NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

Fort Carson Wind Resource 

Assessment 

R. Robichaud

Produced under direction of the Department of Defense by the National 

Renewable Energy Laboratory (NREL) under Interagency Agreement 

IAG-11-1837 and Task No WFL5.1008. 

Technical Report

NREL/TP-7A40-56409

October 2012
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

National Renewable Energy Laboratory

15031 Denver West Parkway

Golden, Colorado 80401

303-275-3000 • www.nrel.gov

Contract No. DE-AC36-08GO28308

Fort Carson Wind Resource 

Assessment

R. Robichaud

Prepared under Task No. WFL5.1008

Technical Report

NREL/TP-7A40-56409

October 2012
NOTICE

This manuscript has been authored by employees of the Alliance for Sustainable Energy, LLC (“Alliance”) under 

Contract No. DE-AC36-08GO28308 with the U.S. Department of Energy (“DOE”).

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.

Cover Photos: (left to right) PIX 16416, PIX 17423, PIX 16560, PIX 17613, PIX 17436, PIX 17721

Printed on paper containing at least 50% wastepaper, including 10% post consumer waste.
iii

Acknowledgments

The wind resource analysis and assessment was sponsored by the Department of Defense 

(DoD). Information regarding the location of each facility, utility use, and cost 

information was provided by Vince Guthrie, energy manager at Fort Carson. The 

installation of the met tower was undertaken by Brett Jackson, Green Buildings Engineer 

with Army National Guard. The Sonic Detection and Ranging (SODAR) was loaned by 

the Department of Energy (DOE) through the National Renewable Energy Laboratory 

(NREL). The SODAR data analysis was sponsored for by the Army National Guard and 

completed by Ken Underwood of Atmospheric Systems Corporation.

NREL staff members involved were Robi Robichaud, principal investigator, and Kate 

Anderson, NREL’s project lead for net zero energy planning at Fort Carson.
iv

List of Acronyms

ASOS automated surface observing systems

AWEA American Wind Energy Association

BAU business as usual

BLCC building life-cycle cost

COE cost of energy

DAS data acquisition system

DOE U.S. Department of Energy

ECIP Energy Conservation and Investment 

Program

EISA Energy Independence and Security Act of 

2007

E.O. Executive Order

EPAct 2005 Energy Policy Act of 2005

ESPC energy savings performance contract

FAA Federal Aviation Administration

ft feet

FY fiscal year

GIS geographic information systems

IEC International Electrotechnical Commission

ITC investment tax credit

LCC life cycle cost

m meter

MCP measure-correlate-predict

MW megawatts

NEXRAD next-generation weather radar program

NOAA National Oceanic and Atmospheric 

Administration

NREL National Renewable Energy Laboratory

NWS National Weather Service

O&M operation and maintenance

PPA power purchase agreement

PTC Production Tax Credit

RFP request for proposal

RLOS radar line of sight

R&D research and development

ROI return on investment

SODAR sonic detection and ranging

SPB simple payback

TI turbulence intensity

TSR tip speed ratio 

UESC utility energy services contract

VWSF vertical wind shear factor

Wp peak Watt
v

Executive Summary

The U.S. Army has long been interested in reducing its dependence on fossil fuels for 

energy, increasing its energy security, and reducing its energy intensity. Increasing the 

use of renewable energy at Army bases serves all of these goals. As part of these efforts, 

the Army has been collaborating with the U.S. Department of Energy’s (DOE’s) National 

Renewable Energy Laboratory (NREL) to evaluate renewable energy options at Fort 

Carson, Colorado.

This report focuses on the wind resource assessment, the estimated energy production of 

wind turbines, and economic potential of a wind turbine project on a ridge in the 

southeastern portion of the Fort Carson Army base.

Wind data was collected from a 50-meter (m) meteorological (met) tower on a small 

ridge in the southeastern part of the Fort Carson base. A mini sonic detection and ranging

(miniSODAR) unit was also deployed at this site to measure wind speeds at elevations 30

to 140 m (98 to 459 ft) above the ground. The data collected provided an effective dataset 

for comparative analysis of wind speed, turbulence intensity, and energy production of 

several wind turbines suitable for the wind conditions at the site. Table ES-1 shows the 

summary results of estimated annual energy production figures, capacity factors, and 

percent of Fort Carson load the wind can supply.

Table ES-1. Summary Wind Project Energy Performance of Sample Wind Turbines 

Table ES-2 provides a sensitivity analysis, comparing the impacts of different project 

financing scenarios assuming third-party ownership with a production tax credit (PTC) of 

$0.022/kWh in effect, and targeting approximately 11.2 megawatts (MW) of wind 

capacity. Two sets of assumptions are analyzed, the first assuming a 20-year power 

purchase agreement (PPA) with 0% debt fraction as the base case. The second set of 

assumptions being the similar, but increasing the debt fraction from 0% to 30% and 

100%. The impacts (items that vary) are shown in the colored boxes.

Turbine Manufacturer 

& Model

Rated 

Power

Mean 

Net 

Power 

Ot t

Mean Net 

Annual Energy 

/Turbine/Yr

Net 

Capacity 

Factor

FC#2 

Site 

Wind 

Plant 

Capacity

Wind Plant 

Annual 

Output

% of Base 

Energy

Turbine MW kW kWh/yr % # Turb. MW MWh/yr %

GE 1.6 XLE 1.6 415 3,634,101 25.9 7 11.2 25,439 15.7%

Suzlon S97 2.1 475 4,162,921 22.6 7 14.7 29,140 18.0%

Siemens SWT-2.3 108 2.3 572 5,014,293 24.9 7 16.1 35,100 21.6%

Siemens SWT-2.3 113 2.3 691 6,049,308 30.0 7 16.1 42,345 26.1%

Nordex N117 2.4 647 5,665,505 26.9 7 16.8 39,659 24.4%

Vestas V112 - 3.0 MW 3.0 677 5,933,315 22.0 7 21.0 41,533 25.6%
vi

Table ES-2. Sensitivity Analysis and Comparison of Financing Scenarios

Overall, the wind resource at the selected sites at Fort Carson is sufficient for a wind 

turbine project, though the specific approach needs refinement. There are a number of 

other factors to consider before turbine selection is undertaken, including cost, 

availability, constructability, and transportability. There are also a number of other 

factors still to be explored as the parameters of this project become more clearly defined,

including on-site military operations, Federal Aviation Administration (FAA), financing, 

National Environmental Protection Act (NEPA), constructability, subsoil/foundations, 

impact on neighbors, and transportation planning and logistics. 

There are a number of proposed tasks to continue to move this project forward, including:

• Fort Carson to complete the NEPA evaluation already underway

• Complete an electrical interconnection study

• Determine the most appropriate financing mechanism and secure project 

funding/finance

• Complete the transportation and logistics study

• Complete the visual and sound impact study

• Develop and implement a public information plan.

Sensitivity Factors Mean Net 

Annual 

Energy 

Output

Net 

Capacity 

Factor

Total of 

Annual 

Energy 

Savings

Annual 

O&M

% AterTax ROI 

to Equity 

Partner

Estimated 

Installed 

Cost

Life Cycle 

Cost

Estimated 

Cost of 

Wind 

Energy

Savings to 

Investment 

Ratio

Simple 

Payback

MWh/yr % $ $ % $ $ $/kWh unitless yrs

PPA - 20 yr; 0% debt 25,439 25.9% $2,060,643 $331,130 4.7% $25,345,600 $1,292,988 $0.056 1.05 14.7

PPA - 20 yr; 30% debt 25,439 25.9% $2,060,643 $331,130 4.5% $25,345,600 $777,496 $0.057 1.04 14.7

PPA - 20 yr; 100% debt 25,439 25.9% $2,060,643 $331,130 -0.03% $25,345,600 ($641,052) $0.061 N/A 14.7

PPA - 25 yr; 0% debt 25,439 25.9% $2,060,643 $331,130 4.9% $25,345,600 $5,735,813 $0.047 1.23 14.7

PPA - 25 yr; 30% debt 25,439 25.9% $2,060,643 $331,130 5.4% $25,345,600 $5,150,676 $0.049 1.29 14.7

PPA - 25 yr; 100% debt 25,439 25.9% $2,060,643 $331,130 pos $25,345,600 $3,472,020 $0.052 N/A 14.7
vii

Table of Contents

Acknowledgments......................................................................................................................................iii

List of Acronyms ........................................................................................................................................iv

Executive Summary ....................................................................................................................................v

Table of Contents ......................................................................................................................................vii

List of Figures.............................................................................................................................................ix

List of Tables................................................................................................................................................x

1 Introduction ...........................................................................................................................................1

2 Location .................................................................................................................................................2

3 Site Characterization ............................................................................................................................4

4 Wind Resource Assessment Campaign .............................................................................................6

4.1 Wind Resource Assessment Activities at Fort Carson.....................................................................6

5 Wind in Colorado ..................................................................................................................................7

6 Instrumentation and Equipment..........................................................................................................9

6.1 Meteorological Towers .....................................................................................................................9

6.2 50-m Met Tower at Fort Carson .......................................................................................................9

6.3 Site Summary – Met Tower..............................................................................................................9

6.4 SODAR Systems ............................................................................................................................10

6.5 MiniSODAR at Fort Carson ............................................................................................................10

6.6 Site Summary – MiniSODAR..........................................................................................................11

7 Data Recovery and Validation ...........................................................................................................12

7.1 Data Analysis..................................................................................................................................12

8 Wind Resource Assessment Summary ............................................................................................14

8.1 Wind Resource Characterization....................................................................................................14

8.2 Measuring Power in the Wind.........................................................................................................14

8.3 Fort Carson Wind Speed Variability ...............................................................................................14

8.4 Fort Carson Monthly Box Plot Statistics .........................................................................................15

8.5 Fort Carson Seasonal Wind Profile ................................................................................................16

8.6 Fort Carson Diurnal Wind Profile....................................................................................................16

8.7 Fort Carson Wind Direction Data....................................................................................................17

8.8 Fort Carson Wind Frequency (Probability) Distribution..................................................................20

8.9 Vertical Wind Shear........................................................................................................................21

8.10 Turbulence Intensity.................................................................................................................25

9 Long-Term Data Adjustment..............................................................................................................28

9.1 Long-Term Datasets.......................................................................................................................28

9.2 ReEDS Data Set.............................................................................................................................28

9.3 Vertical Wind Shear Adjustment.....................................................................................................30

10 Energy Production Estimates............................................................................................................31

10.1 Site Layout ...............................................................................................................................31

10.2 Wind Turbines Modeled ...........................................................................................................32

10.3 Energy Production Loss Factors..............................................................................................32

10.4 Projected Wind Project Performance.......................................................................................32

11 Economic Analysis .............................................................................................................................34

11.1 Incentives .................................................................................................................................34

11.2 Wind Turbine Project Cost Factors ..........................................................................................36

11.3 ECIP Sensitivity Analysis .........................................................................................................40
viii

12 Conclusions and Recommendations................................................................................................42

12.1 Conclusions..............................................................................................................................42

12.2 Recommendations ...................................................................................................................43

Appendix A. Wind Sensors & Tower .......................................................................................................45

Appendix B. Fort Carson Met Tower Commissioning Report ..............................................................48

Appendix C. Preliminary FAA Screening................................................................................................52

Appendix D. Fort Carson Met Tower .......................................................................................................55

Appendix E. Wind Turbine Energy Production Loss Factors...............................................................56
ix

List of Figures

Figure 1. Location of Fort Carson in south-central Colorado.................................................................2

Figure 2. Southeastern Fort Carson with potential met tower sites ......................................................3

Figure 3 Topographical map of Fort Carson area with FC#2 shown .....................................................4

Figure 4. Colorado wind speed map at 80 m ............................................................................................7

Figure 5. Enlarged Colorado 80-m wind map with Fort Carson met tower site circled in blue...........8

Figure 6. The Wind ExplorerTM miniSODAR unit from Atmospheric Systems Corporation 

Photo credit: Robi Robichaud, NREL...................................................................................11

Figure 7. Wind speed variations between miniSODAR and FC#2 met tower......................................13

