University of Florida Thesis Or Dissertation Formatting

FINANCE AND ECONOMICS OF NET ZERO ENERGY K-12 PUBLIC SCHOOLS IN FLORIDA

HAMED HAKIM

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2018

To my precious Mom and Dad, and my lovely Sisters

ACKNOWLEDGMENTS

First and foremost, I would like to express my sincere gratitude to my advisor

Prof. Charles J. Kibert for his continuous support, his patience, inspiration, and for his compassion in sharing his valuable knowledge and expertise during the years of my

Master’s and Ph.D. studies. His guidance over the last six years helped me in many directions. His benevolence and kindness encourage me to portray a similar path for my future. I could not have imagined having a better advisor and mentor for this chapter of my life.

Besides my advisor, I would like to thank the rest of my dissertation committee:

Dr. Ravi Srinivasan, Dr. James G. Sullivan, and Dr. David T. Brown, for their insightful comments and encouragement, and also for the hard questions which incented me to widen my research from various perspectives.

I thank my incredible Powell Center fellows for stimulating a teamwork culture, initiating discussions, for the endless supports, and for motivating each of us in pursuing our ambitious goals. I am grateful to be a member of the Powell Center family!

Last but not least, I would like to thank my precious family who filled me with indefinite love and support throughout my years at University of Florida. Shohreh and

Akbar, my parents, Haleh and Nahal, my sisters, and Sasan, my brother in law have all mentally, emotionally, and spiritually helped me in my accomplishments.

4 TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 8

LIST OF FIGURES ...... 11

LIST OF ABBREVIATIONS ...... 13

ABSTRACT ...... 14

CHAPTER

1 INTRODUCTION ...... 16

Background ...... 16 Problem Statement ...... 17 Research Objectives ...... 19 Scope and Limitations...... 20 Organization of the Study ...... 21

2 REVIEW OF LITERATURE ...... 23

Introduction ...... 23 Net Zero Energy Concept and Definition ...... 24 Energy Life-Cycle Perspective ...... 27 Net Zero Energy Targets ...... 28 Existing Net Zero Energy Buildings ...... 31 The Concept of Green Schools ...... 35 Green Schools ...... 35 The School of the 21st Century ...... 37 Net Zero Energy Schools ...... 40 Net Zero Energy School Definition ...... 40 Net Zero Energy Ready Schools ...... 41 The State of the Art of NZE Schools ...... 43 Viable Renewable Energy Resources ...... 47 The Overview of Energy Production and Consumption in Florida ...... 47 Non-renewable resources ...... 47 Renewable resources ...... 48 Renewable Energy Resources Available for Floridan NZE Buildings ...... 49 Feasibility of NZE ...... 55 Technical Feasibility of NZE ...... 55 Envelope ...... 59 Fenestration and infiltration ...... 60 Electric lighting ...... 60

5 Plug and process loads ...... 62 Heating, ventilating, and air conditioning ...... 62 Service water heating ...... 64 Energy modeling results ...... 64 Economic Feasibility of NZE ...... 66 Net Zero Energy Building Cost Premiums ...... 71 Financing Mechanisms ...... 76 Monetary rebates and incentives ...... 78 Equity financing ...... 80 Debt financing ...... 80 Third party financing ...... 82 Florida Schools Finance and Budgeting ...... 87 Review of Florida’s Cost per Student Station ...... 89

3 METHODOLOGY ...... 95

Technical Assumptions ...... 99 Building Prototypes ...... 99 Reference K-12 school prototype ...... 99 NZE K-12 school building...... 101 Solar PV System, Technical Assumptions...... 102 Financing Assumptions ...... 103 Economic Assumptions ...... 104 Term of LCC ...... 104 General Inflation Rate ...... 104 Energy Escalation Rate ...... 104 Discount Rate ...... 106 Energy Rates ...... 107 Construction Costs ...... 107 PV System Costs ...... 108 Operation and Maintenance Costs ...... 109

4 ANALYSIS AND RESULTS ...... 110

Outline ...... 110 Part I: Analysis Results ...... 111 Part II: Degradation Scenarios ...... 115 Whole Building Degradation ...... 117 Mechanical components ...... 118 Envelope ...... 120 Building components useful life ...... 121 Economic Analysis of Whole Building Degradation ...... 123 PV System Degradation ...... 125 Part III: Future Scenarios ...... 125 Construction Costs Forecast ...... 126 PV System Cost Forecast ...... 131 Economic Feasibility of NZE K-12 Schools Built in 2022, 2026, and 2030 ..... 136

6 Analysis for the current date: The year 2018 ...... 138 Analysis for a future date: The year 2022 ...... 138 Analysis for a future date: The year 2026 ...... 139 Analysis for a future date: The year 2030 ...... 140 Limitations of the analysis for the future years ...... 142 The findings of the analysis for the future scenarios ...... 142 Part IV: Analysis of Financing Mechanisms ...... 143 1-Equity Financing ...... 144 2-Debt Financing ...... 145 3-Third-Party Financing ...... 148 4- Feed in Tariff (FIT) ...... 150 Part V: Proposing a Self-Amortizing Loan ...... 151

5 CONCLUSION ...... 157

Economic Feasibility ...... 157 Findings in Brief ...... 159 Future Studies ...... 160

APPENDIX

A K-12 SCHOOL PROTOTYPE BUILDING SPECIFICATION ...... 161

B K-12 SCHOOL PROTOTYPE COST ESTIMATION (RSMeans) ...... 165

LIST OF REFERENCES ...... 175

BIOGRAPHICAL SKETCH ...... 184

7 LIST OF TABLES

Table Page

2-1 20th century versus 21st century classroom ...... 39

2-2 NREL definitions for NZE buildings considering source of renewables ...... 41

2-3 US net zero energy schools...... 44

2-4 US NZE school energy strategies ...... 46

2-5 Renewable energy resources and their suitability for the zero energy building definitions ...... 52

2-6 Feasibility study prototype characteristics ...... 58

2-7 Space types ...... 59

2-8 Space type breakdown ...... 59

2-9 LPDs by space type ...... 61

2-10 Electric plug and process loads ...... 61

2-11 EUI values for NZE schools ...... 65

2-12 Cost premium ranges to build net zero energy ...... 75

2-13 Net present value (NPV), simple payback (SPB), and return on investment (ROI) to build net zero energy ...... 76

2-14 A summary of the financing mechanism ...... 85

2-15 Number of Design-Build school projects in Florida during 2012 to 2015 ...... 94

3-1 The energy use intensity results of the energy analysis of the primary school prototype ...... 100

3-2 A summary of the energy analysis of the primary school prototype that complies 2015 IECC using the city of Miami climate data ...... 101

3-3 EUI values for NZE schools ...... 102

3-4 Assumptions for a typical solar PV system used in the model ...... 103

3-5 Projected fuel price indices with assumed general price inflation rates of 2%, 3%, 4%, and 5% ...... 105

8 3-6 US Solar Photovoltaic System Cost Benchmark Summary: Q1 2017 ...... 108

4-1 A summary of the economic assumptions used in the NZE-DSS...... 111

4-2 The results of the economic feasibility for the base model ...... 112

4-3 Sensitivity analysis of economic outputs to the building cost premiums ...... 113

4-4 Performance degradation of HVAC components ...... 119

4-5 Performance degradation of different insulation types ...... 120

4-6 ASHRAE equipment life expectancy chart ...... 122

4-7 Average life cycle for building subsystems ...... 123

4-8 The results of the initial economic feasibility model ...... 124

4-9 Sensitivity of outputs to solar panel degradation ...... 125

4-10 The results of the economic feasibility for the base model ...... 138

4-11 Economic outputs for the year 2022 ...... 138

4-12 A sensitivity analysis of the year 2022 results to the PV system forecasted costs ...... 139

4-13 Economic outputs for the year 2026 ...... 139

4-14 A sensitivity analysis of the year 2026 results to the PV system costs ...... 140

4-15 Economic outputs for the year 2030 ...... 141

4-16 A sensitivity analysis of the year 2030 results to the PV system costs ...... 141

4-17 A summary of the results of the future scenarios...... 143

4-18 The results of the base economic feasibility model ...... 145

4-19 The results of the adjusted model with a debt financing scenario for the PV system ...... 146

4-20 The results of the sensitivity analysis of outputs to loan rate ...... 146

4-21 The results of the adjusted model with a debt financing scenario for the PV system ...... 147

4-22 The results of the sensitivity analysis of outputs to loan rate ...... 147

9 4-23 Federal Investment Tax Credit by technology type ...... 149

4-24 The results of the adjusted model with a FIT scenario ...... 151

4-25 The results of the sensitivity analysis of outputs to the FIT rate ...... 151

A-1 Specifications of the K-12 school building prototype ...... 161

B-1 RSMeans square foot cost report for a typical elementary school in Miami ..... 168

B-2 RSMeans square foot cost report for a typical green school in Miami ...... 172

10 LIST OF FIGURES

Figure Page

2-1 Share of total US energy by end-use sector ...... 24

2-2 Frequency of the projects in different Climates, and in democrat and republican regions ...... 34

2-3 Site EUI versus building size; The share of the number of the stories; Site EUI in different climate zones ...... 35

2-4 Key benefits of green schools...... 37

2-5 US climate zones ...... 45

2-6 Annual electricity generation in California, Florida, and Texas ...... 49

2-7 The availability and the power capacity of renewable energy resources in Florida ...... 51

2-8 Roof PV coverage percentage to achieve NZE status for primary schools ...... 66

2-9 Holistic view of a NZE building ...... 69

2-10 Net zero energy building components and strategies for energy savings ...... 71

2-11 Traditional and innovative financing mechanisms to fund a NZE building ...... 77

2-12 New K-12 school construction by owner type ...... 88

2-13 New Public K-12 school construction by school type ...... 88

2-14 History of revenue sources for school district capital projects in Florida ...... 91

2-15 Share of revenue sources for school district capital projects in Florida ...... 91

2-16 Education FCO Appropriation for school district capital projects in Florida ...... 93

3-1 The main feeding elements of the NZE-DSS ...... 96

3-2 The main outputs of the decision support system ...... 96

3-3 Ensuring the accuracy of the model inputs ...... 97

3-4 An overview of NZE-DSS assumptions ...... 98

4-1 Sensitivity analysis of NPV and Payback to blended energy costs and discount rate for the combined model ...... 114

11 4-2 Adjusted sensitivity analysis of the main input variables ...... 114

4-3 Net zero energy building components ...... 117

4-4 Historical trend and forecast for construction costs ...... 128

4-5 RSMeans Square Foot Cost Estimator ...... 129

4-6 RSMeans historic costs for a given school ...... 129

4-7 National building cost index trend ...... 130

4-8 National price indices, historical and forecasts ...... 131

4-9 NREL PV system cost benchmark summary ...... 132

4-10 Historical and forecasted U.S. PV system pricing by market segment ...... 133

4-11 Price per watt of solar PV ...... 133

4-12 Reported utility-scale solar photovoltaic capital costs 2010-2017...... 134

4-13 Global weighted average costs of utility-scale solar PV systems 2009-2025 ... 135

4-14 LCOE values and SunShot goals for the residential, commercial, and utility- scale sectors...... 136

4-15 School construction costs forecast for the NZE-DSS model ...... 137

4-16 PV system costs forecast for commercial building scale ...... 137

4-17 Projected electricity prices for the stochastic analysis ...... 154

B-1 An example of cost estimation inputs in RSMeans square footage cost estimator ...... 165

B-2 Elementary school cost estimations using RSMeans square footage cost estimator ...... 166

B-3 Elementary school cost estimations using RSMeans square footage cost estimator ...... 167

B-4 Green elementary school cost estimations using RSMeans square footage cost estimator ...... 171

LIST OF ABBREVIATIONS

CPI Consumer Production Index

DOE Department of Energy

ECM Energy Conservation Measures

EDA Economic Decision Analysis

EPC Energy Performance Contract

ESCO Energy Services Company

EUI Energy Use Intensity

FEMP Federal Energy Management Program

FIT Feed in Tariff

ITC Investment Tax Credits

LCA Life Cycle Analysis

LCC Life Cycle Costs, Life Cycle Costing

LLCA Life Cycle Costing Analysis

NBI New Building Institute

NPV Net Present Value

NREL National Renewable Energy Laboratory

NZE Net Zero Energy

NZE-DSS Net Zero Energy Decision Support System

PV Photovoltaic

ROI Return on Investment

WBLCCA Whole Building Life Cycle Costing Analysis

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

FINANCE AND ECONOMICS OF NET ZERO ENERGY K-12 PUBLIC SCHOOLS IN FLORIDA By

Hamed Hakim

December 2018

Chair: Charles Kibert Major: Design, Construction, and Planning

Net zero energy buildings can save energy costs, they have fewer carbon emissions, and they are a suitable solution to decrease the rate at which we are depleting non-renewable energy resources. A net zero energy building is an energy- efficient building where its annual energy consumption is less than or equal to the renewable energy generated on-site. Among all building types, K-12 schools have a great potential to target the net zero energy goal. Earlier studies have proven that net zero energy schools are technically feasible, however, there is limited research to show if they are economic. Similarly, the literature fails to properly address the existing and innovative mechanisms to provide funding for the construction of such schools. This issue is more significant for public schools as they have the additional burden of having to justify and raise additional capital for school construction. The existing knowledge gap for decision makers discourages them to embrace the net zero concepts for school buildings. Clearly, economic justifications and innovative financing mechanisms are required for this building type to become mainstream. This study aims to bridge the knowledge gap and analyze the economic feasibility with a use of a net zero energy decision support system that can help owners, designers and developers to target

energy self-sufficient schools. The analysis examines the feasibility of a net zero energy school project from an economic standpoint. It estimates the trigger thresholds for a net zero energy school construction costs relative to a reference school prototype. The analysis also integrates traditional and innovative financing methods into the decision model. Furthermore, the study uses stochastic approaches to determine dept capacities that are secured by energy savings as collateral. A self-amortizing loan structure is introduced as a plausible financing support mechanism to build a net zero energy school. This research reveals that a net zero energy school cost premiums have a simple payback period of less than 15 years in most places in Florida. Also, it is feasible for schools to synthesize a self-amortizing loan mechanism to finance the cost premiums. The outcome of this research can increase the awareness of decision makers of the economics of NZE schools. The scope of this research is limited to the state of Florida. However, with a few changes in the assumptions and input data, the models can be modified for other locations.

CHAPTER 1 INTRODUCTION

Background

Buildings consume significant amounts of energy and are regarded as a primary target for reducing energy consumption and carbon emissions. The advancement and growing number of net zero energy buildings is a proof of practicable solutions to meet the minimum carbon emission target in the building sector. During the past few decades, the concept of net zero energy (NZE) has gained significant attention and shaped vigorous energy targets at the local, state, and federal level. For example, in

2007 the US congress authorized the Energy Independence and Security Act which supported the goal of NZE for all new commercial buildings by 2030. In another example, the California Public Utilities Commission set an energy action plan to achieve

NZE for all new residential construction by 2020 and for all new commercial construction by 2030. Today, numerous action plans are in place simply because buildings consume significant amounts of energy and are regarded as a primary target for energy savings. To achieve these targets, there is a need for collaborative efforts of industry experts and academic researchers.

NZE K-12 school buildings, that is the focus area for this study, are a suitable test platform for adopting and advancing NZE concepts. A NZE school is defined as an energy efficient school that on a source energy basis, the actual annual energy consumption is less than or equal to the renewable energy generated on-site. In a list of

NZE buildings presented by the New Building Institute (NBI), over 500 NZE buildings in different parts of the US are listed. Among them, K-12 Schools, with 18 percent of the projects, is a leading building type in adopting NZE concepts (NBI, 2018).

Problem Statement

Problem in Brief: Public School Districts are long known for facing construction budget deficits, therefore are slow adopters of capital intensive and innovative concepts such as NZE. They have limited information on the feasibility of NZE concepts for their facilities. NZE schools, however technically proven (Bonnema et al., 2016), cannot become mainstream unless they have economic justification. At the date of this study, there is no net zero energy decision support system (NZE-DSS) available for school districts in Florida to analyze the economic feasibility of a NZE project. The list of NZE buildings collected by the NBI presents over 50 NZE K-12 schools in different climate zones in the nation but to this date, none is in Florida. There is little to no previous research and tools to empower decision makers to examine the economic feasibility of zero energy concepts for K-12 school buildings.

Problem in Detail: In a pragmatic environment and to reach the ambitious building energy targets, NZE buildings should have economic justification, meanwhile, financing vehicles should be made available to fund the initial investment costs. Also, the economics and finance of NZE buildings should be understandable to owners, designers, and developers. In most projects, energy savings and renewable energy capturing technologies appear as added costs. Financing this upfront premium is a main challenge especially for public schools. Although NZE buildings can be economical in certain cases such as K-12 schools, traditional financing methods are not suitable for them. The study of literature illustrates that the major barrier to the development of NZE projects is a financial hurdle and not technological advancements in achieving such buildings. Estimating the building costs as well as the financing costs are important factors that can alter the final decisions. NZE schools can be cost effective through

design and practice. One example project that is found economic is not an indication of success for all projects. Therefore, decision makers should be able to evaluate and analyze their decision criteria. A decision maker would question:

• What are the additional initial investment costs to build a NZE school?

• What are the future cost savings for a NZE school?

• What is a right methodology to calculate costs and benefits of a NZE school?

• What are the decision-making criteria for the owners, designers, and developers to build net zero? What economic settings can trigger a decision to pursue a NZE goal?

• After setting the decision criteria, how to analyze the economic feasibility?

• What is a right pair comparison methodology that can save time, costs, and energy to perform the analysis?

• How to consider the effect of uncertain economic inputs?

• What are the meaningful starting technical and economic assumptions for the analysis?

• What are the available and new financing mechanisms that can change the decision?

• What is a right methodology to consider the effect of different financing scenarios?

• What are the ways to save time, cost, and efforts in performing economic evaluations?

• What are the proper ways to communicate the results with other parties involved?

Clearly, a well-designed net zero energy decision support system (NZE-DSS) can create a platform for finding answer to the above questions. The current literature is lacking useful resources that directly focus on the economics of NZE schools.

Moreover, in construction, each project is unique. Knowing that this type of buildings can be cost effective is not enough to trigger a decision to build net zero. Decision-

makers need to use tools that enables them to adjust the decision based on the specifics of every single project, hence, a NZE-DSS can be a useful tool.

Moreover, the concept of NZE schools and its feasibility and finance should be more understandable to owners, architects, design engineers, general contractors, facility managers, and building operations staff. The outcome of this research can increase the awareness of decision makers of the economics of NZE schools. Although the scope of this research is limited to the state of Florida, its outcome, including the decision support model, can be modified for other locations.

Research Objectives

The optimal framework for this study is carefully designed to address the industry and academic research needs such as:

• Identify the definitions of NZE schools and study the status of current projects in the US and Florida

• Study the technical feasibility of NZE school projects in the state of Florida

• Identify the latest developments and trends in incorporating innovative financing mechanisms to fund the construction of the NZE schools in Florida

• Identify the previous research projects that investigated viable strategies to finance renewables, and energy efficient buildings

• Identify the critical knowledge gaps in finance and economic feasibility analysis of NZE schools

• Increase the awareness of the decision makers of the innovative mechanisms that can be integrated to the economic models

• Create a decision-making tool for an early stage feasibility analysis of NZE school projects

• Increase the reliability of the economic outputs by incorporating deterministic and stochastic approaches which consider the effects of uncertain inputs

The deliverables include a study report and an excel-based decision support model that enables the decision-making analysis. The model is programed to evaluate the economic feasibility of the NZE School projects based on the major cost items, and under different parametric scenarios comprehendible to the users.

Scope and Limitations

The scope of the study is limited to the public K-12 school facilities in the state of

Florida. This study can be further continued by other researchers to include different building types and locations. Traditionally, construction economics, energy efficiency economics, and renewable energy economics are studied separately. However, for a

NZE school project, they should all be studied and examined simultaneously. Therefore, the scope of this study covers a range of information on the construction estimation and costs, energy conservation measures (ECM) economics, and renewable energy system economics. Almost all current NZE buildings use solar energy to generate electricity and they use net metering billing mechanism to export the generated electricity back to the grid. Florida has a great potential for generating energy from solar and the state has net metering policy. The renewable energy generating system used in this study is solar photovoltaic system (PV system).

In the models created, the focus is the whole building life cycle cost analysis

(WBLCC) considering two parts. First, an entire building as one unit and second, a solar

PV system. Performing individual LCCA for individual energy efficiency components is not the focus of this study at this point. In future studies, the models can be elaborated to perform LCCA for individual energy saving components that have significant cost

differential between a typical school and a NZE school to enable a value engineering analysis that optimizes the costs with respect to energy savings.

The goal of this study is to provide a straight forward NZE-DSS understandable to building stakeholders. Therefore, where needed, assumptions are taken to simplify the analysis. For example, a blended rate of energy is proposed to be used in the NZE-

DSS models rather than using different rates for gas and electricity. Another example is the input data used are based on of elementary/primary schools only. There are a few differences among elementary, middle, and high school building types. The Department of Energy (DOE) prototypes are separately given for primary and secondary K-12 school buildings. However, in this study the prototype for primary K-12 schools is used.

This is a safe assumption as primary K-12 schools are slightly more energy intensive.

The goal here is to create a decision-making tool for the economic feasibility analysis of NZE schools in the early design phases. At that stage, cost factors are based on the early estimates and not the final costs. To consider the effect of uncertainties in the model inputs and outputs, sensitivity and scenario analysis methods are used. The model outputs are as accurate as the model inputs. Therefore, special attention is given to defining the input assumptions. Some of the inputs should be determined by the user thus the results are also impacted by the accuracy of the user’s estimation of the inputs.

Organization of the Study

Chapter 2 will explore the literature related to the NZE, and NZE school buildings. It starts with presenting the definition of NZE concepts and a few major zero energy targets for building projects. It also presents the status of current NZE buildings

in the US. It follows by a review of green schools, energy efficient schools, and NZE school projects. The last sections of this chapter explore the earlier studies on the feasibility of NZE school buildings, and the final section reviews the available and innovative financing mechanisms applicable for this building type. Chapter 3 presents the methodology taken in this study. The methodology section includes a detailed explanation of the assumptions used in this study which are integrated to the NZE-DSS.

The proposed models are tested and used to analyze the economic feasibility of NZE school projects in chapter 4. This chapter presents the results and discusses the scenarios tested by the models. Chapter 5 includes discussion and conclusions. It also presents the limitations of this study and the areas for future research work.

CHAPTER 2 REVIEW OF LITERATURE

Introduction

In 2015, nearly 200 countries around the world came to a universal climate agreement known as “Paris Agreement” which concluded that nations agreed to hold global warming to “well Below” 2 degrees Celsius compared to the pre-Industrial

Revolution levels. The main goal of the agreement is to prevent worst-case scenarios for global warming. In a recent special report by the Intergovernmental Panel on Climate

Change (IPCC) that was revealed in October 2018 in Korea, the impacts of global warming of 1.5 degrees Celsius above pre-industrial levels are studied (IPCC, 2018).

This report warns the devastating impacts of the global warming phenomenon more than the previous publications. Experts expressed that it is a challenging task to limit the warming to 1.5 degrees and it requires an immediate and significant reduction in emissions from fossil fuels. Meanwhile, it is known that of the total end-use energy consumed in the US, construction sector has the largest share (Figure 2-1). Indeed, construction sector can play a major role in cutting their emission level by reducing energy usage from non-renewable sources and replacing it with clean energy sources.

The concept of net zero energy (NZE) buildings addresses the similar issues. On the plus side, the development of such buildings is rapidly growing (NBI, 2016, 2018).

SHARE OF TOTAL US ENERGY BY END-USE SECTOR, 2016

Transportation 29%

Commercial 19% Buildings 40% Residential 21%

Industrial 31%

Figure 2-1. Share of total US energy by end-use sector, 2016, Source: US Energy Information Administration

In general, the benefits of NZE buildings are threefold. First, they reduce carbon emissions. Second, they consume less energy and therefore, they can be more economic. And third, NZE buildings are a suitable solution to decrease the rate at which we are depleting non-renewable energy resources. This chapter reviews the literature for the definitions of NZE concepts and discusses the status of the existing efforts and successful NZE projects. The discussion is followed by explaining the concept of green schools and NZE schools. The final sections of this chapter discuss the literature on the technical and economic feasibility of the NZE buildings, and the viable financing mechanisms to fund the construction of NZE schools.

Net Zero Energy Concept and Definition

In order for the NZE concepts to become mainstream in the market, a wide consensus on clear definitions of “net zero” should be reached. This agreement is also needed for measuring energy performance and will certainly be helpful in developing effective design and control strategy of NZE buildings (Task 40, 2015; Lu et al., 2015).

According to a study conducted by Lu et al. (2015), the existing literature on the definition of NZE building is still lacking a common framework and NZE is not a consistent concept at the international level. Deng et al. (2014) in a study of “How to evaluate the performance of net zero energy building” also noted that the clarification of

NZE building definitions can effectively help the evaluation process of zero energy objectives. Until the date of this manuscript, there is no consensus on one single common expression for NZE buildings that can satisfy the entire research community.

Therefore, the research emphasized on the importance of defining a framework that includes factors such as boundary, metrics, climate conditions, energy sources etc. The earlier studies suggested that individual participators can specify the details of the definition within the agreed framework. As net zero energy is rather a recent study area for researchers, numerous terms were disclosed in the literature that are used interchangeably around this topic: Zero Energy Building (ZEB), net Zero Energy

Building (nZEB, n-ZEB, netZEB, NZEB), Net Zero Energy Building (NZE building), Zero

Net Energy (ZNE), Energy Neutral, Energy Self Sufficient, and others. In this study, the term net zero energy (NZE) building is used for the consistency of the language.

A widespread definition for NZE buildings is stated in “A Common Definition for

Zero Energy Buildings” a report by the US Department of Energy (DOE, 2015): Net zero energy building is “An energy-efficient building where, on a source energy basis, the actual annual delivered energy is less than or equal to the on-site renewable exported energy.” In this definition, the DOE report explains that the site boundary utilized for on- site renewables is typically the property boundary. It also further elaborates that the purchase of renewable energy certificates (REC) to fully offset the actual annual energy

consumption does not abide by this definition of NZE building. RECs are tradable instruments that can be purchased to offset carbon emissions through the production of green power elsewhere. Buildings can voluntarily purchase RECs to support the deployment of renewables. Green building verification programs such as Leadership in

Energy and Environmental Design (LEED) award points for the use of RECs in their score system.

A frequently cited definition for NZE buildings was presented by Paul Torcellini et al. (2006). They proposed four definitions for NZE buildings (referred to as ZEB): site

ZEB, source ZEB, emissions ZEB, and cost ZEB. The study expresses that the application of these definitions depends on the project goals, project boundary, intentions of the investors, CO2 emissions concerns, and the costs of energy (EPBD,

2013; Lu et al., 2015). The Task 40 (Towards Net Zero Energy Solar Buildings), that has an objective of developing a common understanding and a harmonized international definition framework for NZE buildings, stated a definition that is commonly used by many stakeholders of the so-called NZE buildings: “buildings whose energy consumption are fully offset by renewable energy generated on site” (Task 40, 2015).

The Task 40 remarks that to comply the definitions of net zero and achieve a NZE building, three fundamental steps should be taken. First, to utilize passive building design techniques, second, to maximize energy efficiency strategies that reduce energy demand, and third, to produce renewable energy to offset the energy needs. Passive building design techniques have faced incremental improvements through thousands of years in advance of the creation of mechanical heating and cooling systems (Kylili and

Fokaides, 2015). Clearly, the NZE concept is a progressive evolution of energy efficiency and passive designs.

According to the report of the European concerted action for the building energy performance implementation directive, over 20 different terms have been used across

European countries for defining NZE buildings (Kylili & Fokaides, 2015). The term nearly zero energy is widely used in the discussion of energy policies of European countries. In Europe, the recast of the Energy Performance of Building Directive (EPBD) presented a definition for nearly zero energy as a building that first, has a very high energy performance, and second, generates this low amount of energy usage from onsite or nearby renewable sources (EPBD recast, 2010). Article 9.1. of the recast regulates target timelines for the construction of new buildings in member states (MS) to comply with nearly zero energy outline. The qualitative definition presented by the recast leaves the member states responsible to provide exact definitions for nearly zero energy buildings, which can include a quantitative consumption indicator, based on their regional and national conditions. The advantage of the proposed qualitative definition is that the MS can adapt the details for the definition based on their climate and other regional conditions, while the disadvantage is the ambiguity in the renewable shares and the emission thresholds. A study by Kurnitski et al. (2014) revealed a large gap between 20 and 200 kWh/m2-yr in energy use intensity (EUI) of zero and nearly zero energy buildings in ten different European countries even though some of them have similar climate conditions.

Energy Life-Cycle Perspective

Most definitions of NZE building require the building to offset its site (final or end use) energy consumption from renewable energy sources. In most case studies, a shift

from site energy to source (primary) energy can change the status of NZE buildings to non-zero due to the large energy loss, that is from extraction, transformation, and distribution of the imported energy. Most current NZE building definitions do not take an energy life-cycle perspective. Similarly, they overlook the embodied energy, e.g. in building materials, and only consider the consumption of the operation phase. In other words, the current methodologies for balancing energy usage and production concentrate merely on the operation phase. Cellura et al. (2014) in a study of “Energy life-cycle approach in Net zero energy buildings balance” stated that a reason for neglecting the embodied energy out of the operation phase is the small relative proportions. In most cases, for a standard building, the operational energy consumption has 70 to 90 percent share of the total life cycle.

Clearly, a life cycle analysis approach for energy consumption can increase the complexity of energy accounting and overburdens the achievement of the NZE status as it introduces further deficit in the energy balance (Cellura et al., 2014). Energy loss is more important when a building is connected to the grid. A typical NZE building uses electricity grids as a source of energy and to sink the produced electricity, which allows the building to avoid on-site storage systems. Due to the energy loss, in most cases in

Florida, the source energy usage should be nearly twice larger to meet the site energy usage. Therefore, the adoption of a life cycle energy analysis coupled with embodied energy concepts can cause an even larger imbalance to meet the NZE target (Cellura et al., 2014).

