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Energy Efficiency Measures for Single Family Housing in Florida

Permanent Link: http://ufdc.ufl.edu/UFE0042935/00001

Material Information

Title: Energy Efficiency Measures for Single Family Housing in Florida
Physical Description: 1 online resource (137 p.)
Language: english
Creator: BURGETT,JOE M
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: EFFECTIVE -- EFFICIENCY -- ENERGY -- FLORIDA -- HOUSING -- MEASURES
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: ENERGY EFFICIENCY MEASURES FOR SINGLE FAMILY HOUSING IN FLORIDA Over recent history the sustainability movement has grown by leaps and bounds. Sustainability was once limited to specialized higher level theory but has recently moved into the public mainstream. Fueled by growing social awareness of climate change and the financial benefits, residential home owners are looking to ?go green? and reduce their energy consumption. Home owners are however at a disadvantage as they are generally not well educated on the specifics of energy conservation. When they attempt to find information on how to reduce their energy use they are bombarded with vendors peddling products however the solid data on how effective the measures are can be very illusive. Critical unanswered question on cost, efficiency and return on investment keeps many home owners from acting on their initial intentions. What is worse is many home owners do not know that energy efficiency measures are not consistent throughout the country. Measures that save energy in Florida may actually draw more energy in Wisconsin. Energy efficiency measures are very specific to geographic region and building types. To address this problem this research will take common energy efficiency measures and test them on a computer simulated model of a typical Florida house. The characteristics of the house will be based on actual data collected from Florida housing surveys and represent features common to more than 50% of all Florida houses. The model house will be constructed on a 3D computer modeling platform to ensure the accuracy of the energy and cost estimates. Energy modeling software will be used to calculate the effectiveness of the measures. Once completed a matrix that includes initial capital cost, effectiveness measured in cost per year, and pay back durations based on current finance rates will be created. Home owners can use the matrix and extrapolate the effectiveness and pay back of each of the common measures on their specific residence. As the model house consists of characteristics most common to Florida houses the energy savings should closely mirror the individual home owner?s situation. The residential housing market consumes nearly 40 percent of all of America?s electrical energy. Providing residential home owners the tools to make informed energy reduction decisions is low hanging fruit that should not be ignored.
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 JOE M BURGETT.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2011.
Local: Adviser: Chini, Abdol R.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0042935:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042935/00001

Material Information

Title: Energy Efficiency Measures for Single Family Housing in Florida
Physical Description: 1 online resource (137 p.)
Language: english
Creator: BURGETT,JOE M
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: EFFECTIVE -- EFFICIENCY -- ENERGY -- FLORIDA -- HOUSING -- MEASURES
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: ENERGY EFFICIENCY MEASURES FOR SINGLE FAMILY HOUSING IN FLORIDA Over recent history the sustainability movement has grown by leaps and bounds. Sustainability was once limited to specialized higher level theory but has recently moved into the public mainstream. Fueled by growing social awareness of climate change and the financial benefits, residential home owners are looking to ?go green? and reduce their energy consumption. Home owners are however at a disadvantage as they are generally not well educated on the specifics of energy conservation. When they attempt to find information on how to reduce their energy use they are bombarded with vendors peddling products however the solid data on how effective the measures are can be very illusive. Critical unanswered question on cost, efficiency and return on investment keeps many home owners from acting on their initial intentions. What is worse is many home owners do not know that energy efficiency measures are not consistent throughout the country. Measures that save energy in Florida may actually draw more energy in Wisconsin. Energy efficiency measures are very specific to geographic region and building types. To address this problem this research will take common energy efficiency measures and test them on a computer simulated model of a typical Florida house. The characteristics of the house will be based on actual data collected from Florida housing surveys and represent features common to more than 50% of all Florida houses. The model house will be constructed on a 3D computer modeling platform to ensure the accuracy of the energy and cost estimates. Energy modeling software will be used to calculate the effectiveness of the measures. Once completed a matrix that includes initial capital cost, effectiveness measured in cost per year, and pay back durations based on current finance rates will be created. Home owners can use the matrix and extrapolate the effectiveness and pay back of each of the common measures on their specific residence. As the model house consists of characteristics most common to Florida houses the energy savings should closely mirror the individual home owner?s situation. The residential housing market consumes nearly 40 percent of all of America?s electrical energy. Providing residential home owners the tools to make informed energy reduction decisions is low hanging fruit that should not be ignored.
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 JOE M BURGETT.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2011.
Local: Adviser: Chini, Abdol R.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0042935:00001


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1 ENERGY EFFICIENCY MEASURES FOR SINGLE FAMILY HOUSING IN FLORIDA By JOSEPH M. BURGETT A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MAS TER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2011

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2 2011 Joseph M. Burgett

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3 To my wife and family whose unyielding love and support is a con stant that I can always rely on

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4 ACKNOWLEDGMENTS I would like to thank Dr. Chini, Dr. Sullivan and Dr. Walters for taking the time to serve on my committee and assist with this research. I would like to give a special thanks to Dr. Chini for taking an interest in me and guid ing me along my academic career. I would also like to give Dr. S ullivan special thanks for helping me prepare for my career beyond graduation and encouraging me to expand my horizons. In addition to my committee, I would also like to thank Dr. Ravi Srinivasan who graciously spent time in and outside of class to help m e develop my energy model. I would like to thank Dennis Gallagher, Jim Wells and Chuck Congdon of The Weitz Company. Without their support, encouragement and mentoring I would not be the builder I am today. I am very gratefully for the ir professional e xperience and friendship that they shared throughout my tenure with the company. I would most importantly like to thank my wife Jill for all of her love and support. She represents the best of my past, present and future. Beyond my wife she is my compa nion, partner, comforter, and best friend. I count myself as true blessed to have her in my life

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 9 LIST OF FIGURES ................................ ................................ ................................ ....................... 12 ABSTRACT ................................ ................................ ................................ ................................ ... 13 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .................. 15 Background ................................ ................................ ................................ ............................. 15 Statement of Purpose ................................ ................................ ................................ .............. 15 Objective ................................ ................................ ................................ ................................ 16 Limitations of Research ................................ ................................ ................................ .......... 16 2 LITERATURE REVIEW ................................ ................................ ................................ ....... 18 Overview ................................ ................................ ................................ ................................ 18 Energy Efficiency Measures Available ................................ ................................ .................. 18 Space Conditioning ................................ ................................ ................................ ......... 19 Ceiling fans ................................ ................................ ................................ .............. 19 HVAC tune up ................................ ................................ ................................ ......... 19 Sealing leaking HVAC ductwork ................................ ................................ ............. 20 High SEER HVAC units ................................ ................................ .......................... 21 Water Heating ................................ ................................ ................................ .................. 22 Low flow shower heads and aerators ................................ ................................ ....... 22 Solar water heaters ................................ ................................ ................................ ... 22 Building Envelope ................................ ................................ ................................ ........... 24 Window films ................................ ................................ ................................ ........... 24 Insulatio n ................................ ................................ ................................ .................. 25 Low E glass ................................ ................................ ................................ .............. 25 Light tubes / skylights ................................ ................................ .............................. 26 Lighting, Applian ces, Miscellaneous Electrical Loads ................................ ................... 26 Compact fluorescent lights ................................ ................................ ....................... 26 LED lighting ................................ ................................ ................................ ............. 29 ................................ ................................ ........................ 29 Home Energy Management ................................ ................................ ............................. 30 Standby power loss ................................ ................................ ................................ ... 30 Programmable thermostats ................................ ................................ ....................... 33 Occupancy sensors ................................ ................................ ................................ ... 34 Energy dashboards ................................ ................................ ................................ ... 35 Photovoltaic solar panels ................................ ................................ .......................... 37

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6 Effects of Specific Climates on EEMs ................................ ................................ ................... 40 3 RESEARCH METHODOLOGY ................................ ................................ ........................... 43 Overview ................................ ................................ ................................ ................................ 43 Common Energy Efficiency Measures ................................ ................................ ................... 43 Typical Florida Housing ................................ ................................ ................................ ......... 44 Effectiveness of EEMs ................................ ................................ ................................ ........... 45 Cost Estimates of EEMs ................................ ................................ ................................ ......... 46 Matrix of Result s ................................ ................................ ................................ .................... 46 4 RESULTS AND ANALYSIS ................................ ................................ ................................ 47 Overview ................................ ................................ ................................ ................................ 47 Results and Analysis: Section One ................................ ................................ ........................ 47 Typical Florida Single Family Housing ................................ ................................ .......... 47 3D Model ................................ ................................ ................................ ......................... 48 Common Energy Saving Measures ................................ ................................ ................. 49 Results and Analysis: Section Two ................................ ................................ ....................... 51 Effectiveness Overview ................................ ................................ ................................ ... 51 Energy Modeling Software eQUEST ................................ ................................ ........... 51 eQUEST data collection ................................ ................................ ........................ 52 eQUEST building geomet ry ................................ ................................ .................. 52 eQUEST building components ................................ ................................ .............. 53 eQUEST zones and schedules ................................ ................................ ............... 53 eQUEST energy simulation ................................ ................................ .................. 54 Energy Efficiency Measures ................................ ................................ ............................ 54 Space Conditioning ................................ ................................ ................................ ......... 54 Ceiling fans ................................ ................................ ................................ .............. 54 HVAC tune up (re commissioning) ................................ ................................ ......... 55 Sealing leaking HVAC ductwork ................................ ................................ ............. 56 High SEER AC units ................................ ................................ ................................ 56 Hot Water ................................ ................................ ................................ ........................ 57 Low flow shower heads and aerators ................................ ................................ ....... 57 Solar water heating ................................ ................................ ................................ ... 57 Building Envelope ................................ ................................ ................................ ........... 58 Window film ................................ ................................ ................................ ............ 58 Increased attic insulation ................................ ................................ .......................... 58 Retro foam in walls ................................ ................................ ................................ .. 58 Low E glass ................................ ................................ ................................ .............. 59 Awnings ................................ ................................ ................................ ................... 59 Skylight ................................ ................................ ................................ .................... 60 Strategically placed landscaping ................................ ................................ .............. 60 Lighting, Appliances, Miscellaneous Electrical Loads ................................ ................... 61 Compact fluorescent lights ................................ ................................ ....................... 61 LED lighting ................................ ................................ ................................ ............. 61 clothes washer ................................ ............................ 62

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7 refrigerator ................................ ................................ ... 63 dish washer ................................ ................................ 64 Home Energy Management ................................ ................................ ............................. 65 Standby power lo ss ................................ ................................ ................................ ... 65 Programmable thermostat ................................ ................................ ........................ 65 Occupancy sensor ................................ ................................ ................................ ..... 66 Energy dash boards ................................ ................................ ................................ ... 66 Photovoltaic panels ................................ ................................ ................................ .. 67 5 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ................................ ........ 101 Summary ................................ ................................ ................................ ............................... 101 Matrix of Results ................................ ................................ ................................ .................. 101 Cost vs. Savings Comparison ................................ ................................ ............................... 103 Return on Investment ................................ ................................ ................................ ............ 103 Most Favorable EEM Investments ................................ ................................ ....................... 104 Limitations ................................ ................................ ................................ ............................ 105 Recommendations for Future Study ................................ ................................ ..................... 106 APPENDIX A BASE LINE ENERGY MODEL THE MODEL HOUSE ................................ ................... 115 B ENER GY MODEL OF THE CEILING FAN EEM ................................ ............................. 116 C ENERGY MODEL OF THE HVAC TUNE UP EEM ................................ ........................ 117 D ENERGY MODEL OF THE LEAKING HVAC DUCTWORK EEM ............................... 118 E ENERGY MODEL OF THE HIGH SEER AC UNIT EEM ................................ ................ 119 F ENERGY MODEL OF THE LOW FLOW SHOWER HEADS AND AERATORS EEM ................................ ................................ ................................ ................................ ...... 120 G ENERGY MODEL OF THE WINDOW FILM EEM ................................ ......................... 121 H ENERGY MODEL OF THE BLOWN IN ATTIC INSULATION EEM ............................ 122 I ENERGY MODEL OF THE RETRO FOAM IN WALLS EEM ................................ ........ 123 J ENERGY MODEL OF THE LOW E GLAZING EEM ................................ ...................... 124 K ENERGY MOD EL OF THE WINDOW AWNING EEM ................................ .................. 125 L ENERGY MODEL OF THE SKYLIGHT EEM ................................ ................................ .. 126 M ENERGY MODEL OF THE STRATEGICALLY PLACED LANDSCAPE EEM ............ 127 N ENERGY MODEL OF THE CFL EEM ................................ ................................ .............. 128

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8 O ENERGY MODEL OF THE LED LIGHTING EEM ................................ .......................... 129 P ENERGY MODEL OF THE PROGRAMMABLE THERMOSTATS EEM ...................... 130 Q ENERGY MODEL OF THE OCCUPANCY SENSOR EEM ................................ ............. 131 R PROTOCO L FOR MODEL HOUSE ................................ ................................ ................... 132 LIST OF REFERENCES ................................ ................................ ................................ ............. 133 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ....... 137

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9 LIST OF TABLES Table pa ge 2 1 ................................ 41 4 1 Typical single family housing: general information ................................ ....................... 68 4 2 Typical single family housing: construction characteristics ................................ ........... 68 4 3 Typical single family housing: appliances ................................ ................................ ...... 69 4 4 Ty pical single family housing: furnishings ................................ ................................ ..... 70 4 5 Ceiling fan EEM performance ................................ ................................ ......................... 70 4 6 Ceiling fan EEM cost ................................ ................................ ................................ ....... 71 4 7 HVAC tune up (re commissioning) EEM performance ................................ .................. 71 4 8 HVAC tune up (re commissioning) EEM cost ................................ ................................ 72 4 9 Leaking HVAC ductwork EEM performance ................................ ................................ 72 4 10 Leaking HVAC ductwork EEM cost ................................ ................................ ............... 73 4 11 High S EER a/c unit EEM performance ................................ ................................ ........... 73 4 12 High SEER ac unit EEM performance ................................ ................................ ............ 74 4 13 Low flow shower heads and aerators EEM perfor mance ................................ ................ 74 4 14 Low flow shower heads and aerators EEM cost ................................ .............................. 75 4 15 Solar water heating EEM performance ................................ ................................ ............ 75 4 16 Solar water heating EEM cost ................................ ................................ .......................... 76 4 17 Window film EEM performance ................................ ................................ ..................... 77 4 18 Window film EEM cost ................................ ................................ ................................ ... 77 4 19 Increased attic insulation EEM performance ................................ ................................ ... 78 4 20 Increased attic insulation EEM cost ................................ ................................ ................. 78 4 21 Retro foam in walls EEM performance ................................ ................................ ........... 79 4 22 Retro foam in walls EEM cost ................................ ................................ ......................... 79

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10 4 23 Low E glass EEM performance ................................ ................................ ....................... 80 4 24 Low E glass EEM cost ................................ ................................ ................................ ..... 80 4 25 Awning EEM performance ................................ ................................ .............................. 81 4 26 Awning EEM cost ................................ ................................ ................................ ............ 81 4 27 Skylight EEM performance ................................ ................................ ............................. 82 4 28 Skyli ght EEM cost ................................ ................................ ................................ ........... 82 4 29 Strategically placed landscaping EEM performance ................................ ....................... 83 4 30 Strategically placed landscaping EEM cost ................................ ................................ ..... 83 4 31 Compact fluorescent lighting EEM performance ................................ ............................ 84 4 32 Compact fluorescent lighting EEM cost ................................ ................................ .......... 84 4 33 LED lighting EEM performance ................................ ................................ ...................... 85 4 34 LED lighting EEM cost ................................ ................................ ................................ ... 85 4 35 ES clothes w asher EEM performance ................................ ................................ .............. 86 4 36 ES clothes washer EEM cost ................................ ................................ ........................... 86 4 37 ................................ ................................ 87 4 38 ................................ ................................ .............. 87 4 39 ................................ ................................ 88 4 40 ................................ ................................ .............. 88 4 41 Stand by power loss EEM performance ................................ ................................ .......... 89 4 42 Stand by po wer loss EEM cost ................................ ................................ ........................ 89 4 43 Programmable thermostat EEM performance ................................ ................................ 90 4 44 Programmable thermostat EEM cost ................................ ................................ ............... 90 4 45 Occupancy sensor EEM performance ................................ ................................ .............. 91 4 46 Occupancy sensor EEM cost ................................ ................................ ........................... 91 4 47 Energy dashboards EEM performance ................................ ................................ ............ 92

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11 4 48 Energy dashboard EEM cost ................................ ................................ ............................ 93 4 49 Photovoltaic EEM performance ................................ ................................ ....................... 93 4 50 Photovoltaic EEM cost ................................ ................................ ................................ .... 94 5 1 Matrix of Results ................................ ................................ ................................ ............ 108

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12 LIST OF FIGURES Figure page 2 1 Department of Energy Residential Energy End Use Splits. ................................ ............ 41 2 2 Before and After Blower Cleaning. Image from CCS, LLC. of G ainesville, FL. .......... 42 4 1 The Model House. ................................ ................................ ................................ ............ 94 4 2 Floor Plan of Model House. ................................ ................................ ............................. 95 4 3 Living Room of Model House. ................................ ................................ ........................ 96 4 4 Kitchen of Model House. ................................ ................................ ................................ 96 4 5 West Bedroom of Model House. ................................ ................................ ..................... 97 4 6 Master Bedroom. ................................ ................................ ................................ .............. 97 4 7 Back Yard Patio. ................................ ................................ ................................ .............. 98 4 8 eQUEST I ntroduction. ................................ ................................ ................................ ... 98 4 9 eQUEST Building Geometry. ................................ ................................ ....................... 99 4 10 eQUEST Building Components. ................................ ................................ ................... 99 4 11 eQUEST Zoning and Schedules. ................................ ................................ ................ 100 5 1 Initial Capital Expense. ................................ ................................ ................................ .. 109 5 2 Energy Consumpti on Reduced per Year. ................................ ................................ ....... 110 5 3 Initial Capital Expense vs. Savings. ................................ ................................ ............... 111 5 4 Cost per Kilowatt Hour Conserved. ................................ ................................ ............... 112 5 5 Return on Investment. ................................ ................................ ................................ .... 113 5 6 Duration of Return on Investment. ................................ ................................ ................ 114

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13 A bstract of T hesis P resented t o the G raduate S chool o f the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction ENERGY EFFICIENCY MEASURES FOR SINGLE FAMILY HOUSING IN FLORIDA By Joseph M. Burgett May 2011 Chair: Abdol Chini Major: Building Construction Over recent history the sustainability movement has grown by leaps and bounds. Sustainability was once limited to specialized higher level theory but has recently moved into the public mainstrea m. Fueled by growing social awareness of climate change and the financial consumption. Home owners are however at a disadvantage as they are generally not well educated o n the specifics of energy conservation. When they attempt to find information on how to reduce their energy use they are bombarded with vendors peddling products however the solid data on how effective the measures are can be very illusive. Critical u nan swered question on cost, efficiency and return on investment keep s many home owner s from acting on their initial intentions. What is worse is many home owners do not know that energy efficiency measures are not consistent throughout the country. Measures that save energy in Florida may actually draw more ene rgy in Wisconsin. Energy efficiency measu res are very specific to geographic region and building types. To address this problem this researc h will take common energy efficiency measures and test them on a computer simulated model of a typical Florida house. The characteristics of the house will be based on actual data collected from Florida housing surveys and represent features common to more than 50 % of all Florida houses. The model house will be constructed on a 3D computer modeling platform to ensure the accuracy of the

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14 energy and cost estimates. Energy modeling software will be used to calculate the effectiveness of the measures. Once complete d a matrix that includes initial capital cost, effe ctiveness measured in cost pe r year and pay back durations based on current finance rates will be created. Home owners can use the matrix and extrapolate the effectiveness and pay back of each of the common measures on their specific residence. As the m odel house consists of characteristics most common to Florida houses the energy savings should closely mirror the individual home % electrical energy. Providing resid ential home owners the tools to make informed energy reduction decisions is low hanging fruit that should not be ignored.

