15.5 Assessing the Sensitivity of the Fitch Wind Farm Parameterization to a Three-Dimensional Planetary Boundary Layer Scheme Based on a North Sea Case Study

Thursday, 1 February 2024: 2:45 PM
347/348 (The Baltimore Convention Center)
Nathan Agarwal, DOE, Boulder, CO; Univ. of Colorado Boulder, Boulder, CO; and J. K. Lundquist and A. Rybchuk

Wind turbines generate regions of reduced wind speed called wakes that may negatively affect downwind turbines. Rosencrans et al. (2023) analyze a proposed offshore wind farm in the United States mid-Atlantic and find that wake effects contribute a mean year-long power reduction of 35.9%. These power reductions have steep implications for financial models and numerical weather prediction (NWP) models have been developed to understand the wind resource that turbines experience.

These NWP models present uncertainties, driven mostly by the large number of potential model options. One particularly sensitive model option is the choice of the planetary boundary layer (PBL) scheme. The choice of the PBL scheme has been often shown to be the most important parameter affecting the simulated wind resource. While more than 10 different PBL schemes are available within the Weather Research and Forecasting (WRF) model, no single PBL scheme consistently performs best for wind resource assessment.

Uncertainties are also introduced by representing turbines in these NWP models. Because wind turbines are smaller than common NWP grid spacings, wind turbine impacts on the weather are expressed indirectly through parameterizations. Inaccuracies in these parameterizations have significant implications for power and (consequently) revenue predictions, and as such, several wind farm parameterizations have been, and continue to be, developed. Recently, Vollmer et al. (2023) have proposed a modification to the Fitch wind farm parameterization to account for the role of the wind plant induction zone.

Wind farm parameterization intercomparisons have attempted to identify optimal representations of the relevant physics. Recently, Ali et al. (2023) evaluate five common wind farm parameterizations by comparison to observations at a North Sea wind farm. However, one parameter not considered within the Ali et al. (2023) case study, and generally absent within the literature evaluating wind farm parameterizations, is the influence of the boundary layer scheme. Despite the fact that the PBL scheme has been often shown to be the most important factor influencing the wind resource in turbine-free NWP simulations, research on the impacts of boundary layer scheme on turbine simulations has been limited. This blindspot could potentially lead to unreliable wind farm model valuations.

This work addresses this gap by extending the results of the Ali case study. We extend the Ali et al. (2023) analysis of the Fitch wind farm parameterization by evaluating the impacts of replacing the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme with a three-dimensional PBL scheme outlined in Rybchuk et al. (2022). Further, we compare model results to in situ observations of this case (Siedersleben et al. 2020). We also explore the sensitivity of the induction zone correction factor proposed in Vollmer et al. (2023) to the boundary layer scheme by replacing the MYNN PBL scheme with this three-dimensional PBL scheme. These results offer insight into the importance of the boundary layer scheme in wind energy assessment.

References

Ali, K., D. M. Schultz, A. Revell, T. Stallard, and P. Ouro, 2023: Assessment of five wind-farm parameterizations in the Weather Research and Forecasting model: A case study of wind farms in the North Sea. Mon. Weather Rev., 1, https://doi.org/10.1175/MWR-D-23-0006.1.

Rosencrans, D., J. K. Lundquist, M. Optis, A. Rybchuk, N. Bodini, and M. Rossol, 2023: Annual Variability of Wake Impacts on Mid-Atlantic Offshore Wind Plant Deployments. Wind Energy Sci. Discuss., 1–39, https://doi.org/10.5194/wes-2023-38.

Rybchuk, A., T. W. Juliano, J. K. Lundquist, D. Rosencrans, N. Bodini, and M. Optis, 2022: The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme. Wind Energy Sci., 7, 2085–2098, https://doi.org/10.5194/wes-7-2085-2022.

Siedersleben, S. K., and Coauthors, 2020: Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1). Geosci. Model Dev., 13, 249–268, https://doi.org/10.5194/gmd-13-249-2020.

Vollmer, L., B. A. M. Sengers, and M. Dörenkämper, 2023: Brief communication: A simple axial induction modification to WRF’s Fitch wind farm parameterisation. Wind and the atmosphere/Wind and turbulence,.

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