A Case Study

for Wind Resource Potential for Power Generation

M.Tech. Dissertation ( End Semester Presentation – I )

Guided by Prof.(Dr.) S. S. Chandel Lalit Anjum Roll No. 10M704

Energy Technology (M.Tech III Sem., 2nd yr.)

CENTRE FOR EXCELLENCE IN ENERGY AND ENVIRONMENTNATIONAL INSTITUTE OF TECHNOLOGY,

HAMIRPUR-177005December 2011 1

IntroductionGeneration of electrical energy from wind can be economically

achieved only where a significant wind resource exists. Therefore site selection is the important constituent under Preliminary survey.

As there is a cubic relationship between wind velocity and output energy, sites with small percentage differences in average wind speeds can have substantial differences in available energy.

Therefore, accurate and thorough monitoring of wind resource at potential sites is a critical factor in the siting of wind turbines (in our case SWTs).

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IntroductionWind resource availability in the low windy locations can also be

judicially exploited using wind – solar hybrid systems.Micro-analyzing the potential gives the effective frequency

distribution of mean wind speeds at the site.Thus processing and observing the wind data minutely proves to be

the efficient technique for wind potential estimation.

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OutlineI. Wind Potential Estimation TechniquesII. Literature ReviewIII. Problem IdentificationIV. Research ObjectivesV. Work Plan and Methodology. VI. Work doneVII. Future work to be carried out…VIII.References

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I. Wind Potential Estimation Techniques

Preliminary Investigation of site1. Beaufort Scale for the estimation of wind speeds. 2. Biological Indicators as a tool for estimation of wind

regimes.

Detailed Wind characterization for site1. Wind resource mapping using WAsP simulations.2. Determination of wind characteristics using Weibull

Probability distribution model

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Ground Survey of the site for identification of wind pockets

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1. Beaufort Scale for the estimation of wind speeds…

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2. Mathematical Models for Biological Indicators as a source of wind speeds estimation , (Modified Griggs-Putnam Index) by Wade-Hewson

Wade-Hewson Relation

1. Deformation Index (D) For Conical fir pine trees: D = α/β + γ/34° For Broadleaved trees: D = a / b + γ/34°2. Velocity relation with D V = D x + y x , y are site specific constants

calculated with Regression Analysis.

3. Detailed analysis of wind speeds using Weibull Probability distribution in WAsP modelling

Fig. 1 Weibull Distribution 02/05/23 10

1( ) ( / )( / ) exp ( / )k kF v k c v c v c

• The Weibull distribution function (wind duration curve), which is also a two parameter function for wind speed, is expressed mathematically as

where ‘‘V’’ is the wind speed and shape parameter ( k ) and scale parameter ( c ) are parameters determined from the data.

( )eymC e

• The data are least squares curve-fit with a line of slope m and intercept ye, from which

II. Literature ReviewYear Authors Journal/ Conf. Title Conclusion

2011 Mounir AKSAS, Amor GAMA.…………..

Energy Procedia, ELSEVIER,Sciencedirect.

Assessment of wind and solar energy resources in Batna, Algeria.

Estimation of wind power availability and choosing right wind turbine using Weibull estimation and Windographer software.

2008 James Jensen……………

Department of Community &Economic Development, Alaska Energy Authority, USA

Wind Resource Assessment forNunam Iqua, Alaska, USA.

Annual wind data and analysis of the potential for energy production with Windographer software.

2003 B. Ozerdem, M. Turkeli.…….

Renewable Energy,PERGAMON,Sciencedirect.

Wind characteristics atIzmir Institute of Technologycampus, Turkey

Measureddata set and its evaluation using WasP and windPRO softwares.

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Year Authors Journal/ Conf

Title Conclusion

1997 Bruce H. Bailey, Scott L. McDonald…………

NREL Subcontract No. TAT-5-15283-01

Wind Resource Assessment Handbook-Fundamentals for Conducting a Successful Monitoring Program

Planning and conducting a wind resource measurement program.

