This study uses the Reynolds-averaged Navier–Stokes (RANS) equations to validate a canopy model by computing a fully developed wind flow within and above a horizontally homogeneous dense forest as in the work of Dalpé and Masson. The model is paired with a modified k–ε turbulence closure. A set of boundary conditions (BCs) that rely on the law of the wall for a sustainable atmospheric boundary layer (ABL) is used. All simulations are conducted in the open source software OpenFOAM v.2.4.0 (OpenCFD Ltd (ESI Group)). Two practical aspects are considered in the validation process. First, an accurate leaf area index (LAI) integration to exactly fit the wind shear is evaluated. Since the physical foliage parameters may not be accessible for all type of forests, a generic leaf area density α distribution is tested. The results of this test show that a generic distribution is sufficient for preliminary analyses to improve accuracy of wind flow predictions over forested terrain. Second, the approach of Dalpé and Masson is limited to cyclic BCs which are not practical for real sites. For cases without cyclic BCs, imposing a proper slope on the inlet velocity profile is of high importance. This condition can be achieved through adjustment of the roughness length at the inlet.

References

1.
Morales Garza
,
V.
,
2017
, “
Evaluating the Accuracy of RANS Wind Flow Modeling and Its Impact on Capacity Factor for Moderately Complex Forested Terrain
,” Master's thesis, École de technologie supérieure, Montreal, QC, Canada.
2.
IEA
,
2016
, “
Energy, Climate Change and Environment 2016 Insights
,” International Energy Agency, Paris, France, Report No. ECCE2016.
3.
IEA
,
2016
, “
World Energy Outlook 2016 (Executive Summary)
,” International Energy Agency, Paris, France, Report No. WEO2016.
4.
GWEC
,
2016
, “
Global Wind Report 2015
,” Global Wind Energy Council, Brussels, Belgium, Report No.
GWR2015
.https://gwec.net/publications/global-wind-report-2/global-wind-report-2015-annual-market-update/
5.
ETIPWind
,
2016
, “
Strategic Research and Innovation Agenda 2016
,” ETIPWind, Brussels, Belgium, Report No. ETIPWind-SRIA-2016.
6.
Manwell
,
J. F.
,
McGowan
,
J. G.
, and
Rogers
,
A. L.
,
2009
,
Wind Energy Explained: Theory, Design and Application
, 2nd ed.,
Wiley
,
Chichester, UK
.
7.
Panofsky
,
H. A.
, and
Ming
,
Z.
,
1983
, “
Characteristics of Wind Profiles Over Complex Terrain
,”
J. Wind Eng. Ind. Aerodyn.
,
15
(
1–3
), pp.
177
183
.
8.
Ayotte
,
K. W.
,
2008
, “
Computational Modelling for Wind Energy Assessment
,”
J. Wind Eng. Ind. Aerodyn.
,
96
(
10–11
), pp.
1571
1590
.
9.
Petersen
,
E. L.
,
Mortensen
,
N. G.
,
Landberg
,
L.
,
Højstrup
,
J.
, and
Frank
,
H. P.
,
1998
, “
Wind Power Meteorology—Part II: Siting and Models
,”
Wind Energy
,
1
(
2
), pp.
55
72
.
10.
Lange
,
M.
, and
Focken
,
U.
,
2006
,
Physical Approach to Short-Term Wind Power Prediction
,
Springer-Verlag
,
Berlin
.
11.
Landberg
,
L.
,
Myllerup
,
L.
,
Rathmann
,
O.
,
Petersen
,
E. L.
,
Jørgensen
,
B. H.
,
Badger
,
J.
, and
Mortensen
,
N. G.
,
2003
, “
Wind Resource Estimation—An Overview
,”
Wind Energy
,
6
(
3
), pp.
261
271
.
12.
Richards
,
P. J.
, and
Hoxey
,
R.
,
1993
, “
Appropriate Boundary Conditions for Computational Wind Engineering Using the k-Epsilon Turbulence Model
,”
J. Wind Eng. Ind. Aerodyn.
,
46–47
, pp.
145
153
.
13.
Kim
,
H. G.
,
Patel
,
V. C.
, and
Lee
,
C. M.
,
2000
, “
Numerical Simulation of Wind Flow Over Hilly Terrain
,”
J. Wind Eng. Ind. Aerodyn.
,
87
(
1
), pp.
45
60
.
14.
