Wind turbine farm, feasibility study by Normand Masse

MA GNOTECH, S.A.

14-mar-03 2301 Independencia, Suite B203-B Santo Domingo, Dominican Republic Tel: 809-535-3839, Fax: 809-535-3804 E-mail: magnotech@dr.com

Energy Management Group

Renew able Energy - Preliminary ev aluation Yuma del Mar - 14 mw net Wind RE system Cabo San Rafael Lat 18 Lon -69 System Requirements Single Turbine Rating Number of Turbines Wind Turbine Farm Rating

Annual Energy Demand & Production Grid type Grid peak load Occupancy/Service demand adjusted load Annual consumption (with adjusted load) Renewable energy delivered Excess RE available (for sale back to grid) Net GHG emission reduction Net GHG emission reduction - 25 yrs Investment Terms Initial Costs Incentives / Grants Down Payment Debt Payment Debt Interest Rate Debt Term

kW Unit kW MW

MWh MWh tCO2/yr tCO2

USD/Year Year

Annual Costs O&M Fuel/Electricity Debt Payment Annual Income Energy savings/income (avoided grid consumption) Credit (surplus sold back to grid) at US$/kw hr Capacity savings/income RE Production Credit Income Sav ings Savings / Year Final Cost per kW/hr

2,000 22 44,000 44

Isolated-grid 13,649 13,649 119,565 123,454 9,292 1,107,563 27,689,087

$57,686,629 $0 $0 $5,939,575 6.0% 15 8,196,278 $2,256,703 $0 $5,939,575

0.055

41.8%

$14,091,056 $13,579,981 $511,075 $0 $0

$5,894,778 $0.066

MA GNOTECH, S.A.

14-mar-03 2301 Independencia, Suite B203-B Santo Domingo, Dominican Republic Tel: 809-535-3839, Fax: 809-535-3804 E-mail: magnotech@dr.com

Energy Management Group

Inte re s t = 6 %

CONSORTIUM - OPTIONS Consortium Plan I Number of Consortium Members Project Equity Member Down Payment

M e mbe r Cos t pe r k W/hr

Member fixed monthly Cost Member Monthly Savings Member Annual Savings Consortium Plan II Number of Consortium Members Project Equity Member Down Payment

$ 0 .0 6 6

$49,496.46 $44,864.19 $538,370.30

M e mbe r Cos t pe r k W/hr

Member fixed monthly Cost Member Monthly Savings Member Annual Savings Consortium Plan III Number of Consortium Members Project Equity Member Down Payment

8 $0.00 $0.00 $ 0 .0 6 6

$61,870.57 $56,080.24 $672,962.87

M e mbe r Cos t pe r k W/hr

Member fixed monthly Cost Member Monthly Savings Member Annual Savings Single ownership Plan IIII Single Member Project Equity Member Down Payment

10 $0.00 $0.00

6 $0.00 $0.00 $ 0 .0 6 6

$82,494.09 $74,773.65 $897,283.83

M e mbe r Cos t pe r k W/hr

1 $0.00 $0.00 $ 0 .0 6 6

Member fixed monthly Cost Member Monthly Savings Member Annual Savings

$494,964.56 $448,641.91 $5,383,702.97

Sa v ings

Annual Production @ Minimum Wind Speed Rating Grid Consumption Cost kW/hr Annual Cost Savings / Year

MW/Yr $0.11 39.6%

123,454 $13,579,980.99 $8,196,278.02 $5,383,702.97

14-mar-03

MAGNOTECH, S.A. 2301 Independencia, Suite B203-B Santo Domingo, Dominican Republic Tel: 809-535-3839, Fax: 809-535-3804 E-mail: magnotech@dr.com

Energy Man agement Group

Yuma del Mar - 14 mw net Wind RE system Cabo San Rafael Lat 18 Lon -69 Peak Occuunit Total peak pancy kW kW Factor