Figure 8. Wind data at 50-m at FC#2........................................................................................................15

Figure 9. Boxplot of FC#2 for1/1/2008-8/30/2009....................................................................................15

Figure 10. Seasonal wind speed profile at FC#2 for 1/1/2008-8/30/3009..............................................16

Figure 11. Diurnal profile of the wind speed at FC#2 for 1/1/2008-8/30/3009 ......................................16

Figure 12. Monthly diurnal profile of the wind speed at FC#2 for 1/1/2008-8/30/3009........................17

Figure 13. Wind Frequency Rose on left and Mean of Speed Rose on right at FC#2 for 

1/1/2008-8/30/3009 ...................................................................................................................18

Figure 14. Total wind energy rose at FC#2 for 1/1/2008-8/30/3009.......................................................19

Figure 15. Total wind energy rose by month at FC#2 for 1/1/2008-8/30/3009......................................20

Figure 16. Wind frequency distribution at FC#2 for 1/1/2008-8/30/3009 ..............................................21

Figure 17. Vertical wind shear profile at FC#2 for 1/1/2008-8/30/3009 .................................................24

Figure 18. Daily wind shear profile by month at FC#2 for 1/1/2008-8/30/3009 ....................................24

Figure 19. Representative and mean turbulence intensities at FC#2 for 1/1/2008-8/30/3009 ............26

Figure 20. Turbulence intensity at FC#2 for 1/1/2008-8/30/3009...........................................................27

Figure 21. Long term mean wind speed using the ReEDS data for FC#2............................................29

Figure 22. Potential wind turbine layout in southern half of southeast corner of Fort 

Carson. .....................................................................................................................................31

Figure A-1. Anemometer #40C NRG Systems (item 1899) ....................................................................45

Figure A-2. Wind vane NRG Systems #200P (item 1904) ......................................................................46

Figure A-3. Boom, side, 1.53m (60.5"), galvanized, with clamps (item: 3390).....................................46

Figure A-4. 50m and 60m XHD Tower configuration..............................................................................47

Figure 23 Fort Carson 50m met tower with bird diverters. Photo credit: Robi Robichaud, 

NREL.........................................................................................................................................55

Figure 24 Fort Carson 50m met tower – view from the northwest. Photo credit: Robi 

Robichaud, NREL....................................................................................................................55
x

List of Tables

Table ES-1. Summary Wind Project Energy Performance of Sample Wind Turbines..........................v

Table ES-2. Sensitivity Analysis and Comparison of Financing Scenarios.........................................vi

Table 3. Sensors, Heights, and Orientations at FC#2 for 1/1/2008-10/15/2009......................................9

Table 4. Site Summary of FC#2 for 1/1/2008-8/31/2009..........................................................................10

Table 5. Site Summary of the MiniSODAR Site at Fort Carson for 4/1/2008-9/25/2008 ......................11

Table 6. Dataset Recovery Rates for FC#2 for 1/1/2008-9/30/2009 .......................................................12

Table 7. Wind Speed Recovery Rates for the MiniSODAR for 3/1/2008-9/25/2008..............................12

Table 8. Surface Roughness Lengths and Descriptions.......................................................................22

Table 9. Power Law Exponent and Surface Roughness Length at FC#2 for 1/1/2008-

8/30/3009...................................................................................................................................23

Table 10. IEC Wind Turbine Classes, Ratings, and Characteristics of Turbulence Intensity............26

Table 11. Nearby ASOS Met Towers........................................................................................................28

Table 12. Ratio of the Mean Wind Speed by Year to Long Term Mean at Site #101095.....................29

Table 13. Comparison of Wind Speeds at Common Heights from Three Data Sources....................30

Table 14 Wind Turbine Specifications Used in Modeling......................................................................32

Table 15 Summary Wind Project Energy Performance of Sample Wind Turbines at Fort 

Carson ......................................................................................................................................33

Table 16 Economic Comparison of 20- and 25-year ECIP-funded Wind Project ................................40

Table 17 Sensitivity Analysis of Beneficial Changes to Project Parameters ......................................40

Table 18 Sensitivity Analysis of Negative Changes to Project Parameters ........................................41

Table 19 PPA - Sensitivity Analysis of Financing Factors ....................................................................41

Table 20. Summary of Wind Project Energy Performance of Sample Wind Turbines .......................42

Table 21. Comparison of Financing Scenarios ......................................................................................43
1

1 Introduction

The U.S. Army has long been interested in reducing its dependence on fossil fuels for 

energy; increase its energy security and reducing its energy intensity. Increasing the use 

of renewable energy at Army bases serves all of these goals. As part of these efforts, the 

Army has been collaborating with the U.S. Department of Energy’s (DOE’s) National 

Renewable Energy Laboratory (NREL) to evaluate renewable options at Fort Carson,

Colorado.

This report focuses on the wind resource assessment, the estimated energy production of 

wind turbines, and a survey of potential wind turbine options based upon the site-specific

wind resource.
2

2 Location

Fort Carson, initially named Camp Carson, was established in 1942. It is located several 

miles south-southwest of Colorado Springs, Colorado. Most of the base is in El Paso 

County though it extends into Fremont County to the southwest and into Pueblo County 

to the south and southeast.

Fort Carson encompasses ~137,000 acres extending ~40 kilometers (km) (~25 miles)

south from the primary base facilities near Colorado Springs. The base is located southsoutheast of Pikes Peak, elevation 4,300 m (14,110 ft), in south-central Colorado. Much 

of the base elevation ranges between 1,600 to 1,800 m (5,200 to 5,900 ft) though the 

Front Range of the Rocky Mountains provides rough, mountainous terrain to the west and 

northwest of the northern two thirds of the base with elevations in the 2,000 to 3,000 m 

(6,600 to 9,800 ft) range. Figure 1 shows Fort Carson relative to Colorado Springs.

Figure 1. Location of Fort Carson in south-central Colorado

Source: http://www.colorado.gov/apps/maps/neighborhood.map

The areas of interest (rectangles labeled “Wind site”) for potential wind resource 

assessment and development are shown in the map in Figure 2 below. Two potential met 

tower sites, labeled Met Tower Site #1 and Met Tower Site #2 are marked within the 

areas of interest. Met Tower Site #1 site was eliminated from consideration early in the 

project development cycle due to its close proximity to the area labeled “Off Limits 
3

Impact Area.” Met Tower Site #2 became the primary site of interest for further 

investigation. This site is referred to as Fort Carson #2 (FC#2).

Figure 2. Southeastern Fort Carson with potential met tower sites

Source: Vince Guthrie, Energy Manager, Fort Carson
4

3 Site Characterization

The entire base of Fort Carson (excluding the Pinon Canyon training area) is relatively 

flat, semi-arid terrain that bridges high plains and foothills land formations.1 The Fort 

Carson land has broad, gently sloping valleys and generally rounded ridges markedly 

smoother than the more mountainous regions to the north and northwest. The ridges 

provide improved exposure to wind; though their orientation to prevailing wind direction 

and proximity to more abrupt terrain will impact the degree of turbulence intensity 

experienced at particular sites.

Overall vegetation is relatively sparse compared to the higher terrain of the foothills

region south of Pikes Peak. There are more vegetated pockets scattered around the base 

that tend to be in areas where the terrain provides greater shade or water than the more 

exposed areas do.

The topography of the southern portion of the Fort Carson base is displayed within the 

green boundary on the map below in Figure 3. The green rectangle in the southeast corner 

represents the primary area of interest for wind development. 

Figure 3 Topographical map of Fort Carson area with FC#2 shown

Source: Tibor Hedegus, General Manager, Revolution Energy LLC

Within a 2 km (1.2 mi) radius from FC#2, the landscape is dotted with pinion trees 

ranging in size from ~3 to 8 m (~10 to 25 ft). The terrain near FC#2 is generally 

undulating with small hills, ridges, and canyons. FC#2 is near the top of a small northsouth ridge with elevations varying between 1,700 to 1,730 m (5,580 to 5,675 ft). The 

ridge elevation is generally consistent extending 2 km (1.2 mi) both north and south from 

 1

 Fort Carson Installation Design Guide, Standards, Section 7 – Site Planning Design Standards, Natural 

Conditions, Topography 

http://www.carson.army.mil/DPW/FtCarsonDesignGuide/06_Standards/Section07_SitePlanningDesignSta

ndards/7.4.1_body.htm, accessed Jan 25, 2012.

FC #2
5

FC#2. The land slopes consistently downward from the northeast through southeast. To 

the west is a gently sloping drainage or canyon that slopes south with elevation changes 

from 1,730 to 1,670 m (5,675 to 5,480 ft) from north to south. West of the canyon is a 

slightly higher, more rugged ridge with elevations ranges of 1,710 to 1,760 m (5,610 to

5,775 ft). Winds coming over this ridge from the west moving towards FC#2 will likely 

experience turbulence at lower elevations above the ground due to the undulations of the

canyon/drainage.
6

4 Wind Resource Assessment Campaign

The intent of the wind resource assessment was to characterize the wind resource for the 

southeastern portion of the base in proximity to FC#2. The primary wind characteristics 

of interest include:

• Wind speed at or close to proposed wind turbine sites 

• Vertical wind shear factor (VWSF) to determine wind speeds at hub height of 

potential wind turbines

• Wind speed frequency distribution, or probability distribution function

• Turbulence intensity (TI) to determine turbine site suitability based upon 

standard International Electrotechnical Commission (IEC) classifications.

4.1 Wind Resource Assessment Activities at Fort Carson

Wind measurement equipment and assessment activities were installed and performed in 

the southeastern corner of the base. Due to variation in terrain and large topographical 

features, this wind resource assessment is not suitable for determining the wind resource 

at the cantonment area of Fort Carson. 

Training and operations at Fort Carson make it challenging to find any sites for wind 

development completely out of the way of military activities. FC#2 was deemed 

potentially viable for wind development due to its proximity to the southeastern border of 

Fort Carson. Further investigation with all aspects of Fort Carson’s training and 

operations units will be necessary before any decisions to move forward with a wind 

turbine project.

The wind assessment campaign actively engaged in assessing the wind resource through 

different approaches with a variety of wind sensor equipment, as follows:

• FC#2: 50-m (164-ft) met tower installed and commissioned 12/27/2007 and 

operational for 22 months until 10/15/2009.

• MiniSODAR: trailer unit installed and operational at Fort Carson from 

3/19/2008 through 9/25/2008.

The wind data collected by these devices during the timeframes listed was used for the 

subsequent analyses in this report.
7

5 Wind in Colorado

Wind maps provide a graphical estimation of the wind resource in an area but do not 

incorporate sufficient information to reliably estimate annual electricity generation at any 

specific point. Areas of varying vegetation (e.g., tall trees versus grassland or cropland), 

complex topographical features (e.g., ridges versus valleys or canyons versus mountains), 

and varying surface roughness (e.g., city skyscrapers versus flat or rolling farmland) are 

characterized by highly variable wind resources that are very site specific. 

Sites in close proximity to each other, but with the above variations, can represent 

different wind power densities. Wind maps are valuable for understanding, where strong 

winds merit further investigation with on-site wind monitoring stations. Wind maps are 

not, however, typically used to site large wind farms, because maps lack the micro-siting 

detail required to minimize the energy estimation uncertainty to the level required by 

financiers. On-site wind data collected for a period of 1 to 3 years is the industry norm to 

estimate wind turbine performance accurately. This study used recently collected on-site 

wind data for its analysis and energy production estimates.

The wind map for Colorado, shown in Figure 4, provides a context for the data analysis 

that follows. The wind map indicates that the Fort Carson region has an expected mean 

annual wind speed between 6.0 to 7.0 meters per second (m/s) (13.4 to 15.7 miles per 

hour (mph)) at 80 m (262 ft). Depending upon access to wind as it moves across the 

mountains, rolling hills, canyons and mesas, some variation in wind speeds is expected.

Figure 4. Colorado wind speed map at 80 m

Source: http://www.windpoweringamerica.gov/images/windmaps/co_80m.jpg.
8

Figure 5 shows an enlarged version of the Colorado wind map. The estimated wind speed 

near the FC#2 (blue oval) appears to be between 6.5 to 7.0 m/s (14.5 to 15.7 mph).

