Based on the wind measurement and potential energy assessment, the suitable wind power class for the study site is Class 4-5, with an average wind speed of 7.0-8.0 m/s and wind power density of 400-600 W/m2. The Weibull distribution parameters k and c were estimated using both graphical and approximated methods, with reasonably similar results.

1. CFD EVALUATION OF SUITABLE
SITE FOR WIND TURBINE OF THE
FLOW OVER TERRAIN
THITIPONG UNCHAI
Advisor
ASST.PROF.DR.ADUN JANYALERTADUN

2. Topics
∗ Introductions
∗ Objective
∗ Scope of works
∗ Research Procedure
∗ Theory, Literature reviews and Results of
∗ Potential Energy Assessments
∗ CFD simulations
∗ Pha Taem Hill
∗ Comparison of terrain and geometry shape
∗ Chart generation
∗ Discussions

3. Objective
∗ Investigate wind energy potential of Ubonratchathani
region.
∗ Find suitable site of wind turbine using CFD
simulations.
∗ Generate suitable site chart for trapezoid hill shape.

4. Scope of the work
∗ Wind data collection at 10, 30 40 m height.
∗ Wind energy potential assessment using Weibull
distribution.
∗ CFD simulation of Pha Taem hill.
∗ CFD simulation compare of terrain and geometry
shape.
∗ Generate wind turbine suitable site chart using
extrapolation technique.

5. Introduction
∗ Wind energy
Source : http://www.jewishpolicycenter.org/1415/investment-opportunity-of-the-21st-century

6. Introduction
At a height of 10 m Height of 50 m
Wind
Wind Wind
Power
Power Speed Power Speed
Class
Density (m/s) Density (m/s)
(W/m2) (W/m2)
1 0 – 100 0 – 4.4 0 – 200 0 – 5.6
2 100 – 150 4.4 – 5.1 200 – 300 5.6 – 6.4
3 150 – 200 5.1 – 5.6 300 – 400 6.4 – 7.0
4 200 – 250 5.6 – 6.0 400 – 500 7.0 – 7.5
5 250 – 300 6.0 – 6.4 500 – 600 7.5 – 8.0
6 300 – 400 6.4 – 7.0 600 – 800 8.0 – 8.8
7 400 – 1000 7.0 – 9.4 800 – 2000 8.8 – 11.9
Source : The U.S. Dept. of Energy defined a wind power scale in the Wind Energy Resource Atlas of the
United States, published in 1986.

7. Introduction
∗ Wind turbine site

8. Introduction
∗ Wind potential site in Thailand
Wind speed
Region Province Power Class Wind power
(50 m)
Tai Rom Yen National Park Nakhon Si Thammarat 6-7 8.00 – 11.90 600 – 2,000
Khao Luang National Park Nakhon Si Thammarat 6–7 8.00 – 11.90 600 – 2,000
Khao Pu - Khao Ya National Park Phatthalung 6–7 8.00 – 11.90 600 – 2,000
Wong – Jao National Park Tak 6 8.00 – 8.80 600 – 800
Doi Inthanon Chiang Mai 4 7.00 – 7.50 400 – 500
Kaeng Krung National Park Surat Thani 4–5 7.00 – 8.00 400 – 600
Pranom-Benja National Park Krabi 6 8.00 – 8.80 600 – 800
Ranot Songkhla 4 7.00 – 7.50 400 – 500
Songkhla Lake Songkhla 5–6 7.50 – 8.00 500 – 700
Gulf of Pattani Pattani 4 7.00 – 7.50 400 – 500
Hua Sai Nakhon Si Thammarat 3 6.40 – 7.00 300 – 400

9. Introduction
∗ Alternative Energy Development Plan: 2012-2021

10. Introduction
∗ Wind turbine site
Source : http://www.acusim.com/html/apps/windTurbSiting.html

11. Introduction
∗ Wind turbine site
Source : http://www.lec.ethz.ch/research/wind_energy/cfd

12. Introduction
∗ Wind turbine site
Source : Paul Stangroom. CFD Modelling of Wind Flow Over Terrain. Ph.D. thesis of University of Nottingham.
2004

13. Introduction
∗ Wind turbine site
Source : Keith W. Ayotte. Computational modelling for wind energy assessment. Journal of Wind Engineering
and Industrial Aerodynamics. 96: 2008, 1571–1590

14. Research Procedure
∗ Wind measurement and potential energy assessment.
∗ Simulation of Pha Taem hill.
∗ Comparison of terrain and geometry shape.
∗ Generate suitable position site chart.