Hargreaves
,
D. M.
, and
Wright
,
N. G.
,
2007
, “
On the Use of the k–ε Model in Commercial CFD Software to Model the Neutral Atmospheric Boundary Layer
,”
J. Wind Eng. Ind. Aerodyn.
,
95
(
5
), pp.
355
369
.
15.
Sumner
,
J.
,
Watters
,
C. S.
, and
Masson
,
C.
,
2010
, “
CFD in Wind Energy: The Virtual, Multiscale Wind Tunnel
,”
Energies
,
3
(
5
), pp.
989
1013
.
16.
Weller
,
H. G.
, and
Tabor
,
G.
,
1998
, “
A Tensorial Approach to Computational Continuum Mechanics Using Object-Oriented Techniques
,”
Comput. Phys.
,
12
(
6
), pp.
620
631
.
17.
Versteeg
,
H. K.
, and
Malalasekera
,
W.
,
2007
,
An Introduction to Computational Fluid Dynamics: The Finite Volume Method
, 2nd ed.,
Pearson Education Limited
,
Edinburgh, UK
.
18.
Prospathopoulos
,
J.
, and
Voutsinas
,
S. G.
,
2006
, “
Implementation Issues in 3D Wind Flow Predictions Over Complex Terrain
,”
ASME J. Sol. Energy Eng.
,
128
(
4
), p.
539
.
19.
Launder
,
B. E.
, and
Spalding
,
D. B.
,
1972
,
Lectures in Mathematical Models of Turbulence
,
Academic Press
,
New York
.
20.
Launder
,
B. E.
, and
Spalding
,
D. B.
,
1974
, “
The Numerical Computation of Turbulent Flows
,”
Comput. Methods Appl. Mech. Eng.
,
3
(
2
), pp.
269
289
.
21.
Bardina
,
J. E.
,
Huang
,
P. G.
, and
Coakley
,
T. J.
,
1997
, “
Turbulence Modeling Validation, Testing, and Development
,” NASA Ames Research Center, Moffett Field, CA, Report No.
NASA-TM-110446
.https://ntrs.nasa.gov/search.jsp?R=19970017828
22.
Pope
,
S. B.
,
2000
,
Turbulent Flows
, Vol. 1,
Cambridge University Press
,
Cambridge, UK
.
23.
Stull
,
R. B.
,
1988
,
An Introduction to Boundary Layer Meteorology
, Vol. 13,
Springer Science+Business Media
,
Dordrecht, The Netherlands
.
24.
Raupach
,
M. R.
,
1994
, “
Simplified Expressions for Vegetation Roughness Length and Zero-Plane Displacement as Functions of Canopy Height and Area Index
,”
Boundary-Layer Meteorol.
,
71
(
1–2
), pp.
211
216
.
25.
Verhoef
,
A.
,
McNaughton
,
K. G.
, and
Jacobs
,
A. F. G.
,
1997
, “
A Parameterization of Momentum Roughness Length and Displacement Height for a Wide Range of Canopy Densities
,”
Hydrol. Earth Syst. Sci.
,
1
(
1
), pp.
81
91
.
26.
Svensson
,
U.
, and
Haggkvist
,
K.
,
1990
, “
Two-Equation Turbulence Model for Canopy Flows
,”
J. Wind Eng. Ind. Aerodyn.
,
35
(
1
), pp.
201
211
.
27.
Katul
,
G. G.
,
Mahrt
,
L.
,
Poggi
,
D.
, and
Sanz
,
C.
,
2004
, “
ONE- and TWO-Equation Models for Canopy Turbulence
,”
Boundary-Layer Meteorol.
,
113
(
1
), pp.
81
109
.
28.
Lopes da Costa
,
J. C.
,
Castro
,
F. A.
,
Palma
,
J. M. L. M.
, and
Stuart
,
P.
,
2006
, “
Computer Simulation of Atmospheric Flows Over Real Forests for Wind Energy Resource Evaluation
,”
J. Wind Eng. Ind. Aerodyn.
,
94
(
8
), pp.
603
620
.
29.
Dalpé
,
B.
, and
Masson
,
C.
,
2008
, “
Numerical Study of Fully Developed Turbulent Flow Within and Above a Dense Forest
,”
Wind Energy
,
11
(
5
), pp.
503
515
.
30.
Jeannotte
,
E.
