the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Estimating Long-Term Annual Energy Production of a Large Offshore Wind Farm from Large-Eddy Simulations: Methods and Validation with a 10-Year Simulation
Abstract. Atmospheric large-eddy simulation (LES), a computational fluid-dynamics technique that resolves turbulence in the atmospheric boundary layer, is increasingly used for wind resource assessment (WRA), by including wind turbine parametrizations and using external weather data as initial- and boundary conditions. The large computational costs of doing such a 'real-weather' LES, however, limits length of the simulation to ≤ 1 year; whereas long-term, multi-year, mean power production values are of high interest to many parties in the wind energy sector. To address this need, this work presents several methods to estimate long-term mean power production/annual energy production and wind from a ≤ 1 year LES run, by applying Bayes' theorem on short-term LES output and long-term ERA5 reanalysis data.
A 10-year LES run of a hypothetical large offshore wind farm is performed in order to validate these 'long-term correction' methods, in three scenarios of increasing complexity. First, long-term correction of 365 consecutive days gives estimates of long-term mean power with a mean absolute error of 0.35 %, and 95th percentile of the absolute error within 0.8 % of the long-term mean, reducing the uncertainty by an order or magnitude. Second, in the scenario when the simulation period is not fixed, using several day selection techniques to select the simulation period can reduce the error further. Then, only around 200 days are needed to arrive at the same error values. The results indicate that long-term correction is insensitive to the particulars of the day selection methods, but that including a diverse set of days from different years and seasons is essential. Third, a method to also include wind observations in the long-term correction is presented and tested. This requires an additional 'free stream' LES run without active turbines, and gives estimates of long-term power and wind that are corrected for a potential LES bias. Although validation of this final approach is difficult in the employed modelling strategy, it gives valuable insights, and fits within the common WRA practice of combining models and observations.
The presented techniques are based on physical arguments, computationally cheap, and simple to implement; and as such could be a useful extension to the diverse set of modelling, observational, and statistical techniques used in WRA.
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CC1: 'Comment on wes-2024-54', Miguel Sanchez Gomez, 28 May 2024
Being able to perform WRA using LES for long time scales sounds amazing! However, I am very concerned about the "amount" of turbulence being resolved by the model and the validity of simulating a turbine wake using dx=120 m and dz=30m, particularly for offshore conditions where turbulence intensity can be smaller than onshore. It would be great if the authors could discuss the limitations of using coarse LES to study wakes and WRA. Specifically, I have two comments:
1. Simulate wind turbine wakes using dx of the same order as the turbine's rotor diameter: How can the model resolve a wind turbine wake that is of the same order as the grid spacing of the simulation? I would expect the model to have an effective grid resolution of about 7-8dx; therefore, only turbulence structures of order 1km will be resolved by the model and the turbine wake is partially resolved. If this is the case, wake recovery is largely determined by the SGS model. Even though Baas (2023) showed a relatively small effect when using dx=60m, this grid resolution is still too coarse to accurately resolve a turbine's wake.
2. Resolved turbulence in offshore conditions: A dx=120m and dz=30m grid is extremely coarse to resolve the dominant turbulence structures in the boundary layer for offshore conditions. I think the authors should stress this more clearly in the text. Also, the authors should present the fraction of resolved and modeled turbulence stresses to show if their grid resolution is enough to resolve turbulence in the turbine rotor layer.
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-2024-54-CC1 -
AC1: 'Reply on CC1', Bernard Postema, 31 May 2024
Thank you for your comments on our manuscript. The choice of resolution and its implications on the dynamics and accuracy of the simulations are indeed relevant topics. Our views on the two concerns you raise are listed below. Apart from this written reply, we are also currently setting up an additional resolution study to substantiate it. For this study, we plan to do LES of a real wind farm , with resolutions ranging between 20 m and 120 m. We intend to include its results as supplementary material to the revised version of the manuscript.
Regarding concern 1: We agree that individual turbine wakes are not resolved at these resolutions. Hence, the results are indeed not suitable to study near-wake dynamics at the scale of the rotor (which has never been our intention). However, we are convinced that there is value and predictive power in these simulations for wind resource assessment, because at the scale of the wind farm, the key physical effects are explicitly simulated, and sensitivity to resolution is low. This is what was found by Baas et al. (2023) in a similar modelling setup, and we used this finding in designing the simulations for this study.
Furthermore, the goal of this work is to present the methods of long-term correction; not to validate the modelling approach. So, although we agree that the relatively coarse resolution is a very valid topic to discuss, it does not affect the core of the manuscript, which is presenting statistical methods to derive long-term statistics from a short-term signal. Regarding concern 2: For turbulent structures in the boundary layer, a horizontal resolution of 120 m can indeed be considered coarse, perhaps indeed too coarse for studying details of near-surface offshore turbulence. However, we would like to emphasize that the goal of the manuscript is different: namely to present and validate long-term correction methods. For this purpose, the value of being able to present two 10 year LES runs outweighs the drawbacks of having a relatively coarse resolution. The subsequent resolution study will provide further details on the fraction of resolved and modeled turbulence at different resolutions.Citation: https://doi.org/10.5194/wes-2024-54-AC1
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AC1: 'Reply on CC1', Bernard Postema, 31 May 2024
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RC1: 'Comment on wes-2024-54', Anonymous Referee #1, 21 Jun 2024
The comment was uploaded in the form of a supplement: https://wes.copernicus.org/preprints/wes-2024-54/wes-2024-54-RC1-supplement.pdf
- AC2: 'Reply on RC1', Bernard Postema, 11 Jul 2024
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RC2: 'Comment on wes-2024-54', Anonymous Referee #2, 12 Jul 2024
Review of the manuscript “Estimating Long-Term Annual Energy Production of a Large Offshore Wind Farm from Large-Eddy Simulations: Methods and Validation with a 10-Year Simulation” by Bernard Postema, Remco Verzijlbergh, Pim Van Dorp, Peter Baas, and Harm Jonker submitted for publication in Wind Energy Science.
