A presentation of the work I did during my summer internship at C-WET

1. A STUDY ON WIND RESOURCE ASSESSMENT
Minor Project
done at
C-WET, Chennai
May 2010 - July 2010
Presented by
S. Lakshmi
0907MER

2. Objectives
2
• Exhaustive Study of WRA methodology, steps and
concepts
• Study of different kinds of terrain features and their
influence on wind speeds.
• Calculation of the essential parameters of WRA from
the measured data.
• Estimation of energy output for the given data.
• Study of types of modelling for wind flow analysis.

3. Schedule & details of
3
activities
Month Week Activity
May 4 Study of Wind Resource Assessment in general
1 Visit to Wind Turbine Test Station, Kayathar and Muppandal Wind farm
2 Study of Topographical inputs
Exercise on data analysis and study of GPS, maps, projections and
June 3
instrumentation
Study of Wind turbine generator characteristics, power regulation and power
4
curve
1 Study of modelling – Meso and microscale models
2 Exercise on energy prediction
July Exercise on NCEP/NCAR reanalysis data and Joint frequency distribution
3
calculation
4 Documentation

4. Wind energy scenario
4
Gross Total Capacity (MW)
State Potential till
(MW) 31.03.09
Andhra Pradesh 8968 122.5
Gujarat 10,645 1566.5
Karnataka 11,531 1327.4
Kerala 1171 27.0
Madhya Pradesh 1019 212.8
Maharashtra 4584 1938.9
Orissa 255 -
Rajasthan 4858 738.4
West Bengal 1.1
Tamil Nadu 5530 4304.5
Others 3.2
Total
48,561 10242.3
(All India)
Wind power installations worldwide Indian wind power installation
(Source: World Wind Energy Report, 2009) (Source: http://www.inwea.org/aboutwindenergy.htm)

5. Basic science of wind
5
power
 Wind – manifestation of solar power and rotation of
earth
Kinetic energy = (mV2)/2
Where m= Density (ρ) x Volume
m= ρ x A x V x time
Therefore, Kinetic energy = (ρ x A x V3 x time)/2
Kinetic energy / time = Power = (ρ x A x V3)/2
Power / Area = Wind power density = (ρ x V3)/2
 WRA involves Regional assessment and Siting
 Need for modelling
• Meso- scale modelling
Large area screening & Field visit
Validation (Data collection & Screening)
Micro siting
• Micro-scale modelling

6. 6
Overview
of WRA
Source: http://www.wind-energy-the-facts.org/images/fig/chap1/2-2.jpg

7. Inputs
7
Climatological Topographical Wind turbine
inputs inputs generator
characteristics

8. Climatological and
8
topographical inputs
• Monthly wind speed
• Terrain
• Wind power density – at measured
level as well as extrapolated to 50 • Roughness
m level • Obstacle
• Power law index • Orography
• Energy pattern factor • Maps and map projections
• Air density • SRTM
• Turbulence intensity • GPS
• Weibull parameters • GIS
• Wind rose • UTM co-ordinate system
Climatological Topographical
inputs inputs

9. Modeling
9
Meso-scale modeling
NCEP/NCAR Generalised
reanalysis regional
long term Orography Roughness wind climate
data for large
domains
Micro-scale modeling
Regional
Measured Wind Wind Terrain Wind
Time Speed direction features Climate for
Series the given
location
Combined meso and micro scale modeling
Ex: WAsP- KAMM model

10. WTG Characteristics
10
1. Classification
• Constant speed induction
Generator (asynchronous) machines
• Variable speed induction generator
Axis of • Vertical axis (Darrieus
type) concepts • Synchronous generator (only variable
rotation • Horizontal axis speed)
• Single bladed • Turbines with gear box (mostly
Blade • Two bladed Gearbox constant speed generators)
• Turbines without gear box (mostly
concept •
•
Three bladed
Multi bladed
concepts slow variable speed synchronous
generators used)
Power • Stall regulated
regulation • Pitch regulated
Tower
•
•
Tubular towers (steel)
Lattice towers (steel)
• Active stall concept
concept concepts • Flexible towers (steel)
• Concrete tubular towers

11. WTG Characteristics
11
2. Power regulation
Passive
stall
The driving aerodynamic forces can be reduced by control
• altering the rotor blade’s aerodynamic angle of attack
• reducing the projected rotor-swept area or Active
Yaw
pitch
• changing the flow velocity at the rotor blades control
control
Power
regulation
Passive
Active stall
pitch
control
control
Pitch adjustment (left) and yaw adjustment (right)

