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Combining Gainesville Regional Utilities Solar Feed-In Tariff with Low Income Housing Tax Credits

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Title:
Combining Gainesville Regional Utilities Solar Feed-In Tariff with Low Income Housing Tax Credits Seeking Value for Both Tenants and Project Owners
Physical Description:
1 online resource (101 p.)
Language:
english
Creator:
Cardenas, Adriel J
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.B.C.)
Degree Grantor:
University of Florida
Degree Disciplines:
Building Construction
Committee Chair:
Kibert, Charles Joseph
Committee Members:
Archer, Wayne R
Srinivasan, Ravi Shankar
Smith, Marc T

Subjects

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

Notes

Abstract:
Current research indicates low-income tenants, as compared to median-income tenants, allocate a disproportionately high percent of their income toward utility expenditures. Research also indicates that in recent years low income tenants are struggling to keep up with increasing energy costs. In 2009, Gainesville Regional Utilities launched the first ever Solar Feed-In Tariff in the US. Although the express purpose of the program was not to serve as a housing policy tool, the possibility exists the program could serve a dual purpose. This paper examines the effect on a project owner’s bottom line when combining Gainesville Regional Utilities Solar Feed-In Tariff with Low Income Housing Tax Credits. More specifically, whether or not a project owner aided with the aforementioned subsidies can generate excess cash flow after meeting all project operating expenses and debt service, in addition to paying all tenant electricity expenses.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Adriel J Cardenas.
Thesis:
Thesis (M.S.B.C.)--University of Florida, 2013.
Local:
Adviser: Kibert, Charles Joseph.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-08-31

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046052:00001

MISSING IMAGE

Material Information

Title:
Combining Gainesville Regional Utilities Solar Feed-In Tariff with Low Income Housing Tax Credits Seeking Value for Both Tenants and Project Owners
Physical Description:
1 online resource (101 p.)
Language:
english
Creator:
Cardenas, Adriel J
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.B.C.)
Degree Grantor:
University of Florida
Degree Disciplines:
Building Construction
Committee Chair:
Kibert, Charles Joseph
Committee Members:
Archer, Wayne R
Srinivasan, Ravi Shankar
Smith, Marc T

Subjects

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

Notes

Abstract:
Current research indicates low-income tenants, as compared to median-income tenants, allocate a disproportionately high percent of their income toward utility expenditures. Research also indicates that in recent years low income tenants are struggling to keep up with increasing energy costs. In 2009, Gainesville Regional Utilities launched the first ever Solar Feed-In Tariff in the US. Although the express purpose of the program was not to serve as a housing policy tool, the possibility exists the program could serve a dual purpose. This paper examines the effect on a project owner’s bottom line when combining Gainesville Regional Utilities Solar Feed-In Tariff with Low Income Housing Tax Credits. More specifically, whether or not a project owner aided with the aforementioned subsidies can generate excess cash flow after meeting all project operating expenses and debt service, in addition to paying all tenant electricity expenses.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Adriel J Cardenas.
Thesis:
Thesis (M.S.B.C.)--University of Florida, 2013.
Local:
Adviser: Kibert, Charles Joseph.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-08-31

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046052:00001


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1 COMBINING GAINESVILLE REGIONAL UTILITIES SOLAR FEED IN TARIFF WITH LOW INCOME HOUSING TAX CREDITS: SEEKING VALUE FOR BOTH TENANTS AND PROJECT OWNERS By ADRIEL JESUS CARDENAS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2013

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2 2013 Adriel Jesus Cardenas

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3 To my beloved bride, Kaley, who everyday deposits in me insatiable joy and purpose. What a difference it makes having your soul mate by you your side. Be it for times of motivation, celebration, and companionship, or simply to laugh, cry, and grow old together. Not a day

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4 ACKNOWLEDGMENTS I would like to acknowledge several people that were instrumental in the achievement of my thesis and graduate degree. First, to my mom and dad, Nancy and Frank, I could never thank them enough for all their dedication and encouragement throughout the year s. No greater influence have I had in life than their example of hard work in all circumstances and a deep and unfailing love for God. Simply stated, I could not be the person I am today without their love and support! A special thanks to my sister, Jessi ca, who on countless occasions helped me proof many documents during my time in graduate school. To my brother Frankie thanks for just being Frankie. To my in laws, India and Alexander Hester, special thanks goes to them for their constant support, not o nly in my academic endeavors, but also by entrusting me with their dearest possession, their daughter and my wife Kaley. A better set of in laws do not exist! To my aunt Lizi for encouraging me to push harder and reach higher when it came to academics. To my thesis committee Dr. Kibert, Dr. Archer, Dr. Srinivasan, and Dr. Smith, for guiding me through this research project and encouraging me along the way. I have always been and will always be extremely inquisitive, so I am thankful for their patience in an swering my many questions! To Dottie Beaupied for the support role she played during my time at the Rinker School of Building Construction Her commitment and dedication to students is truly unmatched! A special thanks to imburg Center. It was there where I began to learn more about affordable housing and the many challenges families and individuals across America face in finding decent shelter. It is hard to imagine I could be where I am today without the tutelage I receiv ed from them. And most of all, I thank my Lord and Savior Jesus Christ, for whom without, purpose does not exist!

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 10 2 LITERATURE REVIEW ................................ ................................ .......................... 13 Low Inco me Housing Tax Credit ................................ ................................ ............. 13 Solar Feed In Tariff ................................ ................................ ................................ 15 Gainesville Regional Utilities Solar Feed In Tariff ................................ ................... 19 PV Costs ................................ ................................ ................................ .......... 19 PV System Degradatio n ................................ ................................ ................... 20 Capacity Factors ................................ ................................ .............................. 20 Operation and Maintenance ................................ ................................ ............. 20 Outside Subsidies ................................ ................................ ............................ 20 Case Studies ................................ ................................ ................................ .......... 21 Case Study 1: SOLARA ................................ ................................ ................... 21 Project overview ................................ ................................ ......................... 21 Strategy for energy efficiency ................................ ................................ ..... 22 Passive design measures ................................ ................................ .......... 23 Energy efficient materials and products ................................ ..................... 23 Renewable energy source ................................ ................................ ......... 23 Sources of funding ................................ ................................ ..................... 24 Operating results ................................ ................................ ........................ 24 Case Study 2: Los Vecinos ................................ ................................ .............. 25 Project overview ................................ ................................ ......................... 25 Strategy for energy efficiency ................................ ................................ ..... 25 Passive design measures ................................ ................................ .......... 26 Ener gy efficient materials and products ................................ ..................... 27 Renewable energy source ................................ ................................ ......... 27 Sources of funding ................................ ................................ ........................... 27 Operating Results ................................ ................................ ................................ ... 28 3 RESEARCH METHODOLOGY ................................ ................................ ............... 29 Overview ................................ ................................ ................................ ................. 29 Description of Conceptual Development ................................ ................................ 31 Outline of Scenario 1 Base Year Assumptions ................................ ....................... 32

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6 Description of Steps 1 to 12 ................................ ................................ .................... 32 Project Uses: Replacement Cost of Building ................................ .................... 32 Project Sources: LIHTC Equity and Conventional Debt ................................ ... 33 Operating Revenue ................................ ................................ .......................... 34 Operating Expenses ................................ ................................ ......................... 35 Net Operat ing Income ................................ ................................ ...................... 35 Before Tax Cash Flow ................................ ................................ ...................... 35 Trending Assumptions ................................ ................................ ...................... 35 Return Analysis ................................ ................................ ................................ 36 Outline of S cenario 2 Base Year Assumptions ................................ ....................... 36 Description of Steps 1 to 20 ................................ ................................ .................... 37 Project Uses: Building ................................ ................................ ...................... 37 Project Uses: Solar ................................ ................................ ........................... 37 Project Sources ................................ ................................ ................................ 38 Operating Income ................................ ................................ ............................. 39 Operating Expenses ................................ ................................ ......................... 40 Net Operating Income ................................ ................................ ...................... 41 Before Tax Cash Flow ................................ ................................ ...................... 41 Trending Assumptions ................................ ................................ ...................... 41 Return Analysis ................................ ................................ ................................ 41 4 CONCLUSIONS ................................ ................................ ................................ ..... 42 Iteration 1 ................................ ................................ ................................ ................ 42 Iteration 2 ................................ ................................ ................................ ................ 43 Sensitivity Analyses ................................ ................................ .......................... 44 Occupancy ................................ ................................ ................................ ....... 45 Electricity Inflation ................................ ................................ ............................ 46 Low E Cost Premium ................................ ................................ ....................... 47 Energy Load Reductions ................................ ................................ .................. 48 Benefit to Tenants ................................ ................................ ................................ ... 49 5 AREAS FOR FUTURE RESEARCH ................................ ................................ ....... 51 APPENDIX A NOVOGRASAC & COMPANY LLP RENT & INCOME LIMIT CALCULATOR ........ 52 B UTILITY ALLOWANCE SCHEDULE 2BR ................................ ............................. 56 C SOLAR PANEL SPECIFICATIONS ................................ ................................ ........ 58 D SOLAR ENERGY INCOME ................................ ................................ .................... 60 E STANDARD DEVELOPMENT 15 YEAR PRO FORMA ................................ ......... 62 F ENERGY EFFICIENT DEVELOPMENT 15 YEAR PRO FORMA WITH BUY BACK RATE OF $0.18/ KWH ................................ ................................ ................. 64

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7 G ENERGY EFFICIENT DEVELOPMENT 15 YEAR PRO FORMA WITH BUY BACK RATE OF $0.24/ KWH ................................ ................................ ................. 66 H 2008 10 ENERGY USE DATA FOR GAINESVILLE LIHTC PROJECT .................. 68 LIST OF REFERENCES ................................ ................................ ............................... 98 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 101

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8 LIST OF TABLES Table page 4 1 PVs @ Buy Back Rate of $0.18 per kWh ................................ ........................... 43 4 2 PV @ Buy Back Rate of $0.24 per kWh ................................ ............................. 4 4 4 3 PVs of Vacancy Rates @ DR of 8% ................................ ................................ ... 45 4 4 PVs of Vacancy Rates @ DR of 10% ................................ ................................ 45 4 5 PVs of Vacancy Rates @ DR of 12% ................................ ................................ 46 4 6 PVs of Electricity Inflation @ DR of 8% ................................ .............................. 46 4 7 PVs of Electricity Inflation @ DR of 10% ................................ ............................ 46 4 8 PVs of Electricity Inflation @ DR of 12% ................................ ............................ 47 4 9 PVs of Low E Cost Premium @ DR of 8% ................................ ......................... 47 4 10 PVs of Low E Cost Premium @ DR of 10% ................................ ....................... 48 4 11 PVs of Low E Cost Premium @ DR of 12% ................................ ....................... 48 4 12 PVs of Energy Load Reductions @ DR of 8% ................................ .................... 49 4 13 PVs of Energy Load Reductions @ DR of 10% ................................ .................. 49 4 14 PVs of Energy Load Reductions @ DR of 12% ................................ .................. 49

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9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction COMBINING GAINESVILLE REGIONAL UTILITIES SOLAR FEED IN TARIFF WITH LOW INCOME HOUSING TAX CREDITS: SEEKING VALUE FOR BOTH TENANTS AND PROJECT OWNERS By Adriel Jesus Cardenas August 2013 Chair: Charles Kibert Major: Building Construction Current research indicates low income tenants, as compared to median income tenants, allocate a disproportionately high percent of their income toward utility expenditures. R esearch also indicates that in recent years low income ten ants are struggling to keep up with increasing energy costs. In 2009, Gainesville Regional Utilities launched the first ever Solar Feed In Tariff in the US. Although the express purpose of the program was not to serve as a housing policy tool, the possibil ity exists the program could serve a dual purpose. This paper examines the effect on a project In Tariff with Low Income Housing Tax Credits More specifically, whether or not a p roject owner aided with the aforementioned subsidies can generate excess cash flow after meeting all project operating expenses and debt service, in addition to paying all tenant electricity expenses.

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10 CHAPTER 1 INTRODUCTION For decades now, the U.S. government has subsidized the development of low income housing. In light of the recent housing crisis, the need for suc h aid is becoming more apparent as the country experiences an influx of displaced homeowners. Although income househo lds are facing a new challenge rising energy costs. Unlike housing prices, energy prices do not fluctuate relative to market conditions and neighborhood characteristics. In addition, one can easily deduce that due to the increased susceptibility of deferring routine maintenance, low income tenants often live in homes o r dwellin g units that are less energy efficient The seriousness of the crisis begs the question, what can be done? As demonstrated by empirical data, utility expenses disproportionately affect the poor. Low income families in the U.S. dedicate as much as 26 perce nt of their income t o utility payments (HUD, 2009 ). To illustrate the significance of this figure, consider that median income families typically allocate 4 percent of their income to such costs (HUD, 2009) Yet, perhaps more alarming is that in certain pa rts of the country, failure to make payment on utility bills can account for 26 percent of all tena nt evictions (HUD, 2009 ). The annual report titled The Affordable Energy Gap captures the crisis in aggregate. The focus of the report is to quantify the de ficit of affordable energy bills, relative to actual energy bills, per a given geographic area. In the context of this report, an affordable energy bill is defined as being 6 percent of gross household income (Fisher, Sheehan, & Colton, 2011 ) Hence, the d ifference between affordable and actual energy payments determines the energy gap. In 2011, the energy gap for the entire

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11 country was $29,856,944,854. Incidentally, the findings of this report indicate that this chasm is also widening with time. Since 2002 the gap has swelled by 64.1 percent ( Fisher et al., 2011 ). As an aside it will be helpful at this point to define and differentiate the terms low income households and affordable housing. Though these terms may seem synonymous, there is a significant d ifference between them. For the purpose of this the area median income (AMI), adjusted for family size. Conversely, the term affordable housing will refer to gross househ old costs that do not exceed 30 percent of household income (Shimberg, n.d. The Low Income Housing Tax Credit (LIHTC) subsidizes the vast majority of affordable housing in the U.S. Since multifamily rental properties are unsustainable on low income rent s alone, this funding is considered necessary. Otherwise, it is quite likely that the supply of affordable housing would not keep up with its demand (Serlin, Kimura, Ascierto & McManus, 2011) Under this program, subsidies cover approximately 70 percent of total development costs (Ling and Archer, 2010). The precise level depends on the market value for tax credits at the time of sale as well as a individuals earning less than 60 percent of the area median income (AMI). Another potential subsidy program is a Solar Feed In Tariff (FIT) a progressive energy policy that aims to create an artificial market condition in which Renewable Energy Technology (RET) investments are profitable. Depending on the policy goals of the designer, FIT programs can help stimulate demand in either hydro, so lar, or wind

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12 systems. Back in 2009, the city of Gainesville introduced a solar feed in tariff (FIT) to encourage the generation of clean energy. To stimulate this mark et, Gainesville Regional Utilities (GRU) initially proposed to pay solar energy producers more than double the ir cost for every unit of electricity FIT was structured such that investors in solar RETs would yield a 5 t o 8 percent Internal Rate of Return (IRR) (Regan 2008). Although this program does no t directly that it could in fact serve to mitigate the energy burden confronting low income households. Therefore, the res earch hypothesis st ates that an LIHTC proje ct, if combi ned with could withstand the incursion of all tenant related electricity expenses and be yield accretive as compared to a standard LIHTC investment. More specifically, it is anticipated that remunerations from the FIT will exce ed the added operating expenses resulting from tenant electricity usage. It shall be further ass umed that the project owner would not raise rents as a result of eliminating electricity bills. Should the research hypothesis prove to be true, both the projec t owner and tenants will benefit Tenants would experience financial relief as they will no longer have electricity payments ; a project owner would receive higher returns in exchange for his willingness to take on more risk. Consequently, if and when Solar FITs become more common, this may serve as a future policy tool to help mitigate poverty.

