<%BANNER%>

Regional Renewable Assessment

Permanent Link: http://ufdc.ufl.edu/UFE0024933/00001

Material Information

Title: Regional Renewable Assessment Wind Versus Solar Energy
Physical Description: 1 online resource (87 p.)
Language: english
Creator: Walker, Joshua
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Building Construction -- Dissertations, Academic -- UF
Genre: Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction REGIONAL RENEWABLE ASSESSMENT: WIND V. SOLAR By Joshua Walker August 2009 Chair: Charles Kibert Cochair: Svetlana Olbina Major: Building Construction The purpose of this research is to investigate two renewable sources of energy, wind and solar energy resources. There is difficulty deciding which energy source to utilize when both are present. This research provides break-even points that show at what winds speeds a wind turbine will outperform a photovoltaic array. As the U.S. adopts more sustainable practices, renewable energy systems are going to play a pivotal role in shaping our greener built environment (Lund, 2009). Wind generators and photovoltaics (PVs) are two leading systems in our attempt to harness energy via renewable resources. Wind and solar energy are both considered renewable resources due to the fact that neither will be depleted in the foreseeable future. The aim is to take advantage of these energy sources as opposed to our traditional energy systems such as coal, oil or nuclear. Exploiting the energy provided by wind and solar tends to have much less detrimental effect on the environment. The only emissions associated with these two renewable sources are those connected to the production of the machines and materials used to build and implement the systems that actually capture the energy from the sun or wind. The aim of this research, however, is not to justify these claims; rather it is to compare the implementation of these two technologies throughout different regions of the continental United States. The United States Department of Energy (DOE) has established the National Renewable Energy Laboratory (NREL) to conduct testing and research on 12 main programmatic areas. Two of these areas include Solar Energy Technologies and Wind Technologies. There is an abundant amount of information on solar technology and emerging wind technology. The NREL research has allowed the organization to prescribe beneficial photovoltaic and wind power technologies to consumers at all levels. Of note for this research are the Wind Resource Maps and the Solar Radiation Maps which provide the kilowatt hours (kWh) that are available from these natural resources. The NREL, however, has not yet integrated these two different technologies in a way that allows consumers to quickly decide between a solar or wind system setup. While the National Renewable Energy Laboratory does have Wind Energy Resource Maps and Solar Radiation Maps, it is not clear what regions will benefit more from wind or solar power. This research aims to provide guided information that prescribes which approach is most appropriate for different regions within the U.S that have both wind and solar resources available. The regions are defined based on parameters of the NREL Wind Resource Classification and Solar Radiation areas. With the aid of PVWATTS, FirstLook Wind Maps, and a WindCAD program developed by the 3Tier group, the production value of two models, a wind turbine and photovoltaic array, are compared.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Joshua Walker.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2009.
Local: Adviser: Kibert, Charles J.
Local: Co-adviser: Olbina, Svetlana.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024933:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024933/00001

Material Information

Title: Regional Renewable Assessment Wind Versus Solar Energy
Physical Description: 1 online resource (87 p.)
Language: english
Creator: Walker, Joshua
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Building Construction -- Dissertations, Academic -- UF
Genre: Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction REGIONAL RENEWABLE ASSESSMENT: WIND V. SOLAR By Joshua Walker August 2009 Chair: Charles Kibert Cochair: Svetlana Olbina Major: Building Construction The purpose of this research is to investigate two renewable sources of energy, wind and solar energy resources. There is difficulty deciding which energy source to utilize when both are present. This research provides break-even points that show at what winds speeds a wind turbine will outperform a photovoltaic array. As the U.S. adopts more sustainable practices, renewable energy systems are going to play a pivotal role in shaping our greener built environment (Lund, 2009). Wind generators and photovoltaics (PVs) are two leading systems in our attempt to harness energy via renewable resources. Wind and solar energy are both considered renewable resources due to the fact that neither will be depleted in the foreseeable future. The aim is to take advantage of these energy sources as opposed to our traditional energy systems such as coal, oil or nuclear. Exploiting the energy provided by wind and solar tends to have much less detrimental effect on the environment. The only emissions associated with these two renewable sources are those connected to the production of the machines and materials used to build and implement the systems that actually capture the energy from the sun or wind. The aim of this research, however, is not to justify these claims; rather it is to compare the implementation of these two technologies throughout different regions of the continental United States. The United States Department of Energy (DOE) has established the National Renewable Energy Laboratory (NREL) to conduct testing and research on 12 main programmatic areas. Two of these areas include Solar Energy Technologies and Wind Technologies. There is an abundant amount of information on solar technology and emerging wind technology. The NREL research has allowed the organization to prescribe beneficial photovoltaic and wind power technologies to consumers at all levels. Of note for this research are the Wind Resource Maps and the Solar Radiation Maps which provide the kilowatt hours (kWh) that are available from these natural resources. The NREL, however, has not yet integrated these two different technologies in a way that allows consumers to quickly decide between a solar or wind system setup. While the National Renewable Energy Laboratory does have Wind Energy Resource Maps and Solar Radiation Maps, it is not clear what regions will benefit more from wind or solar power. This research aims to provide guided information that prescribes which approach is most appropriate for different regions within the U.S that have both wind and solar resources available. The regions are defined based on parameters of the NREL Wind Resource Classification and Solar Radiation areas. With the aid of PVWATTS, FirstLook Wind Maps, and a WindCAD program developed by the 3Tier group, the production value of two models, a wind turbine and photovoltaic array, are compared.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Joshua Walker.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2009.
Local: Adviser: Kibert, Charles J.
Local: Co-adviser: Olbina, Svetlana.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024933:00001


This item has the following downloads:


Full Text

PAGE 1

1 REGIONAL RENEWABLE ASSESSMENT: WIND VERSUS SOLAR ENERGY By JOSHUA WALKER A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2009

PAGE 2

2 2009 Joshua Walker

PAGE 3

3 To my family

PAGE 4

4 ACKNOWLEDGMENTS I would like to thank m y family for their support Also, a great deal of gratitude goes to the M.E. Rinker, Sr. School of Buildi ng Construction at the University of Florida. I finally found my niche. The people inside the walls of Rinker Hall have made the difference. To my professors and peers, thank you for your unrivaled spirit, passion and dedication.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4LIST OF TABLES ...........................................................................................................................7LIST OF FIGURES .........................................................................................................................8LIST OF ABBREVIATIONS ........................................................................................................ 11ABSTRACT ...................................................................................................................... .............12 CHAP TER 1 INTRODUCTION .................................................................................................................. 14Nonrenewable Energy ............................................................................................................14Problem Statement ............................................................................................................. .....15Objective ..................................................................................................................... ............15Contribution .................................................................................................................. ..........162 LITERATURE REVIEW .......................................................................................................17Introduction .................................................................................................................. ...........17Wind Energy ....................................................................................................................17Wind Turbines .................................................................................................................17Typical Small Wind Installations .................................................................................... 21Solar Energy ....................................................................................................................24Typical PV Array ............................................................................................................ 27Recent Studies .................................................................................................................28Tools ......................................................................................................................... ..............28PVWATTS ...................................................................................................................... 28FirstLook .........................................................................................................................29WindCad Turbine Performance Model ........................................................................... 303 METHODOLOGY ................................................................................................................. 33Experimental Method ........................................................................................................... ..33Models ....................................................................................................................................35Photovoltaic Array Model ...............................................................................................35Wind Turbine Model .......................................................................................................364 RESULTS AND ANALYSIS................................................................................................. 37Results .....................................................................................................................................37Sampling Organization ...........................................................................................................38

PAGE 6

6 Solar Radiation Zone One ...............................................................................................39Solar Radiation Zone Two ...............................................................................................41Solar Radiation Zone Three .............................................................................................42Overall ....................................................................................................................... ......44Discussion .................................................................................................................... ...........45Solar Radiation Zone 1 .................................................................................................... 45Solar Radiation Zone 2 .................................................................................................... 46Solar Radiation Zone 3 .................................................................................................... 47Summary ....................................................................................................................... ...475 CONCLUSIONS AND SUGG ESTE D RESEARCH ............................................................ 49Conclusions .............................................................................................................................49Suggested Research ................................................................................................................50APPENDIX A SOLAR RADIATION ZONE 1 .............................................................................................51B SOLAR RADIATION ZONE 2 .............................................................................................53C SOLAR RADIATION ZONE 3 .............................................................................................55D OVERALL RESULTS ........................................................................................................... 57E RAW DATA ...........................................................................................................................59F SITE SPECIFIC RESULTS ................................................................................................... 63LIST OF REFERENCES ...............................................................................................................177H8549HBIOGRAPHICAL SKETCH .........................................................................................................178H87

PAGE 7

7 LIST OF TABLES Table page 2-1 AC Energy and Cost Savings Site Identification ...............................................................302-2 AC Energy and Cost Savings Results ................................................................................30A-1 Solar Radiation Zone 1 Ranges and Averages. ...............................................................51B-1 Solar Radiation Zone 2 Ranges and Averages. ...............................................................53C-1 Solar Radiation Zone 3 Ranges and Averages. ...............................................................55D-1 All Zones Ranges and Averages. ..................................................................................... 57

PAGE 8

8 LIST OF FIGURES Figure page 1-1 Components of a typical hor izontal axis wind turbine.. ....................................................201-2 Photovoltaic cell. Cells are connected in module and modules are connected to form panels. A set of panels makes an array.. ............................................................................ 262-1 Example of PVWA TTS input data.. .................................................................................. 312-2 Example of WindCad Turbine Performance Model. ......................................................... 323-1 In color, wind power classifi cation can be seen and mapped.. ..........................................343-2 This map shows three different solar ra diation regions in the Midwest designated by three different color shaded areas.. ....................................................................................35A-1 Annual production (kWh) vs. wind sp eed for Solar Radiation Zone 1. ............................ 51A-2 Annual Production Value vs. wind speed for Solar Radiation Zone 1. ............................. 52A-3 Annual Return on Investment. Solar Radiation Zone 1. .................................................... 52B-1 Annual production (kWh) vs. wind sp eed for Solar Radiation Zone 2. ............................ 53B-2 Annual Production Value vs. wind speed for Solar Radiation Zone 2. ............................. 54B-3 Annual Return on investment. Solar Radiation Zone 2. .................................................... 54C-1 Annual production (kWh) vs. wind sp eed for Solar Radiation Zone 3. ............................ 55C-2 Annual Production Value vs. wind speed for Solar Radiation Zone 3. ............................. 56C-3 Annual Return on Investment. Solar Radiation Zone 3. .................................................... 56D-1 Overall Annual Production (kWh) vs. wind speed for all Solar Radiation Zones. ............ 57D-2 Overall Annual Production Value vs. wind speed for all Solar Radiation Zones. ............. 58D-3 Overall Annual Return on Investment. All Solar Radiation Zones. .................................. 58E-1 Raw data for Solar Radiation Zone 1. ................................................................................60E-2 Raw data for Solar Radiation Zone 2. ................................................................................61F-1 Site Specific Model Performances. Site 1. ......................................................................... 63F-2 Site Specific Model Performances. Site 2. ......................................................................... 63