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15 CHAPTER 1 INTRODUCTION Background Over the past 30 years the general public as a whole has become very sensitive to the growing amo unt of energy that the built environment consumes. Because of the obvious advantages of energy conservation, like lower costs and greater environmental responsibilities, the public is willing to make changes in its lifestyle and invest in capital improvem ents to enjoy these benefits. However the residential market is a vastly underutilized area for energy conservation. According to the Department of Energy, residential buildings consume approximately 38% of the total U S electrical energy. While there have been many improvements with how new homes are built, this only represents a small fraction of the total residential building stock. The Department of Energy also reports that there are approximately 116 million existing homes with only 500,000 2,00 0,000 built every year. Clearly the segment within the residential market that has the most opportunity for improvement is in retrofitting existing homes and making them more efficient. Statement of Purpose Despite the desire to reduce their energy con sumption critical u nanswered question of cost, efficiency and return on investment keep s many home owner s from acting on their initial intentions. As a group, home owner are not well educated on the specifics of conservation techniques, energy modeling, o r construction cost. These areas are the pillars that this study is

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16 Objective This study looks to identify effective means of reducing residential energy consumption research effectiveness will be framed in terms of energy reduced from normal and initial influx of capital expense. Another way of phrasing this is the inverse relationship of energy saved verse capital cost. The first key component of effectiveness is the calculation of energy saved. To this end a computer s imulated model house was created and served as the baseline to which each EEM was compared. Inputs like insulation values, HVAC equipment, window area, and other energy influencing factors were entered into an energy modeling computer program and an avera ge energy consumption value was calculated. With the baseline established each EEM was then entered into the energy model and the saving calculated. The second key component of effectiveness is the estimating of initial cost required to implement the EEM s. To accomplish this published construction cost data in combination w ith estimating software programs were used to create detailed estimates. The estimates were itemized to include factors like labor, material cost, permitting fees, taxes, delivery cha rges, general conditions and overhead & profit. Estimates were verified for accuracy by comparing actual market prices from real world vendors of similar products. Limitations of Research Within the built environment there are many different building type s and climates that have specific qualities which may vary the effectiveness of each EEM. The first limitation of the study is geographical. This research reviewed the hot/humid climate type specifically within the state of Florida. The second limitatio n is the type of residential housing units reviewed. The study ignores all multifamily structures, rental units, attached structures, and manufactured

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17 housing but focuses solely on single family detached houses. The third limitation of the study is on th e type of EEMs tested. There are many EEM available however this study tests only well established residential EEMs. These measures are largely those endorsed by established experts in the fields of building energy use like the U S Department of Energy, U S Green Building Council and the Energy Star program

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18 CHAPTER 2 LITERATURE REVIEW Overview In this age of growing awareness of the Earth consequences of power generation the topic of Energy Efficiency Measures (E E Ms) has been greatly discussed. While there are m any entities that place demands market such as manufacturing, transportation and commerce in the United States one of the heaviest energy using segment s is the residentia l housing market. According to the Department of Energy (2010), residential housing uses 38 % of the total electrical energy produced. With residential housing being such a large consumer of energy, measures that create even a small reduction by percentag e will produce a significant reduction of the total national demand. In this literature review the current state of knowle dge of what EE Ms are available for Florida housing and how sp ecific climates dictate which EE Ms are effective will be reviewed. Energ y Efficiency Measures Available The sustainability movement in the United States has made great strides over the past 15 years. As energy conservation is a key component of this movement a great deal of research has been done on identifying how energy is used and developing measures on how to reduce the demand. However, to get the most return on the investment it is important to focus on the areas of a home that consume the most energy. According to the Department of Energy, on average Americans use two and half times more energy on space heating than on home electronics ( See Figure 2 1 ) Purchasing a more expensive but energy efficient television may yield the same or even less energy savings than if the money were used fo r a programmable thermostat. EE Ms are often categorized into five groupings which will be mirrored in this research : Space Conditioning Water Heating

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19 Building Envelope Lighting, Appliances, Miscellaneous Electrical Loads Home Energy Management In this chapter various specific measure s typical to the hot/humid climate type will be grouped into these same categories and explored in detail. Space Conditioning Ceiling fans Ceiling fans originated in the United States dating back to the mid ninetieth century. Originally they were not po wered by electric motors but by streams of water that would usually power several fans in series and were commonly seen in offices, restaurants and stores. The electric power fan is largely credited to Philip Diehl who introduced the Diehl electric fan in 1882. Ceiling fans remained popular in the United States until the 1930s when their popularity rapidly declined. It was not until the 1970s when they started to become more in vogue (Scharff 1983). Ceiling fans can provide a low cost means of energy re duction when used in tandem with moisture on the skin causing people to feel cooler at higher temperatures. This cooling effect allows for people to increase the temper ature on their thermostats by 3 or 4 degrees and feel just as comfortable. Ceiling fans can also be used in the winter months. Most modern fans have an option to reverse the direction the blades turn. While air flow in the winter months may still increa se evaporation and thus the chill effect, reversed fans can also pull warm air from the ceiling and push it down into the living space (Progress Energy 2010) HVAC tune up Similar to automobiles or any other piece of mechanical equipment HVAC systems need regular maintenance to operate properly. According to a publication made by Energy Star

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20 (Energy Star 2009), recommends that each of the following maintenance items be address ed regularly either by the home owner or a qualified se rvice person. Check the thermostat so that it turns on and off at the set point. If a programmable thermostat is used verify that the program is accurate for the occupancy lifestyle. Verify all electrical connections especially those to the motor are tigh t and adequately secured. Lubricate moving parts. Check to make sure that the condenser line is clear. This will not save energy however a clogged condenser line can cause significant water damage to a home. Check the condenser operation to make sure it h as a proper start up and shut down. Check and clean the filter regularly but never longer than 3 months. Clean indoor and outdoor coils. Clean blower fan (see Figure 2 2). Check the charge of the refrigerant. Too much or too little can diminish the perfor mance of the equipment. Make sure the blower is free from obstructions and debris. Sealing leaking HVAC ductwork Leaking ductwork is one of the largest contributors to residential HVAC equipment inefficienc y According to the Department of Energy, the a verage house looses 20% of their conditioned air through leaking or kinked ductwork (US DOE 2009) Some of the areas that contribute the most to the issue are flexible ductwork that is kinked and restricting flow, poorly connected ducts to registers, leak y or torn ductwork especially at connections and inadequately sealed air handlers. Residential HVAC systems are especially susceptible to leaking ductwork because of the heavy use of duct tape. Despite its seaming unending list of applications, it

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21 actual ly seals ducts very poorly. Over time duct tape loses adhesion and falls apart. The deterioration is accelerated in extreme temperatures commonly found in attics and unconditioned crawl spaces. Repairing the problem can be relatively easy is some areas but also very invasive in others. For instance, resealing air handlers, ductwork, and register connections can be completed easily with minimal cost by homeowners as long as they have proper access. However, ductwork and connections may be in wall caviti es or attics that are not easily accessible making resealing them difficult. Despite the mixed bag of difficulties, pursuing duct leak mitigation can yield some significant benefits. According to the California Energy Commission, providing retrofit repai rs to leaking ductwork in residential homes can typically increase HVAC efficiency by 10% or more (US DOE 2009) High SEER HVAC units efficiency ratio (SEER) is usually what is considered. The SEER rating is calculated by dividing the cooling output during the cooling season by the energy used during this same period. The to the SEER however EER is for total year conditions and SEER is only for the cooling season. The EER is usually less than the SEER and for most residential HVAC units a factor of .875 can be applied to the SEER to convert it to the EER (Air Conditioning, Heatin g and Refrigeration Institute 2008) Starting in 2006, the U S government required that all new HVAC units have a minimum SEER rating of 13. Older units were often found to have SEERs of nine however the number of these units are dwindling as the agin g units are replaced (Norland 2006) More progressive owners who wish for higher efficient units can choose Energy Star systems that have a minimum SEER of 14 (US DOE 2011) Some manufacturers offer super efficient units with

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22 SEER s of 16 to 2 3 however they are at a significantly higher cost than comparable 13 SEER units ( Consumer Search 2011 ). Water Heating Low f low show er h eads and a erators energy efficiency. However, if you consider that most residential homes have a tank style water heater that uses electricity to heat water than t he reduction in water use makes sense. According to the Shimberg Center for Affordable Housing the median year built for Florida single family houses is 1988. This is an important date as it precedes the Water Resources Development Act of 1992. This act put some aggressive restriction on water use for most new residential plumbing fixtures. For example, the act limits the water use of shower heads to 2.5gpm at 80psi where before 1992 some shower heads had a flow rate of 5.5gpm. Showering represent abou t 20% of the total residential water use and presents a good opportunity to reduce overall demand. Fortunately, retrofitting existing homes with new low flow shower heads is relatively simple and cost effective. The use of aerators is another way to redu ce hot water use. These devices will not actually restrict the use of water from a faucet (although models can be purchased that do this as well) however they effectively mix air and water. This mixture of air and water more efficiently allows for solids to be dissolved in water and washed off. Essentially, using aerated water allows for dishes or any other object to be washed quicker with less water. Showers and faucets constitute over 43% of all residential water use so implementing measures to reduce consumption in these two areas can provide a significant return on investment (Vickers 2001) Solar water heaters The use of solar energy to heat water is not a new concept. The history of solar water heating dates back to sketches from Leonardo da V inci, with improvements during the industrial

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23 revolution and introduction into the U S mainstream after the 197 3 Arab ian oil embargo. Modern solar heated water systems are divided into three basic types; low, medium and high temperature systems. Low tem perature systems heat water to a maximum of 110 degrees and are by far the most common. The popularity of these units is due to their effectiveness with residential pools. These solar pool heaters generally use a black flexible mat with integrated tubing as a collector of the solar energy. Water is circulated from the pool, into the collector and then back into the pool. Often times a photovoltaic panel is used to power the pump. Photovoltaic powered pumps are ideally suited for this situation as when there is an abundance of solar energy the pump will circulate the highest amount of water and maximize the heat transferred into the pool. However, on cooler overcast days the pump will not circulate as much water and help avoid the pool loosing heat thro ugh the collector. The second type of water heater is the medium temperature system and heats water between 110 and 180 degrees. Domestic solar heated water systems are generally medium temperature types. One common medium temperature design is the inte grated storage unit type. This design uses several large diameter copper tubes set in an insulated five sided box with a glass lid. The insulated box collects the solar energy and transfers the heat through the copper tube walls. The insulated box is us ually mounted at the roof level and uses municipal water pressure and gravity to provide the necessary water pressure. Another type of medium temperature systems uses a similar insulated box but circulates water through small copper tubes from the box int o a storage tank. This type of system is more common as it is less susceptible to leaks, allows for a conventional heating coil as back up and easier to retrofit into existing residence. High temperature systems are not used residentially and most common ly used for power generation. The system uses parabolic troughs to concentrate solar energy and super heat water to steam This super heated steam heated to

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24 temperatures near 1,450 degrees in some cases, is used to turn turbines to produce electrical en ergy (Wilson 1999). Building Envelope Window films Windows influence the energy consumption of a home more than any other exterior feature. It is estimated that windows account for 15 30 % of the winter heating load and over half of the summertime cooli ng load. Researchers at the Lawrence Berkley National Laboratory estimate that residential windows account for 3.2 % of the total United States annual energy consumption and 9 % of all residential energy consumption. There are many factors that influence t he efficiency of a window such as frame material, layers of glass, air spaces, and insulation to name a few. Most of these measures are not easily retrofitted to existing windows however. One exception to this is the use of externally applied window film These window films are thin plastic sheets applied on the interior side of the glass (Wilson 1996) There are two basic types of window films. The first is a dye tinted film which blocks solar heat gain through the absorption of both visible light a nd solar radiated heat. The dye tinted films have been available for retrofit application since the late 1960s but have not gained much traction with the residential market. This is primarily because home owners are unwilling to substitute low natural li ght for reduced solar heat gain. The second type of film is light spectrum selective and relies on reflectivity and emissivity. These films block the longer infrared and UV light waves, responsible for almost half of the solar heat gain, but still allows most of the shorter visible light waves through. There are many film manufacturers with varying claims of efficiency however on their website 3M state d that their Prestige line of window films allows the owner to enjoy a reduction of 60% of heat gain wit h only a 30% reduction in light emissions (Environmental Building News 2010).

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25 Insulation The exterior of a home is called its shell or envelope and is the point of separation between the outside elements and conditioned space. The envelope however can ha ve many penetrations making it a less effective barrier. Energy Star reports that home owners can easily decrease the load on their HVAC systems by 20 % by properly insulating their home. Adding insulation in the attic floor is one of the easiest and mo st effective ways a home owner can tighten up their homes envelop. The recommended insulation in the attic is R 38 which is between 12 and 15 inches. Adding rigid or spray foam insulation at the roof deck is another way Adding insulation at the roof deck has the advantage of moving the barrier further away from conditioned space. Locating and sealing penetrations in th e walls is another energy efficiency measure. Detecting air penetrations in the wall can be difficult and may require the services of a professional with inferred cameras and specialty instruments. However, once they are located spray foams can be used to seal the penetrations with minimal finish rework (Energy Star 2009). Low E glass Low Emissivity gla ss commonly called Low E glass is specially formulated glass designed to increase the energy performance of the window. The U S Department of Energy E coatings typically cost about 10% 15% more than regular windows, but they reduce energ y loss by as much as 30% E is an extremely thin metal or metallic oxide layer placed on the warm side of the glass. The Low E layer reduces the E coating also diminishe d the amount of visible light transferred through the glass however with the development of spectrally selective coatings the light transmitted is virtually the same as traditional glass. In addition to Low E glass, many other improvements have been made to modern windows. One of these

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26 advances is the use of thermal breaks in the window frame. This reduces the heat transference through the window frame. Another development in window efficiency is the use of double paned insulated glass. This glass has an air space which retards the flow of convection and conduction heat through the glass. In some high efficiency window systems argon gas is used instead of normal nitrogen heavy air a s a means of additional heat transmission reduction (US Department of E nergy 2010) Light tubes / skylights While the use of light tubes has gained some recent public interest it is not a new technology. Rudimentary light tubes have been used aboard ships for centuries. A light tube system consist of a transparent aperture channel or tube that transports the light and a diffuser which disperses the light into occupied space. Light tubes are primarily used in residential applications and the tube ranges in size from thus lost in transport. Skylights are another means of importing natural lights into a building. Skylights are essentially windows on the roof. In years past sk ylights were used for beatification but caused a net increase in power consumption. They provided natural lighting however the increased solar heat gains created added demand on a buildings HVAC system. Today, with the use of double paned high efficiency glass the heat gain has been significantly reduced making them a source of beauty and energy efficiency (Wilson 1999) Lighting, Appliances, Miscellaneous Electrical Loads Compact fluorescent l ights When replacing light bulbs throughout the house many co nsumers think that the wattage indicated on the bulb is a measure of how bright the bulb is. While there can be truth in this, what is not always thought of is that the w att is actually a measure of the rate of energy

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27 conversion or stated another way is o ne joule of energy over one second of time. As a watt is a measure of conversion the higher the wattage of a light bulb the higher the conversion of electrical energy to light. In residential homes the incandescent light is traditionally what is used fo r creating artificial light. The incandescent light bulb is century old technology widely accredited to Thomas Edison although there were 22 individual inventors of different incandescent lamps prior to Edison ( Friedel and Israel 1986 ). The common incand escent light bulb passes current through a filament heating it until it produces visible light. According to General Electric (1964) over 90% of the energy used in an incandescent light bulb is used to generate heat. This heat is not just wasted energy b system. With the obvious disadvantages to the common incandescent lights some consumers have demanded a better option for their home lighting needs. The introduction of the compact fluorescent light (CFL) offers a n opportunity for a significant reduction in energy use which many consumers are finding desirable. The mechanics of compact fluorescents are, as its name suggests, the same as a traditional fluorescent lamp. The lamp is a glass cylinder in which an elec trical charge is used to excite mercury vapors which produces visible light. CFLs are compatible with devices that use traditional incandescent light bulbs. The CFL bulb simply screws into a standard light socket just as an incandescent bulb does. The m ost common types of CFL are the straight tube and the spiral tube type. The straight tube type has a slightly higher efficiency than the spiral type as the spiral type requires a thicker glass wall to support the curved glass. For either type of CFL the efficiency is significantly higher than that of incandescent lamps. On average CFL uses 75% less energy than a comparable incandescent lamp. According to a publication by Energy Star if every home in America were to switch only one of their incandescent lamps to a CFL it would

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28 save enough energy to light 3 million homes for a year, save about $600 million in annual energy costs, and prevent 9 billion pounds of greenhouse gas emissio ns per year, equivalent to Despite the significant energy savings advantages, CFLs represent a small fraction of the lighting market share and it appears to be in a state of decline. In 2009 it was estimated that only 11% of available light sockets were filled with CFL ( Vessel 2009 ) Richard Karney, Energy CFL production manager indicated that sales of CFLs have reduced by 25% from their hat the market is have to contend with. First, CFL use mercury gas to produce light. Consumers are particularly sensitive to mercury levels in food products and concerned about mercury gas in their homes if a bulb were to break. The second issue that may be limiting C FL acceptance by the public is that the initial cost is significantly higher than a comparable incandescent light. The paybacks are decisively doc umented however if a CFL were damaged and needed to be replaced the proforma would change It is important to note however that CFLs have significantly longer life spans than incandescent options which could also be affecting the sales figures. The argum ent about whether CFL producers can win over consumers has largely become moot in recent years. In the early part of the decade several states which include California, Connecticut and New Jersey passed legislation restricting the sale of traditional low efficiency lamp. The unquestionable biggest push forward for CFL came from the Federal government with the passing of the Energy Independence and Security Act of 2007. This act calls for a 30% improvement in efficiency from the traditional incandescent b ulb starting in 2012 through 2014.