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13 CHAPTER 2 LITERATURE REVIEW Low Income Housing Tax Credit The Low Income Housing Tax Credit (LIHTC) program is the primary driver of new affordable housing in the U.S. By current estimates, the program has funded over 1.5 million affordable housing units ( Desai, Dharmapala, and Singhal 2010). The program traces its origins back to the Tax Reform Act of 1986 (TRA86), where congress removed several tax shelters avai lable to investors through real estate holdings. To compensate, lawmakers created several new tax shelters, including the low income housing tax credit (LIHTC) program. This new program provided eligible investors with a vehicle by which to earn returns wh ile simultaneously stimulating the development of affordable housing (Desai et al 2010). According to TRA86, the federal government is charged with annually dispersing tax credits to each state In 2009, for example, each state received the greater of e ither $2.35 per resident, or the federal minimum of $2,665,000 tax credits (Keightley, 2009). Once a state receives their federal allocation, they are subsequently awarded to developers on a competitive basis. Projects are judged according to their complia nce with state issued Qualified Action Plans (QAP) and relative to the overall applicant pool (Keightley, 2009). By federal law, each state is required to produce a QAP outlining the federal minimum standards, as well as state specific criteria for eligibl e projects. Particularly important is the federal mandate giving preference to projects that accommodate the most disadvantaged for the longest period of time (Keightley, 2009). the eligible basis must be calculated. This consists of all depreciable costs such as

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14 construction expenses and architectural and engineering fees. Items which are excluded from the calculation and therefore ineligible for funding typically include land pr ocurement and certain financing costs. The second step involves determining the applicable fraction of the project. The assertion is that eligible projects are not exclusively required to serve low income families or individuals ( Donovan, n.d. ). I n fact, is not uncommon for LIHTC projects to offer both market rate and rent restricted units. However, careful consideration must be given to a federal mandate stipulating that either 20 percent of the units must be restricted for households with 50 percent or l ess of AMI or 40 percent of the units must be restricted for households earning 60 percent or less of AMI (Novogradac 2010). Whichever the case, only the portion of the development reserved for low income use is eligible for funding. The exact value is de termined by the lesser of the following options: the percent of rent restricted units to total units or the percent of square feet in rent restricted units to total square feet ( Novogradac 2010). The final step involves the calculation of the qualified b asis, which simply refers to the applicable fraction of the project in dollars (Donovan, n.d. ). Once this value is known, it is multiplied by the appropriate subsidy factor, either 4 or 9 percent. This result specifies the dollar equivalent of tax credits allocated to the project for a period of ten years. For instance, if the qualified basis of a project is $1,000,000, and a 9 percent subsidy is applied, $90,000 ($1,000,000 x .09) of tax credits is awarded annually for ten years. Therefore, the project own er is granted $900,000 ($90,000 x 10 years) in tax credits. The 4 percent award is calculated in a similar fashion, the only difference being a 4 percent rate is utilized in p lace of the 9 percent rate.

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15 After developers receive their credits, they are s old off to qualified investors. Consequently, an investor becomes a limited, but up to 99.9 percent partner in either a Limited Partnership (LP) or Limited Liability Corporation (LLC) (Donovan, n.d.). On other hand, developers trade tax credits in exchange for capital and retain a .01 percent interest as a General Partner (GP) (Donovan, n.d.). Although investors acquire 10 years of tax credits, state law often requires projects to retain their affordability r estrictions well over 30 years (Serlin, Kimura, A scierto & McManus, 2011) The specific manner in which LIHTCs produce equity for investors is a point that is often overlooked. Returns on such investments are realized through tax credits and interest and depreciation deductions. In essence, such investo rs are seeking to reduce their taxable income or tax liability (Robinson, 2010). Because of passive activity loss restrictions, investors of LIHTC credits are most often limited to corporations. Moreover, approximately 43 percent of LIHTC investors represe nt financial institutions complying with the Community Reinvestment Act (CRA) (Keightley, 2009). The underlying goal of the LIHTC funding is to subsidize development costs in order to reduce the debt service of a project. In turn, this provides developers with the flexibility to offer affordable or submarket rents to income qualifying individuals or families. I n general, the LIHTC was designed to target households earning at or less than 60 percent of AMI (Keightley, 2009). Solar Feed In Tariff As Solangi: people have used since the b Fayaz 2011). This is perhaps the most compelling argument concerning the long term

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16 viability of solar power In addition to the aforementioned, other factors that support the pursuit of solar energy include: It does not deplete natural resources; No emissions of greenhouse (mainly CO2, NOX) or toxic gases (SO2, particulates); Reclamation of degraded land; Redu ction of transmission lines from electricity grids; Improvement of quality of water resources; Increase of regional/ national energy independence; Diversification and security of energy supply; Acceleration of rural electrification in developing countries (Solangi et al, 2011). Yet in spite of these points, solar renewable energy only represents .05 percent of aggregate clean energy production (Solangi et al, 2011). With so much in its favor, why then is solar so poorly represented amongst other clean energ y products? Absent government intervention, the cost of Renewable Energy Technologies (RETs) is historically such that they produce net financial losses. In other words, the cost of purchasing an RET (cas h out) is outweighed by cash flows realized from ele ctricity generated (cash in). In order to compensate for this imbalance, many countries have moved toward the adoption of innovative energy programs, namely solar feed in tariffs (FITs). An FIT is a progressive energy policy that encourages the production of electricity through the use of RETs (Cory, Couture, & Kreycik, 2009). Over the years, many countries have implemented such programs as a means of encouraging the production of clean energy. In doing so, the goal is to either subsidize the cost of RETs

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17 or the cash flows from the electricity generated. In essence, both subsidi es, whether supply or demand side, attempt to reconcile the imbalance of negative cash flows. In addition to FITs, some countrie s are experimenting with other initiatives such as Tra dable Green Certificates (TGCs) and Renewable Portfolio Standards (RPS). However, when instituted proper ly, an FIT is currently regarded as the best means of stimulating demand and meeting clean energy production goals (Couture & Gagnon, 2009) Though Eur opean nations often receive credit for the development of the FIT, the framework for the program was initially conceived under the US Public Utility Regulatory Policy Act of 1978 (PURPA) (Lesser & Su, 2008 ). Under PURPA, however, feed in payments were stru ctured in such a manner that the program was deemed too to per unit of production In other words, due to the inherent challenge of forecasting long r un energy prices, this payment scheme yielded poor results and the concept was ultimately abandoned (Lesser & Su, 2008) Though the pr ogram was never pursued in the States, this did not prevent other nations from exploring the concept further. In fact, t h e first FIT program was institut ed by Germany in 1991, and many European nations followed thereafter. Today, FITs are structured as either fixed or premium price models. The two differ in that the former is independent of the market price for electricity, whereas the latter is dependent (Couture & Gagnon, 2009). In addition, several sub models exist for each of the two program options ; h owever, discussion of the sub models is beyond the scope of this research, thus the focus shall rem ain on the two parent s ystems.

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18 The fixed price model, or market independent model, is regarded as the most popular and effective way to stimulate demand for RETs. In particular, for every unit of electricity produced, investors are guaranteed a fixed rate payment that is well a bove the current retail price. The per unit buy as well as a risk premium, such that investors are appropriately compensated for their risk. When formulating a buy back price, this model considers the expec ted cost of electricity as opposed to the actual cost. The guaranteed price is typically honored for 20 years, which is consistent with the expected life of the product or system. With this policy option investors typically receive better financing terms b ecause of the greater certainty concerning future cash flows (Couture & Gagnon, 2009) In contrast, the market dependent or premium rate policy differs due to the manner in which cash flows are derived. Just as the name suggests, this version is tied to t he market spot rate for electricity, on top of which investors receive a premium. In other words, a prospective investor is guaranteed a fixed percentage above the actual spot rate over the life of the RET. Although this version is not as successful as the fixed price method, it has flourished in certain applications. Among the more heralded examples are the Dutch and Spanish cases (Couture & Gagnon, 2009) It is important to note t wo inherent challenges that exist with this model: investors are exposed to market volatility, which produces uncertain remunerations, and ratepayers are subject to higher utility costs. For instance, if the market spot rate were Conversely, if prices were to increase significantly, ratepayers would then be faced with higher rates. It is important to remember that under s uch programs the generous rate

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19 of return received by investors comes at the expense of ratepayer s Therefore, it is not diff icu lt to see how some constituents may object to FITs altogether. In an effort to protect against such volatility, Spain recently adjusted their model to incorporate a price floor and ceiling (Couture & Gagnon, 2009) Gainesville Regional Utilities Solar Feed In Tariff In February of 2009, Gainesville, FL sparked headlines by implementing a fixed rate, solar FIT (Cory, Couture, & Kreycik, 2009). The announcement was met with much fanfare because it was the first in the U.S.; however, the process was laden with challe nges. Particularly, the central challenge was to identify the feed in subsidy price at which prospective investors would be enticed to participate This point is not only sensitive for investors, but also to ratepayers in the market that bear th e cost of the tariff. Per their initial recommendation investors would receive fixed payments of $0.32 per kWh of electricity placed into the main grid, thereby resulting in a 5 to 8 percent return over a 20 ye ar period. As demand for PVs increases (and theoretically prices decrease) the intent is to scale down the buy back rate of energy such that the investment yield remains neutral. To arrive at this yield GRU considered five factors : Photo Voltaic (PV) cost s, PV system de gradation, capacity factors, Operation and Maintenance, and ou tside subsidies (Regan, 2008 ). Below is a broad outline of the major assumptions GRU used in designing their Solar FIT program (Regan, 2008 ): PV Costs In factoring the average c ost of a PV system, GRU collected local and state cost data. In making this calculation, several cost variables were considered:

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20 installation, materials, inverters, electrical work, and labor. This calculation produced an average cost of $8.50 per watt ins talled (Regan, 2008 ). PV System Degradation With respect to PV systems, the older the product, the more inefficient it becomes at converting sola r energy into electricity (or DC to AC electricity). On average, PV systems lose 20 percent of their efficienc y after 20 years of operation. Accordingly, GRU was able to determine the average annual decrease in product efficiency was 1 percent per year (Regan, 2008 ). Capacity Factors The capacity factor indicates the average number of prime sunlight hours for sol ar collection on an annual basis. Based on historical data, it was determined that the capacity factor for Gainesville, FL was 17 percent, or 4.08 prime sunlight hours per day (Regan, 2008 ). Operation and Maintenance Throughout the life (approximately 20 years) of a PV system, it is reasonable to expect repair and replacement costs. In this category, the largest expenditure is the replacement of the inverter that occurs at year ten. The replacement cost of this component is $1,000/kW. Consequently, when ac counting f or O and M expenses, GRU included a $25/kW year allowance in their calculation (Regan, 2008 ). Outside Subsidies Lastly, two additional outside financial adjustments are built into this calculation. These adjustments are a Federal Investment Tax Credit Rate of 30% and a federal production tax credit of $0.02/kW, which is only available for five years. Other assumptions considered include: that the owner has sufficient tax liabilities to take

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21 advantage of IRS 179 depreciation, an electrical price e scalation rate of 3 percent per year (linearly over the 20 year life of the program), for the IRS tax rate to be 35 percent throughout the analysis, and a PV system life of 20 years (Regan, 2008 ). After considering all of the above factors, GRU recommended setting the initial fixed rate feed in price at $0.32 per kilowatt hour. At this rate, prospective investors of PV systems could earn an after tax internal rate of return (IRR) of 5 to 8 percent. However, should any of the variables in the analysis change this would necessarily cause upward or downward movement in the projected IRR (Regan, 2008 ). Case Studies The purpose of this case study is to review prior work in the field of net zero energy or nearly net zero energy affordable housing. Although this c oncept was once thought to be cost prohibitive for this type of application, time has proven this statement to be false. Thanks in part to federal assistance, as well as good will among affordable housing practitioners and policy makers, the past few years have led to the development of several milestone projects. For the purpose of this study we shall analyze two projects in particular, both of which are located in the Southern California region Case Study 1: SOLARA Project o verview SOLARA, an affordable housing community located in Poway, CA, was designed as a net zero energy development (NZE). Although in practice the project did not meet this benchmark, it came very close to doing so. The project is a joint venture between San Diego based developer Com munity Housing Works and the City of Poway, CA. The housing development is a two story, 56 unit apartment complex, which sits on a 2.5

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22 the Area Median Income ( Green, 2009). Moreover, SOLARA is considered the first multi family rental community to be fully powered with solar energy, producing nearly 100% of its electricity needs on site As such, the project design stipulated that each dwelling unit would receive its o wn dedicated PV system, inverter, and meter. T enants at this site must attend a mandatory green education program and are also afforded the necessary resources to monitor and manage thei r individual energy use ( Green, 2009). Strategy for energy e fficiency The strategy for delivering a green, energy efficient community was formalized through a series of integrated design process meetings The Integrated design process is a holistic approach to project design that encourages joint meetings with key design an Department ( Global Green, 2009). The outcome of this focus group was a roadmap for the effective and efficient delivery of a net zero affordable housing community (Green, 2009). With respect to energy efficiency, the primary outcome was a plan to minimize the building More specifically, it was determined that the be decreased by identifying its optimal orientation, integrating efficient heating and cooli ng systems, and energy efficient lighting (Green, 2009).

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23 Passive design m easures passive design techniques and energy efficient materials and products. The primary passive de sign techniques employed at SOLARA were orienting the building such that the incoming south and southwest ocean breeze maximized cross ventilation at the site, the inclusion of ceiling fans in each unit, and open air corridors located throughout the develo pment, thus collectively eliminating the need for mechanical cooling. Also, with respect to orientation, was the strategic positioning of the broad side of the roof relative to the sun. This measure was put in place so that the PV panels could capture the maximum amount of solar energy. T he solar panels also served a second, albeit lesser purpose, of reducing heat gain via the roof by providing shading (Green, 2009). Ener gy efficient materials and p roducts In addition to passive demand side mitigation tech niques, energy loads were further reduced with the use of energy efficient products. For instance, all the appliances throughout the development were Energy Star approved. Furthermore, instead of using R 19 wall and ceiling insulation, which is customary i n this application, the building plans cal led for R 30 throughout ( Green, 2009). Other materials or products that were installed included tankless water heaters, hydronic heating systems, an Energy Star approved radiant roof barrier, and low E windows (Gre en, 2009). Renewable energy s ource buildings were oriented in a way that maximized their southern exposure. One of the unique aspects of the development is that each apartment recei ves power through its own unit specific panels and inverters. In aggregate, the SOLARA housing community

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24 is equipped with 836 PV panels, which generate 141 kW of electricity ( Green, 2009). This system provides electricity to all 56 units, all common area s including a 2,100 SF community center, and parki ng areas (Green, 2009). Sources of f unding Although the project site was purchased by the City of Poway for $2.7 million dollars, it was subsequently leased to the development team at no cost f or a period of 99 years ( Green, 2009). The total project cost was $16.2 million or approxim ately $290,000 per unit ( Green, 2009). Furthermore, the cost s of greening the project and installation of the PV systems were approximately $330,000 and $1,100,000 respectively ( G reen, 2009). These costs included contractor profit and overhead. The additional $1,400,000 in costs was largely mitigated with funding from the followin g sources (Green, 2009): California Energy Committee Rebate: $409,000 Federal LIHTC green incentive bo ost: $405,000 Federal investment tax credit for solar: $208,000 Total additional funding: $1,022,00 Operating r esults For the purpose of analyzing energy use and savings, an on site monitoring system was installed T he specific goal was to monitor the following three categories: aggregate energy use, solar PV production, and cost savings to the developer and tenants (Green, 2009) After a full year of collecting this data, one of the more significant findings revealed that on average, tenants were abl e to meet 87% of their electricity needs wit h the on site PV system ( Green, 2009). Moreover, at peak demand hours, the development require d less than 1kW of electricity per day from the grid (Green, 2009).

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25 s energy needs were met with its on site PV system, tenant rents did include a utility premium in order to improve the sh flow (Green, 2009). Case Study 2: Los Vecinos Project o verview Los Vecinos is an affordable housing project locat ed in Chula Vista, CA, a suburb of San Diego. This community, which services families earning between 30 and 60 percent of the Area Median Income, is owned and developed by Wakeland Ho using and Development Corp ( Green, 2010). T he housing development consis ts of a three story, 42 unit complex, which sits on a 1.35 acre site. Much like SOLARA, Los Vecinos was designed to operate as a net zero energy affordable housing development, which would meet all of its electricity needs with an on site PV system. One of the major achievements of this particular project was the fact that it met the NZE pe rformance metric and attained LEED Platinum status (Green, 2010). Los Vecinos is only the second NZE affordable housing project within the state of California. Unlike Solara, however, which commenced as a ground up new construction project, Los Vecinos was a rehab of a formerly dilapidated hotel ( Green, 2010). Strategy for energy e fficiency Similar to the SOLARA development, the design and planning of Los Vecinos began with an integrated design process. T he major breakthrough that emerged from these meetings with respect to energy efficiency was a comprehensive energy mitigation pl an that focused on demand side energy needs. Specifically the energy demands of the building were decreased by identifying the opt imal orientation and integrating energy efficient heating and cooling systems, as well as energy efficient

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26 light ing and cooli ng systems (Green, 2010). Overall the design team aimed first to zero out or minimize grid dependence the team then incorporate d a renewable energy suppl y source (Gre en, 2010). Passive design m easures passive design techniques and energy efficient materials and products. The primary passive design technique used at Los Vecinos was the substit ution of mechanical heating and cooling with passive cooli ng and hydronic heating (Gr een, 2010). Because Los Vecinos is located near the coast, and in a Hot Arid climate region, ocean breeze. The first task was orienting the building such that the incoming south and southwest ocean breeze maximized cross ventilation at the site. This organic approach to cooling was further enhanced by the installation of ceiling fans in every uni t, along with open air corridors located throughout the development, thereby eliminating the need for mechanical cooling (Green, 2010). For heating purposes, the building design included a hydronic heating system. This also eliminated the need for traditi onal mechanical heating. Then, in order to positioned such that it maximized its southern exposure. In addition, the solar panels also served a second, albeit lesser purp ose, of reducing daytime heat gain through the roof by providing shading (Green, 2010).

