the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Annual Variability of Wake Impacts on Mid-Atlantic Offshore Wind Plant Deployments
David Rosencrans
Julie K. Lundquist
Mike Optis
Alex Rybchuk
Nicola Bodini
Michael Rossol
Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. Long mid-Atlantic wakes are causing growing concern. We evaluate wake variability and annual energy production with the first year-long modeling assessment using the Weather Research and Forecasting Model, deploying 12-MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. The strongest wakes, propagating 58 km, occur in summertime stable stratification, just when New England’s grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than diurnal variability of wakes. Overall, the mean year-long wake impacts reduce power output by 35.9 %. Internal wakes cause greater year-long power losses (27.4 %) compared to external wakes (14.1 %). Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy (TKE) from turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production (AEP) to New England grid demand and find that the lease areas can supply roughly 60 % of annual load.
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David Rosencrans et al.
Status: final response (author comments only)
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RC1: 'Comment on wes-2023-38', Anonymous Referee #1, 24 May 2023
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2023-38/wes-2023-38-RC1-supplement.pdf
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AC1: 'Reply on RC1', David Rosencrans, 18 Sep 2023
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2023-38/wes-2023-38-AC1-supplement.pdf
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AC1: 'Reply on RC1', David Rosencrans, 18 Sep 2023
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CC1: 'Comment on wes-2023-38', Mark Stoelinga, 02 Jun 2023
Thanks to the authors for this very good contribution. I have a few comments and questions that I'd like to share (references by line number or section).
181-182: I think centered RMSE (cRMSE) is essentially the same as what I’ve heard and referred to as bias-corrected RMSE (or BCRMSE), in which you first calculate the mean model bias error, subtract it from all the model values, then calculate RMSE. And, I believe both are essentially equivalent to the standard deviation of the errors as well. All that is neither here nor there. However, I do think the sentence in lines 181-182 should be clarified, to say that “a value of 0 for cRMSE indicates that all values, after removal of the respective model or measured means, lie on the 1:1 regression line”.
189 (paragraph): Might be good to show model versus measured mean shear exponent, a metric that the wind industry uses extensively and is highly familiar with its typical range of values.
325-326: There is an interesting result in Fig. 8 that you do not comment on, which is similar to behavior other have seen and commented on (including, I believe, one or more of you in previous work, and myself). What I’m referring to is the opposite effect of TKE amount in the near-project versus distant wake environment. Within and near the project, behavior is intuitive: higher TKE dissipates wakes and leads to smaller waked wind deficits. However, farther away, as evidenced by the distance northeastward of the first (0.5 m/s) contour, as well as the area of this contour reported in the text, it is actually slightly farther (and covers more area) with TKE than without it. In other words, at distance, higher TKE actually helps wakes, whereas near or within the project it hurts wakes. I saw the same behavior, and I’m certain you and others have commented on it previously. Do you have any new insights into this behavior?
Appendix E. The authors and I have had discussions in the past about the nature of the noise seen in difference fields (turbines minus no turbines wind speeds). I’m not opposed to the idea that they are purely numerical; I agree that is the most likely explanation. However, I still consider it possible that even the distant differences are perhaps partly physical rather than numerical. They tend to occur in an unstable boundary layer or in convective scenarios. These scenarios are characterized by small-scale, high-amplitude, chaotic structures (convective cells) whose initiation locations are random and probably sensitive to even the smallest perturbations, which may include very subtle and fast-moving gravity waves or other disturbance triggered by the presence of the turbines. For the purpose of energy production, though, they are probably inconsequential because they tend to cancel each other out when averaged either spatially or temporally.
I hope these comments and questions help.
Best regards, Mark Stoelinga
Disclaimer: this community comment is written by an individual and does not necessarily reflect the opinion of their employer.Citation: https://doi.org/10.5194/wes-2023-38-CC1 -
CC2: 'Reply on CC1', Mark Stoelinga, 02 Jun 2023
Well, I see that I missed a key paragraph on my first read, in which you addressed the question of higher TKE actually producing longer-lasting wakes at distance. Sorry for missing that key point. The explanation makes sense. -Mark S
Disclaimer: this community comment is written by an individual and does not necessarily reflect the opinion of their employer.Citation: https://doi.org/10.5194/wes-2023-38-CC2 -
AC2: 'Reply on CC1', David Rosencrans, 18 Sep 2023
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2023-38/wes-2023-38-AC2-supplement.pdf
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CC2: 'Reply on CC1', Mark Stoelinga, 02 Jun 2023
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RC2: 'Comment on wes-2023-38', Anonymous Referee #2, 13 Jun 2023
This study characterizes the wake impact of proposed wind farm in the mid-Atlantic Outer Continental Shelf through a series of model simulations using the Weather Research and Forecasting model. It includes an extensive set of one year long simulations, including a simulation without wind farms, a simulation for Vinyard Wind and a simulation including all lease areas. In addition, two different configurations added TKE are considered (0 % and 100 %). Finally, an additional 4 month long simulation is performed containing also the call areas.
This is an impressive set of simulations with a through analysis for a relevant topic. I find the analysis on the added TKE particularly interesting, especially the conclusion that the impact on power is small on average. I recommend publishing of this manuscript after addressing the numerous minor points below.
Minor comments
- line 68: While 12 MW turbines seem to be similar enough to the 13 MW turbines to be installed at Vineyard Wind, I wonder how realistic the assumption is for the other lease and especially the call areas, since those will be build later than Vineyard Wind. Also how sensitive are your results to the chosen turbine type?- line 73 - 74: Why did you choose this period and not a regular calendar year? Do you run continuously or restart the model after a certain period?
