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The Role of Occupant Behavior in Low-Income High Energy Intensity Households

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Title:
The Role of Occupant Behavior in Low-Income High Energy Intensity Households
Creator:
LOCKE, FRANCES CLAIRE
Copyright Date:
2008

Subjects

Subjects / Keywords:
Cost efficiency ( jstor )
Demand side economics ( jstor )
Electricity ( jstor )
Energy ( jstor )
Energy consumption ( jstor )
Energy efficiency ( jstor )
Heating ( jstor )
Homes ( jstor )
Thermostats ( jstor )
Utilities costs ( jstor )
City of Gainesville ( local )

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Frances Claire Locke. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
12/31/2007
Resource Identifier:
649810221 ( OCLC )

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THE ROLE OF OCCUPANT BEHAVIOR IN LOW-INCOME HIGH ENERGY INTENSITY HOUSEHOLDS By FRANCES CLAIRE LOCKE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Frances Claire Locke

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To the friendships I have gained at the Univer sity of Florida. without which I could have never made it this far.

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iv ACKNOWLEDGMENTS I would like to thank my mother, Ma ry, for her boundless encouragement and guidance. I thank my father, brother, th e entire Dresback family, and my extended family, all of whom have enriched my life and offered continuous support, affection, and direction. I also wish to thank Christophe r Bohn who has provided his endless support throughout this process and has sustained me on this journey both mentally and emotionally. I also extend my gratitude to the professors at the University of Florida for their continued quest for knowledge and profound impact on students, without which I may never have grown intellectually and emotiona lly. In particular, I wish to thank Dr. Grosskopf as his expertise, support, and direc tion has made this entire process possible.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii LIST OF FIGURES.........................................................................................................viii ABSTRACT....................................................................................................................... ..x CHAPTER 1 INTRODUCTION........................................................................................................1 Statement of the Problem..............................................................................................1 Objective of Study........................................................................................................1 Hypothesis Statement...................................................................................................2 Research Methodology.................................................................................................2 2 LITERATURE REVIEW.............................................................................................3 Introduction...................................................................................................................3 History of Utility Demand-Side Management..............................................................3 Demand-Side Management Technologies....................................................................6 Effectiveness of Demand-Side Management Programs...............................................7 The Role of Consumer Behavior in Demand-Side Management Programs...............12 Trends and Success of DemandSide Management Programs...................................14 Local DSM Programs in Progress..............................................................................17 Summary.....................................................................................................................21 3 METHODOLOGY.....................................................................................................24 Introduction.................................................................................................................24 Designing of Survey...................................................................................................24 Selection of Sample Size............................................................................................29 Survey Distribution.....................................................................................................29 Survey Data Collection...............................................................................................31 Summary.....................................................................................................................32 4 DATA ANALYSIS....................................................................................................33

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vi Introduction.................................................................................................................33 Individual Question Results........................................................................................33 Heating Systems.........................................................................................................34 Cooling Systems.........................................................................................................36 Hot Water Usage.........................................................................................................39 Household Laundry Process.......................................................................................40 Appliances..................................................................................................................43 Lighting.......................................................................................................................44 Entertainment..............................................................................................................46 Demographic Information..........................................................................................48 Summary.....................................................................................................................53 Figures........................................................................................................................54 5 SUMMARY AND RECOMMENDATIONS............................................................72 Summary.....................................................................................................................72 Conclusions.................................................................................................................72 Limitations of Study...................................................................................................75 Need for Further Research..........................................................................................75 Recommendations.......................................................................................................76 APPENDIX A GRAPHIC INFORMATION SYSTEM (GIS) MAP.................................................78 B INITIAL SURVEY INSTRUMENT..........................................................................79 C DEED SURVEY INSTRUMENT..............................................................................81 D ENERGY INFORMATION ADMINISTRATION RESULTS.................................93 E GRU SURVEY SUMMARY 2005-2006...................................................................95 F PRELIMINARY RECOMMENDATIONS...............................................................96 LIST OF REFERENCES...................................................................................................99 BIOGRAPHICAL SKETCH...........................................................................................100

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vii LIST OF TABLES Table page 3-1 2005 HUD Low Income Criteria..............................................................................30 A-1 2001 Total Household Energy Expenditures...........................................................94 A-2 GRU 2005-2006 Survey Summary..........................................................................95

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viii LIST OF FIGURES Figure page 2-1 Mail-administered Recruiting Survey......................................................................20 4-1 Primary Heat Sources...............................................................................................54 4-2 The Increase in Cost of Energy compar ed to Heating Temperature Settings of Participants...............................................................................................................55 4-3 Participants that Change Heating Setting While Asleep..........................................55 4-4 Primary Cooling Sources.........................................................................................56 4-5 The Increase in Cost of Energy compar ed to Cooling Temperature Settings of Participants...............................................................................................................56 4-6 Participants that Change Cooling Setting While Asleep..........................................57 4-7 Frequency of Air Conditioner Filter Change...........................................................57 4-8 Number of Months per y ear a Household Opens Windows.....................................58 4-9 Types of Water Heaters in the Household...............................................................58 4-10 Showers per Week in the Household.......................................................................59 4-11 Average Minutes per Shower...................................................................................59 4-12 Number of Loads Washed Per Week.......................................................................60 4-13 Frequency of Drying Clothes by Hanging...............................................................60 4-14 Weekly Meals Prepared at Home.............................................................................61 4-15 Frequency of Microwave / Toaster Oven / Toaster Use..........................................61 4-16 Amount of Indoor Lighting Used Per Day...............................................................62 4-17 Rooms Lit When Lights are in Use..........................................................................62 4-18 Type of Lightbulbs in Household.............................................................................63

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ix 4-19 Hours of Exterior Lighting per Night.......................................................................63 4-20 Number of Televi sions in Household.......................................................................64 4-21 Daily Television Usage............................................................................................64 4-22 Daily Video Game System Usage............................................................................65 4-23 Daily Computer Usage.............................................................................................65 4-24 Daily CD Player / Stereo / Radio Usage..................................................................66 4-25 Number of People in Household..............................................................................66 4-26 Number of Senior Ci tizens in Household................................................................67 4-27 Number of Children in Household...........................................................................67 4-28 Percentage of Households in Which a Member Works From Home.......................68 4-29 Percentage of Households in Which Someone is Home All Day............................68 4-30 Household’s Total 2005 Income Before Taxes........................................................69 4-31 Largest Impact on Ener gy Use of Household..........................................................69 4-32 Level of Concern of Participants Related to Energy Costs in Their Home.............70 4-33 Percentage of Households That Have Made Changes In Past Year to Make Home More Energy Efficient...................................................................................70 4-34 Percentage of Participants Aware of Programs To Help Lower Home Energy Bills..........................................................................................................................71 A-1 GIS Map of Gainesville............................................................................................78 A-2 Preliminary Survey Questionnaire...........................................................................80

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x Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science In Bu ilding Construction THE ROLE OF OCCUPANT BEHAVIOR IN LOW-INCOME HIGH ENERGY INTENSITY HOUSEHOLDS By Frances C Locke December 2006 Chair: Kevin Grosskopf Cochair: Charles Kibert Major Department: Building Construction As energy prices continue to rise, many consumers a nd utilities are looking for ways to cut back on costs. By reducing tota l household energy cons umption, utilities and consumers alike can simultaneously reduce spen ding and help protect the environment by offsetting potentially destructive power plants from being built, consuming less energy, and reducing the rising en ergy demand. It has been found that low-income households, on average, spend a disproportionate amount of their income on the costs of utilities, electricity in particular. Gainesville Regional Utilities (GRU) has studied their billing records and has found that some low-income households actually consume more energy than the average GRU customer. This thesis sets out to determine the factors that may contribute to this high energy use and identify if occupant behavior is a primary issue when dealing with household energy performance. Upon analysis of data, possible methods of implementing appropriate energy efficiency educational services for these lowand fixed-income utility cust omers will also be identified.

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1 CHAPTER 1 INTRODUCTION Statement of the Problem It has been found that low-income h ouseholds (according to HUD low-income limits), on average, spend a disproportionate amount of their income on the costs of utilities, electricity in particular. Gainesvi lle Regional Utilities has studied their billing records and has found that some low-income households consume disproportionately higher amounts of energy than the average GRU customer. Objective of Study The purpose of this study was to determine the factors that cause these low-income households to have such a high energy intensit y. The goal of the resear ch also set out to identify factors that cause some low-inco me households to demand significantly less energy per square foot than ot hers. It was concluded that th e causes would most likely be a combination of both physical characteristics of the home and behavioral factors relating to energy usage in the home. This research aims to determine the specific role and significance of occupant beha vior within this equation. Once the role of occupant behavior is established, demand-side manageme nt programs can be created to cater to the specific needs of the community through educat ional programs, federally funded projects, or rebate programs. From the collected da ta, suggestions as to the focus of these programs will be conveyed and will serve to be tter equip the programs to be effective and successful to both the community and the utility.

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2 Hypothesis Statement The role of occupant behavior in low in come households with high energy intensity is significant and requires demand-side management programs that accommodate behavior-related factors. Research Methodology In beginning the research necessary fo r this study, a literature review was conducted and completed. Upon completion, a survey instrument was created in conjunction with a research project headed by Gainesville Regional Utilities (GRU) which was already in progress. The sample size of this section of the research was determined, mapped out within the city, a nd sent preliminary surveys to determine household eligibility, based on energy consump tion and income level. Eligibility based on income level was determined by HUD 2005 Gainesville, Florida, MSA Low Income Criteria. Once eligibility was determined, a ppointments were scheduled to allow for an in-home energy audit, completed by a GRU Conservation Analyst, and an in-home survey, administered by a graduate student from the University of Florida. Upon completion of the appropriate surveys and coll ection of data, results were combined and analyzed. From these results, energy consump tion issues related to occupant behavior became apparent. In analyzing the sample popul ation and its response to various issues relating to household energy consumption, procedures for creating more targeted and successful demand-side management programs can be realized and implemented.

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3 CHAPTER 2 LITERATURE REVIEW Introduction In determining if occupant behavior had a significant role in the occurrence of high energy intensity in low-income households, it was logical that the driving force behind this study and many other similar studies be re searched and evaluated. This driving force was identified as Demand-Side Manageme nt (DSM) programs which aim to discover sources of high energy consumption and de velop solutions to lower total energy consumption and benefiting both the energy s upplier and consumer. By lowering the total energy consumption, the energy supplier can lower peak demand and offset costs associated with generating more energy capaci ty needed to meet higher demands. In the sections that follow, the history of DSM pr ograms are discussed as well as the typical program design and implementation techniques. The effectiveness of the programs, the potential role of consumer be havior in these programs, and program trends and successes are also offered. This information is followed by case studies of DSM programs in utility companies. History of Utility Demand-Side Management Demand-side management programs originat ed nationwide in th e late 1980s and early 1990s as the need arose to meet th e nation’s ever-growing electricity demand (Peach, 1991). According to the Department of Energy (DOE) in 1991, the nation would require over 100 new large power plants to meet the electricity demand in 2000, which was estimated to increase at a rate of up to 2.4 percent annually from 1991 through 2000

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4 (p. 2). Utility companies responded to th e anticipated need for generating greater capacity with demand-side management pr ograms, which promoted more efficient electricity use and would aid in the avoidance of many envi ronmental and cost concerns that might be associated with building new power plants ( p. 2). Electric utility DSM programs were initially implemented to modify customer load profiles with the goals of peak load reduction, load shape flexibility, a nd increasing total elec tricity sales through the shifting of consumption from peak to off-peak hours of usage (Donald, 1997). These DSM programs encouraged electricity consumer s to take action in using less electricity by replacing older and inefficient appliances w ith more efficient models, as well as better insulating their residences and businesses (Peach, 1991). In theo ry, the energy saved from decreased consumption would be availa ble to satisfy any ne w electricity demand, therefore, prolonging or eliminating the need for new power plants (p. 2). Utilities and regulators in nine states, which represen ted over 33 percent of U.S. electricity consumption, estimated that the implementati on of DSM programs would eliminate up to 15 percent of the total electri city demand, which in effect is anticipated to reduce the additional demand that is expected in a particul ar year by 61 percent (p. 2). In other areas of the country however, demand-side manage ment programs are expected to avoid over 50 percent of the growth in de mand of electricity (p. 2). Utility companies are comprised of public and private utilities (p. 8). Public utilities also encompass cooperatives and account for about one-fifth the sales to customers, while the private utilities, also known as investor-owned utilities, consist of about 270 companies. These private utilitie s supply the remaining 80 percent of needed power (p. 8). Usually these ut ility companies are given a pa rticular geographical area in

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5 which they are the only power supplier and must provide service to a ll customers in that area (p. 8). Public utilitie s, regarding required rates, are not regulated by state commissions, as they are owned by the rate payers, but private utilities are always regulated by these state commissions (p. 8). State regulatory comm issions are the bodies that set the retail electricity rates that the consumers must pay based on a particular revenue requirement (p. 8). This is determ ined through an estimation of the amount of revenue a certain utility would re quire to meet all of its expected costs while also earning a rate of return on the investment (p. 8). At the federal level, the Federal Energy Regulatory Commission controls all wholesale electri city rates and all interstate power sales (p. 8). The Department of Energy’s power marketing administrations, which are composed of the Alaska, Bonneville, Sout heastern, Southwestern, and Western Area Power Administrations, in conjunction with the Tennessee Valley Authority sell power from federally owned generating plants to cu stomer utilities at wholesale rates (p. 9). The public utilities have priority over the pr ivate utilities for all power purchases from federal agencies (p. 9). The expected constant increase in demand for electricity will require these companies to create a larger generating capaci ty to fulfill the expected need. However, according to the Department of Energy in 1990, utilities only planned to build enough new power plants to cover 25 percent of the estimated megawatts of electricity needed by 2000 (p. 9). In response to this, the Nort h American Electricity Reliability Council suggests that the remaining three-quarters of new demand be met from alternate sources of electricity such as pump ed storage, hydropower, and new natural gas, coal, utilityowned oil, and nuclear power plants (p. 9). Any remaining demand that is not met could

