshore wind turbines using 3 years of measurement data was performed for the first time to gain insight into the low-frequency fatigue damage (LFFD) impact on overall consumed life. The LFFD factor depends on the (linear) stress–life (SN) curve slope, heading, site, signal, and turbine type. Up to ∼ 65 % of the total damage can be related to LFFDs. Therefore, in this case study, the LFFD effect has a significant impact on the final damage.
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Offshore wind turbines are beginning to reach their design lifetimes. Hence, lifetime extensions are becoming relevant. To make well-founded decisions on possible lifetime extensions, fatigue damage predictions are required. Measurement-based assessments instead of simulation-based analyses have rarely been conducted so far, since data are limited. Therefore, this work focuses on the temporal extrapolation of measurement data. It is shown that fatigue damage can be extrapolated accurately.
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The article delineates a novel procedure to use 10 min measurement statistics with few known parameters of the wind turbine to determine the long-term fatigue damage probability and compare this with the expected damage levels from the design to provide an indicator of structural reliability and remaining life. The results are validated with load measurements from a wind turbine within an offshore wind farm.
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Short summary
The selection of a suitable site for the installation of a wind turbine plays an important role in ensuring a safe operating lifetime of the structure. In this study, we show that mixture density networks can accelerate this process by inferring functions from data that can accurately map the environmental conditions to the loads but also propagate the uncertainty from the inflow to the response.
The selection of a suitable site for the installation of a wind turbine plays an important role...
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