PAGE 9

9 F-3 Site Specific Model Performances. Site 3. ......................................................................... 64F-4 Site Specific Model Performances. Site 4. ......................................................................... 64F-5 Site Specific Model Performances. Site 5. ......................................................................... 65F-6 Site Specific Model Performances. Site 6. ......................................................................... 65F-7 Site Specific Model Performances. Site 7. ......................................................................... 66F-8 Site Specific Model Performances. Site 8. ......................................................................... 66F-9 Site Specific Model Performances. Site 9. ......................................................................... 67F-10 Site Specific Model Performances. Site 10. ....................................................................... 67F-11 Site Specific Model Performances. Site 11. ....................................................................... 68F-12 Site Specific Model Performances. Site 12. ....................................................................... 68F-13 Site Specific Model Performances. Site 13. ....................................................................... 69F-14 Site Specific Model Performances. Site 14. ....................................................................... 69F-15 Site Specific Model Performances. Site 15. ....................................................................... 70F-16 Site Specific Model Performances. Site 16. ....................................................................... 70F-17 Site Specific Model Performances. Site 17. ....................................................................... 71F-18 Site Specific Model Performances. Site 18. ....................................................................... 71F-19 Site Specific Model Performances. Site 19. ....................................................................... 72F-20 Site Specific Model Performances. Site 20. ....................................................................... 72F-21 Site Specific Model Performances. Site 21. ....................................................................... 73F-22 Site Specific Model Performances. Site 22. ....................................................................... 73F-23 Site Specific Model Performances. Site 23. ....................................................................... 74F-24 Site Specific Model Performances. Site 24. ....................................................................... 74F-25 Site Specific Model Performances. Site 25. ....................................................................... 75F-26 Site Specific Model Performances. Site 26. ....................................................................... 75F-27 Site Specific Model Performances. Site 27. ....................................................................... 76

PAGE 10

10 F-28 Site Specific Model Performances. Site 28. ....................................................................... 76F-29 Site Specific Model Performances. Site 29. ....................................................................... 77F-30 Site Specific Model Performances. Site 30. ....................................................................... 77F-31 Site Specific Model Performances. Site 31. ....................................................................... 78F-32 Site Specific Model Performances. Site 32. ....................................................................... 78F-33 Site Specific Model Performances. Site 33. ....................................................................... 79F-34 Site Specific Model Performances. Site 34. ....................................................................... 79F-35 Site Specific Model Performances. Site 35. ....................................................................... 80F-36 Site Specific Model Performances. Site 36. ....................................................................... 80F-37 Site Specific Model Performances. Site 37. ....................................................................... 81F-38 Site Specific Model Performances. Site 38. ....................................................................... 81F-39 Site Specific Model Performances. Site 39. ....................................................................... 82F-40 Site Specific Model Performances. Site 40. ....................................................................... 82F-41 Site Specific Model Performances. Site 41. ....................................................................... 83F-42 Site Specific Model Performances. Site 42. ....................................................................... 83F-43 Site Specific Model Performances. Site 43. ....................................................................... 84F-44 Site Specific Model Performances. Site 44. ....................................................................... 84

PAGE 11

11 LIST OF ABBREVIATIONS AC Alternating Current AWEA American Wind Energy Association Co. Company DC Direct Current DOE Department of Energy EPA Energy Policy Act GHG Greenhouse gas Inc. Incorporated kW Kilowatt kWh Kilowatt-hour LLC Limited Liability Corporation m/s Meters per second MW Megawatt NASA National Aeronautical Space Administration NREL National Renewable Energy Laboratory PURPA Public Utility Regulatory Policies Act PV Photovoltaic W Watt Wp Peak Watt WPA Wind Powering America

PAGE 12

12 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction REGIONAL RENEWABLE ASSE SSMENT: WIND V. SOLAR By Joshua Walker August 2009 Chair: Charles Kibert Cochair: Svetlana Olbina Major: Building Construction The purpose of this research is to investig ate two renewable sources of energy, wind and solar energy resources. There is difficulty deci ding which energy source to utilize when both are present. This research provides break-even points that show at wh at winds speeds a wind turbine will outperform a photovoltaic array. As the U.S. adopts more sustainable practices renewable energy systems are going to play a pivotal role in shaping our greener bu ilt environment (Lund, 2009). Wind generators and photovoltaics (PVs) are two leading systems in our attempt to harness energy via renewable resources. Wind and solar energy are both considered renewable re sources due to the fact that neither will be depleted in the foreseeable future. The aim is to take advantage of these energy sources as opposed to our tr aditional energy systems such as coal, oil or nuclear. Exploiting the energy provided by wind and so lar tends to have much less detrimental effect on the environment. The only emissions a ssociated with these two renewable sources are those connected to the production of the machines and materials used to build and implement the systems that actually capture the energy from the sun or wind. The aim of this research, however,

PAGE 13

13 is not to justify these claims; rather it is to compare the implementation of these two technologies throughout different regions of the continental United States. The United States Department of Energy ( DOE) has established the National Renewable Energy Laboratory (NREL) to conduct testing and research on 12 main programmatic areas. Two of these areas include Solar Energy Technologies and Wind Technologies. There is an abundant amount of information on solar technology and emerging wind technology. The NREL research has allowed the organization to prescribe benefi cial photovoltaic and wind power technologies to consumers at all levels. Of note for this res earch are the Wind Resource Maps and the Solar Radiation Maps which provide the kilowatt hours (kWh) that are available from these natural resources. The NREL, however, has not yet integr ated these two different technologies in a way that allows consumers to quickly decide between a solar or wind system setup. While the National Renewable Energy Laborat ory does have Wind Energy Resource Maps and Solar Radiation Maps, it is not clear what regions will benefit more from wind or solar power. This research aims to pr ovide guided information that pres cribes which approach is most appropriate for different regions within the U.S that have both wind and solar resources available. The regions are defined based on parameters of the NREL Wind Resource Classification and Solar Radiati on areas. With the aid of PVWATTS, FirstLook Wind Maps, and a WindCAD program developed by the 3Tier gro up, the production value of two models, a wind turbine and photovoltaic array, are compared.

PAGE 14

14 CHAPTER 1 INTRODUCTION Renewable energy m arkets are growing in the U. S. and as they become ever more popular individuals will need to make some decisions on as to what system they wish to purchase. Wind turbines are available to harness wind energy re sources and PV arrays capture he suns energy. While DOE has provided consumers with maps a nd resource allocations, they are still not enough to suggest what energy system individuals should purchase when they have the option of both wind and solar energy resources. This problem of dual energy sources in one location gives rise to this research. By sampling areas in th e U.S. with overlapping wind and solar resources two models can be run to determine performance of a wind turbine and a pv array. This research should show what application performs better gi ven varying wind and sola r resource availability. Nonrenewable Energy Conventional m odes of producing energy in the United States (i .e. coal, oil, and nuclear) tend to have detrimental effects on the environmen t. There are wide spread concerns of these activities contributing to global warming and climate change. The burning of fossil fuels and traditional power plants expel gases such as su lfur dioxide, carbon dioxide, nitrogen dioxide, other nitrogen oxides, particulates and also toxic heavy metals (Matthew, 2006). Collectively these gases are known as greenhouse gases (GHG). These gases stand to increase the global warming potential by allowing solar energy into our atmosphere but trapping in the reflected solar radiation, thus heating the environment. Sulf ur dioxide and other emissions are the cause of acid rain, which tends to kill lakes, deplete forests of their nutrients and also damage buildings and other structures. Energy produced by nuclear fission does not have as many emissions but the toxic nuclear wastes pose a threat to livi ng organisms. While there have been nuclear disasters in the past, nuclear power plants have a safe track record but there are still concerns for

PAGE 15

15 effectively containing the radioactive waste that la sts for thousands of years. All these factors, and more, have led to the widespread search for effective and environmentally friendly modes of producing energy. As opposed to these traditional methods of producing energy, the U.S., European nations, and many other countries have committed to increasing their amount of renewable energy systems (DOE, 2008). Renewable en ergy is energy that is genera ted from naturally occurring resources that are not depleted in the foreseeab le future. These resources include biomass, geothermal heat, rain, sunlight and wind. Two of the leading renewable energy systems in the U.S. are wind turbines and photovoltaic arrays (DOE, 2008). Problem Statement W ith a heavy emphasis on renewable energy sy stems, both wind turbines and photovoltaic arrays are becoming prolific energy systems th at harness renewable resources. Beyond large wind turbine farms and massive fields of PV a rrays, individuals and small businesses have the potential to purchase these systems and participat e in receiving their energy from a renewable resource. It is very difficult, however, to choos e which system is better when both resources are available. Many factors go into deciding between a wind turbine and a PV array. Site constraints and cost restriction can be determining, but if they are not, then the available resource is often a deciding factor. There are limited resources that aid in this decision making process and further research is needed to quantify the performan ce of wind turbines ag ainst PVs in varying geographic locations with different le vels of energy resource available. Objective The objectiv e of this research is to find the break-even point of wind and solar energy systems based on performance in different wind resour ce regions in the U.S. that fall within the different solar radiation zones mapped out by the Department of Energy. By plotting the

PAGE 16

16 performance of a wind turbine and a PV array (k Whs) against the wind velocities in a sampled location, the break-even point can be found for severa l sites. This information will help those in different wind classification and solar zones of th e U.S. decide between a wind turbine and a PV array based on the wind velocitie s and solar radiation that are typical for their location. Contribution This research contributes site specific an alysis of a wind turbine m odel and a pv array model both simulated on the computer. The analys is of the results provides information that shows the varying levels of performance of th e two models and in what regions individuals should pursue renewable energy options based on their wind and so lar classification.