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29 The program starts with lamps of 100 W atts in 2012 and move to 40 W atts bulbs in 2014. Lighting outside this range are not included in the act nor are some specialty bulbs (Energy Independence and Security Act of 2007) LED lighting Light Emitting Diodes commonly shorted to LEDs are semiconductors that emit p h otons in a process called electroluminescence. These p h otons are perceived by people as visual light and are very common in modern society. They were first intro duced in the 1960s and used primarily in electronics. LEDs are small, energy efficient and durable making them ideal for this application. However, since their introduction many advances have been made making them suitable for a variety of other applicati ons. LEDs are now available in a near infinite array of colors and the light output has greatly increased since the 1960s. LEDs can be found now in display boards, specialty lighting, flashlights and general building lighting. As the awareness of energy conservation increases the interest in LEDs for these other application s also increases. This is especially true for general building lighting. The Mark II dimmable LED light bulb manufactured by LED Waves produces the same lighting as a comparable 60 W att incandescent bulb but with a power consumption of only 8.5 W atts. These LED light come with a 3 warranty and are rated to operate continuously for over four and a half years. The cost for these bulbs can be considerably more than traditional incandes cent bulbs however. As of December 2010, the Mark II LED bulb sold on the LED Waves website for $45.95 each (Ehrlich 2010) Energy S tar appliances The Energy Star program is system that rates the energy efficiency of consumer products like clothes washers, dishwashers, and refrigerators. The program was first created in the early 1990s under the direction of the Environmental Protect ion Agency. While specific products may vary, on average a reduction by 20 30 % energy use is required to earn the

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30 Energy Star label. Energy Star has grown significantly since its inception. The program has gone international being adopted by the E U, Taiwan, Australia, Canada, Japan, and other. The Energy Star program has also moved past just rating products but also has a label for residential houses (Tugend 2008). Despite the growth of the program there are still some products lines which Ener gy Star does not rate. Some of these products are dryers, microwave ovens, ovens, and ranges (Energy Star 2010). Home Energy Management Standby power loss Standby power loss is the power that an electrical device uses even though it is not actively pow ered on. This is sometimes called its vampire draw. When consumers look at the energy performance properties of appliances or other electronic equipment the standby power draw is often times overlooked. This consumer oversight is understandable as for e xample intuitively the small power draw of a LED clock on a microwave seems insignificant. However, standby power when in use but is in standby more than 99 % of the time. When calculated over the life of the microwave, the appliance will use more electricity to power the clock than to cook. This issue is compounded by the large number of devices that use standby power. These devices include televisions, comput ers, printers, DVRs, and even disconnected cell phone chargers. Dr In 199 8 the LBNL led by Dr. Meier was tasked to quantify the magnitude of the standby power loss problem. The results of the study were surprising. On average, standby power loss accounted for five percent of the total American home energy use but could be as high as 10 % At the time of the study five percent of the residential energy use equated to 64MWh or the sum

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31 power generation of 18 typical power stations. If the unnecessary power consumption of standby power could be avoided it would save American cons umers more than three billion dollars a year (Meier 2006) The issue has started to receive national attention and in January of 2006 the California Energy Commission enacted new regulatory legislation limiting the standby power draw on many common electro nic devices to three watts per hour. Additionally, in 2001 Executive Order available, off the shelf products that use external standby power devices or that contain a n internal standby power function, shall purchase products that use no more than one watt in their s along with technological improvements have created a bell shaped curve of standby power draw over th e past 40 years. Forty years ago electronic devices had very few peripheral functions requiring power when not in the on position so their standby power was typically zero. Fifteen years ago when electronics were very popular but before legislation and t echnological advancements were made, standby power draw was commonly 15 W atts or more per hour. In more recent years the average standby power draw is closer to one W att per hour. Given the alarming amount of energy that is wasted because of standby power loss, the next natural question is what can be done about it. For existing appliances the only practical option is to disconnect the device from the electrical receptacle. However, several devices are now sold to make this more convenient. One device i s a power strip with an integrated on/off switch. These power strips have the advantage of being able to plug in multiple devices and thus be able to stop all of the standby power loss with one switch. This is particularly advantageous as the two areas o f a home that have the highest losses are at the television/entertainment area

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32 and at the home computer with related accessories. In both of these areas all of the equipment can be plugged into a single power strip and sever the connection with a single s witch. The integrated on/off switch is also typically included in surge protectors commonly used to protect these high cost electrical devices. Still, going to an electrical receptacle to turn off equipment is not always convenient, especially if the rec eptacle is buried behind furniture. Another option that is available is a remote controlled switch. This devise has two parts. The first part is a devise that plugs into a receptacle. The plug in receptacle has a port to have another devise plugged int o it. Within the plug in device is a low voltage relay that opens and closes the circuit to the appliance that is plugged into it. The second part of the remote controlled switch is a transmitter that is often modeled to look like a common light switch. The transmitter is typically mounted to the wall and the user can turn off the power to an appliance by simply turning off the switch. There are several different manufacturers of the remote switch. A popular residential grade switch is called the Handy Switch and costs approximately ten dollars ( Mays 2008 ). Fortunately new appliances have options to make them much more efficient when in the standby mode, especially for low voltage equipment. The traditional way to step down the voltage required for sm aller electronic devices is to use a charger with an iron core surrounded by copper to step down the voltage. Power Integrations in San Jose California provide s these switch mode power supplies to companies such as Sony, Samsung, Motorola, Dell and Apple. Balu Balakrishnan, president of Power Integration, estimates that although these power supplies are a significant improvement, they only account for 20% of th e four billion power supplies sold worldwide each year. The rest of the 80% are the traditional power supplies. The traditional power supplies are cheaper to make so manufacturers are not incentivized to provide them,

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33 meaning that their customers will be paying the higher usage cost. New regulations as discussed earlier are mandating that the manufacturers use the switch mode or other high efficient power supplies and thus transfer the use cost back into the initial purchase price. Programmable thermosta ts According to the U S Department of Energy, heating and cooling represents nearly 50% of residential energy use. However, on average this load can be reduced by 10% by setting back the temperature 10 15 degrees for eight hours a day. This may seem intrusive at first glance but if you consider that in many cases a house is unoccupied for 10 hours a day the savings opportunity for this EE M seems viable Many home owners try to reduce their heating and cooling demand by manually lowering and raising the temperature on their thermostats to coincide with when they are home. While this does lead to some savings the use of a programmable thermostat increases the savings for two main reasons. First, by adjusting the temperature setting of the thermostat manually the home owner runs the risk of forgetting or falling out of habit and thus losing the opportunity for savings. The second reason that a programmable thermostat is more effective is that it can adjust the temperature when the home owner is not av ailable to adjust it manually. This is particularly advantageous at night when the home owners are sleeping. A programmable thermostat can keep the temperature at a comfortable level until after the home owner is asleep and then adjust it to a less energ y intensive setting. Even for energy conscience home owners falling asleep and waking up to uncomfortable air temperatures is usually not worth the energy savings (US DOE 2010). Energy Star produced a manual titled Efficient Heating and In this manual they provide recommend setting for programmable thermostats See Table 2 1 for set points.

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34 Programmable thermostats are not applicable in every condition. One example of where a programmable thermostat is not appropriate is with heat pumps. While in the cooling mode heat pumps act very similarly to traditional DX HVAC systems. When in the cooling mode relatively large swings in temperature to correspond to when the home is occupied will save energy. However, in the cooler months when heat is demanded large swing in temperatures cause a heat pump to operate inefficiently. Despite this limitation progress has been made and new special programmable thermostats are being introduce that can offer efficiencies even in the cooler seasons. Electric resistance heating elements like electric base boards are also not ideally suited for programmable thermostats. This is primarily because electric resistance heating is controlled directly from the line voltage; usually 120v or 240v. Relatively few manufacturers produce a line voltage programmable thermostat for this application and the cost is significantly higher than their low voltage counterparts. Additionally, programmable thermostats do not provide much savings with steam heatin g and radiant flooring. These types of heating have a long response time so there may be few or no on/off cycles throughout the day. It is important to note however that all of the examples mentioned where programmable thermostats are not effective are f or heating and most commonly found in climates with long and severe winters. These heating methods are not commonly found in Florida (US DOE 2010) Occupancy sensors The U S Department of Energy estimates that approximately 10.1 % of a residential buildi have looked to find ways of reducing the waste in their home lighting. One way that can help reduce lighting waste is with the use of occupancy sensors. Occupancy se nsors are devices that detect the presents of people and open and close an electrical circuit accordingly. Lighting is a very common and practical application for occupancy sensors. Occupancy sensors can detect

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35 people in three different ways and often us e them in combination. The first way is the detection of inferred light which is generated from body heat. These are fairly resistant to false ons but require a line of sight to the occupant. A person tucked in a corner of a room may be left in the dark after the internal timer runs out. Another means of detecting people is by emitting a continuous ultrasonic pulse and then detecting any change in reflected sound. This type of occupancy sensor can detect people better than the passive inferred however is more susceptible to false ons from air movement or movement in an adjacent room. The ultrasonic occupancy sensor also has greater limits in the range it can detect people. Passive inferred and ultrasonic detection are often used together to compensate third means of detection. These occupancy sensors have a small microphone which closes the circuit if sound is detected above normal background noise. This type is the most sensitive but also the most susceptible to false ons (Wilson 2003) There are many designs available in which the device can be mounted on any surface in a room but the most common is for it to be combined with the entrance light switch. The switch mounted occupancy sensor usually includes an internal adjustable timer that will leave the circuit closed for a set period of time after it stops detecting an occupant. The switch also includes a manual override button where a user can turn on or off a fixture despite the occupancy of a room. This is especially important for bedrooms where having the lights on when occupied is not desired (Wilson 2003). Energy d ashboards changed when they have real time feedback. As an example, people in general are aware that the slower they drive the more fuel efficient their car is. Despite this general knowledge, the monthly cost of fuel does not significantly influence the speed at which people drive. However,

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36 if a driver has access to real time data significant behavior changes have been observed. Dr. Kevin Little of the Informed Ecological Design, LCC calls this phenomenon the P rius effect. The phenomenon has been applied to the built environment via smart ener gy monitoring units sometimes called energy dashboards. Energy dashboards are electronic devices that track real time energy consumption. For new construction there are a host of methods for tracking real time energy use however for retrofit residential projects the options are fewer. Most residential monitoring systems are wirel ess. These systems monitor overall consumption at the main electrical panel with 2 current transformer ( CT ) rings that clamp around the two leads into the panel. For individual plug in loads, wireless current transmitters plug directly into a receptacle and monitors usage. For hard wired loads like ceiling lights, CT rings with wireless transmitters can be clamped around the outside of the lead wires and transmit the data. All of the data collected is displayed on one or more central monitoring stations. These stations usually provide current electrical consumption in terms of k W h and cost as well as the potential to provide historical consumption information. Some electrical monitoring systems can transmit the information to a website so users can have access to the information away from the house (Wilson 2008). Energy dashboards do not save energy directly but they can influence the behavior of the energy consumer. In 2006 and 2007 the Pacific Northwest National Laboratory (PNNL) in Washington State did a study in which they provided 112 home owners with real time energy consumption for their home. Over the course of the study the researchers found that on average the home owners reduced their consumption by 10 % A similar study was done in 2006 at the University of Oxford and the energy savings were found were consistent with the PNNL study

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37 Photov oltaic s olar p anels When non industry people are questioned about the gree n building movement often times the first thing that comes to mind is solar panels. While the existence of solar panels is widely known the specifics of how they work are not nearly as well understood. There are several different designs however the most common solar modules are made from silicon photovoltaic cells. The process for creating them is very precise which has led to prohibitively high cost in the past. C rystalline silicon is cut into round disks or wafers not more than a centimeter thick. T he wafers are then carefully polished and treated to repair any imperfections created in the cutting process. After this process, chemicals called dopants are added to increase the charge of the polished wafer. Conductors are then applied on top of the w afers in a grid like pattern. This grid is visible on an assembled panel. Having the grid applied uniformly increases the efficiency of the unit. The conductors function is to capture the loose electrons from the wafers. If the grid is spread too far a part the conductors will not take advantage of all of the free electrons. If the grid is too dense it detracts the amount of solar energy that reaches the wafers and adds unnecessary cost to the unit. A sheet of non tinted glass is then applied to the to p of the panel. The glass is to allow solar energy through but at the same time protect the wafers and conductors from damage. On the underside of panel a thermally conductive panel is applied. Similar to the glass the underside panel protects the wafer s and conductors from physical damage. However, unlike the top glass the underside panel needs to be very thermally conductive. Most solar energy not converted to electricity is transformed to heat. Excessive heat buildup can damage the unit as well as reduce efficiency The underside panel must be a good medium to transfer this heat away from the wafers and conductors to the underside of the panel where the heat can be dissipated by the outside air (Solar Panel Information 2010)

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38 These cells produce el ectricity directly from the suns energy without the use of a secondary medium. Sunlight contains energy in different forms and wavelength. One such form is the movement of photons. The photons strike the silicon molecules and essentially knock electrons loose. The movement of electrons is the definition of electricity so the capturing of these loose electrons by the integrated conductor grid is what generates the power. This process is called the photo electric effect (Solar Panel Information 2010). As a single panel does not create much electricity, multiple panels are tied together. It would seem intuitive that the more panels you have the more amperage created but it all depends on how they are wired together. Panels can be tied together in two different configurations; either in parallel or in series. Both produce electricity but have significant differences in their voltage and amperage which obviously is important depending on what is being powered. When a panel is said to be in parallel the positive terminal. Similarly the negative terminal s negative terminal. In this configuration voltage remains constant but the amperage is the sum of each panel. For example, assume you have 10 panels connected together in a parallel configuration and each panel is 12 volts and produces 5 amps. The cumulative output would be (10 panels x 5 amps) 50 amps at 12 volts. When a panel is said to be connected in series the configuration the amperage is con stant but the voltage is cumulative. For example, in the scenario above connecting in series would have a voltage of 120 (10 panels x 12 volts) at 5 amps. The distinction is important because of what the panels may be powering. 12 volt is very common fo r low voltage devises like exterior LED lighting, access control hardware or fire

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39 alarm devises. 120 volt is used for most interior plug in appliances and common electronics. Another important detail with photovoltaics is that the electricity produced is direct current or DC. This is the same as the power generated from a car battery. However because of the excessive electrical waste created when transferring DC power great distances the national power grid is on alternating current or AC. As such, an inverter in needed to change DC to AC if tying the panels into a buildings electrical system (Solar Home 2010). An obvious disadvantage to photovoltaics is that they only create electricity during daylight hours. The traditional answer to this is to add batteries as an intermediate step between when power is generated and when it is needed. This is similar to the battery in automobiles except the source of the power is the engine through the alternator instead of solar panels however the technology is st ill well founded. However as an alternative to this, many municipalities have been offering to buy excess electrical power from private solar arrays when generation exceeds on site demand. Gainesville Regional Utilities participates in this program and o ffers to pay $.12/ k Wh for residential property ( Roland 2008 ). In this scenario currency in the form of credits against future energy use take the place of batteries as the intermediate step between generation and use. This type of system has several adva ntages. The first advantage is obvious as it eliminates the need for expensive and environmentally questionable batteries. Another advantage has to deal with the timing of solar generation. For municipal power generation the peak times are during normal working hours. HVAC, lighting and all other modern necessities have the highest draw. At night, when activity is greatly reduced power demand drops. Because of the head and shoulders shaped demand curve, municipalities need to build the infrastructure to support peak demand to prevent uninterrupted service but have it idle