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6 be supplied by non-utility genera tors (p. 9). These estimates are extremely optimistic as in 1990, only 37 percent of the expected add itions were actually in the construction process (p. 9). Of those, only two-thirds were over half completed (p. 9). As the planning, construction, and licen sing of large power plants requires about 10 years of time, and with current fear of the long te rm environmental consequences of new power plants and the need for generating electrici ty, the option of creating several new power plants seems unrealistic. Demand-Side Management Technologies The technological aspect of DSM programs can be beneficial to the success of the demand management process. Studies co mpleted by the Electric Power Research Institute (EPRI) and the Rocky Mountain In stitute suggested that with current technological advances that increase efficiency, reductions in electricity demand could reach between 24 and 75 percent (p. 10). This percentage does not reflect DSM programs alone but instead signify the potenti al savings that coul d be possible if all available technologies were adopted (p. 11). The researchers deducte d that this reduction in electricity demand, which is equally di stributed among commercial, industrial, and residential sectors, could take place if cust omers simply replaced the current and less efficient technologies with newer, more effici ent ones (p. 11). However, there are some impediments to this suggestion as EPRI stat ed that “Only a fraction of the efficient technologies will be cost-effective at current pr ices of electricity and end-use equipment, and not all customers will implement these cost-effective actions” (p. 12). Researchers at the Rocky Mountain Institute suggested that if the country retrofits its capital stock and implements 1,000 new electricity-saving techno logies, which is currently feasible, the savings potential could reach 75 percent of present power use (p. 12). The nation has

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7 many opportunities for reducing energy consum ption, the most substantial being in heating and cooling, motor usage, lighting, and refrigeration equipment (p. 10). For example, incandescent light bulbs could be replaced with compact fluorescent bulbs which produce the same amount of light and use only 25 percent of the electricity of incandescent bulbs (p. 10). As lighting repres ents one-fourth of the total electricity usage in the United States, this simple cha nge could have profound effects (p.10). Effectiveness of Demand-Side Management Programs As billions of dollars were being spent every year on demand-side management programs, there was a heavy debate between the money spent for these programs and their relation to performance in reduci ng energy costs by shif ting peak loads and decreasing individual consumption (Sonnenb lick, 1994). A project submitted by the Database on Energy Efficiency Programs (DEEP) aims at settling this debate in terms if economic feasibility (p. 1). DEEP set out to document the measured cost and performance of utility-sponsored energy efficiency DSM programs and made adjustments to standardize DSM programs (p. 1). When twenty commercial lighting companies were observed, all twenty programs were judged co st effective when compared to avoided costs in their local areas (p.1). This is precisely what attr acts utilities to demand-side management programs. In promoting efficiency in electrical usage, utilities suppor t installing new and more efficient technologies, providing valuab le information to consumers about benefits and opportunities of being mo re economical in energy c onsumption, and rebating or subsidizing the installation costs or purchase s of newer and more efficient technologies (Peach, 1991). Improving the economic efficien cy by investing in less costly resources to attain the same level of benefits is a nother benefit provided by DSM programs (p. 12).

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8 These programs were intended to be cost-eff ective and when implemented successfully, create a situation in which it is cheaper to conserve a kilowatt-hour than to generate one using other resources such as oil, coal, or nuclear energy (p. 12). The environment was another benefactor of properly executed DS M programs as less electricity usage creates fewer pollutants that are released into the atmosphere. As the burning of fossil fuels, mainly oil, natural gas, and coal, account for over two-thirds of all en ergy created in this country, the generation of electri city contributes to over 65 pe rcent of the sulfur dioxide, and over 30 percent of both the nitrogen oxide and carbon dioxide that is emitted into the environment (p.12). These pollutants have been linked to global warming and other hazardous conditions, such as acid rain, so a reduction in the total amount of these gases that are emitted is vital to the surviv al of our atmosphere and planet. DSM programs may also eliminate the need for the utility to invest in more generating capacity by building new power plants (p. 13). When the programs have been proven cost-effective, the amount of current generating capacity higher than a utility’s normal requirements is minor and therefore, the need to create additional generating capacity is removed (p. 12). The economic viability of DSM programs greatly depends on whether or not it can alleviate the need to construct new capacity to meet demand (p. 13). DSM programs aim to satisfy the system growth needs and not displace the existing power generating plants (p.19). These progr am savings may not offset operating costs alone and utilities could be relu ctant to idle any existing capacity as this could potentially decrease the “rate base” on which the utility ear ns its financial returns (p.19). It makes more economical sense to bypass new plant c onstruction in favor of utilizing current excess capacity and lowering consumption across th e board. This factor is one of the first

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9 that is observed when deciding whether or not to implement a DSM program that will benefit a specific utility. To aid in minimizing the effects of barri ers to DSM programs, many federal laws were enacted to promote such efficient electricity use (Peach, 1991). The National Appliance Energy Conservation Act of 1987 (P .L. 100-12) created efficiency standards and labeling requirements for 13 types of home appliances while the Hoover Power Plant Act of 1984 (P.L. 98-381) requires the Wester n Area Power Administration to introduce new provisions into its sales contracts wh ich demand all customer utilities to employ conservation programs (p. 10). The Ener gy Conservation and Production Act (P.L. 94385) approved federal financial assistance for any implementation of all efficiency improvements in existing bu ildings and industrial plants (p.10). The Act also incorporated provisions that will establish efficiency standards for all buildings that receive this financial aid ( p. 10). The National Energy Conservation Policy Act (P.L. 95619) authorized federal financial assistan ce for any installation of efficiency and conservation measures in hospita ls and schools, and also aide d in financing state energy conservation plans (p. 10). The goal of increased efficiency has met some challenges which have impeded the overall success of DSM programs. The major ity of electric rates are normally based on average production costs rather than the marginal production costs associated with new capacity, which are commonly higher costs (p.4) . These rates also do not include other costs of producing electricity such as environmental and soci etal costs, which may prove of greater importance in some areas. The curr ent regulatory practices may also assist in negating the positive effects of DSM programs. These conventional approaches associate

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10 the revenues and profits of utilities directly with the electricity sales and therefore, provide very little incentive for utilities to implement DSM programs (p. 4). If utilities within the scope of th ese practices decided to initiate DSM programs, electricity sales may be decreased which would in turn also de crease profits earned. In addition to the possibility of reduced profits, there is littl e incentive for utilities to reduce the existing energy demand as doing so may idle some of the capacity that has al ready incurred great capital costs (p. 4). From an economic st andpoint, utilizing DSM programs may only be practical if they substitute for the additional generating capacity in lieu of simply substituting for the increased use of ex isting generating facilities (p. 4). In the utility sector there is uncertainty about the ove rall effectiveness of DSM programs, which lessens the rate of impleme ntation of many of the programs. This uncertainty stems from the fact that accu rately estimating and measuring the net reduction in demand due to DSM programs can be difficult (p. 4). This difficulty is apparent as these programs may cause uni ntended changes in demand due to the consumers’ behaviors. The level of de mand that would exist without the programs implementation is also uncertain (p. 4). Ev idence confirming the accuracy of estimates of demand reduction due to DSM programs is n eeded as without it, utilities would view the majority of DSM programs as too risky an option (p. 28). There are two main reasons that account for the difficulty in measuring energy savings from DSM programs (p. 28). The fi rst reason suggests that energy savings must be estimated, as these savings cannot be dire ctly observed, and are therefore susceptible to error as is evident with all estimating methods. The second reason is that these estimates depend greatly on the analysts’ ability to measure and predict human behavior,

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11 an undertaking that has great un certainties (p. 28). There is an assortment of techniques that have been implemented by utilities to more accurately measure electricity saved through the use of DSM programs. These t echniques include monitoring electricity use for selected customers before and after pa rticipation in a DSM program, estimating the energy saving effect per installation of vari ous energy-efficient devices, and comparing the electricity use of sample groups of participants and non-participants of DSM programs (p. 28). These techniques are still subject to estimating errors, however their variety allows for a greater re presentation of the total energy savings contributed to DSM programs. Human responses to DSM programs are also very difficult to assess and predict. Utilities and regulators must take many factor s into account when determining expected savings, and must take measures to ensure that they are not attributi ng too great a level of energy savings to a particular DSM program. The utilities and regulators must account for the potential of “free riders” or people w ho would have purchased an energy efficient device or practiced energy conservation techniqu es regardless of ex istence of a utility sponsored DSM program (p. 29). Researchers believe free riders can account for 40 to 89 percent of the participants in any given DSM program in extreme cases (p. 29). However, it is extremely difficult to identif y, as well as quantify, such persons in a participant group. For example, if free ride r estimates are not accurate and regulators have approved financial return s to utilities on the basis of energy savings attributed to a DSM program, financial returns to the uti lity would also be inaccurate (p. 29). Regulators and utilities a like are concerned about the accuracy of DSM savings estimates. Regulators must have confidence that expected energy savings of a proposed

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12 DSM program are reasonable in order to de termine its cost effectiveness and possibly approve its implementation (p. 29). Utilities must rely on the savings estimates to determine the amount of additional capacity needed to meet the demand and therefore, expect the estimates to be accurate and reli able (p. 29). For DSM programs to be more widely accepted and implemented, measures must be taken to assure utilities and regulators that the resulting energy savings esti mates are accurate. Utility sponsored energy efficiency pr ograms however, are “not too cheap to meter” at an average cost of 3.9 cents/kWh (Sonnenblick, 1994). The results from this study emphasized the fact that utilities must take active measures to minimize their DSM program costs and rate impacts in order to ma ke them more beneficial and advantageous to the utility itself (p. 2). Researchers ha ve also found that consumers systematically underestimate the value of energy-efficient equi pment, which may allow utilities to play a vital role in terms of alleviating market barriers or imperfections in DSM programs (p. 2). This research suggests that the utility industry as a whole must give greater consideration to the potentia l of DSM programs in transforming the market for energy efficient equipment a nd behavior (p. 2). The Role of Consumer Behavior in Demand-Side Management Programs In research completed by the Oak Ridg e National Laboratory, it is evident that consumers regularly demand greater rates of return on investments for energy-efficiency purposes than on other non-related investme nts (Peach, 3). The most common reasons that researchers believe some consumers may not choose to invest in more efficient devices are a lack of information, a lack of funds, and inadequate marketing channels for these devices (p. 4). Some researchers s uggest that consumers may discount expected savings from energy-efficiency investments more than they discount expected returns

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13 from other investments (p. 21). It has al so been found that consumers do not purchase more efficient models of appliances or othe r devices because they are not aware of the potential monetary and electricity savi ngs certain models offer (p. 21). Often, electricity-efficient devices, incl uding air conditioners, lights, and kitchen appliances, may cost more than their less efficient counterparts. Rational consumers could be willing to purchase these more e xpensive and energy-efficient devices if these devices would save them enough on electricit y expenses to compensate for the higher initial cost. This could essentiall y be viewed as an investment with a given rate of return. Studies completed by the National Resour ces Defense Council have found that on average, consumers will purchase energy-efficien t appliances if the higher initial costs can be made up for through reduced monthly el ectricity bills within 2 years (p.22). This relatively small payback period emphasizes that consumers demand a high rate of return on energy-efficiency investments, possibly mo re so than on other investments (p.22). Also, if the consumer’s choice is not betw een two new appliances but instead between keeping an existing, inefficient model and buying a new, more efficient model, the payback period may be considered much longe r (p.22). In this cas e, the consumer may view the difference in cost as the full purchas e price of the new mode l, instead of only the additional cost of the more efficient mode l if two new devices were being compared (p.22). The method of repayment to the cust omer, the relatively small decreases in monthly electric bills, may also contribute to the reluctance of consumers to purchase more energy-efficient technologi es (p.22). This small amount of savings over time may not supply enough incentive for consumers to pay more initially for more efficient devices.

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14 The residential arrangements of consumers may also a ffect the rate of energyefficient investments. For example, apartmen t renters whose electric bills are included in the monthly rent or who pay a fixed fee for ut ilities have almost no incentive to purchase efficient technologies. In this case, these purchases only act as an added cost as the resulting decreased electricity consumpti on and energy savings are never seen by the occupant. Trends and Success of DemandSide Management Programs To combat the reluctance of consumer s to purchase and utilize more energyefficient models, some utilities have initia ted specific DSM programs aimed at aiding the consumer in financing purchases of more e fficient appliances and devices (p. 21). In addition, these programs provide consumers with vital informa tion regarding the immense benefits, short-term and long-term, of making more energy-efficient purchases (p. 21). The utilities offer financial aid in the form of incentives, such as discounts on monthly bills or rebates, when the consumer takes initiative and purchases these more energy-efficient devices (p. 4) . Utility companies have also offered to install the purchased efficient devices at the homes or businesses of the consumer and provided helpful information regarding available energyefficiency options and various methods to lower electric bills, all as part of DSM programs with a goal of decreased energy usage (p. 4). This information can be provided th rough free energy audits, appliance labels that display the appliance’s elect ricity use, and various ma ilings to consumers (p. 23). State regulators have continue d to experiment with nontra ditional approaches to the regulation process with the aim of overco ming the impediments to implementing DSM programs (p. 24). The regulatory process has been revised in several states to allow ratemaking practices the ability to present the util ities with various DSM incentives (p. 4).