Net Zero Energy Targets

Countries have been pushing their boundaries in engineering and innovations to fight climate change by setting future goals and targets. One such goal is the energy

target which is set to reduce the consumption of fossil fuels. Developed countries such as Germany, United States, France, Sweden, and others are showing positive results in meeting their targets. In Europe, the article 9.1 of the EPBD recast regulates an energy target for the member states: “the Member States shall ensure that by 31 December

2020, all new buildings are nearly zero-energy buildings and after 31 December 2018, new buildings occupied and owned by public authorities are nearly zero-energy buildings.” Similarly, the Buildings Performance Institute Europe (BPIE) has taken an ambitious goal to drastically cut domestic greenhouse gas emissions and promote a sustainable and low carbon built environment in Europe. Many studies conducted by

BPIE have estimated 70 to 90 percent reduction in CO2 emissions by 2050 compared to 1990 levels (Szalay and Zöld, 2014). In 2007, the US Congress authorized the

Energy Independence and Security Act of 2007 (EISA, 2007). This act supported the goal of net zero energy for all new commercial buildings by 2030. It further specified a zero-energy target for 50% of commercial buildings by 2040 while by 2050 all US commercial buildings should be net zero energy (Crawley et al., 2009). In the state level, the California Public Utilities Commission of the USA has taken an energy action plan to achieve net zero energy status for all new residential buildings by 2020 and for all new commercial buildings by 2030 (Deng et al., 2014). The American Society of

Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) Board of Directors has taken an energy target for its code-intended standard to comply with NZE goals in

2031. Similarly, the International Energy Conservation Code (IECC) is tracking a path to

NZE by 2050 (NBI, 2016).

Several US cities are increasingly playing a significant role in moving towards a clean energy future. Seto et al. (2016) studied the emergence of energy targets and adaptation policies of a few urban communities. Buildings consume a significant amount of energy in major cities, thus they are a suitable target area for energy conservation programs. In 2002, the City of Cambridge adopted a Climate Protection plan that set an ambitious goal to decrease greenhouse gas (GHG) emissions by 80% by 2050.

Similarly, in 2015, the City of Fort Collins undertook an aggressive climate action target of 20% emission reductions by 2020, 80% by 2030, and carbon neutrality by 2050. The city of Austin planned for carbon neutrality by 2050. Previously, they decided to build all new single-family homes to be NZE capable starting from 2015. Another example is the city of San Antonio in Texas that set a target to have all new construction to be zero carbon by 2030 (Seto et al., 2016).

Apart from state and federal targets, various non-governmental non-profit organizations drive industries and people to achieve sustainable goals. For example, organizations such as Architecture 2030, US Green Building Council, Living Building

Institute, and New Building Institute are investing tremendous efforts to gain net zero energy in almost all types of buildings. The American Institute of Architects' (AIA) 2030 has established targets that indicate all new buildings and major renovations should be constructed 70 percent more efficient in terms of carbon emissions and energy consumption compared to regional or national average/median. Similarly, existing buildings should be renovated to meet the same target. According to Architecture 2030, the fossil fuel reduction targets shall be increased to 80 percent by 2020, 90 percent by

2025, and carbon-neutral by the year 2030.

Existing Net Zero Energy Buildings

According to the NBI report published in 2018, there are nearly 500 Net Zero

Energy commercial building projects of all sizes and types in the US (over 60 certified and verified, and approximately 440 NZE emerging buildings that have designed for and targeted net zero status yet have not demonstrated achievement of that goal). Simply, a

NZE building consumes only as much energy as can be produced from onsite renewable sources in the course of a year. With innovations in design, construction techniques, and advancement in technology, it is not surprising to see a dramatic increase in the number of NZE buildings. An additional force is the increasing number of

States and local jurisdictions mandating net zero buildings. According to the New

Building Institute (NBI), the number of verified and emerging NZE buildings in the US has had a seven-fold increase since 2012. This section studies the literature for the factors that are essential in the development of NZE buildings. These include location, size, climate zone, energy use intensity, type of ownership, and local politics, to name a few. Evaluating and examining these factors is needed to recognize the key elements in the development of NZE buildings. It is noted that the NZE concept has gained more attention in certain locations than in others.

A report from New Building Institute (NBI, 2016) provided a database for NZE buildings in the US that was utilized here to derive descriptive information on the emergence of such buildings. New Buildings Institute (NBI) is a nonprofit organization that collaborates with industry governments, utilities, energy efficiency advocates, and building professionals to promote advanced design practices, innovative technologies, public policies and programs that improve energy efficiency. It also develops and offers guidance and tools to support the design and construction of energy efficient buildings.

The NBI report included a number of case studies and explained some of the factors relating to the spread of these buildings. In a recent study by Hakim et al. (2018), additional information was added to the database to examine the correlation of studied measures such as Locations/climate zones, energy use intensity (EUI), etc. They explained that the limited number of data and the broadness of input factors that are not independent of each other resulted minimum meaningful statistical inference. However, the study presented a descriptive analysis of a few measurable elements and portrayed a snapshot of the currently built verified NZE buildings.

NBI has studied and verified over 400 ultra-low energy, verified NZE, and emerging NZE buildings and announced that the numbers of NZE buildings are increasing exponentially every year. The institute began its research in 2009 and published the database every two years in its leading reports in 2012, 2014, 2016, and

2018. According to NBI, NZE buildings are defined as “buildings with greatly reduced energy loads such that, totaled over a year, 100 percent of the building’s energy use can be met with onsite renewable energy technologies”. The organization has defined

NZE buildings in 4 categories which are: zero net energy verified buildings (ZNEVB), zero net energy emerging buildings (ZNEB), ultra-low energy verified buildings

(ULEVB), and ZNE Districts.

The study by Hakim et al. (2018) focused on the ZNEVB due to the availability and reliability of the data. NBI 2016 report verifies the NZE status of over 50 buildings throughout the US. Some of the factors discussed are building locations, size, ownership type, site EUI, and the site energy surplus at the time they were built. As stated by NBI, around 80 percent of the NZE verified buildings have footprint less than

25,000 feet. However, the number of large scale buildings is increasing for the emerging

NZE buildings. Considering the type of building, educational facilities, especially K-12 schools, are the most frequent type in the list. By the location it can be observed that several states have dominated the market for existing verified NZE buildings, however, emerging NZE buildings are geographically spreading in almost all states. It is not possible to rank the contributing factors to the spread of such buildings based on the available data. Some studies have stated that “environmental champion” image was one of the motivating factors for individuals who pioneered such projects (Ghiran, A. and Mayer, A., 2012). However, elements such as climatic conditions, sustainability awareness, political party of the region, financial rebates and incentives, and energy costs are among leading decision criteria in developing NZE projects.

Figure 2-2 shows the location of the NZE verified buildings on the ASHRAE climate map. ASHRAE defined eight climate zones for the US, of which seven can be seen on the map and only Alaska and some parts of Canada are in zone 8. As it can be seen on the map, states with milder climate zones have located the majority of the NZE buildings. California with 18 projects is clearly the front-runner state in ZNE activity.

Cities such as Los Angeles, San Diego, San Francisco, are at the lead and have dense

NZE buildings (NBI, 2016). This is an inspiration for the other states in developing their buildings to be NZE to fight against climate change. Considering the frequency of the verified NZE buildings in different climates, zone 3 and 4 have the most number of verified NZE buildings. Due to the very cold and harsh climate, high altitude, and low urban density, there is no NZE building in zone 7 and 8. Considering the dominant political party of a region at the time the building was built, over 40 projects are located

in democrat regions of which almost half are in California, while less than 10 projects are located in republican regions.

Figure 2-2. Frequency of the Projects in Different Climates, and in Democrat and Republican Regions

Almost all NZE cases are, primary, ultra-energy efficient buildings. This is proved by a study of energy use intensity of these buildings. Although the EUI is expected to be lower in locations with milder climates, no statistically significant trend was found for the

EUI of different buildings. We can also critique the EUI measure with respect to the size of the building. Because when we divide the energy consumption by size to obtain the

EUI measure, we imply that the size and energy efficiency have 1 to 1 linear relationship (y=x). However, this relationship is not linear especially in very small or very large-scale projects. Figure 2-3 presents the site EUI of the verified NZE buildings in different climate zones. The number of buildings for zones 1 and 6 is lower than a reliable number to infer statistical results. However, we can see that the density of the

EUI increases around the mean value, especially after excluding the one outlier case in climate zone 3, that is DPR Office- a retrofitted NZE project in San Francisco.

Figure 2-3. Site EUI versus Building Size; The Share of the Number of the Stories; Site EUI in Different Climate Zones

The Concept of Green Schools

The concept of NZE Schools has evolved from the advancements in the domain of energy efficiency for the school buildings. This energy efficiency target is a major goal in design and construction of green schools. Over the last few years, the topic of green schools has gained notable attention from school districts in the US. This section aims to discuss the concept of school of 21st century and green schools.

Green Schools

Education is of utmost importance for society and the families of which it is comprised. According to the National Center for Education Statistics, more than 55 million students enroll annually in the US K-12 schools. In 2013, this figure was around

5.2 million students for private schools and 50.1 million for public schools. These students enroll annually in more than 130,000 schools in US, roughly 75 percent in public school and 25 percent in private ones (DOE Statistics, 2013). Numerous earlier

research studies demonstrate that the performance of this population of students is affected by the quality of the physical environment such as proper temperature, day lighting, air quality, sound, etc. Interestingly, improving such factors can also bring energy reduction. Considering that energy expenses are often the second highest costs after personnel salaries, further attention to maximizing the energy efficiency of schools is a sensible goal. Recent reports about the performance of US green schools show that, on average, $100,000 can be saved annually per school in operating costs by using high performance building strategies (USGBC, 2013; EPA, 2011). It is noted that these savings can pay for two new teachers or be spent on supplies such as books, computers, and other materials and supplies. Furthermore, energy-efficient schools that incorporate new renewable energy technologies can better demonstrate the importance and value of protecting our surrounding environment. As a result, energy- efficient buildings can play a teaching role in illustrating the true impact of building green practices (ASHRAE, 2011).

Each day, a large number of the world’s population spends most of their time in schools as students, teachers, and staff. It is clear that everybody in a school is affected by the physical environment of the school building. The impacts can be seen in student productivity, health, and satisfaction. Education under healthy conditions keeps mind active, reduces absenteeism, and improves the performance of students in tests. Many studies suggest that students with a proper learning environment can enhance their academic skills and score higher on standardized tests than others. School buildings can be designed and constructed in a way that minimizes their harmful impacts on environment. Increasing the indoor quality of a building and at the same time

decreasing the outdoor negative impacts on environment have been the main driving forces behind the creation of green schools. Moreover, schools have significant utility costs, hence applying green strategies will reduce those expenses to a large extent.

The saved money can be spent on other purposes. In addition to savings, the educational role of the school buildings can further promote the benefits of these schools. Figure 2-4 indicates the key benefits of green schools.

Green School Benefits

Educational Environmental Economical

*Healthier *Conserve natural environment *Reduce utility resources and reduce costs waste *Increase *Reduce operation productivity and *Reduce the negative decrease and maintenance impact on environment expenses absenteeism *Operate in a *Contribute to the *The building sustainable manner plays a teaching local economy role

Figure 2-4. Key benefits of green schools

The School of the 21st Century

Changes in the patterns of life in the late 20th and early 21st century have caused new concerns for education systems. In the current era, the quality of education systems is more important to parents. The concept of 21st Century School (21C School)

is a community school model that provides an affordable and quality education system for children. The 21C School notion was launched in 1988 and as of 2015, there are more than 1,300 schools that have implemented the following six major principles, (1)

Guidance and support for parents (2) Childcare with universal access (3) Non- compulsory programs before/after school and during vacations (4) Focus on health, education, services, and overall development of children, (5) High quality program and services, and (6) Professional training and advancement opportunities for education practitioners. The 21C School concept extends well beyond just information delivery and requires knowledge generation (School of the 21st Century, n.d.). Table 2-1 indicates some of the changes in a traditional school system versus the desired features of a 21st century school.

It is obvious that school buildings can have significant influence in achieving 21C learning goals. The factory model of historical schools is now shifting to a model of green construction that utilizes the latest research in high performance green schools.

As we are moving forward, the new and existing school buildings are built and retrofitted with the use of recent technologies that make a building more environmental friendly and more energy efficient. Additionally, the increasing number of educators and responsive school boards encourage innovative designs and further motivate architects to rethink in a sustainable way. Legislators are also paving the way through allocation of funding to the schools. Third-party verification organizations are also playing a fruitful role to adjust the school buildings to the 21st Century School goals. The US Green

Building Council (USGBC) has created a center for green schools and the LEED school rating system can measure how a K-12 school facility can support its occupant’s health

and save resources, energy and money. The Green Building Certification Institute

(GBCI), the certification arm of the USGBC, reviews LEED applications and provides feedback on the registered projects. By 2009, this Institute has certified more than 3,000 schools and the majority of them have been built at little or no additional cost compared to the conventional schools (USGBC, 2009). These green schools, on average, use 32 percent less water and 33 percent less energy than their conventional counterparts, and are able to save an average of $100,000 per year per school on direct operating costs

(USGBC, 2009).

Table 2-1. 20th century vs 21st century classroom. Source: Adapted from the “21st century schools” website

USA 1960’s typical classroom A classroom at the Lady Bird Johnson Middle School in Irving, Texas. Time-based Outcome-based Focus: memorization of discrete facts Focus: what students Know, Can Do and Are Like after all the details are forgotten. Textbook-driven Research-driven Passive learning Active Learning Students work in isolation Students work collaboratively Teacher-centered Student-centered Little to no student freedom Great deal of student freedom Fragmented curriculum Integrated and Interdisciplinary Grades averaged Grades based on what was learned Teacher is judge Self, Peer and Other assessments Print is the primary vehicle of learning and Performances, projects and multiple forms of assessment. media are used for learning and assessment Factory model Global model

Net Zero Energy Schools

Net Zero Energy School Definition

Energy neutral buildings is a concept that evolved as a cutting-edge practice in the field of sustainable construction. A net zero energy school demonstrates a state-of- the-art achievement in the recent surge for green schools. A net zero energy school has the same definition as a net zero energy building, that is simply a building that meets its annual energy demand from on-site renewable energies. In 2015, the National

Renewable Energy Laboratory (NREL) and the Department of Energy (DOE) provided a widespread definition for net zero energy buildings including schools. A NZE School is

“An energy-efficient building where, on a source energy basis, the actual annual delivered energy is less than or equal to the on-site renewable exported energy.”

Considering the source of energy, NREL divides the net zero buildings into four types as shown in Table 2-2. Most schools are situated on a site larger than the building footprint. Therefore, when zero energy building type A (ZEB A), as explained in the table, is not achievable, they still have the potential to target ZEB B. A school can also become net zero energy by purchasing renewable-based energy from the grid (ZEB D category), however, the added value comes when the school is first energy efficient then energy neutral. Moreover, ZEB D is not aligned with the common definition of the

NZE building offered by the DOE in 2015. Considering NZE accounting, it should be noted that a school may not be energy-efficient but can be net zero energy by installing as many solar panels as needed on-site or off-site. This should be the reason that the definition of a net zero energy building is modified by limiting the source of energy to the project site and setting an energy efficiency target in designing such buildings. The definitions do not limit the annual energy use intensity (EUI) of NZE Schools. However,

in practice, the EUI is at least reduced to half of the building codes. A rule of thumb from a study of current NZE Schools limits the EUI between 20 and 35 kBtu/sqft-yr. The number is dependent on the geographical location and climate zone.

On average, schools in the US consume around 75 KBtu/SqFt/Yr. The US

Department of Energy (DOE) states that nationally K-12 schools spend over $6 billion each year on the energy. DOE indicates that at least 25 percent reduction in energy consumption can be achieved through smart energy management (Energy Star, 2014).

The American Society of Heating, Refrigerating and Air Conditioning Engineers

(ASHRAE) in conjunction with The American Institute of Architects AIA, US Green

Building Council (USGBC), and DOE have developed a strategy that designed to achieve 50% energy savings for K-12 schools compared to ASHRAE 90.1 2004. This strategy is essentially a path towards net zero energy buildings that can be used in the early design phase of new schools (ASHRAE, 2011). In general, for a school to become net zero, the energy consumption must be cut in half compared to a conventional school.

Table 2-2. NREL definitions for NZE buildings considering source of renewables NREL definitions of net zero energy buildings ZEB A utilizing renewable energy strategies within building footprint ZEB B utilizing renewable energy strategies within the property site ZEB C utilizing renewable energy within the property site but from off-site resources ZEB D importing renewable energy that is generated outside property lines

Net Zero Energy Ready Schools

Near zero energy schools and net zero ready schools are the schools that are very close to being net zero energy, or they are designed to become net zero by implementing or adding renewable sources of energy in the future. In 2007, the

European Council for Energy Efficient Economy (ECEEE) set a target in its Article 9 of

Energy Performance of Buildings Directive for achieving “nearly-zero energy buildings” for all new buildings in 2020 (ECEEE, 2011). This nearly zero energy building term was defined as a building with very good energy performance. The very-low quantity of energy needed should be covered from renewable source of energy produced on-site or nearby. This is a suitable definition for near zero energy schools. However, an important question is how close they are to being energy neutral. The near zero energy term covers a wide range of low energy buildings and some may outperform existing zero energy buildings in their energy consumption while others are far removed from best practices. This ambiguity can be attributed to the difficulty in ranking projects due to the wide criteria involved in energy performance of a property relative to its peers, taking into account the climate, weather, and business activities. Regarding schools, the

Energy Star rating system adjusts and normalizes its score based on school building size, number of computers and refrigerators, schedule of school on weekends and summer, energy used for cooking, type of the school (for example high school), dominant climate, and heating and cooling degree days, as well as the percent of the building that is heated and cooled (Energy Star Portfolio Manager Technical

Reference).

The current sustainable design practices in the field of green schools have led to the design and creation of many net zero energy ready K-12 schools in the US. These energy efficient schools are either designed as a net zero capable school that are waiting for funding for the installation of solar panels in the future and they have a very close performance to an energy neutral building. Schools such as Pflugerville

Elementary School in Pflugerville, Texas and the Richard J. Lee Elementary School in

Dallas, Texas are good examples of NZE-ready schools (Building Design +

Construction, 2013). These schools are designed to have a great energy performance, but they are not energy neutral mainly due to the high cost of renewable energy systems.

The State of the Art of NZE Schools

School facilities are known to have better potential for adopting net zero strategies and benefiting from sustainable design compared to other building types.

Several reasons including seasonal occupation and partial daily use, large sites and roof area, community owned and educational land use that ends up in less energy consumption, make schools a suitable target for achieving energy neutral goals (Hutton,

2011). There are over a handful of NZE schools in the U.S and some more under construction. Most of them are fitted in the “ZEB B” category of the NREL definition as a building that utilizes renewable energy within the property site. These state-of-the-art cases were claimed or designed to be zero energy. However, most of them are not verified by a third-party verification system like Living Building Challenge (LBC).

Undoubtedly, these buildings are super-energy-efficient and can treat as a role model for other school projects.

The schools in the table 2-3 are collected through reliable websites, case studies, and published research papers. The net zero energy schools under 10,000 square feet

(929 m2) such as, Prairie Hill Learning Center in Roca, Nebraska; Watkinson School in

Hartford, Connecticut; Bertschi School Science Wing in Seattle, Washington; Hood

River Middle School in Hood River, Oregon; Lenawee Intermediate School in Adrian

Township, Michigan, are excluded from the table due to their small size. Net zero energy educational facilities like labs, university buildings, and administration buildings are also not included in this table, since K-12 schools are the center of attention here.

Energy Lab at Hawaii Preparatory Academy; Lenawee Intermediate School District

Center for a Sustainable Future; and George LeyVa Middle School Administration

Building are some examples.

Table 2-3. US net zero energy schools No Name Year Location Area # Students Annual Site . Completed EUI 1 Putney School 2009 Putney, Vermont 16,800ft² 215 11 kBtu/ft² Field House 1,560m² 38kWh/m² 2 Marin County 2010 Corte Madera, 33,000ft² 540 25 kBtu/ft² Day School California 3,065m² 82kWh/m² 3 Hayes Freedom 2010 Camas, 20,500ft² 153 23 kBtu/ft² High School Washington 1900m² 76kWh/m² 4 Richardsville 2010 Bowling Green, 20,500ft² 600 18 kBtu/ft² Elementary Kentucky 1,900m² 60kWh/m² 5 Sangre de Cristo 2011 Mosca, Colorado 80,000ft² 400 22 kBtu/ft² 7,430m² 73kWh/m² 6 Kiowa County 2010 Greensburg, 132,000ft² 370 29 kBtu/ft² School Kansas 12,260m² 95kWh/m² 7 Evie Garrett 2010 Denver, 186,500ft² 1278 26kBtu/ft² Dennis School Colorado 17,320 m² 82kWh/m² 8 Turkey Foot 2010 Edgewood, 133,000ft² 1000 14kBtu/ft² Middle School Kentucky 12,350 m² 44kWh/m² 9 Lady Bird 2011 Irving, 152,000ft² 1000 23kBtu/ft² Johnson Texas 14,120 m² 73kWh/m² 10 Colonel Smith 2011 Fort Huachuca, 88,693ft² 350 15kBtu/ft² Middle School Arizona 8,240m² 47kWh/m² 11 Locust Trace 2011 Lexington, 47,088ft² 250 - AgriScience Kentucky 4,375m² 12 Centennial 2011 Centennial, 60,000ft² 221 14kBtu/ft² School Colorado 5,575m² 44kWh/m² 13 Sandy Grove 2013 Hoke County, 75,930ft² 650 25.6kBtu/ft² Middle School North Carolina 7,054m² 81kWh/m² 14 East Bay MET 2014 New Port, Rhode 16,800ft² 180 - School Island 1,560m² 15 Blackford School 2014 San Jose, - - - California

Table 2-3. Continued No Name Year Location Area # Annual Site . Completed Students EUI 16 P.S. 62 School to be built Staten Island, 68,068ft² 444 34 kBtu/ft² New York 6,320m² 110kWh/m² 17 Cambridge MA - to be built Cambridge, 169,000ft² 740 30 kBtu/ft² MLK School Massachusetts 15,700m² 98kWh/m² 18 New Century to be built Raleigh, 109,758ft² 920 - Elem-Sch North Carolina 10,200m² 19 Richard J. Lee to be built Irving, 95,600ft² - 29 kBtu/ft² Elem-Sch Texas 8,900m² 95kWh/m² 20 Arlington Elem- to be built Arlington, 98,000ft² 630 23kBtu/ft² Sch Virginia 9,000m² 73kWh/m²

Figure 2-5 shows the location of these schools according to the column number in table 2-3. Almost all of them are located in the climate zone 3 to 6. Climate zones 3 and 4 have the most existing NZE-schools.

Climate Number of Zone NZE schools 1 0 1 Very Hot – Humid / Dry 2 0 2 Hot – Humid / Dry 3 7 3 Warm – Humid / Dry / Marine 4 7 4 Mixed – Humid / Dry / 5 4 Marine 6 2 5 Cool – Humid / Dry / 7 0 Marine 6 Cold – Humid / Dry 8 0 7 Very Cold Figure 2-5. US climate zones, Source Climate Zones for US locations from Figure B-1 of ASHRAE 90.1-07

Table 2-4. US NZE school energy strategies

(KW)

dOrientation

rformanceHVAC

StoryBuilding

exchange

igh igh PerformanceEnvelope

Photovoltaic WindTurbines Optimize Multi Daylighting Geo Solar Thermal H High PerformanceLighting High P AutomatedSensors EnergyMonitoring

1 Putney School Field House 37        

2 Marin County Day School 95    

3 Hayes Freedom High-Sch -   

4 Richardsville ES 394       

5 Sangre de Cristo PK-12 -       

*6 Kiowa County School      

7 Evie Garrett Dennis Pre-K12 288        

8 Turkey Foot Middle School 443    

9 Lady Bird Johnson Mid-Sch 550         

10 Colonel Smith Mid-Sch -       

11 Locust Trace AgriScience 175       

12 Centennial PK-12 School -    

13 Sandy Grove Mid-Sch 590 -     

14 East Bay MET School 100 -        

15 Blackford School ------

16 New York P.S. 62 School -          

17 Cambridge MA - MLK 282       

18 New Century Elem-Sch 856      

19 Richard J. Lee Elem-Sch -  -     

20 Arlington Elem-Sch 500 -      - -

*Kiowa County K-12 School is a ZEB D building that means it uses renewable energy generated off site.

Viable Renewable Energy Resources

To comply with the NZE definition for K-12 schools, the use of on-site renewable energy is inevitable. Therefore, for the purpose of this study, a practical view is taken to identify clean energy resources that can be used in Florida to build NZE Schools. The findings illustrate the significant role of solar and biomass in generating renewable energy in Florida due to their potential and availability and the compatibility of their scales and boundaries with the net zero energy definitions.

On-site energy generation from renewable resources is the approach used in almost all NZE buildings. Depending on the boundaries that are defined in the NZE definition, off-site renewables might be acceptable in achieving the NZE status, however, the NZE definition that is used in this study, DOE definition (2015) does not allow the use of off-site energy generation. On-site renewables are preferable in most cases. However, there are practical limitations that can mandate the use of on-site or off-site generations.

The Overview of Energy Production and Consumption in Florida

Non-renewable resources

Florida’s leading end-use energy demands are the transportation sector (36 percent), residential sector (29 percent), commercial sector (24 percent), and industrial sector (11 percent) (EIA, 2015). Tourism is the main reason for the heavy consumption of transportation energy in Florida. Considering the industrial sector, Florida’s energy consumption is relatively low, and for this reason, the per capita energy consumption is among the five lowest states (EIA, 2017). Florida’s crude oil reserves and production are insignificant. There may be substantial reserves in Florida’s western coast, however, in 2006, a ban was established by Congress to protect offshore federal areas

within 125 miles of the coastline from drilling activities. Additionally, there is no significant natural gas and no coal reserves in Florida. These fuels are imported by

Florida from other states and from overseas (EIA, 2017). In the nation, Florida ranks second after Texas in net electricity generation (Figure 6-left), and third after Texas and

California in electricity consumption. Natural gas fuels two-thirds of the net electricity generation in Florida. Both natural gas and coal imported to Florida are mainly used to generate electricity. The industrial sector uses a minor share of the natural gas being imported. Slightly more than 1 percent of the natural gas consumption is by Florida homes for heating and cooking purposes. However, almost all coal demand is for the electric power sector, and its consumption decreased more than 30 percent in the last decade. Nuclear power generation contributes about one-eighth of the state’s electricity supply. But, electricity generation through nuclear plants is expected to decrease over time (EIA, 2017).

Renewable resources

Despite the fact that Florida is one of the five largest energy-consuming states in the US, its energy production using non-renewable and renewable raw resources that exist in the state is substantially low. Electricity generation using renewable resources are shown on the right side of Figure 2-6. Therefore, Florida imports a significant portion of its energy needs which are from non-renewable resources. However, Florida has a great potential for generating energy from renewable resources. In general, there are a few commonly used renewable energy resources available in the nation including, biomass and biofuel (wood and wood waste, municipal solid waste, landfill gas and biogas, ethanol, biodiesel), hydropower, geothermal, wind, solar, hydrogen and fuel cells, and marine and hydrokinetic (NREL, 2017). Unlike fossil fuels, these energy

resources are regenerative and are mostly considered to be infinite in duration. To this date, Florida supplies only a small portion of its energy demand from renewable resources. Of that, biomass resources represent the largest share of energy production through renewables in Florida. The remaining renewable energy generation in Florida is from scattered solar systems around the State and two hydropower generators located in the state’s northern regions (EIA, 2017). Even though Florida ranks third in the US in solar potential, the cumulative solar PV capacity installed ranked 12th in the nation in

2016. Today, substantial growth is planned for the new capacity additions for solar energy. Solar PV is expected to provide more than four-fifths of the additional capacity planned for the state (EIA, 2017).

Figure 2-6. Annual Electricity Generation in California, Florida, and Texas, 2017. Source: EIA (2017)

Renewable Energy Resources Available for Floridan NZE Buildings

There are several renewable energy resources that can be used to offset the energy consumption of a building. However, only a limited number of them can be utilized within the boundaries of the building as stated in the NZE definitions. Therefore,

the definition of NZE buildings and the boundary for the calculations is important and can have significant impacts on the feasible renewable resources for each project.

With the use of National Renewable Energy Laboratory Geospatial Data Science

Maps (NREL, 2017), this study examines the state’s potential for utilizing renewable energy resources. NREL develops and updates a series of maps to support renewable energy development and generation projects. Figure 2-7 is retrieved from the NREL maps and is adjusted for the state of Florida. It presents the capacity of solar, wind, biomass, geothermal, hydropower, marine and hydrokinetic in Florida. It is evident that hydropower, and geothermal are not feasible solutions for energy production in Florida.

There is a need for elevation differences in the topography to generate energy from hydropower. Therefore, Florida with a flat topography, does not meet this requirement.

Geothermal energy is caused by a flow of heat out of the Earth’s hot interior. The heat can be transported by magma flow, conduction, and convection. To run a geothermal powerplant, there should be a coincidence of favorable hydrology and high heat flow from the Earth, which occur only in a few places in the nation. Similarly, considering the average wind speed, generating energy from in-shore winds is not feasible. However, off-shore winds show slightly stronger power capacities. In 2014, Minesto, a Swedish developer of ocean and tidal current technology, started a collaboration with Florida

Atlantic University (FAU) to study the technical, environmental, and economic feasibility of deep current power technology. There are other studies and efforts taken in Florida for utilizing tidal and sea current energy. But, still these technologies have not been commercialized at the utility scale. Additionally, Florida maps indicate a limited capacity for utilizing marine and hydrokinetic sources of energy.

Figure 2-7. The availability and the power capacity of renewable energy resources in Florida. Source: (NREL, 2017)

Despite the resources explained above, solar and biomass are abundant in

Florida. Hence, there is a great potential to capture this renewable energy and transform it into a more usable form, that is electricity. The solar energy in Florida is, on average, between 5 to 6 kWh/m2/Day (NREL, 2017). Solar and biomass are usable within individual building property lines. Most other renewable resources require infrastructure and equipment that cannot be placed in a scale of a building. Compared to other states and considering NZE equation, it is challenging in Florida to reduce the energy use intensity of a building due to the climate conditions. However, the state has a good potential to generate energy from solar and biomass, the two forms of natural energy resources that can be captured within the property boundaries.

