Wind Energy Science
Wind Energy Science
WES
Articles | Volume 9, issue 7
Articles | Volume 9, issue 7
https://doi.org/10.5194/wes-9-1507-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-1507-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 7
Research article
 | 
12 Jul 2024
Research article |  | 12 Jul 2024

Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm

Diederik van Binsbergen, Pieter-Jan Daems, Timothy Verstraeten, Amir R. Nejad, and Jan Helsen

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Short summary
Wind farm yield assessment often relies on analytical wake models. Calibrating these models can be challenging due to the stochastic nature of wind. We developed a calibration framework that performs a multi-phase optimization on the tuning parameters using time series SCADA data. This yields a parameter distribution that more accurately reflects reality than a single value. Results revealed notable variation in resultant parameter values, influenced by nearby wind farms and coastal effects.
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