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  • 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.)



  • 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).


  • 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.


  • OutlineWind Potential Estimation TechniquesLiterature ReviewProblem IdentificationResearch ObjectivesWork Plan and Methodology. Work doneFuture work to be carried outReferences **

  • Wind Potential Estimation Techniques

    Preliminary Investigation of siteBeaufort Scale for the estimation of wind speeds. Biological Indicators as a tool for estimation of wind regimes. Detailed Wind characterization for siteWind resource mapping using WAsP simulations.Determination of wind characteristics using Weibull Probability distribution model**

  • Ground Survey of the site for identification of wind pockets**

  • **

  • 1. Beaufort Scale for the estimation of wind speeds **

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

    1. Deformation Index (D) For Conical fir pine trees: D = / + /34 For Broadleaved trees: D = a / b + /342. 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 **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. The data are least squares curve-fit with a line of slope m and intercept ye, from which

  • II. Literature Review**

    YearAuthorsJournal/ Conf.TitleConclusion2011Mounir 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.2008James JensenDepartment of Community &Economic Development, Alaska Energy Authority, USAWind Resource Assessment forNunam Iqua, Alaska, USA.Annual wind data and analysis of the potential for energy production with Windographer software.2003B. Ozerdem, M. Turkeli..Renewable Energy,PERGAMON,Sciencedirect.Wind characteristics atIzmir Institute of Technologycampus, TurkeyMeasureddata set and its evaluation using WasP and windPRO softwares.

  • **

    YearAuthorsJournal/ ConfTitleConclusion1997Bruce H. Bailey, Scott L. McDonald NREL Subcontract No. TAT-5-15283-01Wind Resource Assessment Handbook-Fundamentals for Conducting a Successful Monitoring ProgramPlanning and conducting a wind resource measurement program.2005T.V. Ramachandra,B.V. ShruthiEnergy 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.2005B. Ozerdem, H.M. TurkeliRenewable Energy,ELSEVIER,Sciencedirect.Wind energy potential estimation and micrositting atIzmir Institute of Technology Campus, TurkeyPredicting the wind energy content and micrositting of small wind turbines.

  • **

    YearAuthorsJournal/ ConfTitleConclusion1986RobertsonInternational Journal of BiometeorologyEstimating Mean Wind flow in Hilly Terrain fromTamarack (Larix laricina (Du Roi) K. Koch) DeformationComparison of different biological indicators for investigation of wind regimes..2002Scott Cullen.Journal of Arboriculture.Trees and Wind: Wind Scales and Speeds.Studying the trees deformation due to the wind loads and prevalent wind characterisation.1994Mick Sagrillo.Home Power #40-41Site Analysis forWind GeneratorsPart 1: Average wind Speeds Part II: Your siteWays of estimating the wind resource in your area. Site analysis and micro-sitting of wind turbines.

  • 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.


  • 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 regionMicro-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.


  • V. Work Plan and MethodologyOn ground investigation of the site under observation for terrain features for concentration of wind.Digitization of the contour map of NITH campus using AutoCAD, ArcGIS software platforms.Collection and analysis of wind monitoring station data for the prevailing wind regimes from 2nd May 2011 to 24th Nov 2011.On site measurements and study of biological indicators in the regions identified in step 1.Analysis of wind characteristics and determination of observed wind climate (OWC).To prepare the wind resource map (wind distribution profiles).Extrapolation for wind profile at different heights.Calculating the energy available from the derived wind potential.**

  • Experimental Platform for monitoring Wind Regimes.10 m GI triangular tower with guy wires.Anemometer. Sensor mounting arm.PV panel for back up power.Pyranometer.Humidity sensor.Location: C.E.E.E Roof TopElevation: 896 m (886+10) (a.s.l)**

  • Experimental set up and Equipments**

  • Anemometer RMY 50103-10-LThe Wind Monitor measures horizontal wind speed and direction.The main housing, nose cone, propeller, and other internal parts are injection moulded U.V. stabilized plastic.Propeller rotation produces an AC sine wave signal with frequency proportional to wind speed.With a constant voltage applied to the 10K potentiometer, the output signal is an analogue voltage directly proportional to wind direction angle.


  • Hand Held Anemometer KM-909Airflow measurements & monitoring.Portable, simple and

    onehand operation. Weight : Approx 390g (including battery and probe).Measurement range 0-100 m/s.Accuracy available 0.3 m/s


  • VI. Work Done in semester- III, July-Dec 2011

    Terrain mapping commenced with noting of obstacle data.Partial digitization of NITH contour map done.Ground Survey done for preliminary site identification.Actual measurements recorded with portable anemometer.Comparative study done to validate the measurements with wind monitoring station data.Influence of terrain on wind directional distribution studied.Wind influenced trees investigated as biological indicators for wind speed estimation.Micro-analysis done to study the energy generation from the prevailing wind regimes.Hybrid wind turbine systems suggested for the site.


  • Data collection using several devices . Devices installed on Wind Monitoring Station at NIT HAMIRPUR campus.


    DevicesRangeAccuracyResolutionOperating Temp.OutputAnemometer (P) KM-9090 30 m/s 3%0.010 50 C VoltageHHA RMY-50103-10-L0 - 100 m/s 0.3 m/s0.001-50 - +50C AC voltageTemperature P- 41342-50 - +50C 0.3C0.1-50 - +50CVoltage Humidity P - 413420 100 %RH 1 %RH %1 -50 - +50C


    PressureP 61302V500-1100 hPa0.3 hPa0.01 hPa-40 - +60CVoltage

  • 3 (c) Terrain map of NIT campus**

  • Defining obstacles in WAsP 1 angle from N to first corner []R1 radial distance to first corner [m] 2 angle from N to second corner []R2 radial distance to second corner [m]h height of obstacle [m]d depth of obstacle [m]P estimated porosity (fraction 0-1)


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


    Building 1 R 1 2R2dhPDBH256.5313.55818.50NKH182.415065210MMH370.545672300MED576085.2190Workshop50535790Library247.95239.445.2250Auditorium296.4324.947250VLH205.2205.255220CED & SBI50807020

  • Wind monitoring tower on NITH Contour map**Wind tower