Figure 5. Enlarged Colorado 80-m wind map with Fort Carson met tower site circled in blue
9

6 Instrumentation and Equipment

6.1 Meteorological (Met) Towers

Met towers are temporary structures installed at, or as close as possible to, potential wind 

turbine sites to reduce the uncertainty of wind turbine energy production estimates. 

Towers may be 40 to 100 m (130 to 330 ft) tall, though 60 to 80 m (200 to 260 ft) is the 

most common for utility-scale wind turbine investigations. Met towers are configured 

with multiple anemometers to measure the wind speed near the top of the tower and at 10

to 15-m (33 to 50-ft) intervals above the ground to a minimum height of 20 to 30 m (65

to 100 ft). Met towers will also typically have two to three wind vanes to measure the 

wind direction at several heights.

6.2 50-m Met Tower at Fort Carson

The Army National Guard at Fort Carson contracted for the purchase and installation of a 

50-m (164-ft) met tower. The tower was installed in December 2007 and commissioned 

on 12/29/2007. The instrumentation consisted of an NRG 50-m Tall Tower, four 

anemometers, two wind vanes, a temperature sensor, and a data logger. The met tower

was erected at the FC#2. Table 1 summarizes details of the sensor configuration on the 

met tower at FC#2. The information was taken from the Fort Carson commissioning 

report.2 Sensor and tower details are in Appendix A.

Table 3. Sensors, Heights, and Orientations at FC#2 for 1/1/2008-10/15/2009

6.3 Site Summary – Met Tower

Table 4 summarizes the dataset properties, environmental conditions, and wind power 

and wind shear coefficients for FC#2.

 2

B. Jackson emailed the report to NREL in January 2008.

ChannelSensor Sensor 

Height

OrientationBoom 

Length

Scale Offset Calibration 

Date

# # m (ft) deg m (ft) mm/dd/yyyy

1 NRG MAX #40 C 48.5 (159) 315 1.2 (3.9) 0.765 0.35 11/20/2007

2 NRG MAX #40 C 48.5 (159) 225 1.2 (3.9) 0.765 0.35 11/20/2007

3 NRG MAX #40 C 40.7 (133.5) 270 1.2 (3.9) 0.765 0.35 11/20/2007

4 NRG MAX #40 C 30 (98.4) 270 1.2 (3.9) 0.765 3.5 11/20/2007

7 NRG #200 - P 48.0 (157) 0 1.2 (3.9) 0.351 0 0

8 NRG #200 - P 29.4 (96.4) 0 1.2 (3.9) 0.351 0 0

9 110S 3 (10) N/A N/A 0.136 -86.383 -86.383
10

Table 4. Site Summary of FC#2 for 1/1/2008-8/31/2009

6.4 SODAR Systems

Mini sonic detection and ranging (miniSODAR) systems are a relatively new, remote 

sensing technology utilized to conduct or augment wind resource measurement and 

characterization. MiniSODAR systems measure the vertical turbulence structure and the 

wind profile of the lower layer of the atmosphere at elevations up to several hundreds of 

meters. SODAR systems operate by emitting an acoustic pulse that travels up into the air 

and is reflected by moisture or particulates moving in the air. The Doppler (frequency) 

shift of the return signal is then analyzed to calculate the speed, direction, and turbulent 

character of the air mass above the SODAR. A profile of the lower atmosphere as a 

function of height is obtained by analyzing the return signal at different intervals that 

follow the transmission of each pulse. A miniSODAR system can effectively characterize 

the wind up to 100 to 150 m (330 to 500 ft) above ground level, which is appropriate for 

wind turbine applications.

6.5 MiniSODAR at Fort Carson

The miniSODAR system deployed at Fort Carson was a series 4000 Wind Explorer unit 

manufactured by Atmospheric Systems Corporation (ASC) and designed to record wind 

speed and direction from 40 to 120 m (130 to 390 ft) above the ground. The Army 

National Guard contracted for the deployment and data analysis of the miniSODAR that 

NREL loaned to Fort Carson. The system was commissioned on 3/19/2008 and was 

operational through 9/25/2008. The period 4/1/2008-9/25/2008 was used for analysis 

purposes.

The SODAR data was analyzed by ACS to discern wind trends at various heights above 

the ground. Their summary data tables and analyses were used in conjunction with the 

collected met tower data to characterize the wind resource at FC#2.

Variable Value

Latitude N 38° 26' 0.1"

Longitude W 104° 44' 22.3"

Elevation 1731 m

Start date 1/1/2008

End date 9/30/2009 23:50

Duration 21 months

Length of time step 10 minutes

Calm threshold 3 m/s

Mean temperature 13.1 °C

Mean pressure 82.24 mbar

Mean air density 1.002 kg/m3

Power density at 50m 241 W/m2

Power law exponent 0.159

Surface roughness 0.0693 m

Roughness class 1.7
11

Figure 6. The Wind ExplorerTM miniSODAR unit from Atmospheric Systems Corporation

Photo credit: Robi Robichaud, NREL

The miniSODAR was used to enhance the wind resource assessment campaign by 

providing wind speed measurement data at elevations significantly above the 

measurements of the met tower.

6.6 Site Summary – MiniSODAR

Table 5 summarizes the dataset properties, environmental conditions, and wind power 

and wind shear coefficients for the met tower site.

Table 5. Site Summary of the MiniSODAR Site at Fort Carson for 4/1/2008-9/25/2008

Variable Value

Latitude N 38° 25' 59.12"

Longitude W 104° 44' 26.12"

Elevation 1727 m

Start date 4/1/2008 

End date 9/25/2008 

Duration 5.8 months

Length of time step 10 minutes

Calm threshold 3 m/s

Mean temperature 3.78 °C

Mean pressure 82.28 kPa

Mean air density 1.035 kg/m3

Power density at 50m 243 W/m2

Power law exponent 0.269

Surface roughness 1.53 m

Roughness class 4.26
12

7 Data Recovery and Validation

The data logger sampled the sensors every 2 seconds and recorded the 10-minute average 

value for each sensor. The collected data was downloaded manually by Vince Guthrie on 

a periodic basis and emailed to NREL. Table 6 shows the dataset recovery rates and other 

major data collection categories for the met tower sensors.

Table 6. Dataset Recovery Rates for FC#2 for 1/1/2008-9/30/2009

Note: Max = maximum wind recorded; Min = minimum wind recorded; Std. Dev = standard deviation

Table 7 displays the data recovery rates for the miniSODAR unit during a shorter, but 

overlapping timeframe. The raw data recovery rate for the miniSODAR, at 41.79%, was 

considerably lower than the data recovery rates for the met tower.

Table 7. Wind Speed Recovery Rates for the MiniSODAR for 3/1/2008-9/25/2008

Note: Max = maximum wind recorded; Min = minimum wind recorded; Std. Dev = standard deviation

7.1 Data Analysis

The wind data from FC#2 was validated by NREL and used for all of the met tower 

analyses. The wind data from the miniSODAR was validated by ASC and used for the 

SODAR data analysis. For the purposes of comparing the wind resources from these two 

assessment tools at Fort Carson, the analysis in this section will examine the time period 

where the met tower has concurrent data with the miniSODAR, March 1, 2008, to 

September 25, 2008.

Label Units Height

Possible 

Records

Valid 

Records

Recovery 

Rate (%) Mean Min Max Std. Dev

Speed 50 m A 315° m/s 48.6 m 94,175 82,518 87.62 5.9 0.4 23.5 3.5

Speed 50 m B 225° m/s 48.6 m 94,175 84,107 89.31 5.9 0.4 24.2 3.6

Speed 40 m 270° m/s 40.8 m 94,175 93,163 98.93 5.7 0.4 23.7 3.4

Speed 30 m 270° m/s 30.1 m 94,175 93,564 99.35 5.3 0.4 23.2 3.2

Direction 48 m ° 48 m 94,175 93,969 99.78 261.3 0.9 359.9 103.8

Direction 30 m ° 29.5 m 94,175 93,969 99.78 275.5 0.9 359.9 103.3

Temperature °C N/A 94,175 93,470 99.25 13.1 -21 38.9 10.3

Label Units Height

Possible 

Records

Valid 

Records

Recovery 

Rate (%) Mean Min Max Std. Dev

Wind speed 34m m/s 34 m 25,488 10,651 41.79 5.9 3.0 21.9 2.4

Wind speed 44m m/s 44 m 25,488 10,651 41.79 6.6 3.0 22.2 2.6

Wind speed 54m m/s 54 m 25,488 10,651 41.79 7.0 3.0 22.0 2.7

Wind speed 64m m/s 64 m 25,488 10,651 41.79 7.3 3.0 22.5 2.9

Wind speed 74m m/s 74 m 25,488 10,651 41.79 7.6 3.0 23.3 3.0

Wind speed 84m m/s 84 m 25,488 10,651 41.79 7.8 3.0 23.4 3.1

Wind speed 94m m/s 94 m 25,488 10,651 41.79 8.0 3.0 23.5 3.2

Wind speed 104m m/s 104 m 25,488 10,651 41.79 8.2 3.0 23.5 3.3

Wind speed 114m m/s 114 m 25,488 10,651 41.79 8.3 3.0 24.0 3.4

Wind speed 124m m/s 124 m 25,488 10,651 41.79 8.5 3.0 24.7 3.4
13

Wind speed data were collected at 50, 40, and 30 m (164, 131, and 98 ft) with a 

redundant wind speed sensor at 50 m (196 ft). The wind speed sensors were mounted on

1.2 m (3.9 ft) boom arms facing southwest (315°) or west by northwest (225°) to 

minimize met tower shading effects.

Two anemometers at FC#2, 50-m A 315° wind speed and 50-m B 225° wind speed, were 

periodically affected by met tower shading and by turbulence caused by wind coming 

over the top of the met tower. These data points have been flagged and removed from the 

datasets.

At times, the miniSODAR wind speed data show significant discrepancies with the met 

tower data as seen in Figure 7. Based on the wind speed variations and the low data 

recovery rate with the miniSODAR, the miniSODAR data was used to establish the 

vertical wind shear factor for FC#2 that was applied in creating a long-term data set. The 

wind speed data from the anemometers on FC#2 were used to determine wind speed, 

direction, turbulence, and other key statistics.

Figure 7. Wind speed variations between miniSODAR and FC#2 met tower

The analyses organized, averaged and sorted the data utilizing a variety of methods to 

help illustrate important trends and other statistical data relevant to the characterization of 

the wind resource.
14

8 Wind Resource Assessment Summary

8.1 Wind Resource Characterization

Uneven heating of the earth’s surface creates wind energy. Variation in heating and 

factors such as surface orientation or slope (azimuth), absorptivity (albedo), and 

atmospheric transmissivity also affect wind energy. In addition, wind energy can be 

accelerated, decelerated, or made turbulent by factors such as terrain, bodies of water, 

buildings, and vegetative cover. 

Wind is air with kinetic energy that can be converted into usable energy by means of a 

wind turbine. Wind is a distributed resource that can generate electricity cost effectively 

and competitively in many regions.

8.2 Measuring Power in the Wind

Wind speeds vary by season, time of day, and according to weather events. 

The wind speed determines the amount of power it contains. The power available is given 

by:

P = 1⁄2 * A * ρ * V3

P = power of the wind [W]

A = windswept area of the rotor (blades) [m2] = πD2/4 = πr

2

ρ = density of the air [kg/m3

] (at sea level at 15°C)

V = velocity of the wind [m/s]

As shown, wind power is proportional to velocity cubed (V3

). This is important to 

understand because as wind velocity is doubled, the available power is increased by a 

factor of eight (23 = 8). Consequently, what may appear to be a small increase in average 

speed yields a significant increase in available energy. Typically, developers looking to 

capture energy from higher velocity winds select taller wind turbine towers. Accordingly, 

the wind industry has been steadily moving toward taller towers, and the industry norm 

has increased from 30 m to 80 m over the last 15 to 20 years. 