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27 Energy efficient materials and p roducts In contrast to the more cost effective passive design approach, on site energy loads were also reduced with energy efficient pr oducts. For instance, all of the appliances throughout Los Vecinos were Energy Star rated products. Furthermore, instead of using R 19 wall and ceiling insulation, which is customary in this application, the building called for R 30 throughout ( G reen, 2010 ). Other notable energy efficient materials or products installed included tank less water heaters, a cool roof, and low E windows (Green, 2010). Renewable energy s ource B green feature is its solar panels, the bui ldings were oriented such that the roof face maximized southern exposure. In aggregate, Los Vecinos housing community boasts a 93 kW PV system that provides electricity to all 42 units, all commons areas, and parki ng areas (Green, 2010). Sources of f undin g The total cost to build Los Vecinos was approximately $17.3 million, or $412,000 per unit (Green, 2010). The funding for this project came from a variety of sources, namely Low Income Housing Tax Credits, the City of Chulavista Redevelopment Agency, the California Community Reinvestment Corporation, a federal solar rebate, and a solar business investment tax credit. Furthermore, the cost of greening the project and installation of the PV system was estimated at $647,300 and $848,523 respectively (Green, 2 010). The fees on the project include d con tractor profit and overhead. An additional $1,495,823 in costs was largely mitigated with funding from the following sources (Green, 2010):

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28 State PV Rebate: $311,400 Additional Housing Tax Credits $620,915 Feder al Solar Tax Credits $157,930 Utility Rebates $6,700 Water Sub metering Payments $23,750 Total additional funding: $1,120,695 Operating Results For the purpose of analyzing energy use and savings, an on site monitoring system was installed. The results from the monitoring indicate d that Los Vecinos is producing 30 percent more electricity than it uses, thus making the project a net exporter of electricity (Green, 2010) Although this statistic is impressive, tenants at this location still pay an average electricity bill o f $39 per month due to State regulations (Gr een, 2010). T his is true given that in California, by virtue of being connected to the electric grid, all utility customers must pay a minimum fee irrespective of energy use ( Green, 2010).

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29 CHAPTER 3 RESEARCH METHODOLOGY Overview The purpose of this analysis is to tes t whether the General Partner ( GP or Owner ) of a 9 percent Low Income Housing Tax Credit (LIHTC) project, when coupled in Tar iff (FIT) subsidy, can generate incremental value from their investment despite i ncurring all tenant electricity costs. The expectation is to find a mutually beneficial outcome, whereby low income tenants are afforded financial relief resulting from no ele ctricity bills and a property owner is also compensated for their added risk. In order to test the forgoing, two investment scenarios derived from a single 9 percent LIHTC developme nt shall be presented and their yields compared. Generally, both investment scenarios will possess the same design attributes with respect to unit and building counts, as well as dimensions. Conversely, each will be unique with respect to their Energy Efficiency Measures (EEMs), capital costs and subsidies, and operating income a nd expenses. Scenario 1: The first investment scenario could be thought of as a base case or standard 9 percent LIHTC development. From a physical standpoint, the project is said to be standard given the assumption it complies with current building requir ements (It should be noted this is not to imply there is a standard or typical LIHTC project that exists in the market place). The financial analysis will also be standard to the extent owner and tenants will each bear their own electricity expenses. Herea fter, this option will be referred to as Scenario 1 or the Standard Development. Scenario 2: The second investment scenario will resemble the first in terms of building structure and unit count. From an operational standpoint, however, it shall be presume d the project owner will incur all tenant electricity costs up to a reasonable and capped amount. This cap shall be put in place in order to protect the owner from the frivolous use of energy. Moreover, th is added cost will appear as a separate line item w ithin the pro forma operating expenses and will be burden, it is reasonable to assume the inclusion of EEMs, which will help mitigate operating expenses.

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30 T his scenario also co ntemplates the inclusion of a Solar FIT operating subsidy to compensate for the increase in risk exposure An additional line item labeled these remunerations. Consequently, Scen ario 2 will differ from Scenario 1 in that it presumes to have not only EEMs, but also a renewable energy source, which will facilitate solar income. This in turn will result in a first cost capital expense premium, relative to Scenario 1 T his scenario wi ll also benefit from a capital subsidy in the form of Incentive Tax Credits (ITCs). Hereafter, this option will be referred to as Scenario 2 or the Energy Efficient Development. Before moving ahead, there are several side notes or clarifications regarding the structure of the analysis that should be addressed. Most notably, because the LIHTC and solar FIT programs are disparate in nature, we shall make some assumptions on how to best combine the two in a manner that simplifies the overall analysis The poi nts that follow speak largely to the differences in the theoretical versus actual application of the various deal components described above. In addition, they will provide instruction on how and when each will be used throughout. First, tenant electricit y expenses will be accounted for as if the project were being master metered, though in practice the project would require sub metering in order to keep track of individual energy use. Second, because the owner of the photovoltaic (PV) system and LIHTC pro ject would be two separate entities, income derived from the solar FIT would be sent to the former and not the later. For simplicity we shall assume the two are a singular entity. Third, according to federal tax code, cash distributions for LIHTC investmen ts must be bifurcated 0.01% to the GP and 99.99% to the LP. As such, it is necessary to discuss the manner by which the GP receives benefits from the project. Along with a developer fee, GPs typically absorb most residual cash flow from operations. This i s the remaining cash flow after the project has met its operating expenses and debt service obligations. This benefit is captured by the GP in the form of

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31 an Incentive Management Fee, which is considered an expense to the project and may account for as muc h as 90 % of residual cash flow. The remaining balance, which is often marginal, is then distributed between the GP and LP per their respective ownership interests. For our purposes, however, we shall assume that 100% of the projects residual income will be allocated to the GP. Finally, because this analysis is not an in depth study on the impact of EEMs on building structures, a categorical cost premium in the form of a percent will simply be applied to the base cost in Scenario 1. T he energy reductions ass ociated with these EEMs, which will also be introduced in the form of a percent, will then be offset against the base anticipated energy loads. Description of Conceptual Development At this point it will be helpful to outli ne the profile of the structure being evaluated. By doing so, this will provide guidance when deriving unit counts, a cost estimate, and the calculation of roof surface area, which will determine the solar watt capacity of the project. The physical structu re in question will consist of six two story garden style apartment buildings. Within each building each unit floor plan shall be 900 SF. Moreover, there are eight units per floor, 16 units per building, and a total of 96 dwelling units throughout the deve lopment. E ach floor level includes a five foot walkway, which bisects the units into two clusters of four foot overhang making the flat Summary of Project Parameters:

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32 # of Units: 96 # of Stories: 2 Unit mix: 96 2 BR units SF/ Unit: 900 Typical Building Gross SF: 121,680 SF Roof Type: Gable Gross SF: 121,680 Outline of Scenario 1 Base Year Assumptions Project Uses Step 1: Calculate Total Development Cost Step 2: Calculate Developer Fee Step 3: Calculate Total Re placement Cost of Development Project Sources Step 4: Calculate LIHTC Equity Step 5: Calculate Debt Service Operating Income Step 6: Calculate Potential Gross Rental Income Step 7: Calculate Net Rental Income Operating Expenses Step 8: Calculate B ase Operating Expenses Net Operating Income Step 9: Calculate Net Operating Income Before Tax Cash Flow Step 10: Calculate Before Tax Cash Flow Trending Assumptions Step 11: Rent and Expense Inflation Return Analysis Step 12: Calculate Present Value Description of Steps 1 to 12 Project Uses: Replacement Cost of Building Step 1: Calculate Total Development Cost (inclusive of hard and soft costs) The cost to construct the two story garden style apartments is $10,281,960 (121,680 SF at $84.50 per SF) (Waier, 2008).

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33 Step 2: Calculate Developer Fee The developer fee is a project expense these guidelines is 16% of total development costs (Florida Housing, 2011). Accordi ngly, the Developer fee for Scenario 1 is $1,645,114. Step 3: Calculate Total Replacement Cost of Development. The Total Replacement Cost of Development is $11,927,074 (the sum of the Total Development Cost ($10,281,960) and Developer fee ($1,645,114)). P roject Sources: LIHTC Equity and Conventional Debt Step 4: Calculate LIHTC Equity Generally, the amount of LIHTCs allocated to a project is equal to the present value of 9 percent of the qualified basis or Total Replacement Cost less ineligible basis cost s factored over ten years. Costs that tend to be ineligible from the qualified basis calculation include land, operating reserves, and third party syndication expenses. Because our analysis does not include a detailed cost budget, we shall assume the proje Cost of Development. Consequently, the total number of LIHTCs allocable to the Standard Development is $10,734,367, which in effect is 90 percent (9% over 10 years) of the Total Replacement Cost of Develo pment ($11,927,074). Once the number of LIHTCs available to the project is known, the value is then multiplied by the price per credit investors are willing to pay on the open market. Nationally, the average price per credit paid by investors in 2012 was $ 0.88 (Novogradac, 2012). Using the national credit price we find that the equity from the sale of LIHTCs is $9,446,243. Step 5: Calculate Debt Service To calculate the annual debt service payment the following variables or assumptions are needed: the principal amount to be borrowed, the interest rate, and the loan term. The amount of principal debt the project

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34 will carry is $2,480,831 (the Total Replacement Cost of Development ($1,927,074) less th e equity raised from the sale of LIHTCs ($9,446,243)). In addition, we shall assume a 4% interest rate and a 30 year amortization period. As such, the total annual debt payment for the Standard Development project is $178,486. Operating Revenue Step 6: Ca lculate Potential Gross Rental Income In the LIHTC industry, Rent & Income Limit Calculator Accordingly, the projected gross rent for a 2 bedroom unit in Gainesville, FL, restricted to those at or below 60% AMI, is $787 (Novogradac, n.d.). In order to arrive at the pro forma or net achievable rent, however, a tenant utility allowance must also be deducted. Typically the l ocal housing authority provides utility allowances. The monthly utility allowance prescribed by the Gainesville Housing Authority for 2 bedroom units is $168 per month (GHA) Therefore, the net achievable rent per unit for this analysis is $619 ($787 $168) On an annual basis Potential Gross Rental Income is $713,088. This figure is derived by determining the product of the net achievable rent per unit ($619) and the 96 projected units factored over a 12 month period. Step 7: Calculate Net Rental Income The Affordable Housing Investors Council (AHIC, 2010) serves as the industry standard for underwriting parameters of Section 42 affordable housing. AHIC recommends underwriting Vacancy and Collection losses at 7% of Potential Gross Rental Income. According ly, the Net Rental Income of the Standard Development is $663,172 (Potential Gross Rental Income ($713,088) less Vacancy and Collection Losses ($49,916)).

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35 Operating Expenses Step 8: Calculate Base Operating Expenses According to a 2012 operating income a nd expense survey published by the National Apartment Association, operating expenses for individually metered properties is $4,485 per unit (Lee, 2010). Although per unit rental expenses will be depicted as one categorical expense, it is important to note this value includes Salaries and Personnel, Insurance, Real Estate Taxes, Utilities, Management Fees, Administrative, Marketing, Contract Services, and Repair and Maintenance costs (Lee, 2010). Utilizing the aforementioned figures we find that the annual Base Operating Expenses for the project are $430,560 ($4,485 multiplied by 96 projected units). Net Operating Income Step 9: Calculate Net Operating Income Net Operating Income for the Standard Development is $232,612 (Net Rental Income ($663,172) less Base Operating Expenses ($430,560)). Before Tax Cash Flow Step 10: Calculate Before Tax Cash Flow The Before Tax Cash Flow for Scenario 1 is $54,126 (Net Operating Income ($232,612) less Annual Debt Service ($178,486)). Trending Assumptions Step 11: Rent and Expense Inflation As mentioned above, underwriting assumptions employed in this analysis shall be consistent with the recommendations of the Affordable Housing Investment Council (AHIC, 2010). As such, the following trending parameters will be applie d to the 15 year forecast:

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36 a. Gross rental income will grow at 2% annually. b. Operating Expenses will grow at 3% annually. Return Analysis Step 12: Calculate Present Value In order to measure the return potential of Scenario 1, various discount rates will be used in calculating a Present Value (PV). The Survey of Emerging Market Conditions indicates that the multifamily yields in the Gainesville, FL, regio n ranged from approximately 8 to 10% in 2012 (Archer and Becker, 2013). Because of the uncertainty or added risk assoc iated with the Energy Efficient Development a 12% discount rate shall also be factored into the analysis. As such, the projected cash flows will be discounted at incremental margins of 8%, 10%, and 12%. The Developer fee will be included in Year 1 cash flow. Outline of Scenario 2 Base Year Assumptions Project Uses: Building Step 1: Calculate Total Development Cost Step 2: Calculate Developer Fee Step 3: Calculate Total Replacement Cost of Development Project Uses: Solar Step 4: Calculate Total Solar Costs Step 5: Calculate Developer Fee for Solar Component Step 6: Calculate Total Replacement Co st of Solar Project Sources Step 7: Calculate LIHTC Equity Step 8: Calculate ITC Equity Step 9: Calculate Debt Service Operating Income Step 10: Calculate Potential Gross Rental Income Step 11: Calculate Net Rental Income Step 12: Calculate Pote ntial Gross Solar Income Step 13: Calculate Net Solar Income Step 14: Calculate Effective Gross Income Operating Expenses Step 15: Calculate Bas e Operating Expenses Step 16: Calculate Tenant Electricity Expense Net Operating Income Step 17: Calculate Net Operating Income

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37 Before Tax Cash Flow Step 18: Calculate Before Tax Cash Flow Trending Assumptions Step 19: Rent Inflation, Expense Inflation, and Energy Inflation Return Analysis Step 20: Cal culate Present Value Description of Steps 1 to 20 Project Uses: Building Step 1: Calculate Total Development Cost (inclusive of EEMs) As stated in Step 1 of Scenario 1, the cost to build the two story garden style apartments is $10,281,960. In addition, the Energy Efficient Development will in clude a $144,000 cost premium in order to enhance the energy performance of the development. That cost premium is $1,500 per each of the 96 projected units, which produces a Total Development Cost of $10,425,960 (Fonorrow, 2013). Step 2: Calculate Develope r Fee The Developer Fee for the Energy Efficient Development is calculated as 16% of Total Development Costs or $1,668,154 (Florida Housing, 2011). Step 3: Calculate Total Replacement Cost of Development. The Total Replacement Cost of the Energy Efficient Development is $12,094,114 (the sum of the Total Development Cost ($10,425,960) and the Developer Fee ($1,668,154)). Project Uses: Solar Step 4: Calculate Total Solar Cost The Total Solar Cost is equal to total watts of photovoltaic (PV) instal led times the cost per watt. According to Solar Impact, an Alachua County based solar installer, the cost per watt of solar PV installed is approximately $3.12 (Wilhoit, 2013). Furthermore, given the roof dimensions specified for this project, it is antici pated the project can accommodate 371,700 watts of solar PV

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38 (Wilhoit, 2013). These figures put the Total Solar Cost for the Energy Efficient Development at $1,159,704. Step 5: Calculate Developer Fee for Solar Component An appropriate fee for a developer of a solar PV project is 10% of the Total Solar Cost (Wilhoit, 2013). Accordingly, the Developer Fee for the solar component of the project in question is $115,970. Step 6: Calculate Total Replacement Cost of Solar The Total Replacement Cost of Solar is $1,275,674 (the sum of the Total Solar Cost ($1,159,704) and Developer fee ($115,970)). Project Sources Step 7: Calculate LIHTC Equity The amount of LIHTCs allocated to the Energy Efficient Development is equal to 9 percent of the qualified basis, which is then factored over a ten year period. Similar to that in Scenario 1, we shall once again set the ($12,094,114). Once the number of LIHTCs available to the project is determine d ($10,884,703), the value is then multiplied by the presumed market price per credit ($0.88) (Novogradac, 2012). These calculations set the amount of equity attributable to the sale of LIHTCs at $9,578,538. Step 8: Calculate ITC Equity The number of ITC s available to a given project is LIHTCs, we shall assume the qualified basis equal to the Total Replacement Cost of Solar ($1,275,674) and the price per credit at $0.88 ( Novogradac, 2012). This amounts to an allocation of $382,702 ITCs and an equity raise of $336,778.