Table 2-5 shows the renewable energy resources that can be used in each of the

NREL definition categories. Solar in ZEB A and ZEB B is the same as solar photovoltaic technologies. However, in a utility scale, solar energy can also be

harvested with the use of solar thermal technologies. Florida is one of only four states that generate electricity from solar thermal in a utility-scale (EIA, 2017). However, it is only a fraction of the energy production through other renewables. For ZEB A, a solar

PV system is the only potential resource since the boundary is limited to the building footprint. Although ZEB A is favorable and has the least impact on the environment, it is hard to be achieved in practice. This is due to the low efficiency of the commercial PV systems and the high energy use intensity of most building types. By increasing the boundary to the property line limits, it is possible to achieve ZEB B. An example is

Richardsville Elementary School in Kentucky that uses both roof and a parking shade to place the PV arrays (Pasunuru et al., 2014). Wind turbines can also be placed within the property boundary to achieve a ZEB B. However, efficient wind turbines are sizable and noisy. They are usually placed in a large number within wind farms. Lady Bird Johnson

Middle School site in Irving, Texas is equipped with small wind turbines that produce only a small fraction of the school’s energy consumption (Kibert et al., 2014). Those turbines are not economic and were placed for education purposes. A building can achieve ZEB C status by using biomass and biofuel resources. They include wood and wood waste, municipal solid waste, landfill gas and biogas, ethanol, and biodiesel.

Table 2-5. Renewable energy resources and their suitability for the zero energy building definitions Source Energy Type Boundary Possible Resources Has Potential in Florida

ZEB A Footprint/Roof Solar Solar ZEB B Property Site Solar, Wind Solar ZEB C Property Site Biomass & Biofuels Biomass & Biofuels Solar, Biomass & Hydropower, Solar, Wind, Biomass Biofuels, Marin & ZEB D Off-Site & Biofuels, Marin & Hydrokinetic Hydrokinetic

A ZEB D building type can be achieved by importing renewable energy that is generated outside property lines (Pless & Torcellini, 2010). Technically, there is no limit on the energy consumption of a ZEB D project. ZEB D can be achieved as long as the energy demand is met through the purchase of energy from renewable resources, such as windfarms and solar power plants. The Kiowa County School in Greensburg, Kansas is an example of a net zero energy school that imports its energy needs from renewables outside property lines. The school purchases energy from a windfarm that is located out of the town.

As stated earlier, the DOE 2015 report “A Common Definition for Zero Energy

Buildings”, provides definitions for Zero Energy Building (ZEB), Zero Energy Campus,

Zero Energy Portfolio, and Zero Energy Community. The definitions are only different in the physical boundary they consider for generating energy from renewable resources.

To meet the NZE accounting, zero energy campuses, portfolios, and communities can aggregate the site boundary of the individual properties. Therefore, it is possible to combine the on-site renewable energy among different sites. A campus is defined as a group of building sites in a specific locality owned by an institution. A portfolio includes a collection of building sites that is managed by a single entity. And, a community is a group of building sites in a specific locality. Zero Energy Communities have a better chance of pooling investments from multiple building owners to invest in renewable energy producing systems (DOE, 2015). These definitions do not allow the use of renewable energy certificates or the purchase of energy from renewable resources that are outside their defined boundary. The DOE report introduces a new definition that is suitable for multi-story buildings in dense urban areas, and/or for buildings with

significant energy use intensity that is “Renewable Energy Certificate - Zero Energy

Building (REC-ZEB): An energy-efficient building where, on a source energy basis, the actual annual delivered energy is less than or equal to the on-site renewable exported energy plus acquired Renewable Energy Certificates (RECs)” (DOE, 2015). Considering the DOE definitions, suitable resources to achieve the net zero energy status include resources such as solar, wind, biomass & biofuels only if the raw source is produced within the boundary, and hydrogen & fuel cells, or a combination of them. Hydropower, marine & hydrokinetic, and geothermal plants require greater investments and are generally developed in larger scales. Therefore, it is less likely to utilize them within the boundary of campuses, portfolios, and communities.

In this section, the capacity of solar, wind, biomass, geothermal, hydropower, marine and hydrokinetic energy was questioned in the state of Florida. It is understood that hydropower, and geothermal energy plants are not feasible solutions for energy production in Florida as they both require specific topography and favorable hydrology that does not exist in Florida. Also, generating energy from in-shore winds is not feasible in Florida due to the low strength of the average wind speed. There is a limited capacity for utilizing marine and hydrokinetic energy in Florida and the technologies for capturing this type of energy are yet to be commercialized. On the other hand, solar and biomass are abundant resources in Florida. Therefore, there is a great potential to capture their renewable energy and transform it into electricity. Solar and biomass are usable within individual building property lines hence, are suitable to achieve zero energy buildings (ZEB) type A and B. Most other renewable resources require infrastructure and equipment that cannot be placed in a scale of a school building.

Compared to other states and considering NZE equation, it is challenging in Florida to reduce the energy use intensity of a building due to the climate conditions. However, the state has a good potential to generate energy from solar and biomass.

Feasibility of NZE

A feasibility study of NZE buildings comprises of two main parts: A technical study and a financial/economic study. In the technical feasibility of a NZE school, a series of assumptions and analysis should be taken to evaluate the possibility of achieving a NZE facility regardless of the financial aspects. However, in the economic feasibility, the focus is on the economic parameters that can justify the investment needed to build net zero. The study of the literature presents a limited number of earlier work in this area. Considering the technical attributes of achieving NZE Schools, NREL and DOE have published a few guidelines and reports on school buildings during the last decade as explained in the following section. However, the economic attributes of

NZE Schools, that is the main objective for this study, are less investigated or documented by researchers and industry professionals.

Technical Feasibility of NZE

In 2008, ASHRAE in a collaboration with the AIA, Illuminating Engineering

Society of North America (IESNA), USGBC, and DOE developed an “Advanced Energy

Design Guide for K-12 School Buildings: Achieving 30% Energy Savings Toward a Net

Zero Energy Building” to help owners and designers of K-12 school buildings obtain a minimum of 30 percent energy savings compared to a minimum baseline requirements of ANSI/ASHRAE/IESNA Standard 90.1-1999, Energy Standard for Buildings Except

Low-Rise Residential Buildings. Few years later, in 2011, the next phase of the design

guide was developed under the same collaboration that targets achieving energy savings of at least 50 percent compared to the baseline. The second design guide provides recommendations that if correctly followed, will result in 50 percent energy savings compared to ANSI/ASHRAE/IESNA Standard 90.1-2004 baseline. Later in

2016, the leading authors of the ASHRAE K-12 Design Guides published a technical report on “Technical Feasibility Study for Zero Energy K-12 Schools” that has a goal to show that zero energy schools are achievable using typical construction techniques

(NREL, 2016). These series of earlier work adequately investigated the technical elements of designing NZE schools in different climate zones in the US. Additionally, the growing number of NZE facilities that are listed in the New Building Institute publications (NBI, 2012, 2016, 2018) are an indication of the technical feasibility of such buildings. The review of the previous literature on the technical elements shows that

NZE school buildings are not only technically achievable but also are a very good platform for applying NZE concepts.

The “Technical Feasibility Study for Zero Energy K-12 Schools” by NREL in 2016 is applied to elementary, middle, and high school buildings (Bonnema et al., 2016). The focus of the study is on new school buildings with typical space types including administrative, offices and classrooms, hallways, and restrooms, gymnasiums with locker rooms and showers, libraries or media centers, and food preparation spaces.

Special spaces such as chemistry laboratories, auto shops, and spaces that have extraordinary energy consumption are not considered in the study. The energy models created in the study meet ASHRAE Standard 55-2013 and ASHRAE Standard 62.1-

2007 for thermal comfort and outside air requirements and meet or exceed the Florida

code-compliant models based on ASHRAE Standard 90.1-2013 for energy efficiency in commercial buildings. To analyze the technical feasibility, in the first step, the study develops K-12 school prototypes based on typical school building practices. In the second step, the study determines energy use intensity allowances based on solar availability for the prototypical buildings. In the third step, the study creates and analyzes low-energy models based on the prototypical buildings. And in the last step, the study verifies that the findings should meet or exceed the NZE goal of the technical feasibility study. Earlier ASHRAE studies of 30 percent and 50 percent energy savings for school buildings as well as case studies of current NZE schools were used to determine the state-of-the-art of energy efficiency strategies including these examples

(Bonnema et al., 2016, page vii):

• “Classroom orientation for a long east-west axis

• Enhanced building opaque envelope insulation, window glazing, and overhangs

• Reduced lighting power density (LPD) based on light-emitting diode (LED)

technology

• Use of vacancy sensors to minimize lighting during non-occupied periods

• Enhanced controls for common areas and exterior lighting based on LED

technology

• Daylighting in classrooms, resource rooms, cafeterias, gyms, and multipurpose

rooms

• Exterior LPD reductions

• Plug load reductions and improved controls for shedding loads during

unoccupied periods

• High-performance commercial kitchen equipment and ventilation

• Demand-controlled ventilation and energy-recovery ventilators using dedicated

outside air systems

• HVAC equipment including system configurations

• High-efficiency service water heating equipment and distribution systems.”

To create the prototype model, the study uses the models that are presented in the DOE Commercial Prototype Building Models (DOE, 2014) as the starting point and modifies the models to comply with the NZE best practices. DOE prototypes offer models for typical primary and secondary school buildings. Middle schools typically fall between the two categories hence, there is no need to be modeled separately. Tables

2-6, through 2-8 show some characteristics of the prototype models.

Table 2-6. Feasibility study prototype characteristics, Source: Bonnema et al. (2016) Building Type Primary School Secondary School Size (ft2) 82,500 227,700

Number of 2 3 Floors Number of 650 1200 Students Space Types Art classroom, cafeteria, Art classroom, cafeteria, classroom, classroom, corridor, multipurpose corridor, multipurpose room, kitchen, room, kitchen, lobby, mechanical lobby, mechanical room, media center, room, media center, office, office, restrooms restrooms Wall Steel-framed Steel-framed Construction Roof Insulation entirely above deck Insulation entirely above deck Construction Window Area 35% window to gross wall area 35% window to gross wall area

Percentage Fully heated and cooled Fully heated and cooled Conditioned Heating, Multizone variable air volume Multizone variable air volume (VAV) Ventilating, and (VAV) dedicated outdoor air system dedicated outdoor air system (DOAS) Air-conditioning (DOAS) with zone-level ground with zone-level ground source heat pump (HVAC) System source heat pump (GSHP) in (GSHP) in classroom wings and common Type classroom wings and common areas; packaged single-zone GSHPs in areas; packaged single-zone gym, kitchen, cafeteria, auditorium GSHPs in gym, kitchen, cafeteria

Table 2-7. Space types, Source: Bonnema et al. (2016) Space Type Primary School Secondary School

Auditorium X Art Classroom X X Cafeteria X X Classroom X X Corridor X X Gym X Kitchen X X Library X Lobby X X Mechanical Room X X Media Center X Multipurpose Room X Office X X Restroom X X

Table 2-8. Space type breakdown, Source: Bonnema et al. (2016) Space Type Primary School Secondary School Area (ft2) Percentage of Total Area (ft2) Percentage of Total Auditorium 0 0% 10634 5% Art Classroom 1744 2% 1744 1% Cafeteria 3391 4% 6717 3% Classroom 35464 43% 72668 32% Corridor 17954 22% 57474 25% Gym/Multipurpose Room 3843 5% 34702 15% Kitchen 1808 2% 2325 1% Library/Media Center 4295 5% 9042 4% Lobby 3100 4% 6780 3% Mechanical Room 2713 3% 7364 3% Office 4747 6% 11452 5% Restroom 3444 4% 6780 3% Total 82503 100% 227682 100%

Envelope

The envelope is assumed to be constructed with steel-framed exterior walls, built-up roofs, and slab-on-grade floors. There are some regional variations, but steel- framed walls and built-up roofs are the most common techniques. The steel-framed wall includes layers consisted of exterior sheathing, insulation, and gypsum board. The

exterior wall R-values (h·ft²·°F/Btu) are R-13 for the air films and sheathing, and R-7.5 for insulation, and U-values (Btu/h·ft²·°F) are U-0.064. These numbers are assumed for climate zones 1 and 2 that dominate Florida regions. The roof exterior finish in is assumed to be a single-ply gray ethylene propylene polymer roof membrane with a solar reflectance of 0.3, a thermal absorption of 0.9, and a visible absorption of 0.7. For climate zone 1, the U-Factor and R-Value are U-0.048, and R-20.0 respectively. For climate zone 2 these values are U-0.039, and R-25.0. The building has slab-on-grade floors, which consisted of a carpet and pad layer over an 8-in.-thick heavyweight concrete layer.

Fenestration and infiltration

Building fenestration includes all envelope penetrations used for ingress and egress or lighting such as windows, doors, and skylights. The fenestration to gross wall area is assumed to be 35%. The U-factors and solar heat gain coefficients (SHGCs) and visible light transmittance (VLT) of the windows are assumed to be 1.22, 0.25. and

0.280 respectively for both climate zones 1 and 2. The infiltration that is an indication of the air leakage is calculated to be with a rate of 0.037 CFM/ft2.

Electric lighting

The assumptions on the lighting power densities (LPDs) are shown in the table 2-

9. The classrooms are assumed to have bilevel switch with the daylighting controls that enables dimming the LED lights in the half of the classroom near the windows. The daylight illuminance is assumed to be 431 lux (40 foot-candles), and the lighting controls are assumed to have continuous dimming from 0 to 100 percent using a closed-loop control scheme. The room surface properties are assumed to be a 90 percent ceiling reflectance, a 60 percent wall reflectance, a 35 percent floor reflectance. The exterior

lights are assumed to be controlled by an astronomical clock that turned the lights on when the sun set and off when the sun rose. Also, an energy-saving feature that turned the lights to quarter power from midnight to 6 AM is another assumption.

Table 2-9. LPDs by Space Type. Source: Bonnema et al. (2016) Space Type Feasibility Study LPD (W/ft2) 90.1-2013 LPD (W/ft2) Auditorium 0.50 0.63 Art Room 0.45 1.24 Cafeteria 0.50 0.65 Classroom 0.45 1.24 Corridor 0.40 0.66 Gym/Multipurpose Room 0.75 1.20 Kitchen 0.45 1.21 Library/Media Center 0.45 1.06 Lobby 0.50 0.90 Mechanical 0.40 0.42 Office 0.50 0.98 Restroom 0.50 0.98 Whole Building 0.50 0.87

Table 2-10. Electric Plug and Process Loads. Source: Bonnema et al. (2016) Primary School Secondary School Space Type Area (ft2) Percentage of Total Area (ft2) Percentage of Total Auditorium NA 0.12 Art Classroom 3.78 3.78 Cafeteria 0.30 1.08 Classroom 0.84 0.54 Corridor 0.00 0.12 Gym/Multipurpose Room 0.00 0.12 Kitchen 14.20 12.00 Library/Media Center 0.30 0.54 Lobby 0.00 0.24 Mechanical Room 0.00 0.24 Office 0.30 0.60 Restroom 0.00 0.24 Calculated Whole Building 0.80 0.50

Plug and process loads

The assumptions for the electric plug and process loads are made in a way to represent a space-by-space 40 percent reduction for a NZE school compared to a typical school loads baseline. This baseline is determined by the plug and process loads from the DOE commercial prototype buildings models (DOE, 2014), with a few modifications based on industry feedback. Electric pug and process loads are shown in the figure above. The computer loads are determined based on assumptions for employing 30-W laptops or mini desktop computers and 18-W LED backlit flat-panel monitors. Server is assumed to be energy efficient with approximately 48 W per connected computer with a power usage effectiveness of 1.2, resulting in 58 W per computer. Other assumptions are also made for addressing miscellaneous loads.

Overall, the total plug load for the 73,962-ft² primary school is 58,257 W, or 0.8 W/ft², and for the 210,892-ft² secondary school is 108,742 W, or 0.5 W/ft². These assumptions are similar for all climate zones.

Heating, ventilating, and air conditioning

Plausible assumptions are made for zoning. The classroom wings and most of the central common spaces are assumed to be served by variable air volume (VAV) dedicated outdoor air system (DOAS) for ventilation along with a ground source heat pump (GSHP) in each zone for space conditioning. The specialty spaces with unusual loads (auditorium in secondary school only, cafeteria, kitchen, gym) are assumed to be served by packaged single zone (PSZ) GSHP systems that provided both ventilation and space conditioning. These systems represent best-in-class efficiency. They are also assumed to be connected to the same ground loop as the zone-level heat pumps.

• Packaged Single-Zone Systems: The primary and secondary schools are assumed to have PSZ heat pump systems serving the auditoriums, cafeterias, gyms, and kitchens. The PSZ heat pump systems included direct expansion heat pump coils with a 19.7 cooling energy efficiency ratio (EER) and a 3.7 heating coefficient of performance (COP), 60 percent efficient constant air volume fans with 1-in. water column (w.c.) pressure drop, and differential enthalpy-controlled economizers. Economizers are not used in climate zones 1A, 2A, 3A, and 4A per Standard 90.1-2013 (ASHRAE 2013b). The PSZ units added energy-recovery ventilators (ERVs) in all climate zones with a 75 percent sensible effectiveness, 69 percent latent effectiveness, and a 0.5-in. w.c. pressure drop. The ERVs are equipped with exhaust-only frost control, with a threshold temperature of -10°F, an initial defrost time fraction of 0.083 min/min, and a defrost time increase rate of 0.024 (min/min)/°C.

• Dedicated Outdoor Air Systems: For most of the floor area of both the primary and secondary schools, a DOAS provides ventilation, and a GSHP provides space conditioning. The DOASs provided ventilation air for the classrooms, corridors, library/media center, lobbies, mechanical rooms, offices, and restrooms. The DOASs have a heat pump (a direct-expansion heating and cooling coil) and a VAV fan. The VAV fan has a fan efficiency of 69 percent, a motor efficiency of 90 percent, and a system pressure drop of 4-in. w.c. The DOAS also included ERVs. Each ERV has a 75 percent sensible effectiveness, 69 percent latent effectiveness, and a 0.5-in. w.c. pressure drop. The ERVs are equipped with exhaust-only frost control, with a threshold temperature of -10°F, an initial defrost time fraction of 0.083 min/min, and a defrost time increase rate of 0.024 (min/min)/°C. The heat pump has a cooling EER of 19.7 and a heating COP of 3.7. The ventilation air from the DOAS are delivered to the zone via a VAV terminal unit that is capable of varying the ventilation rate.

• Ground Source Heat Pump System: Each zone served by the DOAS (classrooms, corridors, library/media center, lobbies, mechanical rooms, offices, and restrooms) are assumed to have a two-speed GSHP. The primary school has 22 separate heat pumps; the secondary school has 42. The heat pumps represent best-in-class efficiency levels, with a cooling EER of 19.7, a heating COP of 3.7, and 50 percent efficient constant-speed fans that cycled with the load (0.25-in. w.c. pressure drop). The heat pumps reject energy to a single plant loop that is served by a 90 percent efficient variable-speed pump with 400 ft of head and a loop temperature set point of 69.8°F. The heat-rejection loop includes a boiler to help maintain loop temperature during the winter. The boiler on the loop has a 90 percent efficient natural gas-fired condensing boiler.

Service water heating:

Both the primary school and secondary schools are assumed to have a 90 percent efficient natural gas-fired storage tank water heater. The secondary school has a 90 percent efficient variable-speed circulation pump with 13.1 ft of head. The primary school has no circulation pump.

Energy modeling results

In the NREL technical feasibility study, the energy-efficiency models were analyzed for 15 cities to establish an EUI goal for a NZE school in each of the ASHRAE climate zone. The results of the energy models are summarized in table 2-11. It shows the EUI targets that can meet or exceed the NZE EUI requirements. The figures in the first two rows of table 2-11 represent the energy consumption of primary and secondary school models for climate zone 1A (very hot, humid) and 2A (hot, humid) which are two dominant climate zones in Florida. The NREL study used EnergyPlus Version 8.4 as the engine for the energy modeling, paired with OpenStudio interface to manage input files, simulations, and results. The DOE NZE definition uses source energy in the NZE accounting. This approach considers the on-site energy and applies a site-to-source conversion to estimate the energy losses from the point of extraction to the site. The conversion factors used in the study are taken from ASHRAE Standard 105 Table J2-A

(ASHRAE, 2014).

One of the main concerns in the technical feasibility is to check if there is sufficient space to place renewable energy sources. The main assumption is that a solar PV system is the only source of renewable energy generation to achieve NZE.

This assumption is reasonable considering the information obtained from the verified net zero energy buildings that are built during recent years. The NREL study also

considers the solar potential for each climate to determine if they match the energy consumption figures. To meet the energy demand, it is assumed that up to 50 percent of the rooftop is suitable for the PV installation. Considering the solar radiation in different cities and a PV system with 18 percent efficiency, the amount of roof area needed to achieve the NZE goal for a primary school is calculated in Figure 2-8. This figure shows that the coverage percentage needed for NZE purpose varies in different climates. Mild climates require smaller coverage ratio than zones with very cold or very hot climates. It can be concluded that in almost all climate zones 7 and 8, NZE can be achieved with dedicating less than 50 percent of the roof solar PV systems. This is an achievable objective for school buildings.

Table 2-11. EUI values for NZE schools. Source: Bonnema et al. (2016) Primary School Secondary School Climate Representative City Zone Site Energy Source Energy Site Energy Source Energy (kBtu/ft2.yr) (kBtu/ft2.yr) (kBtu/ft2.yr) (kBtu/ft2.yr) 1A Miami, FL 25.9 76.4 23.1 68.5 2A Houston, TX 24.3 71.1 21.7 63.5 2B Phoenix, AZ 24.7 72.5 21.9 64.3 3A Memphis, TN 23.8 69.0 21.2 61.6 3B El Paso, TX 23.4 67.8 20.7 60.2 3C San Francisco, CA 21.6 61.9 19.0 54.3 4A Baltimore, MD 23.5 67.6 20.9 60.1 4B Albuquerque, NM 23.1 66.6 20.4 58.8 4C Salem, OR 22.4 64.2 19.7 56.4 5A Chicago, IL 24.3 69.9 21.6 62.2 5B Boise, ID 23.2 66.7 20.4 58.4 6A Burlington, VT 24.5 70.1 21.6 61.9 6B Helena, MT 23.5 66.9 20.5 58.4 7 Duluth, MN 25.9 74.1 22.8 65.1 8 Fairbanks, AL 28.7 82.5 25.0 71.5

Roof PV Coverage Percentage 8 Fairbanks, AL 6B Helena, MT 5B Boise, ID 4C Salem, OR 4A Baltimore, MD 3B El Paso, TX 2B Phoenix, AZ 1A Miami, FL Climate Zone and Representative City Representative and Zone Climate 0% 20% 40% 60% 80% 100%

Figure 2-8. Roof PV coverage percentage to achieve NZE status for primary schools, Source: Bonnema et al. (2016)

Economic Feasibility of NZE

Buildings are consuming significant amount of energy, hence regarded as a suitable target for energy savings. During the last century, the concept of energy efficiency has initially gained attention due to utility cost savings (Hakim et al., 2018). In the recent decades, environmental concerns gave more value to energy efficiency practices beyond just cost benefits. Climate change is a serious threat to human beings and mitigating the negative impacts of burning fossil fuels, as a solution, can be ascertained with increasing energy efficiency and the use of renewable resources. The introduction of the NZE strategy is an effective response to the mentioned environmental concerns. Yet, it should be economic to spread.

Several studies of green building economics have expressed little to no added costs to the construction activities for building green (Kats, 2003). In fact, energy efficient buildings can be cost effective through optimized design. The review of literature proves that a NZE building is first, the state of the art of energy efficiency and

then, it offsets its energy consumption through generating renewable energy. (Hakim et al., 2018). In the widespread definition of a NZE building (DOE, 2015), the Department of Energy also emphasizes on energy efficiency of such buildings. The economic consideration of a net zero energy building is project dependent and can be evaluated through an economic feasibility study of a project. In general, construction costs are immediate expenses however, savings are achieved during the operation years through reduced energy bills.

Savings during the operation years are the outcome of two facts. First, cost savings that are resulted by the reduced energy consumption compared to a benchmark level, and second savings due to the value of energy generated from renewable resources. In this study, the differences in the construction costs of a NZE building with a reference prototype, that is a conventional building, is referred to as cost premium or additional upfront capital costs of building NZE. In many cases, the annual savings can offset the cost premiums within few years. Regardless of economic justification of the life cycle cost savings, the cost premiums should be financed in some way. Here, an attempt is made to evaluate the economic factors that affect the premium amounts as well as the financing mechanisms that are needed to facilitate the budget and the construction of such projects.

In practice, the industry requires technical and economic justifications to embrace the NZE concept. The feasibility of NZE buildings is explained in brief in this section and in a more detail in the methodology section. Two main feasibility studies before starting a NZE project are technical feasibility and economic feasibility studies. As explained in the previous section, the review of literature shows that NZE buildings are proven to be

technically possible. However, the main hurdle in developing such projects is if they are economic. Certain building types such as school buildings that are known to have limited operation time and long life, have a better potential to be economic during their life cycle. By creating a decision-making model that embeds economic factors, we can prove the economic justification of a NZE project. The model should incorporate life cycle costing scenarios for selected features that distinguish a NZE project from a conventional benchmark project. In other words, quantities are measured against a benchmark.

Energy conservation is a vital strategy in building net zero energy. Energy conservation measures (ECM), are classified here into passive and active strategies.

Active strategies include energy efficiency technologies. Major subcategories for these classifications can be recognized to create the life cycle models. The goal of developing a model is to question the final decision based on the economic factors. The complexity of the model increases with the increased level of input data. The model requires historical information, assumptions, and predictions that are subject to uncertainties. An example of input can be financial rebates and incentive programs that to this date, over

3,700 entries of similar contents are reported in the Database of State Incentives for

Renewables & Efficiency (DSIRE). In fact, factors that can significantly affect the economics of a NZE project are similar rebates and incentives that might be available for each ECM subcategory. In addition to being energy efficient, a NZE building resides strategies to generate energy through renewable resources. Photovoltaic (PV) systems are considered as the most viable strategy to harvest renewable energy for individual buildings. Traditionally, economics of ECM and PV systems are investigated as

separate systems and not in a collective manner. However, the argument here is to have a holistic view of a single NZE project. All components life cycle costing models can be combined for analyzing the economic status of a single project. Considering a widespread definition of a NZE building, harvesting renewable energies on-site is inevitable to achieve the net zero status.

Energy Renewable Net Zero Conservation Energy Energy Measures Generating Building (ECM) Systems

Figure 2-9. Holistic view of a NZE building

Even though, a NZE project might be economically feasible proven by a model, still the cost premium hurdle can exist. This premium, against a benchmark building (a reference prototype), will need to be financed. It is worth noting that financing costs can alter the economic viability of that investment (Goswami and Kreith, 2015). In this section, the focus is on the financial factors that contribute to the economic justification of NZE projects. Also, mechanisms that can facilitate funds for the execution of NZE projects are further explored. Although the literature review (Chapter 2) does not intend to analyze the economic feasibility, the findings of this part can be incorporated to the feasibility models.

Based on the definitions, NZE buildings are required to be both energy efficient and energy producer from renewable resources. In almost all NZE schools built to this date, the renewable resources used to generate energy is solar and the type of energy generated is electricity. Solar PV systems greatly comply the definitions of NZE that

require a building to generate energy on-site. To meet a preferred level of energy efficiency, passive and active strategies are integrated in the design of any NZE buildings. Passive strategies including building orientation, shading systems, envelop tightness, etc., are usually the least expensive strategies to cut down the energy consumptions hence are favorable. Active strategies include a series of energy conservation measures (ECM) and technologies that can reduce the energy consumption of a building. The examples are heating and cooling systems, lighting systems, etc. Figure 2-10 presents the strategies that exist in a sample NZE building.

The cells highlighted in grey are the ones that can have significant cost differences between the NZE and a typical building. In a life cycle study of a NZE building, LCC models can be created for each one of the ECM. However, a component based LCC analysis can be time consuming and also challenging that requires skills and expertise.

Alternatively, a whole building LCC is a more suitable approach where there is a need to evaluate the costs and benefits of constructing a NZE building during early design phases. The first step in conducting an LCC analysis, explained in the next section, is to determine the true cost premiums or added costs of a NZE building relative to a conventional building. Since this study focuses on the new school buildings, the conventional building is assumed to be a code-compliant school building prototype.

Orientation

Envelope

Passive Strategies Natural Ventilation

Heating, Cooling, Daylighting Energy Conservation Domestic Hot Water Measures

Renewable Energy Lighting Shading Systems Generating Systems Active Strategies (Energy Efficient Technologies) Appliance and Plug

Loads Net Zero Energy Building ZeroEnergy Net Building Automation

Figure 2-10. Net zero energy building components and strategies for energy savings

Net Zero Energy Building Cost Premiums

Earlier research publications and practical case studies of NZE projects have shown many strategies to construct a NZE building. However, there are two principles that remain the same for any NZE project. First, is to reduce the overall energy consumption, and second, is to install renewable energy generation to offset the building energy demand. Each one of these two principles can have cost implication.

Therefore, in a NZE building project, cost premiums are expected, first, to reach a target level of energy efficiency and, second, to generate energy from renewable resources.

The former can be referred to as a building cost premium for achieving energy efficiency, while the latter can be named as the investment upfront costs to generate energy from renewable resources.

There are countless ways to achieve a target energy efficiency. However, there are not many practical methods to generate energy from renewable resources on the individual project site (Ramsey, 2018). Building lot size creates a major constraint for placing renewable energy resources such as wind, hydropower, and geothermal on-site and makes these energy resources impractical. As explained earlier, from different forms of renewable energy, only solar energy can have a practical application for individual building projects. Calculating the costs of different types of solar systems is not a challenging task. There are many sources that can be used to estimate an upfront capital needed for those systems. A more challenging task is to calculate the additional costs of achieving a target level of energy efficiency (Ramsey, 2018). In every construction project, there are many different components that each can contribute to the overall project costs. These components are usually selected by project owners and designers. Estimating the cost implications of the components that are necessary to achieve an energy saving target is challenging and is subject to many assumptions.