- line 79 - 81: You don't mention section 3
- line 95 ff: Please also provide the WRF option number in addition to the reference
- Figure 1 caption: last sentence, double mentioning of "red"
- line 107 - 114: How realistic is the assumption of regular layout within the areas? To reduce internal wake effects, the turbines might be better placed in an irregular layout
- Figure 2a: Where is region 1? Either start numbering at 1 or mention region 1 as below cut-in
- Figure 3: It would be nice to relate the wind rose to the "regions" in Figure 2. E.g. green could be capped at 11 (below rated power) and one color could be used for region 3. Also "m/s" should be formatted with negative exponents according to the guidelines
- Line 179: Does removing the periods induce a bias? E.g. are they related to the same period / stability category?
- Line 170 - 183: Why do you choose these metrics? How do they compliment each other?
- Line 189 - 196: Following up on the previous comment, how do you interpret the results that you obtain for the different error metrics? E.g. something along those lines: "the results correlate well in time but have an offset ...". This should also be discussed for the stability based analysis
- Line 203: You do not describe, which metric you use to classify stability. I assume you are using the same that you use in section 2.7. Consider to move section 2.7 before section 2.6 so that the reader doesn't need to guess.
- Section 2.7: You discuss in Appendix B that the Obukhov length only represents the surface characteristics. Why do you stick to this classification? Also Appendix B should be referenced in section 2.7. Have you estimated the sensitivity of your results to this particular metric? Platis et al. (2021) suggest that depending on the stability metric the results can vary quite a lot (Platis, A., Hundhausen, M., Lampert, A. et al. The Role of Atmospheric Stability and Turbulence in Offshore Wind-Farm Wakes in the German Bight. Boundary-Layer Meteorol 182, 441–469 (2022). https://doi.org/10.1007/s10546-021-00668-4)
- Line 249 - 251: This wake length estimation seems to be too simplified: What about wake turning? What about other wind directions? Arguably the wind rose does show predominant winds from south-west, but other wind directions are also present. In those cases the wake length will be underestimated. To understand your method it would help to draw the line in figure 1.
- Line 270: Reference Appendix E
- Line 304 - 305: This sentence is difficult to understand. Please revise.
- Line 311 - 319: These results could be much more neatly presented in a table instead of text form.
- Line 325: "although areal coverage is larger from reduced wind speed replenishment". What do you mean by this?
- Line 326 - 327: According to the numbers that you present for stable stratification the waked area is actually larger for TKE_100 (16404 km²) compared to TKE_0 (16060 km²). This contradicts with your conclusion in this sentence. Please clarify.
- Line 341 - 345: Again a table would facilitate a comparison between scenarios
- Line 349: You reference D1 here, but D1 only shows TKE_100 and thus the differences due to different TKE levels cannot be assessed.
- Figure 9: Sub-figure titles are (a) for all
- Line 361 - 362: Can you provide the power losses averaged over the four month for VW_only and VW_waked for comparison?
- Section 3.3.1: You show also diurnal variations, but these are not discussed. Please add this.
- Line 383 - 398: It seems a bit counter-intuitively that losses are not additive, i.e. internal losses + external losses != total losses. While the proposed loss estimates (9) and (10) do make sense, they do not share the same reference (P_VW_only vs P_NWF), which makes it more difficult to compare.
- Line 402: I understand the energy demand estimates are taken for present day? Are there estimates on how the energy demand will change until CA and LA are build?
- Line 408 - 409: Could you add another line in figure 11 representing the stability conditions. This would make it easier to see that the power production is indeed more closely linked to hub-height wind than stability.
- Line 424: Reference figure 2 here again to remind the reader of the definition of region 2 and 3
- Figure 13 caption: "black dots indicate turbine locations": suggesting to add "in TKE_0 and TKE_100", since in NWF they are not included
- Line 508: It would be interesting to discuss, how the difference due to added TKE amount compares to the difference due to different PBL schemes. You mention Rybchuk et al. (2022) at some places through the paper, but don't compare the effects due to PBL schemes and added TKE amount directly.
- Line 537: What do you mean by "the differences ... are precise"?
- Appendix A: The mixture of discussion on variability due to added TKE amount and the special case during calm winds between 12:00 and 15:20 on 12 July is confusing. These two aspects should be kept separate.
- Line 555: the first sentence is a bit difficult to understand. The difference between TKE_0 and TKE_25 seems to be more than 15 to 20 m
- Line 565: The way you reference figures is sometimes confusing to me. For instance, I would reference Figure B1 here as "stratification at the E05 and E06 (Fig. B1) lidars exhibits similar seasonal variability to Vineyard Wind (Fig. 6)". Since vineyard wind is shown in Fig. 6 and not in Fig. B1. Please also check other parts of the manuscript. Note also that you wrote "E05" twice.
- Figure D1: Colorbar is missing; is the upper row just a zoom of the lower row?
- Figure E1: "at which the map occurs" -> suggestion "of the map"
- Line 643 - 646: Difficult to understand. What do you mean by "poses a threat to power estimations". I don't understand the contrast "although ..., we show noise occurring in the SE ..." and why this "underscores the point that ... should only show differences within the wake". Please clarify
- Line 660: Is there a link missing for "OpenEI_link"?
- Line 715: Missing DOI
- Line 717: Missing URL
- Line 839: Missing URL
- Line 844: Missing DOI
Citation: https://doi.org/10.5194/wes-2023-38-RC2 -
AC3: 'Reply on RC2', David Rosencrans, 18 Sep 2023
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2023-38/wes-2023-38-AC3-supplement.pdf
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AC3: 'Reply on RC2', David Rosencrans, 18 Sep 2023
David Rosencrans et al.
David Rosencrans et al.
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