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39 Step 9: Calculate Debt Service The principal debt amount for Scenario 2 is $3,454,472 (the sum of the Total Replacement Cost of Development ($12,094,114) a nd Solar ($1,275,674), less the equity from the sale of LIHTCs ($9,578,538) and ITCs ($336,778)). Moreover, the terms of the debt will consist of a 30 year, 4% fixed rate, fully amortizing loan, thus resulting in an annual payment of $197,961 Operating I ncome Step 10: Calculate Potential Gross Rental Income $713,088 ( Scenario 1, Step 6). Step 11: Calculate Net Rental Income $663,172 ( Scenario 1, Step 7). Step 12: Calculate Potential Gross Solar Income The solar panels used in this study are Hanwha HSL 60 Poly UL ( A ppendix C ). In accordance with the specifications of thi s product and the geographical location of the site, the PV system is expected to generate 503,158 kilowatts of AC energy annually (PV Watts). When taking into consideration the GRU Sola r FIT buy back rate of $0.18 per kilowatt, Potenti al Gross Solar income is $95,845 annually (DSIRE, 2013)(PV Watts, n.d.). Step 13: Calculate Net Solar Income Due to system deterioration over time, a Degradation Factor must be discounted from gross energ y production for each year. The Degradation Factor for solar equipment is approximately 1% annually ( Regan, 2008). This means that by the end of Year 1 of the analysis it is anticipated the PV system will operate at 99% efficiency, followed by 98% efficie ncy in Year 2, 97% in Year 3 and so forth. As such, Net S olar Income in Year 1 is $94,886 Step 14: Calculate Effective Gross Income The Ef fective Gross Income is $758,058 (the sum of Net Rent al ($663,172) and Solar ($94,886 ) Income).

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40 Operating Expenses Step 15: Calculate Base Operating Expenses $430,560 ( Scenario 1, Step 8). Step 16: Calculate Tenant Electricity Expense In deriving Step 16 for this scenario, we shall subdivide this step into four parts: calculate average energy use per unit per year; discount the expected energy reductions resulting from the assumed EEMS in Step 1 of this section; given the assumption of a 7% physical vacan cy, tenant energy use projections shall be consistent portion of expected electricity expenses. 1. Tenant utility expenses for this project will be factored using empiri cal energy data from a local 9 percent tax credit development. The data consists of three consecutive years of energy use for all units within the development. Though the data includes energy use for both 2 and 3 bedroom units, all 3 bedroom data points ha ve been removed ( Appendix H) It should be mentioned that the data Program for Resource Efficient Communities Although the development in question is of a slightly older vintage and consequently less ene rgy efficient than a typical project built according to 2012 energy standards, there are several inherent benefits to using this data. For instance, the data likely accounts for seasonal and behavioral variation as well as other variables such as floor lev el and unit orientations. After modifying the data, it was determined that, on average, each unit in our study will demand approximately 9,125 kilowatt hours per year (based on an approximate daily demand of 25 kilowatt hours per day). 2. According to Ke n Fonorrow of Florida Hero a local Energy Star Rater it is conceivable to attain 35% energy reductions in new multifamily space with approximately $1,500 of energy efficiency upgrades per unit (Fonorrow, 2013). More specifically, this would require the fol lowing upgrades: R 38 insulation in the attic, R 15 blown in fiberglass insulation in the walls, ensuring the envelope of each unit is properly air sealed, duct work located in air conditioned space, double pane low e vinyl windows with a minimum Solar Hea t Gain Coefficient of .20, SEAR 14 HVAC systems, and Energy Star Appliances (Fonorrow, 2013). After accounting for these reductions, it is anticipated that each unit will demand 5,931 kilowatt hours per year or a total of 569,376 kilowatts This will be th e amount of energy use for which the owner will be held responsible.

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41 3. Once gross aggregate energy use for the development is determined, the next step is to further discount this value by 7% such that it reflects the physical vacancy being forecasted. The result is a projected aggregate energy load of 529,520 kilowatt hours per year. 4. The final step in Step 16 involves the calculation of the electricity bill associated with the forecasted tenant energy demand. GRU utilizes a progressive rate structur e with three price breaks for residential use (this calculation is made on a per unit per month basis) Specifically, the first 250 units of electricity used are billed at $0.0340 per kilowatt hour, the next 499 units (251 750) are billed at $0.0680 per ki lowatt hour, and any use above 750 kilowatt hours is billed at $0.1020 per kilowatt hour (Gainesville Regional Utilities, 2012). In addition, factored as electricity use in aggregat e by a $0.0510 multiplier (Gainesville Regional Utilities, 2012). For simplicity we shall utilize an effective monthly rate of $0.1018 per kilowatt hour of electricity used. When energy use in aggregate (529,520) is factored by the effective rate per kilow att hour ($0.1018), this results in an annual Tenant Elect ricity Expense of $53,899 Net Operating Income Step 17: Calculate Net Operating Income Net Operating Income for the Energy E fficient Development is $273,599 ( Effective Gross Income ($758,058 ) le ss Base Operating Expenses ($430,560) and Tenant Electrici ty Expenses ($53,899 )). Before Tax Cash Flow Step 18: Calculate Before Tax Cash Flow The Before Tax Cash Flow is $75,638 (Net Operating Income ($273,599 ) le ss Annual Debt Service ($197,961 )). Tren ding Assumptions Step 19: Rent Inflation (Scenario 1, Step 11), Expense Inflation ( Scenario 1, Step 11), and Energy Inflation. Energy costs will increase at a rate of 3% per year (Regan, 2008)). Return Analysis Step 20: Calculate Present Value (Scenario 1, Step 12)

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42 CHAPTER 4 CONCLUSIONS Iteration 1 After running both comparison models, the results indicate no value add was realized in the Energy Efficient Development. More to the point, when discounted at incremental rates of 8, 10, and 12%, the Energy Efficient Development produced net negative PVs as compared to the Standard Development. T he PVs of the cash flows for the Standard Development actually proved stronger a t each of the se increments. For instance, at an 8% discount rate the net di fference in PVs between the two projects was $131,006. On the other hand, when considering a discount rate of 12%, the net difference in PVs was $70,470. If we isolate the added base year income and expense components of the Energy Efficient Development we can see exactly where and how the project fell sho rt. The project produced $94,885 of Net Solar Income, incurred $53,899 in Tenant Electricity Expenses, and debt service increased by $55,780 ($197,961 (EED) less $142,181 (SD)) due to the added cost of the Solar PV System ( Appendix F) Collectively, this resulted in a net loss of $13,834. Furthermore, because Solar Income decreases over time due to system efficiency loss and Tenant Electricity Expenses are projected to increase due to inflation, this on ly serves to exacerbate the shortfall. Given the assumptions contemplated, we can conclude it is financially unfeasible for a firm or individual to pursue the Energy Efficient development as opposed to the Standard Development A side observation from the analysis was the greater the rate at which the cash flows were discounted, the more de minimis the net difference in PVs became. The

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43 cash flows in the Energy Efficient Development are comparatively larger in Year 1 given higher developer fees fr om higher p roject costs ; however, the project produces cash flows which are comparatively less and which decline over time. In contrast, the Standard Development generates larger and more consistent cash flows throughout the entire holding period. In essence we find that the greater the discount rate the more marginalized the out year cash flows become. This consequently benefits the project with the weaker cash flows at that point in time. So, despite performing poorly relative to the Standard Development, by virtue of producing higher developer fees (which occur in Year 1) the Energy Efficient Development moves closer to appearing net neutral as the discount rate s increase Table 4 1 PVs @ Buy Back Rate of $0.18 per kWh Discount Rate EED SD Net Difference 8% $2,156,752 $2,287,758 ($131,006) 10% $2,078,644 $2,176,124 ($97,480) 12% $2,008,780 $2,079,250 ($70,470) Iteration 2 Although the Energy Efficient Development, when compared to the Standard Development, did not initially provide net positive value, a second iteration of the analysis was conducted. This second iteration involved r olling back th e buy back rate from the 201 3 ($0.18/ kWh) to the 2012 rate ($0.24/ kWh) (DSIRE, 2013) T he results indicate d net positive value w hen running the new caparisons models and holding all other assumptions constant Similar to that in the first iteration, if we isolate the added base y ear income and expense components in conjunction with a buy back rate of $0.24/ kWh, we find the Energy Efficient Development produced net positive value More precisely, with the

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44 aforementioned adjustment Net Solar Income increased to $126,515, and Tenant Electricity Expenses and Debt Service held constant at $53,899 and $55,780 respectively. The result was a net gain of $16,836 in favor of the Energy Efficient Development ( Appendix G) Despite the net positive value found in the second iteration, the noti on of sufficient value is an individual decision left to each particular investor. Because the risk profile of the project in question is unique, it is incumbent on each investor to determine what exactly constitutes sufficient payback. Unlike debt and equ ity instruments or real estate that trade s or exchange s regularly, and thereby provide s investors with a mechanism by which to price risk, there is no such precedence for this type of project. Therefore, this analysis merely attempts to identify points at which the project would succeed or fail if pursued. Table 4 2 PV @ Buy Back Rate of $0.24 per kWh Discount Rate EED SD Net Difference 8% $2,412,179 $2,287,758 $124,421 10% $2,306,386 $2,176,124 $130,262 12% $2,213,362 $2,079,250 $134,112 Sensitivity Analyses As with any forecast, the findings of this research are contingent to several key variables or assumptions holding constant. I t is possible or even likely however, that several of the assumptions posited here will fluctuate with time and affect the outcome of the investment. For this reason, a series of sensitivity analyses were conducted in order to identify the stress points at which the value add of the EED investment might be compromised.

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45 Occupancy The first sensitivity centered on the affe ct that occupancy rates would have on the residual value of the Energy Efficient Development Because Tenant Electricity Expenses are in part a function of occupancy rate s the question posed is whether or not the marginal benefit of a 1 % increa se in occupancy or rental income outweigh s the marginal increase in tenant electricity expenses Per the tables below, we note that with each percent increase in occupancy, the net positive difference in PVs decreases although never to the point where the net difference turns neutral or negative. This would indicate the marginal increase in Tenant Electricity Expenses slightly outweig hs the marginal increase in Occupancy Rate s or Rental Income The tables below provide calculations for vacancy rates rangin g from 7 to 0% (or 93 to 100% occupancy) and discount rates of 8, 10, and 12% Table 4 3 PVs of Vacancy Rates @ DR of 8% Vacancy Rate EED SD Net Difference 7% $2,412,179 $2,287,758 $124,421 6% $2,474,704 $2,356,182 $118,522 5% $2,537,230 $2,424,606 $112,624 4% $2,599,756 $2,493,030 $106,726 3% $2,662,281 $2,561,454 $100,827 2% $2,724,807 $2,629,878 $94,929 1% $2,787,332 $2,698,302 $89,030 0% $2,849,858 $2,766,725 $83,133 Table 4 4 PVs of Vacancy Rates @ DR of 10% Vacancy Rate EED SD Net Difference 7% $2,306,386 $2,176,124 $130,262 6% $2,361,612 $2,236,541 $125,071 5% $2,416,838 $2,296,958 $119,880 4% $2,472,064 $2,357,375 $114,689 3% $2,527,289 $2,417,793 $109,496 2% $2,582,515 $2,478,210 $104,305 1% $2,637,741 $2,538,627 $99,114 0% $2,692,967 $2,599,044 $93,923

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46 Table 4 5 PVs of Vacancy Rates @ DR of 12% Vacancy Rate EED SD Net Difference 7% $2,213,362 $2,079,250 $134,112 6% $2,262,531 $2,133,025 $129,506 5% $2,311,699 $2,186,800 $124,899 4% $2,360,868 $2,240,575 $120,293 3% $2,410,036 $2,294,350 $115,686 2% $2,459,204 $2,348,125 $111,079 1% $2,508,373 $2,401,900 $106,473 0% $2,557,541 $2,455,675 $101,866 Electricity Inflation The second sensitivity focused on changes in the inflation rate of electricity costs. More specifically, the intent was to evaluate the impact of declining electricity costs on the net outcome of the two projects. As one might expect, the net positive value in the Energy Efficient Development increased as electricity inflation or overall operating costs decreased. When comparing inflation rates of 0 and 3% for the Energy Efficient Development along with a discount rate of 8%, this resulted in a net gain of $87, 197 ($2,499,377 less $2,412,179). Conversely, when comparing the net difference in the PVs of the two projects, we also see that the value add at all three discount rates increased at a decreasing rate as inflation decreased. Table 4 6 PVs of Electricit y Inflation @ DR of 8% Inflation Rate EED SD Net Difference 3% $2,412,179 $2,287,758 $124,421 2% $2,443,540 $2,287,758 $155,782 1% $2,472,542 $2,287,758 $184,784 0% $2,499,377 $2,287,758 $211,619 Table 4 7 PVs of Electricity Inflation @ DR of 10% Inflation Rate EED SD Net Difference 3% $2,306,386 $2,176,124 $130,262 2% $2,332,529 $2,176,124 $156,405 1% $2,356,761 $2,176,124 $180,637 0% $2,379,235 $2,176,124 $203,111

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47 Table 4 8 PVs of Electricity Inflation @ DR of 12% Inflation Rate EED SD Net Difference 3% $2,213,362 $2,079,250 $134,112 2% $2,235,319 $2,079,250 $156,069 1% $2,255,717 $2,079,250 $176,467 0% $2,274,680 $2,079,250 $195,430 Low E Cost Premium The third sensitivity examined the impact of cost overruns to the Energy Efficient Development as they relate to low E cost upgrades. The cost overruns shown in the tables below step up in increments of 10% and collectively range from a 0% to 30%. The resu lts indicate that even if costs were to increase by as much as 30%, there is a minimal or immaterial effect on the net positive value of the Energy Efficient Development. This is true given that for each marginal increase in project costs, developer fee in creases as well Moreover, as project basis increases, the amount of LIHTCs allocated to the project increase s as well. These additional tax credits, when subsequently sold, will in part offset cost overruns In addition, the portion of cost overruns that must be financed with debt will benefit from the advantageous 30 year amortization terms that are commonplace with affordable housing projects. In effect, the combinations of these factors serve to minimize residual valu e. Table 4 9 PVs of Low E Cost Premium @ DR of 8% Low E EED SD Net Difference $144,000 $2,412,179 $2,287,758 $124,421 $158,400 $2,412,608 $2,287,758 $124,850 $172,800 $2,413,037 $2,287,758 $125,279 $187,200 $2,413,466 $2,287,758 $125,708

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48 Table 4 10 PVs of Low E Cost Premium @ DR of 10% Low E EED SD Net Difference $144,000 $2,306,386 $2,176,124 $130,262 $158,400 $2,306,966 $2,176,124 $130,842 $172,800 $2,307,546 $2,176,124 $131,422 $187,200 $2,308,126 $2,176,124 $132,002 Table 4 1 1 PVs of Low E Cost Premium @ DR of 12% Low E EED SD Net Difference $144,000 $2,213,362 $2,079,250 $134,112 $158,400 $2,214,063 $2,079,250 $134,813 $172,800 $2,214,764 $2,079,250 $135,514 $187,200 $2,215,465 $2,079,250 $136,215 Energy Load Reductions The fourth and final sensitivity examined what the effect would be if energy reductions were lower than anticipated. Of the various stress scenarios conducted, this sensitivity proved most detrimental to the positive outcome of the Energy Efficient Develop ment. T he tables below show that with energy load reductions of 20% along with a discount rate of 8% the Energy E fficient Development resulted in a net negative PV of $23,555 As the discount rate increased, however, the point at which the Energy Efficie nt Development turned net negative became more elastic. For example, at a discount rate and energy load reduction of 10 and 20%, the net difference was plus $20. Conversely, at a discount rate and energy load reduction of 12 and 20%, the net difference in PVs was plus $18,543. Last, when considering discount rates of 10 and 12% with an energy load reduction of 15%, the net difference in PVs are negative $43,394 and $19,980 respectively.