12. WTG Characteristics
12
3. Power curve and thrust curve
• Thrust curve - related to losses of energy
transformed onto turbulent kinetic energy.
• Used to calculate energy losses due to wake
effect.
• For this reason the thrust curve is also
Source: http://zone.ni.com/devzone/cda/tut/p/id/8189 included as input.
4. Annual energy output prediction
• Annual Frequency distribution
Capacity factor = Average loads for a period
• Power curve of specific turbine of time/ Plant capacity
• Capacity factor
• Losses

13. WTTS, Kayathar
13
Need for • To analyze the suitability
• To satisfy the requirements of purchaser
Testing • For verification and monitoring
• For the investor to analyse performance
Testing • Power performance
• Yaw efficiency
done • Safety and functional testing
• Load measurements
Facilities at • 2 test beds in Kayathar, conforming to the IEC
standards, without obstacles upto 1.5 km.
• Nine 200 kW capacity Micon machines
the WTTS • A 600 kW Suzlon machine
• 2 MW Kenersys machine under installation

14. Snapshots from WTTS
14

15. ஆரல்வாய்ம ாழி
15

16. Exercises & results
16
1. Wind resource assessment Wind Speed
Frequency distribution (%)
(m/s) at 50 m at 30 m at 10 m
Mean Wind
Energy 0-2.5 2.407 4.120 7.361
Height Wind Standard Turbulenc Power
Pattern 2.5-3.5 5.347 7.384 13.287
(m) Speed Deviation e Intensity Density 3.5-4.5 11.921 14.398 18.889
Factor
(m/s) (W/m2) 4.5-5.5 16.065 17.014 17.037
50 6.58 1.06 0.179 1.37 238.16 5.5-6.5 16.111 15.764 16.343
6.5-7.5 14.676 14.514 12.338
30 6.14 1.14 0.208 1.41 199.8
7.5-8.5 13.380 11.690 8.472
10 5.3 1.21 0.258 1.47 133.58 8.5-9.5 9.861 8.333 4.352
9.5-10.5 6.343 4.421 1.134
10.5-11.5 2.338 1.250 0.347
11.5-12.5 0.718 0.556 0.347
12.5-13.5 0.556 0.394 0.093
13.5-14.5 0.231 0.139 0.000
14.5-15.5 0.046 0.023 0.000
15.5-16.5 0.000 0.000 0.000
16.5-17.5 0.000 0.000 0.000
17.5-18.5 0.000 0.000 0.000
18.5-19.5 0.000 0.000 0.000
19.5-20.5 0.000 0.000 0.000
>20.5 0.000 0.000 0.000

17. Exercises & results
17
2. Energy estimation
3. Long term wind speed estimation using NCEP/NCAR Reanalysis data set
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Avg
2000 3.9 2.8 4.5 6.4 7.1 6.2 4.9 3.4 3 2.1 1.4 2.1 4
2001 2.5 3.3 2.1 4.7 7.7 5.4 4.5 3.5 2.7 1.8 0.9 1.3 3.4
2002 1.3 2.3 3.1 5.1 7.5 3.8 7.2 2.6 3.9 1.3 0.6 2.4 3.4
2003 1.9 2.5 2.9 4.1 6.8 6.3 3.3 3.8 2.9 1.7 2.3 2.1 3.4
2004 1.7 2.2 3.2 5.2 4.5 4.4 4.4 3.3 1.3 0.3 0.5 1.3 2.7
2005 2.8 4.3 3.5 3.7 5.7 4.5 4.7 4.1 1.4 1 0.9 0.6 3.1
2006 2.9 2.9 2.5 3.8 5.9 4.2 4.5 2.4 1.2 0.9 0.1 2.3 2.8
2007 1.8 3.4 3.1 3.2 5.6 3.9 4.4 2.8 1.7 1.6 1.2 1 2.8
2008 1.7 2.4 2.4 3.5 8.2 6.1 5.6 3.7 0.9 1.3 0.9 0.7 3.1
2009 2.5 3.2 3.2 5.3 6.4 5.1 3.5 4.2 3.5 1.1 0.7 1.6 3.4
2010 1.3 2.6 3.9 5.3 7.3 5.7 4.35

