wind resource assessment
DESCRIPTION
TRANSCRIPT
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?