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15 The revision of regulatory pro cesses was made possible by allo wing the utilities to collect increased revenues which offset lower sales due to DSM programs, as well as allowing the utilities to collect a financial return on investments for DSM programs (p. 4). This return may only be applied when the utility demonstrates that it has met its specific electricity savings targets for the period (p. 27). Some states allow the utilities to recover the DSM program costs in a way that best fits their needs, such as recovering costs as operating expenses on a quarterly basis or by amortizing the costs and recovering them over several years (p. 27). A number of states have acted to price el ectricity in a manner that best reflects the external costs associated with generating that elec tricity (p. 27). To reflect the environmental cost s of removing residual sulfur dioxide from power plant emissions, some regulators could add a predet ermined amount per kilowatt-hour to the estimated cost of electricity from coal-fired power plants (p. 27). These actions allow DSM programs, along with less polluting elect ricity-generating resources such as hydropower and solar energy, to be much more competitive when compared to traditional coal-fired power options (p. 27). Several uti lities have also employe d electricity rates to reflect any increased costs in generating el ectricity during the p eak periods of high demand, therefore encouraging customers to consume less energy during those periods, further offsetting the need for incr eased generating capacity (p. 28). In dealing with the uncertainty of th e actual impact of DSM programs, state regulators and utilities have adopted proce dures that can better assess, measure, and adjust the effects of these programs (p. 5). As an example, regulators in New York now require the utilities to annually adjust th e estimates of potential future DSM energy savings based on the actual data and experien ce from the previous year (p. 31). Other

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16 methods include more consistent data collecti on, adopting measures that allow regulators to validate the utilities’ calculations of energy savings, and taking steps to better the savings calculation and estimat e techniques (p. 30). In th e Northwest, disagreements between utilities and regulators on energy sa vings calculations led to a joint project, sponsored by the Bonneville Power Administ ration and a local environmental group, to demonstrate the potential for elec tricity efficiency (p. 30). This city-wide test, the Hood River Conservation Project, collected actual DSM electricity savings data for energyefficient technologies and disp layed that “DSM programs sustained for 1 to 3 years or more are able to achieve over 80 percent enro llment of eligible customers” (p. 30). The Department of Energy has initiated a util ity-funded project to promote consistent reporting of DSM electricity savings called the Northeas t Demand-Side Management Data Exchange (NORDAX) Pr oject (p. 31). This project assembles information on energy savings and program costs for various DSM programs from 123 utilities (p. 31). The federal power agencies’ efforts in DSM programs greatly differ, reflecting variations in each agency’s authority to encourage efficient use of power and each agency’s legislative mandate (p. 5). This is evidenced by agencies with the most extensive conservation programs in the na tion, the Bonneville and Western Area Power Administrations (p.5). These agencies have been prompted by laws that allow them link their power rates or their power allocations to the customer utilities’ DSM efforts, and laws that direct them to promote the efficient us e of electricity in particular (p. 5). On the contrary, the authorities of smaller powe r agencies, such as the Southeastern, Southwestern, and Alaska Power Administration, allow them to promote, but not require, the implementation of DSM efforts to their customer utilities (p. 5). According to

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17 Department of Energy and power marketing agen cy officials, these customer utilities are often disinclined to implement DSM programs, which is difficult to overcome without specific statutory authority to link the power rates or power allocations to the customer utilities’ DSM efforts (p. 5). Perhaps Congr ess should enact legisla tion to authorize the smaller power agencies to require their custom er utilities to implement DSM programs. Local DSM Programs in Progress Currently, Gainesville Regional Utilities (G RU) is working with the University of Florida Program for Resource Efficient Commun ities (PREC), in collaboration with the Institute of Food and Agricultural Sciences (IF AS) Statistical Consulting Unit and the M. E. Rinker, Sr. School of Building Constr uction, on a DEED Grant Award aimed at determining the most effective programs that can assist low income customers with energy use reduction. DEED, or the Demonstrat ion of Energy-Efficient Developments, is a program that was developed in 1980 by the American Public Power Association with the intent to sponsor and c onduct activities related to improving efficiencies, energy innovation, and lowering the cost of providing energy services to customers of publicly owned electric utilities. DEED offers funding in the fo rm of grants to DEED member utilities, scholarships to university students studying energy-related disciplines, and joint projects with APPA committees. APPA is the national service organization whose committees consist of community-owned, not-for-p rofit electric utilitie s. This funding is awarded for projects and programs that will demonstrate and deve lop new techniques and technologies. GRU is a multi-service utility owned by the City of Gainesville, Florida. It serves Gainesville, as well as portions of Alachua County, Florida, with water, electric, wastewater, natural gas, and telecommunications services. The utility also provides the

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18 City of Alachua with wholesale power. GRU is the fifth largest municipal electric utility in Florida and employs over 800 employees who assist in providing one or more of the available services to approxima tely 87,000 homes and businesses. The goal of this DEED grant is to complete a survey of low income households to determine the most effective programs that could be implemented to assist these households with reducing their energy use. Th e aim is also to determine the main reasons that GRU residential low income customer s on average have higher energy intensity when compared to others. This will be accomplished by surveying good energy performers in the same areas. A survey instrument will be created, as well as an analytical method, to specifi cally identify and overcome th e barriers to delivering energy efficient services to low income customers in the most cost effective manner. After the surveys have been designed and completed, the results will aid in developing plans and programs to minimize the power demand and energy use of these customers. These plans and programs will include detailed timelin es, budgets, program descriptions, and appropriate measurements of energy use. The project applied for and received a DEED grant in 2005, and began in October of that year. The total duration, including a granted extension, will be one calendar year with a completion date of October 1, 2006. GRU worked with PREC and graduate students from the M.E. Rinker, Sr. School of Building Construction to develop a survey which was completed March 31, 2006. The survey had many drafts but the final survey was approved in early April by the IRB, or the Institutional Review Board of the University of Florida. All parties involv ed with the actual survey administration and collection of data met to collaborate on th e best method of delivery. Two particular

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19 attributes of the population of GRU customers motivated the development of this survey. In implementing a Graphic Information Syst em (GIS), the highest residential energy users within the service area of GRU were id entified. From this first GIS map, another map was created to display the energy intensity of each residential dwelling unit that was included in the first map (See Appendix A). The attributes that motivated the survey development were revealed when the (GIS) data was combined with the customers’ energy use data into one map. First, many low income customers consume significantly more energy per square foot of air-conditio ned living space (i.e., their ‘energy intensity’ is higher) than high income customers. Second, although average energy intensity among low income households is relatively high, a fair portion of these households perform relatively well with respect to energy ef ficiency (i.e., their energy intensity is relatively low). The survey instrument was designed, with the awaren ess of the customer characteristics, to answer the question: What factors (structural features, demographics, behavioral patterns, etc.) cause and/or allo w some low-income households to demand significantly less energy pe r square foot than others? The identification of the major factors th at distinguish low energy intensity, low income (‘LL’) households from high energy intensity, low income (‘HL’) households by comparing survey responses across these two groups of customers was the main goal of this study. The households were coded as LL if their average monthl y energy intensity in 2005 was less than 454 kWh per 1000 square feet and we re coded as HH if their average monthly energy intensity in 2005 was greater than 1096 kWh per 1000 square feet. In order to identify factors that are statistica lly significant at 95% confidence levels, the sampling target was to complete 196 surveys of LL households and 196 surveys of HL

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20 households. The survey instrument had two components: 1) a brief mail-administered recruiting survey and 2) an in-depth in-home energy survey completed by a GRU Conservation Analyst and a trained Univer sity of Florida graduate student. A random sample population was taken from this second GIS map and was sent initial questionnaires to determin e the eligibility of these sele cted customers to participate in the survey (See Appendix B). This recr uiting survey was meant to invite randomly selected households from both the LL and HL customer populations to participate in the in-home energy survey. Name 1 2 3 4 5+ Under $20,000 $20,001 to $25,000 $25,001 to $30,000 $30,001 to $35,000 $35,001 to $40,000 $40,001 to $45,000 $45,001 to $50,000 Over $50,000 Natural Gas Propane 1000 Source Code: Thank you for your participation! 4. How long have you and your family been living in this household? Less than 1 year 1-2 years 2-4 years 4-6 years More than 6 years 2. What is your combined household's annual income before taxes? (See Box 1 on your W-2 forms) 3. What type of water heater do you have? Electric Other______________________________________ Survey Questionnaire Instructions for Head of Household: Please complete the survey questions and mail back to GRU in the pre-paid envelope provided by February 24, 2006. Thank you for your participation. Phone Number (To schedule energy survey)1. How many people live in your household? Figure 2-1: Mail-adminis tered Recruiting Survey This initial survey asked for general de mographic information of the household, as well as willingness to participate in the surve y. This survey was approved on February 7, 2006, and was sent February 17, 2006, via sta ndard U.S. Mail in the form of the recruiting survey with an invitation cover letter signed by the Peegan Hanrahan, the Mayor of Gainesville (See Appendix B). This initial survey was sent to 1000 customers (500 HL and 500 LL) and included a “respond by” date of March 3, 2006. From the households that responded to the initial su rveys and were considered eligible to participate based on income level, telephone cal ls were made to the respondents in order

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21 to schedule an appointment for an in-home survey and energy audit to be completed. Follow up telephone calls and follow up maili ngs, if necessary, were made to nonrespondents from the initial sample populati on of 1000 households. This was completed prior to sending an additional 1000 maili ngs to other LL and HL customers. It was decided that a gradua te student from the M.E. Ri nker, Sr. School of Building Construction would go to each home with a GRU conservation analyst. The GRU conservation analyst completed an energy a udit which consisted of only the physical aspects of the house or apartment. The survey included an in spection of the HVAC system, appliances, the building itself and its structural components, and observation of the premises for any potential leaks. While the GRU conservation analyst completed the technical survey, the occupant s of the household completed an in-home survey given by a graduate student from the University of Florida. The survey concentrated on the occupants’ knowledge and awar eness of their dwelling, as we ll as the specific behaviors of the occupants relating to the energy issu es in a household. Surveys were completed by both home owners and renters in low-income households. These surveys began at the end of April, 2006, and continued through th e end of July, 2006. Upon completion of all surveys, the data collected was analyzed and it was determined which issues played a role in the high energy intensity of low income cu stomers. GRU aimed to complete 392 total surveys to low income households, broken dow n into 196 surveys administered to highuse households and 196 to low-use households. Summary At a time when the entire country is beco ming increasingly reliant on electricity to satisfy the growing energy needs, utilitie s are depending on DSM programs to aid in balancing the electricit y supply and demand. A few key fact ors in securing the success of

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22 DSM programs include instituting regulatory stra tegies that encourage a commitment to the programs and creating a cost-effective me thod of measuring the many impacts of DSM programs. The history of Demand-Side Management programs is not lengthy but does indicate the initiation of a movement toward a more e fficient use of energy through the implementation of programs which reduce overall energy demand. This technique of implementing programs to aid consumers in reducing the total amount of electricity consumed was expected to offset the need for utilities to construct new and expensive power plants. Through successful DSM programs, utilities can help consumers save money as well as reducing their own genera ting costs, due to a reduction in overall demand, especially during peak times. The effectiveness of DSM programs has co me under intense scrutiny. The main debate lies in the relationship between the costs associated with the DSM programs and the savings realized by the utility due to sh ifting peak loads and decreasing individual consumption. Many utilities view the DSM programs as a non-cost-effective option for electricity savings and this fact highly cont ributes to the barriers DSM programs face. These programs do offer several benefits to both utilities and cu stomers alike. DSM programs may improve economic efficiency, le ssen the burden on the environment due to a reduction in the building of new power plan ts and the burning of fossil fuels, satisfy system growth needs, decrease peak demand, and save utilities money in new generating costs. However, there are many barrier s to the implementation of DSM programs including, current regulatory pr ocesses, uncertainty about program effectiveness, and the difficulty in measuring energy savings attributed to DSM programs.

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23 Consumer behavior plays an active ro le in these DSM programs as their willingness to participate determines the succe ss of the program. It has been shown that consumers regularly demand greater rates of return on investments for energy-efficiency purposes than for other non-related inve stments. In making DSM programs more successful, there must be a gr eater incentive for pur chasing more efficient products and technologies. Some trends of DSM programs are aimed at helping the consumer in financing the purchases of mo re efficient devices and appliances. Consumer education about energy usage, as well as efficien t technologies and habits, has also been approached through various DSM programs. Al so, state regulators have experimented with nontraditional approaches to the regulat ory process in hopes of overcoming any and all obstacles to proper implementation of DSM programs. They have also adopted procedures to better assess, measure, and adju st for the effects of these programs such as requiring utilities to annually adjust the es timates of potential future DSM energy savings based on actual data from the previous year. Locally, Gainesville Regional Utilities is working on a DEED grant for a DSM program that will determine the most effective programs that will assist low income customers with energy use reduction. Upon co mpletion of the grant, they will plan for and implement various DSM programs to edu cate local consumers in efficient energy usage and aid in financing projects to insta ll more energy-efficient devices and appliances in these low income households. DSM programs, such as this one, have the potential to greatly impact the way consumers and utilities use electricity and also have the ability to decrease overall dependen ce and demand of energy.

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24 CHAPTER 3 METHODOLOGY Introduction In order to collect the necessary data to identify the factors that lead to high energy intensity in low-income households in Gainesvi lle, Florida, and to determine specifically the role of occupant behavior, an implementa tion plan was designed to begin the process. In the sections that follow, the designing of the survey, the selection of the sample size, and the survey distribution measures will be explained. The specific data collection methods will be given, as well as a summary of the entire research process leading to the analysis and observations of the collected data. The methodology of this research was dete rmined by the objectives of this thesis and the hypotheses stated in Chapter 1. The steps taken were as follows: 1. A literature search was performed to collect any related data and to determine if studies relating to the topic had al ready been performed elsewhere. 2. The particular data necessary fo r this research was identified. 3. In implementing a Graphic Information Syst em (GIS), the highest residential energy users within the service area of Gainesv ille Regional Utilities were identified. 4. From this first GIS, another map was create d to display the energy intensity of each residential dwelling unit that was included in the first map. 5. An initial survey was sent out to determ ine consumer eligibility for the survey. 6. A survey questionnaire was desi gned to obtain pertinent data. 7. The surveys were administered to collect the data. 8. Statistical methods, both analytical and de scriptive, were implemented to assess significance of certain factors re lated to high energy intensity. Designing of Survey The design of the survey focused on a mean s of collecting pertinent information in order to characterize energy use and awareness, and to decipher the ma in factors that lead

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25 to a high energy intensity in many low-inco me households. Several factors were identified that may have possibly contribute d to the areas of high energy intensity and therefore, high energy bills. These factors in cluded the age and type of construction of the structure, the number of people living in the households, th e age, condition, and number of appliances in the household, as well as the possible lack of incentive by absentee landlords to upgrade appliances to more energy-efficient models. The age and type of air conditioning and heating systems in use and the lack of tree cover around the dwelling were also signifi cant factors. Additional fact ors that were taken into consideration included the availa bility of natural gas which often offers a more efficient energy source, a possible lack of knowle dge about conservation opportunities and potential savings, a lack of pr ice signal related to energy us e (flat rent rate including utilities), and whether the structure wa s tenant-occupied or owner-occupied. Collaboration was coordinated with the PR EC team in developing some of the questions for the in-home survey to be given to the participants of the DEED research study (See Appendix C). The questions of most interest related to th e behavioral aspects of the day-to-day lives of the occupants. Focus was placed on behaviors that lend to greater energy usage and have the potential for greater energy savings by reducing the occurrence of the specific behavior. Certain areas of interest were develo ped and focused on when developing the questions. As heating, ventilati on, and air conditioning use a la rge percentage of the total energy used, it was best to address that issue first. There are specific target temperatures for both heating and cooling which have been set by agencies and utility companies alike. The recommended target temperatures for ther mostat settings are 68 degrees Fahrenheit

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26 for heating and 78 degrees Fahrenheit for c ooling. Any deviation from this target temperature can greatly affect the energy bill of the household so it was imperative to get a feel for what the average household thermo stat was set for. According to Amy Carpus1, a Conservation Analyst at GRU, for every de gree above or below th e respective target temperature, the energy usage and bill is incr eased by four percent (4%). For example, if a household normally set the thermostat for summer cooling at 76 degrees Fahrenheit, their energy bill would be eight percent (8%) higher than normal. However, if the thermostat was set at 80 degrees Fahrenhe it for summer cooling, their energy bill would be eight percent (8%) less than normal. The research team collaborated in the development of questions that determined th e typical temperature that a household kept its thermostat set at for bot h winter heating and summer cooling (Questions 21, 26). The importance in determining the daily be haviors of the occupants relating to the heating, ventilation, and air c onditioning systems was noted. For this, aid was given in developing questions which asked about the thermostat setting, for both winter heating and summer cooling, when the occupant was away from home (Questions 22, 27). Also, it was imperative to determine the frequency of filter change in the air conditioning system as this is an important factor in the efficiency of the air conditioning system. If the filter is not changed on a regular basis, the system cannot operate in its full capacity and becomes more energy inefficient, therefore increasing the amount of energy used and increasing the electricity bill. The respectiv e question (Question 29) was developed to determine if the frequency of changing the f ilter was a significant problem area in the 1Carpus, Amy. (2006) Interview. Conservatio n Analyst at Gainesville Regional Utilities.