LOAD ESTIMATE

Service demand Factor

Adjuted load KW

4,500 Small villas (100 m2) 500 Large Villas (150 m2) 5,000 Villas total

3.50 5.00

15,750 2,500 18,250

65% 65%

70% 70%

7,166 1,138 8,304

1,500 Hotel Rooms 7 Hotels Adm/rec/util Hotels total

1.20 300

1,800 2,100 3,900

80% 80%

70% 70%

1,008 1,176 2,184

200

2,000 500 2,500

90% 80%

60% 70%

1,080 280 1,360

60% 50% 50% 80% 90% 75% 75% 80%

120 11 30 240 450 375 375 200 1,801

10 Commercial areas 1 Marina Adm/recr/util Commercial total Project main admin center Street lighting main Street lighting subdiv Television/radio/cable Celular system Water treatment/pumping Waste water treatment Misc Community services

km 15 km 60

TOTAL PEAK LOAD:

200 23 60 300 500 500 500 250 2,333 26,983

ADJUSTED LOAD:

LAND REQUIREMENTS Large winds farm will typically 1.5 to 2.5 hectares per large turbine This represents for this project about 42 hectares = 422,400 m2 = 106 acres on a strip of land aprox 160 m wide by 2.6 km long (length facing south) It is assumed that client has available land within 2 km of project site No costs for purchasing this land are included in the evaluation

13,649

RETScreenÂŽ International is a standardised and integrated renewable energy project analysis software. This tool provides a common platform for both decision-support and capacity-building purposes. RETScreen can be used worldwide to evaluate the energy production, life-cycle costs and greenhouse gas emissions reduction for various renewable energy technologies (RETs). RETScreen is made available free-of-charge by the Government of Canada through Natural Resources Canada's CANMET Energy Diversification Research Laboratory (CEDRL). The user is encouraged to properly register at the RETScreen website so that CEDRL can report on the global use of RETScreen.

Wind Energy Project Model RETScreen is available free-of-charge at

TO START (click here) Brief Description & Model Flow Chart Cell Colour Coding

http://retscreen.gc.ca

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Online Manual Product Data Weather Data Cost Data Currency Options

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Contributors

Energy Model Equipment Data Cost Analysis Greenhouse Gas Analysis Financial Summary Blank Worksheets (3)

Version 2000 - Release 2

85+ Technology Experts Collaborating Organisations

ÂŠ Minister of Natural Resources Canada 1997-2000.

NRCan/CEDRL

RETScreen Energy Model - Wind Energy Project Site Conditions Project name Project location Nearest location for weather data Annual average wind speed Height of wind measurement Wind shear exponent Wind speed at 10 m Average atmospheric pressure Annual average temperature System Characteristics Grid type Grid peak load Wind turbine rated power Number of turbines Wind plant capacity Hub height Wind speed at hub height Wind penetration level Suggested wind energy absorption rate Wind energy absorption rate Array losses Airfoil soiling and/or icing losses Other downtime losses Miscellaneous losses

Annual Energy Production Wind plant capacity Unadjusted energy production Pressure adjustment coefficient Temperature adjustment coefficient Gross energy production Losses coefficient Specific yield Wind plant capacity factor Renewable energy collected Renewable energy delivered Excess RE available

Estimate Yuma del Mar - 14 mw net Wind RE system Cabo San Rafael Lat 18 Lon -69 Barahona m/s 6.3 m 10.0 0.14 m/s 6.3 kPa 100.0 °C 27

kW kW kW m m/s % % % % % % %

Estimate Isolated-grid 13,649 2,000 22 44,000 60.0 8.1 322.4% See manual 93% 3% 2% 2% 3%

kW MW MWh MWh kWh/m² % MWh MWh kWh MWh

Estimate Per turbine 2,000 2 7,026 0.99 0.96 6,677 0.90 1,200 34% 6,034 5,612 5611562 422

Notes/Range

See Weather Database

3.0 to 100.0 0.10 to 0.25 60.0 to 103.0 -20 to 30 Notes/Range

Complete Equipment Data sheet

6.0 to 100.0 3.0 to 15.0

0% to 20% 1% to 10% 2% to 7% 2% to 6% Estimate Total 44,000 44 154,569 0.99 0.96 146,902 0.90 1,200 34% 132,747 123,454 123454373 9,292

Notes/Range

0.59 to 1.02 0.98 to 1.15 0.75 to 1.00 150 to 1,500 20% to 40%

Complete Cost Analysis sheet Version 2000 - Release 2

23/05/2011; Yuma del Mar- Land-Based RE

NRCan/CEDRL

RETScreen® Equipment Data - Wind Energy Project Wind Turbine Characteristics Wind turbine rated power Hub height Rotor diameter Swept area Wind turbine manufacturer Wind turbine model Energy curve data source Shape factor