In the manuscript “Estimating Long-Term Annual Energy Production of a Large Offshore Wind Farm from Large-Eddy Simulations: Methods and Validation with a 10-Year Simulation” the authors present a numerical study focused on estimating long-term wind power production of an offshore wind farm based on mesoscale simulations and limited high-resolution, large-eddy simulations (LES).
General Remarks
While the numerical study presented in the manuscript is unique because it uses a long-term (10-year) LES, the authors did not present a convincing motivation and justification for their numerical study that uses coarse LESs to estimate offshore wind speed and simulate wind farm power production by representing operating wind turbines with an actuator disk model. It is not clear that a coarse LES can deliver any benefit in estimating hub height or rotor equivalent wind speed compared to significantly less costly mesoscale simulations. The LES at resolution of 120 m does not improve wind speed prediction compared to mesoscale simulations (> 1 km) or even ERA5 reanalysis as shown in the manuscript. Coarse LES does not resolve turbulent eddies in the inertial range considering: offshore conditions, effective resolution, and the need for inflow turbulence development not described in the manuscript.
The study presents a Bayesian downscaling approach that combines LES and reanalysis output. While this approach is interesting and the use of LES can be considered as something that has not been explored before, similar methodologies have been used extensively for regional climate downscaling (e.g., Holthuijzen et al., 2021, J. App. Meteorolo. Climat. and references therein). The authors did not provide any references to research that preceded their study, so based on the way the approach is presented, it would seem that this approach is completely novel. The novel part is exploring three scenarios for long-term correction, and this is possibly the most relevant contribution.
The study uses an actuator disk model that is not appropriate for the coarse LES resolution used in the study, i.e. 120 m in horizontal and ~30 m in vertical taking, with the effective resolution that is even coarser. For example, Calaf et al. (2010, also Meyers and Meneveau, 2010, cited in the paper) resolved the rotor with ~10 vertical grid cells. Bass et al. (2023) conducted a sensitivity study with grid cell size of 120 m and 60 m and similar vertical grid as present study and argued that the 120 m grid cell size is adequate, however, their estimates of aerodynamic losses were about 20% larger with coarser resolution – this is significant. In addition, the actuator disk model was implemented in the ASPIRE LES model, a version of a commercial, GPU-based model, which is not publicly available. It is not clear how ASPIRE differs from other versions of the GPU model (e.g., GRASP used in Bass et al., 2023, study) and if ASPIRE was validated in any way.
Although, to achieve greater realism and therefore relevance, the numerical study includes coupling between coarse reanalysis and LES simulated is a hypothetical wind farm which means that the results of the study cannot be validated. The use of a hypothetical wind farm is of a very limited value considering that it is now possible to obtain wind power production data for existing wind farms in the North Sea (see, e.g., https://rave-offshore.de/en/data.html).
Taking all the above in the consideration I do not recommend the manuscript “Estimating Long-Term Annual Energy Production of a Large Offshore Wind Farm from Large-Eddy Simulations: Methods and Validation with a 10-Year Simulation” in Wind Energy Science.
Specific Remarks
- Abstract – The abstract is confusing and poorly written, e.g., no motivation for the use of LES is provided.
- Line 28 – It is stated that “’real- weather’ LES has been demonstrated to be viable… to explicitly model the interactions between wind farms and the atmosphere (Baas et al., 2023)” however the cited study by Bass et al. (2023) does not include a validation that would demonstrate viability.
- Line 68 – ASPIRE model is used in the study and a reference is made to the Dutch Atmospheric Large Eddy Simulation (DALES) model and the GPU version, however, there are no previous references to the ASPIRE model and its validation.
- Line 119 – It is stated that “In the practice of LES modelling, it is often found that the wind speed displays a mean bias of O(0.1 m s−1)…” but no reference is provided for this statement.
- Line 121 – The sentence: “Such a free stream run has no turbines included, or it has turbines that exert no force on the flow, and therefore leave it undisturbed.” can be removed since is nonsensical. Turbines that exert no force on the flow are not turbines, since even turbines at rest exert force on the flow.
- Line 131 - It is stated that “…because of explicit representation of all fluid dynamical… effects…” First, it is not true that all fluid dynamical effects are represented since the rotation of the turbine is not accounted for, and second, at the coarse resolution used in the study it cannot be said that the fluid dynamical effects are represented well.
- Line 160 – How is ASPIRE different from or related to GRASP. Has it been validated?
- Line 164 – Given the resolution, it is not clear how turbulence develops on the inner LES domain.
- Line 165 – It is stated that “…the core LES domain is nested in a coarser mesoscale-type simulation with a resolution of 1.5 km,…” and “This coarser simulation has the same model formulation as the LES…,” however, it is not clear what is the exact model formulation. It is only mentioned that the turbulence parameterization is different, but not how is it different, what other parameterizations were used: radiative transfer, microphysics, land surface, etc. For the study to be reproducible this information should be provided.
- Line 185 – If turbines do not exert any force they are not included in the simulation, so there is no need to mention turbine.
- Line 221 (also Firgure 2) – It is not clear what is the benefit of LES offshore when it results in larger errors and turbulence is not resolved with 120 m grid cell size.
- Line 230 – As shown by Baas et al. (2023) a coarse LES result in overestimation of aerodynamic losses.
Citation: https://doi.org/10.5194/wes-2024-54-RC2 - AC3: 'Reply on RC2', Bernard Postema, 09 Aug 2024
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