DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications

Abstract

Here, the sensitivities of idealized Large-Eddy Simulations (LES) to variations of model configuration and forcing parameters on quantities of interest to wind power applications are examined. Simulated wind speed, turbulent fluxes, spectra and cospectra are assessed in relation to variations of two physical factors, geostrophic wind speed and surface roughness length, and several model configuration choices, including mesh size and grid aspect ratio, turbulence model, and numerical discretization schemes, in three different code bases. Two case studies representing nearly steady neutral and convective atmospheric boundary layer (ABL) flow conditions over nearly flat and homogeneous terrain were used to force and assess idealized LES, using periodic lateral boundary conditions. Comparison with fast-response velocity measurements at five heights within the lowest 50 m indicates that most model configurations performed similarly overall, with differences between observed and predicted wind speed generally smaller than measurement variability. Simulations of convective conditions produced turbulence quantities and spectra that matched the observations well, while those of neutral simulations produced good predictions of stress, but smaller than observed magnitudes of turbulence kinetic energy, likely due to tower wakes influencing the measurements. While sensitivities to model configuration choices and variability in forcing can be considerable, idealized LES are shownmore » to reliably reproduce quantities of interest to wind energy applications within the lower ABL during quasi-ideal, nearly steady neutral and convective conditions over nearly flat and homogeneous terrain.« less

Authors:
 [1];  [2];  [3];  [4];  [5]; ORCiD logo [6]; ORCiD logo [6];  [6];  [7];  [2]; ORCiD logo [8]; ORCiD logo [4]; ORCiD logo [4]; ORCiD logo [2];  [9];  [5];  [5];  [10];  [11];  [12]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); National Center for Atmospheric Research, Boulder, CO (United States)
  4. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  5. Argonne National Lab. (ANL), Lemont, IL (United States)
  6. National Center for Atmospheric Research, Boulder, CO (United States)
  7. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  8. Centro Nacional de Energias Renovables, Navarra (Spain)
  9. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  10. United States Dept. of Energy, Washington, D.C. (United States)
  11. National Renewable Energy Lab. (NREL), Golden, CO (United States); United States Dept. of Energy, Washington, D.C. (United States)
  12. United States Dept. of Energy, Washington, D.C. (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
OSTI Identifier:
1441170
Report Number(s):
NREL/JA-5000-70811
Journal ID: ISSN 2366-7621
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Wind Energy Science Discussions
Additional Journal Information:
Journal Volume: 3; Journal ID: ISSN 2366-7621
Publisher:
European Academy of Wind Energy - Copernicus
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; wind energy; wind power; large-eddy simulation; LES; atmospheric boundary layer

Citation Formats

Mirocha, Jeffrey D., Churchfield, Matthew J., Munoz-Esparza, Domingo, Rai, Raj K., Feng, Yan, Kosovic, Branko, Haupt, Sue Ellen, Brown, Barbara, Ennis, Brandon L., Draxl, Caroline, Sanz Rodrigo, Javier, Shaw, William J., Berg, Larry K., Moriarty, Patrick J., Linn, Rodman R., Kotamarthi, Veerabhadra R., Balakrishnan, Ramesh, Cline, Joel W., Robinson, Michael C., and Ananthan, Shreyas. Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications. United States: N. p., 2018. Web. doi:10.5194/wes-2017-33.
Mirocha, Jeffrey D., Churchfield, Matthew J., Munoz-Esparza, Domingo, Rai, Raj K., Feng, Yan, Kosovic, Branko, Haupt, Sue Ellen, Brown, Barbara, Ennis, Brandon L., Draxl, Caroline, Sanz Rodrigo, Javier, Shaw, William J., Berg, Larry K., Moriarty, Patrick J., Linn, Rodman R., Kotamarthi, Veerabhadra R., Balakrishnan, Ramesh, Cline, Joel W., Robinson, Michael C., & Ananthan, Shreyas. Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications. United States. https://doi.org/10.5194/wes-2017-33
Mirocha, Jeffrey D., Churchfield, Matthew J., Munoz-Esparza, Domingo, Rai, Raj K., Feng, Yan, Kosovic, Branko, Haupt, Sue Ellen, Brown, Barbara, Ennis, Brandon L., Draxl, Caroline, Sanz Rodrigo, Javier, Shaw, William J., Berg, Larry K., Moriarty, Patrick J., Linn, Rodman R., Kotamarthi, Veerabhadra R., Balakrishnan, Ramesh, Cline, Joel W., Robinson, Michael C., and Ananthan, Shreyas. Tue . "Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications". United States. https://doi.org/10.5194/wes-2017-33. https://www.osti.gov/servlets/purl/1441170.
@article{osti_1441170,
title = {Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications},
author = {Mirocha, Jeffrey D. and Churchfield, Matthew J. and Munoz-Esparza, Domingo and Rai, Raj K. and Feng, Yan and Kosovic, Branko and Haupt, Sue Ellen and Brown, Barbara and Ennis, Brandon L. and Draxl, Caroline and Sanz Rodrigo, Javier and Shaw, William J. and Berg, Larry K. and Moriarty, Patrick J. and Linn, Rodman R. and Kotamarthi, Veerabhadra R. and Balakrishnan, Ramesh and Cline, Joel W. and Robinson, Michael C. and Ananthan, Shreyas},
abstractNote = {Here, the sensitivities of idealized Large-Eddy Simulations (LES) to variations of model configuration and forcing parameters on quantities of interest to wind power applications are examined. Simulated wind speed, turbulent fluxes, spectra and cospectra are assessed in relation to variations of two physical factors, geostrophic wind speed and surface roughness length, and several model configuration choices, including mesh size and grid aspect ratio, turbulence model, and numerical discretization schemes, in three different code bases. Two case studies representing nearly steady neutral and convective atmospheric boundary layer (ABL) flow conditions over nearly flat and homogeneous terrain were used to force and assess idealized LES, using periodic lateral boundary conditions. Comparison with fast-response velocity measurements at five heights within the lowest 50 m indicates that most model configurations performed similarly overall, with differences between observed and predicted wind speed generally smaller than measurement variability. Simulations of convective conditions produced turbulence quantities and spectra that matched the observations well, while those of neutral simulations produced good predictions of stress, but smaller than observed magnitudes of turbulence kinetic energy, likely due to tower wakes influencing the measurements. While sensitivities to model configuration choices and variability in forcing can be considerable, idealized LES are shown to reliably reproduce quantities of interest to wind energy applications within the lower ABL during quasi-ideal, nearly steady neutral and convective conditions over nearly flat and homogeneous terrain.},
doi = {10.5194/wes-2017-33},
journal = {Wind Energy Science Discussions},
number = ,
volume = 3,
place = {United States},
year = {Tue Sep 04 00:00:00 EDT 2018},
month = {Tue Sep 04 00:00:00 EDT 2018}
}