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49 Table 4 1 2 PVs of Energy Load Reductions @ DR of 8% % Decrease EED SD Net Difference 35% $2,412,179 $2,287,758 $124,421 30% $2,362,854 $2,287,758 $75,096 25% $2,313,529 $2,287,758 $25,771 20% $2,264,203 $2,287,758 ($23,555) 15% $2,214,878 $2,287,758 ($72,880) Table 4 1 3 PVs of Energy Load Reductions @ DR of 10% % Decrease EED SD Net Difference 35% $2,306,386 $2,176,124 $130,262 30% $2,262,972 $2,176,124 $86,848 25% $2,219,558 $2,176,124 $43,434 20% $2,176,144 $2,176,124 $20 15% $2,132,730 $2,176,124 ($43,394) Table 4 1 4 PVs of Energy Load Reductions @ DR of 12% % Decrease EED SD Net Difference 35% $2,213,362 $2,079,250 $134,112 30% $2,174,839 $2,079,250 $95,589 25% $2,136,316 $2,079,250 $57,066 20% $2,097,793 $2,079,250 $18,543 15% $2,059,270 $2,079,250 ($19,980) Benefit to Tenants The motivation for the analysis was to find a way to relieve low income tenants of their burdensome electricity bil ls. In the case of this study the benefit to tenants is not a question of incremental value or b enefits. In fact, it is an all or nothing proposition given that a prospective owner will either pursue the investment or not. Based on the results of the first iteration, the answer is likely no, thereby passing along zero benefits to tenants In the case of the second iteration, whereby the energy buy back rate was modified per the 2012 rate, we found the project generated sufficient cash flow to meet all of its expenses and debt obligations, as well as to provide residual value over and above that of the Standard Development. Although individual investors may disagree as

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50 to the appropriateness of the risk investor would consider taking on the project. In keeping with the results of the second iterat ion, t he benefit to tenants is equal to the electricity bill for which the owner is willing to pay on their behalf. More specifically, it would be the electricity bill that coincides with the Standard as opposed to the Energy Efficient Development. This is so because under normal circumstances the Owner is not properly incentivized to include energy efficiency upgrades in a typical development. Therefore, the value proposition for which a tenant faces with regard to electricity expenses should be consistent with that of the Standard Development. Accordingly, the estimated electricity bill for the Standard Development is $75 per unit per month, which equates to a monthly gross househo ld rental savings of 21% ($168 divided by $787 ).

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51 CHAPTER 5 AREAS FOR FUTURE RESEARCH The research conducted provides insight as to the financial feasibility of include monetizing or quantifying the impact of leases being terminated prematurel y due to accumulate, this leads to tenants skipping out on their leases sooner than anticipated. Not only is the forgoing detrimental to tenants, but also to Ow ners as well. Some of the adverse impacts include loss of rent, refurbishing units more frequently than anticipated, and legal and administrative fees associated with the actual evictions. At the moment research in this area i s sparse to nonexistent and th ere is a two fold value in learning more about this topic. First, from a public policy standpoint it is difficult to fix problems that can no t be measured. Competition for resources is fierce in the public sphere. For housing policy advocates, understandin ed by electricity bills is vital as this allows for well measured policy recommendations. Second, from the standpoint of a project owner, fewer tenant eviction s translate s into higher returns for all the reaso ns listed above. The question remains, how much of a savings? Should the savings be material, it is conceivable this could incentivize project owners to take a second look at the cost and benefit relationship associated with implementing energy efficiency upgrades.

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52 APPENDIX A NOVOGRASAC & COMPANY LLP RENT & INCOME LIMIT CALCULATOR

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53

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54

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55

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56 APPENDIX B UTILITY ALLOWANCE SCHEDULE 2BR

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57

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58 APPENDIX C SOLAR PANEL SPECIFICATIONS

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59

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60 APPENDIX D SOLAR ENERGY INCOME * AC Energy & Cost Savings Station Identification City: Jacksonville State: Florida Latitude: 30.50 N Longitude: 81.70 W Elevation: 9 m PV System Specifications DC Rating: 371.7 kW DC to AC Derate Factor: 0.875 AC Rating: 325.2 kW Array Type: Fixed Tilt Array Tilt: 14.0 Array Azimuth: 180.0 Energy Specifications Cost of Electricity: 18.0 ¢/kWh Results Month Solar Radiation (kWh/m 2 /day) AC Energy (kWh) Energy Value ($) 1 3.70 35561 6400.98 2 3.95 34112 6140.16 3 5.17 48849 8792.82 4 6.19 55264 9947.52 5 6.22 55504 9990.72 6 5.97 51289 9232.02 7 5.84 51702 9306.36 8 5.56 49489 8908.02 9 5.04 43942 7909.56 10 4.45 40710 7327.80 11 3.93 35289 6352.02 12 3.23 30760 5536.80 Year 4.94 532470 95844.60

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61 * AC Energy & Cost Savings Station Identification City: Jacksonville State: Florida Latitude: 30.50 N Longitude: 81.70 W Elevation: 9 m PV System Specifications DC Rating: 371.7 kW DC to AC Derate Factor: 0.875 AC Rating: 325.2 kW Array Type: Fixed Tilt Array Tilt: 14.0 Array Azimuth: 180.0 Energy Specifications Cost of Electricity: 24.0 ¢/kWh Results Month Solar Radiation (kWh/m 2 /day) AC Energy (kWh) Energy Value ($) 1 3.70 35561 8534.64 2 3.95 34112 8186.88 3 5.17 48849 11723.76 4 6.19 55264 13263.36 5 6.22 55504 13320.96 6 5.97 51289 12309.36 7 5.84 51702 12408.48 8 5.56 49489 11877.36 9 5.04 43942 10546.08 10 4.45 40710 9770.40 11 3.93 35289 8469.36 12 3.23 30760 7382.40 Year 4.94 532470 127792.80

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62 APPENDIX E STANDARD DEVELOPMENT 15 YEAR PRO FORMA

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63

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64 APPENDIX F ENERGY EFFICIENT DEVELOPMENT 15 YEAR PRO FORMA WITH BUY BACK RATE OF $0.18/ KWH

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65

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66 APPENDIX G ENERGY EFFICIENT DEVELOPMENT 15 YEAR PRO FORMA WITH BUY BACK RATE OF $0.24/ KWH

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67

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68 APPENDIX H 2008 10 ENERGY USE DATA FOR GAINESVILLE LIHTC PROJECT Usage Value Year Month Duration Daily Use Premise Unit 0 2010 08 11 0.000 APT 186 0 2009 12 1 0.000 APT 231 0 2009 03 19 0.000 APT 244 0 2008 10 22 0.000 APT 346 0 2008 11 15 0.000 APT 346 0 2008 09 4 0.000 APT 395 0 2008 05 8 0.000 APT 396 7 2009 05 29 0.241 APT 244 14 2009 02 29 0.483 APT 244 6 2010 05 8 0.750 APT 229 35 2009 04 23 1.522 APT 244 14 2010 08 9 1.556 APT 280 13 2009 10 8 1.625 APT 231 22 2009 03 12 1.833 APT 290 63 2009 01 29 2.172 APT 244 67 2010 10 29 2.310 APT 348 82 2010 09 32 2.563 APT 348 78 2010 08 30 2.600 APT 229 81 2010 08 30 2.700 APT 393 73 2010 04 26 2.808 APT 396 31 2008 03 11 2.818 APT 188 100 2008 12 35 2.857 APT 280 78 2010 06 27 2.889 APT 229 87 2010 08 30 2.900 APT 348 86 2009 05 29 2.966 APT 383 6 2010 07 2 3.000 APT 393 91 2010 04 30 3.033 APT 229 38 2009 11 12 3.167 APT 231 91 2010 11 28 3.250 APT 279 90 2008 11 27 3.333 APT 394 52 2010 12 15 3.467 APT 244 52 2008 05 15 3.467 APT 384 104 2010 01 29 3.586 APT 244 76 2010 02 21 3.619 APT 280 128 2009 12 35 3.657 APT 244 74 2010 11 20 3.700 APT 244 26 2010 02 7 3.714 APT 280 26 2008 08 7 3.714 APT 393 38 2008 10 10 3.800 APT 244

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69 Usage Value Year Month Duration Daily Use Premise Unit 96 2010 03 25 3.840 APT 394 66 2009 03 17 3.882 APT 290 79 2009 07 20 3.950 APT 291 129 2009 04 32 4.031 APT 290 37 2009 11 9 4.111 APT 140 29 2010 11 7 4.143 APT 348 112 2010 11 26 4.308 APT 231 35 2008 05 8 4.375 APT 381 124 2010 11 28 4.429 APT 292 130 2010 10 29 4.483 APT 292 131 2010 10 29 4.517 APT 244 158 2010 12 34 4.647 APT 393 168 2008 12 36 4.667 APT 244 140 2010 04 30 4.667 APT 292 132 2010 05 28 4.714 APT 396 128 2009 11 27 4.741 APT 292 38 2009 10 8 4.750 APT 140 139 2009 05 29 4.793 APT 292 154 2009 04 32 4.813 APT 292 140 2010 10 29 4.828 APT 188 34 2010 10 7 4.857 APT 231 157 2010 09 32 4.906 APT 292 167 2009 12 34 4.912 APT 231 163 2010 03 33 4.939 APT 244 35 2010 05 7 5.000 APT 278 10 2008 10 2 5.000 APT 280 131 2008 11 26 5.038 APT 244 142 2010 05 28 5.071 APT 292 153 2009 10 30 5.100 APT 292 148 2010 10 29 5.103 APT 279 169 2010 03 33 5.121 APT 292 155 2008 03 30 5.167 APT 292 172 2009 07 33 5.212 APT 292 157 2010 08 30 5.233 APT 292 184 2008 12 35 5.257 APT 292 159 2008 05 30 5.300 APT 188 122 2008 10 23 5.304 APT 244 154 2009 08 29 5.310 APT 292 160 2009 06 30 5.333 APT 292 173 2009 09 32 5.406 APT 292 157 2009 03 29 5.414 APT 292

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70 Usage Value Year Month Duration Daily Use Premise Unit 76 2010 01 14 5.429 APT 278 180 2010 06 33 5.455 APT 292 131 2010 11 24 5.458 APT 383 143 2008 11 26 5.500 APT 292 171 2008 04 31 5.516 APT 292 162 2008 06 29 5.586 APT 292 169 2010 07 30 5.633 APT 292 170 2009 01 30 5.667 APT 292 165 2008 02 29 5.690 APT 292 75 2009 04 13 5.769 APT 333 162 2010 02 28 5.786 APT 292 174 2008 05 30 5.800 APT 292 203 2009 12 35 5.800 APT 292 195 2008 10 33 5.909 APT 394 196 2008 07 33 5.939 APT 292 167 2010 11 28 5.964 APT 393 175 2010 01 29 6.034 APT 292 186 2008 08 30 6.200 APT 292 185 2009 08 29 6.379 APT 242 188 2009 02 29 6.483 APT 292 13 2009 10 2 6.500 APT 333 222 2010 12 34 6.529 APT 292 219 2008 01 33 6.636 APT 292 221 2008 10 33 6.697 APT 292 204 2010 07 30 6.800 APT 244 220 2009 09 32 6.875 APT 244 159 2009 04 23 6.913 APT 383 90 2009 11 13 6.923 APT 188 182 2008 11 26 7.000 APT 280 14 2008 02 2 7.000 APT 382 228 2010 09 32 7.125 APT 188 50 2008 08 7 7.143 APT 280 129 2008 10 18 7.167 APT 280 208 2008 09 29 7.172 APT 292 203 2010 02 28 7.250 APT 244 204 2009 09 28 7.286 APT 278 240 2010 09 32 7.500 APT 186 83 2008 10 11 7.545 APT 279 227 2008 08 30 7.567 APT 127 206 2009 11 27 7.630 APT 244 232 2009 06 30 7.733 APT 244

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71 Usage Value Year Month Duration Daily Use Premise Unit 210 2009 11 27 7.778 APT 278 282 2008 12 35 8.057 APT 335 178 2010 09 22 8.091 APT 279 268 2009 07 33 8.121 APT 242 236 2008 09 29 8.138 APT 127 270 2009 05 33 8.182 APT 279 272 2010 10 33 8.242 APT 186 249 2010 08 30 8.300 APT 244 34 2008 03 4 8.500 APT 188 258 2009 10 30 8.600 APT 278 43 2009 03 5 8.600 APT 279 165 2009 04 19 8.684 APT 333 261 2009 10 30 8.700 APT 244 296 2010 12 34 8.706 APT 383 262 2010 04 30 8.733 APT 278 151 2010 04 17 8.882 APT 394 89 2010 09 10 8.900 APT 279 232 2010 03 26 8.923 APT 242 282 2008 04 31 9.097 APT 188 302 2010 06 33 9.152 APT 188 213 2008 01 23 9.261 APT 382 158 2009 03 17 9.294 APT 279 270 2008 06 29 9.310 APT 384 205 2008 03 22 9.318 APT 383 299 2009 09 32 9.344 APT 242 310 2010 10 33 9.394 APT 383 264 2010 11 28 9.429 APT 188 95 2008 01 10 9.500 APT 382 277 2008 06 29 9.552 APT 244 258 2008 02 27 9.556 APT 382 29 2009 03 3 9.667 APT 127 107 2008 10 11 9.727 APT 346 265 2009 11 27 9.815 APT 127 296 2009 01 30 9.867 APT 280 322 2009 04 32 10.063 APT 279 303 2008 05 30 10.100 APT 244 334 2009 08 33 10.121 APT 278 71 2010 05 7 10.143 APT 278 297 2008 02 29 10.241 APT 395 313 2009 01 30 10.433 APT 335 126 2009 02 12 10.500 APT 335

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72 Usage Value Year Month Duration Daily Use Premise Unit 305 2008 02 29 10.517 APT 346 32 2009 03 3 10.667 APT 229 363 2010 12 34 10.676 APT 188 171 2008 09 16 10.688 APT 394 139 2010 04 13 10.692 APT 394 322 2008 03 30 10.733 APT 395 333 2008 04 31 10.742 APT 346 312 2010 10 29 10.759 APT 384 226 2008 07 21 10.762 APT 188 281 2008 04 26 10.808 APT 383 433 2010 01 40 10.825 APT 140 304 2010 11 28 10.857 APT 384 326 2010 07 30 10.867 APT 229 327 2009 12 30 10.900 APT 278 338 2008 04 31 10.903 APT 393 22 2010 11 2 11.000 APT 231 332 2010 08 30 11.067 APT 188 246 2010 10 22 11.182 APT 231 347 2008 04 31 11.194 APT 244 370 2010 06 33 11.212 APT 244 351 2008 04 31 11.323 APT 395 352 2008 04 31 11.355 APT 127 378 2010 03 33 11.455 APT 290 344 2008 03 30 11.467 APT 346 335 2010 10 29 11.552 APT 394 81 2009 07 7 11.571 APT 278 349 2010 04 30 11.633 APT 384 82 2008 03 7 11.714 APT 231 341 2009 03 29 11.759 APT 381 59 2008 04 5 11.800 APT 383 356 2010 04 30 11.867 APT 244 309 2008 11 26 11.885 APT 127 393 2008 07 33 11.909 APT 244 311 2008 11 26 11.962 APT 381 396 2010 03 33 12.000 APT 278 350 2008 02 29 12.069 APT 244 350 2010 10 29 12.069 APT 278 340 2010 11 28 12.143 APT 278 401 2010 06 33 12.152 APT 396 366 2008 05 30 12.200 APT 346 232 2008 03 19 12.211 APT 384

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73 Usage Value Year Month Duration Daily Use Premise Unit 405 2009 07 33 12.273 APT 244 320 2008 11 26 12.308 APT 396 361 2010 10 29 12.448 APT 290 263 2010 06 21 12.524 APT 291 379 2010 07 30 12.633 APT 348 417 2008 10 33 12.636 APT 396 380 2008 03 30 12.667 APT 244 408 2009 09 32 12.750 APT 229 370 2009 08 29 12.759 APT 244 294 2009 08 23 12.783 APT 333 358 2010 11 28 12.786 APT 394 283 2009 04 22 12.864 APT 229 389 2010 04 30 12.967 APT 291 273 2010 08 21 13.000 APT 280 391 2010 08 30 13.033 APT 383 393 2008 03 30 13.100 APT 127 211 2009 06 16 13.188 APT 188 132 2008 04 10 13.200 APT 125 396 2010 08 30 13.200 APT 291 226 2009 06 17 13.294 APT 229 469 2009 12 35 13.400 APT 280 149 2010 09 11 13.545 APT 229 434 2010 09 32 13.563 APT 383 327 2010 11 24 13.625 APT 186 398 2008 09 29 13.724 APT 244 386 2009 07 28 13.786 APT 393 194 2009 03 14 13.857 APT 127 291 2010 11 21 13.857 APT 348 487 2008 12 35 13.914 APT 384 390 2010 05 28 13.929 APT 244 460 2009 07 33 13.939 APT 229 489 2008 12 35 13.971 APT 381 451 2009 04 32 14.094 APT 381 141 2008 04 10 14.100 APT 396 395 2010 05 28 14.107 APT 384 413 2008 02 29 14.241 APT 393 429 2009 10 30 14.300 APT 242 474 2010 03 33 14.364 APT 127 173 2009 03 12 14.417 APT 127 463 2009 04 32 14.469 APT 127 420 2008 02 29 14.483 APT 394