Estimate 2,000 60.0 80 5,027 Vestas Wind Systems VESTAS V80-2.0MW Standard 2.0

Wind speed (m/s) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Power curve data (kW) 0.0 0.0 0.0 0.0 44.1 135.0 261.0 437.0 669.0 957.0 1,279.0 1,590.0 1,823.0 1,945.0 1,988.0 1,998.0 2,000.0 2,000.0 2,000.0 2,000.0 2,000.0 2,000.0 2,000.0 2,000.0 2,000.0 2,000.0

kW m m m²

Notes/Range See Product Database

6.0 to 100.0 7 to 72 35 to 4,075

Rayleigh wind distribution

Wind Turbine Production Data Energy curve data (MWh/yr) 407.2 1,201.7 2,421.7 3,908.5 5,461.9 6,933.9 8,237.4 9,323.7 10,168.9 10,771.0 11,145.7 11,321.0 11,330.8 -

Power and Energy Curves Energy

2,500

12,000

2,000

10,000 8,000

1,500 6,000 1,000 4,000 500

Energy (MWh/yr)

Power (kW)

Power

2,000

0 0

10 12 14 16 Wind speed (m/s)

Return to Energy Model sheet Version 2000 - Release 2

NRCan/CEDRL

RETScreen Cost Analysis - Wind Energy Project Type of project: Initial Costs (Credits) Feasibility Study Site investigation Wind resource assessment Environmental assessment Preliminary design Detailed cost estimate Report preparation Project management Travel and accommodation Other Sub-total: Development PPA negotiation Permits and approvals Land rights Land survey Project financing Legal and accounting Project management Travel and accommodation Other Sub-total: Engineering Wind turbine(s) micro-siting Mechanical design Electrical design Civil design Tenders and contracting Construction supervision Other Sub-total: Renewable Energy (RE) Equipment Wind turbine(s) Spare parts Transportation Other Sub-total: Balance of Plant Wind turbine(s) foundation(s) Wind turbine(s) erection Road construction Transmission line and substation Control and O&M building(s) Transportation Other Sub-total: Miscellaneous Training Commissioning Interest during construction Contingencies Sub-total: Initial Costs - Total Annual Costs (Credits) O&M Land lease Property taxes Insurance premium Transmission line maintenance Parts and labour Community benefits Travel and accommodation General and administrative Other Contingencies Annual Costs - Total Periodic Costs (Credits) Drive train Blades End of project life Version 2000 - Release 2

Custom Unit

Quantity

p-d met tower p-d p-d p-d p-d p-d p-trip Cost

20 3 4 30 30 10 10 10 0

p-d p-d project p-d p-d p-d p-yr p-trip Cost

p-d p-d p-d p-d p-d p-yr Cost

kW % turbine Cost

turbine turbine km project building project Cost

p-d p-d % %

Currency: Second currency: Unit Cost USD USD USD USD USD USD USD USD USD

15 20 1 30 45 45 2.00 10 0

USD USD USD USD USD USD USD USD USD

88 66 90 90 60 2.00 0

USD USD USD USD USD USD USD

44,000 2.0% 22 0

800 22,000 800 800 800 800 800 3,000 -

1,200 800 30,000 600 1,500 1,200 130,000 3,000 -

800 800 800 800 800 130,000 -

USD 1,000 USD 44,000,000 USD 33,000 USD -

22 22 4.00 10 1 32 0

USD USD USD USD USD USD USD

20 30 6.0% 5%

USD USD USD USD

Unit

Quantity

% % % % kWh p-trip % Cost %

2.0% 1.0% 3.0% 3.0% 123,454,373 1 6 6% 0 10%

40,000 30,000 50,000 250,000 200,000 20,000 -

800 800 51,933,900 51,933,900

United States Dominican Rep. Amount

USD 13,579,981 USD 13,579,981 USD 13,579,981 USD 2,500,000 USD 0.008 USD 50,000 USD 3,000 USD 1,945,434 USD USD 1,945,434