Works referenced in this record:

LLNL - WRF-LES - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455029

ANL - WRF-LES - Neutral - TTU
dataset, August 2012

  • Kosovic, Branko
  • microscale.anl.wrfles.neutral.ttu, 135 MB
  • DOI: 10.15483/1455030

LANL - WRF-LES - Neutral - TTU
dataset, August 2012

  • Mirocha, J. D.; Churchfield, M. J.; Munoz-Esparza, D.
  • Atmosphere to Electrons, 117 MB
  • DOI: 10.15483/1455031

Numerical simulations of wake interaction between two wind turbines at various inflow conditions
journal, October 2010

  • Troldborg, Niels; Larsen, Gunner C.; Madsen, Helge A.
  • Wind Energy, Vol. 14, Issue 7, p. 859-876
  • DOI: 10.1002/we.433

Review of computational fluid dynamics for wind turbine wake aerodynamics
journal, February 2011

  • Sanderse, B.; Pijl, S. P.; Koren, B.
  • Wind Energy, Vol. 14, Issue 7, p. 799-819
  • DOI: 10.1002/we.458

Generation of Turbulent Inflow Data for Spatially-Developing Boundary Layer Simulations
journal, March 1998

  • Lund, Thomas S.; Wu, Xiaohua; Squires, Kyle D.
  • Journal of Computational Physics, Vol. 140, Issue 2
  • DOI: 10.1006/jcph.1998.5882

An Introduction to Boundary Layer Meteorology
book, January 1988


Efficient Generation of Inflow Conditions for Large Eddy Simulation of Street-Scale Flows
journal, April 2008


The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar
journal, July 2013


Bridging the Transition from Mesoscale to Microscale Turbulence in Numerical Weather Prediction Models
journal, August 2014

  • Muñoz-Esparza, Domingo; Kosović, Branko; Mirocha, Jeff
  • Boundary-Layer Meteorology, Vol. 153, Issue 3
  • DOI: 10.1007/s10546-014-9956-9

Comparison of Measured and Numerically Simulated Turbulence Statistics in a Convective Boundary Layer Over Complex Terrain
journal, November 2016


A field study of the wake behind a 2 MW wind turbine
journal, January 1988


Large Eddy Simulation of wind farm aerodynamics: A review
journal, October 2014

  • Mehta, D.; van Zuijlen, A. H.; Koren, B.
  • Journal of Wind Engineering and Industrial Aerodynamics, Vol. 133
  • DOI: 10.1016/j.jweia.2014.07.002

Subgrid-scale modeling for large-eddy simulations of compressible turbulence
journal, April 2002

  • Kosović, Branko; Pullin, Dale I.; Samtaney, Ravi
  • Physics of Fluids, Vol. 14, Issue 4
  • DOI: 10.1063/1.1458006

Designing large-eddy simulation of the turbulent boundary layer to capture law-of-the-wall scaling
journal, February 2010