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74 Usage Value Year Month Duration Daily Use Premise Unit 466 2009 04 32 14.563 APT 396 426 2009 08 29 14.690 APT 229 485 2008 10 33 14.697 APT 384 487 2008 01 33 14.758 APT 395 489 2008 07 33 14.818 APT 384 416 2010 02 28 14.857 APT 127 477 2009 04 32 14.906 APT 384 495 2008 10 33 15.000 APT 127 495 2008 01 33 15.000 APT 188 240 2010 07 16 15.000 APT 396 498 2010 03 33 15.091 APT 229 166 2009 06 11 15.091 APT 383 453 2008 03 30 15.100 APT 382 438 2009 08 29 15.103 APT 127 469 2008 04 31 15.129 APT 382 454 2008 05 30 15.133 APT 395 455 2010 07 30 15.167 APT 278 440 2009 03 29 15.172 APT 396 501 2008 10 33 15.182 APT 291 458 2008 08 30 15.267 APT 244 458 2010 08 30 15.267 APT 278 306 2010 04 20 15.300 APT 242 123 2009 06 8 15.375 APT 188 492 2010 09 32 15.375 APT 393 448 2009 10 29 15.448 APT 229 541 2008 12 35 15.457 APT 127 434 2010 11 28 15.500 APT 290 93 2008 09 6 15.500 APT 395 515 2008 01 33 15.606 APT 346 110 2009 11 7 15.714 APT 188 504 2010 09 32 15.750 APT 384 473 2010 04 30 15.767 APT 290 474 2010 04 30 15.800 APT 127 237 2008 03 15 15.800 APT 231 522 2008 10 33 15.818 APT 333 459 2008 06 29 15.828 APT 127 475 2009 06 30 15.833 APT 242 523 2008 07 33 15.848 APT 127 478 2008 08 30 15.933 APT 346 463 2008 09 29 15.966 APT 346 528 2010 07 33 16.000 APT 383

PAGE 75

75 Usage Value Year Month Duration Daily Use Premise Unit 465 2008 02 29 16.034 APT 188 519 2010 06 32 16.219 APT 278 472 2008 06 29 16.276 APT 346 326 2009 10 20 16.300 APT 188 538 2010 03 33 16.303 APT 384 49 2009 03 3 16.333 APT 333 490 2009 01 30 16.333 APT 381 180 2008 06 11 16.364 APT 125 543 2010 06 33 16.455 APT 290 445 2009 11 27 16.481 APT 394 479 2009 03 29 16.517 APT 384 349 2009 05 21 16.619 APT 290 483 2010 10 29 16.655 APT 393 500 2008 03 30 16.667 APT 229 550 2008 07 33 16.667 APT 346 468 2009 08 28 16.714 APT 393 502 2010 07 30 16.733 APT 291 504 2008 05 30 16.800 APT 393 488 2008 02 29 16.828 APT 229 472 2010 02 28 16.857 APT 278 524 2008 04 31 16.903 APT 381 510 2008 05 30 17.000 APT 127 255 2008 05 15 17.000 APT 384 494 2009 02 29 17.034 APT 127 480 2008 04 28 17.143 APT 335 499 2009 05 29 17.207 APT 127 517 2008 08 30 17.233 APT 384 552 2009 04 32 17.250 APT 393 508 2009 02 29 17.517 APT 381 492 2010 05 28 17.571 APT 290 651 2010 04 37 17.595 APT 396 528 2008 08 30 17.600 APT 242 405 2009 03 23 17.609 APT 280 495 2010 05 28 17.679 APT 394 553 2008 04 31 17.839 APT 242 518 2010 10 29 17.862 APT 242 536 2008 08 30 17.867 APT 395 468 2008 11 26 18.000 APT 291 506 2010 11 28 18.071 APT 127 580 2010 09 32 18.125 APT 278 601 2008 01 33 18.212 APT 244

PAGE 76

76 Usage Value Year Month Duration Daily Use Premise Unit 183 2009 04 10 18.300 APT 229 531 2009 02 29 18.310 APT 291 642 2008 12 35 18.343 APT 382 350 2010 12 19 18.421 APT 279 535 2010 10 29 18.448 APT 127 535 2008 06 29 18.448 APT 395 629 2010 12 34 18.500 APT 278 407 2009 07 22 18.500 APT 346 538 2009 03 29 18.552 APT 393 652 2008 12 35 18.629 APT 291 599 2010 09 32 18.719 APT 394 562 2010 07 30 18.733 APT 188 619 2008 01 33 18.758 APT 229 619 2008 07 33 18.758 APT 333 544 2010 10 29 18.759 APT 396 563 2009 10 30 18.767 APT 127 508 2009 11 27 18.815 APT 290 565 2009 01 30 18.833 APT 291 548 2008 09 29 18.897 APT 396 531 2010 05 28 18.964 APT 291 532 2010 11 28 19.000 APT 242 572 2009 06 30 19.067 APT 127 534 2010 11 28 19.071 APT 185 515 2009 11 27 19.074 APT 229 229 2009 06 12 19.083 APT 346 344 2010 03 18 19.111 APT 280 670 2008 12 35 19.143 APT 396 115 2009 07 6 19.167 APT 393 537 2010 11 28 19.179 APT 289 558 2009 02 29 19.241 APT 384 616 2009 09 32 19.250 APT 231 560 2009 02 29 19.310 APT 290 271 2010 07 14 19.357 APT 396 562 2009 05 29 19.379 APT 384 640 2008 01 33 19.394 APT 280 566 2009 03 29 19.517 APT 242 586 2010 08 30 19.533 APT 384 196 2010 04 10 19.600 APT 242 510 2008 11 26 19.615 APT 382 628 2010 09 32 19.625 APT 231 157 2010 03 8 19.625 APT 394

PAGE 77

77 Usage Value Year Month Duration Daily Use Premise Unit 532 2009 11 27 19.704 APT 242 594 2008 03 30 19.800 APT 393 614 2008 04 31 19.806 APT 384 555 2010 05 28 19.821 APT 127 595 2008 03 30 19.833 APT 394 615 2008 04 31 19.839 APT 185 596 2009 01 30 19.867 APT 127 696 2009 12 35 19.886 APT 289 577 2008 02 29 19.897 APT 127 637 2010 09 32 19.906 APT 280 639 2009 04 32 19.969 APT 348 660 2008 07 33 20.000 APT 395 661 2008 01 33 20.030 APT 127 642 2009 09 32 20.063 APT 333 602 2008 03 30 20.067 APT 289 583 2010 10 29 20.103 APT 185 664 2008 10 33 20.121 APT 242 605 2010 04 30 20.167 APT 138 121 2009 06 6 20.167 APT 188 586 2008 02 29 20.207 APT 279 710 2009 12 35 20.286 APT 127 609 2008 03 30 20.300 APT 279 691 2010 12 34 20.324 APT 231 610 2008 05 30 20.333 APT 242 610 2008 05 30 20.333 APT 279 610 2010 04 30 20.333 APT 346 591 2008 09 29 20.379 APT 384 592 2008 09 29 20.414 APT 242 572 2010 05 28 20.429 APT 242 409 2008 10 20 20.450 APT 279 533 2008 11 26 20.500 APT 125 574 2010 11 28 20.500 APT 396 719 2009 12 35 20.543 APT 290 144 2009 02 7 20.571 APT 335 679 2009 07 33 20.576 APT 396 660 2009 09 32 20.625 APT 127 725 2008 12 35 20.714 APT 185 622 2009 01 30 20.733 APT 384 623 2010 04 30 20.767 APT 186 603 2009 05 29 20.793 APT 280 603 2008 02 29 20.793 APT 396

PAGE 78

78 Usage Value Year Month Duration Daily Use Premise Unit 604 2009 05 29 20.828 APT 381 690 2008 07 33 20.909 APT 125 607 2009 05 29 20.931 APT 125 628 2008 05 30 20.933 APT 291 650 2008 04 31 20.968 APT 229 609 2008 09 29 21.000 APT 333 609 2009 05 29 21.000 APT 393 695 2008 07 33 21.061 APT 242 569 2009 11 27 21.074 APT 280 721 2009 04 34 21.206 APT 383 615 2009 08 29 21.207 APT 291 680 2010 09 32 21.250 APT 242 638 2008 08 30 21.267 APT 396 553 2008 11 26 21.269 APT 185 298 2008 08 14 21.286 APT 393 724 2010 12 34 21.294 APT 185 619 2009 03 29 21.345 APT 346 619 2010 10 29 21.345 APT 382 641 2009 06 30 21.367 APT 384 620 2008 02 29 21.379 APT 231 620 2009 05 29 21.379 APT 333 642 2010 04 30 21.400 APT 188 642 2009 10 30 21.400 APT 291 643 2008 05 30 21.433 APT 335 752 2008 12 35 21.486 APT 279 172 2009 05 8 21.500 APT 290 624 2009 06 29 21.517 APT 333 646 2009 01 30 21.533 APT 279 690 2009 04 32 21.563 APT 186 626 2009 03 29 21.586 APT 289 281 2008 08 13 21.615 APT 333 627 2010 10 29 21.621 APT 280 649 2008 05 30 21.633 APT 277 671 2008 04 31 21.645 APT 231 260 2010 06 12 21.667 APT 291 586 2009 11 27 21.704 APT 396 391 2008 06 18 21.722 APT 125 719 2008 10 33 21.788 APT 185 632 2009 03 29 21.793 APT 382 720 2010 03 33 21.818 APT 381 568 2008 11 26 21.846 APT 384

PAGE 79

79 Usage Value Year Month Duration Daily Use Premise Unit 636 2009 03 29 21.931 APT 348 702 2009 09 32 21.938 APT 185 746 2010 12 34 21.941 APT 384 615 2009 10 28 21.964 APT 333 703 2010 09 32 21.969 APT 185 638 2009 03 29 22.000 APT 186 662 2008 05 30 22.067 APT 383 133 2009 08 6 22.167 APT 333 665 2008 03 30 22.167 APT 396 711 2009 04 32 22.219 APT 188 667 2008 05 30 22.233 APT 185 669 2010 07 30 22.300 APT 290 580 2009 07 26 22.308 APT 278 781 2008 12 35 22.314 APT 348 625 2010 11 28 22.321 APT 277 760 2008 12 34 22.353 APT 394 761 2010 12 34 22.382 APT 381 650 2009 03 29 22.414 APT 125 785 2009 12 35 22.429 APT 188 673 2010 07 30 22.433 APT 127 673 2009 10 30 22.433 APT 394 763 2010 12 34 22.441 APT 242 741 2009 07 33 22.455 APT 290 741 2010 06 33 22.455 APT 348 652 2008 02 29 22.483 APT 280 659 2009 03 29 22.724 APT 394 750 2008 01 33 22.727 APT 396 683 2010 08 30 22.767 APT 127 754 2008 07 33 22.848 APT 185 663 2009 03 29 22.862 APT 140 801 2008 12 35 22.886 APT 125 665 2009 08 29 22.931 APT 290 690 2008 08 30 23.000 APT 125 621 2009 11 27 23.000 APT 138 621 2009 06 27 23.000 APT 291 253 2009 07 11 23.000 APT 346 759 2008 10 33 23.000 APT 382 760 2009 07 33 23.030 APT 384 691 2008 05 30 23.033 APT 229 807 2009 12 35 23.057 APT 394 740 2009 09 32 23.125 APT 290

PAGE 80

80 Usage Value Year Month Duration Daily Use Premise Unit 765 2008 03 33 23.182 APT 335 673 2009 05 29 23.207 APT 277 651 2010 02 28 23.250 APT 290 628 2009 11 27 23.259 APT 291 607 2008 11 26 23.346 APT 335 655 2010 11 28 23.393 APT 138 679 2008 06 29 23.414 APT 188 703 2008 03 30 23.433 APT 381 774 2009 07 33 23.455 APT 289 704 2009 06 30 23.467 APT 290 705 2009 01 30 23.500 APT 382 729 2008 04 31 23.516 APT 289 659 2010 02 28 23.536 APT 346 778 2010 03 33 23.576 APT 289 731 2008 04 31 23.581 APT 333 685 2009 03 29 23.621 APT 188 756 2010 09 32 23.625 APT 290 662 2010 05 28 23.643 APT 188 710 2008 03 30 23.667 APT 242 714 2009 01 30 23.800 APT 396 691 2009 05 29 23.828 APT 242 668 2010 02 28 23.857 APT 381 835 2008 12 35 23.857 APT 383 454 2010 05 19 23.895 APT 348 789 2009 07 33 23.909 APT 185 742 2008 04 31 23.935 APT 279 696 2009 08 29 24.000 APT 185 672 2010 05 28 24.000 APT 231 720 2008 08 30 24.000 APT 279 817 2010 09 34 24.029 APT 291 529 2010 08 22 24.045 APT 231 722 2010 04 30 24.067 APT 289 723 2009 10 30 24.100 APT 290 699 2009 05 29 24.103 APT 140 699 2009 05 29 24.103 APT 291 699 2008 02 29 24.103 APT 335 796 2008 10 33 24.121 APT 277 797 2008 10 33 24.152 APT 348 773 2009 04 32 24.156 APT 138 725 2010 04 30 24.167 APT 231 798 2008 01 33 24.182 APT 231

PAGE 81

81 Usage Value Year Month Duration Daily Use Premise Unit 847 2009 12 35 24.200 APT 229 726 2009 10 30 24.200 APT 396 678 2010 11 28 24.214 APT 291 630 2008 11 26 24.231 APT 333 800 2010 03 33 24.242 APT 231 679 2010 11 28 24.250 APT 382 801 2010 06 33 24.273 APT 394 170 2008 03 7 24.286 APT 231 778 2009 04 32 24.313 APT 185 803 2010 06 33 24.333 APT 242 852 2009 12 35 24.343 APT 346 731 2008 05 30 24.367 APT 231 782 2009 04 32 24.438 APT 125 709 2009 03 29 24.448 APT 185 709 2009 05 29 24.448 APT 396 662 2009 11 27 24.519 APT 185 737 2010 08 30 24.567 APT 242 664 2009 11 27 24.593 APT 186 787 2009 04 32 24.594 APT 242 812 2008 07 33 24.606 APT 279 714 2010 10 29 24.621 APT 138 813 2008 01 33 24.636 APT 279 864 2009 12 35 24.686 APT 384 790 2009 04 32 24.688 APT 291 667 2009 11 27 24.704 APT 384 668 2009 11 27 24.741 APT 395 718 2009 05 29 24.759 APT 188 743 2008 08 30 24.767 APT 140 795 2009 04 32 24.844 APT 289 721 2010 10 29 24.862 APT 289 746 2009 06 30 24.867 APT 393 821 2008 10 33 24.879 APT 125 871 2008 12 35 24.886 APT 346 747 2009 01 30 24.900 APT 125 747 2008 03 30 24.900 APT 280 822 2008 01 33 24.909 APT 187 25 2009 09 1 25.000 APT 229 650 2008 11 26 25.000 APT 383 727 2008 02 29 25.069 APT 242 702 2010 02 28 25.071 APT 289 878 2008 12 35 25.086 APT 289

PAGE 82

82 Usage Value Year Month Duration Daily Use Premise Unit 728 2008 02 29 25.103 APT 333 529 2008 04 21 25.190 APT 396 656 2008 11 26 25.231 APT 242 556 2010 10 22 25.273 APT 346 835 2008 07 33 25.303 APT 393 658 2008 11 26 25.308 APT 279 734 2008 06 29 25.310 APT 229 735 2009 05 29 25.345 APT 185 737 2008 06 29 25.414 APT 393 890 2008 12 35 25.429 APT 333 738 2009 08 29 25.448 APT 140 738 2009 02 29 25.448 APT 346 815 2010 09 32 25.469 APT 127 841 2008 01 33 25.485 APT 291 841 2008 07 33 25.485 APT 396 765 2010 04 30 25.500 APT 277 740 2009 02 29 25.517 APT 289 740 2009 05 29 25.517 APT 348 741 2008 02 29 25.552 APT 138 741 2009 02 29 25.552 APT 382 690 2009 11 27 25.556 APT 346 820 2009 09 32 25.625 APT 384 795 2008 04 31 25.645 APT 348 667 2008 11 26 25.654 APT 289 822 2009 09 32 25.688 APT 291 849 2008 07 33 25.727 APT 277 748 2009 05 29 25.793 APT 186 774 2009 06 30 25.800 APT 125 749 2009 02 29 25.828 APT 185 905 2008 12 35 25.857 APT 277 854 2008 10 33 25.879 APT 229 777 2010 07 30 25.900 APT 242 829 2009 04 32 25.906 APT 394 701 2010 10 27 25.963 APT 291 728 2010 11 28 26.000 APT 125 806 2008 04 31 26.000 APT 280 52 2008 08 2 26.000 APT 280 755 2009 08 29 26.034 APT 384 834 2010 09 32 26.063 APT 396 756 2010 01 29 26.069 APT 231 783 2009 01 30 26.100 APT 185

