Wind Energy Science
Wind Energy Science
WES
Articles | Volume 11, issue 3
Articles | Volume 11, issue 3
https://doi.org/10.5194/wes-11-771-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-771-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 3
Research article
 | 
06 Mar 2026
Research article |  | 06 Mar 2026

PhyWakeNet: a dynamic wake model accounting for aerodynamic force oscillations

Xiaohao Liu, Zhaobin Li, and Xiaolei Yang

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Short summary
This research addresses the need to predict the dynamic behaviour of wind turbine wakes. We developed a new computer model, PhyWakeNet, that combines physical laws with artificial intelligence. This model successfully simulates how a turbine's wake evolves over space and time under oscillating forces on blades. This capability is a significant step forward, as it can lead to better control strategies for entire wind farms, ultimately helping to improve wind farm performance.
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