Wind Energy Science
Wind Energy Science
WES
Articles | Volume 11, issue 4
Articles | Volume 11, issue 4
https://doi.org/10.5194/wes-11-1383-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-1383-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 4
Data description article
 | 
24 Apr 2026
Data description article |  | 24 Apr 2026

New method to characterize aerodynamic flow state around wind turbine blades

Dimitri Voisin, Didier Velayoudon, Mattéo Capaldo, John-Richard Ordonnez-Valera, Rachel Jorand, and Mohammed Fajar

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Short summary
This study presents a novel method to characterize the aerodynamic flow state on wind turbine blades using eTellTale (eTT) sensors. Deployed on two Vestas V27 turbines, the sensors show that attached flow increases energy production by 15 %, while detached flow reduces it by 30 %. Results indicate that 15 % of potential power is lost during 33 % of operating time, highlighting opportunities for improved real-time turbine control.
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