DOP DOP DOP DOP DOP DOP DOP DOP DOP

0.3%

DOP

DOP DOP DOP DOP DOP DOP DOP DOP DOP

0.9%

0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

DOP

DOP DOP DOP DOP DOP DOP DOP

1.0%

0% 0% 0% 0% 0% 0% 0% 0%

DOP

DOP DOP DOP DOP

79.1%

0% 0% 0% 0% 0%

DOP

DOP DOP DOP DOP DOP DOP DOP

8.8%

0% 0% 0% 0% 0% 0% 0% 0%

DOP

10.0% 100.0%

DOP DOP DOP DOP DOP

57,686,629

0% 0% 0% 0% 0% 0%

DOP

Amount

Relative Costs

16,000 66,000 3,200 24,000 24,000 8,000 8,000 30,000 -

USD

179,200

USD USD USD USD USD USD USD USD USD

18,000 16,000 30,000 18,000 67,500 54,000 260,000 30,000 -

USD

493,500

USD USD USD USD USD USD USD

70,400 52,800 72,000 72,000 48,000 260,000 -

USD

575,200

USD USD USD USD

44,000,000 880,000 726,000 -

USD

45,606,000

USD USD USD USD USD USD USD

880,000 660,000 200,000 2,500,000 200,000 640,000 -

USD

5,080,000

USD USD USD USD USD

16,000 24,000 3,116,034 2,596,695 5,752,729

USD

USD USD USD USD USD USD USD USD USD USD

271,600 135,800 407,399 75,000 987,635 50,000 18,000 116,726 194,543

USD

2,256,703

Unit Cost

Second currency 0.24000 Foreign Amount

0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

USD USD USD USD USD USD USD USD USD

Unit Cost

USD Cost references: DOP Rate: USD/DOP Relative Costs % Foreign

Cost Cost

Period 10 yr 15 yr

USD USD

3,000,000 5,000,000

USD USD USD

Amount 3,000,000 5,000,000 -

Credit

USD

23/05/2011; Yuma del Mar- Land-Based RE

100.0%

% Foreign

Foreign Amount

0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

DOP DOP DOP DOP DOP DOP DOP DOP DOP DOP

DOP

% Foreign 100% 100% 0%

DOP DOP DOP

Foreign Amount 12,500,000 20,833,333 -

Go to GHG Analysis sheet NRCan/CEDRL

RETScreen Greenhouse Gas (GHG) Emission Reduction Analysis - Wind Energy Project Use GHG analysis sheet?

Yes

Type of analysis

Standard

Complete Financial Summary sheet

Background Information Project Information Project name Project location

Yuma del Mar - 14 mw net Wind RE system Cabo San Rafael Lat 18 Lon -69

Global Warming Potential of GHG 1 ton CH4 = 21 tons CO2 1 ton N2O = 310 tons CO2

(IPCC 1996) (IPCC 1996)

Base Case Electricity System (Reference) Fuel type

Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Diesel (#2 oil) Electricity mix

Fuel mix

CO2 emission factor (kg/GJ) 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 74.1 2,684.8

CH4 emission factor (kg/GJ) 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0725

N2O emission factor (kg/GJ) 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0020 0.0725

Fuel conversion efficiency (%) 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0%

T&D losses (%) 8.0% 8.0% 8.0% 8.0% 8.0% 8.0% 8.0% 8.0% 8.0% 8.0% 80.0%

GHG emission factor (tCO2/MWh) 0.975 0.975 0.975 0.975 0.975 0.975 0.975 0.975 0.975 0.975 9.752

CH4 emission factor (kg/GJ)

N2O emission factor (kg/GJ)

Fuel conversion efficiency

T&D losses

GHG emission factor

(%)

CO2 emission factor (kg/GJ)

(%)

(tCO2/MWh)

100.0%

0.0

0.0000

100.0%

8.0%

0.000

(%) 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 1000%

Proposed Case Electricity System (Mitigation) Fuel type

Electricity system Wind

Fuel mix

GHG Emission Reduction Summary

Electricity system

Base case GHG emission factor (tCO2/MWh) 9.752

Proposed case GHG emission factor (tCO2/MWh) 0.000

End-use annual energy delivered (MWh) 113,578 Net GHG emission reduction

Annual GHG emission reduction (tCO2) 1,107,563 tCO2/yr 1,107,563

Complete Financial Summary sheet Version 2000 - Release 2

23/05/2011; Yuma del Mar- Land-Based RE

UNEP/DTIE and NRCan/CEDRL

RETScreen® Financial Summary - Wind Energy Project Annual Energy Balance Project name Yuma del Mar - 14 mw net Wind RE system Project location Cabo San Rafael Lat 18 Lon -69 Renewable energy delivered MWh 123,454 Excess RE available MWh 9,292 Firm RE capacity kW Grid type Isolated-grid

