Resource Analysis

Objectives of Resource Assessment Discussion

• The subject of the second part of the analysis is to dig more deeply into some of the issues discussed earlier. For example, we :– Understand what factors are important and

not very important in cost and benefit analysis– Further elaborate on risk analysis– Evaluate tax benefits in different scenarios– Consider alternative structuring issues

Wind Resource Assessment

Wind Studies

• The first step for the project lenders is to conduct an in-depth analysis of the owner's feasibility study and possibly even hire a consultant to conduct an independent feasibility study. Such studies will analyze the wind resource data and should demonstrate the financial viability of the project. These studies will detail technical, financial and other aspects of the project and are crucial to the lender in its risk assessment of the proposed project.

• Independent Engineers compute the probability of different wind availability. However, these studies are based on the wind measurements for previous years and for a particular site, and while the studies accommodate the fact that the year in which the measurements were taken may have been a particular good or bad year, there is no guarantee that there will not be substantially less wind in the future.

• Off-taking utilities are largely able to mitigate this risk because it is possible to get very accurate wind forecasts, which enables alternative sources to be used in order to maintain grid stability and supply if necessary. For the project itself, however, no wind means zero cash flow.

• Such risk could, in theory, be hedged or covered by insurance, and while some attempts have been made in that respect, such tools are not yet a common feature and thus remain a risk which has to be factored in.

Wind Speed Risk

• A potential and significant risk for any energy project is the underlying resource for its generation – in this case wind. Identifying the availability of wind is paramount. This has two aspects. – The first is the question of whether a particular site has sufficient

wind speeds. This issue is addressed by the lending banks insisting on long-term – usually at least 12 months – wind measurements, which are then used as the basis for a number of wind studies. Banks usually insist on at least two of those coming from reputable wind experts. These wind studies give an estimate of the annual electricity output of a project, based on a probability curve, usually 75% or 90%, that the project will generate x number of full load hours. Depending on the wind turbine used, there is therefore a 75% or 90% respectively, probability that the turbine will generate y kW/h per year when in service.

Value of Renewable (Wind) on Market Basis

• Assumptions– Wind Power Curve– Wind Capacity Factor– Wind Capital Cost– Net Energy Value of Wind– Required Subsidy

Average Capacity Factors

Source of Wind Data

• www.knmi.nl

• http://www.kma.go.kr/kor/weather/climate/climate_03_01.jsp?a=0&b=20&c=1&pop=temp_avg_135-2004.htm

• CONSULT THE REPORTS AT THE SITE:

• http://www.knmi.nl/samenw/hydra

• http://www.ndbc.noaa.gov/station_history.phtml?station=41018

• http://www.ndbc.noaa.gov/station

• http://lwf.ncdc.noaa.gov/oa/ncdc.html

Power Curve of Wind Technology

Power Curve

-20%

0%

20%

40%

60%

80%

100%

120%

0 5 10 15 20

Wind Speed

Ca

pa

cit

y F

ac

tor

MWT-S 2000

MWT - 1,000 kW

Wind Speed by Hour

Wind Speed by Hour of Day and Month of Year

Wind Speed Variation by Month

Capacity Value of Wind

• Assume to Production Cost Runs with the same amount of non-wind capacity, except that one case has some wind capacity– 1. Without Wind– 2. With Wind

• The LOLE in the second case will be lower than the LOLE in the first case because in some high load hours, the wind farm will be running and lower the net load requirements for the other units.

• The value of wind could be – LOLE reduction x Cost of outage– Eg

• .000001 x 10,000 Won/kWh

Weibull Distribution

• In excel, =weibull(Wind Speed,C Factor (e.g. 2),Avg Speed/.89)

• X = wind speed

• K = Average Wind Speed/Gamma Factor = Average Wind Speed/.89

• C = 2

RetScreen Reconciliation

SummaryCapacity factor % 28.7%Electricity delivered to load MWh 0Electricity exported to grid MWh 100,565Power capacity kW 40,000.0

• Total energy delivered after losses and adjustments is 100,565 MWH

• Capacity Factor is – Average Generation:100,565/8760 = 11,480– Divided by 40,000– Equals 28.7%

Start with Monthly Wind Speeds

• Before Working with the Power Curve and the Weibull distribution, adjustments to the wind speeds for height and wind density should be made: Adjustments to Wind Speed Measured 5 M