8.3 Fort Carson Wind Speed Variability

The wind varies widely throughout the day and night and by season as illustrated in the 

graph of two months of data collected at 50 m (164 ft) at FC#2. As shown Figure 8, there 

are a number of 10-minute periods that have wind speeds less than 3 m/s (~7 mph). There 

are also many periods that have wind speeds in excess of 10 m/s (~22 mph). This sort of 

variability is typical, but further statistical analysis will illuminate important trends and 

patterns.
15

Figure 8. Wind data at 50-m at FC#2 

8.4 Fort Carson Monthly Box Plot Statistics

A box plot indicating the monthly maximum wind speed, the daily high, the monthly 

mean, the daily low, and monthly minimum wind speed measured at FC#2 are shown in 

Figure 9. This graphic illustrates the seasonal trends of the local wind resource as well as 

the monthly variability. Every month, FC#2 experiences periods of very high wind 

speeds. FC#2 experiences wind speeds over 20 m/s (~45 mph) in 9 out of 12 month.

Figure 9. Boxplot of FC#2 for1/1/2008-8/30/2009
16

8.5 Fort Carson Seasonal Wind Profile

Figure 10 shows the wind speeds at each anemometer height as they are plotted against 

time to depict the seasonal trends. As can be seen in the graph, the late fall through early 

spring seasons were the windiest periods. Wind speeds typically increase with increased 

height above the ground. The collected data follows that pattern. The anemometers at 

180° at both 40 m and 58 m showed significant effects of tower shading and were not 

included in the subsequent analyses.

Figure 10. Seasonal wind speed profile at FC#2 for 1/1/2008-8/30/3009

8.6 Fort Carson Diurnal Wind Profile

Figure 11 illustrates how the wind speed varies during the course of the day. The wind 

speeds increase during late morning and continue increasing until mid-afternoon. Early 

morning hours are generally the period of lower wind speeds.

Figure 11. Diurnal profile of the wind speed at FC#2 for 1/1/2008-8/30/3009
17

Figure 12 shows the diurnal trends for each month of the year. As seen at FC#2, May 

through August has wind typically peaking in mid-afternoon with very calm conditions in 

the early morning hours. During the day, the wind speeds at 30, 40, and 50 m (98, 131,

and 164 ft) are fairly similar, indicating low vertical wind shear during these periods.

January and December are windy, relative to the other months, both day and night.

Figure 12. Monthly diurnal profile of the wind speed at FC#2 for 1/1/2008-8/30/3009

8.7 Fort Carson Wind Direction Data

Wind direction informs decisions about turbine siting to maximize exposure to the best 

winds and minimize exposure to turbulent winds. In this analysis of direction, the 

compass was divided into 12 sectors, each 30° in size.

8.7.1 Fort Carson Wind Frequency

The graphic on the left in Figure 13 shows the frequency the wind blows from each 

direction at FC#2. As shown, the wind most frequently comes from the southwest-bywest with secondary wind directions coming from the southeast and the north. It is calm 

(i.e., wind speed less than 3 m/s (6.7 mph)) about 20% of the time. 

The graphic on the right in Figure 13 provides the mean wind speed from each direction 

that the wind blows, regardless of how often it comes from that direction. When the wind 

blows, the winds from the north are of nearly as strong as those from southwest-west, 

whereas the winds from the southeast are considerably milder.
18

Figure 13. Wind Frequency Rose on left and Mean of Speed Rose on right at FC#2 for 

1/1/2008-8/30/3009

The Total Wind Energy Rose in Figure 14 summarizes the direction the most energetic 

winds come from. The most energetic winds are those from the southwest through west 

arc. The secondary wind direction is from the north. The winds from the west-southwest 

(225° to 284°) account for 57% of the wind energy, while those from the north (345° to

14°) account for 16% of the wind energy. 

In siting wind turbines at FC#2, there is relatively clear fetch to the west of each potential 

wind turbine, though there is the higher ridge to the west and the small canyon between 

the two. This canyon may be a source of turbulence. To the north, the fetch is generally 

clear with pinion and other relatively short trees and bushes and with the ground 

relatively flat.
19

Figure 14. Total wind energy rose at FC#2 for 1/1/2008-8/30/3009

The monthly total wind energy roses at FC#2 in Figure 15 point to both the southwestthrough-west arc as predominant in the fall/winter (November through March) as a 

source of wind energy. The north sector has its most energetic winds, though with lower 

power, during the spring/summer/early fall (April through October).

There were two anemometers at 48.6 m (159 ft), one at 225° and one at 315°. Given the 

predominant wind direction depicted in Figure 14, there is potential for the tower to 

influence the anemometer readings at 225° (often referred to as tower shading). The 

relatively consistent lower wind speed measurements with the anemometer at 225° vs. the 

anemometer at 315° may be the result of turbulence caused by the tower itself. 

Consequently, for the duration of the report, the anemometer at 315° will be used. In the 

event that the anemometer measurements at 315° are deemed unreliable due to occasional 

tower shading because of the wind direction, the readings from the anemometer at 225° 

will be used.
20

Figure 15. Total wind energy rose by month at FC#2 for 1/1/2008-8/30/3009

8.8 Fort Carson Wind Frequency (Probability) Distribution

Figure 16 illustrates a Weibull distribution of the frequency (percent of time) that the 

wind at 58 m is at a given speed. There are two commonly used factors to describe the 

distribution function, the Weibull c and Weibull k factors. The Weibull c is the scale 

factor for the distribution related to the annual mean wind speed. The Weibull k value is a 

unitless measure indicating the shape of the distribution of the wind speeds about the 

mean with values ranging from 1.0 to 3.0. 

In Figure 16, the best-fit Weibull distribution parameters for the measured data at FC#2

are k = 1.78 and c = 6.71 m/s. The distribution shows that the most frequent winds, or 

mode of the dataset, are between 4 to 5-m/s as measured by the wind sensor at 58 m. 
21

Figure 16. Wind frequency distribution at FC#2 for 1/1/2008-8/30/3009

8.9 Vertical Wind Shear Factor (VWSF)

VWSF is the change in wind speed with increasing height above ground. Typically, wind 

speeds increase with height. This variation of wind speed with elevation is called the 

vertical profile of the wind speed, or VWSF. In wind turbine engineering, the 

determination of VWSF is an important design parameter since: (1) it directly determines 

the productivity of a wind turbine on a tower of certain height, and (2) it can represent the 

level of cyclic mechanical loading on the wind turbine system.

Analysts typically use one of two mathematical relations to characterize the measured 

wind shear profile: 

• Power Law profile

• Logarithmic Law profile.

8.9.1 Power Law

The Power Law equation is:

0 5 10 15 20 25

0

4

8

12

16

Frequency (%)

Probability Distribution Function

Speed 50 m A 315° (m/s)

Actual data Best-fit Weibull distribution (k=1.78, c=6.71 m/s)

Z u

Zref

V = Vref 
22

V = wind speed at height of interest (e.g., hub height)

Vref = wind speed measured at height Zref

Z = height of interest (e.g., hub height)

Zref = height of measured data

α = wind shear exponent

The wind shear exponent, α, or VWSF, defines how the wind speed changes with height. 

When the actual wind shear value is not known, a typical value used for estimation is 

0.14 (1/7 Power Law). When wind speed data are available at multiple heights, the wind 

shear factor can be calculated using the Power Law equation. 

The VWSFs from several heights with known wind speeds are used to estimate both the 

VWSF and wind speed at other heights of interest (e.g., turbine hub height). Depending 

on the type of terrain and surface roughness features, the VWSF may vary from 0.0 to 

0.4. 

8.9.2 Logarithmic Law

The Logarithmic Law uses a parameter known as the surface roughness length (measured 

in meters) in predicting the wind shear profile. Surface roughness length describes the 

conditions of the ground and its expected impact on wind flows and ranges, as shown in

Table 8.

Table 8. Surface Roughness Lengths and Descriptions3

Terrain Description Surface Roughness Length, z0 (m)

Very smooth, ice and mud 0.00001

Calm open sea 0.0002

Blown sea 0.0005

Snow surface 0.003

Lawn grass 0.008

Rough pasture 0.01

Fallow field 0.03

Crops 0.05

Few trees 0.1

Many trees, hedges, few buildings 0.25

Forest and woodlands 0.5

Suburbs 1.5

Centers of cities with tall buildings 3.0

 3 Ray, M.L.; Rogers, A.L.; McGowan, J.G.; (2002). Analysis of Wind Shear Models and Trends in Different 

Terrains. http://www.ceere.org/rerl/publications/published/2006/AWEA%202006%20Wind%20Shear.pdf. 

Accessed July 2011.
23

The Best Fit Power Law Exponent was calculated with the data collected at FC#2. Table 

8 shows the calculated wind shear values in the “Best-Fit Power Law Exponent” column. 

The wind shear exponent is high in the two sectors from 75° to 134° and from 255° to 

315°. Combined, these two sectors represent 46.2% of the data, so the impact is 

considerable.

Table 9 shows the application of surface roughness lengths. The surface roughness 

parameter is “solved for” from the existing wind speed data at various heights. The 

resultant characterization may not always match the actual surface conditions, but it 

serves as a descriptor of the vertical wind shear profile. The surface roughness lengths 

have been calculated for FC#2 and are shown in the “Surface Roughness” column at the 

far right in Table 9. There are two primary directions where surface roughness appears to 

have an impact (high values): from 75° to 134° and from 255° to 315°. There is rough, 

rugged terrain both east and west of FC#2, so this characterization appears accurate.

Table 9. Power Law Exponent and Surface Roughness Length at FC#2 for 1/1/2008-

8/30/3009

Figure 17 is a graph comparing the measured data to the Power Law approach to vertical 

wind shear versus the Logarithmic Law approach. Both methods track closely with the 

measured data at FC#2 and each other. The difference between these approaches, even 

extrapolated to 80 m (262 ft) is negligible. The Power Law was used for subsequent 

energy calculations as it is tied more closely to statistical calculations rather than surface 

roughness approximations.

Speed 50 

m A 315°

Speed 40 

m 270°

Speed 30 

m 270°

 ° # m/s m/s m/s unitless m

15° - 45° 3,867 5.1 5.3 5.1 0.019 0

45° - 75° 3,686 4.3 4.3 4.1 0.101 0.001716

75° - 105° 7,967 4.5 4.0 3.9 0.295 1.366647

105° - 135° 10396 4.6 4.4 4.1 0.220 0.412073

135° - 165° 5187 4.0 4.0 3.8 0.149 0.044264

165° - 195° 4013 4.0 4.0 3.8 0.126 0.012998

195° - 225° 5,992 5.2 5.2 4.9 0.125 0.012433

225° - 255° 12,579 7.4 7.3 6.9 0.145 0.037992

255° - 285° 13,360 7.8 7.5 7.0 0.240 0.588244

285° - 315° 1,020 5.9 5.7 5.4 0.200 0.257560

315° - 345° 2,833 7.0 6.9 6.6 0.149 0.044522

Overall Annual Figure 6.605 6.383 6.245 0.121 0.009460

Direction Sector Time 

Steps Mean Wind Speed Best-Fit Power Law 

Exponent

Surface 

Roughness
24

Figure 17. Vertical wind shear profile at FC#2 for 1/1/2008-8/30/3009

The daily wind shear at Fort Carson as it varies by month is shown in Figure 18 below. 

The months with the higher wind shears generally have higher wind speeds, especially 

during nighttime hours.

Figure 18. Daily wind shear profile by month at FC#2 for 1/1/2008-8/30/3009
25

8.10 Turbulence Intensity (TI)

TI is the standard deviation of the wind speed within a time-step, divided by the mean 

wind speed over that same time-step. TI is a measure of the gustiness of the wind. High 

turbulence is associated with increased wind turbine system wear and increased operation 

and maintenance (O&M) costs. At lower wind speeds, the calculated turbulence intensity 

is higher, as seen in Figure 19. However, the higher turbulence at low wind speeds is not 

a concern because of the low power available at those low wind speeds. Turbulence at 

higher winds speeds is of greater interest and concern to wind turbine manufacturers.

Turbulence analysis determines the suitable types of turbine designs for a wind energy 

project. Because wind turbines must withstand a variety of wind conditions, design 

standards have been developed by the International Electrotechnical Commission (IEC). 

