Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

Duc, Thomas; Coupiac, Olivier; Girard, Nicolas; Giebel, Gregor; Göçmen, Tuhfe

doi:https://doi.org/10.5194/wes-4-287-2019

Articles | Volume 4, issue 2

https://doi.org/10.5194/wes-4-287-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/wes-4-287-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 4, issue 2

Research article

|

22 May 2019

Research article |

| 22 May 2019

Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

Thomas Duc, Olivier Coupiac, Nicolas Girard, Gregor Giebel, and Tuhfe Göçmen

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Final revised paper (published on 22 May 2019)
Preprint (discussion started on 11 Oct 2018)

Interactive discussion

Status: closed

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

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SC1: 'Nice paper, thanks for sharing your methods and results !', Rémi Gandoin, 12 Oct 2018
- SC2: 'Errata', Rémi Gandoin, 12 Oct 2018
RC1: 'Good engineering approach', Anonymous Referee #1, 06 Nov 2018
RC2: 'Anonymous review', Anonymous Referee #2, 24 Nov 2018
AC1: 'Authors response to reviewers', Thomas Duc, 07 Jan 2019

Peer-review completion

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

AR by Thomas Duc on behalf of the Authors (07 Jan 2019) Author's response

ED: Referee Nomination & Report Request started (25 Jan 2019) by Raúl Bayoán Cal

RR by Anonymous Referee #1 (22 Feb 2019)

RR by Anonymous Referee #2 (27 Feb 2019)

Suggestions for revision or reasons for rejection

The authors have definitely improved the clarity of the paper, and I agree that the actual wind farm experimental data make this a worthwhile paper.

I still have several suggestions for further improving the paper:

1. The authors should reference Figure 6 in the last paragraph on Page 9.

2. In Figure 6(a), since there are left (power) and right (TI) axes, I would suggest augmenting the two legend labels with “Jensen, k_w = …” to be “Estimated Power using Jensen, k_w = …” since otherwise readers may not be sure if those curves are to be read with the left or right axis.

In Figure 6(b), it may be beneficial for readers if the curves for k_w = 0.75*TI and k_w = 0.075 have the same color, line, and marker types as the corresponding curves in Figure 6(a).

3. Similar comments apply to Figure 7: Augment the two legend labels with “Jensen, k_w = …” to be “Estimated Power using Jensen, k_w = …”

In Figure 7(b), it would helpful if the curves for k_w = 0.9*TI and k_w = 0.09 have the same color, line, and marker types as the corresponding curves in Figure 7(a).

4. Figure 8: I would suggest using “Above rated WS” rather than “After rated WS”, and similarly in the text discussion.

5. Equation (7): Is the denominator TI_{wa} for the case when there is no curtailment? The right-most column in the case with curtailment in Table 1 is also labeled TI_{wa}.

6. Section 5.5: When you use the word “conservative” in “conservative estimate of 0.3 m/s”, do you mean that 0.3 m/s is a higher wind speed error than would be expected? Or a lower wind speed error than would be expected?

7. Page 20, last paragraph of Section 5.5: “Figure 14 shows that the uncertainty of the calibrated model output is not normally distributed. … It is also seen that there are many outliers in the distribution, which occur near the rated wind speed, i.e. around the operational transition between Region II and III.” How is it possible to know or “see” that the outliers in Figure 14 occur near rated wind speed? There are no absolute wind speeds labeled in Figure 14.

8. I would suggest removing ellipses (three dots) in a formal journal article:

a. On page 21, line 2.
b. On Page 23, line 26. I’m actually not sure why “{ . . . }” appears twice in this reference.

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ED: Publish subject to minor revisions (review by editor) (05 Mar 2019) by Raúl Bayoán Cal

AR by Thomas Duc on behalf of the Authors (11 Mar 2019) Author's response Manuscript

ED: Publish as is (19 Mar 2019) by Raúl Bayoán Cal

ED: Publish as is (07 Apr 2019) by Jakob Mann (Chief editor)

AR by Thomas Duc on behalf of the Authors (26 Apr 2019)

Short summary

Wind turbine wake recovery is very sensitive to ambient atmospheric conditions. This paper presents a way of including a local turbulence intensity estimation from SCADA into the Jensen wake model to improve its accuracy. This new model procedure is used to optimize power production of an operating wind farm and shows that some gains can be expected even if uncertainties remain high. These optimized settings are to be implemented in a field test campaign in the scope of the SMARTEOLE project.