introduction to wind power generation
TRANSCRIPT
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Introduction to Wind Energy
GenerationJulio Lemaitre
Infrastructure - PowerFebruary 5, 2009
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Renewable Generation
Example of Renewable Sources:
Hydro (large small)
Wind
Geothermal Heat
Bio-Fuels
Water Sea Waves, Sea Tides, Rivers
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Introduction
Wind Power:
Wind Power, derived through the kinetic energy of
the wind, utilizes wind blowing over the blades of a
turbine to create a lift which makes the blades
rotate.
The turning blades of the wind turbine rotate the
connected shaft which drives the generator,
converting the mechanical energy into electricity.
The power generated in the individual wind turbinegenerators (WTGs) is collected at a substation
which steps up the voltage to the grid level.
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Wind Turbines
Rotor bladesNacelle
Tower
Rotor HubGenerator
Gear-Box
Hub height
One Blade WTG Two Blade WTG Three Blade WTG
Yaw drive
System
Pitch
System
The three blade WTG is the predominant technology used
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Wind Power
Wind Poweris determined by:
oWind speed at hubheight
oWind direction
oWind distribution: Weibull k-factor
oAir density
oTurbulence
oPower curve of Wind Turbine GeneratorsoLosses
oUncertainties
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Wind Power (cont.) Wind Power is calculated from:
P=* air *A*V3*Cp (Watt)
P = Power (Watt)
air =air density (kg/m3)A= rotor area (m2)
V= wind speed (m/s)
Cp= power coefficient (dimensionless)
E = Energy (kWh)
Emax-annual=P*8.76 (kWh)
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air = air density (kg/m3) depends mainly on:
Air temperature (average on site)
Altitude (topography + hubheight)
Cp = coefficient depending on WTG design and speed.
Cp aver= 0.3 to 0.4 (Cp max=0.59 theoretical max)
V = annual averaged 10minute-average windspeed
Wind speed is measured using special measurement masts that
are installed at the wind farm location (usually more than one) to
register wind speed, wind direction and air temperature.
Wind mast have anemometers (of a certain accuracy class for
wind speed measurment) at 2 or 3 altitudes on the mast, a wind
wane (for wind direction measurement) and thermometers.
Wind speed is measured at least 1 time each 2 seconds (IEC).
Wind Power (cont.)
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Wind power is directly proportional to: Air density (lower density at higher altitudes)
Rotor area (harvested wind area in m2)
(latest average rotor diameters are 80 100m)
Wind Power (cont.)
The
harvested
power
increases
with therotor
swept
area
Source: Danish Wind Industry Association
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Wind Power (cont.)
And increases with the cube of: Wind speed (v3)
(Wind speed is the key evaluation factor for wind projects, as it
is water for hydroprojects)
Definition of Plant Factor (or Capacity Factor):
The plant factor (pf) is the annual energy output divided by thetheoretical maximum output, if the machine were running at its
rated (maximum) power during all of the 8766 hours of the year.
It measures the effective use of the investment (installed power)in the production of energy over a period of time (usually a year).
pf =Ereal (kWh)/ P (kW)*8766(h)
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General Layout of a WTG
WTG with gearbox.
The gearbox is one
of most stressed
components of the
WTG. It increases the
Blade/Rotor speed in
about 40-60 times tooperate the generator.
The pitch regulation
allows for optimal
adjustments of the
blades to the wind
conditions (speed).
The yaw control
positions the nacelle
(rotor) to the wind
direction.
Source: Dirk Kooman
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Power Curve
0
500
1000
1500
2000
2500
1 3 5 7 911
13
15
17
19
21
23
25
PinkW
Va in m/s
Cut in Wind speed
Cut out Wind speed
Nominal Wind speed
The power curve
gives the relation of
wind speed vs. power
for a given WTG.
The WTG requires a
minimum speed to
start generating (cut in
wind speed).
The power produced
will depend on the
wind speed until
reaching the nominal
value.