The IEC 61400-1:20054 has components for wind speed and for turbulence, and can be 

seen in Table 10. The standard designates four different classes of wind turbines, I 

through IV, which are designed for varying degrees of wind resource, with Class I being 

very high mean wind speed and Class IV being low mean wind speed. 

The standard also designates a wind turbulence classification, A through C, that describes 

the amount of turbulence a turbine must be designed to withstand, with A being the 

highest turbulence and C being the lowest. In recent years, wind turbine manufacturers 

have introduced designs for sites with lower wind speeds and low turbulence known as 

low wind speed turbines. These turbines have larger rotors, for a given generator size,

and are thus capable of producing significantly more annual energy at a low wind speed 

site than the Class I or II or Class A or B turbines of similar generator size.

There are several types of TI of interest. The representative TI, for a set of 10-minute 

time-steps, is equal to the 90th percentile of the TI values. Assuming a normal distribution 

of these values, it represents the mean value plus 1.28 standard deviations. The mean TI

is the mean value of all of the TI data at a particular wind speed.

Table 10 displays design wind speed and mean TI ratings for the different wind turbine 

design classes. 

 4 International Electrotechnical Commission (IEC). “International Standard IEC 61400-1 Third Edition.”

Geneva, Switzerland: IEC, 2005.
26

Table 10. IEC Wind Turbine Classes, Ratings, and Characteristics of Turbulence Intensity5

Figure 19 shows the representative and mean TI as a function of wind speed at 50-m 

(164-ft) at FC#2. 

Figure 19. Representative and mean turbulence intensities at FC#2 for 1/1/2008-8/30/3009

Figure 20 shows the IEC turbulence ratings relative to the representative TI. A point of 

primary interest is the mean TI at 15 m/s, which is 0.13 (13%). This indicates low 

turbulence and that a Class B wind turbine is possible. 

 5 IEC/TC88, 61400-1 ed. 3, Wind turbines - Part 1: Design Requirements, International Electrotechnical 

Commission (IEC), 2005.

WTG* Class IEC I 

High 

Wind

IEC II 

Medium 

Wind

IEC III 

Low 

Wind

IEC IV 

Low 

Wind

Vav e average wind speed at hub-height (m/s) 10 8.5 7.5 6

V50 extreme 50-year gust (m/s) 70 59.5 52.5 42

Mean turbulence intensity at 15 m/s - turbulence Class A

Mean turbulenceiIntensity at 15 m/s - turbulence Class B

Mean turbulence intensity at 15 m/s - turbulence Class C

* Wind Turbine Generator

14% - 16%

12% - 14%

0 - 12%
27

Figure 20. Turbulence intensity at FC#2 for 1/1/2008-8/30/3009

Quantity Value

Records in 15 m/s bin 787

Mean TI at 15 m/s 0.13

Representative TI at 15 m/s 0.17

IEC3 turbulence category B
28

9 Long-Term Data Adjustment

It is important to determine if the data monitoring period is representative of the longterm wind resource at the site. Different methodologies are used to estimate the long-term 

wind resource at the site where the short-term met tower study was conducted. A 

standard industry approach with a number of variations is measure-correlate-predict 

(MCP), where a short-term dataset is correlated to a long-term wind dataset from a 

nearby monitoring station (reference site). The correlation relationship is then applied to 

the measured data at the site of interest to project the expected long-term wind resource. 

An industry-standard MCP method, the ratio of the mean of monthly means, was used in 

this analysis.

The purpose of this estimate is to provide a normalized, realistic estimate of the longterm wind resource and the resultant wind turbine energy production. Though wind 

turbine production at any site will vary year-to-year, the goal is to have the long-term 

energy production estimate minimize the uncertainty of the relatively short period of 

collected data. 

9.1 Long-Term Datasets

The Federal Aviation Administration (FAA) and National Weather Service (NWS) own 

and operate automated surface observing systems (ASOS) for the purposes of aviation 

and weather observation. These datasets generally represent the most consistent weather 

observation data as the FAA and NWS are tasked with building a historical long-term 

surface weather observation record. Other long-term weather observation datasets include 

military airfield observations, ocean buoy observations, and other forms of surface 

observations.

The data from the following stations were accessed and analyzed for suitable, long-term 

correlation. For each of the stations, the r2 correlation factors were low and were not used 

for MCP. Generally speaking, r2 values of 0.75 or greater are required to have confidence 

that the two sites are comparable and wind trends observed for the long-term site apply to 

the short-term site of interest. 

Table 11. Nearby ASOS Met Towers

9.2 Regional Energy Deployment System (ReEDS) Data Set

NREL has purchased a wind data set from AWS Truepower6 for a range of wind analysis 

purposes. This data represents a mix of meso-scale modeled data corrected and verified 

 6 AWS Truepower, http://www.awstruepower.com/. Accessed 1/12/2012

Station ID Station Name Mean Annual Distance 

Wind Speed to FC#2 1 hour 8 hours 1 day

 # m/s (mph) km (mi) r

2 r2 r2

724680 FC BUTTS 3.7 (8.3) 27 (~17) 0.243 0.330 0.383

724640 Pueblo 3.6 (8.1) 21 (~13) 0.312 0.467 0.579

724660 Colorado Springs 4.3 (9.6) 43 (~27) 0.047 0.139 0.325

Correlation Timeframe
29

with available met tower measurements. The data sets were created for specific regions 

and have 20-km (12.4-mi) resolution and vary in height above the ground. The data sets 

themselves are proprietary (AWS) and confidential (for NREL). This data was deemed 

more suitable for long-term correlation with FC#2 than the ASOS met tower data due to 

the low r2 values during MCP correlation. The data trends/factors, based on elevation, 

terrain, and wind resource, were applied to a “typical meteorological year7” (TMY) data 

set at the 50-m (164-ft) level as this matches the height of the data collected at FC#2.

The blue line in Figure 21 shows the annual variation in wind speed over a 14-year 

period. The red line represents the long-term mean wind speed from the data set. The 

green shaded box represents the period of interest (2008) that wind speed and direction 

were measured at FC#2. The period of collection at FC#2 represents a higher than 

average wind period and the FC#2 data will need to be adjusted downward to reflect that.

Figure 21. Long term mean wind speed using the ReEDS data for FC#2

For the adjustment of the FC#2 data, only the 2008 data was used. There were nine

months of 2009 data with wide swings in wind speed that were not well suited for a 

partial-year analysis. The ratio of the mean wind speed of the given year (e.g., 2008) to 

the long-term mean wind speed can be seen in Table 12. The wind speed values for the 

data set are 3.76% higher than for the average wind year. Consequently, the collected 

data at FC#2 was adjusted downward 3.76%. 

Table 12. Ratio of the Mean Wind Speed by Year to Long Term Mean at Site #101095

After the adjustment of the measured data at FC#2 for 2008, the ratios in Table 9 were 

applied forward and backward from 2008 to obtain a 14-year data set representative of 

the long term wind speed at the site. 

 7 National Solar Radiation Data base: 1991-2005 Update, Typical Meteorological Year 3.

http://rredc.nrel.gov/solar/old_data/nsrdb/1961-1990/tmy2/ Accessed 5/24/2012.

5.4

5.5

5.6

5.7

5.8

5.9

6.0

6.1

6.2

6.3

Wind Speed (m/s)

Long Term Vs. Short Term Data Trends Near FC#2

LT 50m

Long Term 50m Mean

Year 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Ratio to Mean 0.927 0.951 1.026 1.016 0.969 1.032 1.011 0.971 0.985 1.015 1.006 1.038 1.044 1.010
30

9.3 Vertical Wind Shear Adjustment

To project the annual energy performance of wind turbines with hub heights in the 70 to 

100-m (230-328-ft) range, vertical extrapolations were completed on the existing data 

from FC#2. The extrapolations were done beginning at 50 m (164 ft), increasing by 10-m 

(33-ft) increments to 110 m (361 ft). The miniSODAR measured data from 30 to 120 m 

(98 to 394 ft) above the ground. The ReEDS data set includes wind speed at 50 m, 80 m, 

110 m, and 140 m (164 ft, 262 ft, 360 ft and 459 ft). All the wind speed data was 

compared at the 50 m, 80 m, and the 110 m level with the FC#2 serving as the base since 

its measurements were in between the ReEDS (lower than FC#2) and the miniSODAR 

(higher than FC#2). The results can be seen in Table 13.

Table 93. Comparison of Wind Speeds at Common Heights from Three Data Sources

The data sets are in very close agreement at 80 m (262 ft), though the vertical wind shear 

profiles for each data set vary slightly resulting in variation in wind speeds both below 

and above 80 m (262 ft). The met tower data, conservatively representing actual on-site 

data at multiple heights and its calculated vertical wind shear, based on anemometer 

readings at 30 and 40 m (98 and 131 ft), were deemed suitable for use for the energy 

production analysis that follows.

Data Set 50-m 80-m 110-m 50-m 80-m 110-m

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

ReEDS near FC#2 5.9 6.3 6.5 1.9% 1.6% -1.1%

FC#2 5.8 6.2 6.6 100% 100% 100%

MiniSODAR 5.7 6.3 6.9 -1.8% 1.6% 4.3%
31

10 Energy Production Estimates

This section discusses the potential energy generation from wind turbines at Fort Carson. 

Several layout scenarios and turbine sizes and types were evaluated. Per the preliminary 

screening results with the Federal Aviation Administration (FAA), Fort Carson must 

submit formal applications for the location of specific turbines at predetermined heights 

above ground (including rotor) in order to determine what size wind turbine will 

ultimately be allowed. On-site military operations are a primary concern in this part of 

the base. The results of the preliminary screening are located in Appendix C. 

10.1 Site Layout

There may be transmission/distribution line limitations or mission/operations factors that 

impact the size of the wind project that is ultimately approved and installed at Fort 

Carson. Analysis was conducted for a larger build-out by assuming the siting of utilityscale turbines at every viable site on this ridge. A rough sketch of each potential wind 

turbine footprint is in Figure 22. A complete layout of scenarios with several suitable 

turbines is recommended as the number of 1.6-MW turbines that fit on this ridge is likely 

to be somewhat larger than the number of 3.0-MW turbines that will fit.

Figure 22. Potential wind turbine layout in southern half of southeast corner of Fort 

Carson.

Image Credit: Google Earth (edited by Robi Robichaud)
32

10.2 Wind Turbines Modeled

A broad range of utility-scale wind turbine models were selected to represent potential 

project scenarios at Fort Carson. These turbines were selected based upon IEC turbine 

type as well as general availability and access to the power curves. These turbines 

represent low-wind and moderate-wind classifications. The range of turbines is intended 

to showcase the available turbines with large nameplate capacities (1.6 MW or greater) as 

well as the new generation of low wind-speed machines, which couple an enlarged rotor 

with a standard generator. All power curves were for sea-level air density at 1.225 kg/m3

. 

The modeling accounts for the elevation increase and air density decrease at 1,731 m 

above sea level (5,679 ft). The turbine models are shown in Table 14. Many companies 

are continuing to increase their rotor size and turbine output so there may be even more 

economical wind turbine available in the not-too-distant future. The turbines modeled 

here do not reflect any endorsement on the part of NREL for any particular wind turbine. 

Table 104 Wind Turbine Specifications Used in Modeling

Other factors to consider in the turbine selection process include cost, availability, 

constructability, transportability, warranty, the types of other proximal wind turbines,

O&M, etc.

10.3 Energy Production Loss Factors

All energy projects will incur some type of energy loss due to real-world conditions 

differing from the idealized case. The resulting decrease in efficiency is accounted for 

with a series of estimated and calculated loss factors. The annual wind turbine energy 

production estimates were calculated assuming 17.7% losses, primarily due to wind 

turbine downtime, soiling/icing, electrical and other losses. A more detailed explanation 

of these production loss factors can be found in Appendix E.

10.4 Projected Wind Project Performance

Performance estimates were calculated for several suitable low wind-speed, utility-scale 

turbines using the Windographer software. Table 15 summarizes the annual wind turbine 

energy production estimates. The column at the far right, labeled “% of Base Energy”

indicates how much of Fort Carson’s load the potential wind projects will meet per year. 