2005 T.V. Ramachandra,B.V. Shruthi…………

Energy Conservation and Management,ELSEVIER,Sciencedirect.

Wind Energy PotentialMapping in Karanataka,India using GIS.

Seasonal and annual wind resourse analysis and wind resource estimation done using the GIS & data from IMD.

2005 B. Ozerdem, H.M. Turkeli………

Renewable Energy,ELSEVIER,Sciencedirect.

Wind energy potential estimation and micrositting atIzmir Institute of Technology Campus, Turkey

Predicting the wind energy content and micrositting of small wind turbines.

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Year Authors Journal/ Conf

Title Conclusion

1986 A. Robertson…………

International Journal of Biometeorology

Estimating Mean Wind flow in Hilly Terrain fromTamarack (Larix laricina (Du Roi) K. Koch) Deformation

Comparison of different biological indicators for investigation of wind regimes..

2002 Scott Cullen……….

Journal of Arboriculture.

Trees and Wind: Wind Scales and Speeds.

Studying the trees deformation due to the wind loads and prevalent wind characterisation.

1994 Mick Sagrillo………….

Home Power #40-41

Site Analysis forWind GeneratorsPart 1: Average wind Speeds Part II: Your site

Ways of estimating the wind resource in your area. Site analysis and micro-sitting of wind turbines.02/05/23 13

III. Problem IdentificationA study of Wind Resource Potential for Power Generation To compare the results for the energy estimation from the minute

and hourly averaging methods.Identifying the wind profiles at higher altitudes using mathematical

model of wind power law.Identifying the suitable hybrid wind turbines systems for the site.Building of the wind profile map of the NITH campus.

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IV. Objectives

Ground Survey to seek the sites and locations for assessment.

Finding the relationship between biological indicators available and the prevailing wind speeds in the limited region

Micro-analysis of monthly and seasonal variation of wind flow to determine wind speed probability distribution.

Determining the amount of energy from the available wind potential at NIT Hamirpur.

To study the suitability of wind resource for solar - wind the hybrid systems.

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V. Work Plan and Methodology1. On ground investigation of the site under observation for terrain features

for concentration of wind.2. Digitization of the contour map of NITH campus using AutoCAD,

ArcGIS software platforms.3. Collection and analysis of wind monitoring station data for the prevailing

wind regimes from 2nd May 2011 to 24th Nov 2011.4. On site measurements and study of biological indicators in the regions

identified in step 1.5. Analysis of wind characteristics and determination of observed wind

climate (OWC).6. To prepare the wind resource map (wind distribution profiles).7. Extrapolation for wind profile at different heights.8. Calculating the energy available from the derived wind potential.

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Experimental Platform for monitoring Wind Regimes.1. 10 m GI triangular tower with

guy wires.2. Anemometer. 3. Sensor mounting arm.4. PV panel for back up

power.5. Pyranometer.6. Humidity sensor.7. Location: C.E.E.E Roof Top8. Elevation: 896 m (886+10)

(a.s.l)

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Experimental set up and Equipments

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Anemometer RMY 50103-10-L1. The Wind Monitor measures

horizontal wind speed and direction.2. The main housing, nose cone,

propeller, and other internal parts are injection moulded U.V. stabilized plastic.

3. Propeller rotation produces an AC sine wave signal with frequency proportional to wind speed.

4. With a constant voltage applied to the 10K potentiometer, the output signal is an analogue voltage directly proportional to wind direction angle.

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Hand Held Anemometer KM-909Airflow measurements &

monitoring.Portable, simple and one–hand operation. Weight : Approx 390g (including

battery and probe).Measurement range 0-100 m/s.Accuracy available ± 0.3 m/s

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VI. Work Done in semester- III, July-Dec 20111. Terrain mapping commenced with noting of obstacle data.2. Partial digitization of NITH contour map done.3. Ground Survey done for preliminary site identification.4. Actual measurements recorded with portable

anemometer.5. Comparative study done to validate the measurements

with wind monitoring station data.6. Influence of terrain on wind directional distribution

studied.7. Wind influenced trees investigated as biological indicators

for wind speed estimation.8. Micro-analysis done to study the energy generation from

the prevailing wind regimes.9. Hybrid wind turbine systems suggested for the site.