18. Exercises & results
18
Trend of average
wind speeds for ten
years

19. Exercises & results
19
Number of hours
Direction
N NE E SE S SW W NW
Speed
(m/s)
1 361.75 361.75 361.75 361.75 361.75 361.75 361.75 361.75
3 345.19 99.84 25.93 2.71 7.35 136.99 171.44 13.54
4 318.54 92.13 23.93 2.5 6.79 126.42 158.2 12.5
5 126.57 22.89 4.2 0 0.93 165.81 374.11 21.48
6 118.79 21.48 3.95 0 0.88 155.62 351.12 20.16
Joint frequency
7 109.43 19.79 3.63 0 0.81 143.34 323.43 18.57
distribution
8 30.67 2.36 0 0 0 196.99 586.24 37.75
9 9.98 0.77 0 0 0 64.12 190.84 12.29
10 6.1 0.47 0 0 0 39.21 116.7 7.51
11 1.52 0 0 0 0 16.67 73.23 8.59
12 0.74 0 0 0 0 8.17 35.88 4.21
13 0.38 0 0 0 0 4.17 18.31 2.15
14 0.18 0 0 0 0 2 8.79 1.03
15 0.11 0 0 0 0 1.17 5.13 0.6
16 0.05 0 0 0 0 0.5 2.2 0.26
17 0.02 0 0 0 0 0.17 0.73 0.09
18 0.02 0 0 0 0 0.17 0.73 0.09
JFD (%) 16.28 7.08 4.82 4.18 4.31 16.2 31.64 5.95

20. Exercises & results
20
Observed wind
climate

21. Discussion and
21
conclusion
WIND RESOURCE ASSESSMENT
MWS of 6.58 m/s and MWPD of 238 W/m2 at 50 m. Very good wind power potential for this
particular month. With further data for the rest of the year and any turbine’s characteristics (power
curve), the annual energy output can also be predicted.
ENERGY ESTIMATION
Annual energy output predicted is slightly over 50 lakh units. It also gives a capacity factor of about
32% (without losses), which justifies setting up a wind farm using this particular class of wind
turbines in this location.
NCEP/ NCAR REANALYSIS DATA SET
Given the actual measured values of wind speeds during any intermediate period of time, necessary
comparison and correlation can be done with this data to analyse and thus calculate the percentage
uncertainty factor involved in the energy estimation using this data.
JOINT FREQUENCY DISTRIBUTION
The annual wind speed and direction data recorded by old Second Wind data logger has been
converted to a WAsP compatible .tab file format. This file can be used to further obtain the OWC for
this location, which will also allow an estimation of the mean annual wind speed and wind power
density value. Following that, micrositing can be undertaken.

22. References
22
Centre for Wind Energy Technology (C-WET) 2005, Wind Energy Resource Survey in India –VII, Centre for Wind Energy
Technology, Chennai.
Centre for Wind Energy Technology (C-WET) 2006, Course material – 2nd International Training Program on Wind Turbine
Technology and Applications, Centre for Wind Energy Technology, Chennai
Centre for Wind Energy Technology (C-WET) 2006, Course material – National Training Program on Wind Farm Development and
Related Issues, 1st and 2nd September 2005, Centre for Wind Energy Technology, Chennai
Centre for Wind Energy Technology (C-WET) 2010, Indian Wind Atlas, Centre for Wind Energy Technology, Chennai
European Wind Energy Association (EWEA) (2009), Wind Energy – The Facts – A guide to the technology, economics and future of
wind power, Earthscan, London
Gary L, Johnson 2006, Wind Energy Systems, Electronic Edition, Manhattan
Gipe, Paul 2004, Wind Power, James & James (Science Publishers) Ltd, London
Hau, Erich 2006, Wind Turbines – Fundamentals, Technologies, Application, Economics, 2nd edition Springer
Mani, A 1990, Wind Energy Resource Survey for India – I, Allied Publishers, New Delhi.
Mani, A 1992, Wind Energy Resource Survey for India – II, Allied Publishers, New Delhi.
Mani, A 1994, Wind Energy Resource Survey for India – III, Allied Publishers, New Delhi.
Manwell, JF, McGowan, JG & Rogers, AL 2002, Wind Energy Explained, John Wiley & Sons Ltd., England
Pillai, GM 2006, Wind Power Development in India, World Institute of Sustainable Energy, Pune
Sathyajith Mathew 2006, Wind Energy – Fundamentals, Resource Analysis and Economics, Springer
Skamarock. W., Dudhia. J. et al., (2005) A Description of the Advanced Research WRF Version 2, NCAR Technical note.
Stiebler, Manfred 2008, Wind Energy Systems for Electric Power Generation, Springer, Heidelberg
Strack, M & Riedel, V 2004, State of the Art in Application of Flow Models for Micrositing, DEWEK 2004 Proceedings
Vaughn Nelson 2009, Wind Energy – Renewable Energy and the Environment, CRC Press, New York
World Wind Energy Association (WWEA) 2010, World Wind Energy Report, World Wind Energy Association, Germany
Indian Wind Energy Association (InWEA) 2007, viewed 30 July 2010, http://www.inwea.org/