Optimal tuning of engineering wake  models through lidar measurements

Zhan, Lu; Letizia, Stefano; Iungo, Giacomo Valerio

doi:https://doi.org/10.5194/wes-5-1601-2020

Articles | Volume 5, issue 4

https://doi.org/10.5194/wes-5-1601-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/wes-5-1601-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 5, issue 4

Research article

|

19 Nov 2020

Research article |

| 19 Nov 2020

Optimal tuning of engineering wake models through lidar measurements

Lu Zhan, Stefano Letizia, and Giacomo Valerio Iungo

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Final revised paper (published on 19 Nov 2020)
Preprint (discussion started on 22 Jun 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of Manuscript # wes-2020-72', Anonymous Referee #1, 18 Jul 2020
- AC1: 'Reply to the comments provided by the Anonymous Referee #1 on the manuscript wes-2020-72 entitled “Optimal tuning of engineering wake models through LiDAR measurements”, by L. Zhan, S. Letizia and G. V. Iungo', Valerio Iungo, 04 Aug 2020
RC2: 'Review of wes-2020-72', Anonymous Referee #2, 06 Aug 2020
- AC2: 'Reply to the comments provided by the Anonymous Referee #2', Valerio Iungo, 25 Aug 2020
AC3: 'Markedup version of the manuscript', Valerio Iungo, 25 Aug 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Valerio Iungo on behalf of the Authors (25 Aug 2020) Author's response Manuscript

ED: Publish as is (30 Sep 2020) by Julie Lundquist

ED: Publish as is (01 Oct 2020) by Jakob Mann (Chief editor)

AR by Valerio Iungo on behalf of the Authors (05 Oct 2020) Manuscript

Short summary

Lidar measurements of wakes generated by isolated wind turbines are leveraged for optimal tuning of parameters of four engineering wake models. The lidar measurements are retrieved as ensemble averages of clustered data with incoming wind speed and turbulence intensity. It is shown that the optimally tuned wake models enable a significantly increased accuracy for predictions of wakes. The optimally tuned models are expected to enable generally enhanced performance for wind farms on flat terrain.