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27 participating households and if this topic should be focused on in future plans for demand side management programs. In rounding out the heating, ventilation, and air conditioning aspect of the survey, it was also pertinent to determine the frequency of opening windows, especially during more comfortabl e months, in Gainesville, Florida. The question (Question 30) asked which specifi c months, if any, were windows opened on a regular basis for natural vent ilation. The frequency of ope ning windows was important to determine as the opening of windows woul d eliminate the need for any heating, ventilation, and air conditioning systems and th erefore, decrease the energy consumption of the household. Knowing that clothes dryers also have th e potential to be larg e energy consumers, a question relating to the regularity of households in hanging their clothes to dry instead of always relying on the clothes dryer was included (Question 42) . As an area of possible improvement on household energy consumpti on, this issue should be addressed. Light use is another area th at would be addressed as it also had the potential to be greatly reduced by modifying the behaviors of the occupants. The amount of lights that are used in a home each day can be a large component in the total energy use and energy costs of the household. In developing questions relating to this matter (Questions 46, 47, & 48), it was important to determine the typi cal amount of hours th e indoor lights were on each day and also, how many rooms had th e lights on during those hours of indoor lighting. If the number of hours that lights were on was high on average, this would prove a pertinent matter to incorporate into demand side management programs. These programs could educate occupants of the bene fits and energy saved by simply turning off the lights when a room is not occupied or when daylight is br ight enough and indoor

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28 lights are not needed. The type of indoor lights used is signif icant in that the use of only standard incandescent light bulbs will cons ume a greater amount of electricity and essentially cost more than using fluorescen t or compact fluorescent light bulbs for the same amount of time. Compact fluorescent bu lbs use less than one third of the energy used by standard incandescent bulbs and em it the same wattage. Compact fluorescent bulbs also do not emit heat, unlike standard incandescent bulbs, a nd therefore do not add to the heat load of the house which is pr incipal during months of summer cooling. The use of televisions was an important f actor as many televisi on sets, especially large screen and older models, use a great amount of energy in the home. The number of televisions, as well as how long each television is turned on, can play an integral role in the energy consumption of a household. In developing the appropriate questions (Questions 52 & 53), the aim was to determin e how long at least one television was on in a typical day. The response options consis ted of two-hour time increments that would allow for a general estimation from the occ upant. The respective results can then be compared to determine an average time, among pa rticipants, that at least one television is in use and will allow the researchers to determine if a given household’s daily television use is above or below the average. Once the average time is establis hed, it will determine if television usage is a factor that should be included in later demand-side management programs. Evidence suggests that the occupant’s educa tion level, in terms of energy usage and energy efficiency knowledge, has a strong e ffect on the way energy is used in the household. It was vital to discover what the occupant thought contri buted to the energy usage of the household (Question 63). The resu lts of this question aim to shed light on

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29 any common misconceptions of energy usage an d allow for more targeted and effective demand-side management programs. The ques tions that follow (Questions 64, 65, & 66) relate to the occupant’s t houghts, actions, and education on the subject. The questions revealed the occupant’s level of concern related to energy costs in their home, the occurrence of any changes, in either their life style or their home, ma de in the past year that made the home more energy efficient, and any awareness of current programs that could lower the household’s energy bills. Selection of Sample Size The selection of the sample size was governed by the D EED grant and its requirements. The DEED project called for about 400 total partic ipants; a goal of 196 low-income, low users (LL), and 196 low-inco me high users (HL). This sample size was required to identify statistically significan t factors of household energy use at a 95% confidence interval. For the purpose of this exploratory research, the sample size was exactly one hundred participants, or about one fourth the sample size of the entire DEED project. To ensure that the appropriate quantit y of surveys was collected for each group, LL and HL, the targeted households were coded for one of the two groups. The households were coded as LL if their averag e monthly energy intensity in 2005 was less than 454 kWh per 1000 square feet and were coded as HL if th eir average monthly energy intensity in 2005 was greater than 1096 kWh per 1000 square feet. Survey Distribution A Graphic Information System (GIS) wa s applied and the highest residential energy users within the service area of Gain esville Regional Utilities were identified. From this GIS map, another map was created to display the energy intensity of each

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30 residential dwelling unit that was included in th e first map. The attributes that motivated the survey development were revealed when the (GIS) data was combined with the customers’ energy use data into one map (Appendix A ) . From this map, geographical areas with high and low energy intensity we re identified and a random sample population was obtained. This population was sent pre liminary questionnaires to determine the eligibility of the customers in meeting th e research objectives and requirements. The household income eligibility was based on 2005 HUD Low Income Criteria for Gainesville, Florida. “Low-Income” was define d as 80% of the Median Family Income (MFI) which was $53,550 for the 2005 Fiscal Year in Gainesville, Florida. Table 3-1 below displays the criteria used for low-in come households in Gainesville, Florida. Table 3-1: 2005 HUD Low Income Criteria Number of Residents in Household 1 2 3 4 5 6 7 8 Low-Income Cutoff $30,000 $34,300 $38,600 $42,900 $46,300 $49,750 $53,150 $56,600 This initial survey was sent along with a le tter from the Mayor of Gainesville, Peegan Hanrahan, encouraging participation in the program (Appendix B). 1000 of these preliminary surveys (500 LL and 500 HL) were sent to GRU customers. From the households that responded to th e initial surveys a nd were considered eligible to participate in th e study, telephone calls were made to the respondents in order to schedule an appointment for the administ ration and completion of an in-home survey and energy audit. Follow up telephone calls and follow up mailings, if necessary, were made to non-respondents from the initial sample population of 1000 households. This was completed yet the number of responde nts was inadequate. Another cycle of preliminary surveys was sent to an add itional 1000 GRU customers with the same

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31 breakdown of 500 LL customers and 500 HL customers. Again, eligibility was determined from this second response group a nd telephone calls were made to schedule the appointments for the energy audit and in-h ome survey. This second cycle of mailings produced a response that gave the DEED study enough participants to create statistically significant results. Survey Data Collection From the households that responded to the initial surveys, call s were made to the respondents in order to schedule an appointme nt for an in-home survey and energy audit to be completed. At each appointment, a GRU conservation analyst and a graduate student would arrive and complete the survey s, collecting data about the household. The GRU conservation analyst completed an en ergy audit which consisted of only the physical aspects of the house or apartment. This survey included an inspection of the HVAC system, appliances, the building itsel f and its structural components, and observation of the premises for any potential leaks. While the GRU conservation analyst completed the technical survey, the occupa nts of the household completed an in-home survey given by a graduate student from th e University of Florida. This survey concentrated on the occupants’ knowledge and aw areness of their dwelling, as well as the specific behaviors of the o ccupants relating to the ener gy issues in a household. The completed surveys were then received by th e PREC members who were responsible for compiling the survey responses in a spreadsh eet format. These spreadsheets were then distributed to the University of Florida pa rticipating graduate st udents and Gainesville Regional Utilities for review.

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32 Summary In completing the research for this stu dy, many steps were taken to ensure proper population sampling and data collection. The co llected data was us ed to identify the factors that lead to high en ergy intensity in low-income households in Gainesville, Florida, and to determine th e specific role of occupant behavior in household energy usage. The process of this research was disc ussed including the desi gning of the survey instrument, the selection of the sample si ze, the survey distribution, and the data collection methods. After describing the methods of this research, the following chapter will discuss the specific analysis and obs ervations of the collected data.

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33 CHAPTER 4 DATA ANALYSIS Introduction In completing the surveys and gathering all relevant data from the research participants, it was evident that certain behavi oral factors were recu rring and in need of further analysis. Several of the participan ts exhibited everyday behavior typical of extremely energy-consumptive lifestyles, usua lly oblivious to the effect it had on their energy bill. There was a significant differen ce in the behavior patterns of low energy intensity, low income (LL) households a nd high energy intensity, low income (HL) households. This observation allows the a ssumption that occupant behavior greatly affects the energy intensity of a household and therefore, play s a significant role in the amount of energy consumed in a household. This stated, it is apparent that in order to reduce individual demand, with a goal of decreasing overall energy demand, demand-side management programs should focus on beha vior, concentrating on energy usage education, as a means of lowering energy c onsumption and in turn, lowering utilities’ costs associated with an increa sed need for generating capacity. Individual Question Results The behavior-related questions in the survey aided in shedding light on the differences in the occupant behavior of lo w energy intensity, low income households and high energy intensity, low income households. When a certain question garnered a large difference between the responses of the LL pa rticipants and the HL participants, it was obvious that the particular behavior related to that question should be given attention in

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34 the demand side management programs th at would follow this research. When appropriate, a “No Response” category was incl uded in the charts and is designated by “NR” within the chart or graph. Questions 1 through 18 were not included in the data analysis section of this research as they focused on the physical characteristics of the home and did not discuss the be havioral factors in a home. As behavioral factors in the household are the focus of the research at ha nd, only survey questions relating to these factors were included in the analysis. Heating Systems The results in Figure 4-1 suggest that the primary heating systems that are used in low income households in Gainesville, Flor ida are electric resistance systems, heat pumps, and natural gas furnaces. Electric resistance systems accounted for about one third of all households, while heat pumps and natural gas furnaces each accounted for about 25% of the households surveyed. About 80% of participants also stated that they used no secondary heating systems to suppl ement the primary method of heating their homes. About 60% of the participants had standa rd thermostats to control their main heating system while only about 25% had programmable thermostats. Programmable thermostats offer options to control the hous ehold temperature while away from home, therefore allowing greater ease in using energy more efficiently. According to Gainesville Re gional Utilities, the ideal temperature setting for winter heating is 68F. For every degree above 68F, the cost of operating the heating system increases by 4%. For every degree below 68F, the cost is lowered by 4%. This fact is unknown to most households and can greatly affect the energy costs the household incurs. Therefore, it should be the focal poi nt of demand-side management programs as

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35 higher costs can easily be reversed with simple behavior modifications. Once the knowledge is out there, it is up to the occupa nts to use that knowledge to aid themselves in lowering their monthly energy bills by not setting the thermostat at extreme temperatures. Figure 4-2 demonstrates the relationship between the increased cost associated with higher heating temperatures and the percentage of participants that set their thermostats at varying temperature interv als. The graph also shows that 27% of the sample population kept their thermostat for he ating set at 68F or lower. In addition, it shows that 14% of the population kept th e thermostat around 76F and that these households have an energy bill that is 32% highe r than if the thermost at had been set to the recommended temperature. The majority of respondents, about 60%, ch anged the thermostat setting when they left the home. Most that did change the set ting turned the heating system off while they were away which can save both energy and money. There is no need to heat a home when there is nobody present and it s eems that this fact has proven effective for the population that turns their heating off when away as th is was the case in every low income, low use household that was surveyed. Occupants were asked if they changed the thermostat or other heating control when they were sleeping. Figure 4-3 demonstrates th e results of this signi ficant question which relates to heating and the comfort level of the home while peopl e are present but not awake. Note was taken that households of primarily senior citizens often turned the heating off when away from the home but did not change the heating setting when they went to sleep, adding to the hi gher percentage of respondents that changed the thermostat setting when away compared to when asleep. Perhaps this is due to the idea that older

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36 persons are more sensitive to the cold and th erefore, need a warmer and more constant temperature to be comfortable. The percentage that did change the heating control when sleeping either turned it off or lowered the temperature. Cooling Systems Figure 4-4 shows that almost three-quarters of the survey participants used electric central air conditioning systems as the prim ary cooling system of the household. About 20% of the respondents relied on window or in -wall air conditioning units for the cooling in their home. 3% of the homes surveyed us ed an air conditioner powered by natural gas and 6% relied solely on ceiling fans to c ool their homes. In most cases, the air conditioning system is the single highest c onsumer of energy in the household. 60% of participants had a standard thermostat for their cooling systems while only one-quarter had programmable thermostats. Programmable th ermostats offer the ability to control the setting while away from home, having the potential to greatly reduce the amount of energy consumed if used wisely. Almost half of the survey participants st ated that they had no secondary source of cooling. Of those households that did have a s econdary source of coo ling, the majority of them used ceiling fans in their home. A larg e issue with ceiling fans is the misconception that they use very little energy. Many homes were found to have ceiling fans turned on in rooms that were empty, which can noticeably increase the amount of energy consumed in a home. This factor can be greatly minimized if occupants are informed that ceiling fans should only be used when th ere are people in the room. The recommended thermostat setting for c ooling is 78F. For every degree below 78F, the associated energy costs increase by about 4%. For every degree above 78F, the associated energy costs decrease by about 4%. According to Figure 4-5, almost half

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37 of the surveyed population kept their thermo stat at or above 78 F, possibly lowering expected energy costs. The graph also show s that 22% of the population surveyed keeps their thermostat at a setting which can incr ease their energy bills by up to 16%. Some of the participants that kept the thermostat setting well below the recommended 78F setting were actually wearing sweaters in side during the hottest time of the year in Gainesville, Florida. This situation occurred in homes th at had high energy intensity and complained that their energy bills were t oo high. If these occupants coul d be educated about energy use in their homes and modify their behavior s, an enormous savings could be realized. Air conditioning is an area of high energy usag e and many times is the largest consumer of energy in the household. Attent ion to this issue is required and with proper behaviors and maintenance, such as recommended thermo stat settings and leaky duct repair, a great deal of energy and money can be saved. 60% of participants responded that they changed their thermostat setting when they were away from home. Of this percenta ge, the majority of respondents reported that they turned their air conditioner off while they were away, while the remaining participants set the thermostat at a higher temperature but kept th e cooling system on. This change in thermostat setting while away was a factor that was characteristic of the low income, low use households. By changing the setting, they save money on cooling while there is nobody in the home and when cooling is unnecessary. A much smaller percentage of participants responded that they did change the thermostat setting when sleeping when compar ed to those that changed the thermostat setting while away. Figure 4-6 displays that th is percentage is fair ly low at 37%. This shows that some of the partic ipants realize that when at rest and sleeping, their bodies

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38 produce less heat and need less cooling to remain comfortable. This factor has the potential to produce great savi ngs as the period of sleeping, averaging about eight hours, is equivalent to a third of a day. If the coo ling system can be used minimally during this period, energy savings can be significant. As shown in Figure 4-7, only about one thir d of the participants changed their air conditioning filter at the recommended inte rval of once a month. Of the remaining percentage that changed their air conditioning filter too infrequently, very few of them actually had filters that were supposed to be changed at the longer intervals of time, such as once a year or once every six months. Th e amount of energy consumed in a household is greatly increased by this factor. When th e filters are not changed in a timely manner, the air conditioning unit cannot wo rk at its highest efficien cy and also, may not get a chance to stop running. When the filter is excessively dirty, the air conditioning unit cannot pull air through it as easily and therefore, must work harder to get the required amount of air needed through the filter. Many times, the air conditioner will not cool the home as quickly and in response, the occupa nt will lower the thermostat to a desired temperature and make the unit work even ha rder and consume more energy. The issue is vital to necessary energy c onservation that must be emphasized in community outreach programs and demand-side management program s. There is a great amount of energy to be conserved and money to be saved if a household would change the air conditioning filter once a month or when suggested by the air conditioning manufacturer. Over a third of the participants never opened their windows for natural ventilation throughout the year, according to Figure 4-8. The next highest res ponse suggests that about 11% of participants regularly open their windows six months out of the year.

