Wind Resource AssessmentWind Farm Development, Design, Operation and Maintenance

EPIC Course January 27-29, 2010, Edmonton

Don McKay, ORTECH Power

Wind Resource Assessment

• How Wind is Generated

• Wind Atlas

• Wind Speed Characteristics

• Accessing the Resource

• Project Assessment

• Energy Estimation

• Uncertainty

How wind is generated

Canadian Wind Atlas

Power available in the wind is

P = ½ ρ π R2 v3

Power is very sensitive to wind speed

→ Accurate wind speed measurements are critical

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

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)

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

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

Measure-Correlate-Predict

• Measure wind data

– Install met tower with wind monitoring instruments

– Collect wind data

– QC/QA wind data

– Analyse wind data

(DEWI)

Meteorological Mast (Wind monitoring tower)

R. M. Young Wind MonitorFeaturesPropeller-type anemometer with fuselage and tail wind vane Rugged design for use in a variety of climates worldwide Manufactured by R. M. Young

SpecificationsWind 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)

CR800Measurement and Control Datalogger

FeaturesIdeal 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

SpecificationsAnalog 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

Neutral conditions → logarithmic wind profile (<100m)

Logarithmic Wind Profile

0

* lnvz

z

k

uzh

0

2

4

6

8

10

0 2 4 6 8 10 12 Wind speed (m/s)

0 = water

0 forest z z =

Hei

ght a

bove

sur

face

(m

)

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)

uR is the wind speed at height zr

RR z

z

u

u

Wind Speed Frequency Distribution

Wind Direction Distribution (Wind Rose)

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)

Long term observation of wind speed

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

(DEWI)

Typical Wind Speed Map

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

Basic Parameters for IEC – WTG classes

Power Curve

Turbine Layout

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

Production Losses

• WTG availability• Planned maintenance• Icing & cold temperature related losses• Grid & substation• Grid availability• Blade soiling• High wind hysteresis

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%

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

Uncertainties

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

Questions?