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Article

A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification

1
ForWind-Center for Wind Energy Research, University of Oldenburg, Küpkersweg 70, D-26129 Oldenburg, Germany
2
Fraunhofer Institute for Wind Energy Systems (IWES), Küpkersweg 70, D-26129 Oldenburg, Germany
3
Wobben Research and Development (WRD), Teerhof 59, D-28199 Bremen, Germany
*
Author to whom correspondence should be addressed.
Current address: Energy & Meteo Systems GmbH, Oskar-Homt-Str. 1, D-26131 Oldenburg, Germany.
Academic Editor: Sukanta Basu
Energies 2021, 14(4), 1191; https://doi.org/10.3390/en14041191
Received: 25 December 2020 / Revised: 2 February 2021 / Accepted: 10 February 2021 / Published: 23 February 2021
(This article belongs to the Special Issue Recent Advances in Wind Power Meteorology)
In wind energy site assessment, one major challenge is to represent both the local characteristics as well as general representation of the wind climate on site. Micro-scale models (e.g., Reynolds-Averaged-Navier-Stokes (RANS)) excel in the former, while meso-scale models (e.g., Weather Research and Forecasting (WRF)) in the latter. This paper presents a fast approach for meso–micro downscaling to an industry-applicable computational fluid dynamics (CFD) modeling framework. The model independent postprocessing tool chain is applied using the New European Wind Atlas (NEWA) on the meso-scale and THETA on the micro-scale side. We adapt on a previously developed methodology and extend it using a micro-scale model including stratification. We compare a single- and multi-point downscaling in critical flow situations and proof the concept on long-term mast data at Rödeser Berg in central Germany. In the longterm analysis, in respect to the pure meso-scale results, the statistical bias can be reduced up to 45% with a single-point downscaling and up to 107% (overcorrection of 7%) with a multi-point downscaling. We conclude that single-point downscaling is vital to combine meso-scale wind climate and micro-scale accuracy. The multi-point downscaling is further capable to include wind shear or veer from the meso-scale model into the downscaled velocity field. This adds both, accuracy and robustness, by minimal computational cost. The new introduction of stratification in the micro-scale model provides a marginal difference for the selected stability conditions, but gives a prospect on handling stratification in wind energy site assessment for future applications. View Full-Text
Keywords: atmospheric stratification; complex terrain; downscaling; micro-scale simulations; wind energy site assessment atmospheric stratification; complex terrain; downscaling; micro-scale simulations; wind energy site assessment
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MDPI and ACS Style

Buhr, R.; Kassem, H.; Steinfeld, G.; Alletto, M.; Witha, B.; Dörenkämper, M. A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification. Energies 2021, 14, 1191. https://doi.org/10.3390/en14041191

AMA Style

Buhr R, Kassem H, Steinfeld G, Alletto M, Witha B, Dörenkämper M. A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification. Energies. 2021; 14(4):1191. https://doi.org/10.3390/en14041191

Chicago/Turabian Style

Buhr, Renko, Hassan Kassem, Gerald Steinfeld, Michael Alletto, Björn Witha, and Martin Dörenkämper. 2021. "A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification" Energies 14, no. 4: 1191. https://doi.org/10.3390/en14041191

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