15. Wind measurement
∗ Literature reviews
Researchers Heights Periods
A. Keyhani et al. 10 m 11 years
Ramazan Kose 10, 30 m 20 months
Meishen Li 10 m 5 years
Murat Gokcek et al. 10 m 5 months
Murat Gokcek et al. 6 – 12 m (11 stations) 3 years
W. Al-Nassar et al. 10, 30, 60 m* 46 years
* Extrapolation from the data using the Power-Law are presented.

16. Anemometer Wind Vane
Wind measurement
Parameters Details
Location Khong Chiam, UBN Anemometer
Height from sea
123 m
level
Sampling Period 1 hr
January 1, 2008 to
Data collected
December 31, 2010
Thermometer & Anemometer
Barometer
Data Logger

17. Wind measurement
2008 2009 2010 Average
4.0
∗ Wind speed
3.0
Wind Speed (m/s)
2.0
1.0
0.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month

18. Wind Speed (m/s)
0.0
1.0
2.0
3.0
4.0
0:00
2:00
4:00
10 m
6:00
8:00
10:00
30 m
12:00
Hour of Day
14:00
16:00
Wind measurement
18:00
40 m
20:00
22:00

19. Wind measurement
∗ Wind direction
N
15% NNE
NW 10% NE
5% ENE
W 0% E
ESE
SW SE
SSW SSE
S

20. Potential energy assessment
∗ Power of the wind
1
P = ρAV 3
2
∗ Wind power density developed by Weibull distribution
∞
P 1 1 3  k +3
= ∫ ρV f (V )dV = ρc Γ
3

A 02 2  k 
where k is shape factor and c is scalar factor

21. Potential energy assessment
∗ Weibull distribution
∗ Graphical method
ln[− ln (1 − F (V ≤ V0 ))] = − k ln (c ) + k ln (V0 )
 b 
 
 −k 
c=e
∗ Approximated method
−1.086
σ 
k = 
V 
 m
Vm
c=
Γ(1 + 1 / k )

22. Potential energy assessment
Meteorological Weibull approximated Weibull graphical
Month Vm
P/A E/A P/A E/A P/A E/A
(W/m2) (kWh/m2) (W/m2) (kWh/m2) (W/m2) (kWh/m2)
January 3.91 36.61 27.24 85.97 63.96 82.23 61.18
February 3.72 31.53 21.19 62.39 41.92 59.79 40.18
March 3.64 29.54 21.98 64.05 47.65 61.31 45.61
April 3.31 22.21 15.99 103.17 74.28 93.59 67.39
May 3.23 20.64 15.36 78.47 58.38 88.11 65.55
June 3.29 21.81 15.70 111.25 80.10 97.45 70.17
July 3.50 26.26 19.54 171.73 127.77 122.22 90.93
August 3.53 26.94 20.04 136.13 101.28 123.13 91.61
September 2.83 13.88 10.00 97.52 70.21 91.76 66.07
October 3.46 25.37 18.88 100.86 75.04 94.96 70.65
November 4.19 45.06 32.44 113.08 81.42 80.58 58.01
December 3.73 31.79 23.65 104.42 77.69 107.07 79.66
Annual 3.53 331.65 242.00 1,229.03 899.71 1,102.20 807.01
Note : Details of wind power density calculations are indicated in Appendix B

23. Pha Taem hill

24. Geographic Information System
∗ Geographic information system (GIS) is a system
designed to capture, store, manipulate, analyze,
manage, and present all types of geographical data.

25. Geographic Information System
∗ Literature reviews
Source : Atsushi Yamaguchi, Takeshi Ishihar and Yozo Fujino. Experimental study of the wind flow
in a coastal region of Japan. Journal of Wind Engineering and Industrial Aerodynamics 91 (2003)
247–264

26. Geographic Information System
∗ Literature reviews
Source : Paul Stangroom. CFD Modelling of Wind Flow Over Terrain. Ph.D. thesis of University of
Nottingham. 2004

27. Pha Taem hill
Contour Terrain topography
Parameters Details
Resolution 1 : 50,000
height 240 m
Front slope 20.06°
Rear slope 1.66°
Ground Rocky flat plate

28. Computational Fluid Dynamics
Applying the fundamental laws of mechanics to
𝜕𝜕
a fluid gives the governing equations for a fluid. The
+ 𝛻 ∙ 𝜌𝜌 = 0
conservation of mass equation
𝜕𝑡
𝜕𝑉
𝜌 + 𝜌 𝑉 ∙ 𝛻 𝑉 = −𝛻𝛻 + 𝜌𝑔 + 𝛻 ∙ 𝜏 𝑖𝑖
⃗
and the conservation of momentum equation
𝜕𝑡