There are two common methodologies to estimate this cost premium. First, is to recognize the added costs of the required components that are necessary in achieving a zero energy status. Second, is through a comparison of the cost differences of successfully completed projects. The problem to the second approach is that there are not many completed cases that can be examined for quantifying cost premiums. Also, when studying the actual costs of a completed NZE project, many factors such as location, time of construction, building type, building codes, and project size should be adjusted in the analysis. With insufficient cost data on current NZE buildings, it is hard to determine a good estimate on the cost premium. In this part of the study, a review of

literature is conducted to determine thoughtful estimates for the aforementioned cost premiums.

A study of NZE buildings listed by NBI shows that these buildings are mostly green. Therefore, a part of the cost premium is expected to be caused by the green features. Meanwhile, a few studies of green buildings have shown no statistically significant difference in the construction of building green and the level of green building certificate (Lesniewski et al., 2014; Matthiessen et al., 2004; Morris & Matthiessen,

2007). There are insufficient available cost data and the sample size in most studies is relatively small. Also, there are many intangible factors, such as designer and contractor experience, that influence the costs. These are the barriers in determining the incremental cost of green features from dataset on completed projects. One of the first studies on determining the cost premium for green buildings is conducted by Kats et al.

(2003). They compared the final costs per square foot of green buildings relative to the costs of traditional buildings and estimated an average of two percent cost premium

(Kats et al., 2003). Matthiessen and Morris (2004 and 2007) conducted a similar study with a larger sample size and they concluded a cost increase of 1 to 10 percent. They added that the variation in cost data is so wild that no statistically significant pattern could be found (Matthiessen et al., 2004). In an even larger study conducted by Nyikos et al. (2012), the cost premiums ranged from 2.5 to 9.4 percent and the variation in cost data were not statistically significant (Nyikos et al., 2012).

A study by the Pacific Northwest National Laboratory “Literature Review of Data on the Incremental Costs to Design and Build Low-Energy Buildings” presented a summary of the findings of the literature review on construction cost premiums. The

study stated that the cost premiums raged from 1 to 7 percent for achieving a low- energy building that is 30 to 50 percent more energy efficient compared to a building built to ASHRAE Standard 90.1-2004. The study revealed a premium less than 4 percent in most case studies (Hunt, 2008).

There are a few informal interviews of industry practitioners that present some estimates for the cost premium of NZE buildings. In an example, the Piller & Putz construction estimated a premium between 5 to 15 percent for constructing a high performance building that targets the NZE status. In another example, Brad Liljequist, the former Zero Energy director for the International Living Future Institute stated a cost premium of about 20 percent for the first multi-family NZE building in Issaquah,

Washington. He mentioned that since that project, the cost premium has gone with obtaining more know-how in design and construction industry and with the development of less expensive materials and technology. He mentioned an average cost premium of about 5 to 10 percent in today’s market.

NASA Net Zero Energy Buildings Roadmap published by NREL in 2014 reported that NZE buildings can be cost effective when planned, managed, and verified using innovative, performance-based procurement approach and integrated design. The study discussed a cost premium of 0 to 10 percent with a potential payback periods of 12 to

15 years for constructing a NZE building compared to a typical project based on a limited set of case studies conducted by NBI (Pless et al., 2014).

A recent publication of the Rocky Mountain Institute on single-family homes “The

Economics of Zero-Energy Homes” demonstrates that the cost increase to build a NZE or NZE-Ready home is modest. The study reports incremental costs of about 6.7

percent to 8.1 percent for NZE homes and 0.9 percent to 2.5 percent for NZE-Ready homes (Petersen et al., 2018).

The District of Columbia’s Department of Environment also questioned the costs and benefits associated with net zero energy buildings. They supported the study of

“Net Zero and Living Building Challenge Financial Study: A Cost Comparison Report for

Buildings in the District of Columbia” conducted by NBI and the International Living

Future Institute (ILFI) in collaboration with Skanska construction company (Cortese et al., 2013). Three reference buildings of new office construction, new multifamily construction and office renovation were conceptually modeled. NBI and ILFI provided the appropriate design strategies, while Skanska estimated the costs involved with the various strategies employed. The findings of the study revealed a cost premium of 1 to

12 percent depending on the building type. This premium increases to 5 to 19 percent when including the added cost of PV power supply. Their LCC model presented a return on investment of 6 to 12 percent for the energy efficiency measures alone, and up to 30 percent when factoring tax benefits and renewable energy credits. Tables 2-12 and 2-13 provide a summary of their findings.

Table 2-12. Cost premium ranges to build net zero energy. Source: Cortese et al., 2013 Energy Conservation Net Zero Energy Measures (ECMs) (Renewables with ECMs) Office New Construction 1-6% 5-10% Multifamily New Construction 2-7% 7-12% Office Renovation 7-12% 14-19%

Table 2-13. Net present value (NPV), simple payback (SPB), and return on investment (ROI) to build net zero energy. Source: Cortese et al. (2013) Assumed ECM Only Net Zero with ECM Incremental Cost NPV SPB ROI NPV SPB ROI

Office New $3,790,218 ($396,476) 11 yrs 9.10% $2,672,413 3 yrs 33.80% Construction Multifamily $4,608,518 ($1,772,741) 117.7 5.70% $3,192,398 3 yrs 33.10% New yrs Construction Office $3,464,015 ($137,039) 8.1 12.30% $1,260,704 2.7 yrs 36.80% Renovation yrs

Financing Mechanisms

In corporate finance, the two main financing mechanisms are equity and debt finance. Similarly, in construction industry, equity or debt or a combination of them can provide the required budget to start a project. However, it is not simple to classify financing mechanisms for NZE buildings since the topic includes construction finance, energy efficiency finance, and renewable energy finance. Also, other factors involved such as, the scale and the type of construction projects, ownership status, the availability of fund, etc. can affect the selection of a capital structure for a given project.

In this study, the traditional and innovative financing mechanisms are classified into four categories of financial incentives, equity financing, debt financing, and third-party financing. These methods are briefly explained in the following sections.

Equity financing and debt financing are the two commonly used mechanisms to provide capital for construction projects. Most equity and debt financing structures are similar to the traditional financing methods. The examples are the use of internal funds for equity financing, and the use of bank loans, federal, state, local loans, and the use of bond issuance such as municipality bonds. However, there are innovative debt financing for energy efficiency and renewable energies, such as revolving loans, green

bonds, and property assessed clean energy (PACE) loans to name a few. Apart from the debt financing mechanisms, third-party financing has created rooms for innovation.

The third-party financing mechanisms is a method to bring additional capital to a project.

This capital is often provided by a private investor. Mechanisms such as power purchase agreement (PPA), and lease purchase that might be coupled with energy performance contracting (EPC) are a few examples that enables the third-party financing. Despite most equity and debt financing tools, third-party financing mechanisms are tailored for a specific target. These mechanisms are explained in the following sections. Figure 2-11 summarizes the examples of viable financing mechanisms.

Rebates and Grants Sales Tax Feed-In-Tariff Tax Deductions Property Tax Tax-based Tax Credits Incentives Bank Loans Income Tax (Investment Tax) Accelerated Federal, State, and Qualified Tax Depreciation Local Loans Credit Bonds Production Tax (QTCB) Internal Funds (Capital Budget) Revolving Loans Qualified Energy Equity Financing Federal, State, and Conservation Tax-based Local Bond Bonds (QECB) Revenue Bond Issues Green Bonds Clean Renewable Debt Financing Loans Property Assessed Energy Bonds Clean Energy (CREB) Power Purchase (PACE) Financing Financing Energy

Mechanisms Agreement (PPA) Performance Municipality Bonds Contracting / ESPC Lease Purchase / Solar Lease General Obligation Bonds On-bill Financing Third Party Financing Lease-Lease back

Crowdfunding

Real Estate Investment Trust

Figure 2-11. Traditional and innovative financing mechanisms to fund a NZE building

Monetary rebates and incentives

Monetary rebates and incentives are widely used by policy makers to support the deployment of ECM and renewables. As of 2015, over 48 countries around the world have placed financial incentives to encourage energy efficiency and the adoption of renewable energy strategies (Cox, 2016). In U.S., to this date, over 3,700 entries of similar contents are reported in the Database of State Incentives for Renewables &

Efficiency (DSIRE). Some rebates and incentives might target Energy Conservation

Measures (ECM) and some focus on renewable energy generating systems. Among these systems, Photovoltaic (PV) technology is considered as the most viable strategy to harvest renewable energy for individual buildings.

Financing incentives can be tax-based incentives and/or non-tax related rebates and grants. Tax credits and accelerated depreciations are the key strategies for federal, state, and local governments to incentivize energy efficiency and renewable energies.

Clearly, these incentives benefit tax paying entities such as for-profit organizations and private owners. On the other hand, there are some other rebates that are offered by utility companies to encourage energy conservation and productions through renewables. The irony is that the profits of utility companies are tied to the amount of energy they sell which contradicts to the energy conservation goal. The utility companies’ supports for energy efficiency and renewables are mainly encouraged by a regulated market to support energy conservation. Fortunately, despite the low incentives for some utility companies in certain locations to support renewable energy generation, the sustainability awareness of the corporation leaders and their stakeholders to dedicate a portion of the profit to energy conservation is increasing.

The best examples of non-tax incentives are financial rebates or grants that are mostly offered by product sellers and utility companies. Tax-based incentives are investment-based incentives, capacity-based incentives, and production-based incentive (Ghalebani and Das, 2017). The examples include investment tax credits, production tax credits, and accelerated or bonus depreciation. In general, a particular type of tax credit might be introduced on income taxes, sales taxes, property taxes, capital gain taxes, and depreciation structures. Income taxes, due to a large amount, are a suitable source for designing tax incentives. A common income tax subsidy is the

Solar Investment Tax Credit (ITC). It was introduced by the Energy Policy Act of 2005 to create a 30 percent tax credit for both residential and commercial solar energy systems placed in service from the start of 2006 the end of 2007. This ITC was extended until the end of 2008 stated in the Tax Relief and Health Care Act of 2006. And in 2008, the

Emergency Economic Stabilization Act extended this ITC for additional eight years. As of today, ITC is equal to 30 percent for both residential and commercial projects until

2019 and it steps down to 26 percent and 22 percent in 2020 and 2021 respectively.

After 2021, ITC will be a constant 10 percent for the commercial and utility projects and residential projects are excluded from this tax credit. Under the federal Modified

Accelerated Cost-Recovery System (MACRS), businesses may recover investments in certain property, which includes solar investments, through depreciation deductions.

Recently, the Tax Cuts and Jobs Act of 2017 increased the amount of the bonus depreciation to 100 percent for qualified property acquired and placed in service after

September 27, 2017 and before January 1, 2023 (DSIRE, 2018).

There are a few more policies and mechanisms in some states in the U.S. including Renewable Portfolio Standard (RPS) that requires utility companies to generate a certain amount of energy from renewable sources, Net Metering that credits

PV system owners for the electricity they add to the grid, and Feed-In-Tariff (FIT) that allows PV system owners to receive a set price, above the retail price, for the electricity they generate and add to the grid (EIA, 2013). These mechanisms can directly or indirectly incentivize the installation of renewable energy systems. FIT was first offered in Germany and is more common across Europe. It is offered in limited places in the

U.S.

Equity financing

Equity capital can be a cash on hand or available internal capital that owners use for budgeting a new facility. If the cost of equity is lower than the cost of debt, this mechanism becomes the least expensive option since there is no interest payments of any sort attached to it.

Debt financing

There is a wide range of debt financing mechanisms that can be used to provide a part of, or the entire budget needed to build a NZE project. With a use of economic models, the costs of debt financing and its effects on overall economic outputs can be determined. Clearly, the lower the interest rate, the cheaper the cost of financing and therefore, a better choice for selection.

Two common debt financing tools are loans and bonds. Bonds are very similar to loans in which a sum of money is borrowed and repaid with interest over a period of time. The primary difference is that with a bond, the issuer periodically pays the investors only the interest earned. This periodic payment is called the “coupon interest

payment.” When the bond matures, the issuer returns the face value to the investors.

Bonds are issued by corporations and government entities. Government bonds generate tax-free income for investors, thus these bonds can be issued at lower rates than corporate bonds. This benefit provides government facilities an economic advantage to use bonds to finance projects (Thumann & Woodroof, 2009). Two examples of government bonds that can support the construction of NZE buildings are

Qualified Energy Conservation Bonds (QECB), and Clean Renewable Energy Bonds

(CREBs). There are also a few innovative debt financing mechanisms that can support

NZE buildings. PACE and Green Bond methods are explained below:

The Property Assessed Clean Energy (PACE): It is an innovative mechanism for financing energy efficiency and renewable energy improvements. PACE is available for both residential properties and commercial properties. PACE enables a property owner to finance the up-front cost of energy or other eligible improvements on a property and then pay the costs back over time.

Green Bond: A green bond is a tax-exempt bond issued by federally qualified organizations, multi-national banks, corporations and municipalities to fund and encourage the development of environmentally-friendly projects. The International

Capital Market Association’s (ICMA, 2016) defines Green bonds as “a fund-raising instrument where the proceeds will be exclusively applied to finance or re-finance in part or in full new and/ or existing eligible Green Projects/Instruments”. Green Bonds are becoming an increasingly prevalent form of green finance for a variety of projects such as for renewable energy, urban mass transit systems, water distribution, low carbon buildings, waste and pollution control, industry and energy-intensive commercial, to

name a few. Green bonds offer three main benefits for a country and its environmental goals: (1) it incentivizes the development of sustainable projects by increasing the availability of financial mechanisms, (2) it is a viable tool for incentivizing sustainable investors, (3) it can be a catalyst for further development of domestic capital market and financial systems (Williams et al., 2017). The “Climate Bond Standard” developed by the

Climate Bond Initiative is an example of green bond for low-carbon buildings. It has been created based on existing green building standards.

Third party financing

A third-party lender making a loan to a buyer to purchase an asset is considered a third-party financier. This method is very useful for financing ECMs and NZE projects.

There are many forms of third-party financing which can also lead to a partnership between the owner and the third party. In a particular case, the terms of the contract determine the details of this method. In the following paragraphs, Public Private

Partnerships (PPP or P3) and Energy Performance Contracting (EPC) are briefly explained.

Public–Private Partnership (PPP): PPP is an agreement between a public owner and a private sector for delivery of a project, service or facility by private sector over a specified term. The private sector takes responsibility for design, construction, financing, maintenance and operation of the infrastructure in return for monetary compensation (Koppenjan, 2015). The public owners generally enforce specified level of performance and sustainability requirements and specifications in PPP agreements while private sector brings expertise and innovation to reduce cost and expedite delivery of services (DBIA’s PPP Committee, 2016).

For the NZE buildings, the primary monetary driving force is saving the energy costs which is quite reliable and predictable compared to a captured value from other sectors. While PPP has been popular in public infrastructure projects, fewer cases use

PPP in housing and building construction. One example is a military housing in Fort

Campbell, Kentucky in which the U.S. Army and the housing developer Lend Lease

(US) worked together to design the first “net zero” military housing and efficient maintenance and operating practices in them. The buildings resulted in 54 percent energy reduction and a 27 percent water reduction when compared to a conventionally designed home. The remaining energy is produced with photovoltaic solar panels to achieve a NZE consumption (NCPPP, 2015).

Energy Performance Contracting: In an energy performance contract (EPC), a customer, usually a public owner, enters a contract with an energy services company

(ESCO) to install a series of ECMs. ESCO pays for the ECM improvements and establishes a baseline for the energy usage from which a certain level of energy savings is determined. This level is guaranteed by the ESCO which ensures that the public agency will receive a determined financial savings. In exchange, the ESCO receives a share of the energy savings through efficient operation of the ECMs. The benefits of

EPC are additional upfront capital, guaranteed long-term savings, hedging utility rate, creating jobs, avoidance of deferred maintenance, and enhancement of community sustainability efforts (North Carolina Solar Center, 2014). Two financing mechanisms that usually have energy performance terms are Power Purchase Agreement and Lease

Agreement explained below:

1. Power Purchase Agreement (PPA): PPA is a contract between two parties, one which generates electricity (the seller) and one which is looking to purchase

electricity (the buyer). The PPA defines all the commercial terms for the sale of electricity between the two parties, including when the project will begin commercial operation, schedule for delivery of electricity, penalties for under delivery, payment terms, and termination. A third-party financier will provide the capital to build, operate, and maintain a solar electricity installation for 15 to 20 years. The host customer (building owner) is only responsible for purchasing the electricity produced by the solar system. It is the responsibility of the third-party financier (PPA provider) to assume all risks and responsibilities of ownership. The provider will own, operate, maintain, and clean the system for optimal performance. There are many forms of PPA in use today and they vary according to the needs of buyer, seller, and financing counterparties. PPA Advantages are tax incentives benefits, upfront capital supports, stable and predictable electricity prices, system services agreements, an option to buy the system, and the risk of electricity production on the PPA provider. Its disadvantages are large transaction costs, no ownership of the “clean” energy attributes, extensive negotiation process, requires sizable projects, a need for periodic facility access for the third parties.

2. Solar Lease Agreement: Solar lease is similar to PPA. The key difference is that in a solar lease, the property owner pays a fixed lease payment, which is calculated using the estimated amount of electricity the system will produce, in exchange for the right to use the solar energy system. With a solar PPA, instead of paying a lease amount, the agreement is to purchase the power generated by the system at a set per-kWh price.

Another form of third-party financing that is worth noting here is Lease-

Leaseback Agreement. This is a project delivery method that has seen an increased popularity to deliver educational construction projects in the state of California. In this agreement, a public owner leases a property to a chosen construction company for $1 a year. The company incurs the construction costs. Upon the completion of the project, the owner leases the property back for an amount that includes the construction cost.

A summary of the financing mechanisms to fully or partially support the construction of a NZE school and their advantages and disadvantages are presented in

Table 2-14.

Table 2-14. A summary of the financing mechanism Type Category Sub-category Can be used for Advantages Disadvantage Credits given to taxable entity, Investment Tax Renewables, Historically, has had the highest Taxable income amount, Tax Credit (ITC) Energy Savings income tax credit benefits at the end of the year Production Sales Renewable Tax-based Suitable for utility companies Should be taxable entity Tax Energy Incentives Renewable No sales tax on the renewable Other Sales Tax No sales tax in some states Energy system Rebates Renewable Property Tax and Energy Incentives Renewable Rebates and Grants Energy, Energy Cash, easy use, often instant Low amount, temporary Non Tax-based Savings Renewable Great economic incentives, Incentives, Feed-In-Tariff Limited amount, temporary policy Rebates, Grants Energy secure predetermined rates Renewable Great incentive for non-utility Several disadvantages for utility Net Metering Energy owners of renewables companies

Great source of capital, Simple Not always available, owners take Internal Funds No limits process all risks

Equity Sales Tax, Property For school Using tax-based revenue as a Financing Tax, Utility Tax, buildings this source of existing capital or Communication Defined by Owner holds all risks. can be: Fees internal funds. The process is Service Tax, regulations Requires upfront capital and Tax-based usually simple. Creates Licensing Vehicles Revenue immediate saving costs Revenue Fixed payments and structured to be less than anticipated energy Down payment which limits funds Debt savings, Depreciation and interest Loans Bank Loans No limits for operational expenses and other Financing are tax deductible, The owner priorities. owns the equipment from the start.

Table 2-14. Continued. Type Category Sub-category Can be used for Advantages Disadvantage Federal, State, and Depends on the

Local Loans loan Excess of savings allow the fund Renewables, Require upfront capital, Might take Revolving Loans to be reinvested in additional Energy Savings long to generate savings projects Complex agreements. Require Low and tax-exempt interest rate. input from attorneys, accountants, Depends on the Financing costs can be structured and bankers, which adds Federal Bonds bond to be repaid from positive cash administrative costs and fees. Debt flows. Might require lengthy approval Financing process. State and Local Depends on the Low and tax-exempt interest rate Bonds Bonds bond Renewables, Green Bonds Energy Savings No down payment. Long term Small benefits for leasers. Limited Property Assessed benefits for owners since loan is program availability. Increase Renewables, Clean Energy attached to the propriety. propriety tax bill. Higher interest Energy Savings (PACE) Potential tax credits and rebates. rate. Loan amount is limited to Flexible loan requirements equity the owner has. Can benefit from tax incentives, No ownership of the “clean” energy No up-front capital investments, attributes, High transaction costs, Stable and predictable electricity With Power Purchase Renewable labor intensive negotiation prices, System services provided, performance Agreement (PPA) Energy process, requires a large project, Option to buy the system, The services (e.g. Facility access by third parties is risk of electricity production is Energy Saving necessary borne by the PPA provider Performance Third- Capital lease requires little or no Contracting) party Lease Purchase Renewable down payment, less paperwork, Facility access by third parties is Financing (Solar Lease) Energy and quick approval compared to necessary banks. Lease Lease-back Whole building Eliminates upfront costs. Without Renewable Repayment structures so that the Utilities might be reluctant. performance On-bill Financing Energy payment is lower than the Agreements can be complex. service savings.

Florida Schools Finance and Budgeting

There are a couple of factors that can determine a need for a new school, including city planning and forecasted growth, policies such as School Class Size

Reduction Amendment, age and the condition of current schools to name a few. The

Office of Educational Facilities in the Florida Department of Education provides technical support and information for educational facilities planning, funding, construction, and operations throughout Florida's K-20 Education System (FDOE,

2018). One of their programs is Florida Inventory of School Houses (FISH) that collects data such as, average annual growth, total space, type classrooms, age of facilities, etc.

These data are used to determine a need for a new school. A recent publication of

Florida Legislative Office of Economic and Demographic Research (2017) expresses that new schools are often built in response to a forecasted increase in Capital Outlay

Full-time Equivalent (COFTE). The way capital outlay planning project growth is based on the maximum COFTE student enrolled in the prior 3 years (EDR, 2017).

In Florida from 1999 to 2009, a yearly average of 105 total new K-12 public and private schools were contracted (over two-thirds of them were public) and from 2010 to

2016, on average 36 new K-12 schools were contracted every year (over half of them were private). This trend shows how economic environment can also affect the decision on building a new public school. The Department of Education publications show that from 2014 through present, the construction of new school facilities is accelerating (In the first 9 months of 2016, 16 new public schools and 17 private schools were contracted). The following figures show the historic trend.

120

100

Signed 40

0 New New School Construction Contracts

Dodge Public, excl. charter Dodge Private, incl. charter Figure 2-12. New K-12 school construction by owner type, Source: Dodge Data & Analytics

Signed 20

0 New New School Construction Contracts

Elementary Middle High Figure 2-13. New Public K-12 school construction by school type. Excludes charter schools. Source: Dodge Data & Analytics

In general, public schools use operating and capital funds to finance their programs and services. Operating funds are used for regularly recurring costs of public education including teachers, administrators, books, materials, utilities, etc., whereas, capital funds are used to purchase physical assets, new construction, renovations, building systems and component replacements, furniture and fixtures, etc. In most states, operating funds are collected in an annual basis from fees, taxes, or other public

revenue sources. However, capital funds are often raised through debt and repaid over many years, using the annual revenues to repay the borrowed money. “Capital outlay” is a terminology used by public schools that refers to their capital spending. A section of capital outlay is for school construction (State Capital Spending on K-12 School

Facilities, 2010). School districts create a 5-year educational facilities work plan to determine their needs.

School districts that are fiscally independent can levy their own taxes to raise capital. For example, first a school district identifies the needs for a new building, then estimates the costs, and in the next step goes to voters in a bond referendum to request a tax increase to repay the principal and interest of the bond that will be issued. This is a typical process to raise capital for fiscally independent school districts (almost 90 percent of total districts). In other districts that are fiscally dependent, an appropriation of capital funds is needed from the local municipal or governing entity, and the municipal entity is responsible for raising the revenue to repay debt. In dependent districts, state law determines if there is a need for bond referenda. The law might allow a decision by elected officials without going directly to voters. In US, all states closely regulate these debt limits for both fiscally independent and dependent school districts.

Review of Florida’s Cost per Student Station

A law passed by Florida state in 2016 (Laws of Florida) mandates a study of the cost per student station conducted by the Office of Economic and Demographic

Research (EDR). The cost per student station includes “costs of classroom construction and administrative offices as well as the supplemental costs of core facilities, including required media centers, gymnasiums, music rooms, cafeterias and their associated kitchens and food service areas, vocational areas, and other defined specialty areas,

including exceptional student education areas.” As per Florida Law s. 1013.64(6)(d)2, F.

S., “Cost per student station includes contract costs, legal and administrative costs, fees of architects and engineers, furniture and equipment, and site improvement costs. Cost per student station does not include the cost of purchasing or leasing the site for the construction or the cost of related offsite improvements.” This dollar amount is set as a ceiling or maximum, and its usage is required for the new construction of educational plant space funded by:

• Special Facility Construction Account;

• Public Education Capital Outlay and Debt Service Trust Fund;

• School District and Community College District Capital Outlay and Debt Service Trust Fund;

• Classrooms First Program;

• Non-voted 1.5-mill levy of ad valorem property taxes;

• Classrooms for Kids Program;

• District Effort Recognition Program;

• High Growth District Capital Outlay Assistance Grant Program

Starting from July 1st, 2017, school districts are not allowed to use funds from any sources for new construction that exceeds the statutory maximum cost per student station.

The main part of capital outlay is called Fixed Capital Outlay Expenditure

(FCOE). FCOE funding for Florida Public Schools Capital improvements are collected from federal, state, and local revenues. The primary source of funding for capital projects is local revenues. In 2014-2015, this was 91 percent of the total funding in

Florida. Table and figure below present the history of the total funding based on the

federal, state, and local source. The portion of revenue from each source have fluctuated each year due to the changing policy decisions and economic conditions set by the Legislature and the district school boards. The share of federal funds is less than

0.5 percent each year.

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Federal % State % Local %

Figure 2-14. History of revenue sources for school district capital projects in Florida. Source: School District Annual Financial Reports

FY 2014-15 Local Revenues by FY 2014-15 State Revenues by Type Type All Other, Classroo Racing Impact Fees, 2.40% ms First, Commision, 0.40% All Other, 8.40% 0.80% 2.90%

Sales Capital Surtaxes, Outlay and 17.40% Debt Service (CO&DS), 14.20%

Public Local Education Capital Capital Improve Outlay ment (PECO), Millage, 81.60% 71.90%

Figure 2-15. Share of revenue sources for school district capital projects in Florida. Source: School District Annual Financial Reports

Considering local funding, the largest part of it comes from the non-voted local capital improvement millage levied by school boards. This millage was about 70 percent of all local revenue sources in the fiscal year 2014-2015. As of today, state law caps this levy to 1.5 mills. This funding is authorized for construction activities, school transportation, and payments for the lease-purchase agreements. Additional 0.25 mills for discretionary capital improvement in lieu of operating discretionary millage can be levied by school boards.

Considering state revenue sources, the Public Education Capital Outlay and

Debt Service Trust Fund (PECO Trust Fund) was the largest source of state funding

(around 80 percent of total state share) in 2014- 15 for school district capital outlay needs. PECO Trust Fund and Lottery revenue bonds are the primary sources of state revenue for public schools fixed capital outlay. These funds are used to support the construction of public educational facilities for school districts, charter schools, the

Florida College and University Systems, and other public education programs. To raise fund, “the Florida Constitution23 authorizes state bonds pledging the full faith and credit of the state to be issued by the State Board of Education to finance or refinance capital projects authorized by the Legislature for the state system of public education. The bonds issued are payable from revenues derived from the Gross Receipts Tax. Bonds cannot be issued in an amount exceeding 90 percent of the amount that can be serviced from the Gross Receipts Tax.” All Gross Receipts Tax revenues are deposited in the PECO Trust Fund. These revenue systems are responsible to pay debt service on outstanding PECO bonds; however, the excess revenue after debt payment may be used for other facility needs.

Figure 2-16 shows FCO appropriations in three main groups of maintenance

(includes repair, renovation, and remodeling), new Construction, and Other Uses. On average 76 percent of total funding is spent to support new construction projects.

Education FCO Appropriations FY 1997 through 2017 Other Uses $417.5M Maintenance $3,779.8M

New Construction $13,091.6M Figure 2-16. Education FCO Appropriation for school district capital projects in Florida

Considering the costs per square foot of the construction activities, Florida DOE has historical data for the previous projects. However, no specific information on maximum amount of costs for a project is provided. Each school district determines the needed capital for its construction activities through a series of surveys and also forecasts these costs for a few years in the future considering the need for growth, and economic effects such as inflation. The capital that a district needs is subject to limitations on the availability of funds and maximum amount allowable for the district.

The Florida Department of Education provides monthly disbursements to local school districts based on available revenues, which are allocated by statutory formulas.

Information on how these amounts calculated are given in detail in Florida Department of Education “Funding for Florida School Districts” (2017).

Historically, traditional contract methods (design-bid-build), are the main methods of delivering a new school facility. Contracts and their methods are under

responsibilities of the Office of Contracts and Procurement in Florida Department of

Education. They also manage the processes for executing, amending, and monitoring implementation of contracts on behalf of the department. This office also is responsible for following its duties in accordance with state and federal laws and rules. The 2017

Florida Statutes 1013.45 determines the condition of educational facilities contracting and construction techniques. Different delivery methods including design-build, construction management, etc. are allowed. However, certain regulations are determined for the contracts. For example, “procedures applicable to construction management contracts and the design-build process must conform to the requirements of s. 287.055. A board may not modify any rules regarding construction management contracts or the design-build process.” A review of available data for school construction activities provided by Florida Department of Education, also shown on table 2-15, presents that during 2012 to 2015, between 10 to 30 percent of school construction projects were contracted under design-build delivery method. The design-build delivery method is a more suitable method in delivering a NZE school project compared to the traditional hard bid.