PAGE 17

17 CHAPTER 2 LITERATURE REVIEW Introduction The f ollowing outlines the history and implementation of the two energy resources of concern in this research. Wind and wind turbin es are discussed and explained followed by the solar resource and photovolta ic arrays. The typical installation of either energy capture apparatus is defined, thus justifying the scope of the expe riment. This is followed by recent studies that show current findings and helps to guide this research. Finally the to ols used to run the experiment are explained. These include PVWatts FirstLook wind prosp ecting tool and a Wind Turbine Performance Model. Wind Energy Wind has been used as a power source for several centuries and some evidence suggests even longer. Arthasastra, a classic work of Sanskrit from the 4th century B.C., references the use of water conveyance via wind powered machines (Mathew, 2006). There is no sound evidence that proves these machines existed, but it is also argued that Hammurabi planned for wind machines in his irrigation system schematics in th e seventeenth century B.C. While the origins of wind utilization are debated we do know that in its rudimentary applications wind was used to sail ships and turn windmills to grind grains and pump water to irrigate crop fields. The Persians are credited with the first documented signs of windmill use in 200 B.C (Mathew, 2006). It is this windmill design that has transitioned over the years into todays modern wind powered devices. Wind Turbines In this day and age, large and sm all wind tu rbines capture the winds energy and turn it into useful electricity. Wind tu rbines are composed of a fe w major components including the

PAGE 18

18 rotors, turbine, generator and the tower that serves as a support and places the turbine high in the air to reach the higher wind velocities. The factor s that drive the perfor mance of a wind turbine are the rotor swept area. This is defined by the area of the circle that the rotor blades make when they spin. Also, the wind velocity is a prevailing factor when determining power production: the stronger the wind the greater the power productio n. It should be noted that turbines have optimum speeds at which they operate because tu rbulence or too powerful winds can damage a turbine structurally and internall y. Therefore, most turbines are outfitted with mechanisms that slow the rotors in the event of extreme winds. Other factors such as air density, which can vary with altitude, will affect the overall performance. Th e Betz limit is another important factor that governs the amount of power output. The Betz limit is a theoretical power coefficient that states the maximum efficiency of a wind turbine. According to the limit, a turbine can only convert 59.3% of the available wind energy into mech anical work. This maximum is not usually achieved in practice; rather lower peak efficiencies are experienced. The overall equation that determines the power output from a wind tu rbine is as follows (Burton, et al., 2001): P = .5 Cp AU3 (2-1) Where: P = power output Cp = power coefficient (Betz Limit) = air density (1.225 kg/m3) A = rotor swept area U = wind speed These are the driving factors that affect wind turbine performance. As the equation shows, a doubling of wind speed will increase power output by a factor of eight due to the fact that the wind speed, U, is cubed. Furthermore, because the swept area ( r2) is a function of the diameter of the rotor, simply doubling the rotor length will increase the power output by a factor of four. While engineers and manufacturers are constantly looking for ways to improve

PAGE 19

19 efficiency and performance of wind turbines, the factor with the most in fluence is clearly the wind speed. While the previous is a basic review of the governing principles of wind turbine technology, several different sizes an d styles of turbines have been built and specialized over the years to harness the inherent energy in wind. Th e current and most popular wind turbines utilize a horizontal axis that is essent ially a shaft parallel to the gr ound (Figure 1.1). This low speed shaft is turned by the rotors that are designed to be turned by th e wind. In most applications, the low speed shaft connects internally to a gear box that is in turn connected to a high speed shaft that drives the generator to produce AC electri city. There are other co mmon features of a wind turbine that aid in its function. One item is the cont roller and its job is to start up the machine at the appropriate wind speeds and to shut it down when wind speeds get too high. Also, a brake is utilized to slow or stop the rotor when necessa ry. Once again, wind speeds that are too high will damage the machine. The controller is fed information by an anemometer that measures wind speed. Like the anemometer, a wind vane will collect data that indicates the direction of the wind. This information will control which way th e turbine faces. An upwind turbine must face into the wind and thus a yaw drive is essential to turn the face of the rotor into the wind. A yaw motor powers the yaw drive. Downwind turbines do not require a yaw drive. The nacelle contains the majority of the moving parts of th e wind turbine aside from the actual rotor blades. This nacelle is like a hub that sits atop a tower that hoists the apparatus in the air in order to capture wind speeds that exists at higher eleva tions. Vertical axis wind turbines do exist and they operate much in the same way as a horizonta l axis wind turbine. The main difference is that the low speed shaft is vertical and perpendicular to the ground. Th eoretically, this system should work as well as the horizontal shaft but in practice, the vertical shafts performance has fallen

PAGE 20

20 short. Furthermore, the vertical shaft style of a wi nd turbine encounters problems when it comes to trying to avoid damage from higher wind speeds. Thus few vertical axis turbines are seen and the horizontal axis is the prevalent style of wind turbine used in the industry today. As of April 30, 2009, the U.S. had 28,635 MW of wind power installed across the nation. That is more than ten-fold the amount at th e years end in 1999 a nd a 12.69 percent increase from 2008 (DOE, 2009). Wind energy is clearly a fast growing industry that is backed by federal, state and local policies. The DOE has also proposed the % Wind Energy by 2030 initiative. This report examines the scenario of reaching its goal as opposed to a scenario in the U.S. where no new wind power capacity is devel oped (DOE, 2008). The effort to increase wind power is evidenced by the large wind farms that have sprung up in the Midwest and even in coastal waters. The turbines that make up these fa rms are typically at the utility scale and range from 100kW to the megawatt magnitude. While thes e turbines are significant in the effort to increase wind power capacity, th is research focuses on small wi nd that includes turbines under the 100kW range (DOE, March 2009). Figure 1-1. Components of a typi cal horizontal axis wind turbine. (Source: http://www.storkgears.com/images/hawt.jpg. Last accessed June, 2009).

PAGE 21

21 With over 24% of the U.S. population living in rural areas and over 21 million homes situated on one acre or more, small winds stan ds to make an impact on the energy needs of individuals (DOE, 2005). While small wind turb ines have been around and in successful operation for years, new government funding and incentives, along with global awareness of renewable energy systems, are boosting the de mand for the installations. The government incentives are allowing small wind to enter areas that have not been considered before. In 2007 the federal government funded the entire instal lation of a 10kW wind turbine on a senior housing complex in Winter Harbor, Maine (DOE, 2008). Th e federal grant came from the Residential Energy Assistance Challenge (REACH) in order to lower low the utility costs for the tenants of the building, most who are on a fixed income a nd live in subsidized hous ing. REACH falls under the jurisdiction of the U.S. Department of Health and Human Services Low Income Home Energy Assistance Program (LIHEAP). This prog ram aims to fund energy saving projects for individuals in vulnerable househol ds that consist of either you ng children, disabled persons, or the elderly in poor health. While unique situatio ns like this exist, th ere are many opportunities for the more traditional small wind installation. Typical Small Wind Installations The NREL has provided a publication called Sm all W ind Electric Systems: A Consumers Guide. This guide answers many questions such as: Is Wind Energy Practical for Me? What Size Wind Turbine Do I Need? What are the Basi c Parts of a Small Wind Electric System? These questions are very pert inent for someone seeking to install a small wind turbine. Furthermore, the guide serves as a practical handbook for outlining what makes a successful small wind turbine installation. The first step towards a small wind turbine installation is determining if the site has available winds. The NREL suggests that one live in a Wind Resour ce Classification of at least

PAGE 22

22 two in order to reap the benefits of wind. Th is means that there are annual winds speeds averaging between 5.9 and 6.7 m/s at 50 mete rs in elevation (DOE 2006). Some other preliminary assessments include assuring that there is land space, at least one acre, for installation. Also, zoning codes must allow for th e installation and the user must be willing to accept the cost and investment of the system. Ge nerally, wind turbine installations have high upfront cost, but it is expected that they will ha ve a payback period when the value of the energy they are producing exceeds the system cost over time. The American Wind Energy Association (AWEA) and Bergey WindPower Co. state that a small wind turbine will cost one to six thousand dollars per kW generati ng capacity. Small wind turbine installations are anywhere from the micro level (20-500 Watts) up to 100kW. Th e common installation for a home wishing to impact its energy consumption and cost is a ten kilowatt system mounted on a thirty meter tower. An installation of this magnitude ranges typi cally from 25 to 35 thous and dollars. The common trend with wind is the larger systems cost less per kW and they have a shorter payback period (Matthew, 2006). The next step after choosing and sizing the wi nd turbine is to decide if it will be grid connected. It is recommended that small wind turbin es are connected to the utility grid because most applications will not meet the electrical demands of a home or small business. Most wind applications are intended to subsidize the ener gy needs in hopes that the turbine will pay for itself over its lifetime. A ten kW turbine is often warrantied for five years and life expectancy is 25 years plus. It is important to note that small wind turbines pr oduce direct current (DC) power, while home appliances require alte rnating current (AC) power. This means an inverter must be purchased and is necessary to convert DC electric ity into AC electricity. The inverter is usually part of the package sold to the consumer and its cost is included in pricing estimates. Converting

PAGE 23

23 from DC to AC will lower the efficiency. Furtherm ore, the AC wire runs deplete efficiency more than DC wire runs. These are all things to keep in mind when designing the system. One of the final interests of the consumer is the payback period of their wind turbine installation. As mentioned previ ously, initial investme nts are high but the lifetime reduced or avoided utility cost can allow wind turbines to be competitive with the tr aditional utility. Federal and state subsidizers are also available for those seeking to install a renewable energy system such as a wind turbine. These can significantly lower initial costs. Another incentive is net metering. Net metering is a consumer based renewable energy incentive that credits the consumer for any excess energy produced by their renewable system. With the turbine connected to the grid via the electric meter, any excess ener gy produced will run the meter backwards for the owner of the building. This ca n make a significant difference especially in circumstances such as at night time when ener gy demands are low but the wind is still blowing. Also, federal regulations like the Public Utility Regulatory Policies Act (P URPA) of 1978 require utilities to connect w ith and purchase power from small wind energy systems. This act also protects against discriminatory charges to wards those generating their own electricity. The Energy Policy Act (EPA) of 2005, Section 1251, also requires utility companies to make net metering available upon request. Some net meteri ng jurisdiction has language that handles net excess generation in different ways. Some progr ams will have monthly net metering and others annual net metering. Typically, winds are stronger in the winter, so annu al net excess generation then will apply to summer months where winds are calmer and electric loads from air conditioning are higher. If a grid connection is based on a monthly net excess generation program, this type of transfer of credits is not possible. Another overlooked cost might be insurance. It is often wise to have insurance on such a large investment. So me states even require

