Wind Energy Science
Wind Energy Science
WES
Articles | Volume 9, issue 11
Articles | Volume 9, issue 11
https://doi.org/10.5194/wes-9-2039-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-2039-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 11
Research article
 | 
04 Nov 2024
Research article |  | 04 Nov 2024

Data-driven surrogate model for wind turbine damage equivalent load

Rad Haghi and Curran Crawford

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Short summary
This journal paper focuses on developing surrogate models for predicting the damage equivalent load (DEL) on wind turbines without needing extensive aeroelastic simulations. The study emphasizes the development of a sequential machine learning architecture for this purpose. The study also explores implementing simplified wake models and transfer learning to enhance the models' prediction capabilities in various wind conditions.
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