Table 2-15. Number of Design-Build school projects in Florida during 2012 to 2015 K-12 School Projects Year No. of Design-Build Projects Total Projects Share 2015 5 38 13% 2014 3 32 9% 2013 10 34 29% 2012 5 56 9%

CHAPTER 3 METHODOLOGY

To analyze the economic feasibility of NZE schools, a decision-making tool is modeled with the use of Microsoft excel software. The goal of this tool is to serve as a

Net Zero Energy Decision Support System (NZE-DSS) for public school districts in

Florida. The model enables a user to perform a life-cycle costing analysis (LCCA) of a test NZE school. The model gets economic and technical inputs from both a reference school and a NZE school subject to the feasibility analysis. This study uses NZE school prototypes presented in recent NREL publications (Bonnema et al., 2016). However, the prototype inputs can also be modified for any specific cases. A series of economic and technical inputs are explored in this chapter. In the model, quantities are measured against a reference benchmark that is a code-compliant school building prototype. The initial information for building a reference school is obtained through the review of literature and reliable publications provided by the NREL and DOE. The model enables sensitivity analysis and scenario analysis for the assumptions that are subject to uncertainty. The LCCA methodology used in this study is a method for assessing the costs of facility ownership through the life of a facility. As explained, this study focuses on cost differences between a selected NZE school project and a reference benchmark model. It includes construction costs, operation and maintenance costs, PV systems costs, and financing costs. Figure 3-1 presents the main feeding elements of the NZE-

DSS. The model outputs are shown in figure 3-2.

Third-party Financing Debt Construction Financing Costs

Equity LCCA Financing

Rebates & NZE- Energy Incentives DSS Modeling

Figure 3-1. The main feeding elements of the NZE-DSS

Scenario Analysis Assess Sensitivity Financing Analysis Costs

User- Value friendly Engineering Interface

Early To Go Stage NZE- NZE / No Feasibility Go NZE Analysis DSS

Figure 3-2. The main outputs of the decision support system

It is important to know that the accuracy of the outputs are greatly depending on the accuracy of the input information. Therefore, a special attention is given to the input assumptions of the model. In this study, a comprehensive review of earlier work contributes to choosing right inputs and adopting right assumptions. In addition, this study collected experts’ opinions from a local solar company along with feedbacks from the Alachua county school board to ensure the accuracy of the inputs. Figure 3-3 represents the path taken to ensure the accuracy and usability of the outcomes.

Feedbacks Review of Expert Inputs from a School Earlier Work District

Figure 3-3. Ensuring the accuracy of the model inputs

The main assumptions are categorized in Figure 3-4. As it can be seen in the figure, a series of assumptions are necessary for conducting the analysis. These assumptions are divided into three main categories of technical, economic, and financing assumptions. The details of these assumptions are explained in the following sections of this chapter.

A series of sensitivity and scenario analysis are performed to consider the effect of uncertainties in several input parameters. In most parts, this study has a deterministic approach in structuring the LCC analysis. However, in one section, this study uses a stochastic method to provide more information about potential future outcomes, thereby improving the analysis results. The details of the methods used are explained in the

Analysis Chapter (Chapter 4).

Model Assumptions

Literature Expert Judgment Review

Technical Financing Economic Assumptions Assumptions Assumptions

K-12 School Rebates and Solar PV System Term of LCC Building Incentives

Reference School PV System Solar Radiation General Inflation Equity Construction Info Technical Details Assumption Rate

NZE School Energy System Size Debt Construction Info Escalation Rate

Degradation Assumptions PV Efficiency Third-Party Discount Rate

Replacements Assumptions PV Degradation Energy Rates

Construction Derating Factors Costs

Panel Size PV Costs

Operation and Maintenance Costs

Figure 3-4. An overview of NZE-DSS assumptions

Technical Assumptions

To perform the WBLCC, the NZE-DSS needs technical information related to the main components of a NZE school, that are the school building and the PV system, as well as, technical inputs related to the reference school building. This study uses school building prototypes for both NZE and the reference school. Both prototypes are adopted from the earlier studies of the NREL and DOE. The below sections present information on these prototypes.

Building Prototypes

Reference K-12 school prototype

Two attributes of a reference model are important to feed the NZE-DSS. The first is the estimated costs of the reference model as explained later in this document, and the second is the energy use intensity of it. The reference model is based on a typical new school building in a specific location. This study uses a code-compliant school model prototype used by the Department of Energy. The prototype models are created for the purpose of benchmarking energy analysis. A new construction project for a typical school building should meet the minimum requirements of code systems, therefore, using recent code-compliant prototypes is a rational assumption. The prototypes used should comply the latest energy efficiency requirements adopted by

Florida Buildings Codes. Currently, the state requires the commercial buildings to comply with the 6th Edition Florida Building Code, Energy Conservation. This building code is based on the 2015 IECC, referencing ASHRAE Standard 90.1-2013 with Florida specific amendments.

The EUI of the prototype models are calculated and published in detail for each specific US climate zone. This study uses outputs of a prototype model that complies

the 2015 IECC requirements. The model for the city of Miami is used here. Due to a few differences among elementary, middle, and high school building types, the prototypes are separately given for primary and secondary K-12 school buildings. This study uses the primary K-12 school prototype. This assumption is taken for a simplicity purpose and would have minor impacts on the model results if the input data of a secondary school is used. The tables in Appendix A provide more information about the building specifications of the primary school prototype. The following tables present a summary of the energy analysis for the school prototype using the city of Miami climate data.

Table 3-1. The energy use intensity results of the energy analysis of the primary school prototype that complies 2015 IECC using the city of Miami climate data Program Version: EnergyPlus-Linux 8.0.0

YMD= 2015.09.13

Building: Primary School

Environment: Miami Intl Ap FL USA

Report: Annual Building Utility Performance

For: Entire Facility

Total Building Area 6871 m2: Conditioned 6871 Building Area m2:

Total Energy Per Total Building Energy Per Conditioned Energy Area (MJ/m2) Building Area (MJ/m2) (GJ) Total Site Energy 4342.20 631.96 631.96

Net Site Energy 4342.20 631.96 631.96

Total Source 13983.06 2035.08 2035.08 Energy Net Source Energy 13983.06 2035.08 2035.08

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Table 3-2. A summary of the energy analysis of the primary school prototype that complies 2015 IECC using the city of Miami climate data End Uses Electricity Natural Gas Additional District District Water (GJ) (GJ) Fuel Cooling Heating (m3) Heating 0 127.46 0 0 0 0

Cooling 1081.51 0 0 0 0 0

Interior 755.75 0 0 0 0 0 Lighting Exterior 45.54 0 0 0 0 0 Lighting Interior 1293.20 361.03 0 0 0 0 Equipment Exterior 0 0 0 0 0 0 Equipment Fans 343.52 0 0 0 0 0

Pumps 0.18 0 0 0 0 0

Heat 0 0 0 0 0 0 Rejection Humidification 0 0 0 0 0 0

Heat 128.49 0 0 0 0 0 Recovery Water 25.83 87.86 0 0 0 718.47 Systems Refrigeration 64.89 0 0 0 0 0

Generators 0 0 0 0 0 0

Total End 3765.84 576.35 0 0 0 718.47 Uses Note: Natural gas appears to be the principal heating source based on energy usage

NZE K-12 school building

This study uses a NZE prototype for primary schools used in a recent publication of NREL “Technical Feasibility Study for Zero Energy K-12 Schools” (Bonnema et al.,

2016). In Chapter 2, the “Technical Feasibility of NZE School” section discusses the details of this study. The following table presents a summary of the energy analysis of the NREL study for the NZE primary and secondary school prototype. Similar to the previous section, this study uses the EUI of the prototype for the city of Miami.

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Table 3-3. EUI values for NZE schools Climat Representati Primary School Secondary School e ve City Site Energy Source Energy Site Energy Source Energy Zone (kBtu/ft2.yr) (kBtu/ft2.yr) (kBtu/ft2.yr) (kBtu/ft2.yr) 1A Miami, FL 25.9 76.4 23.1 68.5 2A Houston, TX 24.3 71.1 21.7 63.5 2B Phoenix, AZ 24.7 72.5 21.9 64.3 3A Memphis, TN 23.8 69.0 21.2 61.6 3B El Paso, TX 23.4 67.8 20.7 60.2 3C San Francisco, 21.6 61.9 19.0 54.3 CA 4A Baltimore, 23.5 67.6 20.9 60.1 MD 4B Albuquerque, 23.1 66.6 20.4 58.8 NM 4C Salem, OR 22.4 64.2 19.7 56.4 5A Chicago, IL 24.3 69.9 21.6 62.2 5B Boise, ID 23.2 66.7 20.4 58.4 6A Burlington, 24.5 70.1 21.6 61.9 VT 6B Helena, MT 23.5 66.9 20.5 58.4 7 Duluth, MN 25.9 74.1 22.8 65.1 8 Fairbanks, 28.7 82.5 25.0 71.5 AL

Solar PV System, Technical Assumptions

The assumptions used in the NZE-DSS for a typical solar PV system are given in

Table 3-4. These input data can also be modified by a user to provide a better estimate of the PV system power output. Here, a simple energy calculation is performed to estimate the PV power output. Alternatively, a user can use other resources, such as

NREL PVWatts Calculator, to calculate the amount of energy production for the PV system with more details. The average peak sun hours for Florida is assumed to be 5.5 hours. To be more conservative, the average of Florida is used instead of the peak sun hours for the city of Miami.

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Table 3-4. Assumptions for a typical solar PV system used in the model

Technical Data Energy Production

System Size (kW) 386 # of panels 1169

Roof Size (m2) 6875 Energy output of 1 panel (watts) 530

PV efficiency 0.17-0.19 Annual energy production (kWh) 619547

PV degradation 0.75%

Derating factor 0.80

Nominal panel power output (watts) 330

1 Panel size (m2) 1.6

Sun hours (kWh/m2/day) 5.5

Financing Assumptions

Financing assumptions are necessary as they can alter the decision to build

NZE. Chapter 2 discusses financing mechanisms for the development of NZE buildings in more details. Rebates, grants, and tax-based incentives are also discussed in

Chapter 2 as mechanisms that can reduce the overall expenses. However, since public schools are tax exempt, they cannot directly take the advantage of the tax-based incentives. This is a significant issue for public schools considering the current Federal

Investment Tax Credit (ITC) of 30 percent.

Equity financing is defined as a capital available in the district accounts for building new schools. This is not a common source of funding to build a new school in public school districts. Alternatively, debt financing can provide budget for building new facilities and is a common way to raise capital for public school districts. In most cases, municipality bonds are issued to raise the needed capital. Another financing mechanism is third-party financing which engages a private entity that often offers services to ensure energy savings and productions. In most states, there are regulations that allow 103

the third party to benefit from the federal ITC. This study evaluates the effects of a few financing methods in the analysis chapter. The NZE-DSS is adaptable to perform analysis based on equity and debt financing, and the use of FIT.

Economic Assumptions

Economic assumptions include assumptions for the costs of building NZE including construction costs, PV system costs, and the maintenance costs. A series of assumptions are explained here that are required to perform the LCCA.

Term of LCC

School buildings are assumed to last at least 50 years; however, the PV system is usually considered to live between 25 to 30 years until replacement. This study assumes the term of LCC to be 30 years. This variable can be changed in the model and it automatically updates the results.

General Inflation Rate

Two factors are considered in making a proper assumption for the inflation rate.

The first is a use of historic data on the Consumer Production Index (CPI), and second, is the use of reliable sources that forecast this index. This study considers a constant 2 percent inflation rate for the term of the LCC.

Energy Escalation Rate

The two main sources of energy that is consumed by school the school buildings are electricity and gas. The energy modeling of the primary school prototype in Miami shows that less than 15 percent of the end-use energy is provided by gas. For simplicity, this study assumes that the only energy source is electricity. This assumption does not alter the results for a building in Florida since electricity is the main source of energy. The study uses energy escalation rate for electricity adopted from the “Energy

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Price Indices and Discount Factors for Life-Cycle Cost Analysis – 2017” that is an

Annual Supplement to National Institute of Standards and Technology (NIST) Handbook

135. The table 3-5 is provided for the Florida region and the price indices are given relative to the inflation rate. These indices imply an average electricity escalation rate of approximately 2.4 percent. This is a conservative amount compared to an average of

2.8 percent energy inflation based on the historic data on electricity prices.

Table 3-5. Projected fuel price indices with assumed general price inflation rates of 2%, 3%, 4%, and 5%, by end-use sector and fuel type. Census region 3 including Florida. Source: NIST 2017

Electricity Natural Gas Inflation Rate Inflation Rate Year 2% 3% 4% 5% 2% 3% 4% 5%

2018 1.03 1.04 1.05 1.06 1.09 1.1 1.11 1.12

2019 1.07 1.09 1.11 1.13 1.18 1.2 1.23 1.25

2020 1.12 1.15 1.19 1.22 1.28 1.32 1.36 1.4

2021 1.15 1.2 1.25 1.3 1.33 1.39 1.44 1.5

2022 1.20 1.26 1.33 1.39 1.37 1.44 1.51 1.58

2023 1.24 1.31 1.39 1.47 1.4 1.49 1.58 1.67

2024 1.26 1.35 1.44 1.54 1.45 1.55 1.66 1.78

2025 1.30 1.4 1.52 1.64 1.51 1.63 1.76 1.9

2026 1.34 1.46 1.6 1.74 1.56 1.71 1.86 2.03

2027 1.37 1.51 1.67 1.83 1.63 1.8 1.98 2.18

2028 1.40 1.56 1.74 1.93 1.68 1.87 2.08 2.32

2029 1.44 1.61 1.81 2.03 1.73 1.95 2.19 2.45

2030 1.47 1.67 1.89 2.14 1.78 2.02 2.29 2.6

2031 1.50 1.72 1.96 2.25 1.83 2.1 2.4 2.75

2032 1.52 1.76 2.03 2.34 1.87 2.17 2.51 2.89

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Table 3-5. Continued Electricity Natural Gas Inflation Rate Inflation Rate Year 2% 3% 4% 5% 2% 3% 4% 5%

2033 1.54 1.8 2.1 2.45 1.91 2.23 2.6 3.04

2034 1.56 1.85 2.18 2.56 1.95 2.3 2.71 3.19

2035 1.60 1.9 2.26 2.69 2 2.38 2.84 3.37

2036 1.63 1.96 2.36 2.83 2.05 2.47 2.96 3.55

2037 1.66 2.02 2.45 2.97 2.11 2.56 3.11 3.76

2038 1.69 2.08 2.55 3.11 2.16 2.65 3.25 3.97

2039 1.73 2.14 2.65 3.27 2.21 2.74 3.39 4.19

2040 1.76 2.21 2.76 3.43 2.26 2.83 3.53 4.4

2041 1.79 2.27 2.86 3.6 2.31 2.92 3.68 4.63

2042 1.83 2.33 2.97 3.78 2.37 3.02 3.85 4.89

2043 1.87 2.41 3.1 3.97 2.43 3.14 4.03 5.17

2044 1.91 2.49 3.23 4.18 2.5 3.25 4.22 5.47

2045 1.96 2.57 3.37 4.4 2.56 3.37 4.42 5.77

2046 2.00 2.65 3.51 4.63 2.63 3.49 4.62 6.09

Discount Rate

This study uses the Federal Energy Management Program (FEMP) discount rates for 2018 that are valid from April 1, 2018 to March 31, 2019. According to the

FEMP “The procedure specified in 10 CFR 436A, FEMP Life Cycle Cost Methodology and Procedures, for calculating the real FEMP discount rate resulted in a real discount rate of 0.5 percent for 2018, which is lower than the prescribed floor of 3 percent. Hence the 3 percent floor is used as the real discount rate for FEMP analyses in 2018.” This study adopts a similar view on the discount rate. Since the model created uses a nominal discount rate as an input, the nominal discount rate used in the model is calculated assuming the real discount rate is 3 percent. Considering 2 percent for

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general inflation, the nominal discount rate is approximated to be 5 percent. Compared to a nominal rate for a 30-year risk free federal treasury bond, which is approximately 3 percent at the time of this study, the 5 percent discount rate used here has implemented the risk of solar investment with a conservative approach.

Energy Rates

A blended rate of energy can be used in the NZE-DSS models rather than using different rates for gas and electricity. However, of the total energy consumption of the school prototype in Miami, over 85 percent is from electricity and less than 15 percent from gas. This study approximates a blended energy rate equal to the electricity rate.

EPA provides average price of electricity to ultimate customers by end-use sector. For the commercial sector in Florida, the average of electricity rate is around $0.09 to $0.10 per kWh. To be conservative, we consider the lower amount.

Construction Costs

For construction costs, this study estimates the costs using RSMeans cost database on Commercial New Construction. RSMeans provides comprehensive, localized, and up-to-date construction costs to help create reliable estimates. The assembly cost data is used to approximate the cost per square footage of a new school building at the time of this study. This gives an estimate of the construction costs based on the a few general characteristics of an average building type. Alternatively, with the use of Unit costs, a more accurate cost estimation can be done. This will require the use of construction drawings and detailed specifications. As the economic feasibility study is performed in the early design phases, this study uses the Assembly type in RSMeans.

With the use of RSMeans and the data for the year 2018, the cost of an average code- compliant K-12 school in Miami is $118.20 per square foot of the building (without

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considering costs such as furniture, equipment, land costs, etc.). Appendix B includes the cost details obtained from RSMeans. The costs for constructing a NZE school include the PV system costs, that is explained in the next section, and the costs to build an energy efficient school building. The cost premium for the energy efficient building is assumed to be 10 percent. To be conservative, this amount is rather overestimated compared to other studies that were discussed earlier in the literature review chapter.

This 10 percent premium does not include the costs of the PV system.

PV System Costs

NREL publishes cost benchmark for solar PV system. Currently, the latest publication available is the “U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017” by Fu et al (2017). Table 3-6 provides the summary of this publication. The cost of a commercial roof-mounted PV system is approximated to be $1.85 for every watt of the system size in Direct Current (DC). This number is the national average and is a good estimate for the state of Florida.

Table 3-6. US Solar Photovoltaic System Cost Benchmark Summary : Q1 2017 Unit Description

Values 2017 US Dollars (USD) System Sizes In direct current (DC) terms; inverter prices are converted by DC-to-AC ratios

PV Sector Description Size Range Residential Residential rooftop systems 3-10 kW Commercial Commercial rooftop systems, ballasted racking 10kW-2MW Utility-Scale Ground-mounted systems, fixed-tilt and one-axis tracker >2MW

Based on bottom-up modeling, the Q1 2017 PV cost benchmarks are: $ 2.80 per watt DC or $3.22 per watt AC for residential systems $ 1.85 per watt DC or $2.13 per watt AC for commercial systems $ 1.03 per watt DC or $1.34 per watt AC for fixed-tilt utility-scale systems $ 1.11 per watt DC or $1.44 per watt AC for one-axis-tracking utility-scale systems

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Operation and Maintenance Costs

This study assumes the annual maintenance costs of the PV system is 0.5 percent of the PV system total costs. For both the NZE and the reference school the maintenance costs are assumed to be $1.4 per square foot of the building. The building operation includes the energy costs. This is calculated in the model using the EUI times the square footage of the conditioned area times the energy costs.

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CHAPTER 4 ANALYSIS AND RESULTS

Outline

This chapter includes the economic analysis of a NZE K-12 school building prototype in Florida with a use of the NZE-DSS, an excel-based model that is created in this study to make possible to perform a series of economic analysis. The analysis, in most parts, uses deterministic approaches. In a deterministic approach, the output of the model is measured by the assumptions on the parameter values that are kept similar to the initial conditions. A part of the analysis uses a stochastic approach to provide a better estimate for the electricity price as an input value that is subject to high uncertainty. A stochastic approach uses a set of parameters similar to the deterministic approach, however, it also considers probabilities and will lead to an ensemble of different outputs. The analysis chapter includes five parts:

The first part of this chapter presents the results of the economic analysis on the base model with all the plausible assumptions that were explained in the previous

Chapters. Also, a series of sensitivity analysis are included in the first part to evaluate the sensitivity of the model outputs to the input parameters.

The second part of this chapter analyzes the effect of building degradation on the model results.

The third part of this chapter studies the economic feasibility of NZE schools for three future scenarios 2022, 2026, and 2030.

The fourth part includes an analysis of different financing mechanisms.

The fifth part proposes a self-amortizing loan as a financing support mechanism for the development of NZE schools in the state of Florida.

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Part I: Analysis Results

The model has three main spreadsheets. The first one is for the building energy efficiency and it compares the net zero school prototype relative to a reference school prototype. The second one is for the PV system, and the third one relates to the combined system of the building and the PV system. The analysis is run with a series of plausible assumptions previously explained in Chapter 3. Table 4-1 summarizes the economic assumptions used in the NZE-DSS. The economic outputs are Internal Rate of Return (IRR), Net Present Value (NPV), and Payback periods for the energy efficient building, the PV system, and the combined system (i.e. NZE School). The cost premium for the school building is assumed to be 10 percent. This assumption is explained previously in the literature review chapter. The results are shown in Table 4-2.

Table 4-1. A summary of the economic assumptions used in the NZE-DSS. Reference School Building NZE School Building NZE School PV System Assumptions Assumptions Assumptions Term of LCC (Study 30 Term of LCC 30 Term of LCC 30 Period in yrs) (Study Period in (Study Period in yrs) yrs) General Inflation 2% General Inflation 2% General Inflation 2%

Nominal Discount 5% Nominal Discount 5% Nominal Discount 5% Rate Rate Rate FL Region Energy Table 3-5 FL Region Energy Table 3-5 FL Region Energy Table 3-5 Inflation (Escalation) Inflation Inflation (Escalation) (Escalation) Electricity Costs $0.09 Electricity Costs $0.09 Electricity Costs $0.09 ($/kWh) ($/kWh) ($/kWh) Blended Energy $0.09 Blended Energy $0.09 Blended Energy $0.09 Costs ($/kWh) Costs ($/kWh) Costs ($/kWh) Construction costs $118.52 Construction costs $130.37 Installed Cost $1.85 per ft2 per ft2 ($/Watt) Cost Premium 10% Inverter costs $0.10 ($/Watt) Annual Maintenance $1.40 Annual $1.40 Equipment 1 Inverter per ft2 Maintenance per ft2 Replacement Type System $ - System $ - Equipment 1 15 Replacement costs Replacement costs Replacement Year

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Table 4-2. The results of the economic feasibility for the base model Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.2% 7.2% 7.8%

NPV @ Year30 $396,611 $209,588 $606,199

Payback Period 18 21 19 Simple Payback 13 13 13 Period

Table 4-2 presents a few economic measures that are commonly used. The simple payback period is calculated without discounting the future savings. This is why it outperforms the payback period (compounded payback period). The simple payback period is more commonly used in other studies. The IRR, NPV, and Paybacks for the

Energy Efficient Building are calculated by comparing the cost differences between a conventional school prototype and an energy efficient building part of a NZE school prototype. The size of the PV System in the base model is increased by 10 percent to compensate for the PV degradation through years and make sure that the combined system will remain net zero for almost half of the analysis period.

Table 4-3 presents the sensitivity of the economic outputs to the building cost premium amount. This is useful since the cost premium can significantly vary from project to project. This table is useful for a decision maker to estimate the acceptable cost premiums that can trigger a decision to start a NZE school project. It is shown that for premiums above 15% percent, the project is not justified economically since the costs cannot be offset by savings during the 30-year study period.

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Table 4-3. Sensitivity analysis of economic outputs to the building cost premiums Building Initial Building Combined Cost Premiums NPV (30 yrs) IRR Payback NPV (30 yrs) IRR Payback 0% $ 1,273,659 - 0 $ 1,483,247 17.6% 8 2% $ 1,098,250 37.8% 4 $ 1,307,837 14.3% 10 4% $ 922,840 20.1% 7 $ 1,132,428 12.0% 12 6% $ 747,431 13.8% 10 $ 957,018 10.3% 14 8% $ 572,021 10.4% 14 $ 781,609 8.9% 17 10% $ 396,611 8.2% 18 $ 606,199 7.8% 19 12% $ 221,202 6.6% 23 $ 430,789 6.8% 22 14% $ 45,792 5.3% 29 $ 255,380 6.0% 25 16% $ (129,617) 4.3% Over 30 $ 79,970 5.3% 29 18% $ (305,027) 3.4% Over 30 $ (95,439) 4.7% Over 30 20% $ (480,437) 2.7% Over 30 $ (270,849) 4.1% Over 30 22% $ (655,846) 2.0% Over 30 $ (446,259) 3.6% Over 30 24% $ (831,256) 1.5% Over 30 $ (621,668) 3.1% Over 30 26% $ (1,006,665) 1.0% Over 30 $ (797,078) 2.7% Over 30 28% $ (1,182,075) 0.5% Over 30 $ (972,487) 2.3% Over 30 30% $ (1,357,485) 0.1% Over 30 $ (1,147,897) 2.0% Over 30

Similarly, the sensitivity graphs of NPV and Payback to blended energy costs and to discount rates are shown for the combined model in Figure 4-1. To analyze the degree to which the economic outputs are influenced by the major input assumptions, the study creates a dynamic adjusted sensitivity chart that is a useful addition to the

NZE-DSS. The default values for the input variables are dropped and increased by a same amount of 5 percent to analyze the impact of this change on the model outputs.

As a result, we can notice that changes in the electricity costs and discount rates result in the largest changes to the economic outputs. On the other hand, the PV system output and the EUI estimated for the NZE prototype, that are also uncertain measures during the design phase, have less impact on the output results. The adjusted sensitivity chart is shown on Figure 4-2.

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Sensitivity of NPV to Blended Energy Sensitivity of Paypack to Energy Cost Cost $0.16 $0.16 $0.14 $0.14 $0.12 $0.12 $0.10 $0.10 $0.08 $0.08 $0.06 $0.06 $0.04 $0.04 $0.02 $0.02 $- $- 0 10 20 30 $(1,000,000) $- $1,000,000 $2,000,000 $3,000,000

Sensitivity of NPV to Discount Rate Sensitivity of Payback to Discount Rate 12% 12% 10% 10% 8% 8% 6% 6% 4% 4% 2% 2% 0% 0% $(1,000,000) $- $1,000,000 $2,000,000 $3,000,000 10 15 20 25 30

Figure 4-1. Sensitivity analysis of NPV and Payback to blended energy costs and discount rate for the combined model

Tornado Chart: Adjusted Sensitivity Dynamic Chart

NPV ($) $(150,000) $(100,000) $(50,000) $- $50,000 $100,000 $150,000

Electricity Costs ($/kWh) Nominal Discount Rate NZE EUI (kBtu/sqft-yr)

Building Intitial Cost Premiums Category PV System Costs ($/Watt) PV System output

PV System Building Nominal Electricity PV System NZE EUI Costs Intitial Cost Discount Costs output (kBtu/sqft-yr) ($/Watt) Premiums Rate ($/kWh) % Drop $(39,388) $42,757 $43,852 $44,322 $71,407 $(117,458) Default NPV $- $- $- $- $- $- % Increase $32,850 $(42,757) $(43,852) $(45,950) $(68,138) $117,458

Figure 4-2. Adjusted sensitivity analysis of the main input variables

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Part II: Degradation Scenarios

Materials used in any components of construction projects have certain life.

Through time, they are subject to deterioration. As a result, the performance of an energy conservation measure (ECM) used in a building usually changes over the life of the measure. The terms “decay” and “degradation” are used to describe this change.

The energy efficiency studies primarily focus more on measuring energy savings and less on estimating persistence of these savings, which are affected by degradation over the study period (Hoffman et al., 2016). Evaluating building degradation is important for a few reasons. There are many components that will be subject to replacement after their useful service life that can create significant cost impacts. In economic studies, building systems depreciation, mainly due to tax advantages, is important to building owners. This depreciation occurs as a result of the mentioned deterioration.

Furthermore, degradation of building components can cause certain environmental impacts.

In a life cycle analysis (LCA) of a building, the embodied energy of the materials used as well as the operational energy of the building during its lifecycle are estimated to determine the environmental impacts of the building. Rauf and Crawford (2014) explain that previous analyses of energy across the various life cycle stages have evaluated the share of energy consumption for building operation, and the share of energy embodied in initial materials and components. They stated that service life and durability of materials are the main factors for embodied energy associated with maintenance and replacement of building materials over the life of the building. Clearly, durable materials will have longer lifespan thus can decrease the total embodied energy of that component over the life of a building.

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Considering the operational energy, that is the boundary for the NZE calculation, the energy performance of the systems used is a key factor that should be considered in any LCA and NZE analysis. The building components that can significantly increase the energy use intensity (EUI) of a building due to degradation are: the envelope, lighting system, HVAC system, appliance, and building automation systems. It is difficult to measure the effect of degradation since occupant behavior and weather conditions can also alter energy consumptions over time (Thomas et al., 2015). Furthermore, energy performance can decline due to mismanagement (Eleftheriadis & Hamdy, 2018).

Natural degradation increases by building age. Considering the age of the building, historical energy consumption data show a statistically significant effect on the building energy consumption (Ouf & Issa, 2017). Similarly, Aksoezen et al., found a strong interdependence between energy consumption, compactness, and building age using a

CHAID statistical method (2015).

Figure 4-3 shows several key building components that can significantly affect building energy performance. The components that are highlighted in grey have generally a lower service life compared to the building useful life. Therefore, a study of the component degradation and its effects on building EUI is important, especially when there is a goal to maintain a NZE status.

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Orientation

Envelope

Passive Strategies Natural Ventilation

Heating, Cooling, Daylighting Energy Conservation Domestic Hot Water Measures

Lighting Shading Systems Renewables (PV System) Active Strategies (Energy Efficient Technologies) Appliance and Plug

Loads Net Zero Energy Net Energy Zero Building Building Automation

Figure 4-3. Net zero energy building components

Since HVAC systems, and a few sub-components of the envelope have major impacts on the total EUI, this section focuses on these systems. A few other components are also key determinants of the building EUI; however, their useful life is longer than the study analysis period and they present minimum deteriorations through the study period.

Whole Building Degradation

A review paper by Eleftheriadis and Hamdy (2017) have studied the impact of building envelope and mechanical component degradation on the whole building performance. Their study quantitatively reviewed the impacts of this deterioration on the whole building performance. The finding of their systematic literature review shows that the whole building performance is very sensitive to a few deterioration factors, among which the performance degradation of the heating, ventilation and air conditioning

(HVAC) system is the main one. They presented that the impact of these degradation

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on the whole building performance mostly ranges from 20 percent to 30 percent over 20 years, according to the previous studies in the literature.