Eleveation in Measuring Wind 5

Turbine Elevation 50

Ratio 10

Wind Sheer Exponent 0.1

Raised to Exponent 1.26

Power Density Adjustment 1.13

Total Adjustment to Wind Speeds 1.42

Compute Month by Month Wind Speeds

• This table illustrates how the unadjusted wind speeds are adjusted

UnadjustedAdjusment

Factor AdjustedMonth m/s m/s

January 6.6 1.42 9.38 February 6.1 1.42 8.67

March 6.1 1.42 8.67 April 5.4 1.42 7.67 May 5.0 1.42 7.10 June 4.9 1.42 6.96 July 5.1 1.42 7.24

August 4.9 1.42 6.96 September 5.5 1.42 7.81

October 5.8 1.42 8.24 November 6.5 1.42 9.23 December 6.4 1.42 9.09

Adjusted Wind Speeds

Use the Weibull Distribution to Compute the Average Hourly Output by Month

• This example shows the calculation for the first month. The index function can be used for the same calculation in other months

Month 1

Average Wind Speed 9.38Gamma Factor 0.89Weibull k 10.58Shape Factor 2.00Max Wind Speed 15.00

Wind speed Power curve data Weibull Probability Max Weighted Hourly

m/s kW Probability of Wind Speed Switch Power Production kWh

0 0.0 0.00% TRUE 0.00

1 0.0 1.77% TRUE 0.00

2 0.0 3.45% TRUE 0.00

3 0.1 4.95% TRUE 0.00

4 29.1 6.20% TRUE 1.80

5 113.7 7.15% TRUE 8.13

6 225.2 7.77% TRUE 17.50

7 366.3 8.07% TRUE 29.57

8 582.0 8.07% TRUE 46.97

9 852.5 7.80% TRUE 66.49

10 1,151.4 7.31% TRUE 84.20

11 1,451.2 6.67% TRUE 96.76

12 1,707.5 5.92% TRUE 101.13

13 1,875.2 5.13% TRUE 96.23

14 1,986.6 4.34% TRUE 86.26

15 1,996.2 3.59% TRUE 71.67

16 1,999.0 2.90% FALSE 0.00

17 1,999.7 2.30% FALSE 0.00

18 1,999.9 1.78% FALSE 0.00

19 2,000.0 1.35% FALSE 0.00

20 2,000.0 1.00% FALSE 0.00

21 2,000.0 0.73% FALSE 0.00

22 2,000.0 0.52% FALSE 0.00

23 2,000.0 0.36% FALSE 0.00

24 0.25% FALSE 0.00

25 0.17% FALSE 0.00

Total 99.55% FALSE 0.00

Compute Total Production for Each Month

• Compute the total production for one turbine for one year before adjustments for losses etc. using data table function in excel

Month

Unadjusted Wind speed

m/sMonthCode

UnadjustedHourly

Production kWh

Days in Month

Total Monthly Production for Single Turbine

(MwH) January 6.6 1.0 925.57 31 688.63

February 6.1 2.0 832.09 28 559.16 March 6.1 3.0 832.09 31 619.07

April 5.4 4.0 680.72 30 490.12 May 5.0 5.0 586.63 31 436.46 June 4.9 6.0 562.60 30 405.07 July 5.1 7.0 610.50 31 454.21

August 4.9 8.0 562.60 31 418.57 September 5.5 9.0 703.54 30 506.55

October 5.8 10.0 769.78 31 572.71 November 6.5 11.0 908.00 30 653.76 December 6.4 12.0 889.84 31 662.04

Adjust for Number of Turbines and Loss Factors

Month

Unadjusted Wind speed

m/s

Total Monthly Production for Single Turbine

(MwH) Turbines

Unadjusted Gross

Production (MWH)

Array losses Percent

Airfoil losses Percent

Miscellaneous losses Percent

Un- Availability

PercentTotal

Adjustment

Total Adjusted

Production (MWH)

January 6.6 568.98 20 11,379.56 4.00% 1.00% 3.00% 4.00% 88.5% 10,071.05 8,771February 6.1 485.69 20 9,713.80 4.00% 1.00% 3.00% 4.00% 88.5% 8,596.83 7,944

March 6.1 537.73 20 10,754.56 4.00% 1.00% 3.00% 4.00% 88.5% 9,517.92 8,710April 5.4 453.24 20 9,064.78 4.00% 1.00% 3.00% 4.00% 88.5% 8,022.44 8,321May 5.0 415.46 20 8,309.24 4.00% 1.00% 3.00% 4.00% 88.5% 7,353.78 8,454June 4.9 387.99 20 7,759.85 4.00% 1.00% 3.00% 4.00% 88.5% 6,867.56 8,057July 5.1 429.50 20 8,590.07 4.00% 1.00% 3.00% 4.00% 88.5% 7,602.32 8,277