When the wind
reaches the cut out
wind speed, the WTG
stops generating to
avoid mechanical
stresses.
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Wind speed is very variable and changes permanently with the
time of day, the seasons and the years, as well as with the altitudeabove the ground. To evaluate the wind potential at a site, at least
one year of wind data (speed and direcction) is required (two or
more years are optimal at hub height of the WTG).
The measured wind data (1-2 sec sampling) is filtered andaveraged (10-min averages) per wind direction sector.
The measured wind data is than correlated to a long term data
source of 5-10 years (e.g. close by metheorological station).
Once the wind speed data is available, a wind speed distribution is
calculated at hub height of the specified turbine. From the wind distribution curve, the WTG power curve, the wind
farm layout + topography, the gross energy production over a
period of time (usually a year) can be calculated.
Wind Data and Energy Yield
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Using industry software tools (e.g. WASP1), that account for
topografy, surface roughness, etc., the gross energy yield of thewind farm is calculated.
The net energy production is calculated after considering all
elements affecting the energy production (losses, unavailability,
etc.)
Wind Data and Energy Yield (cont.)
The wind speed distribution showsthe frequency (in hours or per unit-pu) of occurrence of the measured
wind speeds. Combined with the
power curve of the WTG, the gross
energy production over a period oftime can be calculated.
Note 1: WASP is a PC program for predicting wind climates, wind resources and power productions from wind turbines and wind farms.
Frequency of occurrence
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The P50 value corresponds to the annual expected (mean)
net value calculated from the gross output of the measured
data minus the losses.
Main Losses: Range Typical
- Wake effect (wind shade effect from other WTGs) 3% - 10% (7%)
- Electrical losses (cables, grid, etc.) 2% - 4% (3%)
- Non Availability of WTG1 2% - 4% (3%)
- Non Availability of Grid & SS 1% - 4% (1%)
- Icing and blade contamination 0.5% - 1% (1%)
- Others (bird migration, local issues)
- TOTAL 12% - 18% (14%)Note 1: For Offshore ~ 10%
Note 2: In some calculations the topographic/roughness effect is included in the total losses increasing them up to ~25%-30%
Energy Yield
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Uncertainties for the calculation of higher probability of
exceedance values (e.g. P75, P90) are assumedindependent and normal distributed around P50, for 1 year
and 10 year energy yield periods.
Main Uncertainties: Typical- Wind speed statistics 5% - 8%
- Power curve performance 3% - 5%
- Model (topography, wake effect) 2% - 3%
- Metering 0.5% - 1%- Others (array losses, special issues)
- TOTAL Standard Deviation (SD) 11% - 17%
The main uncertainties result in a SD valueUsually the uncertainty (SD) is calculated for a 1year and a 10year period (SD1year>SD10year)
Energy Yield (cont.)
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Energy Yield (cont.) P50 best estimate 50% probability of exceedance
Based on a normal distribution and a Standard Deviation (SD),the 75%, 90% or 95% probability of exceedance values can becalculated.
The SD is calculated from the uncertainties of the data andP50 energy yield calculation.
P75 = P50 - 0,675*SD P90 = P50 - 1,28*SD
P95 = P50 - 1,64* SD
Example: output calculated gross: 100 GWh
Losses: 13% so P50 = 87 GWh Uncertainty SD calculated as 7.3% =6.35 GWh
P75 = 87-4.3= 82.7 GWh
P90 = 87- 8.1=78.9 GWh
=>In the financial evaluation, the P9010year is often used as the base case with
sensitivities ensuring that P901year (or P951year) still enables debt service.