A recent case study of the impacts of this deterioration on the whole building energy performance by Eleftheriadis and Hamdy (2018) focused on envelope elements and heating system components of a single-family house in Germany. They analyzed the energy performance of the building over 20 years and determined the effects of degradation on the energy performance. Their simulation results showed that over a period of 20 years, the building can consume between 18.4 percent and 47.1 percent additional primary energy due to degradation.

An assessment of degradation of equipment and materials in relation to sustainability measures conducted by Magnuson (2013) evaluated the effect of natural degradation of the building and equipment on the energy performance of the building throughout its life. Magnuson used a dynamic degradation model in the research and reported that equipment will use 27.3 percent more electrical use with a total energy use increase of 15.6 percent at the end of the building life under the degradation scenario.

The study noted that this amount is important to be included in total building energy accounting for accuracy.

Mechanical components

Although HVAC components are protected from extreme outdoor weather conditions, they still degrade due to natural ageing and continuous operation. This degradation is more sever in a case of inadequate maintenance (Griffith et al., 2008).

Most publications focus on the degradation of chillers and boilers. Waddicor et al (2016) consider constant degradation rates for chillers and boilers. For boilers, they assume rates range between 6 percent (low degradation scenario) and 10 percent (high

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degradation scenario) every 10 years. For chillers, they assume degradation rates of 10 percent as a low range and 24 percent as a high range for every 10 years. Griffith et al, use NREL assumptions and propose linear models to predict the degradation rate of various HVAC components including direct expansion (DX) coils, boilers, chillers, heat pumps, constant and variable-volume fans and gas heating coils. They presented one scenario with maintenance and one without for each component.

Another study by Zhou et al. assessed a model for a ground-source heat pump

(GSHP). The finding of the model analysis shows a performance decrease of 12.82 percent after 20 years of operation. The result of a study by Hitachi on turbo chillers in power plants shows that the chiller performance due to degradation decreases by 4.4 percent in the first five years of operation. Eleftheriadis and Hamdy summarize the results of these studies shown on Table 4-4.

Table 4-4.Performance degradation of HVAC components Degradation Degradation Parameter Building Type Source Values Interval (years) Commercial (Waddicor et al., 6%-10% 20 (library) 2016) (Griffith et al., Boiler efficiency 5%-20% 20 Commercial 2008) (Griffith et al., 10%-24% 20 Residential 2008)

Commercial (Waddicor et al., 10%-24% 20 (library) 2016) (Griffith et al., Chiller COP 5%-20% 20 Commercial 2008) (Bannai et al., 4.4%-12% 5 Industrial 2008)

Heat pump SCOP 5%-20% 20 Commercial (Hendron, 2006) (Zhou et al., GS Heat pump SCOP 13% 20 Mixed 2016) (Griffith et al., Fan efficiency 4%-10% 20 Commercial 2008) (Griffith et al., Split AC EER 18%-33% 20 Residential 2008) Electric water heater (Griffith et al., 2%-4% 20 Residential efficiency 2008) General HVAC (Powertron 30% 20 NA efficiency Global, 2017) 119

Envelope

Building envelope degrades through the years of operation. The envelope is exposed to both indoor and outdoor climate that cause this degradation. External factors include solar radiation, extreme temperature, humidity, and pollution.

Eleftheriadis and Hamdy (2018) reviewed the related literature on envelop degradation.

Insulation and windows used in envelope can degrade over time that can result in a gradual increase in the energy consumption of a building. One common way to measure degradation of insulation is the conduction of accelerated climate ageing tests that can be done in a laboratory. Eleftheriadis and Hamdy use 7 sources to create the Table 4-5 that shows the aging test results.

Table 4-5. Performance degradation of different insulation types. Source: Eleftheriadis and Hamdy (2018) Insulation Thermal Measure Degradation Degradation Interval Source Type Values (years) PIR Thermal resistivity 12% 2 (Mukhopadhyaya et (m.K.W-1) al., 2002)

23%-27% 3-6 (Bomberg & Kumaran, 1995) XPS R-value (ft2.hr.F.BTU- 22% 15 (Singh & Coleman, 1.in-1) 2007) Thermal resistivity 18%-26% 3 (Bomberg & (m.K.W-1) Kumaran, 1995) Thermal conductivity 12%-21% 17 (Zirkelbach et al., (W.m-1.K-1) 2011) PUR Thermal conductivity 14%-17% 15 (Pu-Europe, 2006) (W.m-1.K-1) VIP Thermal conductivity 80% 31.6 (Simmler & Brunner, (W.m-1.K-1) 2005) R-value (ft2.hr.F.BTU- 10% 5 (Moletti et al., 2017) 1.in-1)

Note: PIR: Polyisocyanurate; XPS: Extruded polystyrene; PUR: Polyurethane; VIP: Vacuum insulation panel

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A study by Asphaug et al. (2016) evaluates the accelerated ageing and durability of double-glazed sealed insulating window panes and the resulted impact on heating demand in buildings. Degradation of a window can happen due to reduction or loss of low-conductance gas concentration between the window panes. The sealing can deteriorate by their exposure to outdoor climate. They found that several double-pane windows, with aluminum spacers and Super Spacers, have been subjected to accelerated ageing. They measured the concentration amount of the argon gas used between the window layers over time and compared these measurements for traditional aluminum spacer and super spacers. The results show that the traditional aluminum spacer system lost on average 7 percent of its gas concentration. This increases the U- value of the system and causes thermal loss through the windows.

Building components useful life

To estimate the useful life of a building and its systems, there are several sources that can be used. Since depreciation has tax advantages, several studies have identified useful life for building components for the tax accounting. Multiple sources are available to provide useful information for owners and facility managers about the replacement timing of the building components. ASHRAE provides a chart for

“Equipment Life Expectancy” shown on Table 4-6.

Similarly, the Stanford University Land and Buildings publication on guidelines for life cycle cost analysis (2005) provides a table that includes assumptions for useful life of building subsystems presented in table 4-7.

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Table 4-6. ASHRAE equipment life expectancy chart Equipment Item Midian Equipment Item Midian Equipment Item Midian Years Years Years Air Conditioners: Air Terminals: Air-cooled 20 condensers Window Unit 10 Diffusers, grilles, and 27 Evaporative 20 registers condensers Residential single or 15 Induction and fan coil 20 Insulation: Split Package units Commercial through-the 15 VAV and double-duct 20 Molded 20 wall boxes Water-cooled package 15 Blanket 24 Heat Pumps: Air washers 17 Pumps:

Residential air-to-air 15 Base-mounted 20 Commercial air-to-air 15 Ductwork 30 Pipe-mounted 10

Commercial water-to-air 19 Sump and well 10 Roof-top Air Conditioners: Dampers 20 Condensate 15

Single-zone 15 Multi-zone 15 Fans: Reciprocating 20 engines Boilers, hot water (Steam): Centrifugal 25 Steam turbines 30 Steel water-tube 24 (30) Axial 20 Electric motors 18 Steel fire-tube 25 (25) Propeller 15 Motor starters 17 Cast iron 35 (30) Ventilating roof- 20 Electric 30 mounted transformers Electric 15 Heat Exchangers:

Shell-and-tube 24 Controls:

Burners 21 Pneumatic 20

Reciprocating 20 Electric 16 compressors Furnaces: Packaged chillers: Electronic 15

Gas or oil-fired 18 Reciprocating 20 Unit heaters: Centrifugal 23 Value actuators: Gas or electric 13 Absorption 23 Hydraulic 15 Hot water or steam 20 Cooling towers: Pneumatic 20 Radiant Heaters: Galvanized metal 20 Self-contained 10

Electric 10 Wood 20

Hot water or steam 25 Ceramic 34

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Table 4-7. Average life cycle for building subsystems Subsystem Categories Average Life Cycle (Years) Roofing-Tile 80 Roofing-Metal, Concrete 50 Roofing-Membrane, Built-up, Shingle, Bitumen, Foam 20 Building Exteriors, Doors, and Windows (Hard) 80 Building Exteriors (Soft) 20 Elevators and Conveying Systems 25 HVAC-Equipment and Controls 20 HVAC-Distribution Systems 40 Electrical Equipment 30 Plumbing-Fixtures 30 Plumbing-Rough-in 50 Fire Protection Systems 40 Fire Detection Systems 20 Built-in Specialties and Equipment 25 Interior Finishes 15 Foundations Lifetime Subgrade drainage and waterproofing As needed Vertical Elements Lifetime Horizontal Elements Lifetime Interior Partitions As needed Electrical Rough-in Lifetime Site Preparation Lifetime

Economic Analysis of Whole Building Degradation

In the models created in this study, the focus is on the whole building life cycle cost analysis considering two components: first, an energy efficient building as one unit and second, a solar PV system. Performing individual LCCA for individual energy efficiency components is not the focus of this study at this point. Although, the models can be elaborated to perform LCCA for individual energy saving components in future studies. In most LCCA models, components’ degradation is overlooked. However, with a review of the literature on building degradation, this study has made plausible assumptions to consider the effect of degradation on the whole building performance.

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Based on the stated literature, this study assumes a 10 percent drop in energy performance of the whole building every 10 years due to degradation. Also, this degradation is assumed to have a linear trend. Therefore, 1 percent annual drop in the energy performance is assumed for both the reference school prototype and the NZE school prototype. This assumption implies a 30 percent increase in energy use by the end of the analysis period (t=30) for both buildings. The economic results for this change are presented in Table 4-8. The base model has previously considered the effect of PV system degradation; however, the effect of whole building degradation was not considered in the previous sections.

Table 4-8. The results of the init ial economic feasibility model Building PV System Combined No building degradation IRR 8.2% 7.2% 7.8% scenario NPV @ Year 30 $396,611 $209,588 $606,199 Payback Period (years) 18 21 19 Simple Payback (years) 13 13 13 1% degradation per year for IRR 9.1% 7.0% 8.2% both reference and NZE NPV @ Year 30 $556,233 $213,312 $769,545 school Payback Period (years) 17 21 19 Simple Payback (years) 12 13 13

Interestingly, the NPV improved as a result of the increasing gap between the energy consumption of the reference and the NZE school. Both buildings now have worse energy performance, however, a larger gap between annual energy consumption of both buildings is a factor for the improving NPV. Considering the PV system, the size of the system was increased approximately 12 percent to meet the added energy consumption. This resulted in a slightly lower IRR but a larger NPV for the PV investment due to the increased amount of the capital investment required. And for the combined model, the overall economic measures slightly improved.

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PV System Degradation

In this study, the PV system is assumed to degrade 0.75 percent every year. This translate into 22.5 percent less energy production in after 30 years life of the system

(18.75 percent after 25 years). This is a reasonable assumption based on the NREL study of US solar photovoltaic system (Fu et al., 2017). A sensitivity analysis of the economic outputs to PV degradation is presented in Table 4-9.

Table 4-9. Sensitivity of outputs to solar panel degradation PV System PV System Combined Degradation NPV (30 yrs) IRR Payback NPV (30 yrs) IRR Payback Simple Payback 0.00% $272,941 7.7% 20 $669,552 8.0% 19 13 0.25% $256,386 7.6% 20 $652,997 7.9% 19 13 0.50% $236,661 7.4% 20 $633,272 7.9% 19 13 0.75% $209,588 7.2% 21 $606,199 7.8% 19 13 1.00% $180,659 7.0% 21 $577,271 7.7% 19 13 1.25% $151,630 6.7% 22 $548,241 7.6% 20 13 1.50% $123,125 6.4% 23 $519,737 7.4% 20 13 1.75% $95,392 6.1% 24 $492,003 7.3% 20 13 2.00% $68,560 5.8% 25 $465,171 7.2% 20 13 2.25% $42,650 5.5% 27 $439,262 7.1% 21 13 2.50% $17,655 5.2% 29 $414,267 7.0% 21 13 Over 30 2.75% ($6,445) 4.9% $390,167 6.9% 21 13 years Over 30 3.00% ($29,575) 4.6% $367,036 6.8% 22 13 years

Part III: Future Scenarios

Historically, building codes have become more stringent on energy efficiency policies for new constructions. This trend shows an upward cost implication for school buildings followed by energy cost savings during the operation years. This is more significant when zero energy targets become a part of building codes. In this section, the study assumes a few future scenarios to test the economic feasibility of NZE schools in Florida in 2022, 2026, and 2030. A hypothetical assumption is that by the year 2030, all new public schools in Florida are required to achieve the NZE status. 125

Thus, a target year is set for 12 years from now. Plausible assumptions are taken to estimate the cost increases during the next 12 years. The cost of the PV system is considered to be separate from the cost of the building. In previous sections, this study analyzes the economic feasibility of NZE for the current study time, 2018. A similar study for 2022, 2026, and 2030 brings insights for the optimized investment time for the

PV system.

Construction Costs Forecasts

Construction costs are expected to increase through time due to a few factors.

Two important factors are the inflation rates and the added costs to comply with new policies. Inflations can be studied per material and equipment costs, and per labor costs. The construction related inflation can be estimated with considering the

Production Price Index (PPI), however, an attempt is made here to estimate the future costs using construction specific indices. The added costs through new policies highly depends on the nature of the upcoming policy. Considering the construction costs, the main policies that affect the costs will be energy codes. New codes can mandate the use of materials with cost premiums to meet the energy saving targets.

From the perspective of school districts, forecasting the capital outlay expenditure is necessary to create educational work plan. However, it is noted in the literature that the current method used by the school facilities does not reflect changes in the construction costs (EDR: Florida Legislative Office of Economic and Demographic

Research, 2017). Although this is not the objective of this research, a brief attempt is made to clarify this problem here. In accordance with the statutory requirement for schools, the cost per student station grows with an inflation obtained from the

Consumer Price Index (CPI) (EDR, 2017). This inflation represents price changes paid

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by general consumers for a variety of services and goods such as shelter, clothing, food, fuels, etc. Clearly, this is not a proper index for capturing price changes in construction materials and services. This method used by Florida Department of

Education is not a suitable method as the construction inflations usually fluctuate more aggressively.

The 2018 North American Construction Forecast Report prepared by the

Oldcastle Business Intelligence presented a few useful historical data and trend for construction costs (Oldcastle, 2018). It presents that in 2018, the expected Real Gross

Domestic Product (GDP) growth is 2.1 percent, unemployment rate will further improve to 4.6 percent, and inflation will be 2.3 percent in the United States. However, the average national construction is expected to grow almost 5 percent in 2018, that is slightly higher than the growth rate in 2017. Similarly, the Turner’s Building Cost Index shows a strong level of construction activity across the US based on the current data.

The fourth quarter of 2017 shows 5.17 percent increase in construction activities compared to the last year. As a result, the constructions costs are also expected to increase with a higher rate compared to CPI inflation. The projection for 2018 indicates around 2-3 percent inflation rate for construction materials. The labor costs are expected to increase by 3-4 percent (Abediniangerabi et al., 2017). Labor shortage is a challenge for the construction industry. This shortage is caused by a lack of skilled labor, inability to hire the younger generation, and strict immigration policies (Ahmadi &

Shahandashti, 2018). Therefore, raising wages is a common strategy to satisfy current labor demand. Considering the forecasts, the available literature only forecasts a few years ahead. Figure 4-4 shows the Engineering News Record (ENR) index for the historical data and a forecast trend for construction prices.

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Figure 4-4. Historical trend and forecast for construction costs. Source: ENR

As shown on the figure, the national construction cost increase rates are higher than the material inflations and lower than the labor inflation. This study does not plan to create a forecast for the construction inflations. However, there is a need to use reliable forecasts that are accessible. There are several price indices that are used for the buildings. Laspeyres index, Paasche index, Fisher index, ENR index, Dow Jones U.S.

Select Home Construction Index, architectural billings index, RSMeans, etc. Since this section of the study seeks index forecasts up to 2030, only long-term forecasts should be considered. However, long-term forecasts for the construction industry is not common due to high price fluctuations in construction market. To forecast future, one method is to use the historical data and consider a similar trend for the next years.

To consider the historical trend, the study used RSMeans Square Foot Cost

Estimator. With the use of RSMeans, an elementary school is modeled with similar assumptions presented for a school building in Chapter 2, also shown in Figure 4-5.

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Then the year built is changed to a year earlier, year by year all the way back to 2008, which is the earliest time that can be selected in RSMeans. This way, a historical construction cost trend is obtained for a specific location.

Square Foot Cost Estimate Report Date: 3/10/2018 Estimate Name: Average K-12 Costs in Miami UF Miami , Florida School, Elementary with E.I.F.S. / Rigid Building Type: Steel Location: MIAMI, FL Story Count: 1 Story Height (L.F.): 17 Floor Area (S.F.): 74000 Labor Type: OPN Basement Included: No Data Release: Year 2018 Costs are derived from a building model with basic components.

FigCosture Per Square4-5. RSMeans Foot: $118.52 Square Foot Cost EstimatorScope differences and market conditions can cause costs to vary significantly. Building Cost: $8,770,796.05 The historic data reveals a 21 percent increase in the construction costs of a % of Total Cost Per S.F. Cost hypotheticalA Substructure elementary school in Miami from 2008 to 2015 shown8.33% in figure7.39 4-6.546,557.43 The A1010 Standard Foundations 3.24 239,394.53 exterior of the buildingFoundation for wall,the CIP,year 4' wall 2016 height, to direct2018 chute, was .148 not CY/LF, available 7.2 therefore1.74 those128,479.15 years Strip footing, concrete, reinforced, load 11.1 KLF, soil bearing 0.99 73,051.98 Spread footings, 3000 PSI concrete, load 100K, soil bearing capacity 0.51 37,863.40 wereA1030 not used. ThSlabis translateson Grade into an annual rate of approximately 3 percent3.97 . This294,088.58 rate Slab on grade, 4" thick, non industrial, reinforced 3.97 294,088.58 canA2010 be used for forecastingBasement Excavation the future trend. However, this is based on historic0.18 data13,074.32 and Excavate and fill, 30,000 SF, 4' deep, sand, gravel, or common 0.18 13,074.32 dBoes Shell not reflect future specific projections. 32.17% 28.51 2,109,373.51 B1010 Floor Construction 0.68 49,966.43 Fireproofing, gypsum board, fire rated, 1 layer, 1/2" thick, 10" steel 0.68 49,966.43 B1020 RSMeansRoof Construction Historic Costs for a Given School 11.11 822,027.52 Roof, steel joists, joist girder, 1.5" 22 ga metal deck, on columns, 10.14 750,678.20 $150.00 Roof, steel joists, joist girder, 1.5" 22 ga metal deck, on columns, 0.96 71,349.32 B2010 Exterior Walls 4.21 311,497.97 $100.00 E.I.F.S., cement board sheathing, 1x8 fascia, R8 insulation, 6" metal 4.21 311,497.97 B2020 Exterior Windows 4.92 364,109.52 Windows, aluminum, awning, insulated glass, 4'-5" x 5'-3" 2.68 198,642.62 $50.00 Aluminum flush tube frame, for 1/4"glass, 1-3/4"x4", 5'x20' 0.93 68,858.23 Glazing panel, insulating, 1" thick units, 2 lites, 1/4" float glass, 1.31 96,608.67 B2030 Exterior Doors 0.7 52,162.96 $- Door, aluminum & glass, with transom, narrow stile, double door, 0.49 36,529.52 2007 2008 Door,2009 steel 182010 gauge,2011 hollow2012 metal, 12013 door with2014 frame,2015 no label,2016 3'- 0.21 15,633.44

FigureB3010 4-6. RSMeansRoof Coverings Historic Costs for a Given School 6.68 494,653.55 Roofing, single ply membrane, EPDM, 60 mils, loosely laid, stone 1.38 101,775.90 Insulation, rigid, roof deck, extruded polystyrene, 40 PSI 3.83 283,305.30 Base flashing, rubber, neoprene, 1/16" thick, 24 ga galv reglet, 24 0.65 47,952.70 Roof edges, aluminum, duranodic, .050" thick, 8" face 0.72 53,618.18 Flashing, aluminum, no backing sides, .019" 0.11 8,001.47 B3020 Roof Openings 129 0.2 14,955.56 Roof hatch, with curb, 1" fiberglass insulation, 2'-6" x 3'-0", 0.09 6,750.94 Smoke hatch, unlabeled, galvanized, 2'-6" x 3', not incl hand winch 0.11 8,204.63

Another historical trend presented by ENR shows a similar trend for the nation.

As it is illustrated in Figure 4-7, on average, the construction costs have increased by an annual rate of 2.8 percent.

Figure 4-7. National Building cost index trend. Source: JLL Research Report, 2017

Alternatively, the study can use the Florida Legislative Office of Economic and

Demographic Research (EDR) cost forecasts. Using the available historic data, EDR forecasts for several national indices from 2000 to 2016 adopted by the National

Economic Estimating Conference held in November 2016. To forecast the cost inflation for school projects, EDR uses “Core construction” index, that accounts for general price changes in both private and public construction, the level of “State and local government investment in K-12 educational buildings”, the “Private nonresidential construction” index, which EDR uses as a proxy for private school construction price changes, as well as the Gross Domestic Product (GDP) deflator for state and local government consumption. They also compared the forecasts with historical data from

RSMeans.

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Figure 4-8 shows the result of the EDR forecasts (EDR, 2017). The indices shown in the chart are all made equal to 100 in 2000 and grown by their respective growth rates.

Figure 4-8. National Price Indices, Historical and Forecasts

This graph shows an increase of 3.2 percent annually for school building costs from 2018 through 2026. This number is very close to the 3 percent inflation that was calculated based on the historical data from the RSMeans.

PV System Cost Forecast

Considering the PV system costs projection, the historic trend consistently shows a downward price trend, however, the trend is far from any linear assumption and it is not possible to create a reasonable forecast based on the historic data. Therefore, the study searches for reliable PV price forecasts, however, different forecasts were found

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to be inconsistent. A study of previously forecasted data reveals significant errors in projecting PV system costs.

Solar analysts illustrate that the US PV market has had several price reduction phases. The first phase was a significant reduction in modules costs, the second was the hardware cost reduction, the third is price reductions due to competitive solar markets, and the fourth is due an effort to reduce soft costs. The PV costs data used in this study are obtained from the NREL PV system cost benchmark Q3, 2017 shown on

Figure 4-9 (Fu et al., 2017).

Figure 4-9. NREL PV system cost benchmark summary (inflation adjusted), 2010-2017 Source: Fu et al. (2017)

A forecast presented by a former NREL solar analyst shown in Figure 4-10 indicates that from 2017 to 2022, average U.S. PV system pricing will drop by 32 percent.

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Figure 4-10. Historical and Forecasted U.S. PV System Pricing by Market Segment. Source: Ben Gallagher, former NREL solar analyst, 2017

Another forecast presented by the Renewable Energy Hub in UK is shown in

Figure 4-11, predicts a 40 percent cost reduction for PV systems from 2018 to 2022

(Renewable Energy Hub, unknown).

Figure 4-11. Price per watt of solar PV. Source: Renewable Energy Hub. Retrieved from https://samsetproject.wordpress.com/2015/07/27/258/

A study of PV costs by US Energy Information Administration (EIA) presented that the costs for utility-scale solar photovoltaic (PV) systems have declined about 10 percent to 15 percent per year from 2010 through 2016. However, it also shows that

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forecasted rates often vary across sources in certain years. The historic trend is pictured in Figure 4-12 (EIA, 2018).

Figure 4-12. Reported utility-scale solar photovoltaic capital costs 2010-2017 (EIA, 2018)

The International Renewable Energy Agency (IRENA) report “The Power to

Change: Solar and Wind Cost Reduction Potential to 2025” projected a continuous rapid growth in solar PV market to between 1,750 and 2,500 GW by 2030 (Taylor et al.,

2016). Their study projected a 57% reduction for the average installed cost of utility- scale PV systems in year 2025 compared to the cost of the system in 2015. Considering a range of uncertainty around cost scenarios, they stated that the cost reduction can be between 45 and 65 percent compared to the 2015 levels. Previously, and for the entire history of solar PV market, the PV costs reduction have been caused by decreases in module prices and the Balance of System (BoS) costs. However, in the future years, the

BoS costs reduction is expected to be the main part of the total cost reduction (IRENA,

2016). Figure 4-13 presents the weighted average historical and forecasted costs utility- scale solar PV systems. Their forecasts for years 2018 to 2025 follows approximately a straight-line pattern.

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0.6

0.5

0.4

0.3

0.2 2015 2015 USD Watt Per

0.1

0 2005 2010 2015 2020 2025 2030 Historical and forecasted

Figure 4-13. Global Weighted Average Costs of Utility-Scale Solar PV Systems 2009- 2025. Source: IRENA, 2016

The SunShot Initiative supported by the Department of Energy sets target for solar electricity. To set a target, reasonable forecasts are needed to estimate the levered cost of solar energy. In their 2030 goal, they set a target plan to reduce the cost of electricity through solar to almost half of its today amount. This translates into around

50 percent cost reduction for the PV system in 2030 compared to 2016. Figure 4-14 shows the SunShot’s 2030 goals (DOE Sunshot, 2016). To conduct the future economic analysis, this study assumes that the SunShot’s 2030 goals are achievable.

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$0.20 $0.18 $0.16 $0.14 $0.12 $0.10

$0.08 USD $0.06 $0.04 $0.02 $- 2016 2020 2030 2016 2020 2030 2016 2020 2030 levered levered costof solar energy in 2016 2016 Cost, 2020 Goal, 2030 Goal

Residential Commercial Utility-Scale

Figure 4-14. LCOE values and SunShot goals for the residential, commercial, and utility-scale sectors. Source: DOE Sunshot, 2016

Economic Feasibility of NZE K-12 Schools Built in 2022, 2026, and 2030

To study the economic feasibility of NZE schools that are built in 2022, 2026, and

2030, future construction costs as well as future PV system costs should be forecasted.

Here, the study assumes the construction costs will rise with the projected construction inflation rate of 3.2 percent based on the EDR forecast that was stated earlier. This is a simple rate due to the way it is calculated, there is no need to compound the numbers.

Figure 4-15 shows the effect of the cost increase for the NZE and the reference school in the model. Since in the economic model, these costs are analyzed against each other, the impact of cost increase is insignificant, considering a similar growth rate for both.

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School Construction Costs Forecast $200.00 $180.00 $160.00 $140.00 $120.00 $100.00 $80.00 $60.00 $40.00 $20.00 $- 2016 2018 2020 2022 2024 2026 2028 2030 2032

Reference School Cost($/sqft) NZE School Cost($/sqft)

Figure 4-15. School construction costs forecast for the NZE-DSS model

This study uses future PV costs shown in Figure 4-16. The assumptions are made according to the earlier section on PV costs forecast. The study assumes that the

PV system costs for commercial buildings will decrease by 30 percent in 2022, and by

50 percent in 2030 compared to the system costs today. A linear trend is assumed for the years in between.

Assumptions for PV System Costs $2.00 $1.80 $1.60 $1.40 $1.20

$1.00 $/W $0.80 $0.60 $0.40 $0.20 $- 2016 2018 2020 2022 2024 2026 2028 2030 2032 Year

Figure 4-16. PV system costs forecast for commercial building scale

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Analysis for the current date: The year 2018

The IRR, NPV, and the Payback period for the building and the PV systems were calculated in the earlier sections. The results for the base model, that are in year 2018, are shown in Table 4-10.

Table 4-10. The results of the economic feasibility for the base model Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.2% 7.2% 7.8%

NPV @ Year30 $396,611 $209,588 $606,199

Payback Period 18 21 19 Simple Payback 13 13 13 Period

Analysis for a future date: The year 2022

The school construction costs and the PV panel costs are adjusted for their future value based on the assumptions presented in the earlier sections. The cost of electricity is assumed to be 10 cents/kWh that is one cent higher than the 2018 assumption. This assumption is made considering a 3.36 percent electricity escalation rate. The construction costs inflation is assumed to be 3 percent while the general inflation is considered to be 2 percent. The panel cost is assumed to be $1.3/watt of the system which follows the pattern in Figure 4-16. All other factors are kept the same as the 2018 model. The results of the analysis are shown in table 4-11.

Table 4-11. Economic outputs for the year 2022 Energy Efficient Combined (Net Zero PV System Building Energy) IRR 8.3% 12.8% 9.9% NPV @ Year30 $504,005 $642,232 $1,146,237 Payback Period 19 11 16 Simple Payback Period 13 9 11

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It can be noticed that the IRR for the school building has slightly changed compared to that of 2018. However, due to a significant PV system cost reduction, the results for the PV system and the combined system have improved.

Since panel future costs are highly uncertain, a sensitivity analysis of the results to the panel cost per watt of the system is shown on Table 4-12.

Table 4-12. A sensitivity analysis of the year 2022 results to the PV system forecasted costs Solar PV System Combined PV Costs NPV (30yrs) IRR Payback PV Costs NPV (30yrs) IRR Payback ($/Watt) ($/Watt) $1.00 $780,903 16.7% 8 $1.00 $1,284,908 10.8% 14

$1.10 $734,679 15.2% 9 $1.10 $1,238,685 10.5% 14

$1.20 $688,456 13.9% 10 $1.20 $1,192,461 10.2% 15

$1.30 $642,232 12.8% 11 $1.30 $1,146,237 9.9% 16

$1.40 $596,008 11.9% 12 $1.40 $1,100,014 9.6% 16

$1.50 $549,785 11.0% 13 $1.50 $1,053,790 9.3% 17

$1.60 $503,561 10.3% 14 $1.60 $1,007,567 9.1% 17

$1.70 $457,338 9.6% 16 $1.70 $961,343 8.8% 18

Analysis for a future date: The year 2026

The results of the analysis for the year 2026 are shown in the Table 4-13. The cost of electricity is assumed to be 12 cents/kWh (~9 c/kWh x (1+3.4%)8). The school construction costs and the PV panel costs are adjusted for their future value. All other factors are kept the same as the 2018 model.

Table 4-13. Economic outputs for the year 2026 Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.9% 17.9% 11.6% NPV @ Year30 $678,339 $980,959 $1,659,298 Payback Period 17 8 13 Simple Payback 12 7 10 Period

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It can be noticed that the IRR for the school building has increased compared to that of 2018. However, due to the PV system cost reduction, the economic outputs for the PV system and the combined system are considerably improved. Table 4-14 shows the sensitivity of the results to the panel cost per watt of the system.