August 4.9 400.93 20 8,018.51 4.00% 1.00% 3.00% 4.00% 88.5% 7,096.48 8,288September 5.5 464.63 20 9,292.69 4.00% 1.00% 3.00% 4.00% 88.5% 8,224.15 8,105

October 5.8 511.74 20 10,234.81 4.00% 1.00% 3.00% 4.00% 88.5% 9,057.94 8,493November 6.5 545.69 20 10,913.76 4.00% 1.00% 3.00% 4.00% 88.5% 9,658.82 8,319December 6.4 558.22 20 11,164.35 4.00% 1.00% 3.00% 4.00% 88.5% 9,880.59 8,708

Total 115,195.99 101,949.89 100,446.61

Alternative Use of Weibull

• Required Inputs

Ave. Wind (m/s) = 6Weibull K = 2Site Altitude (m) = 270Wind Shear Exp. = 0.143Anem. Height (m) = 10Tower Height (m) = 24Turbulence Factor = 10.0%Factor For Wind Density 0.0000918Constant 0.89Wind Turbine Factor = 0.25

Perf. Safety Margin = 0.0%

Inputs:

Preliminary Calculations

• This shows some calculations that are necessary

Tower Height/Anem Height 2.4 =Tower_Height__m/Anem._Height__mTower Height/Anem Height ^ Shear Exp 1.13 =Tower_Height_Anem_Height^Wind_Shear_Exp.Hub Average Wind Speed (m/s) = 6.80 =Tower_Height_Anem_Height___Shear_Exp*Ave._Wind__m_sC Factor for Wiebull: C/Hub Wind Speed 7.64 =Hub_Average_Wind_Speed__m_s/ConstantAir Density Factor = Factor x Altitude -0.001313% =-Wind_Shear_Exp.*Factor_For_Wind_DensityAverage Output of Power per Hour (kW) = 2.48 =SUM(G42:G61)Daily Energy Output (kWh) = 59.41 =Average_Output_of_Power_per_Hour__kW*24*(1-Perf._Safety_Margin)Annual Energy Output (kWh) = 21,686 =Daily_Energy_Output__kWh*365Monthly Energy Output = 1,807 =Annual_Energy_Output__kWh/12Percent Operating Time = 81.1% =SUM(K45:K61)

Preliminary Calculations

Power Curve and Weibull

Wiebull Distribution

WindCad Turbine Performance ModelBWC EXCEL Battery Charging Version

Prepared For: Customer

Site Location: Customer Site

Data Source: DOE Wind Atlas

Date: 5/6/2010

Inputs: Results: =($B$11/($G$10/0.89))*((A21/($G$10/0.89)) (̂$B$11-1))*(EXP(-((A21/($G$10/0.89)) $̂B$11)))

Ave. Wind (m/s) = 6 Hub Average Wind Speed (m/s) = 6.80

Weibull K = 2 Air Density Factor = -2%

Site Altitude (m) = 270 Average Output Power (kW) = 2.41

Wind Shear Exp. = 0.143 Daily Energy Output (kWh) = 57.9Anem. Height (m) = 10 Annual Energy Output (kWh) = 21,148

Tower Height (m) = 24 Monthly Energy Output = 1,762

Turbulence Factor = 10.0% Percent Operating Time = 81.1%

Perf. Safety Margin = 0.0%

Const 0.89C 7.64

Weibull Performance CalculationsWind Speed Bin (m/s) Pow er (kW) Wind Probability (f) Net kW @ V k/c x/c^(k-1) exp(-(x/c)^k)

1 0.00 3.37% 0.000 0.00% 0.26175714 0.13087857 0.98301667 3.37% 3.37%2 0.00 6.40% 0.000 0.00% 0.26175714 0.26175714 0.93377777 6.40% 6.40%3 0.00 8.81% 0.000 0.00% 0.26175714 0.39263572 0.85713246 8.81% 8.81%4 0.22 10.42% 0.023 2.26% 0.26175714 0.52351429 0.76028097 10.42% 10.42%5 0.70 11.16% 0.078 7.28% 0.26175714 0.65439286 0.6516615 11.16% 11.16%6 1.45 11.09% 0.161 15.43% 0.26175714 0.78527143 0.53974891 11.09% 11.09%7 2.24 10.36% 0.232 25.06% 0.26175714 0.91615001 0.43199951 10.36% 10.36%8 3.20 9.16% 0.293 39.25% 0.26175714 1.04702858 0.3341154 9.16% 9.16%9 4.26 7.70% 0.328 59.67% 0.26175714 1.17790715 0.24970745 7.70% 7.70%10 5.40 6.18% 0.333 91.38% 0.26175714 1.30878572 0.18033842 6.18% 6.18%11 6.58 4.74% 0.312 142.12% 0.26175714 1.43966429 0.12585394 4.74% 4.74%12 7.02 3.49% 0.245 167.91% 0.26175714 1.57054287 0.08487252 3.49% 3.49%13 7.02 2.46% 0.173 167.91% 0.26175714 1.70142144 0.05530815 2.46% 2.46%14 7.02 1.67% 0.117 167.91% 0.26175714 1.83230001 0.03482836 1.67% 1.67%15 6.14 1.09% 0.067 120.54% 0.26175714 1.96317858 0.0211933 1.09% 1.09%16 4.39 0.68% 0.030 62.73% 0.26175714 2.09405716 0.01246195 0.68% 0.68%17 2.37 0.41% 0.010 26.81% 0.26175714 2.22493573 0.00708101 0.41% 0.41%18 2.63 0.24% 0.006 30.47% 0.26175714 2.3558143 0.003888 0.24% 0.24%19 2.63 0.13% 0.004 30.47% 0.26175714 2.48669287 0.0020629 0.13% 0.13%20 2.63 0.07% 0.002 30.47% 0.26175714 2.61757145 0.00105768 0.07% 0.07%