Grid peak load Grid energy demand GHG analysis sheet used? Net GHG emission reduction Net GHG emission reduction - 25 yrs

kW MWh yes/no tCO2/yr tCO2

13,649 Yes 1,107,563 27,689,087

Financial Parameters Avoided cost of energy RE production credit RE production credit duration RE credit escalation rate GHG emission reduction credit GHG reduction credit duration GHG credit escalation rate Avoided cost of excess energy Avoided cost of capacity Energy cost escalation rate Inflation Discount rate Project life

USD/kWh USD/kWh

yr % USD/tCO2

yr % USD/kWh USD/kW-yr

% % % yr

0.1100 20 1.0% 10 2.0% 120 3.0% 7.0% 12.0% 25

Debt ratio Debt interest rate Debt term Income tax analysis? Effective income tax rate Loss carryforward? Depreciation method Depreciation tax basis Depreciation rate Depreciation period Tax holiday available? Tax holiday duration

% % yr

100.0% 6.0% 15

yes/no No % 35.0% yes/no Yes Declining balance % 95.0% % 30.0% yr 15 yes/no No yr 5

Project Costs and Savings Initial Costs Feasibility study Development Engineering RE equipment Balance of plant Miscellaneous Initial Costs - Total

USD USD USD USD USD USD USD

179,200 493,500 575,200 45,606,000 5,080,000 5,752,729 57,686,629

Incentives/Grants

USD

Periodic Costs (Credits) # Drive train # Blades # End of project life - Credit

USD USD USD USD

3,000,000 5,000,000 -

% % yr yr

#¡DIV/0! #¡DIV/0! 5.1 57,321,077 7,308,436 #¡DIV/0!

0.3% 0.9% 1.0% 79.1% 8.8% 10.0% 100.0%

Annual Costs and Debt O&M Fuel/Electricity Debt payments - 15 yrs Annual Costs - Total

USD USD USD USD

2,256,703 5,939,575 8,196,278

Annual Savings or Income Energy savings/income Capacity savings/income RE production credit income - 20 yrs GHG reduction income - 10 yrs Annual Savings - Total

USD USD USD USD USD

13,579,981 13,579,981

Schedule yr # 10,20 Schedule yr # 15 Schedule yr # 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 Schedule yr # 25

Financial Feasibility Pre-tax IRR and ROI After-tax IRR and ROI Simple Payback Year-to-positive cash flow Net Present Value - NPV Annual Life Cycle Savings Profitability Index - PI Version 2000 - Release 2

USD USD

Calculate RE production cost? Calculate GHG reduction cost? GHG emission reduction cost Project equity Project debt Debt payments Debt service coverage RE production cost

yes/no yes/no USD/tCO2 USD USD USD/yr

USD/kWh

Yes No Not calculated 57,686,629 5,939,575 1.95 0.0549

Yearly Cash Flows Year Pre-tax # USD 0 1 5,633,133 2 5,883,728 3 6,135,079 4 6,386,736 5 6,638,202 6 6,888,930 7 7,138,317 8 7,385,703 9 7,630,363 10 1,970,053 11 8,108,269 12 8,339,703 13 8,564,780 14 8,782,379 15 (4,803,880) 16 15,129,725 17 15,317,131 18 15,491,504 19 15,651,149 20 4,185,173 21 15,918,744 22 16,022,546 23 16,103,298 24 16,158,478 25 16,185,360 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 -

After-tax

Cumulative

USD

5,633,133 5,883,728 6,135,079 6,386,736 6,638,202 6,888,930 7,138,317 7,385,703 7,630,363 1,970,053 8,108,269 8,339,703 8,564,780 8,782,379 (4,803,880) 15,129,725 15,317,131 15,491,504 15,651,149 4,185,173 15,918,744 16,022,546 16,103,298 16,158,478 16,185,360 -

5,633,133 11,516,861 17,651,939 24,038,675 30,676,877 37,565,807 44,704,124 52,089,826 59,720,189 61,690,243 69,798,511 78,138,214 86,702,994 95,485,373 90,681,493 105,811,218 121,128,349 136,619,853 152,271,003 156,456,176 172,374,920 188,397,466 204,500,764 220,659,243 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 236,844,602 NRCan/CEDRL

