Articles | Volume 8, issue 5
https://doi.org/10.5194/wes-8-691-2023
https://doi.org/10.5194/wes-8-691-2023
Research article
 | 
05 May 2023
Research article |  | 05 May 2023

The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data

Robert Braunbehrens, Andreas Vad, and Carlo L. Bottasso

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Carlo L. Bottasso on behalf of the Authors (10 Feb 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (21 Feb 2023) by Jens Nørkær Sørensen
RR by Anonymous Referee #1 (26 Feb 2023)
RR by Anonymous Referee #2 (08 Mar 2023)
ED: Publish as is (16 Mar 2023) by Jens Nørkær Sørensen
ED: Publish as is (16 Mar 2023) by Sandrine Aubrun (Chief editor)
AR by Carlo L. Bottasso on behalf of the Authors (05 Apr 2023)  Manuscript 
Download
Short summary
The paper presents a new method in which wind turbines in a wind farm act as local sensors, in this way detecting the flow that develops within the power plant. Through this technique, we are able to identify effects on the flow generated by the plant itself and by the orography of the terrain. The new method not only delivers a flow model of much improved quality but can also help in understanding phenomena that drive the farm performance.
Altmetrics
Final-revised paper
Preprint