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39 Opening windows for natural ventilation allows the home to be conditioned naturally by the outside environment and eliminates the need for energy-consuming cooling systems to be used. In addition to saving energy, re gularly opening windows a llows fresh air into the home and eliminates stagnant air, allo wing for a healthier indoor environment and better indoor air quality. Hot Water Usage There is a relatively equal split between electric and gas water heaters in the surveyed households shown in Figure 4-9. Th e difference in energy usage of these two types of water heater is minimal. Many re spondents that used gas water heaters did however mention that they were hesitant to touch or adjust the water heater because of the danger when using gas. Regardless of the type of water heater , a common issue with water heaters was the temperature setting. Many times the temperature was set above 130F when the recommended temperature setting is around 115F. Another common issue with water heaters was un-insulated pipe s which carry and distribute the hot water. These differences may seem minimal, but when the water heater is working to constantly keep the water temperature at a much higher level and heat is lo st through distribution, the appliance is consuming significantly more energy. This increase in usage can affect the monthly cost of energy, especially with the rising gas prices. The research data shows that the highest re sponse rate was from participants that do not know the age of their water heater. This is significant as many participants may have water heaters that are very old and extrem ely inefficient when compared to newer models. Most occupants are unaware of the difference a newer, more energy efficient water heater will create on the energy usage of the household. Also, a high percentage of participants had a water heater that was less than two years old. This shows that almost

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40 20% of the respondents are saving energy by usi ng a newer device, which could be due to an increased awareness of the energy-saving pot ential of energy-efficient appliances such as those with the EnergyStar logo. Figure 4-10 corresponds direc tly to the amount of peopl e living in the household. In this case, the highest response group indi cates a household with about two people. This is consistent with the response rate of participants that stat ed they had two people in their households. For the most part, participants ba sed their responses on one shower or bath per day, per person. The group with the highest re sponses in Figure 4-11 consis ted of participants that stated the average shower time in their hous ehold was six to ten minutes. The longer the shower, the more hot water is used, and the more energy consumed. The highest response group seems to exemplify a good target time for bathing as anything extremely higher than this could create a significantly higher energy bill. Household Laundry Process As 95% of participants had a washing machine in their home, this is an area that people can benefit from energy awareness. It should be focused on in demand-side management programs as there is great pot ential for a change toward greater energy efficiency and reduced energy consumption, as the population that could be impacted with energy savings would be very large. The research data s hows that the highest response rate was from participants that do not know the age of their washing machine and those whose washing machine was two to five years old. This is significant as many participants may have washing machines that are very old and extremely inefficient when compared to newer models. Most occupants ar e unaware of the difference a newer, more energy efficient washing machine will create on the energy usage of the household. Also,

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41 a good percentage of participants had washi ng machines that were less than two years old. The data shows that almost 20% of th e respondents are saving energy by using a newer device, which could be due to an increased awareness of the energy-saving potential of energy-efficien t appliances such as thos e with the EnergyStar logo. Figure 4-12 demonstrates that the highest response groups were participants that washed three to five loads of clothes per w eek or less. The information relies directly on the number of people in the household. When wash ing clothes, it is important to be aware that using hot water consumes more energy th an washing with warm or cold water and should be done as seldom as possible. Also, it is much more energy efficient to wash a full load of wash than a smaller load and th is should be utilized whenever possible. In this case, the results were in the averag e range and demonstrate that demand-side management programs should focus their reso urces on more pressing issues of energy consumption. In the laundry cycle, dema nd-side management programs should focus more directly on reducing the use of clothes dryers as they consume significantly more energy per wash cycle than a washing machine. 45% of the participants never use hot water to wash their clothes and 30% occasionally use hot water to wash their clothes. These are fairly high percentages and a key that perhaps this area of interest is not in as much need of attent ion as others, in terms of electricity conservation. Us ing hot water when washing clothes uses notably more energy than when washing with warm or cold water. By eliminating the unnecessary use of hot water when washing clothes, a hous ehold can save a considerable amount of energy and money each month. Perhaps this i ssue could be touched on in demand-side management programs but by no means should it be a focus point.

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42 As not as many households have a clothe s dryer when compared to a washing machine, 85% have a dryer compared to 95% that have a washing machine, it is notable to mention that on average, a clothes dryer us es considerably more energy than a washing machine per load of laundry. Dryers cons ume large amounts of energy and can be a culprit in high energy bills for households that do many loads of laundry. This is interesting as the highest per centage of the participants re ported that their dryer was between five and ten years old, followed by the second highest group which stated that their dryer was between ten and twenty years old. It seems that people keep their dryers for a much longer time than they do their washers. Electric clothes dryers were found in the ma jority of homes that did have a dryer. With the recent rise in gas prices, electric dryers have become the more cost effective choice for households in Gainesville, Florida. However, the cost of gas and electricity varies widely from state to state and throughout the year so the most cost effective option when choosing a dryer depends on the costs in that area. Regardless of the energy source of the dryer, the important fact or when it comes to clothes dr yers is the frequency of their use. Due to their high energy consumption, they should be used minimally. Figure 4-13 displays that 65% of responde nts stated that they never hang their clothes to dry. The large percen tage of this sample population relies solely on the dryer to dry their laundry. If this participant gr oup laundered an average number of loads of clothes per week, three for example, th en the respective energy costs would be significantly greater in this household when compared to a household that always hangs the clothes to dry. The process of dr ying clothes needs great emphasis when implementing demand-side management programs. It seems, on average, that households

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43 have older dryers than washing machines. Dryers consume more energy per load of laundry than washing machines and should ha ve at least the same energy rating and efficiency level of the washing machines found in the same household. The issue at hand should be emphasized in educational programs or possibly grants related to demand-side management programs that could offer assi stance in upgrading to newer and more energy-efficient clothes dryers. Appliances 58% of participants had an electric st ove in their home. A lesser percentage reported having a gas-powered stove. As in most appliances, the newer the appliance, the more energy efficient it is. The amount of energy consumed when cooking directly relates to the frequency and duration of usage. Figure 4-14 shows the number of weekly meals prepared at home in the households th at were surveyed. The more meals cooked per week, the more energy consumed in the cooking process. In the homes that were surveyed, the stove did not pose a serious issue in energy consumption unless it was being used every day for hours at a time. As this was only the case in one household in which an occupant made baked goods every day, it does not seem to be a critical issue at this time. Throughout the survey process, it was found th at the majority of households rarely cooked at home. Many dined out for every meal, except breakfast in some cases. The habits seemed unusual as low income households were being surveyed and in general, it is cheaper to cook at home than to dine out. Regardless, the majority of households prepared a meal on the stove or in th e oven about once a day or less. The high number of households that dine out often made it apparent that these particular households would cau se the use of microwaves to be high as well. The findings

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44 in Figure 4-15 could be due to the fact that leftovers are taken home from dining out and must be reheated. Also, some households c ook only a few times a week but cook enough to last a few days, in which case each subs equent meal would need reheating in the microwave. The 21% of partic ipants that reported using the devices several times a day consisted of primarily these households. Many participants reported that they used a toaster every morning for toast which may have added significantly to the 53% who stated using a microwave, toaster, or toaster oven once or twice a day. Lighting According to Figure 4-16, the highest res ponse rate of particip ants suggests that over 25% use their indoor lights between f our and six hours each day. The percentage seems average and not excessive in any wa y. However, over 10% of respondents stated using indoor lights for more than twelve hours each day. This percentage seems excessive as natural daylight can light the home for about twelve hours each day during most parts of the year. Demand-side management progr ams must target these groups that use excessive indoor lighting daily. Quite a few of the participants stated th at when the indoor lights were on, only one room was lit at a time. The research summari zed in Figure 4-17 suggest s that this 39% of the total respondents was pr udent about turning off lights when the rooms were unoccupied. A few households even stated that this behavior was stressed daily to the children in hopes of developing less energy c onsumptive habits. Over two thirds of the entire sample population stated having less than three rooms lit at once. However, when a household consistently has more than th ree rooms lit at one time, energy will be consumed unnecessarily, causing the energy bill to be higher than needed. This is an

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45 exemplary issue when it comes to ways in which behavior can significantly affect household energy consumption. The fact that most of the participants had solely sta ndard incandescent bulbs in their homes was not surprising. As demonstrated in Figure 418, less than ten homes had 25% of their light coming from compact fl uorescent bulbs (CFL) and even fewer had a greater percentage of these energy-saving li ght bulbs. Compact fluorescent bulbs last about ten times longer than standard incandesc ent bulbs while only using a fraction of the energy. In addition to using less than a third of the amount of energy needed for standard incandescent bulbs, CFL’s put out the same wattage and br ightness but do it without emitting heat. CFL’s are slightly more expens ive, but the energy savings and long life of the bulb allow it to quickly recover its co st. Compact fluorescent bulbs are the obvious choice but it seemed that many participants were unaware of the immense savings they produce. In our surveys, each participant wa s given three compact fluorescent bulbs free of charge. Perhaps future demand-side mana gement programs could continue this trend and offer households a few compact fluorescent bulbs at no charge, and aid in lowering the overall household energy consumption. This would allow them to observe the savings due to the use of CFL’s and encourage them to buy additional CFL’s for their home. As 86% of respondents had exterior flood lights around th eir home, it is important to determine how those lights are used. Fi gure 4-19 shows that the majority of the participants used their exteri or lights for less than two hour s each night. Almost 30% of the respondents used motion sensors to cont rol their exterior lights, a more energy efficient alternative to indoor switches. The problem with indoor switches lies in the occupant’s behavior. Many times, an i ndoor switch may be unknowingly left on

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46 overnight, unnecessarily c onsuming energy for a long pe riod of time. As a large percentage of exterior lights are c ontrolled by an indoor switch, demand-side management programs must emphasize conservati ve behavior in regards to energy used throughout the night. Perhaps motion sensors co uld be incorporated into demand-side management programs in terms of educational information and possibly product offers or rebates. The findings suggest that ex terior lighting is not an issue that is dominant throughout the population. Almost 60% of respo ndents have their exterior lights on for less than two hours each night. The majority of this percentage included occupants that only had their exterior lights on for a few mi nutes each night, only when someone had to go outside. A small percentage of participants reported keep ing the exterior lights on for the entire night and viewed this as a safety measure. For the most part, when households did choose to keep their exteri or lights on for long periods of time, only one small light was used. The issue at hand does not stand as something that should be given much attention in demand-side management program s. Although lighting, esp ecially when used for long periods of time, can consume a si gnificant amount of energy, safety is an underlying factor that ra tionalizes and overrides the energy issue here. Entertainment The question regarding the number of tele visions within the household had the most evenly distributed results in the su rvey. According to Figure 4-20, the highest response rate came from particip ants that had three televisions in their home. The number of participants that had one, two, or four televisions in their home was about the same. Televisions, depending on their age, type, a nd size, can significantly contribute to a household’s energy usage and should be used, as most devices, in moderation. The newer

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47 and larger televisions are tec hnically energy efficient, but use a much greater amount of energy when in use and when in standby mode. All televisions consume energy in standby mode so measures should be taken to li mit the number of televisions that are in use. If a television is not used regularly, it s hould not be plugged into the electri cal outlet. Figure 4-21 displays the daily television usage of the participants. The fact that such a large percentage of respondents watched at least one television for over eight hours each day was astonishing. Some occupant s even admitted that every television in the home was on from the time they awoke until the time they went to sleep. This occurred most frequently in homes that had retired persons who lived alone. The television seemed to be the only source of entertainment for them. Perhaps programs to promote community and create an area for gath ering or social events would allow these retirees a varying form of entertainment and perhaps lower thei r energy consumption by reducing the amount of time the television was on. This would also save energy in terms of heating or cooling. If the occupants had somewhere to go and meet, they would spend less time in their own home which would re quire less energy of th e heating or cooling system as it could be adjusted to decreas e demand while the occupant was away. The data regarding use of a video game sy stem was of no surprise after completing only a few initial surveys. As almost 75% of the households surveyed did not have any children, Figure 4-22 shows that the majority of the participants neither owned nor used a video game system. Also, the households that owned a video game system did not use it as often as might be expected. About half of the homes surveyed did not own a computer, which was initially surprising. Many homes consisted of senior citizens for which a computer was not a

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48 necessity and was actually of no interest. Al though the households were low income, the ones consisting of children usually had a co mputer. Even the households that owned a computer did not use it very often. The typi cal surroundings in a university town in which student and faculty alike rely on computers each and every day for almost everything they do, seemed a sharp contradiction to this scene. The majority of these occupants did not rely on a computer for everything they did which seemed somewhat liberating. Computers, when left on for long periods of time, can consume significant amounts of energy and can even raise the temperature of the room with the heat they expel. The effect can cause the air conditioning unit to work harder to cool the room and therefore, add to the energy costs the household faces. It was found that the low percentage of high computer users, shown in Figure 4-23, was a positive behavior and that this was not an area that needed much attention in terms of a need for conservation of energy. The findings displayed in Figure 4-24 were surprising as it was anticipated that the amount of participants that li stened to music by means of a CD player, radio, or stereo system would be higher. Almost 45% of re spondents did not listen to any music on a daily basis. In fact, very few households that were surveyed even had stereos, radios, or CD players. It seemed that the majority of the occupant’s entert ainment came from the television. Apparently this is not an area th at requires much focus for improvement in future demand-side management programs. Demographic Information Figure 4-25 displays the numb er of people in the househol ds that were surveyed. 35% of the respondents had two people in th eir household, followed by over 25% that had only one person in the household. Only 4% of the respondents had more than five people in their households. The majority of th e participants were retirees or disabled