September 1999

•

NREL/CP-500-27032

Dominican Republic Wind Energy Resource Atlas Development

D. Elliott Presented at SATIS ‘99 San Juan, Puerto Rico August 25–27, 1999

National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 NREL is a U.S. Department of Energy Laboratory Operated by Midwest Research Institute • Battelle • Bechtel Contract No. DE-AC36-98-GO10337

NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Available to DOE and DOE contractors from: Office of Scientific and Technical Information (OSTI) P.O. Box 62 Oak Ridge, TN 37831 Prices available by calling 423-576-8401 Available to the public from: National Technical Information Service (NTIS) U.S. Department of Commerce 5285 Port Royal Road Springfield, VA 22161 703-605-6000 or 800-553-6847 or DOE Information Bridge http://www.doe.gov/bridge/home.html Printed on paper containing at least 50% wastepaper, including 20% postconsumer waste

Dominican Republic Wind Energy Resource Atlas Development Dennis L. Elliott National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, CO USA techniques employed in previous mapping efforts, such as the Wind Energy Resource Atlas of the United States (Elliott et al. 1987) and the Wind Energy Resource Assessment of the Caribbean and Central America (Elliott et al. 1987). The two primary inputs to NREL’s wind mapping system are gridded terrain data with 1 km2 resolution and formatted meteorological data. The meteorological data sources include surface (land and open-ocean) and upper-air data sets. These data are screened to select representative stations and data periods for use as input to the mapping system. The final meteorological inputs to the mapping system are vertical profiles of wind power density, wind power roses, which express the percentage of total potential power from the wind by direction sector, and the openocean wind power density where appropriate for coastal areas. The GIS determines any required adjustments to these composite distributions for each 1-km2 grid cell. The factors that have the greatest influence on the adjustment for a particular grid cell are the topography in the vicinity of the grid cell and a combination of the absolute and relative elevation of the grid cell. The primary output of the mapping system is a color-coded map containing the estimated wind power density, and equivalent wind speed, for each individual grid cell.

Introduction A wind resource analysis and mapping study was conducted for the Dominican Republic. The purpose of this study was to identify most favorable wind resource areas and quantify the value of that resource within those areas. This was a major study and the first of its kind undertaken for the Dominican Republic. The key to the successful completion of the study was an automated wind resource mapping program recently developed at the National Renewable Energy Laboratory (NREL), a U. S. Department of Energy (DOE) national laboratory. DOE and the U.S. Agency for International Development (USAID), in collaboration with Winrock International and the U.S. National Rural Electric Cooperative Association (NRECA), sponsored this study to facilitate and accelerate the large-scale use of wind energy technologies in the Dominican Republic. NREL had the lead responsibility in administering and conducting this project and in collaborating with USAID, NRECA, and Winrock on project activities. The primary goal of the project was to develop detailed wind resource maps for all regions of the Dominican Republic and to produce a comprehensive wind resource atlas documenting the mapping results.

To portray the mapping results, the Dominican Republic was divided into four regions—southwestern, northwestern, central, and eastern. Each region covered an area of approximately 160 km by 160 km. The regional divisions were determined principally by the geography of the country and the desire to maintain the same map scale for each region. Surface, satellite, and upper-air data were assembled, processed, and analyzed. These data sets included information provided by the Dominican Republic meteorological service (Oficina Nacional de Meteorologia), the Dominican Republic hydrological service (Instituto Nacional de Recursos Hidraulicos), USAID, U.S. National Climatic Data Center, U.S. National Center for Atmospheric Research, and other U.S. sources. The data from USAID’s sites (Figure 1) were collected in collaboration with the NRECA and Winrock International/REGAE (Renewable Energy Growth Assistance Entity). The satellite data sets of calculated ocean wind speeds were extremely useful in this analysis due to the large expanse of ocean surrounding

The Wind Energy Resource Atlas of the Dominican Republic (Elliott et al. in progress) presents the wind resource analysis and mapping results for the Dominican Republic. The wind resource maps were created using a program developed at NREL based on Geographic Information System (GIS) software. The mapping program combines high-resolution terrain data and formatted meteorological data and is designed to highlight the most favorable wind resource areas for wind energy projects based on the level of wind resource. Mapping System and Methodology NREL recently developed an automated wind resource mapping system to replace the manual analysis

usually viable at lower wind speeds (5 to 6 m/s), in some cases at wind speeds as low as 4.5 m/s.

the Dominican Republic and the limited number and value of land-based observations. The mapping system generated a composite national wind resource map of the Dominican Republic and the four regional wind resource maps.