PAGE 24

24 insurance policies that cover up to one million dolla rs despite there never having been a liability claim or monetary award relate d to electric safety involving a small wind turbine (DOE, 2005). Several states have realized this burdensome insurance requirement and have banned excessive coverage policies (California, Georgia, Maryland, Nevada, Okla homa, and Washington). Other states, like Idaho and Virginia, have reduced the amount to similar re sidential and commercial policies. The NREL consumers guide cites a small wind installation that occurred in 1983 and is still in operation. This install included a 10kW turbine m ounted on a 100 foot high tower on a farm in Southwestern Kansas. The turbine produces 1700-1800 kilowatt-hours per month and cost 20 thousand dollars at the time of installation. Estimated maintenance and operation costs have been 50 dollars a month. This example s hows clearly that a maintained wind turbine can prove to be a beneficial economic and environmentally friendly investment. Solar Energy Solar cells, also known as photovoltaics (PVs) we re first utilized to make electricity in the 1950s by scientists at the Bell Laboratory in New Jersey. PVs are named so due to the photovoltaic effect that was di scovered in 1839 by a French scie ntist Edmund Becquerel. When exposed to light, Becquerel discovered that cert ain materials would produ ce an electric current. The phenomenon that Becquerel wa s witnessing was that photons were hitting a substance and exciting electrons and causing them to be displaced and become part of an electrical current. The scientists in the New Jersey Bell Laboratory were able to take advantage of this phenomenon by taking two dislike semiconductors and sandwiching them together separated by a junction. Then, by attaching an electrical contact to either side of the cell and connecting the contacts with a wire, an electrical circuit is fo rmed when the apparatus is expose d to light, or in essence, photons (Wilson 2001).

PAGE 25

25 The National Aeronautic s and Space Administration ( NASA) was one of the first to find an application for this technology. They were also one of the few who could afford it. At one thousand dollars per peak watt (Wp) there we re limited uses for PVs beyond NASAs satellite program. By the s the price of PVs had dropped to 100 dollars per Wp and they could be used in remote locations powering transmitters and other devices far from grid power. Prices continued to drop in th e eighties and PVs were continually more efficient. At this point residential homes far from grid power could afford the ten dollars per Wp. Today PVs are sold for as little as three dollars per Wp and their efficiencies are steadily increasing. Now that PVs are commercially available and much more affordable, the market for them has grown rapidly. Manufacturers are still st riving to drive down costs while improving efficiency in order to compete with the traditional electric utilities. The less efficient a solar cell, the larger the array need and the higher the co st. The best commercially available PVs tend to operate at fifteen percent efficiency while cheaper arrays are as low as seven percent efficient. The efficiency of a PV array is measured by the percent of the available sunlight it converts into useful energy. In the laboratory, on the other hand, PVs operate at a much higher efficiency. The current commercially available PVs that are prev iously discussed can operate up to twenty four percent efficiency in a labor atory setting. However, institutio ns like the National Renewable Energy laboratory, of Golden Colorado, have devel oped PVs that are over forty percent efficient. These super efficient and very expensive PVs pow er satellites and the Mars Rovers. It is expected that these will one day be commercially available and affordable. Beyond developing their own PV systems and research, the NREL will conduct tests on PV systems from industry partners and manufacturers in order to collect da ta and develop standard s along with testing the performance and durability of the PVs.

PAGE 26

26 Other innovations have ai ded in the expansion of PV use. Thin film PVs use semiconductors that are only a few micrometers thick. These PVs are often put on a flexible substrate that makes them not only versatile but cheaper because less material is required and they still maintain fifteen percent efficienc y. Some manufacturers have incorporated this technology by making thin film PVs that serve as roof shingles. The PVs taking on another function, such as roof shingles or tiles, serve to decr ease overcall cost of a building. Now that shingles are no longer necessary th is could prove the PVs a more cost effective solution. These thin film PVs are also incorporated into buildi ng glazing, facades, and sky lights. Some argue that these attempts diminish the quality of both produc ts, the PVs and the system they are replacing. If these types of systems can be perfected it wi ll go a long way in justifying the cost of a PV array. The most common PVs used today are silicon based cells (Figure 1-2). These provide the most cost effective arrays and commercially they operate at up to fifteen percent efficiency. Figure 1-2. Photovoltaic cell. Cells are connected in module and modules are connected to form panels. A set of panels makes an array. (Source: http://www.storkgears.com/images/hawt.jpg. Last accessed June, 2009).

PAGE 27

27 There are much more efficient cells in the la boratory that utilize indium and gallium as semiconductors, but these are far t oo expensive to compete in the commercial market. Solarbuzz, LLC is a company that produces global reports a nd offers consulting services that follow the solar market worldwide. According to Solarbuzz, current PV array price is $4.61 per watt. This is concurrent with phone survey s done by this researcher to PV array manufacturers. While 2008 prices remained fairly steady at near $4.88, the trend is that ov er time PV modules are dropping in price. Typical PV Array For the purpose of this research a typical PV installation is most appropriate. For a house or a sm all building, PV cells and panels are connected in parallel or series and combined until the desired size and capacity are r eached. The PV panels are mounted often times on the roof of a structure in order not to take up valuable real estate and for more sun exposure. There are several mounting systems and styles of array. Some syst ems are tracking systems that will follow the sun from east to west and at the appropriate a ngle throughout the day. These tracking systems are known as double axis systems. Single axis trackin g systems will either track the Suns angle from the horizon or its movement from east to west. These systems are much more expensive and are not typically used on the roof of a home or even small building. Fixed tilt systems are preferred. A fixed tilt system is faced south wher e it will receive the most sunlight and it is angled based on the latitude coordinate of the system. An array located on a roof at latitude -45 degrees West will be facing south and angled at 45 degrees for maximum sun exposure. Like a small wind turbine, a PV array will produce DC el ectricity and an inverter is necessary to convert to AC. Also, similar to a wind turbine, PV systems can be grid connected and owners can participate in federal and state incentives that include net metering and tax rebates.

PAGE 28

28 Recent Studies While many emerging renewable energy system s have their advantages and drawbacks, it is very difficult to compare the different ener gy resources. Current research is under way and some groups and individuals have already trie d to compare wind and solar energy technologies. For example, due to power output fluctuations, PV integration is more costly than wind at the utility scale (megawatt faciliti es) (Apt and Cartwright, 2007). Detronics Limited conducted a study that includes smaller scale wind and PV comparisons (Detronics, 2006). They set up a wind turbine and PV array and monitored them fo r one year. Because the systems had different power capacities, this study compared the Price per Rated Watt to the price per produced KWh. This study suggests that purchase consider ations should be based on price per produced kWh, and the wind turbine had the advantage ov er the solar array. As the study suggests, performance will vary on the resource available. Therefore, it is very difficult to know what system will outperform the other when it comes to wind turbines and PV arrays. While site specific surveys can be conducted, they are time consuming and very expensive. Several maps and useful tools are readily available and can help determine when winds versus PV applications are appropriate. Tools PVWATTS PVWatts is a calculator developed by the NRELs Electricity, Resources, and Building System s Integration Center. This calculator allows individuals to quickly estimate the performance of hypothetical PV systems (Figur e 2-1). By selecting a physical location, the online program will run a series of monthly and annual power production for the inputted design specifications of the hypothetical model. The user chooses a system size, derate factor (DC to AC conversion), array tilt, array azimuth, trackin g or non tracking, and utili ty cost (Figure 2-2).

PAGE 29

29 After summing hourly production to achieve monthl y and annual energy outputs the calculator will estimate the value of the energy produced based on the chosen locations utility cost. PVWatts Version 2 allows users to select any point in the United States. This is a widely used and accepted estimation tool in the industry and scientific field. FirstLook The Am erican Wind Energy Association has rece ntly awarded the FirstLook prospecting tool with the Commercial Achievement Award. Devel oped by 3TIER, FirstLook is a wind and solar energy assessment tool that allows users to quic kly sample areas in the western hemisphere. An interactive map allows users to select coordina tes and receive wind resour ce data for any location in the western hemisphere (or so lar resource data while in the solar mode). Registered members can receive the basic online package that s hows average annual wind speeds and aggregate global horizontal irradiance avai lable at http://firstlook.3tiergroup.com/. Exte nded datasets are, that include site specific nu mbers and results, are available for purchase for $1,000 and $2,500 for a professional set. The 3TIER group devel oped the wind datasets with 5km resolution. Traditional wind resource maps interpolate wi nd patterns between points while the FirstLook program uses integrated statistical methods via the Numerical W eather Prediction (NWP) models. NWP utilizes simulations of the intera ctions between the atmosphere and the earths surface to create models of wind patterns. The maps are further developed by using techniques such as jet level dynamics and surface level proc esses. This tool is useful for allowing nonexperts to easily receive accu rate estimates of wind speeds throughout the country. For this research, the FirstLook wind prospec ting tool is utilized to estim ate the winds speeds in sampled sites. That gathered data is then run in the wind turbine performance model in order to estimate the annual kWh output of a 10kW wind turbine.