PAGE 83

83 Usage Value Year Month Duration Daily Use Premise Unit 758 2008 06 29 26.138 APT 185 837 2009 04 32 26.156 APT 277 786 2010 04 30 26.200 APT 125 734 2010 11 28 26.214 APT 229 682 2008 11 26 26.231 APT 138 341 2009 07 13 26.231 APT 291 761 2008 06 29 26.241 APT 279 919 2008 12 35 26.257 APT 242 814 2008 04 31 26.258 APT 140 736 2010 02 28 26.286 APT 229 763 2008 09 29 26.310 APT 291 763 2009 02 29 26.310 APT 396 737 2010 11 28 26.321 APT 140 843 2009 04 32 26.344 APT 280 764 2008 06 29 26.345 APT 277 764 2009 03 29 26.345 APT 277 765 2008 02 29 26.379 APT 348 739 2010 02 28 26.393 APT 231 871 2010 03 33 26.394 APT 125 872 2010 06 33 26.424 APT 231 689 2008 11 26 26.500 APT 231 875 2010 03 33 26.515 APT 346 770 2010 10 29 26.552 APT 229 691 2009 06 26 26.577 APT 279 904 2010 12 34 26.588 APT 127 719 2009 11 27 26.630 APT 277 719 2009 11 27 26.630 APT 289 880 2009 07 33 26.667 APT 140 934 2008 12 35 26.686 APT 188 774 2008 02 29 26.690 APT 187 774 2008 09 29 26.690 APT 382 774 2009 02 29 26.690 APT 394 777 2008 09 29 26.793 APT 277 885 2008 10 33 26.818 APT 138 885 2008 07 33 26.818 APT 289 805 2008 08 30 26.833 APT 335 805 2008 03 30 26.833 APT 348 806 2008 03 30 26.867 APT 187 807 2008 03 30 26.900 APT 277 700 2008 11 26 26.923 APT 277 754 2010 05 28 26.929 APT 138

PAGE 84

84 Usage Value Year Month Duration Daily Use Premise Unit 808 2009 10 30 26.933 APT 280 862 2010 09 32 26.938 APT 244 809 2008 08 30 26.967 APT 291 729 2009 11 27 27.000 APT 333 810 2009 01 30 27.000 APT 346 864 2009 09 32 27.000 APT 396 892 2008 07 33 27.030 APT 229 811 2009 06 30 27.033 APT 381 784 2009 05 29 27.034 APT 394 894 2009 07 33 27.091 APT 127 759 2010 02 28 27.107 APT 394 787 2008 09 29 27.138 APT 280 842 2008 08 31 27.161 APT 394 788 2009 05 29 27.172 APT 289 789 2009 03 29 27.207 APT 291 789 2008 09 29 27.207 APT 393 898 2010 03 33 27.212 APT 140 898 2010 03 33 27.212 APT 277 762 2010 02 28 27.214 APT 125 245 2010 11 9 27.222 APT 280 790 2008 02 29 27.241 APT 277 791 2010 01 29 27.276 APT 127 764 2010 11 28 27.286 APT 381 928 2010 12 34 27.294 APT 290 901 2008 10 33 27.303 APT 140 901 2008 10 33 27.303 APT 335 710 2008 11 26 27.308 APT 188 792 2008 02 29 27.310 APT 381 820 2009 10 30 27.333 APT 185 903 2009 07 33 27.364 APT 188 903 2009 07 33 27.364 APT 277 821 2008 03 30 27.367 APT 333 876 2009 04 32 27.375 APT 346 904 2008 10 33 27.394 APT 289 795 2009 05 29 27.414 APT 138 795 2009 02 29 27.414 APT 383 823 2009 01 30 27.433 APT 394 933 2010 12 34 27.441 APT 125 796 2008 09 29 27.448 APT 279 714 2009 03 26 27.462 APT 333 824 2010 04 30 27.467 APT 333

PAGE 85

85 Usage Value Year Month Duration Daily Use Premise Unit 797 2009 08 29 27.483 APT 186 907 2008 01 33 27.485 APT 381 825 2008 05 30 27.500 APT 140 882 2009 09 32 27.563 APT 394 829 2010 07 30 27.633 APT 231 581 2010 09 21 27.667 APT 229 803 2009 03 29 27.690 APT 231 803 2009 03 29 27.690 APT 395 914 2008 10 33 27.697 APT 395 831 2009 06 30 27.700 APT 140 804 2009 03 29 27.724 APT 138 915 2010 06 33 27.727 APT 127 915 2010 03 33 27.727 APT 393 832 2008 03 30 27.733 APT 185 416 2010 03 15 27.733 APT 280 334 2009 06 12 27.833 APT 346 835 2010 07 30 27.833 APT 394 919 2010 03 33 27.848 APT 185 780 2010 02 28 27.857 APT 393 836 2009 10 30 27.867 APT 277 921 2010 06 33 27.909 APT 138 924 2010 06 33 28.000 APT 125 841 2009 10 30 28.033 APT 384 815 2008 02 29 28.103 APT 291 225 2008 08 8 28.125 APT 393 844 2010 04 30 28.133 APT 140 844 2010 07 30 28.133 APT 384 816 2009 02 29 28.138 APT 125 845 2009 06 30 28.167 APT 186 818 2009 02 29 28.207 APT 242 819 2009 02 29 28.241 APT 279 735 2008 11 26 28.269 APT 395 933 2008 01 33 28.273 APT 242 736 2008 11 26 28.308 APT 186 850 2009 06 30 28.333 APT 289 826 2009 02 29 28.483 APT 188 826 2008 06 29 28.483 APT 333 941 2008 10 33 28.515 APT 393 827 2008 09 29 28.517 APT 185 856 2010 08 30 28.533 APT 396 828 2008 06 29 28.552 APT 335

PAGE 86

86 Usage Value Year Month Duration Daily Use Premise Unit 1001 2009 12 35 28.600 APT 186 944 2010 06 33 28.606 APT 185 945 2008 10 33 28.636 APT 383 802 2010 05 28 28.643 APT 125 946 2008 01 33 28.667 APT 393 861 2009 01 30 28.700 APT 277 861 2010 08 30 28.700 APT 394 833 2008 06 29 28.724 APT 396 1006 2009 12 35 28.743 APT 242 863 2010 04 30 28.767 APT 185 863 2009 01 30 28.767 APT 289 950 2010 03 33 28.788 APT 186 838 2009 02 29 28.897 APT 280 867 2008 03 30 28.900 APT 291 899 2008 04 31 29.000 APT 277 870 2008 05 30 29.000 APT 382 1016 2008 12 35 29.029 APT 229 929 2009 04 32 29.031 APT 382 871 2008 08 30 29.033 APT 277 959 2008 01 33 29.061 APT 348 495 2008 08 17 29.118 APT 333 874 2009 10 30 29.133 APT 279 991 2010 12 34 29.147 APT 186 1021 2008 12 35 29.171 APT 231 848 2009 08 29 29.241 APT 381 848 2008 02 29 29.241 APT 384 966 2010 03 33 29.273 APT 291 880 2008 05 30 29.333 APT 186 968 2008 07 33 29.333 APT 383 851 2008 09 29 29.345 APT 125 998 2009 07 34 29.353 APT 333 822 2010 02 28 29.357 APT 384 881 2010 04 30 29.367 APT 382 852 2008 06 29 29.379 APT 242 1030 2008 12 35 29.429 APT 186 884 2008 08 30 29.467 APT 185 974 2010 03 33 29.515 APT 187 856 2009 08 29 29.517 APT 289 887 2009 01 30 29.567 APT 242 858 2008 06 29 29.586 APT 394 888 2009 10 30 29.600 APT 289

PAGE 87

87 Usage Value Year Month Duration Daily Use Premise Unit 860 2009 08 29 29.655 APT 277 890 2008 03 30 29.667 APT 138 861 2008 06 29 29.690 APT 383 1010 2010 12 34 29.706 APT 394 863 2010 01 29 29.759 APT 229 984 2008 01 33 29.818 APT 333 865 2008 06 29 29.828 APT 291 866 2010 10 29 29.862 APT 277 896 2009 01 30 29.867 APT 333 329 2008 11 11 29.909 APT 346 987 2008 10 33 29.909 APT 381 838 2010 05 28 29.929 APT 186 868 2008 02 29 29.931 APT 140 899 2009 06 30 29.967 APT 185 899 2008 05 30 29.967 APT 348 1050 2009 12 35 30.000 APT 395 901 2009 10 30 30.033 APT 395 903 2010 08 30 30.100 APT 125 905 2009 01 30 30.167 APT 383 997 2009 07 33 30.212 APT 186 846 2010 05 28 30.214 APT 289 787 2008 11 26 30.269 APT 140 909 2008 05 30 30.300 APT 333 880 2009 08 29 30.345 APT 394 850 2009 08 28 30.357 APT 231 820 2009 11 27 30.370 APT 125 243 2010 08 8 30.375 APT 231 1005 2010 03 33 30.455 APT 333 1068 2008 12 35 30.514 APT 138 979 2010 09 32 30.594 APT 289 888 2009 05 29 30.621 APT 346 919 2008 03 30 30.633 APT 140 920 2009 06 30 30.667 APT 280 1075 2009 12 35 30.714 APT 381 1014 2008 01 33 30.727 APT 277 922 2008 08 30 30.733 APT 383 1077 2009 12 35 30.771 APT 138 863 2010 02 28 30.821 APT 187 1079 2009 12 35 30.829 APT 396 925 2009 01 30 30.833 APT 187 896 2009 02 29 30.897 APT 187

PAGE 88

88 Usage Value Year Month Duration Daily Use Premise Unit 990 2009 04 32 30.938 APT 140 1022 2008 01 33 30.970 APT 140 992 2009 04 32 31.000 APT 231 1024 2008 01 33 31.030 APT 335 931 2010 04 30 31.033 APT 393 869 2010 02 28 31.036 APT 396 933 2009 01 30 31.100 APT 188 902 2010 01 29 31.103 APT 187 1089 2008 12 35 31.114 APT 395 935 2009 06 30 31.167 APT 138 935 2010 04 30 31.167 APT 395 1091 2009 12 35 31.171 APT 277 904 2009 03 29 31.172 APT 278 873 2010 02 28 31.179 APT 185 905 2008 02 29 31.207 APT 290 1031 2008 07 33 31.242 APT 138 907 2009 02 29 31.276 APT 333 907 2008 09 29 31.276 APT 348 939 2009 10 30 31.300 APT 138 814 2008 11 26 31.308 APT 187 908 2008 02 29 31.310 APT 289 908 2010 01 29 31.310 APT 381 1097 2009 12 35 31.343 APT 187 627 2008 05 20 31.350 APT 381 1004 2009 09 32 31.375 APT 140 910 2010 01 29 31.379 APT 280 1036 2009 07 33 31.394 APT 381 377 2008 07 12 31.417 APT 188 912 2008 09 29 31.448 APT 383 850 2009 11 27 31.481 APT 187 819 2008 11 26 31.500 APT 229 945 2010 08 30 31.500 APT 277 851 2009 11 27 31.519 APT 348 883 2010 11 28 31.536 APT 395 1041 2010 03 33 31.545 APT 188 947 2008 08 30 31.567 APT 348 1012 2010 09 32 31.625 APT 382 1013 2010 09 32 31.656 APT 277 919 2008 02 29 31.690 APT 186 888 2010 11 28 31.714 APT 346 920 2008 09 29 31.724 APT 186

PAGE 89

89 Usage Value Year Month Duration Daily Use Premise Unit 952 2010 07 30 31.733 APT 186 921 2008 09 29 31.759 APT 138 1080 2010 12 34 31.765 APT 289 1112 2009 12 35 31.771 APT 185 922 2009 03 29 31.793 APT 187 1050 2008 07 33 31.818 APT 394 828 2008 11 26 31.846 APT 393 892 2010 05 28 31.857 APT 277 956 2010 08 30 31.867 APT 185 1052 2010 06 33 31.879 APT 384 957 2009 06 30 31.900 APT 277 1087 2010 12 34 31.971 APT 187 960 2009 10 30 32.000 APT 381 288 2008 03 9 32.000 APT 384 1025 2009 09 32 32.031 APT 381 930 2010 01 29 32.069 APT 346 866 2009 11 27 32.074 APT 381 866 2009 11 27 32.074 APT 383 1092 2010 12 34 32.118 APT 291 1061 2008 10 33 32.152 APT 231 965 2010 08 30 32.167 APT 290 901 2010 11 28 32.179 APT 333 934 2010 01 29 32.207 APT 393 838 2008 11 26 32.231 APT 348 935 2009 02 29 32.241 APT 277 1034 2009 09 32 32.313 APT 289 1067 2008 07 33 32.333 APT 348 1003 2008 04 31 32.355 APT 138 906 2010 11 28 32.357 APT 187 1069 2010 06 33 32.394 APT 280 972 2009 01 30 32.400 APT 231 972 2010 07 30 32.400 APT 333 908 2010 05 28 32.429 APT 346 974 2009 01 30 32.467 APT 348 942 2010 01 29 32.483 APT 290 943 2008 09 29 32.517 APT 335 911 2010 02 28 32.536 APT 140 979 2008 05 30 32.633 APT 289 1077 2010 06 33 32.636 APT 277 1045 2009 09 32 32.656 APT 277 980 2010 08 30 32.667 APT 382

PAGE 90

90 Usage Value Year Month Duration Daily Use Premise Unit 1046 2009 09 32 32.688 APT 393 948 2010 10 29 32.690 APT 125 948 2010 01 29 32.690 APT 185 1079 2008 07 33 32.697 APT 291 949 2008 09 29 32.724 APT 140 949 2010 10 29 32.724 APT 333 982 2008 03 30 32.733 APT 186 1146 2009 12 35 32.743 APT 125 984 2009 01 30 32.800 APT 138 984 2008 08 30 32.800 APT 186 953 2010 10 29 32.862 APT 140 1021 2008 04 31 32.935 APT 291 990 2008 05 30 33.000 APT 138 924 2010 02 28 33.000 APT 277 1092 2008 10 33 33.091 APT 188 894 2009 11 27 33.111 APT 393 1061 2010 09 32 33.156 APT 140 995 2009 06 30 33.167 APT 348 929 2010 05 28 33.179 APT 140 1099 2009 07 33 33.303 APT 125 1066 2009 09 32 33.313 APT 138 1000 2010 07 30 33.333 APT 138 934 2010 05 28 33.357 APT 279 1169 2009 12 35 33.400 APT 348 1036 2008 04 31 33.419 APT 394 1103 2009 07 33 33.424 APT 348 936 2010 02 28 33.429 APT 242 1003 2010 07 30 33.433 APT 125 1006 2010 04 30 33.533 APT 381 302 2010 05 9 33.556 APT 348 1108 2008 10 33 33.576 APT 186 1075 2010 09 32 33.594 APT 333 975 2010 01 29 33.621 APT 125 1110 2008 01 33 33.636 APT 384 944 2010 05 28 33.714 APT 185 978 2010 01 29 33.724 APT 289 978 2009 05 29 33.724 APT 335 978 2010 01 29 33.724 APT 394 1181 2008 12 35 33.743 APT 393 979 2009 02 29 33.759 APT 348 1081 2009 04 32 33.781 APT 278

PAGE 91

91 Usage Value Year Month Duration Daily Use Premise Unit 981 2009 02 29 33.828 APT 231 1186 2008 12 35 33.886 APT 187 1119 2009 07 33 33.909 APT 280 1119 2010 03 33 33.909 APT 395 1120 2008 01 33 33.939 APT 138 1154 2010 12 34 33.941 APT 277 1190 2009 12 35 34.000 APT 393 988 2009 05 29 34.069 APT 231 1091 2009 09 32 34.094 APT 279 1126 2008 01 33 34.121 APT 290 1058 2008 04 31 34.129 APT 187 1024 2008 08 30 34.133 APT 382 990 2008 06 29 34.138 APT 231 994 2009 08 29 34.276 APT 138 1201 2009 12 35 34.314 APT 291 1134 2009 07 33 34.364 APT 138 1203 2009 12 35 34.371 APT 333 1103 2009 09 32 34.469 APT 186 1105 2009 09 32 34.531 APT 188 1036 2008 08 30 34.533 APT 138 1176 2010 12 34 34.588 APT 382 1039 2010 07 30 34.633 APT 185 1040 2009 10 30 34.667 APT 186 1041 2009 10 30 34.700 APT 348 1041 2009 10 30 34.700 APT 383 1007 2008 06 29 34.724 APT 348 1008 2009 08 29 34.759 APT 125 1008 2008 09 29 34.759 APT 231 1148 2008 07 33 34.788 APT 382 1044 2010 08 30 34.800 APT 138 1046 2009 01 30 34.867 APT 393 977 2010 02 28 34.893 APT 188 1047 2009 10 30 34.900 APT 125 1048 2008 05 30 34.933 APT 187 982 2010 02 28 35.071 APT 333 1020 2008 06 29 35.172 APT 186 1020 2009 12 29 35.172 APT 383 1161 2010 06 33 35.182 APT 140 988 2010 05 28 35.286 APT 335 1024 2008 06 29 35.310 APT 138 1130 2009 04 32 35.313 APT 395