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49 persons that either lived alone or with their significant other. As 73% of participants had no children in the household (F igure 4-30), these responses are consistent with other areas of the survey. Due to the fact that many of th e participants lived in relatively small households and were adults, th ere is no reason that behavior s should not be modified to reflect less consumptive lifestyles. Many households that were surveyed consis ted of retirees. According to Figure 426, about 30% of households with senior citizens consisted of one senior citizen. Also, 11% of the participants had two senior citizens in the household, but over 50% had no senior citizens in the home. Apart from the need for warmer temperatures for comfort, it was found that households which contained one or more senior citizens usually used less energy. The findings may be due to the fact th at senior citizens were raised in a time when resources were scarce and these habi ts of minimal use and conservation have remained with them through the years. Al so, retired persons are usually on a fixed budget and therefore, cannot afford to spe nd large amounts of m oney for their energy bills. Figure 4-27 shows that almost 75% of th e participants had no children in their household, which is consistent w ith the findings that suggest th e majority of participants were either retired or disa bled persons on a low fixed income. Children can significantly affect the energy usage of a household. In many cases, a greater amount of laundry is completed, especially with young babies, and when they are older, children can substantially increase the nu mber of hours a computer, tele vision, or video game system is in use. . As this is the case, it seems reasonable to conclude that perhaps a full and

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50 representative cross section of the low income population in Gainesville, Florida was not gathered in this study. While 90% of respondents did not regularly work from home, almost 75% stated that someone was home all day. Further emphasis may be put on the idea that many of the respondents were either re tired or disabled so they di d not work but were home most of the day. The 10% that regularly worked from home, shown in Figure 4-28, justified their possibly higher energy usage due to extended lighting or device use. As many of the occupants surveyed were di sabled persons or retirees, the findings in Figure 4-29 seemed appropriate. 73% of the participants stated that someone in the household is home all day on a typical day. The large population that stays home most of the day seemed to have a high correlation to the population that watched at least one television for eight hours or more per day. Ma ny occupants live alone and the television provides their only form of entertainment a ll day long. Perhaps demand-side management programs could think outside of the box and offer community activities or programs to give the high retiree and di sabled population something to do during the day instead of sitting at home, watching the tele vision all day, and consuming energy. According to Figure 4-30, the majority of re spondents stated an income of less than $20,000 in 2005. It must be noted that income levels may not be accurately representative of the survey population as these income levels were collected solely from the occupant and not cross-referenced with filed tax reports. Responses to the income level of the households in this analysis may be different fr om the income levels reported in the initial survey questionnaire to determine income elig ibility. According to Wikipedia, an online encyclopedia, the median income for a household in Gainesville, Florida is $28,168 and

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51 the per capita income for the city is $ 16,779. Over one quarter (26.7%) of the population is below the poverty line which produces a great need for lowered energy bills within the community. The population in Gainesville, espe cially the high low-income percentage, could benefit significantly from demand-side management programs that would assist in lowering energy bills as well as helping the loca l utility company offset their costs and in turn, require less tax money from the city. Figure 4-31 displays that concerns about the heating, ventilation, and the air conditioning system in a home had the highest frequency of being identified by participants as having the largest impact on the energy use of a household. Although many respondents had various id eas about which issues had th e largest impact, the most significant result for this question is the 19% of respondents that did not respond because they did not know what could cause a large impact on the energy use of the home. This data is precisely why community education is such a pressing matter and must be implemented into demand-side management programs. If occupants do not know which habits and behaviors can greatly affect the energy intensity of their home, they will not know how to modify their behavior to fo llow a less energy consumptive lifestyle. Figure 4-32 shows the level of concern of participants regarding energy costs in their home. While 68% of the participants we re very concerned about the energy costs in their home, only 6% were not concerned. The remaining 26% were only somewhat concerned about their energy costs. The la tter group consisted of both high and low energy users that seemed to care about the costs of energy, but di d not care enough to make an effort to make the home more en ergy efficient. The group, as well as the participants that were very concerned a bout energy costs, should be targeted when

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52 creating demand-side management programs. When someone does not feel strongly about an issue, such as energy savings, a program should aim to promote the issue in simple manner and encourage a positive change that is easily attained. For example, if a more efficient appliance is needed in th e home, a household may be much more willing to make the purchase if there was a reba te program or other incentive. While 68% of the respondents stated that th ey were very concerned with the energy costs in their home (Figure 4-32), only about 50% of res pondents had actually made a change to make their home more energy efficient, according to Figure 4-33. The remaining percentage of the participants consis ted of respondents that made no changes to their home or their lifestyle and therefor e, garnered no savings from reduced energy consumption. Perhaps in future studies or surv eys, questions can be created to discover the possible reasons for a strong concern within a household but little effort being made to better the energy consumi ng realities of that home. Perhaps, in some cases, only motivation is required which can easily be created through appr opriate demand-side management programs. Figure 4-34 displays that almost 90% of respondents were unaware of any programs that were available to aid in lowering home energy bills. The staggering percentage emphasized the fact that de mand-side management programs must be marketed more effectively. Whether it is th rough higher frequency of programs, greater advertising, or more accessible information, a communication plan must be applied to these programs. These DSM programs are deve loped to aid both the utility and the energy consumer but too few of the respondents were aware of any available programs to make an impact on the community. The important knowledge must be passed

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53 successfully throughout the communities for the beneficial effects to be widespread and the programs to be worthwhile. Summary Based on the results of this survey, ther e are a few key issues that should be focused on when creating and implementing demand-side management programs. The key issues displayed a potential for great ener gy savings if measures are taken to reduce the consumption on a regular basis. The ma in areas to focus on included the use of lighting in the home, the use of televisions, a nd the temperature settin gs of thermostats, when home and away, for heating and cooling. Another important factor that remains an energy issue is the frequency of changing the filter for the cooling system. All of these issues are completely behavior related and can easily be modified to reflect less energyconsumptive lifestyles. Appendix D shows the results of a Residential Energy Consumption Survey completed in 2001 by th e Energy Information Administration of the United States of America. If these areas of interest are at the center of demand-side management programs, the utility and the co mmunity have much to gain in terms of savings, when the programs are impl emented widely and successfully. Appendix E shows the results of a full y ear of in-home energy audits completed during 2005 and 2006, by Amy Carpus, a Conserva tion Analyst at Gainesville Regional Utilities. The results further emphasize the importance of occupant behavior in household energy usage. When looking at the combined total of all apartments, owned homes, and rented homes, two of the top five highest occurring factors were strictly behavior dependent. These two factors were the occurr ence of a dirty filter, signaling that it was not changed at the appropriate interval, and a thermostat set ting that was more than five degrees away from the recommended temper ature setting. These same issues proved

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54 important issues in my research as well and should be at the core of demand-side management programs. Getting the messa ge out about savings and motivating households to simply modify their behavior towards more energy-conserving habits can make a significant change in household en ergy intensity. The following chapters will discuss the summary and conclusions of th is study, as well as recommendations for further research. Figures Electric Resistance 33% Natural Gas Furnace 27% LP gas Furnace 2% Heat Pump 26% Kerosene Space Heater 5% None 0% Other 4% Portable Electric Heater 2% Wood Stove/ Fireplace 1% Natural gas logs 0% Figure 4-1: Primary Heat Sources

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55 0% 1% 11% 6% 14% 12% 8% 20% 27% 64% 56% 48% 40% 32% 24% 16% 8% 0% 0% 10% 20% 30% 40% 50% 60% 70% >8282=8080=7878=7676=7474=7272=7070=68<=68 Figure 4-2: The Increase in Co st of Energy compared to Heating Temperature Settings of Participants Yes 44% No 44% No Answer 12% Figure 4-3: Participants that Ch ange Heating Setting While Asleep

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56 Electric Central AC 72% Natural Gas AC 3% Whole house fan 0% Window/ wall/ room AC 18% Other 0% None 1% Floor/ box fans 0% Ceiling fans 6% Figure 4-4: Primar y Cooling Sources 48% 5% 22% 4% 8% 11% 2% 0% 8% 16% 24% 32% 40% 48% 0% 10% 20% 30% 40% 50% 60% >=7878=7676=7474=7272=7070=68<68 % of Respondents % Rise in Energy Bill Figure 4-5: The Increase in Co st of Energy compared to Coo ling Temperature Settings of Participants

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57 Yes 37% No 50% No Response 13% Figure 4-6: Participants that Cha nge Cooling Setting While Asleep Once a month 37% Once every 23 months 32% Once every 46 months 16% Once a year 3% Dont know 12% Figure 4-7: Frequency of Ai r Conditioner Filter Change

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58 0 5 10 15 20 25 30 35# of Households 0123456789101112N/R # of Months Figure 4-8: Number of Months per year a Household Opens Windows Gas 55% Electric 42% LP Gas 1% Other 2% No Response 0% Figure 4-9: Types of Water Heaters in the Household

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59 0 5 10 15 20 25 30 35Number of Responses 7 or less8 to 1415 to 2122 to 2829 to 3536 to 4243+ Number of Showers Figure 4-10: Showers per Week in the Household 0 5 10 15 20 25 30 35 40 45 N o R e s p o n s e 1 t o 5 6 t o 1 0 1 1 t o 1 5 1 6 t o 2 0 2 1 t o 2 5 2 6 t o 3 0 > 3 0 Figure 4-11: Average Minutes per Shower

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60 0 5 10 15 20 25 30 35 40 No Response 0 to 23 to 56 to 89 to 11>11 Figure 4-12: Number of Loads Washed Per Week Always 15% Frequently 6% Occasionally 13% Never 65% NR 1% Figure 4-13: Frequency of Drying Clothes by Hanging

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61 0 5 10 15 20 25 30 35 40Number of Responses 5 or less6 to 1011 to 1516+NR Number of Meals Figure 4-14: Weekly Meals Prepared at Home Never 3% Once a week 7% Every other day 16% Once or twice a day 53% Several times a day 21% Figure 4-15: Frequency of Microwav e / Toaster Oven / Toaster Use

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62 0 5 10 15 20 25 30Number of Responses < 2 h r s 2 t o 4 h r s 4 t o 6 h r s 6 t o 8 h r s 8 t o 1 0 h r s 1 0 t o 1 2 h r s 1 2 + h r s Figure 4-16: Amount of Indoor Lighting Used Per Day One 39% Two 33% Three 21% Four 3% Five 4% Figure 4-17: Rooms Lit When Lights are in Use

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63 0 5 10 15 20 25 30 35 40 45 50Number of Responses 2 5 % 5 0 % 7 5 % 1 0 0 % 2 5 % 5 0 % 7 5 % 1 0 0 % 2 5 % 5 0 % 7 5 % 1 0 0 % 2 5 % 5 0 % 7 5 % 1 0 0 % Std Incan. Flourescent CFL Other Figure 4-18: Type of Lightbulbs in Household 0 10 20 30 40 50 60Number of Responses < 2hrs2 to 4hrs 4 to 6hrs 6 to 8hrs 8 to 10hrs 10 to 12hrs 12+ hrsNR Figure 4-19: Hours of Exte rior Lighting per Night

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64 One 18% Two 19% Three 33% Four 19% Five or more 10% None 1% Figure 4-20: Number of Te levisions in Household 0 5 10 15 20 25 30 35 40 45Number of Responses None< 2hrs2 to 4hrs4 to 6hrs6 to 8hrs8+ hrs Figure 4-21: Daily Television Usage

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65 0 10 20 30 40 50 60 70 80Number of Responses None< 2hrs2 to 4hrs4 to 6hrs6 to 8hrs8+ hrs Figure 4-22: Daily Video Game System Usage 0 5 10 15 20 25 30 35 40Number of Responses None< 2hrs2 to 4hrs4 to 6hrs6 to 8hrs8+ hrs Figure 4-23: Daily Computer Usage

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66 0 5 10 15 20 25 30 35 40 45Number of Responses None< 2hrs2 to 4hrs4 to 6hrs6 to 8hrs8+ hrs Figure 4-24: Daily CD Player / Stereo / Radio Usage 0 5 10 15 20 25 30 35 40 No Response 12345>5 Number of People Figure 4-25: Number of People in Household

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67 One 34% Two 11% None 54% Four 1% Three 0% Five+ 0% Figure 4-26: Number of Seni or Citizens in Household One 12% Two 5% Three 7% Four 3% Five+ 0% None 73% Figure 4-27: Number of Children in Household

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68 Yes 10% No 90% Figure 4-28: Percentage of Households in Which a Member Works From Home Yes 73% No 27% Figure 4-29: Percentage of Households in Which Someone is Home All Day

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69 0 5 10 15 20 25 30 35 40 45Number of Responses < $ 2 0 , 0 0 0 $ 2 0 , 0 0 1 t o $ 2 5 , 0 0 0 $ 2 5 , 0 0 1 t o $ 3 0 , 0 0 0 $ 3 0 , 0 0 1 t o $ 3 5 , 0 0 0 $ 3 5 , 0 0 1 t o $ 4 0 , 0 0 0 $ 4 0 , 0 0 1 t o $ 4 5 , 0 0 0 $ 45 , 0 0 1 t o $ 5 0 , 0 0 0 $ 5 0 , 0 0 1 t o $ 5 5 , 0 0 0 O v e r $ 5 5 , 0 0 0 Figure 4-30: Household’s Total 2005 Income Before Taxes 0 5 10 15 20 25 30 35 40 45 N R C o n s t r u c t i o n H V A C W a t e r H e a t e r K i t c h e n A p p l i a n c e s L i g h t s T V C o o k i n g D r y e r R i s i n g C o s t s Figure 4-31: Largest Impact on Energy Use of Household

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70 Very Concerned 68% Somewhat Concerned 26% Not Concerned 6% Figure 4-32: Level of Concern of Participants Related to Energy Costs in Their Home Yes 51% No 49% Figure 4-33: Percentage of Hous eholds That Have Made Cha nges In Past Year to Make Home More Energy Efficient

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71 Yes 11% No 89% Figure 4-34: Percentage of Pa rticipants Aware of Programs To Help Lower Home Energy Bills

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72 CHAPTER 5 SUMMARY AND RECOMMENDATIONS Summary This chapter highlights the findings of th is research and presents the general conclusions regarding the role of occupant behavior in lo w-income households with high energy intensity. The literature review co rresponding to demand-side management programs has been discussed, as well as the en tire methodology of the study leading up to the results. The data analysis chapter discusse d in detail the specifi c survey questions and the findings of the research study. The limitati ons of the study and the need for further research will also be discussed. Conclusions The goal of this research was to determin e how significant a role occupant behavior played in the energy consumption of a hom e. Although this research is strictly exploratory, the data collected suggests that the occupant’s behavior is critical in the amount of energy a household consumes. The ener gy intensity of a home has a direct and strong correlation to the habits and practices of its inhabitants. The results of this research have determin ed several key issues in the energy usage of a household that are highly behavior depe ndent. Many of the most important issues deal with energy usage habits related to they home’s heating, ventilation, and air conditioning system. The temperature setting on the thermostat is wholly controlled by the occupants and for the most part, was not set at the recommended temperature setting in the homes that were surveyed. This is an issue in both heating and cooling situations.