PAGE 30

30 Table 2-1. AC Energy and Cost Savings Site Identification Table 2-2. AC Energy and Cost Savings Results WindCad Turbine Performance Model While there is a simple formula to determine the power output of a wind turbine, a WindCad program will accommodate several factor s to more accurately estimate the turbines performance. Bergey Wind Co. provided this research project with a WindCad Turbine Performance Model for an Excel-S grid tied turbine developed by 3TIER. This performance model accounts for the traditional factors that influence power out put, but it also introduces a City Portland State OR Latitude 45.60N Longitude 122.60W Elevation 12m DC Rating 4.88kW DC to AC Derate Factor0.77 ACRating 3.76kW Array Type Fixed Tilt Array Tilt 45.6N Array Azimuth 205.0N Cost of Electricity 7.2/kWh Station Indentification Month Solar Radiation (kWh/m2/ day) AC Energy (kWh) Energy Value ($) 12.0122316.06 22.5325118.07 33.8342230.38 44.3646233.26 55.3958141.83 65.3855139.67 76.2465246.94 85.658041.76 94.9750236.14 103.6939728.58 111.9519814.26 121.4115610.51 Year3.954965357.48

PAGE 31

31 Weibull calculation. Because wind speeds vary, a Weibull distribution will help model the different variations of wind in a location base d on average wind speeds. This gives a more accurate estimation of potential power output. Figure 2-1. Example of PVWA TTS input data. (Source: http://rredc.nrel.gov/solar/calculators /PVW ATTS/version2/inputv2.cgi?Cell_ i_d_=0204360&Latitude=40.133&longitude =-106.896&State=Colorado&Electric_r =8.188. Last accessed June, 2009).

PAGE 32

32 WindCad Turbine Performance Model BWC EXCEL-S, Grid Intertie Tier-SH305522-BWC Prepared For: Progress Energy Site Location: Okahumpka, FL Data Source: 3Tier FirstLook Date: 6/24/2009 Inputs: Results: Ave. Wind (m/s) = 3.5 Hub Average Wind Speed (m/s) = 3.80 Weibull K = 2 Air Density Factor = 0% Site Altitude (m) = 30 Average Output Power (kW) = 0.59 Wind Shear Exp. = 0.200 Daily Energy Output (kWh) = 14.2 Anem. Height (m) = 20 Annual Energy Output (kWh) = 5,177 Tower Height (m) = 30 Monthly Energy Output = 431 Turbulence Factor = 0.0% Percent Operating Time = 50.9% Figure 2-2. Example of WindCad Turbine Pe rformance Model. Supplied by Bergey Wind Company and developed by 3TIER. Source: http://www.bergey.com/

PAGE 33

33 CHAPTER 3 METHODOLOGY Experimental Method Within the realm of this research, two typical wind and solar power generating systems were modeled and placed in diffe rent regions of the United States. Both systems are typical for a home or small building. On average, U.S. fa milies use nearly 10,000 kWh per year to power their homes. Energy efficient homes tend to require half of that (DOE, 2009). The models have the capacity to power single family dwellings that are energy conscious homes or drastically contribute to individual households and small building energy demands. The Wind Resources Map (Figure 3-1) and So lar Radiation Map (Fi gure 3-2) provided by the DOE and the National Renewable Energy La boratory are used to define the geographic locations where the wind and solar models will be tested. The lower 48 states of the U.S. have, essentially, three different radi ation regions and five different wind resource regions. The two energy models will be run in overlapping regi ons in order to compare their energy production based on the cost of the electric utility in th at region. Based on the DOEs Wind Resource Map, winds are concentrated in the Midwest, while other regions have vi rtually no useful wind resource contributions. Thus, the sample points are also concentrated in the Midwest narrowing the focus of this study. In order to test the solar m odel, PVWATTS V2 is utilized to calculate the annual energy production of the photovoltaic system. Then, utilizing the Excel based WindCAD Turbine Performance Model, the wind turb ines performance is tested based on capacity and average annual wind velocity found from FirstLook wind datase ts paired with the re gional utility electric cost. The important data collected is the va lue and kWh of energy production of each system within the region. These numbers can be compared to investigate if there is a difference, thus

PAGE 34

34 accepting or failing to accept the hypothesis that there is a difference in the value of energy produced regionally between wind and solar genera tors. These findings are intended to bring us one step closer to helping select what renewa ble system to utilize based on our geographic location that falls within the different zones on the DOEs Wind Resource and Solar Radiation maps. Figure 3-1. In color, wind power classificat ion can be seen and mapped. (Source: http://www .nrel.gov/wind/systemsintegration/images /home_usmap.jpg. Last accessed June, 2009).

PAGE 35

35 Figure 3-2. This map shows three different solar radiation regions in the Midwest designated by three different color shaded areas. (Source: http://rredc.nrel. gov/solar/old_data/ nsrdb/redbook/atlas/serve.cgi. Last accessed June, 2009). Models Photovoltaic Array Model The proposed PV model used in this study is a 10kW system faci ng south with the tilt angle defined by the latitude of the test site. A derate factor of 0.77 is used and the utility cost is also defined by the location for the test site. PV WATTS is automatically set the parameters of this system based on the coordinate inputs. An example can be seen in the Figure 3-2. It is assumed that in this application the PV array is grid connected. The cost of a system such as this is quoted as $60,000 (installed) by Solar Impact, Inc.

PAGE 36

36 Wind Turbine Model The proposed wind turbine model used in this study, provided by Bergey Wind Co., is a 10kW turbine (BWC EXCEL-S, Grid Intertie) mounted on a 30 meter tower. This system is also grid connected. The system is sold as a package where turbine, tower and wiring kit equipment cost is $43,645. Individually, the turbin e cost $29,500 and the tower starting cost is 12,900 dollars, tower kit cost $1,245 and an appr opriate inverter costs $2,495. Bergey Wind indicates that installation cost will be in the range of $6,000 (s elf installed) to $15,000 (certified dealer installed and expensive permitting). If installation cost is a ssumed as $12,000 dollars due to certified installation and average permitting cost then the systems total installed cost is $58,140.

PAGE 37

37 CHAPTER 4 RESULTS AND ANALYSIS Results The collected data (F igures E-1 through E-3) is organized by sampled sites within the three different solar radiation zones. The following is a description of the information in these figures. First recorded were the 44 differe nt data points. Each data point is assigned a site number in the Site column for referencing purposes. A phys ical description, noted as Descriptions, indicates the state in which the coordinates are located. The latitude a nd longitude coordinates are noted next to give a specific location of th e sample point. These ar e labeled Lat/Lon. The next column indicates the elevati on of the site, in meters, above s ea level. This information aided in determining the wind energy poten tial due to the fact that elevation influences air density and thus the production of the wind turbine. Followi ng elevation are the so lar and wind classes of each site. Solar class is designated by the research er based on one of the three different levels of solar radiation labeled on the DOEs annual radi ation map. The wind classes are indicated on the Wind Resource Energy Map provided by the DOE. The wind classifications are separated by color and are described as follows: Class 3 (yel lowfair), Class 4 (p ink-good), Class 5 (purpleexcellent), Class 6 (red-outstanding) and Class 7 (blue superb). The next column of data is the utility cost, labeled Util. Cost (cents). This cost is provide d by PVWATTS based on the input coordinates. Following utility co st, is the sampled wind speed in m/s at each site. The FirstLook wind prospecting tool supplied this estimated da ta. The value of the annual production for the PV model, in dollars, follows the sampled wind speeds. This column is labeled Value of Annual Solar Production ($). This value is also calculated by PVWATTS based on the program parameters. PVWATTS will also provide the data for the next column, Annual kWh produced (solar), or this value can be calculated by divi ding the Value of Annua l Solar Production ($)

PAGE 38

38 by the Utility Cost. The Val ue of Annual Wind Production ($) is the next column of data. These values are found after determining the column to the right, Annual kWh produced (wind). The kilowatt hours produced by the wind turbine are determined by locating the latitude and longitude points of the site on the FirstLook prospecting tool. Average annual wind speeds are then estimated and plugged into the Wind CAD program, along with the other determining factors noted in the Research Methods section of this paper, and the outpu t is the estimated kWh produced annually. Using the cost of the utility, the value of t hose produced kilowatt-hours is then backed into, supplying the data in the V alue of Annual Solar Pr oduction ($) column. The final two columns are the Annual Return on Inve stment for the PV array model and the wind turbine model, respectively. This value is a percen t, and is determined by dividing the Value of Annual Production by the initial investment on the model. Sampling Organization The raw data tables (Figure E-1, Figure E-2, and Figure E-3) are organized by solar classification. Coordinates falling in the weakes t of the solar radiat ion zones, solar radiation zone one, are paired with wind power classificati on zones first in ascending order (Fair-Superb, weakest to strongest, three to seven). This is the typical organization for e ach data set. The first 15 sample points fall within solar radiation zone 1, the second 15 points ar e solar radiation zone 2, and the final 14 points are solar radiation zone 3. This type of organization allows the research to exhibit trends within each different pairing of wind and sola r resource classifications. Also, separating the data by solar zones allows for qui ck determination of th e performance of two models within the different zones. Finally, due to the fact that the data is organized into different solar radiation zones, the variable of interest is the wind velocity. With in each solar radiation zone the PV model should have consistent results due to the invariability of solar resource. However, within these zones the

PAGE 39

39 different wind classifications ar e sampled leading to highly varied wind speeds. By plotting the sought after data against wind velocities, the pe rformance of the two models can be compared and contrasted based on resource availability. Solar Radiation Zone One Overall performances : Within the first set of data poi nts, solar kilowatt-hour production ranges from 11119.02kWh to 14205.94kWh with an average production of 13023.86kWh (Table A-1). There is little variability, as the solar class is consistently solar radiation zone one. The wind turbine model produced kilowatt-hours in the range of 8991kWh to 21652kWh. The average production of the wind turbine model is this first set of data is 16282.86kWh. The value of the kWhs produced is dependent on the cost of utility in the corres ponding site location. For the PV model these values ranged from $751.09 to $1,205.72 and had an average of $1,014.92. For the wind turbine model the production values ranged from $587.53 to $1819.25 and had an average of $1,261.06. Sampled wind speeds within this zone had a minimum of 4.4 m/s and a maximum of 7.5 m/s. The average wind speed was 5.63 m/s. Trends: Plotting production over varying wind speed s elicits the trends within the different solar zones (Figure A-1). For Solar Radi ation Zone 1 the PV mode l displays a relatively flat line as wind speeds increase. This is expected as the solar radiation has little variance within the same zone. The wind turbine, however, has a positive sloping line corresponding to improved performance as wind speeds increase. The produc tion value graph (Figure A-2) shows a similar trend with the PV model displaying a relatively flat line and a positively sloping line representing the wind turbine model. As wi nd speeds increase the production value typical increases for the wind turbine model while the PV model does not exhibit improved value over increasing wind speeds. There are slight variances w ithin each model due to different utility cost