,
2013
, “
Estimation of Lidar Bias Over Complex Terrain Using Numerical Tools
,” Master's thesis, École de technologie supérieure, Montreal, QC, Canada.
31.
Arroyo
,
R. C.
,
Rodrigo
,
J. S.
, and
Gankarski
,
P.
,
2014
, “
Modelling of Atmospheric Boundary-Layer Flow in Complex Terrain With Different Forest Parameterizations
,”
J. Phys.: Conf. Ser.
,
524
, p.
12119
.
32.
Boudreault
,
L. É.
,
Bechmann
,
A.
,
Sørensen
,
N. N.
,
Sogachev
,
A.
, and
Dellwik
,
E.
,
2014
, “
Canopy Structure Effects on the Wind at a Complex Forested Site
,”
J. Phys.: Conf. Ser.
,
524
, p.
12112
.
33.
Grant
,
E. R.
,
Ross
,
A. N.
, and
Gardiner
,
B. A.
,
2016
, “
Modelling Canopy Flows Over Complex Terrain
,”
Boundary-Layer Meteorol.
,
161
(
3
), pp.
417
437
.
34.
Apsley
,
D. D.
, and
Castro
,
I. P.
,
1997
, “
A Limited-Length-Scale k-ε Model for the Neutral and Stably-Stratified Atmospheric Boundary Layer
,”
Boundary-Layer Meteorol.
,
83
(
1
), pp.
75
98
.
35.
Mortensen
,
N. G.
,
Heathfield
,
D. N.
,
Rathmann
,
O.
, and
Nielsen
,
M.
,
2011
,
Wind Atlas Analysis and Application Program: WAsP 10 Help Facility
,
DTU Wind Energy
, Copenhagen,
Denmark
.
36.
Morales Garza
,
V.
,
Nathan
,
J.
,
Sumner
,
J.
, and
Masson
,
C.
,
2019
, “
Evaluating the Accuracy of RANS Wind Flow Modeling Over Forested Terrain—Part 2: Impact on Capacity Factor for Moderately Complex Topography
,” ASME J. Solar Energy Eng. (under review).
37.
Chen
,
J. M.
, and
Cihlar
,
J.
,
1996
, “
Retrieving Leaf Area Index of Boreal Conifer Forests Using Landsat TM Images
,”
Remote Sens. Environ.
,
55
(
2
), pp.
153
162
.
38.
Omasa
,
K.
,
Hosoi
,
F.
, and
Konishi
,
A.
,
2007
, “
3D Lidar Imaging for Detecting and Understanding Plant Responses and Canopy Structure
,”
J. Exp. Botany
,
58
(
4
), pp.
881
898
.
39.
Desmond
,
C. J.
,
Watson
,
S. J.
,
Aubrun
,
S.
,
Ávila
,
S.
,
Hancock
,
P.
, and
Sayer
,
A.
,
2014
, “
A Study on the Inclusion of Forest Canopy Morphology Data in Numerical Simulations for the Purpose of Wind Resource Assessment
,”
J. Wind Eng. Ind. Aerodyn.
,
126
, pp.
24
37
.
40.
Boudreault
,
L. É.
,
Bechmann
,
A.
,
Tarvainen
,
L.
,
Klemedtsson
,
L.
,
Shendryk
,
I.
, and
Dellwik
,
E.
,
2015
, “
A LiDAR Method of Canopy Structure Retrieval for Wind Modeling of Heterogeneous Forests
,”
Agric. For. Meteorol.
,
201
, pp.
86
97
.
41.
Patankar
,
S.
,
1980
,
Numerical Heat Transfer and Fluid Flow
,
Hemisphere
,
Washington, DC
.
42.
Ferziger
,
J. H.
, and
Peric
,
M.
,
2002
,
Computational Methods for Fluid Dynamics
, 3rd ed.,
Springer-Verlag
,
Berlin
.
43.
Sumner
,
J.
, and
Masson
,
C.
,
2012
, “
k–ε Simulations of the Neutral Atmospheric Boundary Layer: Analysis and Correction of Discretization Errors on Practical Grids
,”
Int. J. Numer. Methods Fluids
,
70
(
6
), pp.
724
741
.
44.
Amiro
,
B. D.
,
1990
, “
Comparison of Turbulence Statistics Within Three Boreal Forest Canopies
,”
Boundary-Layer Meteorol.
,
51
(
1–2
), pp.
99
121
.
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