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73 In heating, it was found that about 12% of th e sampled population kept their thermostat six degrees higher than the recommended se tting of 68 degrees Fahrenheit, causing a 24% increase in their energy bills. For cool ing, it was found that 22% of the sample population kept their cooling temperature four degrees below the re commended setting of 78 degrees Fahrenheit, causing a 16% increa se in their energy bill. In addition to temperature setting, the frequency of changing th e system filter can also greatly affect the amount of energy consumed by heating and cool ing systems. Only about one third of the participants changed their filter at the recomm ended interval of once a month. If the filter is not changed at this rate, it may become too dirty to properly filter air and in some cases, act as a barrier for the air supply, wh ich causes the air conditioning unit to work much harder than necessary and consume more energy. Other behavioral factors th at can consume high amounts of energy in a household included the use of televisions, lighting, and a clothes dryer. For televisions, the highest response rate came from particip ants that had three televisions in their home. Televisions, depending on their age, type, and size, can significantly contribut e to a household’s energy usage. All televisions consume ener gy while in use and also when in standby mode. For this reason, only televisions that are used regularly should be plugged into an electrical outlet. Indoor lighti ng also has the potential to be one of the largest energy consumers in the household. Over 10% of respon dents stated that their indoor lights were on for more than twelve hours each day. When i ndoor lighting is in use, over two thirds of the entire sample population stated having less than three rooms lit at once. However, when a household consistently has more than three rooms lit at one time, energy will be consumed unnecessarily, causing the energy bill to be substan tially higher than needed.

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74 Also, most of the participants had solely st andard incandescent bulbs in their homes, and less than ten homes had twenty-five per cent of their light coming from compact fluorescent bulbs (CFL). Compact fluorescent bulbs last about ten times longer than standard incandescent bulbs while only usi ng a fraction of the energy. In addition to using less than a third of the amount of en ergy needed for standard incandescent bulbs, CFL’s put out the same wattage and br ightness but do so without emitting heat. Clothes dryers were found in 85% of th e surveyed households and can greatly affect the total energy consumption of a ho me. Although the cost of different types of energy varies from area to area, 85% of par ticipants with a dryer had an electric one. Regardless of energy source, the main issue facing dryers is their frequency of use. Dryers consume more energy pe r load of laundry than washi ng machines so the higher the number of loads, the higher the energy cons umption. In lieu of using a clothes dryer, some homes did hang their clothes to dry, al though 65% of respondent s stated that they never hang their clothes to dry. These are all exemplary issues when it comes to ways in which behavior can significantly affect household energy consumption. These issues must be focused on when developing demand-side management programs for a community. There are physical aspects of the home that also come into play when measuring its energy intensity. These include the presence of weather stripping, the presence of leaks in ducts and air handlers that suppl y and distribute air, and the insulation levels within the home and around necessary pipes. The mentione d issues are essential when determining the energy intensity of a home, but considera tion must also be give n to the behavioral issues of energy consumption.

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75 The marketing of the demand-side manageme nt programs must also be done more effectively. Gainesville Regional Utilities currently has thirty-six DSM programs currently offered or in the making. Of the 100 participants in this study, 89% of them were not aware of any programs that could he lp them in lowering their energy bills. The message of the various DSM programs is not ge tting across to the co mmunity as a whole. The delivery methods of these programs must be revised and information regarding them must be more readily available to the public. Limitations of Study Although a substantial amount of data was collected for this study, there are some limitations to the information gathered during this research. The total sample size of 100 participants may be too small to get a clear and accurate cross-section of the low-income households of Gainesville, Florid a. Contributing to this issue is the fact that many of the respondents were from a specific demographic group, retired or disa bled persons, which may have skewed the results of so me of the survey questions. Need for Further Research This research does not aim to solve every issue related to the high energy usage in low-income households. In order to move clos er to the mutual goal of reducing the total amount of energy used and moving towards more conservative habits, further steps must be taken. Perhaps more energy audits must be completed to obtain a better picture of the entire community as a whole, which could mo re accurately assess the issues and needs of the area. Energy conservation techniques and practices can be more widely available through specific services or products that ta rget the reduction of energy usage. Such products and services include compact fluores cent light bulbs, energy efficient devices and appliances, and free services to ai d in obtaining information and products.

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76 As education is a key point in the su ccess of demand-side management programs and overall energy conservation, re search must be completed to determine the best means of developing and delivering that educati on to the public. Once the proper method of education is determined, the success of the programs and the spreading of useful knowledge will have no limit. Recommendations After completing this research, the re commendations are few. Education and incentive are the key factors in creating successful demand-side management programs which can help alleviate the issue of high energy intensity in low-income households. As it has been discovered that occupant beha vior plays a crucial role in the energy consumption of a household, this issue s hould be emphasized in DSM programs. As homes may have physical issues such as poor construction or a leaky duct system that may affect energy consumption, the habits of the household can be modified immediately to reflect a less consumptive lifestyle. Also, unlike physical issues that require repairs that can be costly, behavior-related factor s can be changed for the benefit of the household free of charge. These programs must have an emphasis in educating the pubic as a whole. Whether it be through bill stuffers, emails, or commun ity meetings, the information available must be effectively distributed to the households. Many times an incentive is needed to promote a change and for a DSM program to be truly successful, education must be combined with an incentive. This marketing t ool may be a number of things such as an additional credit on the energy bill if a decrease in consumption is realized over a given period of time. Other possible incentives include giveaway s, contests, or rebates on

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77 energy efficient devices. Regardless of the type of incentive, it is necessary when trying to reach a large crowd to get useful and important knowledge distributed. In addition, perhaps DSM programs coul d extend their realm of duties and incorporate these issues into efforts to change local legislation in favor or more energyefficient practices. William Shepherd at Gain esville Regional Utilities has been working on a template to present to the City of Gainesv ille in an effort to change the local building code to reflect a shift toward energy cons ervation. This outline can be found in Appendix F of this study.

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APPENDIX A GRAPHIC INFORMATION SYSTEM (GIS) MAP Figure A-1: GIS Map of Gainesville

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79 APPENDIX B INITIAL SURVEY INSTRUMENT February 6, 2006 Dear Family Bill-Payer: As fuel prices continue to rise, families througho ut Gainesville are looking for ways to reduce home energy expenses. GRU and the City of Gainesville are developing ways to help you save energy, but we need your help. We hope you will be part of a study that will help you and other customers save energy and money. Your home has been selected to represent at least 50 others in your neighborhood, so your partic ipation is important. Please fill out the short form included with this letter and mail it back to GRU in the enclosed postage-paid envelope by February 24, 2006. Y our responses will tell us if you and your home meet the needs of the study. If you qualify , we will contact you at the telephone number you provide to schedule an in-home energy assessme nt. During our visit, we will 1) perform a detailed energy survey at no charge to you, an d 2) with your help, complete an in-depth questionnaire about your energy usage and pertinent features of your home such as appliances, number of rooms, windows, a nd insulation levels. If you are selected and agree to participate, we will thank you by installing three energy saving compact fluorescent light bulbs in your home for free! These light bulbs will help reduce your home’s energy use and save you money. We hope you will take this chance to conserve energy, save on your monthly energy bill, and improve the environment. Fill out the short form and drop it in the mail today! If you have questions about the enclosed form or the energy survey itself, please contact Amy Carpus in GRU’s Conservation Services Depart ment at (352) 393-1450. Thank you for your participation! Sincerely, Pegeen Hanrahan Mayor, City of Gainesville RJL:CEP Enclosure

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80 Name 1 2 3 4 5+ Under $20,000 $20,001 to $25,000 $25,001 to $30,000 $30,001 to $35,000 $35,001 to $40,000 $40,001 to $45,000 $45,001 to $50,000 Over $50,000 Natural Gas Propane 1000 Source Code: Thank you for your participation! 4. How long have you and your family been living in this household? Less than 1 year 1-2 years 2-4 years 4-6 years More than 6 years 2. What is your combined household's annual income before taxes? (See Box 1 on your W-2 forms) 3. What type of water heater do you have? Electric Other______________________________________ Survey Questionnaire Instructions for Head of Household: Please complete the survey questions and mail back to GRU in the pre-paid envelope provided by February 24, 2006. Thank you for your participation. Phone Number (To schedule energy survey)1. How many people live in your household? Figure A-2: Preliminary Survey Questionnaire

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81 APPENDIX C DEED SURVEY INSTRUMENT DEED HOME ENERGY SURVEY Section 1: INFORMATION ABOUT YOUR HOME We would like to begin by asking some information about the home in which you now live. Q1. When did you move into this home? 1 Less than 1 year ago Date given: _____________________ 2 1 year to less than 2 years ago 3 2 years to less than 3 years ago 4 3 years to less than 5 years ago 5 5 years to less than 10 years ago 6 10 years ago or longer Q2. How many months per year do you live in this home? 1 Less than 3 months 2 3 months to just under 6 months 3 6 months to just under 9 months 4 9 months to 12 months Q3. Do you expect to move from this home in the next 12 months? 1 Yes Explanation, if offered: 2 No 3 Uncertain Q4. Do you own your home? 1 Yes, I own (or am buying) my home 2 No, I’m renting/leasing my home 3 Other: Q5. When was your home built? 1 Less than 5 years ago Year if known: _____________________ 2 5 years to just under 10 years ago 3 10 years to just under 20 years ago 4 20 years ago or more 5 Don’t know Q6. What direction do es the longest side of your home face? 1 West (or East) 2 Southeast (or Northwest) 3 Southwest (or Northeast) 4 South (or North)

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82 Q7. Which best describes the foundation of your home? 1 Slab on grade 2 Raised wood floors Insulated? ___Yes ___No ___Uncertain 3 Other: Q8. What is the major wall type of your home? 1 Concrete block 2 Brick 3 Wood frame 4 Other: Q9. What is the shap e of your home’s roof? 1 Flat 2 Shed 3 Gabled 4 Hipped 5 Other: Q10. Does your home have an attic? 1 Yes Insulated? ___Yes ___No ___Uncertain 2 No Q11. What is your home’s roofing material? 1 Asphalt shingles 2 Wooden shakes 3 Tile (clay or concrete) 4 Metal 5 Other: Q12. What is the color of your home’s roofing material? 1 White or silver 2 Light grey or tan 3 Red or orange 4 Dark brown or dark grey 5 Black 6 Other: Q13. What is the total square footage of your home, including bathrooms and hallways? (Do not include garages, outside patios or porches) 1 Less than 500 GRU Records / Appraiser Value:Merge Record # 2 500-999 3 1000-1499 4 1500-1999 5 2000-2499 6 2500-2999 7 3000-3999 8 4000 or more Specific #, if

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83 offered: ___________ ft2 9 Don’t Know Q14. Describe your home’s exterior doors. Description Total # # Weather-stripped 1 Wood 2 Metal Insulated 3 Glass 4 Other: Q15. Describe your home’s windows. Description Total # # Weatherstripped # Doublepaned Frame Material (majority) Window Covering (majority) 1 Single Hung Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: 2 Double Hung Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: 3 Casement Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: 4 Jalousie Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: 5 Awning Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: 6 Sliding Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: 7 Other: Wood / Vinyl / Metal / Other: None / Drapes / Blinds / Other: Q16. What type of floor coverings does your home have? (Circle all that apply and indicate percentage covering) Description Percent Covering 1 Hardwood 25% 50% 75% 100% 2 Carpet or Area Rugs 25% 50% 75% 100% 3 Tile (Ceramic) 25% 50% 75% 100% 4 Vinyl or Linoleum 25% 50% 75% 100% 5 Other: 25% 50% 75% 100%

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84 Q17. During a typical summer day, to what extent do trees help shade your house in the morning ? (around 8AM) 1 Almost totally shade the house 2 Partially shade the house 3 No shading of the house Q18. During a typical summer day, to what exte nt do trees help shade your house in the late afternoon ? (around 4PM) 1 Almost totally shade the house 2 Partially shade the house 3 No shading of the house Section 2: KEEPING YOUR HOME COMFORTABLE The next step is intended to gather some info rmation about how you keep your home warm in the winter and cool in the summer. Q19. What are the main types of heating systems that you use? Primary Secondary 1 Electric resistance 1 Electric resistance 2 Natural gas furnace 2 Natural gas furnace 3 Liquid propane gas furnace 3 Liquid propane gas furnace 4 Heat pump __ Central __ Non-central 4 Heat pump __ Central __ Non-central 5 Portable electric heater 5 Portable electric heater 6 Kerosene space heater 6 Kerosene space heater 7 Wood stove / fireplace 7 Wood stove / fireplace 8 Natural gas logs 8 Natural gas logs 9 None 9 None 10 Other: 10 Other: Q20. What type of thermostat controls your main heating system? 1 Standard Thermostat 2 Programmable Electronic Thermostat 3 No Thermostat Q21. At what temperature do you normally set your th ermostat for winter heating? ________F Q22. Do you change your th ermostat setting or other heatin g control when you are away? 1 Yes To what temperature is it changed? 2 No ________F Q23. Do you change your thermo stat setting or other heating control when you are sleeping? 1 Yes To what temperature is it changed? 2 No ________F Now we’re going to ask about how you keep your home cool in the summer. Q24. What are the main types of coo ling systems that you use in your home?