PAGE 40

40 at each sampled site. The cost of electricity with in the region will determ ine the exact value of the energy produced. Break-even point: As seen by the trend lines and pl otted production in Figure A-1, the intersection of the two plotted lines represents th e point at which the wind turbine model starts producing more electricity than the PV model. Th e point is represented by a wind velocity. In Solar Radiation Zone 1, the PV model outperforms the wind turbine model at the lowest sampled wind velocities. At 5.09 m/s the two performance lines intersect. Therefore, at this point the wind and PV model have similar performance outputs, and thus similar production value. Any wind speeds above this point will allow the turbine model to generate more electricity perform better than the PV model. Production value: The production value graph (Figure A-2) displays the same break-even point as the performance graph. This graph shows exactly how much better or worse each model is performing compared to each other based on the value of the electricity they are producing at different wind speeds. While so lar production value varies by less than $500 a year the wind turbines production values range from $587.53 to $1819.25. This is a difference of $1231.72 a year. Return on investment: When the PV array performs better than the wind turbine the percent annual return on investme nt typically is better due to the fact that the systems are very close in cost and each model is tied to the same utility cost within the sampled sites. This is also true for the wind turbine when it outperforms the PV array. Sin ce the wind turbine is over $1000 cheaper it will always have a better return on investment when outperforming the PV array. In Solar Radiation Zone 1 (Figure A3) it is apparent that after the first three lowest sampled wind speeds the turbine has a higher annu al percent return on investment for the rest of the sites at

PAGE 41

41 higher wind speeds. It is also apparent in this solar zone that as wind speeds increase, so does the difference between the annual percent return on investment between the two models with the same sampled site. Solar Radiation Zone Two Overall performance: W ithin this set of data poin ts, solar kilowatt-hour production ranges from 14008.99kWh to 15703.97kWh with an average production of 14895.66kWh. Again, there is little variability within this set of solar data, as the solar class is consistently solar radiation zone two, but this zone does outperfor m Solar Radiation Zone 1 as expected. The wind turbine model produced kilowa tt-hours in the range of 17350kWh to 24989kWh. The average kWh production of the wind turbin e model in this set of data is 20115.13kWh. The range of production values for the PV model is $937.96 to $1,593.88 with an average production value of $1,366.99. The wind turbine model produced an av erage electricity value of $1,822.69 and ranged from $1,395.30 to $2,204.34. The average sample d wind velocity for this region was 6.33 m/s and ranged from 5.70 m/s to 8.15 m/s. Trends: The PV model had a very consistent pr oduction of kWhs in this solar radiation zone. Due to a very small range of production th e slope of the line is nearly zero. This flat horizontal line represents th e steady and unvarying production of the PV model in Solar Radiation Zone 2. The line in Figure B-1 repres enting the wind turbine models performance is slightly positively sloped. As wind speeds increa se so does the production performance. Again, the range of production performance for the wi nd turbine model is smaller than in Solar Radiation Zone 1, leading to less varied results and a smaller sloping line. This zone does not show the increasing production values as wind speeds increase (Figure B-1). This is due to varied cost of the electric utility in different sites. The site with higher wind speeds must have

PAGE 42

42 had lower energy cost thus lead ing to production value decreasing as wind speeds improve. This phenomenon occurs with cost not production in kWh. Break-even point: Within this set of data for Solar Radiation Zone 2 (Figure B-1) there is no break-even point. From the lowest sampled wind velocities to the highest sampled wind velocities the wind turbine model constantly outperforms the PV array model. However, the mathematical break-even point for this set of data by extending the data would be 4.97 m/s. Within this zone, this break-even poin t occurs at a lower wind velocity. Production value: Production values for the PV array model remain relatively consistent throughout this zone. In sites with higher wi nd speeds the production value for the PV model fell, but it also fell for the wind turbine model. Again, production of the kWhs did not fall but the corresponding cost of electricity must have been less than the ot her sampled sites that had lower wind speeds. While production value can be a usef ul indicator, it is important to note that production value is relative to the si tes cost of electric utility. Return on investment: In this zone the Annual Percent Return on Investment is always higher for the wind turbine model (Figure B-3). Ho wever, the same trends from Solar Radiation Zone 1 are not present. As wind speed increas e there is not the same trend of increasing difference between the return on investment as wind velocities increase. In this zone some of the highest Annual Percent Returns on Investment occurred at the mid-range of sampled wind velocities. The varying cost of utility could play a role in this phenomenon. Solar Radiation Zone Three Overall performance: This last set of data represents the highest and strongest solar radiation zone. Once again, the PV model perform ance improve d. The range of solar power production is 15428.97kWh to 16692kWh. The average performance of the PV model in this section is 16006.22kWh. As expect ed, the PV model relying on th e solar resource improved as

PAGE 43

43 the solar radiation zone improved. The wind turb ine model produced kilowatt-hours in the range of 8160kWh to 24452kWh. The average kWh production of the wind turbine model in this set of data is 17834.29kWh. Again, the value of the kWhs produced is dependent on the cost of utility in the corresponding site location. For the PV model these values ranged from $1,175.57 to $1,858.08 and had an average of $1,567.73. For the wind turbine model the production values ranged from $810.53 to $2,581.64 and had an averag e of $1,645.49. Sampled wind speeds within this zone had a minimum of 4.45 m/s and a maxi mum of 7.05 m/s. The average wind speed was 5.85 m/s. Trends: As with the other solar radiation zones this zone produced another flat line for the PV model production (Figure C-1). The consistent radiation zone led to a small range of production for the PV model across the different sampled sites in Solar Radiation Zone 3. The wind turbine however, has a positive slope with less production at lower wind speeds of 4.45 m/s up to much higher production of energy at 7.05 m/s. The plotted production values for this set of data resemble that of Solar Radiation Zone 1. The break-even point th at exists in the kWh production can be seen in the energy production value (Figure C-2). Also, higher winds speed are correlated with a higher production value in this zone. Break-even point: In Solar radiation Zone 3, the plot ted lines (Figure C-1) intersect at roughly 5.74 m/s. This break-eve n point shows the wind velocity at the PV model and wind turbine model have the same energy output. This break-even point has increased from Solar Radiation Zone 1 by 0.74 m/s. This represents an improved perf ormance of the PV array model as compared to lower solar radiation zones. Production value: The production values are plotted ag ainst increasing wind velocities in Figure C-2. This graph shows a greater degree of variance among the PV model for production

PAGE 44

44 values than the other sampled zones. This would suggest a greater degree of variance in either the cost of the utility due to the consistency of the production of kWhs in Figure C-1. The wind turbine model shows increasing produc tion value and wind speeds increase. Return on investment: This zones Annual Return on Inve stment looks more like that of Solar Radiation Zone 1 (Figure C-3). At the lower sampled wind speeds the PV array has a higher percent return, but then as wind speeds increase the wind model eventually takes over and exhibits a higher Annual Return on Investment. In this zone, the first seven sampled sites, wind velocities 4.45 to 5.55 m/s, show the PV array performing better. Again, some lower wind speeds in this zone, where the turbin e model outperforms the PV array, show better Annual Return on Investment than higher wind velocity sampled sites. It is assumed that the higher cost of utility give the energy a higher production value a nd thus a great return on investment. Overall Overall performance: Across all s olar radiation zones wind speeds varied from 4.40 m/s to 8.15 m/s with an average of 5.94 m/s (Table D-1). This led to wind turbine production that ranged from 8160.00 kWh to 24989.00 kWh with an average of 19946.35 kWh. This is higher than the overall average PV production of 14641.91. The PV performance ranged from 11119.02kWhs to 16692.00kWhs. Trends: There are a few trends that exist in th e overall numbers for this experiment ( Figure D-1 and Figure D-2). It is typical for energy produc tion and the value of energy produced to increase as wind velocities increa se. Across all wind velocities the PV models performance varies only slightly and does not stray far from the average. The wind turbines performance is seen as a positively sloping line with drastic improvement from the lowest sampled wind speeds to the highest sampled wind speeds. The production value graph (Figure D2) shows similar trends but represents the value of the energy produced in dollars.

PAGE 45

45 Break-even point: The overall break-even point is determined in excel by finding the xintercept of the data numbers. The overall br eak-even point was determined to be 5.44 m/s (Figure D-1). Production value: Across all zones, annual energy produced by the PV model was valued from $751.09 to $1,858.08. The average value of annual energy produced by the PV model was $1,316.55. The value of the annual energy produced by the wind turbine m odel ranged from $587.53 to $2,581.64. The average annual energy value for this overall set of data was $1,576.41. Plotted production value versus wind velocities (Figure D2) show the difference in the value of the energy produced at different wi nd speeds. This information is contingent upon the utility cost within each sampled site. Return on investment: After running each model in the sampled geographic locations, the wind turbine overall had a better rate of return. The overall average annual rate of return on solar energy systems was 2.19 %. The average annual rate of return on wind systems was 2.76%. The PV array rate of return c onsistently increased as solar ra diation zones improved from one to three. The average rate of return varies within the different sola r radiation zones and within the different wind velocities. While the rates of return vary due to va ried utility cost, overall it is higher for the wind turbine m odel than the PV model. Discussion Solar Radiation Zone 1 While m any higher wind classes had higher wind production, the final two superb classifications appear to have under-performed based on the higher wind speed potentials. This indicates that the wind model placed in sites loca ted within the lower wind speed classifications are sometimes performing better than the sites with higher wind speed classi fications. This is not necessarily consistent with expected results, but by plotting performance against wind speeds

PAGE 46

46 this negates these inconsistencies. Therefore, the wind classification assigned by the DOE carries less precedence and the actual wind ve locities can be used to make determinations and decisions when selecting and wind turbine. As expected the PV model had consistent resu lts due to the fact the solar radiation zone remains consistent. This led to the flat performance lines in the figures. Also, as wind speed increases so does the wind turbine performance lead ing to a positively sloped line in the figures. By graphing the results the br eak-even point is determined to be 5.09 m/s for this zone. The average wind velocity in this zone is above th at point at 5.63 m/s leading to an overall better performance of the wind turbine compared to the PV array in Solar radiation Zone 1. Solar Radiation Zone 2 As with the previous zone, perform ance was plotted against ascending sampled wind velocities. The PV array maintained relatively consistent production numbers and a small range of varying performance. Plotting the wind tu rbines performance, based on sampled wind velocities showed that in this radiation zone, the wind turbine model consistently outperformed the PV array model. A break-even point is not seen on the graph because the lines do not intersect. However, the break-even point can be mathematically extrapolated. The results showed this point to be 4.97 m/s which is very similar to the 5.09 m/s from solar radiation zone one. This suggests that the PV array did not improve enough in performance to increase the break-even point. The Production Value and Annual Return on Inve stment figures do not exhibit trends as clear in this set of data. However, by viewing the raw data, it is clea r that there is a wide range of utility cost among the sampled site s. These different utility cost will affect the shapes and trend lines of the plotted graphs. The Annual Production Value of the models in this zone (Figure B-2) shows that there is a consistent higher production value of electr icity for the wind turbine model.