Large-eddy simulation of a very large wind farm in a stable atmospheric boundary layer
journal, June 2011

  • Lu, Hao; Porté-Agel, Fernando
  • Physics of Fluids, Vol. 23, Issue 6
  • DOI: 10.1063/1.3589857

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications
journal, January 2014

  • Mirocha, J. D.; Kosovic, B.; Aitken, M. L.
  • Journal of Renewable and Sustainable Energy, Vol. 6, Issue 1
  • DOI: 10.1063/1.4861061

Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model
journal, May 2014

  • Aitken, Matthew L.; Kosović, Branko; Mirocha, Jeffrey D.
  • Journal of Renewable and Sustainable Energy, Vol. 6, Issue 3
  • DOI: 10.1063/1.4885111

A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics
journal, January 2012


The Influence of Stable Boundary Layer Flows on Wind Turbine Fatigue Loads
conference, June 2012

  • Sim, Chungwook; Basu, Sukanta; Manuel, Lance
  • 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition
  • DOI: 10.2514/6.2009-1405

Implications of Stably Stratified Atmospheric Boundary Layer Turbulence on the Near-Wake Structure of Wind Turbines
journal, September 2014


A methodology for the design and testing of atmospheric boundary layer models for wind energy applications
journal, January 2017

  • Sanz Rodrigo, Javier; Churchfield, Matthew; Kosovic, Branko
  • Wind Energy Science, Vol. 2, Issue 1
  • DOI: 10.5194/wes-2-35-2017

PNNL - WRF-LES - Convective - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455025

ANL - WRF-LES - Convective - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455026

LANL - WRF-LES - Convective - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455027

Convective - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455028

LLNL - WRF-LES - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455029

ANL - WRF-LES - Neutral - TTU
dataset, August 2012

  • Kosovic, Branko
  • microscale.anl.wrfles.neutral.ttu, 135 MB
  • DOI: 10.15483/1455030

LANL - WRF-LES - Neutral - TTU
dataset, August 2012

  • Mirocha, J. D.; Churchfield, M. J.; Munoz-Esparza, D.
  • Atmosphere to Electrons, 117 MB
  • DOI: 10.15483/1455031

NREL - SOWFA - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455032

LANL - Convective - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455034

LANL - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455035

Tower - TTU (SWiFT) Tower, All levels - Processed Data
dataset, August 2012


Tower - TTU (SWiFT) Tower, All levels - Raw Data
dataset, January 2020

  • Ennis, Brandon
  • Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
  • DOI: 10.21947/1329252

Radar - TTU radar - Raw Data
dataset, January 2020

  • Ennis, Brandon
  • Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
  • DOI: 10.21947/1329730

Nrel
dataset, January 2021

  • Anderson, Amanda
  • Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
  • DOI: 10.21947/1435011

NREL - Domain - d03
dataset, January 2021

  • Anderson, Amanda
  • Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
  • DOI: 10.21947/1435012

PNNL - Domain - d03
dataset, January 2021

  • Anderson, Amanda
  • Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
  • DOI: 10.21947/1435013

The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar
journal, July 2013


Application of a Perturbation Recycling Method in the Large-Eddy Simulation of a Mesoscale Convective Internal Boundary Layer
journal, August 2002


Implications of Stably Stratified Atmospheric Boundary Layer Turbulence on the Near-Wake Structure of Wind Turbines
journal, September 2014


A methodology for the design and testing of atmospheric boundary layer models for wind energy applications
journal, January 2017

  • Sanz Rodrigo, Javier; Churchfield, Matthew; Kosovic, Branko
  • Wind Energy Science, Vol. 2, Issue 1
  • DOI: 10.5194/wes-2-35-2017

Works referencing / citing this record:

LLNL - WRF-LES - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455029

ANL - WRF-LES - Neutral - TTU
dataset, August 2012

  • Kosovic, Branko
  • microscale.anl.wrfles.neutral.ttu, 135 MB
  • DOI: 10.15483/1455030

LANL - WRF-LES - Neutral - TTU
dataset, August 2012

  • Mirocha, J. D.; Churchfield, M. J.; Munoz-Esparza, D.
  • Atmosphere to Electrons, 117 MB
  • DOI: 10.15483/1455031

NREL - SOWFA - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455032

LANL - Neutral - TTU
dataset, January 2018

  • Kosovic, Branko
  • Pacific Northwest National Laboratory; PNNL
  • DOI: 10.15483/1455035

Tower - TTU (SWiFT) Tower, All levels - Processed Data
dataset, August 2012


A New Planetary Boundary Layer Scheme Based on LES: Application to the XPIA Campaign
journal, August 2019

  • Senel, Cem Berk; Temel, Orkun; Porchetta, Sara
  • Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 8
  • DOI: 10.1029/2018ms001580

Large eddy simulations of floating offshore wind turbine wakes with coupled platform motion
journal, July 2019