This document discusses wind resource assessment for wind farm development. It covers how wind is generated, accessing wind resources through measurement and modeling, and estimating energy production with uncertainties. Key steps include measuring wind speeds on site, correlating to long-term reference stations to predict long-term distributions, modeling wind flows, planning turbine layouts, and estimating annual energy yields while accounting for production losses and uncertainties. Accurate wind assessment is critical for maximizing energy production estimates and ensuring project viability.

1. Wind Resource Assessment Wind Farm Development, Design, Operation and Maintenance EPIC Course January 27-29, 2010, Edmonton Don McKay, ORTECH Power

2. Wind Resource Assessment How Wind is Generated Wind Atlas Wind Speed Characteristics Accessing the Resource Project Assessment Energy Estimation Uncertainty

3. How wind is generated

4. Canadian Wind Atlas

6. Power available in the wind is P = ½ ρ π R 2 v 3 Power is very sensitive to wind speed -> Accurate wind speed measurements are critical

7. Example Wind speed of 8 m/s vs 8.2 m/s = 2.5% difference in wind speed = 7.7% increase in power, theoretically = 5% increase in power, realistically

8. Example (cont’d) For a 100 MW wind farm, this could mean 300 GWh/yr vs 315 GWh/yr = difference of $1,500,000 (assuming $0.10/kWh)

9. Example (cont’d) Moral: WRA program designed for maximum accuracy is critical to the success of your wind farm Overpredict: impacts shareholders, credibility Underpredict: impacts financing opportunities

10. Wind Resource Assessment (WRA) Measure wind speed and wind system Correlate to long-term reference station Predict long-term wind speed distribution at the site Wind flow modelling Micrositing Annual Energy Yield prediction

11. Measure -Correlate-Predict Measure wind data Install met tower with wind monitoring instruments Collect wind data QC/QA wind data Analyse wind data

12. (DEWI) Meteorological Mast (Wind monitoring tower)

13. R. M. Young Wind Monitor Features Propeller-type anemometer with fuselage and tail wind vane Rugged design for use in a variety of climates worldwide Manufactured by R. M. Young Specifications Wind Speed Range: 0-134 mph (0-60 m/s) Accuracy: ±0.6 mph (0.3 m/s) Starting threshold: 2.2 mph (1.0 m/s) Gust survival: 220 mph (100 m/s) Wind Direction Range: 0-360° mechanical, 355° electrical (5° open) Accuracy: ±3° Starting threshold at 10° displacement: 2.2 mph (1.1 m/s)

14. CR800 Measurement and Control Datalogger Features Ideal datalogger where only a few sensors will be measured Stores 4 Mbytes of data and programming in SRAM Data format is table Operating system: PakBus® Software support offered in LoggerNet or PC400 (full-featured) or ShortCut (programming) Detachable keyboard/display, the CR1000KD, can be carried to multiple stations Supports Modbus protocol, SDI-12 protocol, and SDM devices Specifications Analog inputs: 6 single-ended or 3 differential, individually configured Pulse counters: 2 Switched voltage excitations: 2 Control/digital ports: 4 Scan rate: 100 Hz Analog voltage resolution: to 0.33 µV A/D bits: 13

15. Neutral conditions -> logarithmic wind profile (<100m) Logarithmic Wind Profile Height above surface (m)

16. Power Law Profile - use wind speed measurements at two heights to find α - then use a to calculate wind speed at hub height α is the power law exponent (wind shear exponent) u R is the wind speed at height z r

17. Wind Speed Frequency Distribution

18. Wind Direction Distribution (Wind Rose)

19. Measure- Correlate-Predict Correlate to long-term reference stations 12 months of measured site data recommended Find appropriate long-term reference stations Determine correlation between site data and reference stations for a concurrent period Determine long-term wind data set for site Predict long-term windspeed distribution at the site (i.e. at the location of the met mast)

20. Long term observation of wind speed

21. Wind flow modelling Input predicted long-term wind data into wind flow model (e.g. WAsP) Input digital terrain data (topographic data, vegetation data) Output wind flow map over site

23. (DEWI) Typical Wind Speed Map

24. Micrositing Purpose: design turbine layout optimized on energy production, minimized on wake losses Input wind flow map Input terrain data Input site constraints Site boundary Setbacks for: roads, buildings, environmental constraints (wetlands, migratory routes), wooded areas, water bodies/courses Noise restrictions Visual impact Input number of turbines, turbine specs, turbine constraints Nameplate capacity, hub height, rotor diameter Power curve Thrust coefficient RPM Maximum slope for turbine Turbine spacing

25. Basic Parameters for IEC – WTG classes

26. Power Curve

27. Turbine Layout

28. Annual Energy Yield Prediction Ideal Energy Yield Gross Energy Yield, adjusted for Topography Roughness wake effect air density high wind speed hysteresis Net Energy Yield, adjusted for Production losses Capacity Factor

29. Production Losses WTG availability Planned maintenance Icing & cold temperature related losses Grid & substation Grid availability Blade soiling High wind hysteresis

30. Example – Annual Energy Yield Prediction for 100 MW wind park Ideal energy yield: 867.8 GWh/yr Gross energy yield: 350 GWh/yr Production Losses: 10% Net energy yield: 315 GWh/yr Capacity Factor: 36%

31. P50 Previous example: Annual Energy Yield = 315 GWh/yr = P50 P50: statistical mean or the probability that this value will be exceeded 50% Actual annual energy production will vary from the P50 in direct proportion to the uncertainty

32. Uncertainties

33. Conclusions Project viability depends on the wind resource Wind conditions are site specific Wind data vary with time and height Accuracy is critical Carefully assess uncertainties Good financing terms depends on a WRA program that has been designed for maximum accuracy

34. Questions?