PAGE 47

47 While overall Annual Return on Investment is impor tant, the graphs (Figure B-3) do elicit an important trend. Solar Radiation Zone 3 The data, and resulting visual representations, of Solar radiation Zone 3 are sim ilar to the data set of Solar Radiation Zone 1. The PV model has a consistent production value, higher than zones 1 and 2, and the wind turbine performance in creases as wind velocities increase. The lower wind speeds in this zone have a lower production than the PV array up until 5.74 m/s (the breakeven point). As expected, this break-even point is higher than z ones 1 and 2 due to the increased performance of the PV array model. In th is scenario, the PV array improved enough in performance to increase the break-even point meaning that stronger winds are needed to keep up with the performance of the PV array model. The Annual Production Value and Annual Return on Investment acted similar to Solar Radiation Zone 1 again in this set of data. W ith increasing wind velocities, the margin of the difference in the value of electric ity produced also increases. This would suggest that utility cost are similar enough to not make a huge impact on annual return or production values. Summary The overall perform ance of the two models (Appe ndix D) brings to light the general trends and findings of the experiment. For the sampled sites, it is clear that increasing wind speeds generate enough energy for the wi nd turbine to eventually outperf orm the PV model at a breakeven point of 5.44 m/s (Figure D-1). While th e PV model improves across ascending solar radiation zones, the wind turbine model improves more dramatically over the sampled increasing wind velocities. Only the bottom 20% of sample d sites, based on wind velocity, had the PV model perform better than the wind turbine model.

PAGE 48

48 The overall Annual Production Value and Annual Return on Invest have similar trends in that they show the wind turbine model havi ng increasing Production Value and Return on Investment as the wind velocities increase (Figur e D-2). The different cost of the utility at different sites affects these numbers, but the gene ral trends are still ev ident when the overall numbers are combined in the overall tables a nd figures. The greater performance of the wind turbine model at higher wind speeds, combined with the cheaper cost contributes to these results (Figure D-3).

PAGE 49

49 CHAPTER 5 CONCLUSIONS AND SUGGESTED RESEARCH Conclusions The origin al problem statement notes that it is difficult to choose between two renewable energy systems when both renewable energies are available. This study focused on wind and solar renewable resources. Because the U.S. has geographic areas of varying wind and solar resources the choice becomes even more difficult. The experimental design attempted to pair two models, a PV array model and a wind turbine mode l, in different geographic location of varying wind and solar resources. The performance of th e two models was compared, and based on what zone or classification of resource the models fell in, it could be de termined what scenarios suited the different renewable resource systems. In order to make comparisons, the collected performance data for bot h the PV array model and the wind turbine model was plotted against wind velocity. This plot allowed the researcher to note a break-even point that indicates at what wind speed, throughout different solar radiation zones, the wind turbine model would have a high er production output than the PV model. While site specifics such as utility cost and Annual Return on Investment were measured, the most significant contribution of this research relies on the break-even point data. The results of this study sugge st that where high wind resources are available, wind classes three to seven based on the DOEs wind resour ce maps, wind energy is more often a better choice of renewable resour ce than solar energy based on a typical system installation represented by the two models used in this research. While the DOEs maps were helpful in selecting areas with wind resources and overlapping areas among the different solar radiation zones, the implications of various performances were seen when they were plotted against the different wind velocities.

PAGE 50

50 As previously stated, the major contribution of this research is the indication of when the wind turbine model outperformed the PV model. The indicator, in this case, is the break-even point. The break-even point can be seen in each solar radiation zone or throughout all sampled sites in the research. The research that took place to perform this experiment indicates that wind speeds are not the only factor when choosing be tween a wind turbine and PV array. Items such as: site restrictions, permitting, and incentives that change the upf ront cost of renewable systems play a major role in system selection. Suggested Research While this study only m odeled two energy system s it is also not unreasonable to believe that further research should be conducted to verify or contend this information. Suggestions for further research include sampling areas based on population density. Sample s for this study were selected solely based on overlapping wind a nd solar resource regions. Adding the population factor would help determine what energy syst ems should be utilized where individuals are already populated and discard any geographic location that is not f easible for system integration. Also, more data points tend to illicit trends better. Continuing to sample more locations will increase the validity of results. The method of sampling in this experiment restricts itself to overlapping resource zones near and within the Midwest. Future sampling could take place in more areas of interest or across the United Stat es. Or future sampling could attempt to locate more areas that have overlapping resource zones and available resource data.

PAGE 51

51 APPENDIX A SOLAR RADIATION ZONE 1 Table A-1. Solar Radiation Z one 1 Ranges and Averages. Figure A-1. Annual production (kW h) vs. wi nd speed for Solar Radiation Zone 1. 0.00 5000.00 10000.00 15000.00 20000.00 25000.00 4.4 0 4.7 0 4.8 0 4.8 0 5.3 0 5.5 0 5.55 5.75 5.8 0 5.9 0 5.9 0 5.9 0 6.15 6.45 7.5 0 Models' kWh Productio n Wind Velocity (m/s) Solar Radiation Zone 1 Annual kWh produced (PV array) Annual kWh produced (turbine)

PAGE 52

52 Figure A-2. Annual Production Value vs. wi nd speed for Solar Radiation Zone 1. Figure A-3. Annual Return on Invest ment. Solar Radiation Zone 1. 0 200 400 600 800 1000 1200 1400 1600 1800 20004.40 4.70 4.80 4.80 5.30 5.50 5.55 5.75 5.80 5.90 5.90 5.90 6.15 6.45 7.50Value of Energy Production $Wind Velocity (m/s) Solar ZoneRadiation 1 Production Value Annual Solar Production ($) Annual Wind Production ($) 0.00 1.00 2.00 3.00 4.00 4.404.704.804.805.305.505.555.755.805.905.905.906.156.457.50% Annual ReturnWind Velocity m/s Annual Return on Investment Solar Radiation Zone 1 Annual Return on Investment (solar) Annual Return on Investment(wind)

PAGE 53

53 APPENDIX B SOLAR RADIATION ZONE 2 Table B-1. S olar Radiation Zone 2 Ranges and Averages. Range Average Sampled Wind Velocity (m/s) 5.70-8.15 6.33 Value of Annual Solar Production ($) 937.96-1593.88 1366.99 Annual kWh Produced (solar) 14008.99-15703.97 14895.66 Value of Annual Wind Production ($) 1395.30-2204.34 1822.69 Annual kWh Produced (wind) 17165 24989 20115.13 Figure B-1. Annual production (kWh) vs. wi nd speed for Solar Radiation Zone 2. 0.00 5000.00 10000.00 15000.00 20000.00 25000.00 30000.00 Models' kWh ProductionWind Velocity (m/s) Solar Radiation Zone 2 Annual kWh produced (PV array) Annual kWh produced (turbine)

PAGE 54

54 Figure B-2. Annual Production Value vs. wi nd speed for Solar Radiation Zone 2. Figure B-3. Annual Return on invest ment. Solar Radiation Zone 2. 0 500 1000 1500 2000 25005.70 5.70 5.70 5.75 5.80 5.95 6.10 6.10 6.25 6.35 6.50 6.80 6.85 7.25 8.15 Value of Energy Production $Wind Velocity (m/s) Solar Zone 2 Model Production Value Annual Solar Production ($) Annual Wind Production ($) 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 5.705.705.705.755.805.956.106.106.256.356.506.806.857.258.15% Annual ReturnWind Velocity m/s Annual Return on Investment Solar Radiation Zone 2 Annual Return on Investment (solar) Annual Return on Investment(wind)

PAGE 55

55 APPENDIX C SOLAR RADIATION ZONE 3 Table C-1. S olar Radiation Zone 3 Ranges and Averages. Range Average Sampled Wind Velocity (m/s) 4.45-7.05 5.85 Value of Annual Solar Production ($) 1175.57-1858.08 1567.73 Annual kWh Produced (solar) 15428.97-16692.00 16006.22 Value of Annual Wind Production ($) 810.53-2581.64 1645.49 Annual kWh Produced (wind) 8160.00-24452.00 16744.93 Figure C-1. Annual production (kWh) vs. wi nd speed for Solar Radiation Zone 3. 0.00 5000.00 10000.00 15000.00 20000.00 25000.00 30000.00 4.454.955.055.556.456.857.05Models' kWh ProductionWind Velocity (m/s) Solar Radiation Zone 3 Annual kWh produced (PV array) Annual kWh produced (turbine)

PAGE 56

56 Figure C-2. Annual Production Value vs. wi nd speed for Solar Radiation Zone 3. Figure C-3. Annual Return on Invest ment. Solar Radiation Zone 3. 0 500 1000 1500 2000 2500 30004.45 4.85 4.95 4.95 5.05 5.25 5.55 6.2 6.45 6.45 6.85 6.85 7.05 7.05 Value of Energy Production $Wind Velocity (m/s) Solar Zone 3 Model Production Value Annual Solar Production ($) Annual Wind Production ($) 0.00 1.00 2.00 3.00 4.00 5.00 4.454.854.954.955.055.255.556.26.456.456.856.857.057.05% Annual ReturnWind Velocity m/s Annuual Return on Invest Solar Radiation Zone 3 Annual Return on Investment (solar) Annual Return on Investment(wind)

