Articles | Volume 11, issue 4
https://doi.org/10.5194/wes-11-1383-2026
https://doi.org/10.5194/wes-11-1383-2026
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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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2026-6', Anonymous Referee #1, 08 Feb 2026
    • AC2: 'Reply on RC1', Dimitri Voisin, 24 Feb 2026
  • RC2: 'Comment on wes-2026-6', Anonymous Referee #2, 18 Feb 2026
    • AC1: 'Reply on RC2', Dimitri Voisin, 24 Feb 2026
      • RC3: 'Reply on AC1', Anonymous Referee #2, 26 Feb 2026

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Dimitri Voisin on behalf of the Authors (06 Mar 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (30 Mar 2026) by Emmanuel Branlard
ED: Publish as is (01 Apr 2026) by Paul Veers (Chief editor)
AR by Dimitri Voisin on behalf of the Authors (08 Apr 2026)  Manuscript 
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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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