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I. Data collection using several devices …. Devices installed on Wind Monitoring Station at NIT

HAMIRPUR campus.

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Devices Range Accuracy Resolution

Operating Temp.

Output

Anemometer (P) KM-909

0 – 30 m/s ± 3% 0.01 0 – 50 °C Voltage

HHA RMY-50103-10-L

0 - 100 m/s ± 0.3 m/s 0.001 -50 - +50°C AC voltage

Temperature P- 41342

-50 - +50°C ± 0.3°C 0.1 -50 - +50°C Voltage

Humidity P - 41342

0 – 100 %RH ± 1 %RH

%1 -50 - +50°C Voltage

PressureP – 61302V

500-1100 hPa 0.3 hPa 0.01 hPa -40 - +60°C Voltage

3 (c) Terrain map of NIT campus

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Defining obstacles in WAsP

α 1 angle from N to first corner [º]R1 radial distance to first corner

[m]α 2 angle from N to second corner

[º]R2 radial distance to second

corner [m]h height of obstacle [m]d depth of obstacle [m]P estimated porosity (fraction 0-1)

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Ground Survey for distance among obstaclesParameters of buildings from the foot of Wind Monitoring Tower

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Building α 1 R 1 α 2 R2 d h P

DBH 256.5 313.5 58 18.5 0

NKH 182.4 150 65 21 0

MMH 370.5 456 72 30 0

MED 57 60 85.2 19 0

Workshop 50 53 57 9 0

Library 247.95 239.4 45.2 25 0

Auditorium

296.4 324.9 47 25 0

VLH 205.2 205.2 55 22 0

CED & SBI

50 80 70 20

Wind monitoring tower on NITH Contour map

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Wind tower

Digitization of Contour map of NIT campus

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Digitization of contour map was done in AutoCAD, WAsP Map Editor 10.1.1

Purple regions is at the higher altitude above m.s.l

Dark Greenish region is the forest covered area.

Orange denotes the regions of lower altitudes.

Purple : 805-899 m Dark Green : 785-799 mOrange : 745-774 m

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Digitized Contour Map of NIT campus

Wind Directional and Frequency Distribution at NIT Hamirpur campus from 2nd May to 24th Nov 2011.

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Winter winds

Summer winds Lower

Shiwalikrange931m a.s.lW

ind

chan

nel

Visualization of the roughness and orography map

North

South

EastWest

896m a.s.l

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Winter winds

Summer winds

Lower Shiwalik Ranges931m a.s.l

Analysis of the dataIn the summer months from May to July the wind regimes mainly lie

within 30° SSW mainly due to the advancing monsoons.In the winter months the winds blow from the higher reaches of

Himalayas towards the plains.In winters, the air being cold is heavy ,thus it rushes downwards

towards plains.The winds usually gets channelized due to the topographical effect of

the surroundings hills of NIT campus.

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Observations and inferencesThe wind speed measurements were taken at the highest available

elevations in the NITH campus on different days of Oct 2011.The places identified were Manimahesh Hostel (Highest point),

CEEE & MED (wind channel) and CEEE Roof Top.With the measurement of wind speeds with Hand Held Portable

Anemometer at the initially identified sites in the campus, it was observed that the readings taken were in conformity with the data logged by the Electronic Wind Monitoring Data Logger.

Further it was also observed that there was very less deviation of the wind speeds on ground measurements at above mentioned places and anemometer on wind monitoring tower.

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Study of Biological Indicators as tool for wind estimation

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Preliminary readings and measurements of the biological indicators i.e. trees bent under the influence of the wind are taken for the analysis.

The linear regression will be performed on the values obtained for the site under study.

The constant values then obtained will be calibrated for the relationship between Deformation Index and the wind speeds for the site.

