Investigating energy production and wake losses of multi-gigawatt offshore wind farms with atmospheric large-eddy simulation
- 1Whiffle, Molengraaffsingel 8, 2629 JD Delft, The Netherlands
- 2Delft University of Technology, Department of Engineering Systems & Services, Jaffalaan 5, 2628 BX Delft, the Netherlands
- 3Delft University of Technology, Department of Geosciences & Remote Sensing, Stevinweg 1, 2628 CN Delft, the Netherlands
- 1Whiffle, Molengraaffsingel 8, 2629 JD Delft, The Netherlands
- 2Delft University of Technology, Department of Engineering Systems & Services, Jaffalaan 5, 2628 BX Delft, the Netherlands
- 3Delft University of Technology, Department of Geosciences & Remote Sensing, Stevinweg 1, 2628 CN Delft, the Netherlands
Abstract. As a consequence of the rapid growth of the globally installed offshore wind energy capacity, the size of individual wind farms is increasing. This poses a challenge to models that predict energy production. For instance, the current generation of wake models has mostly been calibrated on existing wind farms of much smaller size. This work analyses annual energy production and wake losses for future multi-gigawatt wind farms with atmospheric large-eddy simulation. To that end, one year of actual weather has been simulated for a suite of hypothetical four-gigawatt offshore wind farm scenarios. The scenarios differ in terms of applied turbine type, installed capacity density, and layout. The results suggest that production numbers increase significantly when the rated power of the individual turbines is larger, while keeping the total installed capacity the same. Even for turbine types with similar rated power, but slightly different power curves, significant differences in production were found. Although wind speed was identified as the most dominant factor determining the aerodynamic losses, a clear impact of atmospheric stability has been identified. By analyzing losses of the first-row turbines, the yearly average global-blockage effect is estimated between 2 to 3 %, but it can reach levels over 10 % for stably stratified conditions and wind speeds around 8 ms−1. Using a high-fidelity modeling technique, the present work provides insights in the performance of future, multi-gigawatt wind farms for a full year of realistic weather conditions.
Peter Baas et al.
Status: final response (author comments only)
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RC1: 'Comment on wes-2022-116', Oliver Maas, 06 Jan 2023
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2022-116/wes-2022-116-RC1-supplement.pdf
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RC2: 'Comment on wes-2022-116', Anonymous Referee #2, 25 Jan 2023
This work used a year-long LES simulation dataset to looks at energy production and wake losses for six different 4 GW offshore wind farm scenarios. Authors looked at wake and losses for six different scenarios as a function of wind speed and direction, stability, as well as different wind farm layouts.
I believe that paper is well structured, and this work is very relevant for the entire wind energy community.
Some specific comments:
Line 72 and 77: decide if you would like to use “subgrid models” or “subgrid-models” and be consistent.
Line 80: Km is not defined
Line 83: “eddy-viscosity model specifically developed for anisotropic grids. “ So the grid is anisotropic? Need more details about grid spacing.
Line 88: So this model includes moisture and phase changes? How ere clouds and precipitations treated in the model? Need more information about moist processes in the model.
Line 152: Why you picked 2015? Is there any particulate reason? Need additional info about this choice.
Line 156: What type of “Vertical grid stretching”? How many points there is in Z direction and how is greed spacing distributed? Need additional clarification.
Very important note here (regarding model setup): Many studies reported that wind farm generates gravity waves (for example Allaerts (2017)), and I’m not sure that authors accounted for that fact. Without proper treatment of these waves, they might affect overall result, so should be properly addressed. Authors should address/discuss absence of proper treatment of farm induced gravity waves and their possible impact on this whole analysis.
Line 156: Is there a reason for a domain to be horizontally 76800m long?
Line 157: what about upper boundary comditions?
Line 293: “Schneemann et al. (2021), . “ delete ,
Line 341: “averaged over all the entire year” delete “all”
- RC3: 'Comment on wes-2022-116', Anonymous Referee #3, 27 Jan 2023
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RC4: 'Comment on wes-2022-116', Anonymous Referee #4, 29 Jan 2023
This paper investigates the energy production and wake losses of multi-gigawatt offshore wind farms using the LES approach. I like the research idea and the approach of using GPU to perform LES simulations with real atmospheric-driven forcings. I would support publication after the authors addressing these minor comments.
- Line 212: Please make a table showing the total number of wind turbines for each wind farm scenarios (Figure 3).
- Figure 5: Can the authors better explain how they calculate the free-stream production and the actual production? I would imagine the free-steam production (Figure 5a) of the first 4 scenarios to be 42TWh. However, the figure only shows about half of that magnitude.
- I would assume that the layout of the wind farm would have a substantial impact on the power production and the aerodynamic loss (Figure3). Do the authors find any significant differences in the result between scenario 6 and the rest.
- Why are the turbine spacings in these scenarios different (Table1). Shouldn’t the authors just change the wind turbine type while keeping everything else the same?
Peter Baas et al.
Peter Baas et al.
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