Articles | Volume 5, issue 1
https://doi.org/10.5194/wes-5-309-2020
https://doi.org/10.5194/wes-5-309-2020
Research article
 | 
05 Mar 2020
Research article |  | 05 Mar 2020

Optimizing wind farm control through wake steering using surrogate models based on high-fidelity simulations

Paul Hulsman, Søren Juhl Andersen, and Tuhfe Göçmen

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Paul Hulsman on behalf of the Authors (13 Nov 2019)  Author's response   Manuscript 
ED: Publish as is (05 Dec 2019) by Athanasios Kolios
ED: Publish as is (15 Dec 2019) by Joachim Peinke (Chief editor)
AR by Paul Hulsman on behalf of the Authors (25 Dec 2019)
Download
Short summary
We aim to develop fast and reliable surrogate models for yaw-based wind farm control. The surrogates, based on polynomial chaos expansion, are built using high-fidelity flow simulations combined with aeroelastic simulations of the turbine performance and loads. Optimization results performed using two Vestas V27 turbines in a row for a specific atmospheric condition suggest that a power gain of almost 3 % ± 1 % can be achieved at close spacing by yawing the upstream turbine more than 15°.
Altmetrics
Final-revised paper
Preprint