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40 produces power concurrent to when it is needed the most. An opportunity exists for municipalities to reduce the cost of added electrical power infrastructure as populations increase if they require solar power production on new developments. If existing peak demand remains constant in the face of additional population then existing infrastructure will not need to be upgraded. These budgeted (or unbudgeted but future anyway) funds could be used to mitigate the upfront cost of solar power (Solar Panel Information 2010). E ffects of Specific Climates on EE Ms The core principle of sustai nability is to have a close synergetic relationship between the built and natural environment. Working in harmony with the natural environment is also a good approach to energy conservation. However, throughout the Earth there are some vastly different t ypes of climates. It is logical to think that to minimize a h Ms should be appropriate for its specific climate zone. Of the eight unique climate zones recognized by the Department of Energy, the entire state of Florida is categorized as hot/humid. As the name suggests the hot/humid climate zone has above average temperature and humidity when compared to the rest of the country. As such the built environment will be expending a large percentage of its energy budget to mov e heat and remove water vapor from the indoor air. Solar energy is abundant in this climate zone which is can be a double edge d sword. Solar radiation can be a significant heat load adding to energy consumption; however, long day light hours create oppor tunities to replace artificial light with natural light. This creates the dual benefit of reduced energy use and improved light quality. Additionally hot/humid climates are idea l for photovoltaic power generation and solar water heating as the long days maximize the solar exposure and the frequent rains help keep panels clean. Hot/humid climate zones are more temperate year round which makes natural ventilation a possibility. Climate considerations are in promoting simple design approaches,

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41 rather than energy (Givoni 1998). Table 2 1. Energy Star Recommendations for Residential HVAC Settings Setting Time Set Point Temp : Heat Set Point T emp : Cool Wake 6:00 am < 70 degrees > 78 degrees Day 8:00 am Set back at least 8 degrees Set up at least 7 degrees Evening 6:00 pm < 70 degrees > 78 degrees Sleep 10:00 pm Set back at least 8 degrees Set up at least 7 degrees Figure 2 1. Departme nt of Energy Residential Energy End Use Splits

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42 Figure 2 2. Before a nd After Blower Cleaning. Image from C CS LLC. o f Gainesville, FL

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43 CHAPTER 3 RESEARCH METHODOLOGY Overview In this chapter the procedures for how the data were collected, analyzed and used to pr oduces the research conclusions will be elaborated on. There are four areas in which data were collected. The first two dealt with common energy efficiency measures (E E Ms) and typical characteristics of Florida housing. The others dealt with the effecti veness and cost of the EE Ms on a typical Florida home. These are directly affected by the results of the first two. Once all of the data were collected and analyzed a matrix was provided to illustrate the results in terms of immediate capital cost, effec tiveness in kilowatts conserved and return of investment duration. C ommon Energy Efficiency Measures The literature review chapter provided a topical review of the research that has been conducted on measures that will reduce energy consumption in a home. The first step in the research was to identify a list of commonly used measures appropriate for Fl Many of the EE M identified had practical applications in the commercial sector. Because of the unique properties of a residence, many of those measures were not commonly use d in the residential sector. EE M which were solely tailored for commercial construction were omitted fro m the study. Some identified EE M were highly theoretical and did not have a history of prac tical applications. Th ese EE M s were also omitted from the study. The EE Ms examined were primarily those that had well established track records of yieldin g documented energy savings. EE Ms endorsed by established organizations like Energy Star the U S Department of Energy and the U S Green Building Counsel were included on the list. The only filter that would preclude an EE M endorsed by one of these established organizations was if the measure was exclusively designed for conditions not found in Florida. An example of th is type of

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44 precluded measure would be geothermically heated water like that found in Iceland. Any preconceived notion or public perception that an EE high was ignored. To determine the cost eff ectiveness of an EE M was the purpose of the study and unsupported opinions were not allowed to influence the findings. T ypical Florida Housing To determine if the EE Ms were effective, a quantification of typical single family housing in Florida needed to be established The state of Florida is fortunate to have the Shimberg Center for Housing Studies which is a vast clearing house for residential housing data. With the resources of the Shimberg Center, the US. Census Bureau and the U S Energy Information Agency a lis t of common characteristics of Florida housing was created. With this information a typical Florida house can be modeled. This research calls this typical house the Florida houses. Each of the specified characteristics are characteristics that are shared by at least 50% of al l Florida houses. All of the EE Ms were tested for effectiveness and estimated for cost using the Model House. The use of the Model House prov ides a baseline in which to consistently measure the com parative effectiveness of the EE Ms. To assist in the visualization of the Model House and to more accurately quantify the cost estimates, a 3D model was created. The 3D model is a rudimental buildin g plan and contains generic building information. In addition to the specified characteristics identified in the Model House design, all dimensions, wall heights, insulation R values with locations, and an exterior wall section were provided. The 3D mode l provides the necessary information to accurately estimate the cost of each of the E E Ms. The 3D model also provides two additional peripheral benefits not related to this research. First, the 3D model provides a graphic repres entation of how the EE Ms wo rk. An example is that landscaping is not intuitively thought of as an EE M.

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45 However, the 3D model can show that if a certain height tree is planted close to a window on the East or West elevation it can limit the solar heat gain without significantly imp acting the exterior view. The other secondary contribution is that i t provides information on how EE Ms can impact the aesthetics of a home. Landscaping again can be a means of reducing energy consumption while also beatifying the home. However, a solar panel array can also reduce the demand on the central energy grid but can have a negative aesthetics reaction by the home owner. It is important to note that for this research aesthetics was not a factor when determining effectiveness. Effectiveness of EE Ms The core of this research was focused on the ef fectiveness of the identified EE Ms and their cost in relation to that effect iveness. The measure of each EE M was solely based on how much energy (measured in kilowatts) was reduced. The analysis was done by comparing the energy con sumption before and after the EE M was implemented. In this study the baseline was the energy used in the Model House. To calculate energy consumption two methods were implemented. First, an energy modeling software package fr om Elite Software Development, gy Audit was largely used for EE Ms that affected the entire house. These global measures include insulation improvement, HVAC upgrades, and lighting loads, among others. However, the re are many measures which reduce the electrical draw on small devices and have smaller reductions for singular applications but in cumulative have a significant impact. An example would be the reduction in the standby power draw (sometimes called the vam pire draw). These measures may not be able to be calculated on a software package designed for global energy reductions so manual calculations for these specific measures were completed.

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46 Cost Estimates of EE Ms The second core component of this research was the estimate of the cost of each EE M. With the aid of the 3D model actual units, distances, and logistical data can be taken off and used Means. The medium t o gather the RS Means unit costs was through their published catalogs and their online pricing software, CostWorks. The specific published catalogs used were RS Means conditions, insurance rates, and supervision were also added to the estimates. M atrix of Results Once the EE Ms were identified, reviewed for effectiveness, and priced a m atrix was created to illustrate the r esults. The matrix ranks the EE Ms in order of their cost effectiveness ratio (CER). The cost effectiveness ratio was defined as the total initial capital expense divided by annual cost savings in energy (CER = capital expense/annual savings). The energy cost was based on the average energy cost per kilowatt hour in the state of Florida. Additionally, based on current finance rates the length of time to return to the owner the initial capital expense was provided.

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47 CH APTER 4 RESULTS AND ANALYSIS O verview The results and analysis is divided into two main sections. The first section elaborates on owners. The second section uses the i nformation compiled in the first section to determine effectiveness and cost. R esults and Analysis: Section One Typical Florida Single Family Housing To determine the common characteristics of Florida housing, information from The Shimberg Center for Affordable Housing (2010), U.S. Census Bureau (2006 2008), and the U.S. Energy Information Administration (2005) was collected and analyzed. The characteristics found in typical single family housing were separated into four categories; General Informat ion, Construction Characteristics, Appliances, and Furnishings. When creating the list of common characteristics reasonable extrapolations of the data were needed. For example the average Florida house hold size is 2.5 people. To create a realistic scen ario having a half of a person is impossible so the model house rounded up to 3 people. Similarly the average Florida house has 2.38 bedrooms. Having a fraction of a bedroom would not create a realistic model so as the total house hold size was rounded u p so also was the number of bedrooms. This is a limitation to the Table 4 1. Another important component in def ining a typical Florida house is the construction characteristics. The characteristic relate directly to the structure and construction methods used

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48 when building the residence. A summary of the construction characteristics can be found in Table 4 2. Ano ther key component of the typical Florida house is its appliances. The appliances represent non HVAC residential equipment used to satisfy basic human needs like hygiene, cooking, and cleaning. Entertainment or business equipment is included in another c ategory to follow. The appliance category is extremely important as much of the monthly energy budget is used with these de vices. Table 4 3 provides the typical appliances for a Florida single family house. Home equipment that is related to personal ent ertainment or business has been categorized in this research as furnishings. Similar to the appliance category, furnishing can be a significant portion of the home owners monthly utility cost. In Table 4 4 a summary of common furnishings found in Florida single family homes is provided. 3D Model Once the data was collected to identify what the characteristics of typical Florida house are a 3D building information model (BIM) was needed (Figure 4 1) On the surface creating a 3D model may not seem necess ary however it aided the study in three key ways. First the 3D model was transformed into a 2D floor plan (Figure 4 2) The 2D information was then used to do quantity take offs for the EEM s cost estimates. The second f unction that the 3D model was use d for was to create a simulated structure in which to test the EEMs. An example of this was when testing the savings associated with LED lighting. Individual rooms with specific sizes and light intensities were needed to simulate the lighting power use. Without the model there would not be enough specific data to accurate ly simulate the baseline energy use or the effect of the applied EEM. The third benefit of using the 3D model is that it helps establish the parameters of the experiments. Many charact eristics of the model house like the building shape or lighting

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49 location s are most accurately and easily illustrated graphically. The 3D model documents the parameters of the experiment and allows for the results of the study to be reproduced and built up on for future research. There are many different 3D building information modeling (BIM) software packages available. For this study Home Designer by Chief Architect Software was used. This software package was selected because it is designed for resident ial applications, is easy to use, has a large library of preloaded building components and is inexpensive to purchase. Home Designer is not nearly as power ful as Revit Architecture by Aut odesk however Chief Architect Software does make commercial grade ve rsions of Home Designer that may be closer. As of the November 2010 the package could be purchased for 99 dollars which was comparable to other competing products with similar levels of sophistication. In addition to the three core benefits of using a 3D model mentioned above, using Home Designer and its preload library of building components landscaping, furniture, paint col ors and finishes created a more realistic representation of an actu al real world house (See Figure s 4 3 through 4 7 ). Common Energy Saving Measures The second set of information that needed to be collected in the first section was the list of common energy saving measures. These measures were identified in several est ablish green organizations like the U S Department of Energy, Energy Star and the U S Green Building Council. The following list provides a summary of the common EEMs tested on the model house. Space c onditioning Ceiling Fans: Raises the temperatur e that house residences are comfortable at.

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50 HVAC Tune Up (re commissioning): Re commissions HVAC equipment so that it operates more efficiently. Leaking HVAC Ductwork: Reduce the air loss through ductwork so that more cool air is delivered to conditioned space and not lost in unconditioned space. High SEER AC Unit: Replace existing unit with a high efficiency HVAC unit. Water h eating Low Flow Shower Heads and Aerators: Reduction in water reduces energy needed to heat it. Solar Water Heating: Using sol ar energy to heat water instead of using electrical energy. Building e nvelope Window Film: Reduces solar heat gain through windows and glass openings. Blow In Attic Insulation: Increasing insulation in attic and lower heat gain into conditioned space. R etro Foam for Wall Insulation: Seals penetrations in walls to reduce air infiltration. Low E Glass: Replace existing windows with higher efficiency windows. Window Awning: Reduces solar heat gain through windows by blocking direct solar energy. Light Tubes / Skylight: Reduce the need for artificial light by taking efficient advantage of natural lighting. Strategically Placed Landscaping: Reduces solar heat gain through windows when placed so that the shade provided reduces solar heat gain through gl ass openings. Lighting, a ppliances, m iscellaneous e lectrical l oads Compact Fluorescent Lights: Use of high efficiency lighting to reduce energy consumption. LED Lighting: Using high efficiency light emitting diode (LED) type lighting to reduce energy co nsumption. Appliances: Replace existing appliances with high efficiency, energy star rated appliances. Specific appliances to be replaced are the clothes washer, refrigerator and dish washer. Home energy m anagement

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51 Standby Power Loss: Pow er used when devices are plugged in but not being actively used. Programmable T Stats: Manages HVAC unit so it reduces run time when not needed. Occupancy Sensor: Automatically turns off lights when residences are not in the room. Energy Meter: Allows h ome residence to be informed of real time energy use so that they can make behavior changes. Photovoltaic Solar Panels: Adding energy producing solar panels to reduce the demand on the central energy grid. R esults and Analysis: Section Two Effectiveness Overview The second section of this chapter uses the compiled data collected in the first section to measure the effectiveness and cost of each EEM. The effectiveness of each EEM was measured in total reduction in electrical consumptions using the Model House as a baseline. A detailed summary of the Model Houses energy consumption can be found in Appendix A Each was either done by computer simulation or by manu al calculations. As a general rule, EEMs that had more global impacts like with attic insulation were computed using the computer simulation. To calculate the effectiveness for smaller or device specific EEMs manual calculations were used. Energy Modelin g Software eQ UEST Similar to the BIM software available there are many different energy modeling programs to choose from For this study eQUEST version 3.64 was used. eQUEST is an acronym for QU ick E nergy S imulation T ool. The software was selected f or several key reasons. First, it is endorsed by the U S Department of Energy and a favorable review of its performance can be found on the DOE website ( US DOE 2011 ) Additionally, eQUEST is the energy modeling software taught at the M.E. Rinker Sr. Sch ool of Building Construction at the

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52 University of Florida. The development of the software was paid for by the state of California and made available to the public at no cost The package provides whole building modeling for both resi dential and commerci al projects It comes with a large library of preloaded building components, schedules, equipment performance data and default settings creating an environment where accurate energy models can be created by novice energy modelers The program also allow s the user to create custom building assemblies and unique occupancy schedules making the software ideal for this study (Figure 4 8) eQUEST d a ta c ollection To create a model in eQUEST there are steps or levels of input required. The first step is the c ollection and organization of the building characteristics data. Much of th e building data came from the U S Census Bureau Shimberg Center and the EIA as described earlier in the chapter. While t here was overlap between the agencies the U S Census pro vided the basic characteristics of the occupants, the Shimberg Center described the building construction type and components and the EIA outlined energy use patterns. In addition to these organizations the 1987 Florida Energy Code was used to supplement missing details of some construction component The 1987 code was used as the median Florida house was built in 1988 and was assumed to be permitted the year before. Where modeling inputs like building perimeter length were not available assumptions wer e made and documented in the building protocol (see Appendix R). eQUEST b uilding g eometry Once the building and occupant data is collected the energy model can start to be created. The software package Home Designer was used to create a floor plan. Fro m the floor plan a p line drawing was then created in AutoCAD by Autodesk. The p line drawing traced the exterior

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53 perimeter as well as the outline of the interior rooms. The AutoCAD file was then imported into eQUEST and u pe (Figure 4 9) eQUEST building components As mentioned earlier, eQUEST comes with an extensive library of preload building components as well as the ability to create custom components or assemblies. This study required the use of both functions. For example, in 1987 the minimum insulation value required for exterior walls was an R 4. This can be accomplished stucco wall assemb ly and as such is not included in the eQUEST library. However, to accurately model the energy performance the wall components were selected from the library and a custom assembly was created. In some cases w h ere specific construction data was not availab le b uilding components out of eQUEST ere used. For example the specific type and thermal properties of the typical Florida house front door was not available. For this case an insulated metal door was assumed and the average thermal properties of this type of door were pulled from the library and included in the model (Figure 4 10) eQUEST zones and schedules A critical part of energy modeling is the creating of zones and schedules. For this study a zone is synonymous with an individual roo m. Zones provide the boundaries for the different lighting intensities and equipment energy use levels The z one s boundaries are created by importing an AutoCAD file in eQUEST similar to the creation of the building shell. The specific characteristics of the zone can the n be input into the program. In addition to building zones schedules are a critical part of energy modeling. The energy draw for lighting is different at 9:00am than at 9:00pm. Similarly the energy need for home equipment is different on a workday

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54 than from a weekend. A schedule simulates these fluctuating energy use patterns and allows eQUEST to model the effects (Figure 4 11) eQUEST energy simulation Once all of the information has been entered into the program and a model is cre ated a n energy simu lation audit can be run. eQUEST will generate a report that shows the energy used per month broken down into the major energy use categories. The energy use in the baseline Model House can be seen in Appendix A. To test the effectiven ess of the different EEMs a copy of the baseline energy model was created. The copy of the energy model is then modified to reflect the implementation of the EEM. An energy simulation audit was then run on the new energy model and compared with the basel ine. The difference in energy use between the new energy model and the baseline is the net energy savings of the EEM. Energy Efficiency Measures The following paragraphs provide a description of th e EEMs tested The majority of the EEM s tested used the e nergy modeling software to determine the reduced energy consumption The results of each of the EEM s energy simulation audits can be found in Appendix B Q. However, for some EEM s it was more appropriate to do a manual calc ulation of the energy reductio n The manual calculations are show below with the respective EEM. Space Conditioning Ceiling fans This EEM employed ceiling fans to reduced energy consumption by raising the air temperature that the home occupants are comfortable at by three degrees. In the baseline model there is only one ceiling fan in the house located in the central living room. This EEM adds a ceiling fan in each of the three bedrooms. This could potentially be a means of reducing the heat load during the winter months by reversing the fan direction and drawing down warm air from

