Articles | Volume 6, issue 4
https://doi.org/10.5194/wes-6-1015-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-6-1015-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
WRF-simulated low-level jets over Iowa: characterization and sensitivity studies
Jeanie A. Aird
CORRESPONDING AUTHOR
Sibley School of Mechanical and Aerospace Engineering, Cornell
University, Ithaca, New York, USA
Rebecca J. Barthelmie
Sibley School of Mechanical and Aerospace Engineering, Cornell
University, Ithaca, New York, USA
Tristan J. Shepherd
Department of Earth and Atmospheric Sciences, Cornell University,
Ithaca, New York, USA
Sara C. Pryor
Department of Earth and Atmospheric Sciences, Cornell University,
Ithaca, New York, USA
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Low-level jets (LLJs) are special types of non-ideal wind profiles affecting both wind energy production and loads on a wind turbine. However, among LLJ researchers, there is no consensus regarding which definition to use to identify these profiles. In this work, we compare two different ways of identifying the LLJ – the falloff definition and the shear definition – and argue why the shear definition is better suited to wind energy applications.
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Knowing the wind speed across the rotor of a wind turbine is key in making good predictions of the power production. However, models struggle to capture both the speed and the shape of the wind profile. Using machine learning methods based on the model data, we show that the predictions can be improved drastically. The work focuses on three coastal sites, spread over the Northern Hemisphere (the Baltic Sea, the North Sea, and the US Atlantic coast) with similar results for all sites.
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Using lidar-derived wind speed measurements at approx. 150 m height at onshore and offshore locations, we quantify the advantages of deploying wind turbines offshore in terms of the amount of electrical power produced and the higher reliability and predictability of the electrical power.
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Low-level jets (LLJs) are special types of non-ideal wind profiles affecting both wind energy production and loads on a wind turbine. However, among LLJ researchers, there is no consensus regarding which definition to use to identify these profiles. In this work, we compare two different ways of identifying the LLJ – the falloff definition and the shear definition – and argue why the shear definition is better suited to wind energy applications.
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Windstorms during the last 40 years in the US Northeast are identified and characterized using the spatial extent of extreme wind speeds at 100 m height from the ERA5 reanalysis. During all of the top 10 windstorms, wind speeds exceeding the local 99.9th percentile cover at least one-third of the land area in this high-population-density region. These 10 storms followed frequently observed cyclone tracks but have intensities 5–10 times the mean values for cyclones affecting this region.
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Short summary
Low-level jets (LLJs) are pronounced maxima in wind speed profiles affecting wind turbine performance and longevity. We present a climatology of LLJs over Iowa using output from the Weather Research and Forecasting (WRF) model and determine the rotor plane conditions when they occur. LLJ characteristics are highly sensitive to the identification criteria applied, and different (unique) LLJs are extracted with each criterion. LLJ characteristics also vary with different model output resolution.
Low-level jets (LLJs) are pronounced maxima in wind speed profiles affecting wind turbine...
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