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Example of Energy YieldTurbine V90 3MW
Hub Height (m) 105
Rated Capacity (MW) 3Number of Turbines 52
Site Capacity (MW) 156
Hub Height Wind speed (m/s) 7.1
Gross Wind Farm Energy Production (GWh/annum) 387.3
Gross Plant Factor 28.3%
Corrections and Losses
Topographic/Roughness Effect 0.997
Wake Losses 0.933
Electrical Transmission Efficiency 0.980
Substation Maintenance 0.998Grid downtime 0.990
Turbine Availability 0.970
Power Curve Performance 0.980
Icing and blade degradation 0.995
Wake from existing wind farms 0.998
Bird Migration Effect 0.990
Overall Conversion Efficiency 0.842
P - Values
Net P50 Wind Farm Yield (GWh/annum) 325.99
Net P50 Plant Factor 23.9%
Uncertainty over 1 year (incl . annual w ind speed variation)
Standard error in result 17.60%
P90 Energy Yield over 1 year (GWh/annum) 252.55
P90 Plant Factor over 1 year 18.5%
Uncertainty over 10 years (incl. annual wind speed variation)
Standard error in result 12.00%
P75 Energy Yield over 10 years (GWh/annum) 299.58
P75 Plant Factor over 10 years 21.9%
P90 Energy Yield over 10 years (GWh/annum) 275.92
P90 Plant Factor over 10 years 20.2%
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The final wind farm energy yield calculation can only be done
once the micrositting has been completed.
Micrositing is the process of optimally locating the individual WTGs
in the available land spaces to maximize the wind farm energy
production and minimize the wake and array losses1.
Appropiate spacing between WTGs is essential to achieve balance
between wake losses and construction costs (roads, electrical
network)
The adequate ditance will depend on the prevailing wind speed
and direction distribution at the site (wind rose). A spacing of 5 9 rotor diameters is recommended in the
prevailing wind direction.
A spacing of 3 5 rotor diameters is recommended in the
directions perpendicular to the prevailing wind direction.Note 1: Array losses originate from wind distortions created by close by located WTGs.
Wind Farm Layout
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Wind Farm Layout (cont.)
Prevailing wind direction
5-9 rotor diameters apart
in the wind direction
3-5 rotor diameters apart
Source: Danish Wind Industry Association
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In the construction and financing of a Wind Farm, several
contractual arrangements and legal aspects play an important
role:
Land Agrements (Lease or Purchase)
Turbine Supply Agreement (TSA) Engineering, Procurement and Construction (EPC) &
Installation or Balance of Plant (BOP)
Operation and Maintenance Agreement (O&M)
Power Purchase Agreement (PPA) Grid Interconnection Agreement (GIA)
Warranties and Guaranties, Insurance, etc.
Contractual Arrangements
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Vestas (DENMARK)
GE Energy (USA)
Gamesa (SPAIN)Enercon (GERMANY)
Suzlon (INDIA)
Siemens (GERMANY)
Goldw ind (CHINA)
Sinovel (CHINA)
Nordex (GERMANY)
Others
2007 Market Share of Top 10 Global WTG
Manufacturers
Top 10 WTG Manufactures
21%
15%
14%
13%
7%
10%
21%
4%
3%
3%
Source: BTM Consult Aps
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Based on wind farms developed so far we can comment on