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55 the ceiling space. However, using the fan in the winter months could also create a wind chill effect. For this reason this EEM was assumed only to be applied during the warmer months. The calculation of energy savings was a combination of the energy modeling software and a manual calculation. The software was used to calculate the reduced cooling load T he software does not model specific pieces of equipment well so the direct energy draw from the three fans was calculated manually. The annual savings in energy cost is $50 .63 with an initial capital input of $888.87. The energy savings and capital expense summary can be seen on Tables 4 5 and 4 6 The energy model simulation using this EEM can be seen in Appendix B The calculation for the added load for the 3 fans is as follows. Reduced HVAC load from Computer Simulation Model = 1,420k W h/year Additional Electrical Load from Ceiling Fan 75 W atts/hr 12hr/day *365days/year 3 fans = 985,500 W atts or 985.5k W h Total Energy Conserved = Heat Load Reduction Added Direct Fan Consumption 1,420k W h 985.5k W h = 434.5k W h Energy Cost Savings 434.5k W h $.1165/k W h = $50.62 HVAC tune up (re commissioning) The HVAC Tune up EEM provides the HVAC unit a The operation is usually performed by a professional contractor who will provide services like recharging the refrigerant, cleaning the coils, lubricating mechanical components, adjusting belts and removing air obstruct ions from the condensing unit. By servicing the unit the efficiency can be increased by ten percent but for this research a more conservative five percent will be

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56 assumed. The annual savings in energy cost is $44 .27 with an initial capital input of $528. 58. The energy savings and capital expense summary can be seen on Tables 4 7 and 4 8 The energy model simulation using this EEM can be seen in Appendix C Sealing leaking HVAC ductwork The Department of Energy reports that in many older homes there is an average of 20% has a similar 20% loss. This measure will include repairing torn ductwork, resealing duct connections, un kinking flexible ductwork and reseal ing the air handler resulting in a reduction of air loss to 10%. Often times the cause of the leaks is due to duct tape that has failed over time. The assumed repair includes in part replacing failed duct tape with a mastic duct adhesive that meet s curre nt Florida code. A 50% reduction in air loss is a conservative value used to account for sections of ductwork and the air handler that are inaccessible for repair. The annual savings in energy cost is $87.38 with an initial capital input of $1,591.71. T he energy savings and capital expense summary can be seen on Tables 4 9 and 4 10 The energy model simulation using this EEM can be seen in Appendix D High SEER AC units The median Florida single family house was built in 1988. At that time, the Florid a Energy Code required a minimum HVAC SEER of 9. However, because of the age of the house it is likely that the HVAC unit would have had to have been replaced. For this simulation it is assum ed that the Model House replaced in 2003 with a SEER 12 but has regressed to a SEER 10. This measure will replace the M odel H Energy Star Rated SEER 14 unit. The annual savings in energy cost is $250 .48 with an initial capital input of $3,231.41. The energy savings and capital expense summary can be seen on Tables 4 11 and4 12. The energy model simulation using this EEM can be seen in Appendix E

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57 Hot Water Low flow shower heads and aerators The energy required to heat water represents a significant percentage of a home energy consumption. In 2010 the DOE reports that water heating represents 11% of all residential energy use and is only behind space heating and cooling in total energy draw (Figure 2 1). For this EEM two low flow shower heads and faucet aerator s will be applied to both bathrooms in the Model House to reduce hot water demand. The total hot water used was reduced from 28,250 gallons/year to 22,995 gallons/year or approximately 19%. This calculation only takes into account the hot water reduced. However, this measure will also have a peripheral benefit of reducing unheated water use as well which is not considered in this energy consumption study The annual savings in energy cost is $50 .10 with an initial capital input of $49.52. The energy sa vings and capital expense summary can be seen on Tables 4 13 and 4 14. The energy model simulation using this EEM can be seen in Appendix F. Solar water heating For this measure a solar water heating system will be used instead of an electric storage tank style water heater. The solar unit will have a collection plate on the roof and will circulate heated water to a central 120 gallon storage tank. The storage tank will have two electric backup heating elements used for 20% of domestic water heating Th e backup heating will be used when the storage tank is depleted of hot water without sufficient tim e to heat additional water with solar energy. This is likely to happen with large immediate hot water draws or with extensive periods not conducive to solar thermal harvesting The annual savings in energy cost is $210 .87 with an initial capital input of $5,604.99. The energy savings and capital expense summary can be seen on Tables 4 15 and 4 16

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58 Building Envelope Window film This EEM provides a low E wi ndow film on all exterior windows. The product used was Low E film is used to reduce the amount of solar heat gain. Although advances have been made with spectrally selective film, the reduced solar heat gain us ually also reduces the amount of visible light albeit not necessarily to the same proportion. The specific product used for this study with the window glazing has a combined visible light transferred of 69%, an infrared rejection of 97%, ultraviolet refle ction of 99.9% and a shading coefficient of .58. The annual savings in energy cost is $55.59 with an initial capital input of $568.87. The energy savings and capital expense summary can be seen on Tables 4 17 and 4 18. The energy model simulation using this EEM can be seen in Appendix G. Increased attic insulation In this EEM additional insulation will be added to the attic floor. The 1987 Florida Energy Code required a minimum of R19 insulation be used for residential homes. For this simulation an ad in insulation was added. This additional insulation will increase the total R value to 42. This is slightly higher than the DOE recommendation of R38 for this ulation is purchased in. The annual savings in energy cost is $10 .49 with an initial capital input of $1,101.83. The energy savings and capital expense summary can be seen on Tables 4 19 and 4 2 0 The energy model simulation using this EEM can be seen i n Appendix H Retro foam in wall s In this measure air penetrations in the wall are located and sealed with expansive foam insulation. The process involves using thermal cameras and other heat detection equipment to

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59 locate areas of high outside air infiltr ation. At these points holes are drilled into the CMU cavities and filled with expansive foam. Often times these locations are at electrical junction boxes where the block has been pene trated on one side to provide space to install the box. Window perim eters are another area of high air infiltration that can be sealed with foam or caulk. Despite the added foam insulation the R value added to the walls is marginal In this simulation the expected effectiveness of the retro foam is that it will reduce th e air infiltration of the home by 30% overall The annual savings in energy cost is $20 .97 with an initial capital input of $7,217.69. The energy savings and capital expense summary can be seen on Tables 4 2 1 and 4 2 2 The energy model simulation using this EEM can be seen in Appendix I Low E glass In this measure the windows are replaced with double panel Low E glass. In addition both sliding glass doors are replaced with new doors with similar Low E gla zing T he Low E between the glass layer s The annual savings in energy cost is $51 .26 with an initial capital input of $5,647.52. The energy savings and capital expense summary can be seen on Tables 4 2 3 and 4 2 4 The energy model simulation using this EEM can be seen in Appendix J Awnings For this measure a fabric window awnings will be applied to all of the windows and sliding glass doors on the East, West and South Elevations. The awnings will be used to re duce the amount of thermal energy penetrating the building envelope and lower the cooling load. The awnings have an aluminum frame anchored to the CMU wall. The frame supports a fabric covering which provides the shading. The awning covers the length of the window opening and ex tends horizontally 3 feet from the face of the wall The annual savings in energy cost is $64.08 with an initial capital input of $1,691.49. The energy savings and capital expense summary can

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60 be seen on Tables 4 2 5 and 4 2 6 Th e energy model simulation using this EEM can be seen in Appendix K Skylight located in the dining room and the living room. A five foot light w e ll was required to gain studs with a level 4 painted drywall finish. Unlike all of the other EEMs tested this measure had a negative energy savings. This EEM would add to the annual energy consumption of the house. The minimal amount of lighting savings was negated by the additional load placed on the air conditioning system. The annual savings in energy cost is $<11 .65> with an initial capital input of $2,998.19. The energy savings and c apital expense summary can be seen on Tables 4 2 7 and 4 28 The energy model simulation using this EEM can be seen in Appendix L. Strategically placed landscaping In this measure two large trees are strategically placed to provide shading at glazed openin gs. This study assumed the trees were red maples as this species has a full canopy and large broad leaves to maximize the shading. However, the results of the experiment would be similar for any tree that had similar shading characteristics. The trees a re specifically located outside the windows of the East and West bedrooms. The energy simulation was run at the point when the trees are just planted however the savings will increase as the trees grow in size. The annual savings in energy cost is $11 .65 with an initial capital input of $1,074.87. The energy savings and capital expense summary can be seen on Tables 4 29 and 4 30. The energy model simulation using th is EEM can be seen in Appendix M

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61 Lighting, Appliances, Miscellaneous Electrical Loads Co mpact fluorescent lights For this experiment an average light l evel of 12 foot candles was assumed Additionally, the baseline model assumed that the primary source of light in the house came from 60W incandescent lamps which emit approximately 800lumens. With these assumptions the total number of incandescent light bulbs can be calculated by multiplying the house area (1 ,80 3 sqft ) by the light intensity ( 12 foot candles ) and then divided by the per bulb lighting intensity ( 800 lumens ) This calculation r eveals that 27 bulbs are need ed to provide the Model House an average lighting intensity of 12 foot candles. If you multiply the total number of bulbs (27) by their wattage (60) and then divide the result by the area of the house (1,80 3 ) you would derive the average power intensity of .9 Watts/sqft. eQUEST uses w atts/sqft as the unit of measure for calculating lighting intensity. For this EEM the 60 W incandescent light bulbs were replaced with high efficiency compact fluorescent light bulbs. The CFL as sumed used 14 W to provide an equivalent light output of 800lumens each. The average light level before and after the EEM was implemented remained 12 foot candles. The annual savings in energy cost is $475.32 with an initial capital input of $59.42. The energy savings and capital expense summary can be seen on Tables 4 3 1 and 4 3 2 The energy model simulation using this EEM can be seen in Appendix N A limitation to this study is that it do es not take into account the risk of damaged lamps If CF L lam ps are damaged before their expected lifespan it will influence the proforma of the EEM. LED lighting This measure is very similar to the CFL measure however instead of CFL lighting the incandescent lamps are replaced with LED lamps. However, a key differ ence with LED lighting is that LED lamps do not emit the same lighting intensity as incandescent or CFLs. As opposed

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62 to the 800 lumens emitted from incandescent lamps the LED light bulb assumed only emits 510 lumens This means that it will take 43 bulbs to provide the same lighting level as 27 incandescent bulbs The annual savings in energy cost is $481 .15 with an initial capital input of $2,104.28. The energy savings and capital expense summary can be seen on Tables 4 3 3 and 4 3 4 The energy model si mulation using this EEM can be seen in Appendix O Similar to the CFL this study does not assume any of the LED lamps will be damaged before their expected lifespan However, many of the LED lamps come with 5 year warranties which helps mitigate the risk Energy Star appliances clothes washer This measure is one of three that test the energy savings by using an Energy Star appliance. This specific EEM is for replacing a clothes washer with a new Energy Star model. By using the published data pro vided by the Energy Star website the savings were manually calculated as shown below. About two thirds of the energy saved came from the reduced hot water use. The other third came from the reduced direct energy needed to run the appliance. The cost e stimating of all of the Energy Star appliances came from actual vendor pricing. As RS Means does not track the pricing of Energy Star appliances specifically the website. The annual savings in energy cost is $ 29 .76 with an initial capital input of $627.39. The energy savings and capital expense summary can be seen on Tables 4 3 5 and 4 3 6 Direct Electricity Use Traditional Unit Electricity = Total Loads/Week *52 Weeks 1.242k W h/load 4 loads/week 52 week s *1.242k W h/load = 258.34k W h/year Energy Star Unit Electricity = total loads/Week 52 Weeks 1.272k W h/load 70% 4 loads/week *52 weeks *(1.242k W h/load *(100% 30%)) = 180.84k W hs/year Reduction from Traditional to Energy Star Electricity = Traditional Energy Star 258.34k W h 180.84k W h = 77.50k W hs/year

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63 Energy to Heat Water Traditional Hot Water Use = loads/week 52 weeks/year *gallons/load 2 loads/week 52weeks/year 31.07gallons/load = 3,231.28 gallons/year Energy Star Hot Water Use = loads/week 52 weeks/year *gallons/load 50% 2 loads/weeks 52 weeks/year (31.07 gallons/load 50%) = 1,616 gallons/year Reduction from Traditional to Energy Star Hot Water Use = Traditional Energy Star 3,231.28gallons/year 1,616 gallons/year = 1,616 gallons/year Energy Requi red to Heat Water Heat added to water = Hot Water Temperature Municipal Water Temperature 120 degrees 75 degrees = 45degrees Electrical Energy Required to Heat Water (1,616 gallons/year (8.35lbs/gallon) = 13,494lbs/year 13,494lbs 45 degre es = 607,212btu 607,212btu (1 W h/3.41214btu) (.80 inefficiency) = 142,365 W h or 142.37 k W h Total Energy Conserved = Direct Electrical Energy + Electricity for Water 77.50k W h + 142.37 k W h = 219.9 k W h Energy Cost Savings 255.46k Wh $.1165/k W h = $29.76 Energy Star appliance refrigerator The energy reduced by using an Energy Star refrigerator was the second of three appliances tested. For a refrigerator to receive an Energy Star label it must use 20% less energy than a comparable unit. They define a comparable unit as a similar model with an energy draw of 529kWh/year With this information the manual calculation can be performed as shown below The annual savings in energy cost is $12 .33 with an initial capital input of $712.59. The energy savings and capital expense summary can be seen on Tables 4 3 7 and 4 38 Total Energy Conserved Energy Saved With Energy Star Refrigerator = Traditional Energy Use 20% 529k Wh /year 20% = 105.8k W h/year Energy Cost Savings 105.8k W h/year *.1165/k W h = $ 12.33/year

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64 Energy Star appliances dish washer The reduced energy from using an Energy Star dish washer was the thir d of three appliances tested. See the manual calculation for the savings below. In contrast to the clothes washer approximately on e third of the energy saved comes from w ater heating and two thirds comes from the direct energy need ed to run the appliance. The annual savings in energy cost is $14.02 with an initial capital input of $549.65. The energy savings and capital expense summary can be seen on Tables 4 39 and 4 4 0 Direct Electricity Use Traditional Unit Electricity = Total Cycles/Week *52 Week s k W h/cycle 4.13 cycles/week 52 weeks/year *1.67k W h/cycle = 358.65k W h/year Unit Electricity = Total Cycles/Week 52 Weeks/Year k W h/cycle 4.13 cycles/week *52 weeks/year *1.33k W h = 285.63k W h/year Reduction from Traditional to En ergy Star Electricity = Traditional Energy Star 358.65k W h 285.63k W h = 73.02k W h/year Energy to Heat Water Traditional Hot Water Use = cycles/week 52 weeks/year *gallons/cycle 4.13 cycles/week 52weeks/year 6 gallons/cycle = 1,288.56 gallo ns/year Energy Star Hot Water Use = cycles/week 52 weeks/year *gallons/cycle 4.13cycles/weeks 52 weeks/year 4 gallons/cycle = 859.04 gallons/year Reduction from Traditional to Energy Star Hot Water Use = Traditional Energy Star 1,288.56 gallons/year 859.04 gallons/year = 429.52 gallons/year Energy Required to Heat Water Heat added to water = Hot Water Temperature Municipal Water Temperature 120 degrees 75 degrees = 45degrees Electrical Energy Required to Heat Water (429.52 gallons/year (8.35lbs/gallon) = 3,586.49lbs/year 3,586.49lbs 45 degrees = 161,392btu 161,392btu (1 W h/3.41214btu) *(.8 for inefficiency) = 37,839 W h or 37.8 k W h/year Total Energy Conserved = Direct Electrical Energy + Electricity for Water 73.02k W h/year + 37.8 k W h/year = 110.86 k W h/year Energy Cost Savings 120.32k W h/year $.1165/k W h = $14.02/year

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65 Home Energy Management Standby power loss In the standby power loss EEM a device was used to disconnect appliances from their power source when not b eing actively used. There are a variety of devices on the market but for The intention is that by applying these switches it becomes convenient enough for the resident to disconnect the power when th e home equipment is not actively needed. The concept is that without the switch it would be too inconvenient to disconnect the power and t he resident would elect to leave them plugged in and forego the savings. The devices were placed at the two locations with the highest wasted standby power; the computer station and central entertainment center. See the manual calculation for the savings below. The annual savings in energy cost is $17 .01 with an initial capital input of $38.13. The energy savings and capit al expense summary can be seen on Tables 4 4 1 and 4 4 2 Total Energy Conserved : Number of Units Average Standby Draw Duration 5 units 10 W atts 8 hours = 400 W h/day or .4k W h/day .4k W /day 365 day/year = 146k W h/year Energy Cost Savings 146k W $.1165/k W h = $17.01 Programmable thermostat This EEM provides savings on the homes cooling and heating system by using a programmable thermostat. The programmable thermostat allows the resident to adjust the set point higher (or lower setting dependi ng on the season) when there is not a d emand for space conditioning. Essentially it is a low tech way of making a building produce cooling or heating only when it is needed. The programmable thermostat generally has three set back points. In the case of cooling, the lowest temperature set point is at the period when the building is most likely to be occupied The second lowest set point is after the resident goes to sleep and elect s to raise

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66 the set point to save energy. The highest temperature set poin t would be when there is no one in the building and no need for space conditioning. The annual savings in energy cost is $160 .77 with an initial capital input of $265.41. The energy savings and capital expense summary can be seen on Tables 4 4 3 and 4 4 4 The energy model simulation using this EEM can be seen in Appendix P Occupancy sensor The occupancy sensor EEM reduces the time that lights are turned on when not actively needed The savings comes from reducing direct electrical consumption from the l ight use and from less demand on the HVAC system. In this simulation integrated light switch type occupancy sensors will be installed in all 3 bedrooms, the kitchen, dining room and living room. ASHRAE 90.1, table G3 .2 approximates that the lighting load will be reduced by 10% when using automatic lighting controls. This approximation will be used for this research as well. The annual savings in energy cost is $51.26 with an initial capital input of $475.13. The energy savings and capital expense summa ry can be seen on Tables 4 4 5 and 4 4 6 The energy model simulation using this EEM can be seen in Appendix Q Energy dashboards The use of energy dashboards does not save energy directly but modifies occupant behavior by providing real time energy use fee dback. For this experiment, a n energy dashboard system called the Envi by Power Save Inc was simulated The system includes a wireless transmitter located in the el ectrical panel. In a ddition four 220volt current transformers are used to monitor the en ergy draw from the air handler, condenser unit, water heater, and oven. Also included with the experiment are two 120volt wireless appliance transmitter to monitor the home entertainment center and computer area. The power use information is sent wirele ssly to a portable display that shows current energy use and historical information. The University of

