Wind Energy Science
Wind Energy Science
WES
Articles | Volume 11, issue 9
Articles | Volume 11, issue 9
https://doi.org/10.5194/wes-11-3171-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-3171-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 9
Research article
 | 
02 Sep 2026
Research article |  | 02 Sep 2026

Gaussian process surrogate modeling for efficient controller tuning and fatigue load prediction of the helix wake-mixing method

Daan van der Hoek, Tim Dammann, and Jan-Willem van Wingerden

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Latest update: 02 Sep 2026
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Short summary
Wind farms suffer power losses and increased structural loading due to wake interactions. The helix method mitigates this by continuously moving upstream turbine blades to accelerate wake recovery. We developed two surrogate models from high-fidelity simulations: one identifying optimal pitch settings, achieving 7.5 % power gain, and one predicting fatigue loads under various conditions. This enables joint evaluation of power gains and load penalties, supporting informed wind farm control design.
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