Wind Energy Science
Wind Energy Science
WES
Articles | Volume 9, issue 11
Articles | Volume 9, issue 11
https://doi.org/10.5194/wes-9-2235-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-9-2235-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 11
Research article
 | 
27 Nov 2024
Research article |  | 27 Nov 2024

Development and validation of a hybrid data-driven model-based wake steering controller and its application at a utility-scale wind plant

Peter Bachant, Peter Ireland, Brian Burrows, Chi Qiao, James Duncan, Danian Zheng, and Mohit Dua

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Short summary
Intentional misalignment of upstream turbines in wind plants in order to steer wakes away from downstream turbines has been a topic of research interest for years but has not yet achieved widespread commercial adoption. We deploy one such wake steering system to a utility-scale wind plant and then create a model to predict plant behavior and enable successful control. We apply calibrations to a physics-based model and use machine learning to correct its outputs to improve predictive capability.
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