Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-35-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-35-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Feb 2017
Research article |
| 09 Feb 2017
A methodology for the design and testing of atmospheric boundary layer models for wind energy applications
Wind Energy department, National Renewable Energy Centre (CENER),
Sarriguren, 31621, Spain
Matthew Churchfield
National Wind Technology Center, National Renewable Energy Laboratory
(NREL), Golden, 80401 CO, USA
Branko Kosovic
Research Applications Laboratory, National Center for Atmospheric
Research (NCAR), Boulder, 80307 CO, USA
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Cited
23 citations as recorded by crossref.
- Diurnal cycle RANS simulations applied to wind resource assessment J. Barcons et al. 10.1002/we.2283
- Evaluation of three mainstream numerical weather prediction models with observations from meteorological mast IJmuiden at the North Sea P. Kalverla et al. 10.1002/we.2267
- Impact of Negative Geostrophic Wind Shear on Wind Farm Performance A. Stieren et al. 10.1103/PRXEnergy.1.023007
- Development of a Time–Height Profile Assimilation Technique for Large-Eddy Simulation D. Allaerts et al. 10.1007/s10546-020-00538-5
- Sensitivity of nocturnal low-level jets to land-use parameters and meteorological quantities A. Ziemann et al. 10.5194/asr-16-85-2019
- Classifying Regions of High Model Error Within a Data-Driven RANS Closure: Application to Wind Turbine Wakes J. Steiner et al. 10.1007/s10494-022-00346-6
- Microscale simulations of extreme events in complex terrain driven by mesoscalar budget components M. Avila et al. 10.1088/1742-6596/2265/2/022021
- Mesoscale to Microscale Coupling for Wind Energy Applications: Addressing the Challenges S. Haupt et al. 10.1088/1742-6596/1452/1/012076
- Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy S. Haupt et al. 10.5194/wes-8-1251-2023
- Using observational mean‐flow data to drive large‐eddy simulations of a diurnal cycle at the SWiFT site D. Allaerts et al. 10.1002/we.2811
- Data-driven turbulence modeling for wind turbine wakes under neutral conditions J. Steiner et al. 10.1088/1742-6596/1618/6/062051
- Nudging based computational wind engineering simulation of the Atmospheric Boundary Layer M. Kotsiopoulou & D. Bouris 10.1016/j.jweia.2023.105627
- Future emerging technologies in the wind power sector: A European perspective S. Watson et al. 10.1016/j.rser.2019.109270
- Powering the 21st century by wind energy—Options, facts, figures K. Rohrig et al. 10.1063/1.5089877
- Data-driven RANS closures for wind turbine wakes under neutral conditions J. Steiner et al. 10.1016/j.compfluid.2021.105213
- Coupling Mesoscale Budget Components to Large-Eddy Simulations for Wind-Energy Applications C. Draxl et al. 10.1007/s10546-020-00584-z
- The ALEX17 diurnal cycles in complex terrain benchmark J. Sanz Rodrigo et al. 10.1088/1742-6596/1934/1/012002
- Consistent Boundary-Condition Treatment for Computation of the Atmospheric Boundary Layer Using the Explicit Algebraic Reynolds-Stress Model V. Želi et al. 10.1007/s10546-018-0415-x
- Modeling dynamic wind direction changes in large eddy simulations of wind farms A. Stieren et al. 10.1016/j.renene.2021.02.018
- Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mast A. Peña et al. 10.5194/wes-6-645-2021
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-7-345-2022
- Large-eddy simulation sensitivities to variations of configuration and forcing parameters in canonical boundary-layer flows for wind energy applications J. Mirocha et al. 10.5194/wes-3-589-2018
- Energy Exascale Computational Fluid Dynamics Simulations With the Spectral Element Method E. Merzari et al. 10.1115/1.4064659
23 citations as recorded by crossref.
- Diurnal cycle RANS simulations applied to wind resource assessment J. Barcons et al. 10.1002/we.2283
- Evaluation of three mainstream numerical weather prediction models with observations from meteorological mast IJmuiden at the North Sea P. Kalverla et al. 10.1002/we.2267
- Impact of Negative Geostrophic Wind Shear on Wind Farm Performance A. Stieren et al. 10.1103/PRXEnergy.1.023007
- Development of a Time–Height Profile Assimilation Technique for Large-Eddy Simulation D. Allaerts et al. 10.1007/s10546-020-00538-5
- Sensitivity of nocturnal low-level jets to land-use parameters and meteorological quantities A. Ziemann et al. 10.5194/asr-16-85-2019
- Classifying Regions of High Model Error Within a Data-Driven RANS Closure: Application to Wind Turbine Wakes J. Steiner et al. 10.1007/s10494-022-00346-6
- Microscale simulations of extreme events in complex terrain driven by mesoscalar budget components M. Avila et al. 10.1088/1742-6596/2265/2/022021
- Mesoscale to Microscale Coupling for Wind Energy Applications: Addressing the Challenges S. Haupt et al. 10.1088/1742-6596/1452/1/012076
- Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy S. Haupt et al. 10.5194/wes-8-1251-2023
- Using observational mean‐flow data to drive large‐eddy simulations of a diurnal cycle at the SWiFT site D. Allaerts et al. 10.1002/we.2811
- Data-driven turbulence modeling for wind turbine wakes under neutral conditions J. Steiner et al. 10.1088/1742-6596/1618/6/062051
- Nudging based computational wind engineering simulation of the Atmospheric Boundary Layer M. Kotsiopoulou & D. Bouris 10.1016/j.jweia.2023.105627
- Future emerging technologies in the wind power sector: A European perspective S. Watson et al. 10.1016/j.rser.2019.109270
- Powering the 21st century by wind energy—Options, facts, figures K. Rohrig et al. 10.1063/1.5089877
- Data-driven RANS closures for wind turbine wakes under neutral conditions J. Steiner et al. 10.1016/j.compfluid.2021.105213
- Coupling Mesoscale Budget Components to Large-Eddy Simulations for Wind-Energy Applications C. Draxl et al. 10.1007/s10546-020-00584-z
- The ALEX17 diurnal cycles in complex terrain benchmark J. Sanz Rodrigo et al. 10.1088/1742-6596/1934/1/012002
- Consistent Boundary-Condition Treatment for Computation of the Atmospheric Boundary Layer Using the Explicit Algebraic Reynolds-Stress Model V. Želi et al. 10.1007/s10546-018-0415-x
- Modeling dynamic wind direction changes in large eddy simulations of wind farms A. Stieren et al. 10.1016/j.renene.2021.02.018
- Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mast A. Peña et al. 10.5194/wes-6-645-2021
- Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions M. Howland et al. 10.5194/wes-7-345-2022
- Large-eddy simulation sensitivities to variations of configuration and forcing parameters in canonical boundary-layer flows for wind energy applications J. Mirocha et al. 10.5194/wes-3-589-2018
- Energy Exascale Computational Fluid Dynamics Simulations With the Spectral Element Method E. Merzari et al. 10.1115/1.4064659
Latest update: 23 Nov 2024
Short summary
The series of GABLS model intercomparison benchmarks is revisited in the context of wind energy atmospheric boundary layer (ABL) models. GABLS 1 and 2 are used for verification purposes. Then GABLS 3 is used to develop a methodology for using realistic mesoscale forcing for microscale ABL models. The method also uses profile nudging to dynamically reduce the bias. Different data assimilation strategies are discussed based on typical instrumentation setups of wind energy campaigns.
The series of GABLS model intercomparison benchmarks is revisited in the context of wind energy...
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