As shown, these wind projects could meet 16-27% of Fort Carson’s annual electric load 

which would make wind a solid contributor in the Net Zero Energy Initiative. 

Turbine Manufacturer, 

Size, and Model

Nameplate 

Capacity

Turbine 

Class

Hub 

Height

Rotor 

Span

Max 

Height

Max 

Height

FC#2 Site 

Scenario

Wind Plant 

Capacity

MW # m m m ft # turbines MW

GE 1.6 XLE 1.6 III 80 100 130 427 7 11.2

Suzlon S97 2.1 III A 80 97 128.5 422 7 14.7

Siemens SWT-2.3 108 2.3 III 80 108 134 440 7 16.1

Siemens SWT-2.3 113 2.3 III 99.5 113 156 512 7 16.1

Nordex N117 2.4 II-III a 91 117 149.5 490 7 16.8

Vestas V112 - 3.0 MW 3.0 II a 84 112 140 459 7 21.0
33

Table 115 Summary Wind Project Energy Performance of Sample Wind Turbines at Fort 

Carson

Turbine Manufacturer 

& Model

Rated 

Power

Mean 

Net 

Power 

Ot t

Mean Net 

Annual Energy 

/Turbine/Yr

Net 

Capacity 

Factor

FC#2 

Site 

Wind 

Plant 

Capacity

Wind Plant 

Annual 

Output

% of Base 

Energy

Turbine MW kW kWh/yr % # Turb. MW MWh/yr %

GE 1.6 XLE 1.6 415 3,634,101 25.9 7 11.2 25,439 15.7%

Suzlon S97 2.1 475 4,162,921 22.6 7 14.7 29,140 18.0%

Siemens SWT-2.3 108 2.3 572 5,014,293 24.9 7 16.1 35,100 21.6%

Siemens SWT-2.3 113 2.3 691 6,049,308 30.0 7 16.1 42,345 26.1%

Nordex N117 2.4 647 5,665,505 26.9 7 16.8 39,659 24.4%

Vestas V112 - 3.0 MW 3.0 677 5,933,315 22.0 7 21.0 41,533 25.6%
34

11 Economic Analysis

There are several financial paths that may be open to Fort Carson. In this section, primary 

options are investigated and their similarities and differences explained beginning with 

the potential impact of various incentives.

11.1 Incentives

Incentives can take many forms and each incentive may appeal to different parties to a 

wind turbine project depending upon their role in the project, their available resources, 

and the impact of the incentive on their resources. Incentives, such as the Production Tax 

Credit (PTC), have been strong drivers for equity partners in wind farms. Net metering 

has been an incentive that appeals to the local owner of a smaller, distributed generationtype of wind project as there are size limits well below commercial wind turbine range. 

11.1.1 Production Tax Credit (PTC)

The PTC8 has been a significant driver in the wind energy boom of the last seven years as 

it has been in place continuously since 2005. The PTC enables eligible taxpayers to 

receive a tax credit equal to $0.022/kWh for every kWh produced during the first ten 

years of operation of a wind (and other renewable energy technologies) project and sold 

to a third party. Depending on the wind resource and the competing cost of energy 

(COE), the PTC value may represent 15 to 40% of the cost of energy produced. Due to 

many factors, the net effect of the PTC is somewhat less than $0.022/kWh. In other 

words, if the COE for a wind turbine project was $0.096/kWh without the PTC incentive, 

utilizing the PTC does not typically result in the new COE being $0.074/kWh. It may be 

more likely in the range of $0.078 to $0.085/kWh depending on a range of other project 

cost factors.

The PTC is not available in the case where Fort Carson purchases the wind turbine 

outright with cash through the Energy Conservation Investment Program (ECIP) because 

neither Fort Carson nor the Army are taxpaying entities. In the case of energy savings 

performance contract (ESPC) or power purchase agreement (PPA) scenarios, a third party 

would take advantage of the PTC to enhance the overall project economics. 

The PTC is scheduled to expire on Dec 31, 2012. It is not certain if Congress will extend 

the PTC for one or more years. It has been extended retroactively several times in the 

past but the economics of wind without incentives has improved considerably since the 

early 2000s. At this point in time (8/2012), indications from Senate Finance Committee 

are that the PTC will be extended for one year.9

 8 Renewable Energy Production Tax Credit (PTC), FEDERAL Incentives/Policies for Renewables & 

Efficiency, DESIRE Database of State Incentives for Renewables & Efficiency. 

http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=US13F&re=1&ee=1, accessed January 

2012 and Renewable Electricity, Refined Coal, and Indian Coal Production Credit, IRS Form 8835 2009, 

http://www.irs.gov/pub/irs-pdf/f8835.pdf, accessed January 2012. 9 Colman, Z., E2 Wire, THE HILL’S Energy & Environment Blog, 08/07/2012. 

http://thehill.com/blogs/e2-wire/e2-wire/242559-reid-very-confident-wind-credit-will-clear-senate
35

11.1.2 Targeted Incentives

There are several other types of incentives available for renewable energy systems in 

Colorado. Unfortunately, they target sectors such as residential, commercial, industrial, 

state, or community renewable energy projects, not the federal government. Many of 

these incentives have size restrictions limiting systems to 10, 25, or 100 kW. As such, 

they will not help Fort Carson in regards to a multi-megawatt wind project.

One utility incentive that may have implications that could be of value to Fort Carson is 

an aspect of the Renewable Portfolio Standard (RPS) that Colorado instituted in 2004 and 

adopted modifications in 2007.

Municipal utilities, such as Colorado Springs Utilities, must have a certain percentage of 

their retail sales come from either wholesale distributed generation or retail distributed 

generation, regardless of technology type, according to the following schedule10:

• 1% of its retail electricity sales in Colorado for the years 2008-2010;

• 3% of its retail electricity sales in Colorado for the years 2011-2014;

• 6% of its retail electricity sales in Colorado for the years 2015-2019; and

• 10% of its retail electricity sales in Colorado for the year 2020 and each 

following year.

There are credit multipliers for four types of projects that apply to the utilities as an 

incentive to work with entities to accomplish certain renewable energy goals. One project 

can only receive one multiplier and they cannot be combined. They include:

• Each kilowatt-hour (kWh) of eligible electricity generated in state, other than 

retail distributed generation, can receive 125% credit for RPS-compliance 

purposes.

• Electricity generated at a “community-based project,” a project not greater 

than 30 megawatts (MW) in capacity that is located in Colorado and owned 

by individual residents of a community or by an organization or cooperative 

that is controlled by individual residents, or by a local government entity or 

tribal council, can receive 150% credit for RPS-compliance purposes.

• Solar electricity located in the territory of a cooperative or municipal utility 

and generated by a facility that begins operation before July 1, 2015, can 

receive 300% credit for RPS-compliance purposes. (Solar electricity 

generated by a facility that begins operation on or after July 1, 2015, receives 

100% credit.)

• Projects up to 30 MW that are interconnected to electrical transmission or 

distribution lines owned by a cooperative or municipal utility, which are 

 10 Colorado Incentives/Policies for Renewables & Efficiency, Renewable Energy Standard, DESIRE 

Database of State Incentives for Renewables & Efficiency. 

http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=CO24R&re=1&ee=1. Accessed Feb 

2012.
36

installed prior to December 31, 2014 can receive 200% credit for RPScompliance purposes. With the exception of investor-owned utilities using this 

multiplier, it is only available for the first 100 MW of projects statewide.

It appears that either the first (with no time limit) or the fourth (must be installed by Dec 

31, 2014 and is available only for the first 100 MW statewide) might serve as an 

incentive for Colorado Spring Utilities to support the development of a wind project at 

Fort Carson in some way and it merits further exploration. The RPS may be a driving 

force for Colorado Springs Utilities to want/need to develop a utility energy services 

contract (UESC) for wind and other energy services with Fort Carson.

11.1.3 Renewable Energy Certificates

Renewable energy projects generate additional value in the form of Renewable Energy 

Certificates (RECs). RECs capture the beneficial renewable energy attributes of the 

project (i.e., electricity produced with no greenhouse gas production). In many renewable 

energy projects, the RECs can provide a small, additional revenue stream to enhance the 

project economics. There are organizations that verify the green attributes for the 

existence of RECs with particular projects and there are markets for buying and selling 

RECs. Some states have programs whereby the value of RECs is considerable and they 

play a vital part in the economics of renewable projects.

Due to the requirements of the Energy Policy Act of 2005 (EPAct 2005), for Fort Carson

to meet the renewable energy requirements of the law, it must retain the RECs associated 

with the production of wind energy in this project. In cases where the market value for 

RECs are high, some federal entities and others have sold the RECs that are associated 

with their on-site renewable energy project and purchased replacement RECs at a much 

reduced cost to gain capital advantage to enhance project economics. Solar RECs are 

often ones that have a high value. If one was worth $0.15/kWh, it would be possible to 

sell it and purchase a cheaper renewable REC for $0.002/kWh (typically from a landfill 

methane-type project) and use the net difference of $0.148/kWh to help finance the 

project with an initial cash infusion to help buy down the cost of the renewable energy 

project. If the project involved tens of millions of kWh per year, the economic advantages 

of this approach become more apparent. 

The value of RECs varies over time. Estimates for national wind RECs in 2011 were in 

the $2 to $8/megawatt-hour (MWh) ($0.002-0.008/kWh) range.11 Realistically, there may 

not be a large enough margin for wind RECs to justify trading them. The more easily 

realized value is keeping them with the project owner. If Fort Carson were not to own the 

wind turbine project, it could consider structuring its PPA or ESPC such that Fort Carson 

would obtain the ownership of RECs to meet EPAct 2005 renewable energy goals.

11.2 Wind Turbine Project Cost Factors

There are many economic factors to consider in a wind turbine project. Factors such as 

the wind turbine cost, balance of system, foundation, interest rates, discount factors, 

interconnection, environmental impacts, etc. all have a role to play in the analyses. Many 

of these factors vary from project to project and there is not an effective predictor of what 

 11 http://apps3.eere.energy.gov/greenpower/markets/certificates.shtml?page=5. Accessed Feb 2012.
37

the costs will be at a given site in the future. It is usually more effective to analyze the 

cost and performance parameters of actual bids that developers submit responding to a

request for proposal (RFP) than to develop a full range of expected cost and performance 

parameters from developers’ speculations. The developers understand they can’t be held 

to speculative estimates and also that it might not be in their best interests to divulge 

competitive pricing information short of an official response to an RFP. Even the best 

intentioned speculative bid will be impacted by dynamic market forces affecting the 

turbine supply chain, raw material costs, regulatory timeframes and cost, etc. such that 

the bid may be unrepresentative of actual expected costs three to six months later.

A reasonable sampling of historical wind farm project data has been collected, analyzed,

and summarized in the annual Wind Technologies Market Report12. Economic cost data 

for modeling purposes was obtained from this report with the focus on comparable wind 

projects in the 5 to 20 MW range, utilizing 1.5 to 3 MW turbines and installed in the 

Mountain West. The average installed cost in this scenario was ~$2,200/kW. 

Gearbox and blade replacement and annual O&M costs were derived from cost ratio 

figures in the series of WindPACT13 studies that NREL completed during the early 

2000s. The figures cited for blade replacement were applied at a 75% factor due to low 

turbulence at Fort Carson. 

Recent utility summary data provided to NREL by Fort Carson indicated an annual 

electric load of 191,804 MWh/yr (excluding the solar phovoltaic system production) with 

an estimated cost of $11.3 million/year resulting in a blended rate of $0.059/kWh for 

electrical energy. These figures were used for the economic modeling. 

Two primary driving factors for economically viable wind turbine projects are wind 

power density (derived from wind speed) and competing COE. A high wind power 

density and high COE ensure solid economics. Most other scenarios require a detailed 

investigation. The mean annual wind speed of 6.2 m/s at 80 m at Fort Carson is a 

moderate wind resource. Fort Carson has a relatively low COE at $0.059/kWh. These 

driving factors suggest a potentially viable wind project, but not one with a large profit 

margin that would enable a large range of financing scenarios.

