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Complex terrain wind resource estimation with the wind-atlas method: Predictionerrors using linearized and nonlinear CFD micro-scale models
Troen, Ib; Bechmann, Andreas; Kelly, Mark C.; Sørensen, Niels N.; Réthoré, Pierre-Elouan; Cavar,Dalibor; Ejsing Jørgensen, Hans
Publication date:2014
Document VersionPeer reviewed version
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Citation (APA):Troen, I. (Author), Bechmann, A. (Author), Kelly, M. C. (Author), Sørensen, N. N. (Author), Réthoré, P-E.(Author), Cavar, D. (Author), & Ejsing Jørgensen, H. (Author). (2014). Complex terrain wind resource estimationwith the wind-atlas method: Prediction errors using linearized and nonlinear CFD micro-scale models.Sound/Visual production (digital), European Wind Energy Association (EWEA).
Complex terrain wind resource estimation with the wind-atlas method: Prediction errors using linearized and nonlinear CFD microscale models.
Ib Troen, Andreas Bechmann, Mark C. Kelly, Niels N. Sørensen, Pierre-Elouan Réthoré, Dalibor Cavar, Hans E. Jørgensen
DTU Wind Energy, Technical University of Denmark
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Outline
• Wind Atlas Analysis, Wind Atlas Application (WAsP)
• The linear model (BZ)
• Known deficiencies in complex terrain and possible remedies
• The fully nonlinear RANS model (Ellipsys3D)
• Form drag issue
• Validation
• Delta-RIX revisited
• Conclusions
EWEA 2014, Barcelona Spain
DTU Wind Energy, Technical University of Denmark
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Sector wise histograms of measured winds
Wind measuring site Maps, location
Orographic flow model (BZ)
Roughness change model (IBL)
Wind Atlas data set
Roughness change factors
Effective upstream roughness, land fraction
Stability correction
Corrected histograms
”up” transformation: histograms of Geo-wind
”down” transformation: to std z over std z0s
Weibull fitting
Height
Orographic correction factors, turning
EWEA 2014, Barcelona Spain
Wind Atlas Analysis (IBZ)
DTU Wind Energy, Technical University of Denmark
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Target site Maps, location
Orographic flow model (BZ)
Roughness change model (IBL)
Roughness change factors
Effective upstream roughness, land fraction
Interpolation and stability correction
Target Weibull parameters
Upstream Weibull parameters
Height
Orographic correction factors, turning
EWEA 2014, Barcelona Spain
Wind Atlas data set
Ressource data: mean, power…
WT data Wind Atlas Application (IBZ)
DTU Wind Energy, Technical University of Denmark
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Sector wise histograms of measured winds
Wind measuring site Maps, target area
3D grid generation
Terrain flow model (Ellipsys)
Wind Atlas data set
Effective upstream roughness, land fraction
Stability correction
Corrected histograms
”up” transformation: histograms of Geo-wind
”down” transformation: to std z over std z0s
Weibull fitting
Height, location
Terrain flow corrections result volume
Terrain flow corrections
EWEA 2014, Barcelona Spain
Wind Atlas Analysis (CFD)
DTU Wind Energy, Technical University of Denmark
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Ressource data: mean, power…
Maps, target area
3D grid generation
Terrain flow model (Ellipsys)
Effective upstream roughness, land fraction
Interpolation and stability correction
Upstream Weibull parameters
Height, location
Terrain flow corrections result volume
Terrain flow corrections
Wind Atlas data set
Target Weibull parameters
WT data
EWEA 2014, Barcelona Spain
Wind Atlas Application (CFD)
DTU Wind Energy, Technical University of Denmark
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BZ model
• Linearized spectral flow model for neutral boundary layer.
• Spectral expansion in terms of
Fourier-Bessel series in polar
coordinates with ”zooming” radial
grid distances
• Calculates flow perturbation only at the central point.
• Very fast for calculating flow perturbation at single points in the terrain, and vertical profiles.
• Integrated in WAsP.
7 29 June 2015
DTU Wind Energy, Technical University of Denmark
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Linear model forcing term
Figure adapted from Wood and Mason 1993:
The pressure force induced by neutral, turbulent flow over hills QJRMS, vol 119, pp 1233-1267
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Ruggedness IndeX (RIX)
from: Bowen, A.J. and Niels G. Mortensen (2004):
WAsP prediction errors due to site orography Risø-R-995(EN)
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Ellipsys3D
• Multiblock finite volume discretization of the incompressible Reynolds Averaged Navier-Stokes (RANS) equations in general curvilinear coordinates
• Neutral atmospheric stability in WAsP-CFD configuration
• Fully dynamic model with nonlinear terms, energy-dissipation two equation turbulence closure
• One simulation (steady state) for each of 36 upstream wind directions
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Ellipsys surface grid
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Diameter = 30 km
DTU Wind Energy, Technical University of Denmark
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Volume grid
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Result 3D volume for each of 36 directions
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DTU Wind Energy, Technical University of Denmark
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Formdrag – small scales: roughness
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DTU Wind Energy, Technical University of Denmark
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Form drag – larger scales
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In CFD physics, but B.C.s, not in IBZ, link to RIX ?
DTU Wind Energy, Technical University of Denmark
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Validation
• 9 complex sites, each with several masts
• Levels from 10m (1 site with 5 masts) to 100m (1 site, 2 masts)
• Mast distances from ~1 km to ~15km
• Sites in Europe, Americas, A-Asia
EWEA 2014, Barcelona Spain
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Site example with (2km by 2km) CFD tile
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Horizontal 10m-20m
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Horizontal 30m-40m
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Horizontal 50m-60m
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Horizontal 80m-100m
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All upwards extrapolations
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All horizontal predictions by distance
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Delta-RIX revisited
EWEA 2014, Barcelona Spain
,
DTU Wind Energy, Technical University of Denmark
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Finer scale features - example
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BZ CFD
Slopefix Delta-RIX
DTU Wind Energy, Technical University of Denmark
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Conclusions
• Wind Atlas method in WAsP has been extended to allow for more advanced flow modelling (via Cloud).
• Validation of system against available complex terrain data show significant improvement of CFD over linearized flow model.
• CFD can give additional siting information (TKI, tilt)
• For the specific use of predictions from well exposed locations to well exposed locations the delta-RIX correction show good skill in reducing the error variance of the linear model, but correction ”aliasing” to larger scales could be an issue. Slanted extrapolations ? Combination with moderate ”landfill” ?
• The delta-RIX method depends, however, on some empirical fitting of parameters, but is otherwise very convenient.
• More (complex) site data would be very desirable for further validation.
• Large scale field experiments in complex terrain are needed to help improve physical models and to guide the simpler ones (NEWA project).
EWEA 2014, Barcelona Spain
Thanks for your attention !
EWEA 2014, Barcelona Spain