29. Computational Fluid Dynamics
The term 𝜏 𝑖𝑖 in the equation is the Reynolds
𝜏 𝑖𝑖 = −𝑢′𝑖 𝑢′
stress for Reynolds Averaged Navier-Stokes equations
𝑗
𝜏 𝑖𝑖 = � 𝑖 � 𝑗 − 𝑢′𝑖 𝑢′
𝑢 𝑢
and the subgrid-scale stress for Large Eddy Simulation
𝑗

30. Turbulence Models dependence
• Literature reviews
Researcher Article Topics Knowledge
Comparison of
• k-l model indicated
turbulence models for • Use k-l and k-ε
Ove Undheim more inaccuracy
wind evaluation in model
complex terrain
Investigation of wind • Use k-ω, k-ε model
Pual Carpenter and • k-ω model
speeds over multiple • Imported model
Nicholas Locke improved k-ε
2D hills from GIS data
• Wind Atlas using
• Comparison LES
Computational extrapolation
simulation with
Keith W. Ayotte modelling for wind method to predict
European Wind
energy assessment speed in vertical
Atlas
and horizontal
A new low-Reynolds-
• low-Reynolds- • In low-Reynolds-
number nonlinear two-
D.D. Apsley and number flow number flow, RSM
equation turbulence
M.A. Leschziner • Use RSM , k-ε is better than k-ε
model for complex
model
flows

31. Turbulence Models
∗ Standard k-ε model
∗ The two-equation k-ε turbulence model and its variants
𝑘2
𝜇𝑡 = 𝐶𝜇 𝜌
are most commonly used in wind energy researches.
𝜀
where
k is turbulence kinetic energy
ε is dissipation rate

32. Turbulence Models
∗ Standard k-ω model
∗ One of the advantages of the k-ω formulation is the near
𝑘
𝜇𝑡 = 𝜌
wall treatment for low-Reynolds number computations.
𝜔
where
k is turbulence kinetic energy
ω is specific dissipation rate

33. Turbulence Models
∗ Reynolds Stress Model
the individual Reynolds stresses, 𝑢′𝑖 𝑢′ . The individual
∗ Using differential transport equations for calculation of
𝑗
Reynolds stresses are then used to obtain closure of the
Reynolds-averaged momentum equation.

34. Grid dependence
Properties Coarse Medium Fine
Dimension 2,000×1,000 m 2,000×1,000 m 2,000×1,000 m
First grid cell size 0.25493 m 0.04181 m 0.00709 m
Increasing rate 8% 10% 12%
Largest cell size 70.20 m 85.64 m 96.59 m
Coarse Medium Fine

35. Grid dependence
∗ Grid resolution sensitivity
1.10
Coarse x/H = 0 x/H = 1 x/H = 3
1.08
Medium
Height (Z/H)
1.06
Fine
1.04
Measure
1.02
1.00
0 1 2 3 4 0 1 2 3 4 0 1 2 3 4
Wind Speed

36. Initial and boundary conditions
∗ Literature reviews
Researcher Article Topics
Turbulence characteristics of
• Increased porous fences
T. Takahashi et al., wind over a hill with a rough
from 0% to 100%.
surface
• Simulated problem of wall
CFD simulation of the function.
Bert Blocken atmospheric boundary layer : wall • Irrespective of the wall
function problems functions and near wall grid
resolution.
On the use of the k–ε model in
D.M. Hargreaves and commercial CFD software to • Shear stress applied to the
N.G. Wright model the neutral atmospheric top boundary of the domain.
boundary layer
• The influence of a roughness
change spreads upwards in
2D simulations of terrain effects
O. Undheim the boundary layer
on atmospheric flow
downstream from the
roughness change.

37. Initial and boundary conditions
Parameters Type
Solver Segregated
Formulation Implicit
Space 3D
Time Unsteady
Velocity Formulation Absolute
Unsteady Formulation 1st Order Implicit
Turbulent Model - standard k-ε model
- standard k-ω model
- Reynolds Stress Model
Near Wall Treatment Enhance Wall Treatment
Model Constant Cμ , Cε1 , Cε2 , σk , σε
Air Density 1.225 kg/m3
Time Step 0.1 second
Max Iteration / Time Step 20,000
Inflow boundary Velocity inlet
Outflow boundary Pressure outlet
Top boundary Zero-gradient
Ground boundary Wall

38. Results
∗ Wind velocity profile at reference station
k-epsilon k-omega Reynolds stress measure
0.2
0.15
Height (Z/H)
0.1
0.05
0
0 0.5 1 1.5 2 2.5 3 3.5 4
Wind speed (m/s)

39. Results
∗ Comparison of increasing speed at hill top
k-epsilon k-omega Reynolds stress measure
0.20
0.15
Height (Z/H)
0.10
0.05
0.00
-20% -10% 0% 10% 20%
Wind speed increase (%)