The average wind speed is not the best indicator of the resource. Instead, the level of the wind resource is often defined in terms of the wind power density value, expressed in watts per square meter (W/m2). This incorporates the combined effects of the wind speed frequency distribution and the dependence of the wind power on air density and the cube of the wind speed. Thus, six wind power classifications, based on ranges of wind power density values, were established in each of two categoriesâ&#x20AC;&#x201D;one for utility scale applications, ranging from marginal to excellent, and one for rural power applications, ranging from moderate to excellent. This classification scheme is presented in Table 1.

A combination of wind characteristics helps to determine the wind energy resource in a particular area. Factors such as the annual and monthly average wind speeds and the seasonal and diurnal wind patterns affect the suitability of an area for development. In general, locations with an annual average wind speed of 7 meters per second (m/s) or greater at turbine hub height are most suitable for utility grid-connected wind energy systems, and some locations with speeds between 6 and 7 m/s may be viable. Rural power applications are

Table 1. Wind Power Classification Class

Resource Potential Utility Rural

1 2 3 4 5 6

Marginal Moderate Good Excellent Excellent Excellent

Moderate Good Excellent Excellent Excellent Excellent

Wind Power Density (W/m2) @ 30 m asl 100-200 200-300 300-400 400-600 600-800 800-1000

Wind Speed (a) (m/s @ 30 m asl) 4.9 – 6.1 6.1 – 7.0 7.0 – 7.7 7.7 – 8.9 8.9 – 9.8 9.8 – 10.5

(a)

Mean wind speed is estimated assuming a Weibull distribution of wind speeds with a shape factor (k) of 3.0 and standard sea-level air density. The actual mean wind speed may differ from these estimated values by as much as 20 percent, depending on the actual wind speed distribution (or Weibull k value) and elevation above sea level.

east. The extreme southwestern and northwestern regions of the country are estimated to have the greatest number of areas with good-to-excellent wind resources for utility-scale applications, because the upper-air winds and ocean winds are greatest in these regions.

Wind Mapping Results The wind resource in the Dominican Republic is strongly dependent on elevation and proximity to the coastline. In general, the wind resource is best on hilltops, ridge crests, and coastal locations that have excellent exposure to the prevailing winds from the

The wind mapping results (Figure 2) show many areas

windy land areas have been estimated to exist with good-to-excellent wind resource potential. This windy land represents less than 3% of the total land area (48,442 km2) of the Dominican Republic. Using conservative assumptions of about 7 MW per km2, this windy land could support over 10,000 MW of potential installed capacity and potentially delivering over 24 billion kWh per year. Considering only these areas of good-to-excellent wind resource, there are 20 provinces in the Dominican Republic with at least 100 MW of wind potential and 3 provinces with at least 1000 MW of wind potential. However, additional studies are required to more accurately assess the wind electric potential, considering factors such as the existing transmission grid and accessibility.

of good-to-excellent wind resource for utility-scale applications or excellent wind resource for village power applications, particularly in the extreme southwestern and northwestern regions of the country. The best wind resources are found in the southwestern provinces of Pedernales and Barahona and the northwestern provinces of Puerto Plata and Monte Cristi. Significant areas of good-to-excellent wind resource can be found in many other locations, such as well-exposed hilltops and ridge crests of the Samana peninsula and other near-coastal locations throughout the Dominican Republic and the major mountain ranges including Cordillera Septentrional, Cordillera Oriental, Cordillera Central, and Sierra Neiba. The mapping results show many additional areas of moderate wind resource for utility-scale applications or good wind resource for village power applications, including many east-facing coastal locations along the eastern and northern coasts of the Dominican Republic.

If the additional areas with moderate wind resource potential (or good for rural power applications) are considered, the estimated total windy land area increases to more than 4400 km2, or slightly more than 9% of the total land area of the Dominican Republic. This windy land could support more than 30,000 MW of installed capacity, delivering more than 60 billion kWh per year. There are 12 provinces with at least 1000 MW of wind potential and all except for three provinces have at least 100 MW of wind potential.