Table 4-14. A sensitivity analysis of the year 2026 results to the PV system costs Solar PV System Combined PV System NPV (30yrs) IRR Payback PV System NPV (30yrs) IRR Payback Costs/Watt Costs/Watt $0.60 $1,216,700 32.1% 4 $0.60 $1,895,038 13.3% 11

$0.70 $1,170,476 27.8% 5 $0.70 $1,848,815 12.9% 11

$0.80 $1,124,252 24.5% 6 $0.80 $1,802,591 12.6% 12

$0.90 $1,078,029 21.9% 6 $0.90 $1,756,367 12.3% 12

$1.00 $1,031,805 19.8% 7 $1.00 $1,710,144 11.9% 12

$1.10 $985,581 18.1% 8 $1.10 $1,663,920 11.6% 13

$1.20 $939,358 16.6% 8 $1.20 $1,617,696 11.3% 13

$1.30 $893,134 15.4% 9 $1.30 $1,571,473 11.0% 14

$1.40 $846,911 14.3% 10 $1.40 $1,525,249 10.7% 14

$1.50 $800,687 13.3% 11 $1.50 $1,479,026 10.5% 14

$1.60 $754,463 12.5% 12 $1.60 $1,432,802 10.2% 15

Analysis for a future date: The year 2030

The results of the analysis for the year 2030 are shown in Table 4-15. The cost of electricity is assumed to be 13 cents/kWh (~9 c /kWh x (1+3.4%)12). The school construction costs and the PV panel costs are adjusted for their future value. All other factors are kept the same as the 2018 model.

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Table 4-15. Economic outputs for the year 2030 Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.6% 22.9% 12.0% NPV @ Year30 $688,009 $1,189,613 $1,877,622 Payback Period 18 6 12 Simple Payback 13 5 10 Period

It can be noticed that the IRR for the school building has slightly increased compared to that of 2018. However, due to the PV system cost reduction, the outputs for the PV system and the combined system have significantly improved. Since panel future costs are highly uncertain, a sensitivity analysis of the results to the panel cost per watt of the system is shown on Table 4-16.

Table 4-16. A sensitivity analysis of the year 2030 results to the PV system costs Solar PV System Combined PV System NPV (30yrs) IRR Payback PV System NPV (30yrs) IRR Payback Costs/Watt Costs/Watt $0.50 $1,388,374 41.1% 3 $0.50 $2,076,383 13.5% 11

$0.60 $1,342,151 34.6% 4 $0.60 $2,030,160 13.1% 11

$0.70 $1,295,927 29.9% 5 $0.70 $1,983,936 12.8% 12

$0.80 $1,249,703 26.4% 5 $0.80 $1,937,712 12.4% 12

$0.90 $1,203,480 23.6% 6 $0.90 $1,891,489 12.1% 12

$1.00 $1,157,256 21.4% 6 $1.00 $1,845,265 11.8% 13

$1.10 $1,111,032 19.5% 7 $1.10 $1,799,042 11.6% 13

$1.20 $1,064,809 18.0% 8 $1.20 $1,752,818 11.3% 13

$1.30 $1,018,585 16.6% 8 $1.30 $1,706,594 11.0% 14

$1.40 $972,362 15.5% 9 $1.40 $1,660,371 10.8% 14

$1.50 $926,138 14.5% 10 $1.50 $1,614,147 10.5% 14

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Limitations of the analysis for the future years

A major assumption holding constant is energy use intensity (EUI) of the reference and NZE building. New building codes can lower the EUI of the new buildings.

At the same time, NZE buildings can also become more energy efficient so that the difference stays similar to the base year. The new building codes can also affect the construction costs. One argument is that this cost implication is already considered in the forecasts used in projecting the future construction cost increase.

The findings of the analysis for the future scenarios

A comparison of the above economic analysis for three future scenarios is discussed in this paragraph. A 10 percent cost premium is considered in all models for the NZE school compared to the reference school. It can be noticed the IRR, and the payback period for the building have not seen a dramatic change in the models for different years. However, the PV system costs have significantly declined from year to year. This created a considerable increase in the figures for IRR, NPV, and the Payback period. As a result, the combined models have seen a remarkable improve from 2018 to

2030. Although the economic results in 2018 are not appealing for a decision maker, the improvements of the figures in 2030 can create a better market for NZE schools. This is especially important considering the EISA Act of 2007. The EISA Act set by the US

Congress requires all new commercial governmental buildings built on 2030 and after to achieve the NZE goal. The results of the future scenarios are summarized in Table 4-

17.

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Table 4-17. A summary of the results of the future scenarios Year of Energy Efficient Combined (Net Zero Output PV System analysis Building Energy) IRR 2018 8.2% 7.2% 7.8% NPV @ Year30 $396,611 $209,588 $606,199 Payback Period 18 21 19 Simple Payback 13 13 13 Period

IRR 2022 8.3% 12.8% 9.9% NPV @ Year30 $504,005 $642,232 $1,146,237 Payback Period 19 11 16 Simple Payback 13 9 11 Period

IRR 2026 8.9% 17.9% 11.6% NPV @ Year30 $678,339 $980,959 $1,659,298 Payback Period 17 8 13 Simple Payback 12 7 10 Period

IRR 2030 8.6% 22.9% 12.0% NPV @ Year30 $688,009 $1,189,613 $1,877,622 Payback Period 18 6 12 Simple Payback 13 5 10 Period

Part IV: Analysis of Financing Mechanisms

The net zero energy decision support system developed in this research provides an analytical tool to assess the economic and financial feasibility of building a NZE school. Since there are costs attached to a selected financing mechanism, that mechanism must be built into the model. Financing mechanisms vary in costs and can alter the decision to start a project. The models that are developed here aim to create a test platform that can be used for analyzing a few different financing methods as explained in this section.

Similar to the previous sections, the model outputs are NPV, IRR, and Payback

Periods. The base model results are based on no specific financing assumptions. This

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is the case when internal funds are used. The model can also analyze the effect of using loans for both building and the PV system separately and combined. For this purpose, a user needs to determine a few financing input parameters.

This study classifies the financing mechanisms according to general finance terms of equity, debt, and third-party financing that is a newer concept. A third-party is often a private entity that signs a contract with the building owners. In addition to providing funding, it can offer services that are determined in the terms of the contract.

Furthermore, there are some incentive-based financing mechanisms such as rebates, and Feed in Tariff (FIT). The model is programed to analyze the effects of a Feed in

Tariff (FIT) contract. The outline for these financing mechanisms are discussed in

Chapter 2. This section aims to analyze the effect of a few financing mechanisms on the economic outputs. In practice, the availability of fund and budget is determined by the policies, owners, macroeconomic factors, and type of projects, and there is not much room for optimizing the selection process of the financing methods. If there are debt financing options to choose from, recognizing the least expensive debt mechanisms are usually straightforward. To better clarify the role of financing methods, this section provides an analysis of a few hypothetical financing scenarios.

1-Equity Financing

Equity capital can be a cash on hand or available capital that school districts have for budgeting a new facility. It can be regarded as the least expensive option since there is no interest payments of any sort attached to it. According to the NREL publication “Financing Options for Solar Installations on K-12 Schools”, although it is unlikely in the current economic environment that a school district has available general- fund resources on hand to purchase a PV system without financing, it is not out of the

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question (Coughlin & Kandt, 2011). Here, the basic economic model is first designed considering that all available funds are internal. Therefore, in building a model for a school funded entirely by equity capital, there is no specific consideration for financing parameters. Table 4-18 presents the outputs of the basic model used for assessing equity financing.

Table 4-18. The results of the base economic feasibility model Energy Efficient Building PV System Combined (Net Zero Energy)

IRR 8.2% 7.2% 7.8% NPV @ Year30 $396,611 $209,588 $606,199 Payback Period 18 21 19 Simple Payback 13 13 13 Period

2-Debt Financing

There is a wide range of debt financing mechanisms that can be used to provide a part of, or the entire budget needed to build a NZE school. Although these debt mechanisms can vary by interest rates, with creating a few changes and simple additions to the base model, the costs of the debt financing and its effects on overall economic outputs can be determined. Clearly, the lower the interest rate, the cheaper the cost of financing and therefore, a better choice for selection.

By assuming a hypothetical loan for funding the PV system with 5 percent interest rate, 15 percent down payment, and 10 years loan term, the economic output changes slightly for the PV system and the combined system. The output of this scenario is shown in Table 4-19.

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Table 4-19. The results of the adjusted model with a debt financing scenario for the PV system Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.2% 8.5% 8.3% NPV @ Year30 $396,611 $209,588 $606,199 Payback Period 18 21 19 Simple Payback 13 17 14 Period

To consider the effect of loan rates on the model results, a sensitivity table is created and presented in Table 4-20. From the table, it is clear that the lower the loan rate gets, the outputs become more attractive. Therefore, a decision process aims at selecting a debt financing with the minimum loan rate. In other words, the rate is the key determinant of the selection process.

Table 4-20. The results of the sensitivity analysis of outputs to loan rate Loan PV System Combined Rate NPV (30 yrs) IRR Payback NPV (30 yrs) IRR Payback Simple Payback 3% $267,116 9.9% 19 $663,727 8.7% 18 13 4% $238,711 9.2% 20 $635,322 8.5% 19 14 5% $209,588 8.5% 21 $606,199 8.3% 19 14 6% $179,762 7.9% 22 $576,374 8.1% 20 14 7% $149,252 7.3% 23 $545,864 7.9% 20 14 8% $118,075 6.8% 25 $514,686 7.7% 21 15 9% $86,247 6.3% 26 $482,859 7.5% 21 15 10% $53,789 5.8% 28 $450,400 7.3% 22 16 11% $20,717 5.3% 29 $417,329 7.1% 22 16 Over 30 12% ($12,948) 4.8% $383,663 6.9% 23 16 years Over 30 13% ($47,188) 4.4% $349,423 6.8% 24 16 years Over 30 14% ($81,985) 4.0% $314,627 6.6% 24 17 years Over 30 15% ($117,317) 3.6% $279,294 6.4% 25 17 years

In another hypothetical loan for the PV system, the term is assumed to be equal to the study period of 30 years, 5 percent interest rate, and with no down payment.

These assumptions are made to check if the energy savings are enough to offset the

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annual loan payments. The results of the analysis are shown in Table 4-21. With considering a 5 percent discount rate and assuming a 5 percent loan rate, we expect a similar compounding effect. Therefore, the model is run again to create a sensitivity table based on different loan rates shown in table 4-22.

Table 4-21. The results of the adjusted model with a debt financing scenario for the PV system Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.2% N/A 9.5% NPV @ Year30 $396,611 $209,588 $606,199 Payback Period 18 1 16 Simple Payback 13 1 11 Period

Table 4-22. The results of the sensitivity analysis of outputs to loan rate Loan PV System Combined Rate NPV (30 yrs) IRR Payback NPV (30 yrs) IRR Payback Simple Payback 3% $363,625 N/A 1 $760,237 10.6% 14 10 4% $288,859 N/A 1 $685,471 10.1% 15 11 5% $209,588 N/A 1 $606,199 9.5% 16 11 6% $126,186 35.0% 7 $522,798 8.9% 17 12 7% $39,053 9.7% 22 $435,664 8.3% 19 13 Over 30 8% ($51,413) 0.1% $345,199 7.6% 20 14 years Over 30 9% ($144,819) -8.4% $251,792 6.9% 23 14 years Over 30 10% ($240,794) N/A $155,818 6.2% 25 16 years Over 30 11% ($338,991) N/A $57,620 5.4% 28 18 years Over 30 Over 30 12% ($439,095) N/A ($42,484) 4.7% 19 years years Over 30 Over 30 13% ($540,824) N/A ($144,212) 3.9% 21 years years Over 30 Over 30 14% ($643,925) N/A ($247,314) 3.0% 23 years years Over 30 Over 30 15% ($748,183) N/A ($351,571) 2.1% 25 years years

A loan with a rate up to 7 percent and with a term equal to 30 years can be taken to finance the solar PV system while keeping a positive NPV. This satisfies the assumed discount rate of 5%.

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3-Third-Party Financing

The models for assessing a third-party financing for the solar PV system can vary depending on the target user of the model. Both owners, and third-party financers should build their own models to evaluate the economic outputs and reach an agreement on the terms of the contract. Unfortunately, a very popular third-party financing mechanism for public buildings is not applicable for public schools in Florida.

The most common type is a Power Purchase Agreement (PPA) that creates economic advantages for both public and private entities. One of the main impetuses of a private entity to enter a PPA agreement is to take the benefits of the ITC and accelerated depreciations. Under the federal Modified Accelerated Cost-Recovery System

(MACRS), businesses may recover investments in certain property, which includes solar investments, through depreciation deductions. Recently, the Tax Cuts and Jobs

Act of 2017 increased the amount of the bonus depreciation to 100 percent for qualified property acquired and placed in service after September 27, 2017 and before January

1, 2023 (DSIRE, 2018). Private parties can take the advantage of the bonus depreciation when entering a PPA agreement. The key drivers to embark on a PPA agreement for a public entity are the additional capital provided, a possible lower cost of electricity and the inclusion of energy performance contract. Unfortunately, PPA is not permitted in Florida. So far, PPA and Solar Lease contracts are used in almost 70 percent of all solar installation in the US. Although solar lease can also bring similar advantages as PPA, the Florida regulations are known to be rather unclear and unsupportive of this method. It is not difficult to modify the base model for assessing both PPA, and solar lease. However, the costs of these contracts are highly subjective

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and depend on the terms of the contract and the amount of available incentives, as well as the local policies and regulations that are subject to periodic changes.

The most recent amendment of the federal ITC for PV systems presented in

Table 4-23 shows that ITC will be dropped to 0 percent for residential buildings, and 10 percent for commercial buildings after 2021(DOE, 2018). Clearly, this will have direct impacts on the inclusion of the third-party financers to sign PPA and solar lease contracts with public facilities and ultimately can increase the cost of energy saving performance contracts (ESPC). Although ESPC outsources the maintenance efforts and guarantees the energy performance that are helpful to public school facility manager, they will come at a price. The perception of the author is that public schools can have access to less expensive capital, and facility managers can be trained for the maintenance needs of the PV system and its components. Therefore, this study prefers to focus on the debt financing mechanisms as a method with most attractive economic outputs, especially when incentives such as ITC are not applicable.

Table 4-23. Federal Investment Tax Credit by technology type Future Technology 12/31/16 12/31/17 12/31/18 12/31/19 12/31/20 12/31/21 12/31/22 Years PV, Solar Water Heating, Solar Space 30% 30% 30% 30% 26% 22% 10% 10% Heating/Cooling, Solar Process Heat Hybrid Solar Lighting, Fuel 30% 30% 30% 30% 26% 22% 22% N/A Cells, Small Wind Geothermal Heat Pumps, Microtubines, 10% 10% 10% 10% 10% 10% N/A N/A Combine Heat and Power Systems Geothermal 10% 10% 10% 10% 10% 10% 10% 10% Electric

Large Wind 10% 24% 18% 12% N/A N/A N/A N/A

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The main advantages of using a third-party contract, like the benefits of ESPCs, are to cover the upfront capital needed to purchase the PV system. Even if this mechanism is not economic, there are terms in most contracts that require the third party to manage and guarantee the system. Moreover, school projects are mandated to use traditional financing methods which are not flexible for funding the additional upfront costs. Therefore, third-party financing has major benefits for schools even when they are costly.

The economic outputs after adding tax benefits for both ITC and 100 percent

Bonus depreciation become more attractive. The IRR, Payback, and Simple Payback for the PV system after adding the tax benefits will be 12.7 percent, 10 years and 8 years respectively. This also influences the outputs for the combined system and will result in an IRR, Payback, and Simple Payback of 9.8 percent, 15 years, and 11 years.

Private schools can take these benefits. Under a solar lease contract, a private party can also make an agreement with public schools and can take the advantages of the tax benefits. However, the private party will take some level of risks and will not share all the tax benefits with the school.

4- Feed in Tariff (FIT)

FIT is not a direct financing mechanism; however, it can change the economic justification of a PV project. Here, the study examines the role of a hypothetical FIT contract assuming 20 cents/kWh for the FIT rate and 4 cents/kWh for the avoided utility costs. The results of the analysis are shown in Table 4-24. No tax benefits are considered in calculating this part. We can see that the FIT is a very attractive mechanism and can persuade investors to flow funds into the PV market. The city of

Gainesville in Florida started the first FIT program in the US. However, the program has 150

been suspended and is no longer accepting applications or adding capacity. FIT is also suitable in attracting private parties to invest on solar projects for public facilities.

Table 4-24. The results of the adjusted model with a FIT scenario Energy Efficient Building PV System Combined (Net Zero Energy) IRR 8.2% 19.0% 13.2% NPV @ Year30 $396,611 $1,580,916 $1,977,527 Payback Period 18 7 11 Simple Payback 13 6 8 Period

The results of a sensitivity analysis of the outputs to the FIT rate are presented in

Table 4-25.

Table 4-25. The results of the sensitivity analysis of outputs to the FIT rate FIT PV System Combined Rate NPV (30 Simple ($/kWh) NPV (30 yrs) IRR Payback IRR Payback yrs) Payback $0.15 $965,655 14.0% 10 $1,362,267 10.9% 13 10

$0.16 $1,088,707 15.0% 9 $1,485,319 11.3% 12 10

$0.17 $1,211,759 16.0% 8 $1,608,371 11.8% 12 9

$0.18 $1,334,811 17.0% 8 $1,731,423 12.3% 11 9

$0.19 $1,457,863 18.0% 7 $1,854,475 12.7% 11 9

$0.20 $1,580,916 19.0% 7 $1,977,527 13.2% 11 8

$0.21 $1,703,968 19.9% 7 $2,100,579 13.6% 10 8

$0.22 $1,827,020 20.9% 6 $2,223,631 14.1% 10 8

$0.23 $1,950,072 21.8% 6 $2,346,683 14.5% 9 8

$0.24 $2,073,124 22.8% 6 $2,469,735 15.0% 9 8

$0.25 $2,196,176 23.7% 6 $2,592,787 15.4% 9 7

Part V: Proposing a Self-Amortizing Loan

This section aims to calculate the potential debt capacity of the energy cost savings from being a net zero school and propose a self-amortizing loan that matches the debt capacity. Debt capacity here is defined as the amount of money that can be 151

borrowed pledging only the energy savings as collateral. The base case assumptions are the same as previous sections. However, this section assumes a plausible stochastic process for the price of electricity. Earlier in this chapter, a sensitivity analysis of the economic outputs to several input parameters were examined. Among all parameters, outputs are most sensitive to the electricity price changes. Additionally, the model holds assumptions for future electricity prices which are subject to high uncertainty. Therefore, this section takes a stochastic approach in analyzing the effect of the electricity prices with a purpose to increase the reliability of the model outputs. In other words, the effect of uncertain changes in the cost of electricity is taken into account considering a probability that the prices can go up in different paths.

The price of electricity starts out at the current base case level and can change by an amount that is deemed reasonable. The study assumes that the electricity prices only change every five years. That means that electricity prices change five times over the 30-year life of the investment. Therefore, there are 25=32 electricity price paths. The debt is assumed to have an annuity structure with equal payments each year. The first objective is to find the maximum amount of debt payments that could be pledged by annual energy savings so that default occurs on only 3 paths. The second objective is to calculate the debt capacity with similar constraints as the first objective; however, this time the energy cost savings that are not pledged as payments to creditors are assumed to be deposited in an escrow account that can be used to cover creditor payments during periods where savings are low. The third objective is to propose a self- amortizing loan that corresponds to the calculated debt limits.

To calculate the debt capacity of the energy cost savings, the decision support models were modified to input different electricity price paths. The base case level for

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the cost of electricity is $ 0.09/kWh. To make reliable assumptions for the escalation rates used in the stochastic analysis, a distribution function of the projected escalation rates for the next 30 years, that were used in the base case model, is analyzed.

The average escalation rate is 3.4 percent when considered as a simple rate (not compounded) or 2.4 percent when compounding the rate. This study considers two scenarios of reasonable low and reasonable high for the escalation rate every five years. The reasonable low rate is assumed to be 2 percent and the reasonable high rate is conservatively assumed to be 5 percent. Considering 5-year constant rates, this translates to an increase of approximately $0.010 (~$0.09/kWh x [(1+2%)^5-1]) every 5 years for the low rate, and $0.025 (~$0.09/kWh x [(1+5%)^5-1]) as the high rate.

Therefore, the price of electricity is considered to increase either 1 cent, or 2.5 cents every five years. Now, 32 paths should be analyzed, and the probability of each path should be determined before the calculation of the NPV. The probability of either one of both scenarios is assumed to be 50 percent. Therefore, each path has an equal probability of occurrence of 1/32. Figure 4-17 shows a tree chart representation of the possible outcomes for every 5 years.

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$0.215 $0.190 $0.200 $0.165 $0.200 $0.175 $0.185 $0.140 $0.200 $0.175 $0.185 $0.150 $0.185 $0.160 $0.170 $0.115 $0.200 $0.175 $0.185 $0.150 $0.185 $0.160 $0.170 $0.125 $0.185 $0.160 $0.170 $0.135 $0.170 $0.145 $0.150 $0.090 $0.200 $0.175 $0.185 $0.150 $0.185 $0.160 $0.170 $0.125 $0.185 $0.160 $0.170 $0.135 $0.170 $0.145 $0.155 $0.100 $0.185 $0.160 $0.170 $0.135 $0.170 $0.145 $0.155 $0.110 $0.170 $0.145 $0.155 $0.120 $0.155 $0.130 $0.140

Figure 4-17. Projected electricity prices for the stochastic analysis

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The potential debt capacity for the combined model is calculated considering annual savings (pledged as payments to creditors) in the combined model should be enough to compensate for the annual debt payments of all except a maximum of 3 paths. The calculation shows a maximum annual debt capacity of $102,750.

In the model for the PV system, there is a replacement cost for the inverter. This lumpsum amount will cause a negative number for the year 15 in most paths. Therefore, this year are not considered as an indication of default. This replacement cost is not significant and will be paid off by the savings in other years.

In another scenario when an escrow account is used to accumulate the savings after setting aside the annual debt amount, the debt capacity is expected to be a larger amount than the scenario without an escrow account. Given that the escrow account starts with a zero balance, the result will be $103,450 that is slightly a larger number than a scenario without an escrow account. However, if the escrow account can have an initial balance of approximately $70,000 (assuming that the escrow grows at a rate equal to the discount rate), then the debt capacity will be at its maximum level of

$115,050 when default is allowed in only 3 paths. This is calculated using trial and error or alternatively with a use of Microsoft Excel Solver add-in. One major constraint is that in year 30 the NPV should be greater or equal to the initial balance amount.

The proposed self-amortizing loan that corresponds to the above debt capacities has a maximum nominal rate of 5.0 percent with no escrow account and 6.0 percent when an escrow account is used. This means that the payments on any loan with a rate lower than these amounts can be pledged by the project savings (energy savings plus energy production).

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Two main risks that can affect a loan rate are project credit risk (default) and interest rate risk. This study assumed only 3 default paths out of 32 total paths which corresponds to a default rate of approximately 10 percent. To consider the interest rate risk (rate fluctuations), the duration of the loan was calculated using Macaulay duration indicator. The duration of the loan is approximately 12 years. Therefore, to consider what loan rate is reasonable for a solar project with 10 percent default rate and 12 years duration, this study compares the maximum possible loan rates that was calculated above with a corporate bond with (Triple-B-rated) BBB investment grade credit rating of a similar duration. Since public schools can issue tax-exempt loans, the rate of a corporate bond should be adjusted to a tax-exempt rate equivalent. This can be done by measuring the tax-exempt marginal tax rate which can be derived by comparing the rates on a 10-year treasury bond and a 10-year municipality bond. At the time of this study, 10-year high quality corporate bonds have an average rate of 4.18 percent.

According to Bloomberg Barclays Indices, a triple-B-rated corporate bond has a rate of

4.6 percent. A 10-year treasury bond yield (r(T)) is currently 3.2 percent and a 10-year municipal bond has 2.8 percent yield (r(Muni)). The tax-exempt marginal tax rate is calculated to be [1-r(Muni)/r(T)] 12.5 percent. Assuming that the solar PV project has the same risk as a triple-B-rated corporate bond with 4.6 percent rate, the equivalent tax- exempt rate that is reasonable for this investment is approximately 4 percent [4.6*(1-

0.125) =4.025]. This amount is lower than the maximum rate calculated based on the debt capacity earlier in this section. Therefore, the proposed self-amortizing loan structure is deemed reasonable.

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CHAPTER 5 CONCLUSION

Economic Feasibility

A K-12 school is a great test platform for adopting NZE concepts. The recent NBI report published in 2018 collected over 500 NZE verified and emerging projects of which K-12 schools with about 20 percent of the total population are the most common building type. Although the technical feasibility of NZE schools is proven through numerous published research work and case studies, the economic feasibility of this building type has barely received adequate attention. Clearly, economic justifications are required for NZE schools to become mainstream. By creating and using a Net Zero

Energy Decision Support System that embeds technical, economic, and financial parameters, this study analyzes the economic justification of a NZE school prototype project in Miami, Florida. Miami is in zone 1A of the ASHRAE climate zone classification. A very hot-humid nature of this zone creates harsher conditions to achieve NZE compared to other places in Florida that are mostly in climate zone 2. The city of Miami is chosen due to the availability of the defined prototypes and earlier reliable publications by US DOE and NREL in performing the energy analysis of the prototypes. The results based on Miami are expected to be more conservative, therefore findings can be extended to most other locations in Florida.

The model used in this study incorporates life cycle costing scenarios for selected features that distinguish a NZE project from a conventional reference project

(also referred to as a benchmark or prototype project). In other words, quantities were measured against a benchmark. Despite most LCC studies that are optimistic about the input parameters, this study followed a conservative approach in the assumptions taken for the parameters with high level of uncertainties. Since the accuracy of the model

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outputs are depending on the accuracy of the model inputs, a special attention is given to defining the input assumptions. As an important assumption, this study considered the availability of the net metering incentive during the life of the study.

The results show a payback period shorter than 20 years (simple payback period of less than 15 years) when the cost premium for building a NZE school is between 10 and 12 percent. This estimated premium is the costs added compared to a reference conventional school and is mainly due to improvements in the energy conservation measures excluding the PV system costs. PV system costs create additional 5 to 10 percent premium. Since the premium is different from case to case, the study conducted a sensitivity analysis of the output results to this input parameter. This sensitivity table is particularly useful to owners/designers/builders or generally decision makers to estimate what level of construction cost premiums are still economically justifiable. Although the calculated payback period of 19 years (simple payback period of 13 years) is not very attractive in the industry, a NZE K-12 school project in Florida shows a positive net present value of approximately $600,000 within 30 years. School buildings are designed to last more than the 30-year life we considered in this study. Also, the IRR of approximately 7.8 percent, calculated here for this building type, is greater than most interest rates by which school districts can raise debt.

The input parameters in this study are estimated with assumptions for future years. Therefore, there is some level of uncertainty involved in the output results.

Clearly, the level of uncertainty is different for each parameter. This study showed that the outputs are more sensitive to the changes in the electricity prices and discount rate, and less sensitive to the changes in the PV system generation output and the estimated

EUI for the NZE school. This study uses sensitivity and scenario analysis to evaluate

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the effect of the uncertain inputs. The methodology taken has a deterministic approach in most parts except when determining the debt capacities to propose a self-amortizing loan mechanism, where a stochastic approach is taken for the electricity price.

Findings in Brief

The analysis chapter included five major parts that represent the findings of the study. The first one is the economic outputs including IRR, NPV, and Payback periods and their sensitivity to a few uncertain parameters. It was shown that the investment on energy efficiency and solar PV system has a reasonable payback that is less than 20 years. Considering the simple payback (which does not discount the future savings), the investment is paid off in 13 years that is less than half of the system life. The second part analyzed the effect of building degradation. It was shown that despite building degradation diminishes the energy performance of the school building, the economic outputs were slightly improved due to the increased gap between the energy consumption of the reference school compared to the NZE school. The third part analyzed the economic feasibility in future years 2022, 2026, and 2030 with a perspective that by 2030, new school buildings are set to be net zero. The results show that the economic feasibility is improved in future years (simple payback period of 13,

11, 10, 10 for the year 2018, 2022, 2026, and 2030 respectively). However, this improvement happens if the cost of the PV system is dropped by 50 percent in 2030 compared to its value today which is a highly uncertain assumption and is deemed to be optimistic. The calculated simple payback period slightly improves in future years.

Considering the results for the combined system that includes an energy efficient building plus a PV system, this study shows that there are no significant cost benefits in holding the investment for future dates. More importantly, a decision to hold an

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investment does not consider the environmental benefits of utilizing renewable energies, therefore is not recommended. The fourth part presented different financing mechanisms for the solar PV system and analyzed the result with assuming equity financing, debt financing, third-party financing, and a feed-in-tariff scenario. It was shown that the feed-in-tariff resulted in the most attractive economic outputs. This method is very effective in attracting private investors to solar market. The fifth part introduced a self-amortizing loan mechanism. A stochastic approach for electricity price was considered in the fifth part to estimate the debt capacities that are secured by energy savings. This study showed that public schools can establish a self-amortizing loan structure by creating an escrow account to accrue the savings from energy efficiency and energy productions. This way, any loan with a rate smaller than 5 percent can be paid off through the escrow account and the cost premium of building net zero is financed through energy savings.

Future Studies

The scope of the study is limited to the public K-12 school facilities in Florida.

However, this study can be further continued to include different ownership types, building types, and locations. Future case studies can be performed using the net zero energy decision support system that was created in this research to provide a better estimate of the economic outputs based on the characteristics of a particular case. Each one of the five parts in the analysis section can be elaborated and extended in more details. Future studies can extend this research to all US climate zones and also include private schools in the analysis.