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92 Usage Value Year Month Duration Daily Use Premise Unit 1096 2008 04 31 35.355 APT 186 1026 2010 01 29 35.379 APT 384 1066 2009 10 30 35.533 APT 393 1031 2008 06 29 35.552 APT 382 249 2010 03 7 35.571 APT 242 997 2010 05 28 35.607 APT 333 1033 2009 08 29 35.621 APT 279 1069 2010 07 30 35.633 APT 289 1069 2010 08 30 35.633 APT 333 1213 2010 12 34 35.676 APT 333 1071 2009 10 30 35.700 APT 187 1072 2009 01 30 35.733 APT 229 1072 2009 06 30 35.733 APT 394 1180 2010 03 33 35.758 APT 382 1074 2009 06 30 35.800 APT 396 682 2008 09 19 35.895 APT 395 1185 2010 06 33 35.909 APT 289 1043 2009 02 29 35.966 APT 138 1188 2010 03 33 36.000 APT 138 1045 2009 05 29 36.034 APT 229 976 2009 11 27 36.148 APT 279 1231 2010 12 34 36.206 APT 396 978 2008 05 27 36.222 APT 125 1051 2008 02 29 36.241 APT 185 1088 2008 08 30 36.267 APT 231 1197 2008 07 33 36.273 APT 335 1161 2009 09 32 36.281 APT 382 254 2010 10 7 36.286 APT 346 109 2009 06 3 36.333 APT 291 1054 2009 08 29 36.345 APT 348 1091 2009 01 30 36.367 APT 186 1203 2010 03 33 36.455 APT 335 1095 2010 07 30 36.500 APT 280 1096 2008 05 30 36.533 APT 280 1063 2008 09 29 36.655 APT 188 1063 2008 06 29 36.655 APT 289 1100 2009 01 30 36.667 APT 290 1101 2008 03 30 36.700 APT 125 1102 2010 04 30 36.733 APT 187 993 2009 11 27 36.778 APT 335 994 2009 11 27 36.815 APT 382

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93 Usage Value Year Month Duration Daily Use Premise Unit 1068 2008 09 29 36.828 APT 289 1217 2010 03 33 36.879 APT 348 1108 2008 03 30 36.933 APT 290 1184 2009 04 32 37.000 APT 187 1223 2008 07 33 37.061 APT 140 1114 2009 10 30 37.133 APT 382 223 2009 03 6 37.167 APT 280 1079 2009 02 29 37.207 APT 186 1079 2009 05 29 37.207 APT 395 335 2008 08 9 37.222 APT 280 1080 2008 06 29 37.241 APT 381 1192 2009 04 32 37.250 APT 335 1304 2008 12 35 37.257 APT 278 1081 2010 01 29 37.276 APT 396 1119 2008 08 30 37.300 APT 289 1085 2009 08 29 37.414 APT 188 1311 2008 12 35 37.457 APT 140 899 2010 01 24 37.458 APT 140 1049 2010 07 28 37.464 APT 393 1237 2009 07 33 37.485 APT 279 1089 2009 08 29 37.552 APT 396 1277 2010 12 34 37.559 APT 140 1202 2010 09 32 37.563 APT 125 1127 2010 08 30 37.567 APT 279 1127 2009 10 30 37.567 APT 346 1128 2008 08 30 37.600 APT 188 716 2010 08 19 37.684 APT 186 1094 2010 10 29 37.724 APT 335 1132 2010 04 30 37.733 APT 279 1132 2010 04 30 37.733 APT 348 1247 2008 01 33 37.788 APT 186 1247 2010 06 33 37.788 APT 186 1247 2010 06 33 37.788 APT 333 1247 2009 07 33 37.788 APT 394 1096 2008 09 29 37.793 APT 229 1248 2008 07 33 37.818 APT 186 1097 2009 05 29 37.828 APT 382 1135 2009 06 30 37.833 APT 231 1250 2010 06 33 37.879 APT 187 493 2009 09 13 37.923 APT 383 1253 2008 10 33 37.970 APT 187

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94 Usage Value Year Month Duration Daily Use Premise Unit 1103 2010 01 29 38.034 APT 277 1143 2009 06 30 38.100 APT 278 1108 2010 10 29 38.207 APT 395 1340 2008 12 35 38.286 APT 290 1114 2009 02 29 38.414 APT 393 1076 2010 05 28 38.429 APT 393 1115 2008 06 29 38.448 APT 187 1269 2010 06 33 38.455 APT 279 1154 2010 07 30 38.467 APT 277 1119 2010 01 29 38.586 APT 242 1158 2008 08 30 38.600 APT 229 1082 2010 05 28 38.643 APT 280 1243 2009 09 32 38.844 APT 187 1323 2010 12 34 38.912 APT 395 1136 2009 02 29 39.172 APT 140 1293 2008 01 33 39.182 APT 185 1098 2010 02 28 39.214 APT 279 1139 2010 10 29 39.276 APT 187 1102 2010 02 28 39.357 APT 138 1102 2010 02 28 39.357 APT 186 1299 2008 01 33 39.364 APT 125 1104 2010 11 28 39.429 APT 335 1185 2010 07 30 39.500 APT 140 1146 2009 02 29 39.517 APT 278 1268 2009 09 32 39.625 APT 125 1348 2010 12 34 39.647 APT 229 1351 2009 07 34 39.735 APT 231 1153 2009 05 29 39.759 APT 278 1154 2009 05 29 39.793 APT 187 1155 2008 02 29 39.828 APT 278 878 2009 03 22 39.909 APT 229 1238 2008 04 31 39.935 APT 290 1160 2009 03 29 40.000 APT 335 1041 2008 11 26 40.038 APT 290 1122 2010 02 28 40.071 APT 382 1324 2008 10 33 40.121 APT 290 1128 2010 05 28 40.286 APT 395 1330 2008 01 33 40.303 APT 394 1169 2009 08 29 40.310 APT 280 1171 2009 08 29 40.379 APT 382 1333 2008 07 33 40.394 APT 231

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95 Usage Value Year Month Duration Daily Use Premise Unit 1214 2008 05 30 40.467 APT 394 405 2009 02 10 40.500 APT 335 1221 2008 03 30 40.700 APT 278 1222 2010 04 30 40.733 APT 335 937 2009 08 23 40.739 APT 346 1304 2009 09 32 40.750 APT 395 1345 2008 01 33 40.758 APT 289 1225 2010 07 30 40.833 APT 381 1349 2008 10 33 40.879 APT 278 1187 2008 09 29 40.931 APT 290 246 2009 11 6 41.000 APT 383 1191 2008 06 29 41.069 APT 140 1150 2010 05 28 41.071 APT 381 1235 2010 08 30 41.167 APT 289 1319 2009 09 32 41.219 APT 348 1238 2009 01 30 41.267 APT 278 1239 2008 05 30 41.300 APT 290 1199 2008 02 29 41.345 APT 125 1246 2009 01 30 41.533 APT 140 1205 2008 09 29 41.552 APT 187 1209 2010 01 29 41.690 APT 333 1211 2008 09 29 41.759 APT 381 627 2010 12 15 41.800 APT 279 1305 2008 04 31 42.097 APT 278 548 2009 06 13 42.154 APT 229 1265 2010 08 30 42.167 APT 140 1184 2010 02 28 42.286 APT 335 1270 2010 04 30 42.333 APT 280 255 2009 08 6 42.500 APT 346 1193 2010 02 28 42.607 APT 383 1407 2010 06 33 42.636 APT 382 1241 2010 01 29 42.793 APT 382 1455 2010 12 34 42.794 APT 348 1372 2010 09 32 42.875 APT 346 1293 2010 07 30 43.100 APT 382 1208 2010 05 28 43.143 APT 187 1385 2010 09 32 43.281 APT 187 1256 2010 01 29 43.310 APT 279 1431 2010 03 33 43.364 APT 279 1129 2008 11 26 43.423 APT 278 1309 2010 07 30 43.633 APT 346

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96 Usage Value Year Month Duration Daily Use Premise Unit 1441 2010 06 33 43.667 APT 346 1441 2010 06 33 43.667 APT 395 1312 2008 08 30 43.733 APT 381 1446 2010 06 33 43.818 APT 381 1227 2010 05 28 43.821 APT 382 1448 2008 07 33 43.879 APT 381 1229 2010 02 28 43.893 APT 348 1319 2010 08 30 43.967 APT 335 1454 2010 06 33 44.061 APT 393 970 2008 05 22 44.091 APT 396 1415 2010 09 32 44.219 APT 335 1284 2010 01 29 44.276 APT 383 1464 2009 07 33 44.364 APT 382 1288 2010 01 29 44.414 APT 186 1563 2009 12 35 44.657 APT 382 1432 2010 09 32 44.750 APT 138 1433 2010 09 32 44.781 APT 395 1254 2010 02 28 44.786 APT 291 1347 2010 08 30 44.900 APT 187 1348 2010 08 30 44.933 APT 395 1441 2009 09 32 45.031 APT 280 1352 2010 07 30 45.067 APT 279 1356 2009 06 30 45.200 APT 335 1357 2009 06 30 45.233 APT 187 1269 2010 02 28 45.321 APT 395 1498 2010 06 33 45.394 APT 335 1503 2009 07 33 45.545 APT 187 1324 2010 01 29 45.655 APT 138 1508 2008 01 33 45.697 APT 278 1371 2009 01 30 45.700 APT 395 1330 2008 06 29 45.862 APT 290 872 2010 11 19 45.895 APT 280 1377 2008 08 30 45.900 APT 290 1377 2010 07 30 45.900 APT 335 1470 2009 09 32 45.938 APT 335 1379 2010 07 30 45.967 APT 187 1477 2009 09 32 46.156 APT 346 1351 2009 08 29 46.586 APT 187 1633 2009 12 35 46.657 APT 279 1402 2010 08 30 46.733 APT 346 1402 2010 04 30 46.733 APT 383

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97 Usage Value Year Month Duration Daily Use Premise Unit 1411 2008 05 30 47.033 APT 278 1413 2009 06 30 47.100 APT 395 1557 2010 03 33 47.182 APT 383 1375 2009 02 29 47.414 APT 395 1614 2010 12 34 47.471 APT 138 1568 2009 07 33 47.515 APT 335 1381 2010 01 29 47.621 APT 291 1382 2010 01 29 47.655 APT 188 1388 2009 08 29 47.862 APT 395 1438 2008 08 30 47.933 APT 187 1448 2010 08 30 48.267 APT 381 918 2009 09 19 48.316 APT 383 1363 2010 05 28 48.679 APT 383 1665 2010 12 34 48.971 APT 335 1427 2009 02 29 49.207 APT 229 1481 2009 10 30 49.367 APT 335 1639 2009 07 33 49.667 APT 395 1510 2009 06 30 50.333 APT 382 1461 2008 06 29 50.379 APT 280 1461 2009 08 29 50.379 APT 383 1666 2008 07 33 50.485 APT 290 1465 2008 09 29 50.517 APT 278 1466 2010 01 29 50.552 APT 395 1469 2010 10 29 50.655 APT 381 1674 2008 07 33 50.727 APT 187 1477 2010 01 29 50.931 APT 348 1686 2009 07 33 51.091 APT 383 1540 2010 07 30 51.333 APT 395 1809 2009 12 35 51.686 APT 335 1709 2008 07 33 51.788 APT 280 1580 2010 06 30 52.667 APT 383 1013 2009 06 19 53.316 APT 383 1590 2009 08 29 54.828 APT 335 1759 2010 09 32 54.969 APT 381 1933 2010 12 34 56.853 APT 346 1992 2010 12 34 58.588 APT 280

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98 LIST OF REFERENCES Ahic underwriting guidelines (2010, November 17). Retrieved from http://www.ahic.org/tools resources/ Archer, W. R., & Becker, T. S. (2013, March 13). Survey of emerging market conditions Retrieved from http://warrington.ufl.edu/centers/cres/survey.asp Cory, Karlynn S., Toby Couture, and Cl aire Kreycik. Feed in tariff policy: Design, implementation, and RPS policy interactions. National Renewable Energy Laboratory, 2009. Couture, T., & Gagnon, Y. (2010). An analysis of feed in tariff remuneration models: Implications for renewable energy inv estment Energy Policy 38 (2), 955 965. Desai, M., Dharmapala, D., & Singhal, M. (2010). Chapter 6: Tax Incentives for Affordable Housing: The Low Income Housing Tax Credit In NBER/Tax Policy & the Economy (University of Chicago Press) (pp. 181 205). University of Chicago Press. Donovan, S. (n.d.). LIHTC Basics Retrieved from website: http://portal.hud.gov/hudportal/HUD?src=/program_offices/comm_planning/afford ablehousing/training/web/lihtc/basics DSIRE. (2013, January 14). Gainesville regional utilit ies solar feed in tariff Retrieved from http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=FL77F Fisher, Sheehan, & Colton, Home Energy Affordability Gap, (2011 ). The home en ergy affordability gap april 2011 Retrieved from http://www.homee nergyaffordabilitygap.com/06b_Prior_Year_Data.php Florida Housing Finance Corporation. (2011, June). 2011 universal application instructions Retrieved from http://www.floridahousing.org/FH ImageWebDocs/UniversalApps/2011/ApplicationInstructionsRules/2011 06 10_Board_Meeting_Submissions/6 2 11_Draft_Instructions.pdf Fonorrow, K. (201 3, March 20). Interview by Adriel Cardenas []. Energy reduction potential in multifamily housing. Gainesville Regional Utilities (2012, November). Calculating your gru residential electric bill Retrieved from https://www.gru.com/Portals/0/Legacy/Pdf/calculatingElectric.pdf Green, G. (2009). Case study: SOLARA. 2009a) Print Green, G. (2010). Case study: Los vecinos 2010a) Print

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99 HUD (2009). Utility bills burden the poor and can cause homelessness. Retrieved from website: http://www.hud.gov/offices/cpd/library/energy/homelessness.cfm Keightley, M. P. Congressional Research Service, (2009). An introd uction to the design of the low income housing tax credit (RS22389). Retrieved from website: www.crs.gov Lee, C. (2012, August). 2012 survey of operating income & expenses inrental apartment communities Retrieved from http://www.naahq.org/learn/income and expenses survey/2012 survey Lesser, J. A., & Su, X. (2008). Design of an economically efficient feed in tariff structure for renewable ene rgy development Energy Policy, 36(3), 981 990. doi:10.1016/j.enpol.2007.11.007 Ling, D. C., Archer, W. R., & Archer, W. (2010). Real estate principles, a value approach (3rd ed. ed.). McGraw Hill/Irwin. Novogradac & Company, LLC. (2010). Low income housing tax credit handbook (2010 ed.). Clark Boardman Callaghan. Novogradac & Company, LLC. (2012, May). Affordable housing resource center Retrieved from http://www.novoco .com/low_income_housing/facts_figures/index.php Novogradac & Company, LLC. (n.d.). Rent & income limit calculator Retrieved from http://www.novoco.com/tenant/rentincome/calculator/z 4.jsp PV Watts. (n.d.). Retrieved from http://rredc.nrel.gov/solar/calculators/PVWATTS/version1/US/code/pvwattsv1.cgi Regan, E. (2008, October 13). Proposal to r eplace non residential solar photovoltaic rebate and net metering financial incentives with a solar feed in tariff Retrieved from https://financere.nrel.gov/finance/node/1561 Robinson, L. A. (2010). Do firms incur costs to avoid reducing pre tax earnings? Evidence from the accounting for low income housing tax credits. The Accounting Review, 85(2), 637 669. Serlin, C., Kimura, D., Ascierto, J. & McManus, J. (2011). Housing for all americans: The low income housing tax credit. Affordable Housing Finance, Shimberg Center for Housing Studies. (n.d.). A z index Retrieved from http://flhousingdata.shimberg.ufl.edu/apps/azindex.pl Solangi, K. H., Islam, M. R., Saidur, R. R., Rahim, N A., & Fayaz, H. H. (2011). A review on global solar energy policy Renewable & Sustainable Energy Reviews, 15(4), 2149 2163. doi:10.1016/j.rser.2011.01.007

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100 Sovacool, B. K. (2009). The importance of comprehensiveness in renewable electricity and energy efficiency policy Energy Policy, 37(4), 1529 1541. doi:10.1016/j.enpol.2008.12.01 Waier, P. R. (2008). Rs means building construction cost data (67th ed.). Kingston, MA: Construction Publishers & Consultants. Wilhoit, R. (2013, April). Interview b y Adriel Cardenas []. Solar impact: Solar photo voltaics.

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101 BIOGRAPHICAL SKETCH Adriel is a graduate of the University of Florida where he received a M aster of Science in r eal e stat e and will soon be receiving a M aster of Science in building c onstruction He als o holds a B achelor of S cience in e conomics from the University of Central Florida. In addition Adriel served as a Political Appointee at the US Department of Commerce as a project manager, and also has experience in construction management and est imating.