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85 Primary Secondary 1 Electric central air conditioner 1 Electric central air conditioner 2 Natural gas air conditioner 2 Natural gas air conditioner 3 Window / wall / room air conditioner 3 Window / wall / room air conditioner 4 Whole house fan 4 Whole house fan 5 Ceiling fans 5 Ceiling fans 6 Floor / box fans 6 Floor / box fans 7 None 7 None 8 Other: 8 Other: Q25. What type of thermostat is used to co ntrol your home’s main ai r conditioning system? 1 Standard Thermostat 2 Programmable Thermostat 3 No Thermostat Q26. At what temperatu re do you normally set your thermostat for summer cooling? ________F Q27. Do you change your thermo stat setting or other cooling co ntrol when you are away from home? 1 Yes To what temperature is it changed? 2 No ________F Q28. Do you change your th ermostat setting or other coolin g control when you are sleeping? 1 Yes To what temperature is it changed? 2 No ________F Q29. How often is the air conditioner filter changed? 1 Once a month 2 Once every 2-3 months 3 Once every 4-6 months 4 Once a year 5 Don’t know Q30. During what months of the year, if any, do you open windows on a regular basis for natural ventilation? __ January __ April __ July __ October __ February __ May __ August __ November __ March __ June __ September __ December __ Never Open Windows

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86 Section 3: APPLIANCES IN YOUR HOME The next step is intended to gather some in formation about appliances and water use in your home. Use side notes to indicate if an appliance is Energy Star rated, is particularly out of date, or there are other factors that could be affecting its efficiency. Q31. What type of hot water heater do you have? 1 Gas 2 Electric 3 LP Gas 4 Other: Q32. About how old is your main water heater? 1 Less than 2 years old 2 2 to just under 5 years old 3 5 to just under 10 years old 4 10 to just under 20 years old 5 20 years or older 6 Don’t know Specific age, if offered: ___________ years Q33. In a typical week (7 days) , about how many baths and showers are taken in your home? 1 7 or less # per day: ___________ 2 8 to 14 3 15 to 21 4 22 to 28 5 29 to 35 6 36 to 42 7 43 or more Q34. About how long is a typical shower? ___________ minutes Q35. Do you have a washing mach ine (or machines) in your home? 1 Yes 2 No SKIP to Q39 Q36. About how old is your main washer? 1 Less than 2 years old 2 2 to just under 5 years old 3 5 to just under 10 years old 4 10 to just under 20 years old 5 20 years or older 6 Don’t know Specific age, if offered: ___________ years Q37. How many loads of clothes do you wash in a typical week (7 days) ? ______________

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87 Q38. How often do you use hot water to wash your clothes? 1 Always 2 Frequently 3 Occasionally 4 Never Q39. Do you have a clothes dryer (or dryers) in your home? 1 Yes 2 No SKIP to Q42 Q40. About how old is your main dryer? 1 Less than 2 years old 2 2 to just under 5 years old 3 5 to just under 10 years old 4 10 to just under 20 years old 5 20 years or older 6 Don’t know Q41. What type of energy does your dryer use? 1 Gas 2 Electric Q42. How often do you hang your clothes to dry? 1 Always 2 Frequently 3 Occasionally 4 Never Q43. What type of energy does your stove/oven use? 1 Gas 2 Electric 3 Other: Q44. In a typical week, how ma ny meals are prepared at home? (breakfast, lunch, and dinner each count as one meal) 1 5 or less 2 6 to 10 3 11 to 15 4 16 or more Q45. How frequently do you use a microwave, toaster oven, or toaster? 1 Never 2 Once a week or less 3 About every other day 4 Once or twice a day 5 Several times a day

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88 Section 4: LIGHTING IN YOUR HOME Q46. During a typical day, how many hour s do you use indoor lights in your home? (consider both morning and night hours) 1 less than two hours 2 2 to just under 4 hours 3 4 to just under 6 hours 4 6 to just under 8 hours 5 8 to just under 10 hours 6 10 to just under 12 hours 7 12 hours or more Specific #, if offered: ___________ hours Q47. When using your indoor lights, how many rooms usually have lights on? 1 One 2 Two 3 Three 4 Four 5 Five or More Q48. What type of light bulbs do you us e in your home? (include rough percentage) Type Percent of Total 1 Standard Incandescent 25% 50% 75% 100% 2 Fluorescent 25% 50% 75% 100% 3 Compact Fluorescent 25% 50% 75% 100% 4 Other: 25% 50% 75% 100%

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89 Q49. Do you have exterior flood lights around your home? 1 Yes 2 No Q50. How are your exterior lights controlled? 1 Indoor switch 2 Timer 3 Motion Sensor 4 Other: Q51. How many hours per night are exterior lights typically on? 1 Less than 2 hours 2 2 to just under 4 hours 3 4 to just under 6 hours 4 6 to just under 8 hours 5 8 to just under 10 hours 6 10 to just under 12 hours 7 12 hours or more Specific #, if offered: ___________ hours Section 5: HOME ENTERTAINMENT Now, think about some of the other energy users in your home, such as electronic equipment. Q52. How many TVs are in your home? 1 One 2 Two 3 Three 4 Four 5 5 or more Of all TVs, how ma ny are large screens? ________ 6 None

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90 Q53. About how many hours will at le ast one TV be on in a typical day? 1 None 2 Less than 2 hours 3 2 to just under 4 hours 4 4 to just under 6 hours 5 6 to just under 8 hours 6 8 hours or more Specific #, if offered: ___________ hours Q54. About how many hours per day is a video game system typically in use? 1 None 2 Less than 2 hours 3 2 to just under 4 hours 4 4 to just under 6 hours 5 6 to just under 8 hours 6 8 hours or more Specific #, if offered: ___________ hours Q55. About how many hours per day is a computer ty pically in use? 1 None 2 Less than 2 hours 3 2 to just under 4 hours 4 4 to just under 6 hours 5 6 to just under 8 hours 6 8 hours or more Specific #, if offered: ___________ hours

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91 Q56. How many hours per day is a CD playe r, radio, or other type of stereo system typically in use? 1 None 2 Less than 2 hours 3 2 to just under 4 hours 4 4 to just under 6 hours 5 6 to just under 8 hours 6 8 hours or more Specific #, if offered: ___________ hours Section 6: HOUSEHOLD DEMOGRAPHICS Finally, we would like to ask a few questions about you and your family. Please remember that your information will be grouped together with other families’ responses and will not be linked directly to your household. We will u se the results of this survey to help you and your neighbors lessen the burden of monthly energy bills, so your continued input is important. Q57. Including yourself, how many people live in your home (i.e., sleep here at least five nights a week)? ___________ Q58. How many senior citizens (65 years or older) are in your household? 1 One 2 Two 3 Three 4 Four 5 Five or more 6 None Q59. How many children (17 years or younger) are in your household? 1 One 2 Two 3 Three 4 Four 5 Five or more 6 None Q60. Do any members of your hous ehold regularly work from home? 1 Yes Occupation, if offered: 2 No Q61. During a typical work w eek, is someone at home all day? 1 Yes 2 No Q62. What was your household’s total 2005 income before taxes? (See Box 1 on your W-2 forms)

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92 1 $20,000 or less 2 $20,001 to $25,000 3 $25,001 to $30,000 4 $30,001 to $35,000 5 $35,001 to $40,000 6 $40,001 to $45,000 7 $45,001 to $50,000 8 $50,001 to $55,000 9 Over $55,000 Specific #, if offered: $____________ Q63. What things do you feel have the largest impact on your household’s energy use? Q64. How concerned are you ab out energy costs in your home? 1 Very concerned 2 Somewhat concerned 3 Not concerned Q65. In the past year, have you or anyone else in your household made any changes – in either your home or your lifestyle – to make your home more energy efficient? 1 Yes Explain: 2 No Q66. Are you aware of any programs that are available to help you lower your home energy bills? 1 Yes Explain: 2 No Those are all of our questions, but before we wrap up, we would be happy to answer any questions you may have for us. [REMEM BER TO GIVE RESPONDENT 3 CFLs once they’ve completed the survey] Thank you for your time and patience.

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93 APPENDIX D ENERGY INFORMATION ADMINISTRATION RESULTS

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94 Table A-1: 2001 Total Household Energy Expenditures

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95 APPENDIX E GRU SURVEY SUMMARY 2005-2006 Table A-2: GRU 2005-2006 Survey Summary Owned % Rental % Apartment % Total Refrigerant line 214 19 23 32 82 40 319 CC Damaged 104 9 11 15 46 23 161 CC Dirty 143 13 15 21 43 21 201 CC air flow restricted 144 13 13 18 27 13 184 Filter Dirty 249 22 32 44 95 47 376 Filter Missing 25 2 4 6 12 6 41 Air by-passing filter 45 4 2 3 10 5 57 AHC Dirty 76 7 15 21 84 41 175 AHC poss dirty 37 3 10 14 27 13 74 Temp Drop 37 3 1 1 16 8 54 Duct Leaks 329 29 22 31 28 14 379 Ducts need insulation 12 1 2 3 1 0 15 AH Leaks 343 30 17 24 56 27 416 Rust in furnace 40 4 2 3 6 3 48 Yellow Flame 10 1 5 7 0 0 15 Home needs Insulation 208 18 26 36 9 4 243 Insulate attic access 137 12 15 21 9 4 161 Thermostat setting 313 28 20 28 75 37 408 Doors for circulation 40 4 3 4 14 7 57 Use of fans 124 11 8 11 21 10 153 Shade/Cover windows 106 9 0 0 10 5 116 Weatherstrip & caulk 215 19 20 28 63 31 298 Hot Water from WH 157 14 9 13 51 25 217 Feel test indicates leak 13 1 2 3 9 4 24 WH pipes need insulation 496 44 36 50 67 33 599 WH pipes corroded/rust/leak 224 20 13 18 43 21 280 Insulate WH tank 26 2 7 10 7 3 40 Waterwaster showerhead 62 5 6 8 16 8 84 Irrigation 100 9 1 1 1 0 102 Pool pump 107 9 0 0 0 0 107 Refrigerator seals/coils 37 3 5 7 15 7 57 Close fireplace damper 68 6 0 0 2 1 70 Lighting 0 0 0 0 0 0 0 Pond 0 0 0 0 5 2 5 Spa 0 0 0 0 31 15 31 Whole house fan 0 0 1 1 5 2 6 Radon fan system 0 0 0 0 2 1 2

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96 APPENDIX F PRELIMINARY RECOMMENDATIONS Preliminary recommendations for minimum en ergy standards appear below. Some parts of the building envelope (e .g., wall insulation, eave overha ngs, etc.) are difficult or impossible to retrofit, so these should not be regulated by this code. The standards should include recognition that certain requirement s may not be achievable due to physical constraints; such as where ” ceiling boa rd can not support the weight of additional insulation or old knob-and-tube wiring in the attic prohibits the inst allation of insulation. Some form of disclosure shoul d be provided to the renter wh en the standards are waived due to these constraints. Ceiling Insulation R-19 minimum insulation leve l is required. Blown-in cellulose recommended due to its inherent ability to reduce air infiltrati on. Cautions: 1. Ability of ceiling to handle additional weight; 2. Additional insulation should not be installed when knob-and-tube electrical wiring is present; 3. Additional insulation must not bl ock eave ventilation (baffles should be used duri ng installation or the eave vent s should be blown clear from underneath after installation). Air Distribution System Integrity The duct system should be substantially leak free; with leakage lim ited to 15% of total airflow as determined by a pressurization test (e.g., blower door, duct blaster, air analysis system, etc.) Should we allow a grace period fo r this to occur such as 24 months? The pressurization of the building should be neut ral or slightly positive, especially when combustion appliances use air from insi de the structure for combustion. This recommendation needs more deta il for effective application. Central Cooling System Efficiency Central cooling systems must have a Seasona l Energy Efficiency Ratio (SEER) equal to or greater than 10. This recommendation applies to split system AC units of less than five (5) tons in capacity. An exemption should be given to AC units less than Ten (10) years of age, since the embodied energy in the AC system has not been effectively distributed over the unit’s life. Room Cooling System Efficiency Room air conditioners must have an Energy Efficiency Ratio (EER) equal to or greater than 10.7 .

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97 Central Heating System Efficiency Heat pumps must have a Heating Season Perf ormance Factor (HSPF) equal to or greater than 6.8 (see age exemption above). Combus tion furnaces must have an Annual Fuel Utilization Efficiency (AFUE) equal to or greater than 0.78 (see age exemption above). Central electric resistance heat ing systems should not be allowed. Programmable Thermostat A programmable thermostat should be installe d with clear directions on how to use given to the tenant or displayed next to the un it. At time of installation it should be programmed to set back temperature at the current unoccupied times of the household. Water Heater Efficiency Electric water heaters must have an Energy F actor (EF) equal to or greater than 0.88 (see age exemption above). Combustion water heater s must have an EF equal to or greater than 0.6 (see age exemption above). Electric wate r heaters must be set to a temperature of no greater than 120* F. Showerheads Showerheads should be limited to a flow rate of 2 gpm or less. Faucet Aerators Faucet aerators must be limited to a flow rate of 1 gpm or less. Outdoor Security Lighting Outdoor security lighting must be controlled by photo cells. In ground Irrigation Systems In ground irrigation systems must be controlled by a timer set to run no more than 2 times per week under normal circumstances and only between the hours of 4 p.m. and 10 a.m. An operable rain sensor must also be in installed. Pool Pumps Pool pumps must be controlled by a timer se t to run no more than xx hours per day under normal circumstances. Compact Fluorescent Lamps CFL’s must be installed in all interior light ing fixtures (designed for use of an A-Lamp) of the house unless those fixtures ar e connected to dimming switches.

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98 Energy Efficiency Renter’s Guide Each tenant to be given a current copy of GRU’s Energy Efficiency Renter’s Guide. Weather Stripping All exterior doors must have weather stripping and all windows or ot her penetrations to the structure must caulked or otherwise sealed.

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99 LIST OF REFERENCES Donald, Channele. (1997). U.S. Electric Utility Demand-Si de Management: Trends and Analysis. http://www.eia.doe.gov/cneaf/pubs_ht ml/feat_dsm/contents.html Shepherd, William. (2006). Preliminary Recommendations for Minimum Energy Standards . Draft to be presented to City of Gainesville. Sonnenblick, Richard (1994). Is Demand-Side Management Economically Justified? CBS Newsletter. Page 7. Peach, J. Dexter. (1991). Electricity Supply microform: Utility demand-side management can reduce electricity use: Report to the Chairman, Environment, Energy, and Natural Resources Subcommittee, Committ ee on Governmental Operations, House of Representatives. General Accounting Office. US Department of Energy.(2001) Table CE1-5.1u. Total Energy Consumption and Expenditures by Household Member and Demographics. Energy Information Administration.

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100 BIOGRAPHICAL SKETCH Frances Claire Locke was born in 1982 in Osorno, Chile. She liv ed on a rural farm until the age of 3 when she moved to the United States of America with her parents, Mary and Gregory Locke. She was raised in Sout h Florida for the remainder of her youth but returned to Chile regularly to visit family. Frances graduated from Spanish River Hi gh School in Boca Raton, Florida in 2001. She participated in swimming and soccer throughout her high school career and successfully completed five Advanced Placement classes for college credit. Frances continued her education at the University of Florida in Gainesville, Florida. She completed her Bachelor’s degr ee in Classical Studies in May of 2005, after completing a semester abroad in Florence, Italy. Frances continued her higher education in pursuit of her Masters of Science in Building Construction degree from the M. E. Rinker School of Building Construction at the University of Florida. She expects to graduate in the fall semester of 2006.