Wind Flow Over Forested Hills:

Mean Flow and Turbulence Characteristics

CEsA - Centre for Wind Energy and Atmospheric Flows, Portugal

J. Lopes da Costa, José Laginha Palma

Peter Stuart, Ian Hunter

Renewable Energy Systems Ltd., UK

What we do with CFD:Understand the flow over a wind farm.

Effectively place meteorological masts.

Site turbines better.

Complement linear and empirical models.

Wind resource predictions.

Replace linear and empirical models.

What we don’t do with CFD:

CFD Model

Computer codeCommunity trade mark nº 4706438Office for Harmonisation in the Internal Market (OHIM)

Mathematical and Physical Modelling• Reynolds averaged Navier Stokes (RaNS) equations

• Two-equation (k-ε) turbulence model with canopy model

• Terrain-following coordinate system

Numerical Techniques• Finite volume

• SIMPLE algorithm

• Steady State & Transient

Svensson Canopy Model (in 2004)

The drag due to the canopy is taken into account via an additional term entering the momentum equation :

iDi UUCF 2

1 α (in m2m-3) is the leaf foliage area per unit of volume

CD is the canopy drag coefficient.

3

2

1UCS Dk 3

42

1UCC

kS D

The effects of the canopy on turbulence are accounted for by additional source terms Sk and Sε in the transport equations of k and ε

Lopes da Costa, J. C., Castro F.A., Palma J.M.L.M., Stuart P. “Computer Simulation of Atmospheric Flows over Real Forests for Wind Energy Resource Evaluation”, journal of Wind Engineering and Industrial Aerodynamics, 94 (2006) P. 603-620, 7th February 2006.

New Canopy Model (in 2008)

Model βp Βd Cε4 Cε5

Svensson et al (1990) 1.0 0.0 1.95 0.0

Lopes da Costa (New Model) 0.17 3.37 0.9 0.9

Lopes da Costa, J. C. P., “Atmospheric Flow Over Forested and Non-Forested Complex Terrain”,PhD Thesis University of Porto, July 2007.

kUUCS dpDk

3

UCU

kCCS dpD 5

3

4

The canopy model constants are derived by comparing CFD simulations of an idealised canopy step change with Large Eddy Simulations (LES).

The new canopy model includes extra terms in the turbulence and dissipation equations:

RANS vs. Large Eddy Simulation (LES)

Wind SpeedTurbulence

Site Characterisation (1)

• European site with complex orography and extensive forest cover (H ~ 15m).

• 6 meteorological masts used for validation.

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Predicted and measured shear exponents for 330° direction.

Measured ShearCFD (New Canopy Model) CFD (Svensson Canopy Model) H = 15m, CD = 0.25 and α = 0.2

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Measured Turbulence Intensity

CFD (New Canopy Model) CFD (Svensson Canopy Model)

Predicted and measured turbulence intensity for 330° direction.

H = 15m, CD = 0.25 and α = 0.2

Site Characterisation (2)

Optimisation of Canopy Parameters…

Reducing the canopy density improves agreement, but even with α = 0.05 the predicted shear exponents are still too high.

2nd Iteration: α → 0.13

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Measured ShearCFD (New Canopy Model) CFD (Svensson Canopy Model)

Site Characterisation (2)

3rd Iteration: α → 0.05

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Measured ShearCFD (New Canopy Model) CFD (Svensson Canopy Model)

Site Characterisation (3)

Further improvement gained by using an effective tree height of ¾ the actual height.

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Shear From Concurrent Data Shear From All Data

CFD (New Canopy Model) CFD (Svensson Canopy Model)

Predicted and measured shear exponents for 330° direction.

Final canopy parameters: H = 11.25m, CD = 0.25, α = 0.05

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Turbulence From Concurrent Data Turbulence From All Data

CFD (New Canopy Model) CFD (Svensson Canopy Model)

Predicted and measured turbulence intensity for 330° direction.

Site Characterisation (4)Optimised parameters derived from 330° direction applied to 300° direction.

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Shear From Concurrent Data Shear From All Data

CFD (New Canopy Model) CFD (Svensson Canopy Model)

Predicted and measured shear exponents for 300° direction.

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Turbulence From Concurrent Data Turbulence From All Data

CFD (New Canopy Model) CFD (Svensson Canopy Model)

Predicted and measured turbulence intensity for 300° direction.

Wind Speed Profiles

Turbulence Intensity Profiles

Conclusions

• Svennson and new model are similar > 3 tree heights.

• New model better < 3 tree heights.

• Tune α (canopy density) to better predict shear and turbulence.

Further Work

• Investigate applying a vertically variable canopy density.

VENTOSTM

http://paginas.fe.up.pt/ventos/

REShttp://www.res-group.com