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6 7 O xford did a study and found that a simi lar energy dashboard system reduce the average energy consumption by 10%. For this stud y the same 10% reduction was used. The annual savings in energy cost is $264 .46 with an initial capital input of $1,223.17. The energy savings and capital expense summary can be seen on Tables 4 4 7 and 4 48 Photovoltaic panels In this measure a photovoltaic array w ill be added to the Model House. T he energy produced is less than the house is consuming so a utility buy back option was not considered The average number of direct sunlight hours in Florida is 4.5 hours per day Although there are more daylight hours in a day this number accounts for overcast days, cloud cover, and less intense sunlight near dawn and dusk. The system assumed for this experiment can produce 10 W atts of energy for every square foot of the array at full sun. The system will be mounted o ver the garage where the roof angles toward the south. The annual savings in energy cost is $229 .62 with an initial capital input of $9,793.83. The energy savings and capital expense summary can be seen on Tables 4 49 and 4 5 0 The manual calculation of energy produced can be seen below. Size of unit = length height Total Energy Conserved Array output per hour = size x watts/hour 120sqft 10 W atts/hour = 1200 W atts/hour Yearly energy output = average direct sun rays w atts/ hour 365days/year 4.5hrs/day 1,200 W atts/hour 365days/year = 1,971,000w/year or 1,971kw/year Energy Cost Savings Cost Savings = k W /year .1165 /k W h 1,917 $.1165/k W h = $229.62

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68 Table 4 1. Typical s ingle f amily h ousing: g eneral i nformation St ructural Characteristic Structural Quantity/Affirmation Resident Characteristic Resident Quantity/Affirmation Area Florida Number of o ccupants 3 people Residence t ype Single f amily Tenure in h ouse 6 years Median year b uilt 1988 Median just v alue $149,00 0 Median s ize 1,800sqft Mortgage on h ouse Yes Total r ooms 7 Mortgage/Total i ncome 31% Bedrooms 3 Average utility c ost $131/month Bathrooms 2 Someone home during d ay No Garage 2 car Automobiles o wned 2 Table 4 2. Typical single family h ousing: c ons tr uction c haracteristics Characteristic Quantity/Affirmation Exterior s tructure Reinforced C.M. U. w all Foundation Monolithic concrete s lab Exterior wall f inish Cement stucco with painted f inish Interior w alls Wo od framing with painted gypsum b oard Win dow t ype Single pane glass in f rame Roofing t ype Asphalt s hingle Truss t ype Wood t russ Window /Floor r atio 15% Access to natural g as Yes Use of natural gas in h ouse No Central heat and air s ystem Yes Heat p ump No Area of house c onditioned 100% (excl uding garage) Programmable t hermostat No Large trees shading h ouse No

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69 Table 4 3. Typical s ingle f amily h ousing: a ppliances Characteristic Quantity/Affirmation Oven 1 Self c leaning Yes Integrated r ange Yes Fuel s ource Electric Refrigera tor 1 Frost f ree Yes Top bottom d oor Style Yes Exterior water/i ce Dispenser No Energy Star No S ize 15 18cuft Age 6 years Dishwasher 1 Age 4 years Electric coffee m aker 1 Microwave o ven 1 Clothes w asher 1 Top l oaded Yes Age 5 years Clothes d ryer 1 Fuel s ource Electric Age 5 years Ceiling fans in h ouse 1 Water h eater 1 Fuel s our ce Electric Size 31 49 gallons Age 6 years

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70 Table 4 4. Typical s ingle f amily h ousing: f urnishings Characteristic Quantity/Affirmation Entertainment s ystem Television 2 VCR p layer 1 DVD p layer 1 Cable or satellite d ish Yes Video gaming s ystem No Personal computer s ystem Computers 1 Monitors 1 s tandard CRT Internet a ccess Yes c able or DSL Printer (without fax/copy capability) 1 Stereo s ystem 1 Tab le 4 5. Ceiling fan EEM p erformance Parameters Characteristics Collected s tatistical d ata Required c alculation a ssumptions Value Number of existing f ans X 1 Number of Added f ans X 3 Location of f ans X Master b edroom Guest b edroom 1 Guest b edroom 2 Increase of cooling set p oint X 3 degrees Fan s ize X 48 inches Fan power d raw X 75 W atts/hour Duration fan in on per d ay X 12 hours Calculation Manual/Comp s imulation Savings 434.5k W h/year $50.62/year

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71 Table 4 6. Ceiling f an E EM c ost Energy e fficiency m easure: Additional ceiling f ans Labor Material Item Quantity Hours Rate Subtotal Unit c ost Subtotal Total Ceiling f an 3 1 $49 $147 $120 $360 $506.18 Light k it 3 1 $38 $113 $26 $78 $191.25 Material t ax $0 $0.00 $32.90 Subtotal $730.33 General c onditions 5% $36.52 Over head & p rofit 15% $115.03 Total $881.87 Note: Professional, non union installation Price source was Means Pricing Guide Repair and Remodeling Cost 2005 Geographic Multiplier used was .85 of national F Table 4 7. HVAC t une up (re commissioning) EEM p erformance Parameters Characteristics Collected s tatistical d ata Required c alculation a ssumptions Value HVAC system t ype X Split s ystem Air handl er l ocation X Conditioned c loset Condenser unit l ocation X Outside, ground level Number of u nits X 1 Increased e fficiency X 5 % C alculation Computer s imulation Savings 380k W h/year $44.27/year

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72 Table 4 8. HVAC t une u p (re co mmis sioning) EEM c ost Energy e fficiency m easure: HVAC tune u p Labor Material Item Quantity Hours Rate Subtotal Unit c ost Subtotal Total Basic tune u p 1 $0 $65 $65 $65.00 Additional r efrigerant 1 $0 $175 $175 $175.00 Additional r epai rs 1 $0 $175 $175 $175.00 Material t ax $0 $0.00 $22.75 Subtotal $437.75 General c onditions 5% $21.89 Overhead & p rofit 15% $68.95 Total $528.58 Note: Professional, non union installation. P rice source was Interview with Ron Bennett, o wner of CCS LLC: 352 317 3846: http://climatecontrolservicesllc.com/default.asp. Repair included electrical check, delta T check, blower and amp draw optimization, lubrica te parts, tighten belts, static pressure test and refrigerant check. Table 4 9. Leaking HVAC ductwork EEM performance Parameters Characteristics Collected statistical data Required calculation a ssumptions Value Model House ductwork l oss X 20 % Reduced d uctwork l oss X 10 % C alculation Computer s imulation Savings 750k W h/year $87.38/year

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73 Table 4 10. Leaking HVAC ductwork EEM cost Energy efficiency measure: Sealing Ductwork Labor Material Item Quantity Hours Rate Su btotal Unit cost Subtotal Total Diagnostics t esting 1 $0 $200 $200 $200.00 Blower t esting 1 $0 $200 $200 $200.00 Repair 1 $0 $850 $850 $850.00 Material tax $0 $0.00 $68.25 Subtotal $1,318.25 General conditions 5% $65.91 Overhead & profit 15% $207.62 Total $1,591.79 Note: Professional, non union installation. Price source was Interview with Ron Bennett, owner of CCS, LLC: 3352 317 3846: http://climatecontrolservicesll c.com/default.asp. Repair included pressurizing ductwork to identify leaks, torn or leaking duct r epaired using mastic compound. Table 4 11. High SEER a/c unit EEM performance Parameters Characteristics Collected statistical dat a Required calculation assumptions Value Existing SEER rating X 10 SEER New SEER rating X 14 SEER System t ype X Split DX with direct return Calculation Computer s imulation Savings 2,150kWh/year $250.48/year

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74 Table 4 12. High SEER a c unit EEM performance Energy efficiency measure: New high SEER AC u nit Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Compressor d emo 1 1 $296.85 $296.85 $0.00 $0.00 $296.85 Compressor i nstall 1 1 $170.85 $170.85 $5 52.50 $552.50 $723.35 Cond unit d emo 1 1 $101.15 $101.15 $0.00 $101.15 Cond unit i nstall 1 1 $416.50 $416.50 $777.75 $777.75 $1,194.25 Material tax $0.00 $0.00 $150.51 Permit 1 $0.00 $210.00 $210.00 $210.00 Subtotal $2,676.11 General conditions 5% $133.81 Overhead & profit 15% $421.49 Total $3,231.41 Note: Professional, non union installation. Price source was Means Pricing Guide Repair and Remodeling Cost 2005. Geographic Multiplier used was .85 of national. Size assumed was a 3 ton unit. Table 4 13. Low flow shower heads and aerators EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Baseline hot wa ter u sage X 28,250 gallons/year Hot water u sage with EEM X 22,995 gallons/year Percent r eduction X 19% EEM u sed X Two low flow shower h eads & 2 a erators Water heater l oad X 4,500wh Electric input r atio X 1.3 Municipal water t emperature X 75 degrees Hot water t emperature X 120 degrees Calculation Manual Savings 430k W h/year $50.10/year

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75 Table 4 14. Low flow shower heads and aerators EEM cost Energy efficiency measure: Low flow shower heads and a erators Labor Mate rial Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Shower h eads 2 $0 $18.96 $37.92 $37.92 Aerators 2 $0 $4.29 $8.58 $8.58 Material tax $0 $0 $3.02 Subtotal $49.52 General conditions 5% n/a Overhea d & profit 15% n/a Total $49.52 Note: Home owner installation. website 12/22/10 Shower head assumed was manufactured by Alsons model number 654CPK. Price s website 12/22/10 Aerator assumed was manufactured by Neoperl model number 37.0084.98 Table 4 1 5 Solar water heating EEM performance Parameters Characteristics Collected statistical data Required ca lculation assumptions Value Solar water heating s tyle X Medium temp u nit circulating water Draw of backup h eating Elements X 4,500wh Circulation p ump X Solar p ower Tank s ize X 120 gallon Solar collector s ize X 48sqft Backup heating element u se X 20% Hot water u sage X 25.8 gallons/person/day Calculation Computer simulation Savings 1,810k W h/year $210.87/year

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76 Table 4 1 6 Solar water heating EEM cost Energy efficiency measure: solar water h eating Labor Material Item Quantity H r Rate Subtotal Unit cost Subtotal Total Collector k it 1 16 $28.40 $454.40 $976.50 $976.50 $1,430.90 Tank 1 8 $28.40 $227.20 $935.00 $935.00 $1,162.20 Tank hook up 40 4 $23.05 $92.20 $3.77 $150.80 $243.00 Drainback a ssembly 1 8 $23.05 $184.40 $475.00 $475.00 $659.40 Mounting k it 1 8 $28.40 $227.20 $65.63 $65.63 $292.83 Shipping 1 $0.00 $373.00 $373.00 $373.00 Material tax $0.00 $0.00 $270.49 Permit 1 $0.00 $100.00 $210.00 $210.00 Subtotal $4,641. 82 General conditions 5% $232.09 OH&P 15% $731.09 Total $5,604.99 Note: Professional, non union installation. Price source was from EnergySupermarket.com System assumed was a Sun Earth Active So lar Water Heater Panel. Tank size assumed was 120 gallons. Tank and piping price source was from RS Means, 2010, Residential New Construction Pricing Guide.

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77 Table 4 1 7 Window film EEM performance Parameters Cha racteristics Collected statistical data Required calculation assumptions Value Window film l ocation X All exterior w indows U Value with w indow X .99 Shading coefficient with w indow X .58 Visible light t ransmittance X .69 Calculation Computer simulation Savings 460k W h/year $55.59/year Table 4 18 Window film EEM cost Energy efficiency measure: w indow f ilm Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Window f ilm 15 $0 $35.61 $534. 15 $534.15 c leaning Accessories 1 $0 $0.00 $0.00 Material tax $0 $0.00 $34.72 Subtotal $568.87 General conditions 5% n/a Overhead & profit 15% n/a Total $568.87 Note: Home owner installation. website 12/22/10. Cleaning accessories assumed were Gila Complete Window Film Application Kit model number RTK500SM.

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78 Table 4 19 Increased attic insulation EEM performan ce Parameters Characteristics Collected statistical data Required calculation assumptions Value Original insulation v alue X R19 Increase of i nsulation X R 23 blown in i nsulation Type of i nsulation X in i nsulation Location X Attic f loor over Existing i nsulation Calculation Computer simulation Savings 90k W h/year $10.49/year Table 4 2 0 Increased attic insulation EEM cost Energy efficiency measure: attic i nsulation Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Install i nsulation 1800 1 $0.20 $367.20 $0.27 $489.60 $856.80 Material t ax $0.00 $0.00 $55.69 Subtotal $912.49 General conditions 5% $45.62 Overhead & profit 15% $143.72 Total $1,101.83 Note: Professional, non union installation. Price source was Means Pricing Guide Repair and Remodeling Cost 2005. Geographic Multiplier used was .85 of national. Insulation assumed had an R value of 23 a in.

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79 Table 4 2 1 Retro foam in walls EEM performance P arameters Characteristics Collected statistical data Required calculation assumptions Value Reduction in air i nfiltration X 30% Calculation Computer simulation Savings 180k W h/year $20.97/year Table 4 2 2 Retro foam in walls EEM cost Energy efficiency measure: Retro foam in w alls Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Foam Subcontractor 1984 $0.00 $2.50 $4,960.00 $4,960.00 F inish r epair 1 16 $34.54 $552.57 $100.00 $100.00 $652.57 Material tax $0.00 $0.00 $364.82 Subtotal $5,977.38 General conditions 5% $298.87 Overhead & profit 15% $941.44 Total $7,217.69 Note: P rofessional, non union installation. Price source was Total Comfort Installation, LLC from Jacksonville, FL. Material used was spray polyurethane foam.

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80 Table 4 2 3 Low E glass EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Baseline window t ype X Single c f rame without b reaks New window t ype X Double Low E (e3 = .2) Frame with insulated b reak Window/Floor s pace X 15 % Calculation Computer simulation Savings 440k W h/year $51.26/year Table 4 2 4 Low E glass EEM cost Energy efficiency measure: Low E window r eplacement Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Wi ndows 6 1 $81.05 $486.29 $276.25 $1,657.50 $2,143.79 Sliding g lass d oor 2 1 $223.13 $446.25 $531.25 $1,062.50 $1,508.75 Finish r epair 8 2 $34.53 $552.50 $10.00 $80.00 $632.50 Material tax $0.00 $0.00 $182.00 Permit 1 $0.00 $210.00 $210.00 $ 210.00 Subtotal $4,677.04 General conditions 5% $233.85 Overhead & profit 15% $736.63 Total $5,647.52 Note: Professional, non union installation. Price source was Means Pricing Guide Repair and Remode ling Cost 2005. Geographic Multiplier used was .85 of national. Window assumed was a double hung, two light double glazed aluminum window with screen. Sliding glass door assumed was an insulated door with an a luminum frame.

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81 Table 4 2 5 Awning EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Elevation overhangs l ocated X East elevation West elevation South elevation Depth of o verhang X 3 feet Overhang t ype X Fabric over aluminum frame Calculation Computer simulation Savings 550k W h/year $64.08/year Table 4 2 6 Awning EEM cost Energy efficiency measure: awnings over o penings Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Window a wning 4 1.00 $27.63 $110.50 $165.75 $663.00 $773.50 Sliding glass d oor 64 1.00 $2.77 $177.34 $5.70 $364.48 $541.82 Material tax $0.00 $0.00 $85.50 Subtotal $1,400.82 General conditions 5% $70.04 Overhead & profit 15% $220.63 Total $1,691.49 Note: Professional, non union installation. Price source was Means Pricing Guide Repair and Remodeling Cost 2005. Geographic Multiplier used was .85 of national. finish. Sliding glass awing assumed was a roll up type.

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82 Table 4 2 7 Skylight EEM performance Table 4 28 Skylight EEM cos t Energy efficiency measure: s kylight Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Skylight 2 1 $83.73 $167.45 $293.25 $586.50 $753.95 Demo/Protection 2 3.3 $34.53 $227.91 $15.00 $30.00 $257.91 Light well f raming 2 4 $34.53 $276.25 $75.00 $150.00 $426.25 Light w ell Drywall 2 3 $34.53 $207.19 $45.00 $90.00 $297.19 Light well f inishing 2 2.5 $34.53 $172.66 $15.00 $30.00 $202.66 Roof f epair 2 1 $127.50 $255.00 $61.20 $122.40 $377.40 Material tax $0.00 $0.00 $57.62 Permit 1 $0.00 $110.00 $110.00 $110.00 Subtotal $2,482.97 General conditions 5% $124.15 Overhead & profit 15% $391.07 Total $2,998.19 Note: Professional, non union installation. Price source was Means Pricing Guide Repair and Remodeling Cost 2005. Geographic Multiplier used was .85 of na tional. Parameters Characteristics Collect ed statistical data Required calculation assumptions Value Size of s kylights X Location X Dining r oom Living r oom Light well d epth X Skylight c onstruction X Dome aluminum frame with breaks and double acrylic g lazing Calculation Computer simulation Savings Negative 100kWh/year Negative $11.65/year

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83 Table 4 29 Strategically placed landscaping EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Number of existing shading t rees X 0 Number of t re es a dded X 2 Location X East & West Elevation Trees s pecies X Red Maple 16 with diameter truck. Reduction in solar load at east and west w indows X 50% Calculat ion Computer simulation Savings 1 00 k W h/year $1 1.65 /year Table 4 3 0 Strategically placed landscaping EEM cost Energy efficiency measure: Strategically placed l andscaping Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Red m aple 16 ( 3 c aliper) 2 3.2 $20.99 $134.36 $298.43 $596.86 $731.22 Tree g uying 2 0.457 $19.06 $17.42 $16.46 $32.92 $50.34 3" aged bark m ulch 2 0.08 $17.19 $2.75 $0.76 $1.52 $4.27 Delivery 1 $50.00 $50.00 $50.00 Mate rial tax $54.33 Subtotal $890.16 General conditions 5% $44.51 Overhead & profit 15% $140.20 Total $1,074.87 Note: Professional, non union installation. Price source was RS Means Cost W orks Residential New Construction 2010. Geographic Multiplier used was .85 of national. Delivery cost was an estimated assumption for residential retrofit work.