For analysis purposes, a “typical” 1.6 MW wind turbine designed for low wind speeds 

was selected. The key factor in the economic analysis is how many kWh/year a turbine 

will produce to offset the installation and O&M costs. As project costs vary depending 

upon a number of factors, some of which may change considerably between now and the 

issuance of an RFP, attempting to project the installation and O&M costs for a number of 

turbines fraught with uncertainty.

 12 Wiser, Ryan and Bolinger, Mark - 2010 Wind Technologies Market Report, U.S. Department of Energy, 

Energy Efficiency & Renewable Energy, June 2011. 13 Wind Partnership for Advanced Component Technology, Department of Energy, Office of Energy 

Efficiency and Renewable Energy, National Renewable Energy Laboratory. 

http://www.nrel.gov/wind/windpact.html. Accessed Feb 2012.
38

11.2.1 Financing Scenarios

There are typically several financing approaches available to DoD facilities for energy 

projects. They include:

• Business as usual – continue to purchase electricity from the utility as is 

currently done

• Cash purchase of wind turbines by Fort Carson utilizing ECIP cash grant

• ESPC or UESC funded purchase of wind turbines

• PPA by third party owner/operator of wind turbines.

As stated above, the existing driving factors limit economic financing options. To provide 

Fort Carson with effective decision-making information, the economic analyses focused 

on three project scenarios:

• Business as usual – no wind turbines

• Seven 1.6 MW Class III wind turbines purchased/installed using an ECIP 

grant for funding 

• Seven 1.6 MW Class III wind turbines purchased/installed using a PPA

There are numerous variations to the wind farm scenario that could be investigated and 

optimized, but the intent of this analysis is to frame the economics to provide realistic 

expectations for moving forward.

11.2.2 General Modeling Assumptions

Several assumptions were made concerning the parameters of the economic modeling. 

These assumptions included:

• Annual averaged wind turbine output (3,634,101 kWh/yr) for a 1.6-MW 

turbine was used for all energy production calculations. Overall loss factor of 

17.7% was assumed.

• Purchase/installation and annual O&M, contract, insurance and warranty costs 

were modeled using estimated figures obtained for each scenario from 

industry sources or partners, all are estimates for an “unknown” project and 

they varied, but represent the best available figures for that segment of the 

industry.

• Fort Carson would complete the required NEPA permitting and the contractor 

would not be expected to conduct nor pay for any part of the NEPA approval 

process.

• The project life is assumed to be 20 years. The wind turbine useful life is 

estimated to be 20 to 30 years. This generation of 1+ MW turbines is not yet 

20 years old so there is little field experience to point to for verification. 

To enable smooth continuous operations with minimal downtime, in the event of a 

catastrophic equipment failure, it is prudent to put aside an annual self-imposed fee from 

the beginning of the project. An escrow account for capital repairs (blade failure, 
39

gearbox failure, etc.) is often used for this purpose. Though it is not possible to predict 

exactly when repairs will be necessary, having this fund ready will enable Fort Carson to 

have repairs taken care of quickly as there will be no need to search for funding to pay for 

them, the funds will be in escrow waiting. The funding and expense stream are not 

possible to match, but the escrow fund should prepare Fort Carson to meet any capital 

repair expenses that may arise. 

The Capital Repair Escrow Fund may work differently depending on the finance 

scenario. In the ECIP - Cash Purchase model, Fort Carson should have the funds from 

savings set aside in escrow so they can be deployed immediately for a repair. This was 

not captured in the model. It is assumed that in the PPA scenario the capital repair cost 

would be “built-in” to the energy cost being charged to Fort Carson though there was no 

accounting for this in the model.

The expected salvage value of the wind turbine with significant components made of 

steel, copper, etc. is expected to have enough residual value to cover the demolition costs. 

What is occurring in many sites that have smaller, older wind turbines 15-20 years old is 

a process called “re-powering”, that is the existing turbine nearing the end of its useful 

life is replaced with a newer, sometimes larger turbine since the permitting, electrical, 

etc. issues have already been addressed. Full turbine/foundation demolition and site 

restoration are not common.

11.2.3 Business as Usual

The business-as-usual scenario pits the EPAct 2005 annual 2% energy reduction

requirement against electricity price inflation to keep the annual electricity expense under 

control. Commercial electricity rates in Colorado have increased an average of 5.1% per 

year from 2000 to 2010.14 The “Energy Price Indices and Discount Factors for Life-Cycle 

Cost Analysis – 201115” predicts annual project inflation of 0.9% over the next 20 years.

The Energy Escalation Rate Calculator estimates the nominal energy escalation factor to 

be 2.99% over the next 20 years. If the historical increasing electricity price trend 

continues, even while doing the business-as-usual scenario with energy consumption 

declines, Fort Carson will likely see its annual electricity expenditure increasing over the 

next 20 or 25 years.

11.2.4 ECIP Funding

Economic analysis was completed assuming no finance charges through an ECIP-funded 

project. Though the overall cost for a 7-turbine wind farm may be outside the range of 

ECIP project budget, it is useful to set the cost parameter framework. Since Fort Carson 

is not a tax-paying entity, no PTC was used for these initial calculations. The simple 

payback results can be seen in Table 1612. The first line is labeled “ECIP – 20 yr life.”

The simple payback is 21.7 years and the Life Cycle Cost (LCC) is negative. However, 

the effect of extending the project life 25 years can be seen in the second line of the table 

 14 Department of Energy, Energy Information Agency. http://www.eia.gov/electricity/data.cfm#sales. 

Accessed March 2012.

15 Energy Price Indices and Discount Factors for Life-Cycle Cost Analysis – 2011, U.S. Department of 

Commerce. http://www1.eere.energy.gov/femp/pdfs/ashb11.pdf. Accessed March 2012.
40

in the orange-shaded boxes. The LCC becomes positive and savings-to-investment (SIR) 

exceeds 1.0.

Table 16 Economic Comparison of 20- and 25-year ECIP-funded Wind Project

 

11.3 ECIP Sensitivity Analysis

A sensitivity analysis was undertaken to illustrate the relative importance of key project 

factors. The economics were re-run against the ECIP 20-year life case (labeled ECIP –

Original in the table) to provide a constant barometer of relative impact. In the first 

scenario, beneficial factors were applied as the mean annual wind speed was increased by 

10%, the installed cost per kW was decreased by 10% and the competing COE was 

increased by 10%. The results can be seen in Table 17. The shaded boxes indicate factors 

that have changed compared to the ECIP – Original case. In each case, the LCC becomes 

positive, Savings to Investment (SIR) exceeds 1.0 and Simple Payback falls below 20 

years.

Table 137 Sensitivity Analysis of Beneficial Changes to Project Parameters

A second sensitivity analysis was completed with the same factors moving in a negative 

manner relative to the ECIP – Original case. That is, the wind speed decreased by 10%, 

the installed cost per kW increased by 10% and the competing COE decreased by 10%. 

As shown in Table 18, a negative trend applied to any of these factor results in the SIR 

moving below 1.0 and Simple Payback extending beyond 20 years.

Sensitivity Factor Annual 

Energy 

Output

Net 

CF *

Annual 

Energy 

Savings

Annual 

O&M **

% of FC 

Energy

Estimated 

Installed 

Cost

Life Cycle 

Cost 

Savings

Cost of 

Wind 

Energy

SIR *** Simple 

Payback

MWh/yr % $ $ % $ $ $/kWh - yrs

ECIP - 20 yr Life 25,439 25.9% $1,500,962 $331,130 13.3% $25,345,600 ($1,027,270) $0.061 0.96 21.7

ECIP - 25 yr Life 25,439 25.9% $1,500,962 $331,130 13.3% $25,345,600 $5,808,288 $0.051 1.23 21.7

* CF = Capacity Factor; ** O&M = Operations & Maintenance; *** SIR = Savings to Investment Ratio

Sensitivity 

Factors

Annual 

Energy 

Output

Net 

CF *

Annual 

Energy 

Savings

Annual 

O&M **

% of FC 

Energy

Estimated 

Installed 

Cost

Life Cycle 

Cost 

Savings

Cost of 

Wind 

Energy

SIR *** Simple 

Payback

MWh/yr % $ $ % $ $ $/kWh - yrs

ECIP - Original 25,439 25.9% $1,500,962 $331,130 13.3% $25,345,600 ($1,027,270) $0.061 0.96 21.7

Wind Speed - 10% ? 29,686 30.3% $1,751,465 $331,130 15.5% $25,345,600 $4,333,656 $0.052 1.17 17.8

Installed Cost -10% ? 25,439 25.9% $1,500,962 $331,130 13.3% $22,811,040 $1,230,460 $0.057 1.05 19.5

COE - 10% ? 25,439 25.9% $1,651,059 $331,130 13.3% $25,345,600 $2,185,195 $0.061 1.09 19.2

* CF = Capacity Factor; ** O&M = Operations & Maintenance; *** SIR = Savings to Investment Ratio
41

Table 148 Sensitivity Analysis of Negative Changes to Project Parameters

11.3.1 Power Purchase Agreement (PPA)

Another option to consider is to sign a long-term PPA with a wind developer where Fort 

Carson would purchase energy generated by the wind project at a negotiated price. This 

option has the potential to provide the best value to Fort Carson, but the contracting 

vehicle for federal agencies to sign PPA’ s for wind is not well-established at this time.

The assumptions applied here include:

• Equity partner could vary equity position from 0 – 100%

• 5% interest rate for a loan 

• The offset cost of electricity was $0.059/kWh

• PTC of $0.022/kWh was in place for the project.

The results are in Table 19. The ROI for equity partner is below current rates (~9 to 12%) 

and it may be difficult to attract an equity partner for a PPA. The 100% debt financing 

option is not financially feasible as modeled. The shorter Simple Payback (14.7 yrs vs. 

21.7 in other tables) is due to the third party owner-operator being able to take advantage 

of the PTC.

Table 159 PPA - Sensitivity Analysis of Financing Factors

ESPC and UESC approaches were not modeled given the low ROI’s calculated under the 

PPA. Generally, ESPC and UESC have higher ROI expectations so it was assumed that if 

the ESCO or utility had a fixed ROI of 15 to 25% (upfront fee often charged for ESPC 

contracts), that the resultant COE to Fort Carson would be unacceptably high.

Sensitivity 

Factors

Annual 

Energy 

Output

Net 

CF *

Annual 

Energy 

Savings

Annual 

O&M **

% of FC 

Energy

Estimated 

Installed 

Cost

Life Cycle 

Cost 

Savings

Cost of 

Wind 

Energy

SIR *** Simple 

Payback

MWh/yr % $ $ % $ $ $/kWh - yrs

ECIP - Original 25,439 25.9% $1,500,962 $331,130 13.3% $25,345,600 ($1,027,270) $0.061 0.96 21.7

Wind Speed - 10% ? 21,123 20.5% $1,186,522 $331,130 11.0% $25,345,600 ($6,478,596) $0.073 0.74 27.7

Installed Cost - 10% ? 25,439 25.9% $1,500,962 $331,130 13.3% $27,880,160 ($3,285,002) $0.065 0.88 23.8

COE - 10% ? 25,439 25.9% $1,350,866 $331,130 13.3% $25,345,600 ($4,239,735) $0.061 0.83 24.9

* CF = Capacity Factor; ** O&M = Operations & Maintenance; *** SIR = Savings to Investment Ratio

Sensitivity 

Factors

Annual 

Energy 

Output

Net 

CF *

Annual 

Energy 

Savings

Annual 

O&M **

% AfterTax ROI 

to Equity 

Partner

Estimated 

Installed 

Cost

Life Cycle 

Cost 

Savings

Cost of 

Wind 

Energy

SIR *** Simple 

Payback

MWh/yr % $ $ % $ $ $/kWh - yrs

PPA - 20 yr; 0% debt 25,439 25.9% $1,500,962 $331,130 3.5% $25,345,600 $1,292,988 $0.056 1.05 14.7

PPA - 20 yr; 30% debt 25,439 25.9% $1,500,962 $331,130 3.4% $25,345,600 $777,496 $0.057 1.04 14.7

PPA - 20 yr; 80% debt 25,439 25.9% $1,500,962 $331,130 2.6% $25,345,600 ($209,976) $0.060 0.96 14.7

PPA - 25 yr; 0% debt 25,439 25.9% $1,500,962 $331,130 4.9% $25,345,600 $5,735,813 $0.047 1.23 14.7

PPA - 25 yr; 30% debt 25,439 25.9% $1,500,962 $331,130 5.4% $25,345,600 $5,150,676 $0.049 1.29 14.7

PPA - 25 yr; 80% debt 25,439 25.9% $1,500,962 $331,130 8.2% $25,345,600 $3,994,369 $0.051 1.79 14.7

* CF = Capacity Factor; ** O&M = Operations & Maintenance; *** SIR = Savings to Investment Ratio
42

12 Conclusions and Recommendations

12.1 Conclusions

Wind data was collected from a 50-m met tower on a small ridge in the southeastern part 

of the Fort Carson base. A miniSODAR unit was also deployed at this site to measure 

wind speeds at elevations 30 to 140 m (98 to 459 ft) above ground. The data collected 

provided an effective dataset for comparative analysis of wind speed, turbulence 

intensity, and energy production of several wind turbines suitable for the wind conditions 

at the site. 