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Preliminary study of Deformation-Index

Micro-Analysis of Wind profiles from 2nd May 2011 to 24th Nov 2011

1. It involves the periodic assessment and data processing for deriving the useful information out of it.

2. The study of wind data reveals the prevailing variation of the wind speeds with time and season.

3. The information gathered from the analysis and mathematical modeling brings out the best fit results for further processing and system designing.

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May-2011

June-2011

Daily hours

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Winter wind

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18m

50m

100m

51

1429 hours

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Analysis and findingsEnergy estimation from different turbines, confirms the fact that the lower

wind speeds can also be utilized for the small applications like battery charging, street lighting etc.

The rated power at a specific wind speed has very little to do with how much energy the wind turbine will deliver to the load. Much of the time small wind turbines operate at well below their rated speed. By lowering the rated speed, we can effectively lower the kW rating of the wind turbine.

The wind regimes present here can be effectively utilized if the micro- analysis is done keeping the minutes as the averaging interval rather than the hourly intervals as in case of utility scale modeling.

The site under present study show the appreciable amount of energy available for the small wind turbines ranging from 100 W to 5 kW.

Therefore, it is suggested from the above exercise that the micro-analysis is the effective tool in assessing the wind potential at the low windy places like Hamirpur H.P.

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Models SNT 1 SNT 10 SNT 25 SNT 50 SNT 75 SNT 100

Equivalent Rated Output 700w 1,400w 2,800w 5,000w 7,500w 10,000w

Storage Capacity Per day @ Avg. Wind speed 5.5 m/s

2.5kwh 5kwh 10kwh 20kwh 30kwh 40Kwh

Suggested Solar PV Modules 150w 300w 600w 1200w 1800w 2400w

Rated capacity of Hybrid System 0.85kw 1.7kw 3.4kw 6.8kw 9.3kw 12.4kw

Suggested battery Bank For Hybrid system

3.6kw 7.2kw 14.4kw 28.8kw 43.2kw 57.6kw

No. of blades Three Three Three Three Three Three

Rotor Diameter 6 feet 10 feet 14 feet 14 feet 20 feet 20 feet

Rated wind Speed 11m/s 11m/s 11m/s 11m/s 11m/s 11m/s

Start up wind Speed 2.0m/s 2.2m/s 2.8m/s 3.0m/s 3.0m/s 3.0 m/s

Type of Load AC/DC AC AC AC AC/Three Phase

AC/Three Phase

Inverter 700 VA 1400 VA 3500 VA 3500 VA 5000 VA 5000 VA

Tower Erection Tilting pipe

Tilting pipe

Tripod Tower

Structure

Tripod Tower

Structure

Tripod Tower

Structure

Tripod Tower

Structure

SUPERNOVA SMALL WIND TURBINE WITH HYBRID GENERATOR SYSTEM

Energy Ball V100

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Cut-in speed 2.7 m/s

Due to the unusual and exceptional aerodynamics characteristics of the Energy Ball®, it creates a wind flow pattern that converges first and is then accelerated through the rotor, resembling the rapids in a river (the so-called Venturi effect). This translates into a higher aerodynamic efficiency compared to conventional wind turbine designs.

The Energy Ball® starts producing electric energy as from very low wind speeds and has therefore a very low standstill time. The unique design makes that an electricity producing Energy Ball® is virtually transparent.

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Wind - SolarHybrid Systems

SuperNova 10

Energy Ball V100

Energy Ball V100

VII. Further work to be carried out…To prepare the topographical vector map of NITH campus. To collect the wind data for the maximum period available. Analysis of the wind data using different softwares. Analysis of data with WRPLOT, WAsP softwares. Estimation of annual energy generation. Calculation of wind speeds at different heights by mathematical models Study of energy generation with available wind resource.

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VIII. References 1. Mounir AKSAS, and Amor GAMA, “Assessment of wind and solar

energy resources in Batna, Algeria,” Energy Procedia ELSEVIER Journal, vol.6, pp 459-466, 2011.

2. James Jensen, “Wind Resource Assessment for Nunam Iqua, Alaska ,” Department of Community & Economic Development, Alaska Energy Authority, USA , pp. 1-9, Feb. 2007.