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84 Table 4 3 1 Compact fluorescent lighting EEM performance Parameter s Characteristics Collected statistical Data Required calculation assumptions Value Number of replaced l ights X 27 bulbs Original bulb d raw X 60 W att CFL bulb d raw X 14 W atts Average lighting l evel X 12 foot Average CFL light o utput X 8 00 lumens Calculation Computer simulation Savings 4,080k W h/year $475.32/year Table 4 3 2 Compact fluorescent lighting EEM cost Energy efficiency measure: compact fluorescent light r eplacement Labor Material Item Quantity Hours Rat e Subtotal Unit cost Subtotal Total CFL b ulbs (4 pack) 7 $0 $8 $56 $55.79 Material tax $0 $0 $3.63 Subtotal $59.42 General conditions 5% n/a Overhead & profit 15% n/a Total $59.42 Note: Home owner installation. Price source was Home Depot website on 12/22/10. Bulb assumed was a EcoSmart 14W Daylight CFL (4 pack) Assumed bulb model number was ES5M814450K Pricing does not include allowance for replacements if new lamps are damaged.

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85 Table 4 3 3 LED lighting EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Number of LED l ights X 43 bulbs Number of o riginal i ncandescent b ulbs X 27 bulbs Original bulb d raw X 60 W att LED bulb d raw X 8.5 W atts Average lighting l evel X 12 foot Average LED light o utput X 51 0 warm light lumens Original incandescent bulb l ight o utput X 800 warm light lumens Calculation Computer simulation Savings 4, 130 k W h/year $ 481.15 /year Table 4 3 4 LED l ighting EEM cost Energy efficiency measure: LED lighting r eplacement Labor Material Item Quant. Ho urs Rate Subtotal Unit cost Subtotal Total L ED b ulbs 43 $0 $45.95 $ 1,975.85 $ 1,975.85 Material tax $0 $0 $ 1 28.43 .55 Subtotal $ 2, 104 28 General conditions 5% n/a Overhead/ profit 15% n/a Total $ 2, 10 4.28 Note: Home owner installation. Price source was from LED Wave website. Blub assumed was a Mark II (A19 A60) incandescent replacement LED Pricing does not include allowance for replacements if new lamps are d amaged.

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86 Table 4 3 5 ES clothes washer EEM performance Table 4 3 6 ES clothes washer EEM cost Energy efficiency measure: Energy Star clothes w asher Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Clothes d ryer 1 $0.00 $539.10 $539.10 $539.10 Delivery/Install 1 $0.00 $ 50.00 $50.00 $50.00 Material tax $0.00 $0.00 $38.29 Subtotal $627.39 General conditions 5% n/a Overhead & profit 15% n/a Total $627.39 Note: Home owner installation. s website 12/22/10. Washer assumed was a Maytag Bravos X (4.3 cuft). Parameters Characteristics Collected statistical data Required calculation assumptions Value Clothes washer u se X 4 loads per week Loads using hot w ater X 2 loads per week Energy Star reduc tion in e lectricity X 30% Energy Star reduction in w ater X 50% Traditional unit electricity u se X 1.242kWh/load Traditional unit w ater use X 31.07gallons/load Calculation Manual Savings 255.46kWh/year $29.76/year

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87 Table 4 3 7 E nergy S tar refrigerator EEM performance Table 4 38 Energy Star refrigerator EEM cost Energy e fficiency measure: Energy St ar r efrigerator Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Refrigerator 1 $0.00 $619.10 $619.10 $619.10 Delivery/Install 1 $0.00 $50.00 $50.00 $50.00 Material tax $0. 00 $0.00 $43.49 Subtotal $712.59 General conditions 5% n/a Overhead & profit 15% n/a Total $712.59 Note: Home owner installation. website 12/22/10. Refrig erator assumed was a Maytag 21.0cuflt top freezer refrigerator model (M1TXEMMWW). Parameters Characteristics Collected s tatistical data Required calculation assumptions Value Refrigerator s tyle X Top bottom d oor Size X 15 18cuft Average energy u se X 529k W h/year Reduced e nergy with Energy Star X 20% r eduction Calculation Manual Savings 105.8k W h/year $12.33/year

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88 Table 4 39 Energy Star dishwasher EEM performance Table 4 4 0 Energy Star d ishwasher EEM cost Energy efficiency measure: Energy Star d ishwasher Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Dishwash er 1 $0.00 $404.10 $404.10 $404.10 Delivery/Install 1 $0.00 $112.00 $112.00 $112.00 Material tax $0.00 $0.00 $33.55 Subtotal $549.65 General conditions 5% n/a Overhead & profit 15% n/a Total $549.6 5 Note: Home owner installation. website 12/22/10. Dishwasher assumed was a Maytag JetClean Plus built in tall tub model number MDBH969AWW. Parameters Characteristics Collected statistical data Required calculation assumptions Value Dishwasher loads per w eek X 4.13 loads/week Tradit ional unit electricity u se X 1.33kWh/cycle Traditional unit hot water u se X 4 gallons/cycle Energy Star electricity u se X 1.67kWh/cycle Energy Star hot water u se X 6 gallons / cycle Calculation Manual Savings 120.32kWh/year $14.02 /year

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89 Table 4 4 1 Stand by power loss EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Number of a ppliances X 5 units Number of power in terrupters X 2 units Appliance t ypes X Television VCR Cable b ox PC m onitor PC p rinter Average standby power d raw X 10 W atts Time t u rned off & n ot in standby X 8 hours/day Calculation Manual Savings 146k W h/year $17.01/year Table 4 4 2 Stand by power loss EEM cost Energy efficiency measure: reduce standby power l oss Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtota l Total Power i nterrupters 2 $0 $9.95 $20 $19.90 Shipping 2 $0 $7.95 $16 $15.90 Material tax $0 $0 $2.33 Subtotal $38.13 General conditions 5% n/a Overhead & profit 15% n/a Total $38.13 Note: Ho me owner installation. Price source was www.asseenontv.com Device assumed was the Handi Switch.

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90 Table 4 4 3 Programmable t hermostat EEM performance Parameters Characteristics Collected statistical data Required calculation assu mptions Value Number of HVAC u nits X 1 u nit Temp set in warm m onths X 76 degrees Temp set in cool m onths X 65 degrees Temp set back in warm m onths X 7 degrees Temp set back in cool m onths X 8 degrees Set back s chedule X 9:00am 5:00pm M F Calculation Computer simulation Savings 1,380k W h/year $160.77/year Table 4 4 4 Programmable t hermostat EEM cost Energy efficiency measure: programmable t hermostat Labor Material Item Quantity Hours Rate Subtotal Unit cost Subt otal Total Programmable T Stat 1 1 $38 $38 $168.56 $168.56 $206.39 Material tax $0 $0.00 $13.42 Subtotal $219.80 General conditions 5% $10.99 Overhead & profit 15% $34.62 Total $265.41 Note: Profession al, non union installation. Price source was Means Pricing Guide Repair and Remodeling Cost 2005. Geographic Multiplier used was .85 of national. Thermostat assumed as 2 set point capability.

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91 Table 4 4 5 Occupancy sensor EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Lighting power i ntensity X .9 W atts/sqft Number of OS i nstalled X 6 Rooms OS installed X Master b edroom East b edroom West b edroom Ki tchen Dining r oom Living r oom Reduction from ineffective l ighting X 10 % Calculation Computer simulation Savings 440k W h/year $51.26/year Table 4 4 6 Occupancy sensor EEM cost Energy efficiency measure: Occupancy Sensor Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Occupancy Sensors 6 1 $17.77 $107 $39.99 $239.94 $346.53 Plate 6 1 $3.78 $23 $0.29 $1.73 $24.43 Material tax $0 $0.00 $22.52 Subtotal $393.48 General co nditions 5% $19.67 Overhead & profit 15% $61.97 Total $475.13 Note: Professional, non union installation. Price source for install is Means Pricing Guide Repair and Remodeling Cost 2005. Geographic Mu ltiplier used was .85 of national. Occupancy sens with Eco dim. website 12/22/11.

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92 Table 4 4 7 Energy dashboards EEM performance Parameters C haracteristics Collected statistical data Required calculation assumptions Value System c omponents X 1 central monitoring s tation 1 main panel t ransmitter 4 plug in t ransmitters 5 hard wire CT t ransmitters Location of individual Appliance m onitor X 1 computer a rea 1 entertainment c enter Location of hard w ire Transmitters X 1 water h eater 1 HVAC 1 o ven 1 d ryer Reduction in consumer demand X 10 % Calculation Computer simulation Savings 2,270k W h/year $264.46/year

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93 Table 4 4 8 Energy dashboard EEM cost Energy efficiency measure: energy monitoring d ashboard Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total Display and w hole h ouse t ransmitter 1 1 $37.72 $38 129.00 $129 $166.72 Additional 208 CT m onitor 4 2 $37.72 $302 79.00 $316 $617.75 Additional individual appliance monitor 2 0.25 $37.72 $19 79.00 $158 $176.86 Material tax $0 $0.00 $51.65 Shipping 1 $0 24.75 $25 $24.75 Subtotal $1,012.98 General condi tions 5% $50.65 Overhead & profit 15% $159.54 Total $1,223.17 Note: Professional, non union installation. Price source was Power Save website 12/29/10. Energy monitor assumed was the Envi by Power Sav er Inc. Table 4 49 Photovoltaic EEM performance Parameters Characteristics Collected statistical data Required calculation assumptions Value Photovoltaic array s ize X Average length of direct s un X 4.5 hours per day utput X 10 W atts/sqft/hour Calculation Manual Savings 1,971k W h/year $229.62/year

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94 Table 4 50 Photovoltaic EEM cost Energy efficiency measure: photovoltaic panel a rr ay Labor Material Item Quantity Hours Rate Subtotal Unit cost Subtotal Total PV panels 1 10 $32.68 $326.80 $5,550.00 $5,550.00 $5,876.80 AC/DC i nverter 1 2 $32.89 $65.78 $1,500.00 $1,500.00 $1,565.78 Material tax $0.00 $0.00 $458.25 Permit 1 $0.00 $210.00 $210.00 $210.00 Subtotal $8,110.83 General conditions 5% $405.54 Overhead & profit 15% $1,277.46 Total $9,793.83 Note: Professional, non union installation. Price source wa s Means Pricing Guide 2010 Cost Data for New Commercial Construction. Geographic Multiplier used was .85 of national. Figure 4 1. The Model House.

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95 Figure 4 2. Floor Plan of Model House

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96 Figure 4 3 Living Room of Model House. Figure 4 4 Kitchen of Model House.

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97 Figure 4 5 West Bedroom of Model House. Figure 4 6 Master Bedroom.

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98 Figure 4 7 Back Yard Patio. Figure 4 8. eQUEST Introduction.

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99 Figure 4 9 eQUEST Building Geometry. Figure 4 10. e QUEST Building Components.

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100 Figure 4 11. eQUEST Zoning and Schedules.

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101 CHAPTER 5 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS Summary The focus of this research was to identify common energy efficiency measures and test their effectiveness on typical Florida housing. To test the effectiveness a computer simulated house was created that shared characteristics most common to Florida single family homes. This research called the computer simulation the Model House. Effectiveness was defined by two com ponents; cost and savings. Cost was measured by the initial influx of capital expense required to apply the measure to the Model House. Savings was measured by determining the yearly consumption of energy after an EEM was applied and comparing it to the baseline energy use. Matrix of Results The Matrix of Results is a table that includes the raw data collected from the study and can be found in Table 5 1. The graphs that follow pull their information from this matrix and show trends in th e data. However, before the data can be analyzed it is important to fully understand what the co lumns represent C apital Cost: The capital cost represents the initial influx of financial resources to implement the EEM. The column values are cost estimat es calculated by performing a quantity take off, applying unit costs and adding appropriate mark ups. The summary of these estimates can be found in the tables at the end of chapter four An example of the cost estimate for the additional ceiling fan EEM can be found in Table 4 6. Kilow att Saved: The kilowatt saved column i s the quantity of energy reduced per year can be found in Appendix A. The summary of energy reduced with the assumptions made can be found in th e tables at the end of chapter four An example of the kilowatts saved for the additional ceiling fan EEM can be found in Table 4 5. Savings from EEM/year: This column represent s in financial terms the value of the conserved energy. The average cost of electrical energy in Florida is $.1165 per kWh. The additional ceiling fan EEM for example reduces the energy use by 435kWh per year.

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102 By multiplying the energy saved by the average energy cost (435k Wh $.1165/ kWh) you can see the yearly energy savings in financial terms ($50.68). Gross ROI Time: This column calculates the number of years required for the Saving s from EEM/year to cumulatively equal the value of the Capital Cost The calculation is performe d by dividing the Capital Cost column by the Savings from EEM/year column. For the additional ceiling fan EEM the calculation would be $882/$50.68. Competing Investment Rate: This study evaluates the EEMs in terms of investment returns. However, to determine if an EEM is a favorable investment there must be a set value that represents the estimated return of competing investments. In a report published by the Florida Solar Energy Center a rate of eight percent was used as the minimum expected retur n for a favorable EEM investment (Fairey & Vieira 2009) This value was computed by taking the guaranteed return from the State of Florida DROPS retirement account and adding an additional 1.5%. This study will use the same expected return value in its a nalysis. EEM ROI: This column is the gross return on investment from each of the EEMs. The calculation is the division of the column. For the additional ceiling fan EEM it would be $50.68/$882 which equal 5.75%. The percentage represents the return on an annual basis. Return Above Competing Investments: This column is the determin ation of whether an EEM is column takes the percent return of competing is positive then the value represents the percent return the EEM will earn above the competing in vestments and is considered favorable. If the value is negative then the EEM will generate a return less than that of competing investments and is considered unfavorable. In the case of the additional ceiling fan EEM the EEM ROI of 5.75% is subtracted by the assumed competing investment return of eight percent resulting in a n un favorable investment of 2.25% lower than other investment options. Net ROI Time Net ROI Time however the rate of return o f competing investments is considered. With traditional investments at the end of the investment period the investor receives the interest earned plus the original principle. For EEM the original principle is converted to a fix ed asset and will not be co nverted back to cash at the end of the investment period. This column calculates the length of time it will take the EEM to return the original prin ciple investment (initial capital cost ) while still providing interest ( savings from EEM/year ) at the same rate of competing investments. In the case of the additional ceiling fan EEM the return is less than eight percent so this EEM will never return its initial capital cost. For the LED lighting EEM however, this column calcul ates the time required for the 14.87 % ROI abov e competing investments to accumulate to the initial capital cost of $ 2,104 The calculation is capital cost divided by the capital cost return above competing investments [2,104/(2,104 .1487 )]. Some of the EEM do not have returns above the assumed eight

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103 percent of competing investments and will never return their initial principle (Capital C N et ROI Time value. Cost/Kilowatt Saved: This column provi des information on w hat the capital cost is to save with the resulting measurement in years. For the additional ceiling fan EEM the capital cost of $882 is divided b y the k ilowatt s aved of 435kWh/year resulting in a cost of $2.03/kWh saved each year. Cost vs. Savings Comparison An important analysis of the find ing s is to compare the capital cost with the energy savings. As defined earlier the capital cost is the ini tial investment of financial resources to implement the EEM. Figure 5 1 ranks the EEM by their initial capital cost. The savings is illustrated in Figure 5 2 and ranks the EEM by the total kilowatts saved per year. The savings can also be represented in financial terms by the amount of kilowatts saved multiplied by the cost of the kilowatt. The comparison of initial capital cost and energy cost savings can be found in Figure 5 3. In this comparison there is not a direct relationship between capital exp ense and energy savings. To illustrate, the retro foam and stand by power loss EEMs have nearly the same energy savings however the retro foam initial capital cost is $7,218 as compared to only $38 from the stand by power loss EEM. Another way of evaluat ing the cost benefit of the EEM is by reviewing the cost per kilowatt conserved. Figure 5 4 provides an illustration of this by indicating the influx of capital cost required to save one kilowatt hour each year The cost per kilowatt chart provides a mea ns of prioritizing which EEM will have the most effect for the least initial cost. Return on Investment The comparison between an EEM and a traditional investment is a close but not perfect analogy. When investing in traditional investments at the end of the investment period the investor expects to receive a cash payout equal to the interest earned plus principle. For an EEM

