Articles | Volume 9, issue 11
https://doi.org/10.5194/wes-9-2039-2024
https://doi.org/10.5194/wes-9-2039-2024
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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Data-driven surrogate model for wind turbine damage equivalent load Rad Haghi https://doi.org/10.5281/zenodo.12583597

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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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