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APPENDIX A K-12 SCHOOL PROTOTYPE BUILDING SPECIFICATION

Table A-1. Specifications of the K-12 school building prototype Prototype Building Modeling Specifications Pacific Northwest National Laboratory, updated on Friday, August 14, 2015

Data Source Item Descriptions

Program Vintage NEW CONSTRUCTION Location Zone 4A: Baltimore (mild, Zone 6A: Burlington (cold, Zone 1A: Miami (very hot, (Representing 8 Climate Zones) humid) humid) humid) Zone 4B: Albuquerque Zone 6B: Helena (cold, dry) Zone 1B: Riyadh, Saudi (mild, dry) Zone 7: Duluth (very cold) Arabia (very hot, dry) Zone 4C: Salem (mild, Zone 8: Fairbanks Zone 2A: Houston (hot, marine) (subarctic) humid) Selection of representative Zone 5A: Chicago (cold, Zone 2B: Phoenix (hot, dry) climates based on Briggs et al. humid) Zone 3A: Memphis (warm, (2003) Zone 5B: Boise (cold, dry) humid) Zone 5C: Vancouver, BC Zone 3B: El Paso (warm, (cold, marine) dry) Zone 3C: San Francisco (warm, marine) Available fuel types Gas, electricity Building Type (Principal Building Education BuildingFunction) Prototype Primary School Form Total Floor Area (sq feet) 73, 960 (340 ft x 270 ft) Building shape

Aspect Ratio 1.3 Number of Floors 1 Window Fraction (Window-to-Wall Ratio) 35% for all facades Ribbon window across all facades

Window Locations Continuous Band Shading Geometry none Azimuth non-directional Thermal Zoning Classrooms zoned by exposure. Corner classrooms separated out from single exposure classrooms.

Double loaded corridors zoned separately.

Administrative area, Gymnasium , mechanical, media center, lobby, kitchen, and cafeteria are single zones.

See Zone Summary.

Floor to floor height (feet) 13

Floor to ceiling height (feet) 13

Glazing sill height (feet) 3.6 (top of the window is 8.1 ft high with 4.5 ft high glass)

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Table A-1. Continued Architecture Exterior walls Construction Construction type: 2003 CBECS Data and PNNL's CBECS Study Steel-framed Walls (2x4, 16" OC) 2007. 0.75" stucco + 0.625" gypsum board + cavity insulation + 0.625" gypsum board Exterior wall layers: default 90.1 layering

2 Requirements in codes or standards U-factor (Btu / h * ft * °F) and/or Applicable codes or standards R-value (h * ft2 * °F / Btu) Nonresidential; Walls, Above-Grade, Steel-Framed Dimensions Based on floor area and aspect ratio Tilts and orientations Vertical Roof Construction Construction type: 2003 CBECS Data and PNNL's CBECS Study Built-up roof 2007. Roof membrane + roof insulation + metal decking Roof layers: default 90.1 layering

2 U-factor (Btu / h * ft * °F) and/or Requirements in codes or standards Applicable codes or standards R-value (h * ft2 * °F / Btu) Nonresidential; Roofs, Insulation entirely above deck

Area (ft2) 73,960 Tilts and orientations Horizontal Window Dimensions Based on window fraction, location, glazing sill height, floor area and aspect ratio

Glass-Type and frame Hypothetical window with weighted U-factor and SHGC

U-factor (Btu / h * ft2 * °F) Requirements in codes or standards Applicable codes or standards SHGC (all) Nonresidential; Vertical Glazing

Visible transmittance Same as above requirements

Operable area 35% PNNL 's Glazing Market Data for ASHRAE spreadsheet Skylight Dimensions Gymnasium/Multipurpose Room (4 ft x 4 ft) x 9 skylights = 144 ft² total Skylight Area AEDG K-12 Guide 3.75% of gym roof area Glass-Type and frame Hypothetical glass and frame meeting requirements in codes or standards below U-factor (Btu / h * ft2 * °F) Requirements in codes or standards Nonresidential; Skylight with curb, Glass, 2.1-5% SHGC Applicable codes or standards

Visible transmittance Foundation Foundation Type Slab-on-grade floors (unheated) Construction 6" concrete slab poured directly on to the earth + carpet Thermal properties for ground level floor Requirements in codes or standards Applicable codes or standards F-factor (Btu / h * ft2 * °F) Nonresidential; slab-on-grade floors, unheated and/or R-value (h * ft2 * °F / Btu) Thermal properties for basement NA Dimensions Based on floor area and aspect ratio

Interior Partitions Construction 2 x 4 uninsulated stud wall Dimensions Based on floor plan and floor-to-floor height Internal Mass 6 inches standard wood (16.6 lb/ft²) Air Barrier System Reference: Infiltration PNNL-18898. Infiltration Peak: 0.2016 cfm/sf of above grade exterior wall surface area, adjusted by wind (when Modeling Guidelines for fans turn off) Commercial Building Energy Off Peak: 25% of peak infiltration rate (when fans turn on) Analysis . Additional infiltration through building entrance PNNL-20026. Energy Saving Impact of ASHRAE 90.1

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Table A-1. Continued HVAC System Type Heating type 1. Gas furnace inside packaged air conditioning unit 2. Hot water from a gas boiler for heating Cooling type Packaged air conditioning unit 2003 CBECS Data, PNNL's CBECS Study 2006, and 90.1 Distribution and terminal units 1. CAV systems: direct air from the packaged air conditioning unit Mechanical Subcommittee input. 2. VAV systems: VAV terminal box with damper and hot water reheating coil Zone Control Type: minimum supply air at 30% of the zone design peak supply air

HVAC Sizing Air Conditioning Autosized to design day Heating Autosized to design day HVAC Efficiency Air Conditioning Varies by climate location and design cooling capacity Requirements in codes or standards Applicable codes or standards Minimum equipment efficiency for Air Conditioners and Condensing Units Heating Varies by climate location and design heating capacity Requirements in codes or standards Minimum equipment efficiency for Warm Air Furnaces Applicable codes or standards Minimum equipment efficiency for Gas and Oil-fired Boilers HVAC Control Thermostat Setpoint 75°F Cooling/70°F Heating

Thermostat Setback 80°F Cooling/60°F Heating

Supply air temperature Minimum 50 °F and maximum 122 °F

Chilled water supply temperatures NA

Hot water supply temperatures 180 °F

Economizers Requirements in codes or standards Applicable codes or standards

Outdoor Air Ventilation ASHRAE Standard 62.1 or International Mechanical Code Applicable codes or standards See under Outdoor Air. Demand Control Ventilation Requirements in codes or standards Applicable codes or standards Energy Recovery Requirements in codes or standards Applicable codes or standards Supply Fan Fan schedules See under Schedules Supply Fan Mechanical Efficiency Requirements in applicable Depending on the fan motor size and requirements in codes or standards (%) codes or standards for motor efficiency and fan power Supply Fan Pressure Drop Depending on the fan supply air cfm limitation Pump Pump Type Variable speed

Rated Pump Head 60 ft Pump Power autosized

Cooling Tower Cooling Tower Type NA Cooling Tower Power NA Service Water Heating SWH type Storage Tank Fuel type Reference: PNNL 2014. Enhancements to Natural gas (main); electric (dishwasher booster) ASHRAE Standard 90.1 Prototype Building Models Thermal efficiency (%) Requirements in codes or standards Applicable codes or standards

Tank Volume (gal) 200 (main); 6 (dishwasher booster) Reference: Water temperature setpoint 140 F (main); 180 F (dishwasher booster) PNNL 2014. Enhancements to Water consumption (peak gpm) ASHRAE Standard 90.1 See under Schedules Prototype Building Models

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Table A-1. Continued Internal Loads & Schedules Lighting

Requirements in codes or standards Lighting power density (W/ft2) Applicable codes or standards See Zone Summary

Schedule See under Schedules

Daylighting Controls Requirements in codes or standards Applicable codes or standards

Occupancy Sensors Requirements in codes or standards Applicable codes or standards Plug load Average power density (W/ft2) User's Manual for ASHRAE See under Zone Summary Standard 90.1-2004 (Appendix G) Schedule See under Schedules Refrigeration Equipment Walk-in freezer and display case both with air-cooled local condensers

Occupancy Average people See under Zone Summary

Schedule See under Schedules

Misc. Elevator Peak Power Not modeled.

Schedule Not modeled. Exterior Lighting Peak Power (W) Based on design assumptions for façade, parking lot, entrance, etc. and requirements in codes or standards Applicable codes or standards Schedule See under Schedules and control requirements in codes or standards Applicable codes or standards References 1 Briggs, R.S., R.G. Lucas, and Z.T. Taylor. 2003. Climate Classification for Building Energy Codes and Standards: Part 2—Zone Definitions, Maps, and Comparisons. ASHRAE Transactions 109(2). 2 PNNL's CBECS Study. 2007. Analysis of Building Envelope Construction in 2003 CBECS Buildings. Dave Winiarski, Mark Halverson, and Wei Jiang. Pacific Northwest National Laboratory. March 2007. 3 PNNL's CBECS Study. 2006. Review of Pre- and Post-1980 Buildings in CBECS – HVAC Equipment. Dave Winiarski, Wei “StudyJiang and of the Mark U.S. Halverson. Market For Pacific Windows, Northwest Doors, National and Skylights”, Laboratory. American December Architectural 2006. Manufacturers Association, Window & 4 GoelDoor S,Manufacturers M Rosenberg, Association, R Athalye, 2006.Y Xie, W Wang, R Hart, J Zhang, V Mendon. 2014. Enhancements to ASHRAE Standard 90.1 Prototype Building Models. PNNL-23269, Pacific Northwest National Laboratory, Richland, Washington. http://www.pnnl.gov/main/publications/external/technical_reports/PNNL-23269.pdf

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APPENDIX B K-12 SCHOOL PROTOTYPE COST ESTIMATION (RSMeans)

Figure B-1. An example of cost estimation inputs in RSMeans square footage cost estimator

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Figure B-2. Elementary school cost estimations using RSMeans square footage cost estimator

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Figure B-3. Elementary school cost estimations using RSMeans square footage cost estimator

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Table B-1. RSMeans square foot cost report for a typical elementary school in Miami Square Foot Cost Estimate Report Date: 3/10/2018 Estimate Name: Average K-12 Costs in Miami UF Miami , Florida School, Elementary with E.I.F.S. / Rigid Building Type: Steel Location: MIAMI, FL Story Count: 1 Story Height (L.F.): 17 Floor Area (S.F.): 74000 Labor Type: OPN Basement Included: No Data Release: Year 2018 Costs are derived from a building model with basic components. Cost Per Square Foot: $118.52 Scope differences and market conditions can cause costs to vary significantly. Building Cost: $8,770,796.05

% of Total Cost Per S.F. Cost A Substructure 8.33% 7.39 546,557.43 A1010 Standard Foundations 3.24 239,394.53 Foundation wall, CIP, 4' wall height, direct chute, .148 CY/LF, 7.2 1.74 128,479.15 Strip footing, concrete, reinforced, load 11.1 KLF, soil bearing 0.99 73,051.98 Spread footings, 3000 PSI concrete, load 100K, soil bearing capacity 0.51 37,863.40 A1030 Slab on Grade 3.97 294,088.58 Slab on grade, 4" thick, non industrial, reinforced 3.97 294,088.58 A2010 Basement Excavation 0.18 13,074.32 Excavate and fill, 30,000 SF, 4' deep, sand, gravel, or common 0.18 13,074.32 B Shell 32.17% 28.51 2,109,373.51 B1010 Floor Construction 0.68 49,966.43 Fireproofing, gypsum board, fire rated, 1 layer, 1/2" thick, 10" steel 0.68 49,966.43 B1020 Roof Construction 11.11 822,027.52 Roof, steel joists, joist girder, 1.5" 22 ga metal deck, on columns, 10.14 750,678.20 Roof, steel joists, joist girder, 1.5" 22 ga metal deck, on columns, 0.96 71,349.32 B2010 Exterior Walls 4.21 311,497.97 E.I.F.S., cement board sheathing, 1x8 fascia, R8 insulation, 6" metal 4.21 311,497.97 B2020 Exterior Windows 4.92 364,109.52 Windows, aluminum, awning, insulated glass, 4'-5" x 5'-3" 2.68 198,642.62 Aluminum flush tube frame, for 1/4"glass, 1-3/4"x4", 5'x20' 0.93 68,858.23 Glazing panel, insulating, 1" thick units, 2 lites, 1/4" float glass, 1.31 96,608.67 B2030 Exterior Doors 0.7 52,162.96 Door, aluminum & glass, with transom, narrow stile, double door, 0.49 36,529.52 Door, steel 18 gauge, hollow metal, 1 door with frame, no label, 3'- 0.21 15,633.44 B3010 Roof Coverings 6.68 494,653.55 Roofing, single ply membrane, EPDM, 60 mils, loosely laid, stone 1.38 101,775.90 Insulation, rigid, roof deck, extruded polystyrene, 40 PSI 3.83 283,305.30 Base flashing, rubber, neoprene, 1/16" thick, 24 ga galv reglet, 24 0.65 47,952.70 Roof edges, aluminum, duranodic, .050" thick, 8" face 0.72 53,618.18 Flashing, aluminum, no backing sides, .019" 0.11 8,001.47 B3020 Roof Openings 0.2 14,955.56 Roof hatch, with curb, 1" fiberglass insulation, 2'-6" x 3'-0", 0.09 6,750.94 Smoke hatch, unlabeled, galvanized, 2'-6" x 3', not incl hand winch 0.11 8,204.63

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C Interiors 18.02% 15.97 1,181,636.53 C1010 Partitions 2.17 160,781.21 Metal partition, 5/8"fire rated gypsum board face, no base,3 -5/8" 1.44 106,663.01 Metal partition, 5/8" high abuse gypsum board face, no base layer, 0.36 26,878.21 Gypsum board, 1 face only, exterior sheathing, fire resistant, 5/8" 0.24 18,079.25 Add for the following: taping and finishing 0.12 9,160.74 C1020 Interior Doors 1.46 108,277.86 Door, single leaf, kd steel frame, hollow metal, commercial quality, 1.46 108,277.86 C1030 Fittings 1.02 75,618.45 Toilet partitions, cubicles, ceiling hung, painted metal 0.71 52,603.27 Chalkboards, liquid chalk type, aluminum frame & chalktrough 0.31 23,015.18 C3010 Wall Finishes 1.17 86,520.87 Painting, interior on plaster and drywall, walls & ceilings, roller 0.47 34,713.25 Painting, interior on plaster and drywall, walls & ceilings, roller 0.19 14,265.79 Ceramic tile, thin set, 4-1/4" x 4-1/4" 0.51 37,541.83 C3020 Floor Finishes 5.24 387,486.64 Carpet, tufted, nylon, roll goods, 12' wide, 36 oz 0.45 33,252.42 Carpet, padding, add to above, 2.7 density 0.09 6,450.80 Terrazzo, maximum 1.79 132,104.80 Vinyl, composition tile, maximum 1.4 103,434.24 Oak strip, sanded and finished, minimum 1.23 90,934.01 Underlayment, plywood, 3/8" thick 0.29 21,310.37 C3030 Ceiling Finishes 4.9 362,951.50 Acoustic ceilings, 3/4"mineral fiber, 12" x 12" tile, concealed 2" bar 4.9 362,951.50 D Services 41.24% 36.55 2,704,576.03 D2010 Plumbing Fixtures 5.64 417,724.40 Water closet, vitreous china, bowl only with flush valve, wall hung 2.9 214,496.40 Urinal, vitreous china, wall hung 0.33 24,361.91 Lavatory w/trim, wall hung, PE on CI, 20" x 18" 1.18 87,077.28 Kitchen sink w/trim, countertop, stainless steel, 43" x 22" double 0.27 19,954.54 Service sink w/trim, PE on CI,wall hung w/rim guard, 24" x 20" 0.14 10,392.07 Water cooler, electric, wall hung, wheelchair type, 7.5 GPH 0.83 61,442.20 D2020 Domestic Water Distribution 0.63 46,416.64 Gas fired water heater, commercial, 100< F rise, 300 MBH input, 0.63 46,416.64 D2040 Rain Water Drainage 0.88 65,103.13 Roof drain, CI, soil,single hub, 5" diam, 10' high 0.78 57,844.32 Roof drain, CI, soil,single hub, 5" diam, for each additional foot add 0.1 7,258.81 D3010 Energy Supply 7.45 551,514.60 Commercial building heating system, fin tube radiation, forced hot 7.45 551,514.60 D3050 Terminal & Package Units 8.15 603,398.22 Splt sys, air cooled condensing unit, schools and colleges, 20,000 8.15 603,398.22 D4010 Sprinklers 1.88 139,213.98 Wet pipe sprinkler systems, steel, light hazard, 1 floor, 50,000 SF 1.88 139,213.98 D4020 Standpipes 0.35 25,850.42 Wet standpipe risers, class III, steel, black, sch 40, 4" diam pipe, 1 0.17 12,278.33 Wet standpipe risers, class III, steel, black, sch 40, 4" diam pipe, 0.18 13,572.09 D5010 Electrical Service/Distribution 0.57 41,820.92 Overhead service installation, includes breakers, metering, 20' 0.17 12,229.34 Feeder installation 600 V, including RGS conduit and XHHW wire, 0.12 9,100.86 Switchgear installation, incl switchboard, panels & circuit breaker, 0.28 20,490.72

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D5020 Lighting and Branch Wiring 7.96 588,849.49 Receptacles incl plate, box, conduit, wire, 8 per 1000 SF, .9 W per 2.4 177,835.32 Wall switches, 2.0 per 1000 SF 0.33 24,255.72 Miscellaneous power, 1.2 watts 0.24 17,562.42 Central air conditioning power, 4 watts 0.44 32,781.26 Fluorescent fixtures recess mounted in ceiling, 1.6 watt per SF, 40 4.55 336,414.77 D5030 Communications and Security 2.95 217,947.19 Communication and alarm systems, includes outlets, boxes, 0.23 16,803.50 Communication and alarm systems, fire detection, addressable, 1.68 123,973.02 Fire alarm command center, addressable with voice, excl. wire & 0.26 18,884.47 Communication and alarm systems, includes outlets, boxes, 0.26 19,286.18 Communication and alarm systems, includes outlets, boxes, 0.26 19,119.47 Internet wiring, 2 data/voice outlets per 1000 S.F. 0.27 19,880.54 D5090 Other Electrical Systems 0.09 6,737.04 Generator sets, w/battery, charger, muffler and transfer switch, 0.09 6,737.04 E Equipment & Furnishings 0.24% 0.21 15,461.03 E1020 Institutional Equipment 0.21 15,461.03 Architectural equipment, laboratory equipment, counter tops, 0.21 15,461.03 E1090 Other Equipment 0 0 F Special Construction 0% 0 0 G Building Sitework 0% 0 0

SubTotal 100% $88.62 $6,557,604.52 Contractor Fees (General Conditions,Overhead,Profit) 25.00% $22.15 $1,639,401.13 Architectural Fees 7.00% $7.75 $573,790.40 User Fees 0.00% $0.00 $0.00 Total Building Cost $118.52 $8,770,796.05 **** Indicates Assemblies or Components have been customized.

Audit Trail Notes There are no audit trail notes associated with this estimate.

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Figure B-4. Green elementary school cost estimations using RSMeans square footage cost estimator

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Table B-2. RSMeans square foot cost report for a typical green school in Miami Square Foot Cost Estimate Report Date: 3/10/2018 Estimate Name: Average K-12 Costs in Miami UF Miami , Florida School, Elementary (Green) with Stucco & Building Type: Concrete Block / Rigid Steel Location: MIAMI, FL Story Count: 1 Story Height (L.F.): 17 Floor Area (S.F.): 74000 Labor Type: OPN Basement Included: No Data Release: Year 2018 Costs are derived from a building model with basic components. Cost Per Square Foot: $143.88 Scope differences and market conditions can cause costs to vary significantly. Building Cost: $10,646,963.85

% of Total Cost Per S.F. Cost A Substructure 10.09% 10.85 802,997.61 A1010 Standard Foundations 3.41 252,361.38 Strip footing, concrete, reinforced, load 5.1 KLF, soil bearing 3.41 252,361.38 A1030 Slab on Grade 4.04 299,120.58 Slab on grade, 4" thick, non industrial, reinforced, recycled plastic 4.04 299,120.58 A2010 Basement Excavation 0.1 7,471.04 Excavate and fill, 30,000 SF, 4' deep, sand, gravel, or common 0.1 7,471.04 A2020 Basement Walls 3.3 244,044.61 Foundation wall, CIP, 4' wall height, direct chute, .148 CY/LF, 7.2 3.3 244,044.61 B Shell 26.26% 28.25 2,090,618.93 B1020 Roof Construction 9.52 704,579.16 Roof, steel joists, beams, 1.5" 22 ga metal deck, on columns, 7.93 586,775.60 Roof, steel joists, beams, 1.5" 22 ga metal deck, on columns, 1.59 117,803.56 B2010 Exterior Walls 5.96 441,227.66 Stucco, 3 coat, self furring metal lath 3.4 Lb/SY, on regular CMU, 5.96 441,227.66 B2020 Exterior Windows 4.03 297,963.93 Windows, aluminum, awning, insulated glass, 4'-5" x 5'-3" 4.03 297,963.93 B2030 Exterior Doors 0.7 51,936.25 Door, aluminum & glass, with transom, narrow stile, double door, 0.49 36,529.52 Door, steel 18 gauge, hollow metal, 1 door with frame, no label, 3'- 0.21 15,406.73 B3010 Roof Coverings 8.04 594,911.92 Roofing, single ply membrane, TPO, 60 mil membrane, heat welded 1.56 115,070.00 Insulation, rigid, roof deck, polyisocyanurate, 2#/CF, 3.5" thick 4.56 337,736.00 Insulation, rigid, roof deck, polyisocyanurate, tapered for drainage 0.93 68,498.10 Base flashing, rubber, neoprene, 1/16" thick, 24 ga galv reglet, 24 0.16 11,988.18 Roof edges, aluminum, duranodic, .050" thick, 8" face 0.72 53,618.18 Flashing, aluminum, no backing sides, .019" 0.11 8,001.47

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C Interiors 17.68% 19.02 1,407,388.99 C1010 Partitions 3.15 232,833.60 Concrete block (CMU) partition, light weight, hollow, 6" thick, no 3.15 232,833.60 C1020 Interior Doors 1.46 108,277.86 Door, single leaf, kd steel frame, hollow metal, commercial quality, 1.46 108,277.86 C1030 Fittings 1.73 128,288.18 Toilet partitions, cubicles, ceiling hung, stainless steel 0.7 51,570.90 Chalkboards, liquid chalk type, aluminum frame & chalktrough 1.04 76,717.28 C3010 Wall Finishes 3.03 224,432.37 2 coats paint on masonry with block filler, low VOC 0.76 56,115.89 Painting, masonry or concrete, latex, brushwork, addition for block 0.6 44,513.78 Wall coatings, acrylic glazed coatings, maximum 0.23 16,984.67 Ceramic tile, thin set, 4-1/4" x 4-1/4" 0.51 37,541.83 Painting, masonry or concrete, latex, brushwork, primer & 2 coats, 0.94 69,276.21 C3020 Floor Finishes 4.74 350,605.49 Carpet tile, nylon, fusion bonded, 18" x 18" or 24" x 24", 24 oz 0.97 71,517.67 Terrazzo, maximum 1.79 132,104.80 Vinyl, composition tile, 12" x 12" x 1/8" thick, recycled content 1.99 146,983.02 C3030 Ceiling Finishes 4.9 362,951.50 Acoustic ceilings, 3/4"mineral fiber, 12" x 12" tile, concealed 2" bar 4.9 362,951.50 D Services 45.70% 49.16 3,638,113.63 D2010 Plumbing Fixtures 13.05 965,521.90 Water closet, vitreous china, bowl only w/ auto flush sensor flush 7.13 527,527.71 Urinal, vitreous china, wall hung, waterless, ADA 0.24 17,868.03 Lavatory w/trim, wall hung, PE on CI, 20" x 18", faucet w/ hydroelec 3.4 251,491.31 Kitchen sink w/trim, countertop, stainless steel, 43" x 22" double 0.15 11,307.57 Service sink w/trim, PE on CI,wall hung w/rim guard, 24" x 20" 0.12 8,833.26 Shower, stall, baked enamel, terrazzo receptor, 36" square 0.72 52,921.88 Water cooler, electric, wall hung, 8.2 GPH, GreenSpec certified 1.29 95,572.15 D2020 Domestic Water Distribution 0.12 8,956.54 Gas fired water heater, commercial, 100< F rise, tankless, on- 0.12 8,956.54 D2040 Rain Water Drainage 1.36 100,644.00 Roof drain, CI, soil,single hub, 5" diam, 10' high 0.71 52,445.52 Roof drain, CI, soil,single hub, 5" diam, for each additional foot add 0.65 48,198.49 D3040 Distribution Systems 0.41 30,402.38 Heat recovery pkgs, air to air, enthalpy recovery wheel, 20,000 max 0.41 30,402.38 D3050 Terminal & Package Units 15.65 1,157,940.90 Rooftop, multizone, air conditioner, food supermarkets, 25,000 SF, 15.65 1,157,940.90 D4010 Sprinklers 1.88 139,213.98 Wet pipe sprinkler systems, steel, light hazard, 1 floor, 50,000 SF 1.88 139,213.98 D4020 Standpipes 0.35 25,850.42 Wet standpipe risers, class III, steel, black, sch 40, 4" diam pipe, 1 0.17 12,278.33 Wet standpipe risers, class III, steel, black, sch 40, 4" diam pipe, 0.18 13,572.09 D5010 Electrical Service/Distribution 0.43 32,135.19 Overhead service installation, includes breakers, metering, 20' 0.12 8,688.66 Feeder installation 600 V, including RGS conduit and XHHW wire, 0.1 7,262.34 Switchgear installation, incl switchboard, panels & circuit breaker, 0.22 16,184.19 D5020 Lighting and Branch Wiring 11.3 836,275.55 Receptacles incl plate, box, conduit, wire, 8 per 1000 SF, .9 W per 2.4 177,835.32 Wall switches, 2.0 per 1000 SF 0.33 24,255.72 Miscellaneous power, 1.2 watts 0.24 17,562.42 Central air conditioning power, 3 watts 0.43 31,512.16 LED fixtures recess mounted in ceiling, 0.69 watt per SF 5.77 427,316.03 Daylight dimming control system, 10 fixtures per 1000 SF 1.28 95,044.86 Lighting on/off control system, 10 fixtures per 1000 SF 0.85 62,749.04

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D5030 Communications and Security 4.02 297,588.29 Communication and alarm systems, includes outlets, boxes, 0.23 16,803.50 Communication and alarm systems, fire detection, non- 1.08 79,641.10 Communication and alarm systems, fire detection, addressable, 1.68 123,973.02 Fire alarm command center, addressable with voice, excl. wire & 0.26 18,884.47 Communication and alarm systems, includes outlets, boxes, 0.26 19,286.18 Communication and alarm systems, includes outlets, boxes, 0.26 19,119.47 Internet wiring, 2 data/voice outlets per 1000 S.F. 0.27 19,880.54 D5090 Other Electrical Systems 0.59 43,584.48 Generator sets, w/battery, charger, muffler and transfer switch, 0.07 4,907.40 Energy monitoring systems, electrical, three phase, 5 meters 0.17 12,438.10 Energy monitoring systems, mechanical, BTU, 3 meters w/3 duct & 0.32 23,338.15 Energy monitoring systems, Front end display 0.01 598.38 Energy monitoring systems, Computer workstation 0.03 2,302.45 E Equipment & Furnishings 0.27% 0.29 21,227.65 E1020 Institutional Equipment 0.21 15,461.03 Architectural equipment, laboratory equipment, counter tops, 0.21 15,461.03 E1090 Other Equipment 0.07 5,134.70 Waste handling, recycling, tilt truck, plastic, with wheels, 1.0 C.Y., 0.07 5,134.70 E2020 Moveable Furnishings 0.01 631.93 Signage, exterior, surface mounted, 24 ga aluminum, 10" x 7", no 0.01 631.93 F Special Construction 0% 0 0 G Building Sitework 0% 0 0

SubTotal 100% $107.57 $7,960,346.80 Contractor Fees (General Conditions,Overhead,Profit) 25.00% $26.89 $1,990,086.70 Architectural Fees 7.00% $9.41 $696,530.35 User Fees 0.00% $0.00 $0.00 Total Building Cost $143.88 $10,646,963.85 **** Indicates Assemblies or Components have been customized.

Audit Trail Notes There are no audit trail notes associated with this estimate.

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Florida Department of Education. (2018). Funding and Financial Reporting. Retrieved from: http://www.fldoe.org/finance/fl-edu-finance-program-fefp/

Florida Department of Education. (2018). Class Size. Retrieved from: http://www.fldoe.org/finance/budget/class-size/index.stml

Florida Department of Education. (2017). 2017-10 Funding for Florida School Districts. Retrieved from: http://www.fldoe.org/core/fileparse.php/7507/urlt/Fefpdist.pdf

The 2018 Florida Statutes. (2018). K-20 Education Code. Retrieved from: http://www.leg.state.fl.us/statutes/index.cfm?App_mode=Display_Statute&Search _String=&URL=1000-1099/1013/Sections/1013.64.html

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BIOGRAPHICAL SKETCH

Hamed Hakim receives his doctorate degree from the University of Florida

College of Design Construction and Planning in December 2018. He has been working as a graduate research assistant at the Powell Center for Construction & Environment since 2013. He received his Bachelor of Science in Civil Engineering with an emphasis on Water Resources from Isfahan University of Technology and he holds a Master of

Science at in Construction Engineering Management (Herbert Wertheim College of

Engineering) and a Master of Science in Finance (Warrington College of Business) at the University of Florida. Since 2012, Hamed has devoted his time to study and conduct research on green buildings and the sustainable built environment and has developed several publications in this area. His research focuses on Economic Decision Analysis of Net Zero Energy Schools and introducing Alternative and Innovative Financing

Mechanisms for the development of such projects. His other research interests include

Life Cycle Assessment, Construction Automation, and Offsite Construction techniques. During these years, he has served as teaching assistant to Dr. Kibert, Dr.

Lucas, and Dr. Sullivan for several graduate and undergraduate level courses. Hamed has industry experiences of over three years as assistant project manager in commercial building projects as well as internships in healthcare and heavy civil construction.

Apart from the academic activities, Hamed has been involved in several organizing activities including the preparation of iiSBE Net Zero Energy Symposium in

2014, Ethics and the Built Environment (EBE) Symposium in 2016, and The State of the

Art of Modular Construction in 2017. He served as president of College of Design,

Construction, and Planning Graduate Student Association (DCP-GSA), USGBC Rinker

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Student Chapter, treasurer of ISA organization, and Sustainability Director of

Sustainable Business Group (SBG) organization, and co-founder of Rinker Doctoral

Forum.

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