some reference values for the main topics:
Investment costs
O&M costs
Performance
Schedule
Benchmarking Values
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Investment Costs
Benchmarking Values
Project WTG-Type WTG Total WTG
MW MW # Total Inv $/kW /kW Hard Cost Soft Cost Non EPC
$ million % CAPEXKavarna V90 - 3MW 3.0 156.0 52 378.0 2,423 1,731 84% 16% 4.6%(Bulgaria)Totoral V90 - 2MW 2.0 46.0 23 136.0 2,957 2,112 91% 9% 12.0%(Chile)
Zorlu GE - 2.5MW 2.5 135.0 54 294.0 2,178 1,556 85% 15% 10.0%(Turkey)
Samana E57 - 0.8MW 0.8 100.8 126 126 1,250 893 N/A N/A 10.0%Saundatti E57 - 0.8MW 0.8 82.4 103 106.0 1,286 919 N/A N/A 10.0%(India)
Typical 2,000-3,000 1,400-2,200 80% 20% 10%-15%
1U$ = 1.4 India 1,200-1,600 860 - 1,150
3.6% Funded +
Sponsor Support
7% under PFA
Funds
2.8% Development Fee
CAPEX
5% Funded +
Contingency
Sponsor SupportSponsor Support
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O&M Costs (per year)
Benchmarking Values
Project WTG-Type WTG Total WTG Total Inv
MW MW # $ million Type of $/kW $/kWh $/WTG % CAPEX TotalO&M $/year
Kavarna V90 - 3MW 3.0 156.0 52 378.0 WTG Suppl ier 44.4 2.11 133,135 1.83% 6,923,000(Bulgaria) Own (after 4y) 21.8 1.04 65,520 0.90% 3,407,040
Totoral V90 - 2MW 2.0 46.0 23 136.0 WTG Suppl ier 43.0 1.80 86,000 1.45% 1,978,000(Chile) Own (after 3y) 33.5 1.40 66,990 1.13% 1,540,770
Zorlu GE - 2.5MW 2.5 135.0 54 294.0 Own 37.4 1.25 93,411 1.72% 5,044,200(Turkey)
Samana E57 - 0.8MW 0.8 100.8 126 126 WTG Suppl ier 14.1 0.57 11,288 1.13% 1,422,225Saundatti E57 - 0.8MW 0.8 82.4 103 106.0 WTG Suppl ier 14.1 0.62 11,288 1.10% 1,162,613(India)
Typical WTG Suppl ier 42 - 46 1.7 - 2.4 80k - 130k 1.5% - 2.5%1U$ = 1.4 Own 20 - 37 1.0 - 1.4 40k - 90k 1.0% - 1.5%
India 15 - 20 0.5 - 1.0 10k - 30k 1.0% - 1.5%
O&M
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Performance
Benchmarking Values
Project WTG-Type WTG Total WTG Total Inv Total Losses Availability Average P50 Energy
MW MW # $ million % % P50 P90 Wind Speed per MW inst.
m/s P50 P90 MWh/year
Kavarna V90 - 3MW 3.0 156.0 52 378.0 15.8% 96.0% 23.9% 20.2% 7.10 326.6 276.0 2094(Bulgaria)
Totoral V90 - 2MW 2.0 46.0 23 136.0 26.3% 95.0% 27.3% 21.0% 6.65 110.0 84.6 2391(Chile)Zorlu GE - 2.5MW 2.5 135.0 54 294.0 12.6% 95.0% 34.2% 28.1% 7.20 404.2 332.2 2994
(Turkey)Samana E57 - 0.8MW 0.8 100.8 126 126 20.7% 96.0% 28.5% 22.5% 6.90 251.4 198.4 2492Saundatti E57 - 0.8MW 0.8 82.4 103 106.0 19.2% 96.0% 25.8% 18.7% 6.80 186.5 135.4 2262(India)
1U$ = 1.4 Typical 12%-18% 95% - 97% 25%-35% 20%-25% 6.0 - 8.0
* High value due to Topographic/Roughness effect (*) 15%-25%
Plant Factor - pf Energy
GWh/year
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Project Schedule (*)
Benchmarking Values
(*) From Permitting to Commercial Op.
(Resource Assessment & Site Selection
could add 6 12 months to the process)
Project WTG-Type WTG Total WTG Total InvMW MW # $ million
Kavarna V90 - 3MW 3.0 156.0 52 378.0(Bulgaria)Totoral V90 - 2MW 2.0 46.0 23 136.0(Chile)Zorlu GE - 2.5MW 2.5 135.0 54 294.0(Turkey)
Samana E57 - 0.8MW 0.8 100.8 126 126
Saundatti E57 - 0.8MW 0.8 82.4 103 106.0(India)
Typical1U$ = 1.4
19 - 22
23 - 25
23 - 24
(Months)
19 - 22
Total Project Schedule
24 - 26
26 - 27