Articles | Volume 5, issue 1
Wind Energ. Sci., 5, 309–329, 2020
https://doi.org/10.5194/wes-5-309-2020
Wind Energ. Sci., 5, 309–329, 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 et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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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)
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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°.