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104 investment the initial principle or capital cost in transferred into a fix ed asset. In theory however, when the home owner sells their house they will be able to convert the initial investment back in to cash through the higher selling price of the improved property. Despite this imperfect comparison, using tools to evaluate traditional investment are often the same as when evaluati ng an EEM. Figure 5 5 provides a graphical representation of the rate of return from each of the tested EEMs. is calculated on an annual basis. The computation is made by dividing the sa vings the EEM has per year by the initial capital expense. For this simulation it is assumed that the home owner s competing investment option s yield an average return of eight percent The EEMs that have a return of less than eight percent would be cons idered less favorable investments than these other traditional investment options. Competing investment options is an important factor in reviewing the net return on investment duration as show in Figure 5 6 In this chart the time it will take for the E EM to pay for itself (initial capital cost) and the savings equal to competing investments is calculated. Many of these EEM are not financially viable as their savings do not equal the return from competing investment options. Some of the EEM like window films and occupancy sensors do have savings above the competing investment rate however it will take longer to return their initial capital cost than the life span of the EEM. Most Favorable EEM Investments As shown in Figure 5 5, there are six EEM s that stand out as ha ving the highest rate of return These top six measure s all have returns above 20% which is twice the return of the next closest EEM. The bullets below will list these most favorable EEM investments and explain the driv ers leading to their high returns. CFL Replacement: This EEM has a return on investment of 800% and is the largest return by percentage of capital cost of all of the studied EEM s This high return is due to its low cost to implement and high energy savings. Of the EEM s stu died the CFL replacement

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105 measure has the third lowest cost and the second highest energy reduction The measure is an excellent illustration that there is not a direct relationship between initial capital cost and energy reduction. Low Flow Water Fixture s: This EEM has a return on investment of 1 01%. Although the actual kilowatts saved are close to the median the capital cost is very low. The low capital cost is the drive r behind the high rate of return. Programmable Thermostat : This EEM has a rate o f return of 61%. The favorable return is due to a fairly strong reduction in energy and also its low cost to implement. Of the EEM tested this measure has the fourth lowest capital cost. Reduction of Stand by Power Loss: This EEM has a return of 45%. Although there is high rate of return the driver of this percentage is the low capital cost to implement. The overall energy savings is only 146kWh or a savings of $17.01 per year LED Lighting: This EEM has rate of return of 23%. The high rate of retu rn is due primarily to the high energy savings. Of all of the EEM tested this measure has the highest reduction in energy use. Stated another way, although there are other EEM with high return percentages this EEM will reduce utilit y cost more than any o ther measure tested. Energy Dashboard: This EEM has a rate of return of 22%. The initial capital cost is slightly above the median EEM test ed however the energy savings is th e third highest. T he large energy savings drives the high rate of return for th is measure The residential market consumes nearly 40% of all domestic electrical energy. Within that market the existing home stock represents over 99% of the homes. There are numerous ways in which to lower energy consumption however barriers still e xist that keep home owners from acting. The energy retrofit market is low hanging fruit that should not be ignored to improve our national economic efficiency and global climate responsibility. Limitations It is important to note that the most significan t limitation for the research is that it house but there are a near infinite number of combinations of these characteristics. It is impossible to simulate all F lorida houses with a single model. In addition to construction, the Model House also simulated occupant behavior. However, there again it is impossible to

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106 simulate all scenarios with a single model. The findings can provide expected results and order of magnitudes however the data must be extrapolated when applied to any real world situation Recommendations for Future Study This study provides valuable information in the field of residential energy conse rvation, however there are several areas the rese arch does not explore and are recommended for future study. As there are many combinations of housing characteristics and occupant behavior it is recommended that additional models with different combinations of characteristics be created. To maximize t he effectiveness of the additional models a sensitivity study is recommended. The study should look at characteristics of the Model House and energy modeling assumptions to determine which of these characteristics have the most impact. With this informa tion new models could be created to specifically target these high impact areas. Specific areas that may be of interest are energy cost, number of occupants, house size, and climate differences in the hot/humid zone. Dif ferent housing types should be rev iewed for future study. This research is exclusive to single family detached houses but ignores multifamily complexes, rental units, and manufactured homes. A study of EEM effectiveness on different economic groups may provide interesting results. Prel iminary studies have shown that low income households are disproportionately burdened with high utility cost. A review of additional EEM s both established and cut edge would benefit this field of study The energy savi ngs provided by multiple EEM s appl ied together may not be cumulative. Competing EEMs like a super efficient water heater and a solar water heater when applied

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107 together would not have the aggregate savings as each applied independently. There would be value in researching the effectivenes s of groups or packages of EEMs. Stud y ing which EEM s complement each other and provide the highest effectiveness in combination would be valuable research. This study provides a very simplified approach when comparing the EEMs and other investments Fo r example, the interest earned on traditional investments is taxed however the savings of energy (or money not spent) is not. There would be value in an advanced review of the financial impacts of the savings over extended periods of times. Items not inc luded in this study but would be of benefit in future research include life spans of the EEM, inflation rates, net present value of energy savings, future value of initial capital cost and decreased return/efficiency on EEM over time.

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108 Table 5 1. Mat rix of Results

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109 Figure 5 1. Initial Capital Expense

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110 Figure 5 2. Energy Consumption Reduced per Year

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111 Figure 5 3. Initial Capital Expense vs. Savings.

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112 Figure 5 4. Cost per Kilowatt Hour Conserved.

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113 Figure 5 5. Return on Investment.

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114 Figure 5 6. Duration of Return on Investment.

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115 APPENDIX A BASE LINE ENERGY MOD EL THE MODEL HOUSE

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116 APPENDIX B ENERGY MODEL OF THE CEILING FAN EEM

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117 APPENDIX C ENERGY MODEL OF THE HVAC TUNE UP EEM

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118 APPENDIX D ENERGY MODEL OF THE LEAKING HVAC DUCTWOR K EEM

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119 APPE NDIX E ENERGY MODEL OF THE HIGH SEER AC UNIT EE M

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120 APPENDIX F ENERGY MODEL OF THE LOW FLOW SHOWER HEAD S AND AERATORS EEM

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121 APPENDIX G ENERGY MODEL OF THE WINDOW FILM EEM

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122 APPENDIX H ENERGY MODEL OF THE BLOWN IN ATTIC INSUL ATION EEM

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123 APPENDIX I ENERGY MO DEL OF THE RETRO FOAM IN WALLS EEM

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124 APPENDIX J ENERGY MODEL OF THE LOW E GLAZING EEM

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125 APPENDIX K ENERGY MODEL OF THE WINDOW AWNING EEM

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126 APPENDIX L ENERGY MODEL OF THE SKYLIGHT EEM

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127 APPENDIX M ENERGY MODEL OF THE STRATEGICALLY PLACED LANDSCAPE EEM

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128 AP PENDIX N ENERGY MODEL OF THE CFL EEM

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129 APPENDIX O ENERGY MODEL OF THE LED LIGHTING EEM

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130 APPENDIX P ENERGY MODEL OF THE PROGRAMMABLE THERMOS TATS EEM

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131 APPENDIX Q ENERGY MODEL OF THE OCCUPANCY SENSOR EEM

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132 APPENDIX R PROTOCOL FOR MODEL H OUSE General Param eters 3 bedroom, 2 baths and 2 car garage. 1,803 sqft under air. 21,165 sqft total. Built in 1988. Energy efficiency based on 1987 Florida Energy Code. Perimeter of 248 lnft. Exterior wall surface area 1,984 sqft. Energy sou rce is electric without access to gas. North central Florida climate zone. Site Model is located on acre site. No trees or adjacent structures shading site. House is orientated East/West with the front facing direction West. Schedule and Occupancy 3 resi dents in home. Weekday peak loads are 6 9am and 5 10pm Monday Friday. Weekend peak loads are 7am 10pm Saturday, Sunday and holidays. US standard holidays observed. Interior Loads Average lighting intensity of .9 W atts per sqft Plug in devise intensity of .75 W atts per sqft Utility cost of $.1165 per k ilowatt. Shell Construction on center. Roo f composed of dark colored asphalt Roof on a 5/12 pitch R19 insulation located at attic floor level. Exterior glazing is 1 5% of floor space. Windows are operable single hung with Exterior doors are insulated metal doors. HVAC System Split system. Condenser unit located outside. Air handler unit located in conditioned AC closet. Direct return. 10 SEER efficiency Cooling set point of 76 degrees. Heating Set point of 65 degrees. Average heat gain per person is 450 BTU/hour (250 BTU/h sensible and 200 BTU/hour latent). Hot Water System 40 gallon storage type style system. 4,500 W att output. Average water use of 25 .8 gallons per person per day. Input temp of 75 degrees. Output temp of 120 degrees. Electric fuel source.

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133 LIST OF REFERENCES Air Conditioning, Heating and Refrigeration Institute. (2008). 2008 Standard for Performance Rating of Unitary Air Conditioning & Air Source Heat Pump Equipment Retrieved from http://ari.org/ARI/util/showdoc.aspx?doc=1718 Chandler, Claudia. (1999). Leaking Ducts Can Cost Big Bucks California Energy Commission, Me dia and Public Communication Office. Retrieved from The California Energy Commission, Media and Public Communication website: http://www.energy.ca.gov/releases/1 999_releases/features/1999 feature 05.html Consumer Search. (2011). High efficiency 16 to 23 Seer Central Air Conditioner Retrieved from http://www.consumersearch.com/central air conditioners/high efficiency 16 to 23 seer central air conditioner Ehrlich, Brent. (2010). Modular LED Lighting Enters the Mainstream Environmental Building News, 19(11). Retrieved from http://www.buildinggreen.com/auth/article.cfm/2010/10/29/Modular LED Lighting Enters the Mainstream/ Energy Independence and Security Act of 2007, H.R 6 2,110td cong. (2007). Fairey, Philip, & Vieira Robin. (2009). Energy Cost Effectiveness Test for Residential Code Update Processes (FSEC CR 1794 09). Friedel, Robert, & Paul Israel. (1986). Edison's electric light: biography of an invention (pp. 1 15 117) New Brunswick, New Jersey: Rutgers University Press. Givoni, Baruch. (1998). Climate Considerations in Building and Urban Design New York City, New York: John Wiley & Sons, Inc. Green product sub category: solar control window film. (2010 April). Environmental Building News. Retrieved from http://www.buildinggreen.com/auth/productsByCsiSection.cfm?SubBuilderCategoryID=1813 General Elec tric Company. (1964). Incandescent Lamps (TP 11 0). Lee, Jeffery. (2009, February). Real Time Feedback. Eco Home Magazine Retrieved from http://www.ecohomemagazi ne.com/home technology/real time feedback.aspx Means Residential Repair & Remodeling Cost. (2005). Reed Construction Data Kingston, MA.: Reed Construction Data. Means Residential Detailed Cost. (2005). Reed Construction Data. Kingston, MA.: Ree d Construction Data.

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134 Norland, Jim. (2006, August). How High Will SEER Go?. The Air Conditioning, Heating and Refrigeration NEWS Retrieved from http:/ /www.achrnews.com/Articles/Cover_Story/ca042ea2d95dc010VgnVCM100000f932a8c0_ ___ Progress Energy. (2010). Ceiling Fans Retrieved from http://www.progress energ y.com/custservice/flares/energytips/ceilingfans.asp Pulling the plug on standby power. (2006, March). The Economist. Retrieved from http://www.economist.com/node/5571582?story_id=55 71582 Roland, Megan. (2008, October 13). GRU Unveils New Solar Incentives. Gainesville Sun. Retrieved from http://www.gainesville.com/art icle/20081013/NEWS/810140283?Title=GRU unveils new solar incentives Scharff, Robert. (1983). The Fan Book (pp.128). Reston, VA. Reston Publishing Co, Inc. Shimberg Center for Affordable Housing. (1995). A Cost Comparison Study Between Steel and Wood Residential Framing Systems (Technical Note Series 95 2). Shimberg Center for Affordable Housing. (2010). Florida Housing Data Clearing House Retrieved from http://flhousingdata.shimberg.ufl.edu/a/construction_sales?report=unit_characteristics_all &repor t=a1_total_units_homestead&report=a2_year_built&report=a3_size_type&report=a4_size_year_ built&report=a5_valuations&action=results&nid=1&go.x=6&go.y=20 Solar Home. (2010 ). Solar Wiring? Retrieved from http://solarhome.org/infosolarwiring.html Solar Panel Information. (2010). How are Solar Panels Made Retrieved from http://www.solarpanelinfo.com/sola r panels/how are solar panels made.php State of Florida, Department of Community Affairs Energy Code Program. (1987). Energy Efficiency Code For Building Construction 1986, Revised January 1987. Tankless water heaters. (2006, September). Environmenta l Building News. Retrieved from http://www.buildinggreen.com/auth/article.cfm/2009/8/28/Tankless Water Heaters/ Tugend, Alina. (2008, May). If Your Applianc The New York Times Retrieved from http://www.nytimes.com/2008/05/10/busi ness/yourmoney/10shortcuts.html?_r=1&scp=1&sq=ap pliances%20avocado%20green&st=cse

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135 U.S. Census Bureau. (2008). American Community Survey. Retrieved from http://factfinder.census.gov/servlet/ADPTable?_bm=y& geo_id=04000US12& qr_name=ACS_2008_3YR_G00_DP3YR4& ds_name=ACS_2008_3YR_G00_& _lang=en& _sse=on U.S. Energy Information Administration. ( 2005). 2005 Energy Consumption Survey Retrieved from http://www.eia.doe.gov/emeu/recs/recs2005/hc2005_tables/detailed_tables2005.html U.S. Energy Informati on Administration. (2008) Average Monthly Bill by Census Division, and State 2008 Retrieved from http://www.eia.doe.gov/cneaf/electricity/esr/table5.html U S Department of Energ y. (20 11 ). Central Air Conditioning Retrieved from http://www.energystar.gov/index.cfm?fuseaction=find_a_product.showProductGroup&pgw_cod e=CA U S Department of Energy. (2009). Duct Sealing. (Memo Number EPA 430 F 09 050). Retrieved from http://www.energystar.gov/ia/products/heat_cool/ducts/DuctSealing Brochure04.pdf US Department of Energy, (2011). eQ UEST Retrieved from http://apps1.eere.energy.gov/buildings/tools_directory/software.cfm/ID= 575/pagename=alpha_li st U S Department of Energy. (2010). Lower Water Heating Temperature for Energy Savings Retrieved from http://www.energysavers.gov/your_ho me/water_heating/index.cfm/mytopic=13090 U S Department of Energy. (2010). Low Emissivity Window Glazing or Glass. Retrieved from http://www.energysav ers.gov/your_home/windows_doors_skylights/index.cfm/mytopic=13430 U S Department of Energy. (2010). Thermostats and Control Systems Retrieved from htt p://www.energysavers.gov/your_home/space_heating_cooling/index.cfm/mytopic=12720 U.S. Department of Energy, Energy Star. (2008). Light Bulbs CFLs for Consumers Retrieved from http://www.energystar.gov/index.cfm?fuseaction=find_a_product.showProductGroup&pgw_cod e=LB U.S. Department of Energy, Energy Star. (2009). A Guide to Energy Efficient Heating and Cooling Retrieved from http://www.energystar.gov/ia/partners/publications/pubdocs/HeatingCoolingGuide%20FINAL_9 4 09.pdf U.S. Department of Energy, Energy Star. (2010). Find Energy Star Products Product. Retrieved from http://www.energystar.gov/index.cfm?c=products.pr_find_es_products

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136 Vessel, Leora Broydo. (2009, September 28). As C.F .L. Sales Fall, More Incentives Urged. New York Times. Retrieved from http://green.blogs.nytimes.com/2009/09/28/as cfl sales fall more incentives urged/ Vi ckers, Amy. (2001). Handbook for Water Use and Conservation Amherst, MA: Waterplow Press. Water Resources Development Act of 1992, H.R. 6167 102 nd td cong. (1992). Wilson, Alex. (1996). Windows: Looking Through the Options. Environmental Buil ding News 5(2). Retrieved from http://www.buildinggreen.com/auth/article.cfm/1996/3/1/Windows Looking through the Options/ Wilson, Alex. (1999). Bringing Daylighting Deeper Into Buildings. Environmental Building News, 8(10). Retrieved from http://www.buildinggree n.com/auth/article.cfm/1999/10/1/Daylighting Part 2 Bringing Daylight Deeper into Buildings/ Wilson, Alex. (1999). Is Solar Still Active? Water Heating and Other Solar Thermal Applications. Environmental Building News, 8(7). Retrieved from http://www.buildinggreen.com/auth/article.cfm/1999/7/1/Is Solar Still Active Water Heating and Other Solar Thermal Appli cations/ Wilson, Alex. (2003). Lighting Controls: Beyond the Toggle Switch. Environmental Building News, 12(6). Retrieved from http:/ /www.buildinggreen.com/auth/article.cfm/2003/6/1/Lighting Controls Beyond the Toggle Switch/ Wilson, Alex. (2008). Energy Dashboards: Using Real Time Feedback to Influence Behavior. Environmental Building News, 17(12). Retrieved from http://www.buildinggreen.com/auth/article.cfm/2008/11/24/Energy Dashboards Using Real Time Feedback to Influence Behavior/

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137 BIOGRA PHICAL SKETCH Joe Burgett was born in 1980 in Saint Petersburg Florida. He is the younger of 2 sons to Dan and Sally Burgett. He graduated from Northeast High School in the spring of 1998. After graduating high school Joe attended the University of Flor ida where he received his Bachelor of S cience from the M.E. Rinker Sr. School of Building Construction. After graduating, Joe spent eight years in the construction industry working largely for The Weitz Company. While in the industry, Joe worked primari ly on state and local government project but has experience with hotels, hospitals, biomedical research, schools, multifamily condos, single family residences and retirement campuses. The majority of his construction experience was in operations serving a s a superintendent and project manager however he also spent several years in preconstruction. While in preconstruction he estimated over 800 million dollars of work. In 2010, Joe returned to the U niversity of Florida to pursue and PhD degree s i n construction management. He is currently enrolled in the M.E. Rinker Sr. School of Building Construction and is expected to graduate in the spring of 2011. Joe is married to his wife Jill and has two daughters with her. His youngest daughter Emma w as born in March of 2010 and his older daughter Kate was born in September of 2008. Joe and his family currently reside in Gainesville, Florida.