PAGE 57

57 APPENDIX D OVERALL RESULTS Table D-1. All Zones Ranges and Averages. Range Average Sampled Wind Velocity (m/s) 4.40-8.15 5.94 Value of Annual Solar Production ($) 751.09-1858.08 1316.54667 Annual kWh Produced (solar) 11119.02-16692.00 14641.91 Value of Annual Wind Production ($) 587.53-2581.64 1576.41 Annual kWh Produced (wind) 8160.00-24989.00 19946.35 Figure D-1. Overall Annual Production (kWh) vs. wind speed for all Solar Radiation Zones. 0.00 5000.00 10000.00 15000.00 20000.00 25000.00 30000.004.40 4.80 4.95 5.25 5.55 5.70 5.75 5.90 5.95 6.15 6.35 6.45 6.85 7.05 7.50 Models' kWh ProductionWind Velocity (m/s) All Solar Radiation Zones Annual kWh produced (PV array) Annual kWh produced (turbine)

PAGE 58

58 Figure D-2. Overall Annual Production Value vs. wind speed for all Solar Radiation Zones. Figure D-3. Overall Annual Return on I nvestment. All Solar Radiation Zones. 0 500 1000 1500 2000 2500 30004.40 4.80 5.05 5.55 5.70 5.80 5.95 6.2 6.45 6.85 7.05 Value of Energy Production $Wind Velocity (m/s) All Solar Zones Model Production Value Annual Solar Production ($) Annual Wind Production ($) 0.00 1.00 2.00 3.00 4.00 5.004.40 4.70 4.80 4.95 5.05 5.30 5.55 5.70 5.70 5.75 5.80 5.90 5.95 6.10 6.2 6.35 6.45 6.50 6.85 6.85 7.05 7.50 % Annual ReturnWind Velocity m/s Annual Return on Investment All Sites Annual Return on Investment (solar) Annual Return on Investment(wind)

PAGE 59

59 APPENDIX E RAW DATA

PAGE 60

60 Figure E-1. Raw data for Solar Radiation Zone 1.

PAGE 61

61 Figure E-2. Raw data for Solar Radiation Zone 2.

PAGE 62

62 Figure E-3. Raw data for Solar Radiation Zone 3.

PAGE 63

63 APPENDIX F SITE SPECIFIC RESULTS Figure F-1. Site Specific M odel Perf ormances. Site 1. Figure F-2. Site Specific M odel Performances. Site 2. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 1 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 2 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 64

64 Figure F-3. Site Specific M odel Performances. Site 3. Figure F-4. Site Specific M odel Performances. Site 4. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 3 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 4 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 65

65 Figure F-5. Site Specific M odel Performances. Site 5. Figure F-6. Site Specific M odel Performances. Site 6. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 5 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 6 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 66

66 Figure F-7. Site Specific M odel Performances. Site 7. Figure F-8. Site Specific M odel Performances. Site 8. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 7 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 8 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 67

67 Figure F-9. Site Specific M odel Performances. Site 9. Figure F-10. Site Specific Model Performances. Site 10. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 9 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 10 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 68

68 Figure F-11. Site Specific Model Performances. Site 11. Figure F-12. Site Specific M odel Performances. Site 12. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 11 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 12 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 69

69 Figure F-13. Site Specific Model Performances. Site 13. Figure F-14. Site Specific Model Performances. Site 14. 0 5000 10000 15000 20000 25000 30000 35000 0246810kWh ProductionWind Velocity m/s Site 13 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 14 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 70

70 Figure F-15. Site Specific Model Performances. Site 15. Figure F-16. Site Specific Model Performances. Site 16. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 15 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 16 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 71

71 Figure F-17. Site Specific Model Performances. Site 17. Figure F-18. Site Specific Model Performances. Site 18. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 17 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 18 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 72

72 Figure F-19. Site Specific Model Performances. Site 19. Figure F-20. Site Specific Model Performances. Site 20. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 19 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 20 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 73

73 Figure F-21. Site Specific Model Performances. Site 21. Figure F-22. Site Specific Model Performances. Site 22. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 21 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 22 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 74

74 Figure F-23. Site Specific Model Performances. Site 23. Figure F-24. Site Specific Model Performances. Site 24. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 23 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 24 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 75

75 Figure F-25. Site Specific Model Performances. Site 25. Figure F-26. Site Specific Model Performances. Site 26. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 25 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 26 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 76

76 Figure F-27. Site Specific Model Performances. Site 27. Figure F-28. Site Specific Model Performances. Site 28. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 27 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 28 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 77

77 Figure F-29. Site Specific Model Performances. Site 29. Figure F-30. Site Specific Model Performances. Site 30. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 29 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 0246810kWh ProductionWind Velocity m/s Site 30 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 78

78 Figure F-31. Site Specific Model Performances. Site 31. Figure F-32. Site Specific Model Performances. Site 32. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 31 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 32 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 79

79 Figure F-33. Site Specific Model Performances. Site 33. Figure F-34. Site Specific Model Performances. Site 34. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 33 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 34 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 80

80 Figure F-35. Site Specific Model Performances. Site 35. Figure F-36. Site Specific Model Performances. Site 36. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 35 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 36 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 81

81 Figure F-37. Site Specific Model Performances. Site 37. Figure F-38. Site Specific Model Performances. Site 38. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 0246810kWh ProductionWind Velocity m/s Site 37 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 38 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 82

82 Figure F-39. Site Specific Model Performances. Site 39. Figure F-40. Site Specific Model Performances. Site 40. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 39 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 40 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 83

83 Figure F-41. Site Specific Model Performances. Site 41. Figure F-42. Site Specific Model Performances. Site 42. 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 41 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 40000 0246810kWh ProductionWind Velocity m/s Site 42 Model Performance Site Specific Turbine Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 84

84 Figure F-43. Site Specific Model Performances. Site 43. Figure F-44. Site Specific Model Performances. Site 44. 0 5000 10000 15000 20000 25000 30000 35000 0246810kWh ProductionWind Velocity m/s Site 43 Model Performance Site Specific Turbine Performance Curve Sampled Site PV Performance Sampled Site Turbine Performance 0 5000 10000 15000 20000 25000 30000 35000 0246810kWh ProductionWind Velocity m/s Site 44 Model Performance Site Specific Turbine Performance Curve Sampled Site PV Performance Sampled Site Turbine Performance

PAGE 85

85 LIST OF REFERENCES Apt and Curtwright (2007). The Spectrum of Power from Utility-Scale Wind Farms and Solar Photovoltaic Arrays. John W iley & Sons, Ltd. Burton, et al. (2001). Wind Energy Handbook. Wiley & Sons. Deltonics Limited. (2006). Renewable Energy Comparison of Wind and Photovoltaic Solar Retrieved May 14, 2009, from http://www.detronics.net/wind_solar.pdf Lund. P. (2009). Effects of energy policies on industry expansion in renewable energy. ScienceDire ct.,134 (1), 53-64. Mathew, S. (2006). Wind Energy Fundamentals, Resource Analysis and Economics. Springer Berlin Heidelberg National Renewable Energy Laboratory. (January 2001). NREL/CP-500-29164 Geographic Information Systems in Support of Wind Energy Activities at NREL Retrieved April 15, 2009, from http://www.windpoweri ngamerica.gov/pdfs/gis_nrel.pdf U.S. Department of Energy. (May 2008). 20% Wind Energy Diversify ing Our Energy Portfolio and Addressing Climate Change. Retrieved May 1, 2009, from www.eere.energy.gov/windandhydro U.S. Departm ent of Energy. (July 2008). 20% Wind Energy by 2030 Increasing Wind Energys Contribution to U.S. Electricity Supply DOE/GO-102008-256. Retrieved May 1, 2009, from http://www.windpoweringame rica.gov/pdfs/20_percent_wind_2.pdf U.S. Department of Energy. (May 2008). Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007 Primary authors Ryan Wiser Lawrence Berkeley National Laboratory Mark Bolinger Lawrence Be rkeley National Laboratory DOE/GO-1020082590. Retrieved February 10, 2009, from http://e etd.lbl.gov/EA/emp/reports/lbnl-275e.pdf U.S. Department of Energy. (August 2007). Wind Energy Multiyear Program 2007-2012 DOE/GO-102007-2451. Retrieved April 11, 2009, from http://www1.eere.energy .gov/windandhydro/pdfs/40593.pdf U.S. Department of Energy. (January 2008) Federal Grant Fully Funds Small Turbine Installation at Maine Senior H ousing ComplexJanuary 2008 DOE/GO-102008-2508. Retrieved May 1, 2009, from http://www.windpoweringamerica.gov/pdfs/sm all_wind/2008/grant_senior_housing.pdf U.S. Department of Energy. (March 2005). Small Wind Electric Systems A U.S. Consumers Guide Produced for the U.S. Department of En ergy by the National Renewable Energy Laboratory, a DOE national laboratory DOE/GO-102005-2095 Retrieved April 19, 2009, from http://www.windpoweringamerica.gov/pdf s/sm all_wind/small_wind_guide.pdf

PAGE 86

86 U.S. Department of Energy. (March 2009). Energy Efficiency and Renewable Energy: Wind and Hydropower Technologies Program-Small Wind Retrieved February 21, 2009, from http://www.windpoweringamerica.gov/small_wind.asp U.S. Department of Energy. (May 2009). Energy Efficiency and Re newable Energy: Wind and Hydropower Technologies Program Retrieved February 12, 2009, from http://www.windpoweringamerica.gov/ wind_installed_capacity.asp Wilson, A., & Yost, P., (2001) Building-Integr ated Photovoltaics: Putting Power Production Where It Belongs. Environmental Building News. March 1, 2001.

PAGE 87

87 BIOGRAPHICAL SKETCH Joshua W alker hails from Tampa, Florid a where he attended Jesuit High School. After graduation he proceeded to the University of Florid a in the city of Gainesville. There he earned a bachelors degree in health science with a focu s on premedical studies. After shifting career paths in 2007, Joshua was enrolled at the gradua te level in the M.E. Rinker, Sr. School of Building Construction at the Univer sity of Florida. There here pursued his graduate studies while working in the field with the Facilities Devel opment Department of a major hospital. As an intern Joshua was able to work on an airport renovation project and a notable 62 million dollar high school project. His classr oom studies led him to inves tigate sustainable construction practices and an ultimate thesis topic that dealt with the potentials of renewable energy systems.