The mean annual wind speed during the period of investigation was 5.9 m/s (13.2 mph) at 

50 m. After normalizing this figure to account for the long-term wind trends with a 

modeled 14-year data set (ReEDS), the adjusted mean annual wind speed was 5.7 m/s 

(12.7 mph). 

Applying vertical wind shear factors obtained from the miniSODAR unit resulted in a 

mean annual wind speed of 6.2 m/s (13.9 mph) at 80 m. The mean turbulence intensity 

factor at 15 m/s was 0.13 which makes the site suitable for the newer low wind speed 

turbines (i.e., Class III IEC rating).

Table 20 shows the summary results of annual wind speeds, estimated annual energy 

production (AEP) figures, capacity factors, and the percent of Fort Carson’s electricity

load generated.

Table 20. Summary of Wind Project Energy Performance of Sample Wind Turbines

A comparison of the various financing scenarios modeled shows the tradeoffs between 

each approach. A 7-turbine wind plant rated at 11.2 MW was assumed with constant 

annual energy output of 25,439 MWh/yr, net capacity factor of 25.9%, annual energy 

savings of $1.5 million, installed cost of $25.4 million, and annual O&M of $331,000. 

Given the wind resource and the current cost of electricity at Fort Carson, the most viable 

option for a small wind farm appears to be ECIP funding, which is compared to other 

funding options in Table 21. The estimated purchase/installation cost of $25 million may 

be a barrier, but it provides the most compelling economic advantages to Fort Carson. 

Turbine Manufacturer 

& Model

Rated 

Power

Mean 

Net 

Power 

Ot t

Mean Net 

Annual Energy 

/Turbine/Yr

Net 

Capacity 

Factor

FC#2 

Site 

Wind 

Plant 

Capacity

Wind Plant 

Annual 

Output

% of Base 

Energy

Turbine MW kW kWh/yr % # Turb. MW MWh/yr %

GE 1.6 XLE 1.6 415 3,634,101 25.9 7 11.2 25,439 15.7%

Suzlon S97 2.1 475 4,162,921 22.6 7 14.7 29,140 18.0%

Siemens SWT-2.3 108 2.3 572 5,014,293 24.9 7 16.1 35,100 21.6%

Siemens SWT-2.3 113 2.3 691 6,049,308 30.0 7 16.1 42,345 26.1%

Nordex N117 2.4 647 5,665,505 26.9 7 16.8 39,659 24.4%

Vestas V112 - 3.0 MW 3.0 677 5,933,315 22.0 7 21.0 41,533 25.6%
43

Table 21. Comparison of Financing Scenarios

One possible approach within the ECIP scenario would be to request funds for 40-60% of 

the wind farm with the caveat that the annual savings could be saved over time to 

purchase the remainder of the farm at a future date. This approach, though not currently 

allowed by DoD, would enable Fort Carson to self-fund future renewable energy projects 

using savings from installed renewable energy projects. This approach could prove to be 

a model worth replicating after obtaining the necessary permission to pursue it.

The economic conditions for a PPA do not generally appear to be attractive to an investor 

at this time due to the relatively low COE ($0.059/kWh) that Fort Carson pays. The 

longer the project life, greater the overall ROI is expected to be. There is some 

uncertainty in this concept, as turbines in the size considered for this project have not 

been operating in the field for 20 to 25 years so the true O&M costs and turbine viability

at that later stage is somewhat speculative. It is reasonable to expect that if Fort Carson is 

willing to pay a premium for its wind-generated electricity, then a third-party investor 

could obtain a viable ROI.

12.2 Recommendations

Overall, the wind resource at the selected sites at Fort Carson is sufficient for a wind 

turbine project, though the specific approach (financing and ownership) and size still 

need more refinement. There are a number of other factors to consider before turbine 

selection is undertaken, including cost, availability, constructability, and transportability. 

There are also a number of other factors still to be explored as the parameters of this 

project become more clearly defined, including on-site military operations, FAA

restrictions and requirements, financing, NEPA restrictions and requirements, 

constructability, subsoil and foundations, impact on neighbors, and transportation 

planning and logistics. 

There are a number of proposed tasks to continue to move this project forward, including:

• Fort Carson to complete the NEPA evaluation already underway

• Complete an electrical interconnection study specifically assessing a 

distribution voltage possibility as well as the transmission voltage option

Sensitivity 

Factors

% After-Tax ROI 

to Equity 

Partner

Life Cycle 

Cost 

Savings

Cost of Wind 

Energy

SIR * Simple 

Payback

% $ $/kWh - yrs

ECIP - 20 yr Life N/A ($1,027,270) $0.061 0.96 21.7

ECIP - 25 yr Life N/A $5,808,288 $0.051 1.23 21.7

PPA - 20 yr; 0% debt 3.5% $1,292,988 $0.056 1.05 14.7

PPA - 20 yr; 30% debt 3.4% $777,496 $0.057 1.04 14.7

PPA - 20 yr; 80% debt 2.6% ($209,976) $0.060 0.96 14.7

PPA - 25 yr; 0% debt 4.9% $5,735,813 $0.047 1.23 14.7

PPA - 25 yr; 30% debt 5.4% $5,150,676 $0.049 1.29 14.7

PPA - 25 yr; 80% debt 8.2% $3,994,369 $0.051 1.79 14.7

* SIR = Savings to Investment Ratio
44

• Determine the most appropriate financing mechanism and secure project 

funding/finance

• Complete the transportation and logistics study

• Complete the visual and sound impact study

• Develop and implement a public information plan.
45

Appendix A. Wind Sensors & Tower

Met tower components for Fort Carson at FC#2:

• NRG Systems 50 m XHD Tower:

o Six NRG Systems #40C anemometers (item 1899)

o Two NRG Systems #200P wind vanes (item 1904)

o One NRG Systems #110S temperature sensor (item 1906)

o One SymphoniePLUS® data logger (item 4289).

• NRG Systems #40C Anemometer (item: 1899). The NRG Systems #40C

anemometer is the industry standard anemometer used worldwide. NRG 

Systems #40C anemometers have recorded wind speeds of 96 m/s (214 mph). 

Their low moment of inertia and unique bearings permit very rapid response 

to gusts and lulls. Because of their output linearity, these sensors are ideal for 

use with various data retrieval systems. A four-pole magnet induces a sine 

wave voltage into a coil producing an output signal with a frequency 

proportional to wind speed. The #40C is constructed of rugged Lexan cups 

molded in one piece for repeatable performance. A rubber terminal boot is 

included.

Figure A-1. Anemometer #40C NRG Systems (item 1899)16

• NRG Systems #200P Wind Direction Vane, 10K (item: 1904). The NRG 

Systems #200P wind direction vane is the industry standard wind direction 

vane used worldwide. The thermoplastic and stainless steel components resist 

corrosion and contribute to a high strength-to-weight ratio. The vane is 

connected directly to a precision conductive plastic potentiometer located in 

the main body. An analog voltage output directly proportional to the wind 

 16 Photo courtesy of NRG Systems, Inc. 

http://www.nrgsystems.com/AllProducts/SensorsandTurbineControl.aspx
46

direction is produced when a constant DC excitation voltage is applied to the 

potentiometer. A rubber terminal boot is included.

Figure A-2. Wind vane NRG Systems #200P (item 1904)17

• Mounting booms. NRG side-mounting booms allow you to easily mount 

sensors to your tower or mast at any height. Mounting hardware is included. 

Heavy-duty mounting booms are designed specifically for icing environments 

and mounting NRG IceFree sensors.

Figure A-3. Boom, side, 1.53m (60.5"), galvanized, with clamps (item: 3390)18

 17 Photo courtesy of NRG Systems, Inc. 

http://www.nrgsystems.com/AllProducts/SensorsandTurbineControl.aspx

18 Photo courtesy of NRG Systems, Inc. 

http://www.nrgsystems.com/AllProducts/SensorsandTurbineControl.aspx
47

Figure A-4. 50m and 60m XHD Tower configuration19

 19 Diagram courtesy of NRG Systems, Inc. http://www.nrgsystems.com/sitecore/content/Products/4063-

4290-4199.aspx. 
48

Appendix B. Fort Carson Met Tower Commissioning Report

The following was submitted by the installer, Advanced Turbine Service, Inc., to Brett 

Jackson of the Army National Guard.
49
50
51
52

Appendix C. Preliminary FAA Screening

FAA Long Range Radar Screening Results

NEXRAD Radar Preliminary Screening Results
53

Military Operations Preliminary Screening Results
54
55

Appendix D. Fort Carson Met Tower

Below are photos of the met tower and the met tower site.

Figure 23 Fort Carson 50m met tower with bird diverters. Photo credit: Robi Robichaud, 

NREL

Figure 24 Fort Carson 50m met tower – view from the northwest. Photo credit: Robi 

Robichaud, NREL
56

Appendix E. Wind Turbine Energy Production Loss Factors

The annual wind turbine energy production estimates were calculated assuming 17.7% 

losses, primarily due to wind turbine downtime, soiling/icing, electrical and other losses. 

The components of this loss factor include:

• Array efficiency: This loss parameter is associated with the wakes created by 

the turbines. This results in a decrease in wind speed and increase in 

turbulence as the wind moves through the wind farm array. This is a value 

estimated at 5%.

• Turbine availability: This term accounts for the expected downtime a wind 

turbine will experience during its annual operation. This includes routine 

maintenance, faults, and any component failures. Turbine availability or 

uptime is typically covered in the manufacturer’s warranty terms with a value 

of 95% or greater. 97% was assumed.

• Electrical: Electrical losses occur in the process of collecting and transmitting 

the project energy across the site. As the power moves through the 

transformers and collection system, a certain percentage will be lost as heat. 

This value is typically estimated at 2%.

• Hysteresis: This is the term for when a turbine shuts down to protect itself 

from ambient climate events that are outside of the design envelope. This 

typically involves a high wind event that forces the turbine to shut down for a 

period of time. Based on on-site data, these are expected to be negligible.

• Environmental: Environmental losses occur because of ambient conditions 

that may affect blade aerodynamics or turbine operation. This includes icing, 

blade soiling, insect accumulation, and extreme cold or hot events. This is 

expected to happen at Fort Carson and is estimated to be on the order of 4%.

• Operational: Operational energy requirements such as power for the control 

system, heating system, and other parasitic loads are estimated at 2%.

• Power curve variation: The power curve may deviate from the 

manufacturer-stated designation due to yaw system misalignment, incorrect 

programming, or ambient weather events such as high turbulence or variations 

in atmospheric stability. This is not believed to be an issue for Fort Carson.

• Substation downtime: The collection substation on the Fort Carson side of 

the utility interconnection will likely require some downtime for routine 

maintenance. This is estimated at 0.5% for Fort Carson.

• Utility downtime: Utility transmission and distribution uptime or availability 

is generally very high. However, there are certain areas of the country or 

seasons of the year with more risk. The Fort Carson site is assumed to 

experience energy loss of 0.5% due to the utility electrical system being 

unavailable for power transmission.