Wind Electric Potential The assumptions and methods for converting the wind resource to wind energy potential were based on those in the report Renewable Energy Technology Characterizations (DeMeo and Galdo 1997) and are listed at the bottom of Table 2. About 1500 km2 of

Table 2. Dominican Republic—Wind Electric Potential Good-to-Excellent Wind Resource at 30 m (Utility Scale) Wind Resource Utility Scale

Wind Power W/m2

Wind Speed M/s*

Total Area km2

Total Cap Installed MW

Total Power GWh/yr

Good Excellent Excellent Excellent Total

300 400 600 800

7.0 7.7 8.9 9.8

1,022 377 61 22 1,482

7,000 2,600 400 200 10,200

15,600 7,100 1,400 500 24,600

– 400 – 600 – 800 – 1000

– 7.7 – 8.9 – 9.8 – 10.5

Wind speeds are based on a Weibull k value of 3.0

Assumptions Turbine Size: 500 kW Rotor Diameter: 38m Capacity/km2: 6.9 MW

Hub Height: 40m Turbine Spacing: 10D by 5D

the highest wind resource from June to August and December to February, with a maximum in July and a minimum in October. The diurnal pattern of wind speeds on exposed ridge crests tend to have the highest speeds during the night and early morning hours and lowest during mid-day.

Wind Resource Characteristics The seasonal and diurnal (time-of-day) variability of the wind resource depends on several factors including proximity to coastline and exposure to ocean winds, elevation above sea level and surrounding terrain, and geographic location. High ridge crests that have excellent exposure to the winds are expected to have

At most inland locations, the wind resource is typically highest from June through August due to greater winds aloft and greater vertical mixing, with a secondary seasonal maximum from March through May. The wind resource at inland locations is usually lowest from October through December. The wind resource at inland locations is typically highest during late morning and afternoon and is lowest from late night to early morning. In most coastal areas where land-sea breeze effects and other land-based influences are prominent, the seasonal and diurnal variations of the wind resource are usually similar to those for inland areas.

References DeMeo, E.A., and J.F. Galdo, Renewable Energy Technology Characterizations, Office of Utility Technologies, Energy Efficiency and Renewable Energy, U.S. Department of Energy, Washington D.C., December 1997. Elliott, D.L., C.I. Aspliden, G.L. Gower, C.G. Holladay, and M.N. Schwartz, Wind Energy Resource Assessment of the Caribbean and Central America, Pacific Northwest Laboratory, Richland, Washington, April 1987, 115 pp.

Coastal points on capes and peninsulas that are well exposed to the ocean winds are expected to have the highest wind resource from June to August and December to February. Generally, these types of locations will exhibit very small diurnal variations in the wind resource and are not significantly influenced by land-sea breeze flows and other types of land-based effects on the wind flow.

Elliott, D.L., C.G. Holladay, W.R. Barchet, H.P. Foote, and W.F. Sandusky, Wind Energy Resource Atlas of the United States, Solar Energy Research Institute, Golden, Colorado, 1987. Elliott, D., M. Schwartz, R. George, S. Haymes, D. Heimiller, and G. Scott, Wind Energy Resource Atlas of the Dominican Republic, National Renewable Energy Laboratory, Golden, Colorado, in progress.

Conclusions and Recommendations The wind resource maps and other wind resource characteristic information in the Dominican Republic wind atlas will be useful for identifying prospective areas for wind energy applications. However, very limited data were available to validate the wind resource estimates. Therefore, it is strongly recommended that wind measurement programs be conducted to validate the resource estimates and refine the wind maps and assessment methods where necessary. A wind measurement program is underway by USAID in collaboration with NRECA and Winrock/REGAE, and it is hoped that this program can be improved and expanded to include additional locations that are particularly valuable in the validation of this wind mapping assessment. Acknowledgements I would like to thank Marc Schwartz, Ray George, Steve Haymes, Donna Heimiller, and George Scott of NRELâ&#x20AC;&#x2122;s wind resource assessment group, and Jack Kline of RAM Associates, for their contributions to software development, data processing, and GIS mapping applications. This paper was written at the National Renewable Energy Laboratory in support of U.S. Department of Energy under contract number DEAC36-98GO10337, and U.S. Agency for International Development under Interagency Agreement No. 517-P00-00151-00, FWP#WF7A-5600.