40. Results
∗ Comparison of velocity in longitudinal direction
500
x/H = -1.0 x/H = 0 x/H = 1.0 x/H = 2.0
400
Height (Z/H)
300
200
100
0
0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4

41. Results
∗ Comparison of turbulence kinetic energy in
longitudinal direction
500
x/H = -1.0 x/H = 0 x/H = 1.0 x/H = 2.0
400
300
Height (m)
200
100
0
0.00 0.05 0.10 2 2
0.15 0.20 0 0.05 0.1 2 2 0.15 0.2 0.00 0.05 0.10 2 2 0.15 0.20 0.00 0.05 0.10 2 2 0.15 0.20
TKE (m /s ) TKE (m /s ) TKE (m /s ) TKE (m /s )

42. Comparison of Pha Taem geography
and geometry shape
0.5 Geometry Geography hill
Height
0
0 1 Distance 2 3
y = 0.3653x - 0.0352 y = -0.029x + 0.3994
R² = 0.9549 R² = 0.9543
0.4 0.4
Height
0.2 0.2
0.0 0
0.0 0.5 1.0 1.0 2.0 3.0 4.0
Distance Distance

43. Results
∗ Comparison of increasing speed
1.2 1.2 1.2
Vertical height (Z/H)
1.1 1.1 1.1
1.0 1.0 1.0
-20%-10% 0% 10% 20% -20%-10% 0% 10% 20% -20%-10% 0% 10% 20%
k-epsilon model k-omega model Reynolds Stress model

44. Results
∗ Comparison of increasing turbulence kinetic energy
1.2 1.2 1.2
Vertical height (Z/H)
1.1 1.1 1.1
1.0 1.0 1.0
0% 10% 20% 30% 0% 10% 20% 30% 0% 10% 20% 30%
k-epsilon model k-omega model Reynolds Stress model

45. Wind turbine suitable site chart
Typical Roughness Length
Land Cover Types
(m)
Farmland and grassy plains 0.002-0.30
Many trees and hedges, a few buildings 0.30
Scattered trees and hedges 0.15
Many hedges 0.085
Few trees (summer) 0.055
Crops and tall grass 0.050
Isolated trees 0.025
Few trees (winter) 0.010
Snow-covered cultivated farmland 0.002
Large expanses of water 0.0001-0.001
Flat desert 0.0001-0.001
Snow-covered flat ground 0.0001
Mud flats and ice 0.00001-0.00003
Parameters Details
Hill angle 5°, 10°, 15°, 20°, 25°, 30°, 35°, 40°, 45°
Wind speed 2, 4, 6, 8, 10 m/s
Roughness height 0.0001, 0.001, 0.01, 0.1 m

46. Wind turbine suitable site chart
0.20
Suitable site chart for trapezoid terrain
(Roughness 0.0001)
0.15 40°
height ( Time of hill height)
30°
20°
0.10 10°
40
30
0.05
20
10
0.00
0.0 0.1 0.2 0.3 0.4 0.5
length ( Time of hill height)

47. Wind turbine suitable site chart
0.20
Suitable site chart for trapezoid terrain
(Roughness 0.001)
0.15 40°
30°
20°
height
0.10 10°
40
30
0.05 20
10
0.00
0.0 0.1 0.2 0.3 0.4 0.5
length

48. Wind turbine suitable site chart
0.20
Suitable site chart for trapezoid terrain
(Roughness 0.01)
40°
0.15
30°
height ( Time of hill height)
20°
0.10 10°
40
30
20
10
0.05
0.00
0.0 0.1 0.2 0.3 0.4 0.5
length ( Time of hill height)

49. Wind turbine suitable site chart
0.20
Suitable site chart for trapezoid terrain
(Roughness 0.1)
40°
0.15
30°
20°
40
height
0.10 10° 30
20
10
0.05
0.00
0.0 0.1 0.2 0.3 0.4 0.5
length

50. Concluding Remarks
∗ Wind energy potential of UBN regions is about
1,102 – 1,229 W/m2
∗ The simulation results of Pha Taem hill indicated that
RSM method is most similar with measurements.
∗ Comparison of hill and geometry are 95.46% matching
terrain with 9.72% of difference results.
∗ Extrapolation technique have been used to generated
wind turbine suitable site charts.

51. Suggestion
∗ More measure station with more frequency and more
sensitive instruments should be provided to collect
most accurate wind data.
∗ The measurement data from the station in single row
do not indicated that same particle of the air.
∗ The 1:50,000 scales of data include much error into
the simulations because GIS data non-included any
obstacles.

52. Thank you