Complex terrain wind resource estimation with the wind-atlas method: Prediction errors using linearized and nonlinear CFD micro-scale models

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Complex terrain wind resource estimation with the wind-atlas method: Prediction errors 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 Version

Author final version (often known as postprint) Link to publication

Citation (APA):

Troen, I., Bechmann, A., Kelly, M. C., Sørensen, N. N., Réthoré, P-E., Cavar, D., & Ejsing Jørgensen, H. (2014).

Complex terrain wind resource estimation with the wind-atlas method: Prediction errors using linearized and nonlinear CFD micro-scale models European Wind Energy Association (EWEA). [Sound/Visual production (digital)]. European Wind Energy Conference & Exhibition 2014, Barcelona, Spain, 10/03/2014

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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

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DTU Wind Energy, Technical University of Denmark

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”Header & Footer”

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

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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

Wind Atlas Analysis (IBZ)

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Target site Maps, location

Orographic flow model (BZ) Roughness change

model (IBL)

Roughness change factors

Interpolation and stability correction

Target Weibull parameters

Upstream Weibull parameters Height

Orographic correction factors, turning

Wind Atlas data set

Ressource data: mean, power…

WT data

Wind Atlas Application (IBZ)

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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

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

Wind Atlas Analysis (CFD)

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Ressource data: mean, power…

Maps, target area

3D grid generation Terrain flow model

(Ellipsys)

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

Wind Atlas Application (CFD)

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BZ model

• Linearized spectral flow model for neutral boundary layer.

• Spectral expansion in terms of Fourier-

B

essel series in polar

coordinates with ”

z

ooming” 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

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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

Diameter = 30 km

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Volume grid

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Result 3D volume for each of 36 directions

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Formdrag – small scales: roughness

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Form drag – larger scales

In CFD physics, but B.C.s, not in IBZ, link to RIX ?

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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

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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 ,

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Finer scale features - example

BZ CFD

Slopefix Delta-RIX

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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).

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Thanks for your attention !