3. B. Ozerdem, and M. Turkeli, “An investigation of wind characteristics on the campus of Izmir Institute of Technology, Turkey,” Renewable Energy PERGAMON Journal, vol. 28, pp 1013-1027, 2003.

4. Tsang-Jung Chang, Yu-Ting Wu, Hua-Yi Hsu, Chia-Ren Chu, and Chun-Min Liao, “Assessment of wind characteristics and wind turbine characteristics in Taiwan,” Renewable Energy PERGAMON Journal, vol. 28, pp 851-871, 2003.

5. N. Vogiatzis, K. Kotti, S. Spanomitsios, and M. Stoukides, “Analysis of wind potential and characteristics in North Aegean, Greece,” Renewable Energy ELSEVIER Journal, vol. 29, pp 1193-1208, 2004.

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References6. A. Keyhani, M. Ghasemi-Varnamkhasti, M. Khanali, and R. Abbaszadeh, “An

assessment of wind energy potential as a power generation source in the capital of Iran, Tehran,“ Energy ELSEVIER Journal, vol. 35, pp.188–201, 2010.

7. A. Al-Mohamad, and H. Karmeh, “ Wind energy potential in Syria,” Renewable Energy PERGAMON journal, vol. 28, pp.1039-1046, 2003.

8. Julie Lundquist, Scott Schreck, and William Shaw , “Research Needs for Wind Resource Characterization ,” U.S. Department of Energy Workshop , Broomfield, Colorado, January 14 – 16, 2008, pp.45-59.

9. Paul Gardner, Andrew Garrad, Lars Falbe Hansen, and Nicholas Fichaux, “Wind energy-The Facts, E-chapter Series EWEA,” www.platform.eu, 2008.

10. Bruce H. Bailey ,and Scott L. McDonald, AWS Scientific, Inc. CESTM, 251 Fuller Road Albany, NY 12203, “ Wind Resource Assessment Handbook, Fundamentals for Conducting a Successful Monitoring Program,” National Renewable Energy Laboratory1617 Cole Boulevard Golden, CO 80401, NREL Subcontract No. TAT-5-15283-01, April 1997.

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References11. B. Ozerdem, and M. Turkeli, “Wind energy potential estimation and micrositting on

Izmir Institute of Technology Campus, Turkey,” Renewable Energy ELSEVIER Journal, vol. 30, pp. 1623-1633, 2005.

12. Paritosh Bhattacharya, and Rakhi Bhattacharjee, “ A Study on Weibull Distribution for estimating the parameters,” Journal of Applied Quantitative methods, vol. 5 No. 2, pp. 234-241, 2010.

13. www.WINDPOWER.org © 199814. WAsP 10.01.0100 : http://www.wasp.dk/download/ WAsP 10.01.0100 15. WRPLOT View 7.0.0: http://www.weblakes.com/products/wrplot7.0.0/index.html16. Rakesh Bakshi, “Wind Energy in India”, IEEE Power Engineering Review, pp.16-

18, September 2002.17. D.V. Giri, “9th NTC in Wind Energy at C-WET, Chennai,” July 2010.18. Nilesh Diwakar, Subramanyam Ganesan, and Siraj Ahmed. “Prediction of wind

power potential by wind speed probability distribution in a hilly terrain near Bhopal, Madhya Pradesh”, International Journal on Emerging Technologies, vol.1 No. 1, pp.80-86, 2010.

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References19. A. Robertson, “Estimating Mean Wind flow in Hilly Terrain from Tamarack (Larix

laricina (Du Roi) K. Koch) Deformation”, International journal of Biometeorology, vol. 30, No. 4, pp.333-349, 1986.

20. E.W. Hewson, J.E. Wade, and R.W. Baker, Department of Atmospheric Sciences, Oregon state University, Oregon 97331, “A Handbook on the use of trees as an indicator of wind power potential,”,Department of Energy, Division of Distributed Solar Technology, Federal Wind Energy Program, DOE contract No. EY-76-506-227, Task Agreement-24, June 1979.

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THANK YOU

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