Wake steering optimization under uncertainty

Quick, Julian; King, Jennifer; King, Ryan N.; Hamlington, Peter E.; Dykes, Katherine

doi:https://doi.org/10.5194/wes-5-413-2020

Articles | Volume 5, issue 1

https://doi.org/10.5194/wes-5-413-2020

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

https://doi.org/10.5194/wes-5-413-2020

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

Articles | Volume 5, issue 1

Research article

|

30 Mar 2020

Research article |

| 30 Mar 2020

Wake steering optimization under uncertainty

Julian Quick, Jennifer King, Ryan N. King, Peter E. Hamlington, and Katherine Dykes

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Final revised paper (published on 30 Mar 2020)
Supplement to the final revised paper
Preprint (discussion started on 14 Oct 2019)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review Comments for wes-2019-72', Anonymous Referee #1, 07 Nov 2019
- AC1: 'Response to Referee 1', Julian Quick, 15 Jan 2020
RC2: 'Review of “wes-2019-72”', Erik Quaeghebeur, 15 Nov 2019
- AC2: 'Response to Referee 2', Julian Quick, 15 Jan 2020

Peer-review completion

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

AR by Julian Quick on behalf of the Authors (15 Jan 2020) Author's response Manuscript

ED: Publish as is (06 Feb 2020) by Michael Muskulus

ED: Publish as is (14 Feb 2020) by Gerard J.W. van Bussel (Chief editor)

AR by Julian Quick on behalf of the Authors (24 Feb 2020) Author's response Manuscript

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Short summary

We investigate the trade-offs in optimization of wake steering strategies, where upstream turbines are positioned to deflect wakes away from downstream turbines, with a probabilistic perspective. We identify inputs that are sensitive to uncertainty and demonstrate a realistic optimization under uncertainty for a wind power plant control strategy. Designing explicitly around uncertainty yielded control strategies that were generally less aggressive and more robust to the uncertain input.