1997, Bergey Windpow er Co. Totals: 99.64% 2.414

Weibull Calculations:Wind speed probability is calculated as a Weibull curve defined by the average wind speed and a shape factor, K. To facilitate piece-wise integration, the wind speed range is broken down into "bins" of 1 m/s in width (Column 1). For each wind speed bin, instantaneous wind turbine power (W, Column 2)) is multiplied by the Weibull wind speed probability (f, Column 3). This cross product (Net W, Column 4) is the contribution to average turbine power output contributed by wind speeds in that bin. The sum of these contributions is the average power output of the turbine on a continuous, 24 hour, basis.Best results are achieved using annual or monthly average wind speeds. Use of daily or hourly average speeds is not recommended.

Raw Wind Speed Analysis

Raw Wind Speed Data

Actual Distribution vs Weibull

Weibull versus Actual

Alternative Power Curves

Alternative Power Curves

Variation in Average Wind Speeds

Variation in Capacity Factor from Wind Speed Variations

Solar Resource Analysis

Solar Radiation in Energy per m2

MonthAir

temperatureRelative humidity

Daily solar radiation - horizontal

°C % kWh/m²/dJanuary -10.8 70.0% 1.53February -9.2 67.0% 2.58March -2.7 65.5% 3.64April 5.6 61.5% 4.64May 12.8 62.0% 5.36June 17.9 65.5% 5.94July 20.8 67.5% 5.86August 19.2 71.0% 4.92September 14.3 73.5% 3.58October 7.9 72.0% 2.33November 1.0 76.0% 1.31December -7.6 76.0% 1.08Annual 5.8 69.0% 3.57

Capacity Factor

PhotovoltaicType mono-SiPower capacity kW 100.00ManufacturerModel 1 unit(s)Efficiency % 11.7%Nominal operating cell temperature °C 45Temperature coefficient % / °C 0.40%Solar collector area m² 855

Solar Production by Month

MonthDaily solar radiation -

horizontalDaily solar

radiation - tiltedElectricity

export rate

Electricity exported to

gridkWh/m²/d kWh/m²/d $/MWh MWh

January 1.53 2.98 420.0 8.813February 2.58 4.39 420.0 11.555

March 3.64 4.78 420.0 13.593April 4.64 4.87 420.0 13.008May 5.36 4.97 420.0 13.357June 5.94 5.22 420.0 13.290July 5.86 5.28 420.0 13.689

August 4.92 4.88 420.0 12.752September 3.58 4.11 420.0 10.621

October 2.33 3.25 420.0 8.943November 1.31 2.09 420.0 5.777December 1.08 2.02 420.0 5.962Annual 3.57 4.07 420.00 131.360

Computation of Solar Energy per m2

Clearness Index

Day

Monthly averagedaily clearness

index (KT bar)

Monthly Average Extra terrestial Ratiation

from Last Sheet

Monthly averagedaily radiationon horizontal

surface(MJ/m²/d) Check

17 0.4610 11.9479 5.508 5.50847 0.5323 17.4491 9.288 9.28875 0.5263 24.8988 13.104 13.104

105 0.5052 33.0638 16.704 16.704135 0.4929 39.1476 19.296 19.296162 0.5122 41.7454 21.384 21.384198 0.5220 40.4132 21.096 21.096228 0.5004 35.3933 17.712 17.712258 0.4633 27.8204 12.888 12.888288 0.4277 19.6118 8.388 8.388318 0.3567 13.2210 4.716 4.716344 0.3703 10.4989 3.888 3.888