S-LAB FINAL TEAM REPORT: A CASE STUDY ON THE CLINTON

CLIMATE INITIATIVE

MIT Sloan School of Management

May 15, 2008

Kate Burke-Wallace, Nikhil Garg, Todd Rakow, Ting Shih

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Contents

1. Project Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

3. Summary of F indings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

4. User Needs and Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

5. Current Retrof it Analys is Models and Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

6. Test of Se lect Current Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Figure 1a……………………………………………………… . .……………………………………10 Figure 1b……………… . .……………………………………………………………………………11 Figure 2a… . .…………………………………………………………………………………………12 Figure 2b…… . .………………………………………………………………………… ……………13

7. Gaps in Existing Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

8. Recommended Framework for Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Figure 3a……………………………… .……………………………………………………………16 Figure 3b………………………… .…………………………………………………………………17

Figure 4a………………………… .…………………………………………………………………18 Figure 4b……………………………… .……………………………………………………………19 Figure 4c………………………………… .…………………………………………………………19 Figure 5a……………………………… .…………………………………………………………… 20 Figure 5b………………………… .………………………………………………………………… 21 Figure 5c………………………… .…………………………………………………………………21 Figure 6a………………………………… .………………………………………………………… 22 Figure 6b………………………………………… .………………………………………………… 23

9. Conclus ion and Areas for Further Explorat ion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Appendix A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

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1. Project Overview

Background

The Clinton Climate Initiative (CCI) was created by the William J. Clinton Foundation to combat climate change by helping cities reduce their greenhouse gas emissions. This project focuses on CCI’s Energy Efficiency Building Retrofit Program aimed at encouraging building owners to retrofit existing buildings to achieve energy savings, one of the most direct ways to lower greenhouse gas emissions on a global scale. CCI is working with energy services companies (ESCOs) and financial institutions to develop economic models suited for this unique opportunity. However, existing tools to evaluate retrofit opportunities do not adequately highlight the effectiveness of alternative financing mechanisms. Our team was tasked with generating a framework for an analysis tool to help building owners evaluate retrofit opportunities in their existing buildings in order to accelerate their energy conservation projects and achieve cost savings.

Objective

Define a framework for a useable model for building owners to analyze the tradeoffs of funding building retrofit opportunities. The model needs to demonstrate the value of funding and motivate the use of alternative funding mechanisms. The proposed framework for building a financial model would establish not only a project’s economic viability but also the conditions that justify the funding needs.

2. Methodology

In order to work towards this objective, we collaborated both with the Clinton Climate Initiative (CCI) staff as well as CCI’s trial partners in Chicago (i.e. City Colleges of Chicago and Shedd Aquarium). Our team developed this framework through the following project phases:

- Determine user requirements for model: interview stakeholders (e.g. building owners, facilities managers, CFOs) to determine needed elements of a financial model (e.g. quarterly savings estimates, up-front investment, incremental investment, etc.)

- Search for existing retrofit analysis tools: examine existing industry tools that analyze potential cost savings for participating companies in retrofit energy conservation projects.

- Analyze findings and determine model criteria: based on findings from existing models and industry research in model development, determine optimal set of criteria necessary for the framework to enable the creation of a financial model that would accelerate project funding for energy conservation projects.

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- Develop framework for model creation: based on analysis from existing models and

user research, develop a framework that incorporates desired functionalities of various models as well as new features while addressing deficiencies in existing tools.

- Pilot test framework: test the framework on existing CCI contacts involved in energy

conservation projects and revise framework based on feedback.

3. Summary of F indings

Through research and interviews, we found that CFO-level users would benefit most from a model that clearly displays the financial benefits of a retrofit project. The ideal model for these users would incorporate a variety of financial metrics, discussion of plowback (using the savings from one retrofit project to fund another), discussion of funding, and a demonstration of the benefits of accelerating investment in a retrofit project. After surveying the existing models already available and testing their reliability using CCI client data, we determined that while existing models provided many features demanded by users, they did not clearly and adequately address the benefits of accelerating investment in retrofit projects. Accordingly, we designed a framework for a model that provides a clear comparison of the financial benefits that can be derived from beginning a retrofit project at three different points in time: immediately, in a few years, and delaying the project indefinitely.

4. User Needs and Requirements

Our group felt it was imperative to gain a clear understanding of the specific project justification devices desired by our clients as well as many other entities that were involved in retrofitting projects. Through research and a series of interviews, data was collected from both current and potential users of building retrofit models to better understand users’ needs. We sought to understand what features decision makers would look for in an ideal tool to help them determine whether or not to proceed with a building retrofit project. This input would allow us to better develop a framework for the theoretical building retrofit model that were outlining. The majority of the users we targeted were public or private colleges or universities. Our results were fairly consistent, with all users and potential users indicating that a variety of financial metrics were extremely important criteria in prioritizing and choosing retrofit projects. It is clear that any model designed for review by a CFO or equivalent decision maker must include such metrics. Other important determining factors include plowback calculations, calculations demonstrating the necessity of project acceleration, and a range of qualitative factors. The main categories of decision criteria are described below.

Financial metrics

All users and potential users emphasize the importance of financial metrics in determining whether or not to pursue a retrofit project. This was true for both private and public colleges

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and universities, as well as for users from other sectors. For a majority of users, financial metrics were considered the most important features to be included in a model. The most frequently cited metrics include:

Net present value of total project

Total project cost

Savings from project

Return on investment (ROI)

Payback (in years)

CFOs and equivalent decision makers understand these metrics more thoroughly than complex engineering data. Cost control, return on investment, and the length of time needed before benefits can be derived from investments are criteria that CFOs and their equivalents use on a regular basis to make a variety of decisions. The ability of financial metrics to translate the benefits of a retrofit project into the CFO’s language makes them an invaluable component of a retrofitting tool.

Plowback

Several potential users indicated the importance of plowback, which in this context can be defined as the use of a high-ROI component of a retrofit project to fund a lower-ROI component of the project, in persuading CFOs to proceed with retrofitting. Certain retrofitting components are sometimes referred to as “low-hanging fruit” due to their substantial cost savings, high overall ROI, and short payback period. Pairing these project components with components with a less substantial payback makes it easier to convince decision makers to proceed with retrofitting aging systems that could become prone to breaking down. The importance of plowback was discussed with facilities managers at a college in Chicago. The facilities managers were working as part of a team attempting to convince the CFO and ultimately, the Board of Directors of the college, to proceed with a retrofitting project. The lighting system used in the buildings on campus was not considered to be a critical system or close to breaking down. However, retrofitting the lighting system provided obvious financial benefits. The payback time for the lighting system alone was estimated to be between four and five years. In contrast, the chillers located in the buildings on campus were outdated, and many of the team members thought they should be replaced before they reached the point of near-breakdown. However, retrofitting the chillers had a much longer estimated payback period of over 20 years. Accordingly, persuading management to immediately retrofit the chillers alone would have been a difficult task. The facilities manager’s team would have encountered little difficulty in persuading the CFO and Board to proceed with retrofitting the buildings’ lighting system by itself. However, the team elected to package the lighting retrofit together with a retrofit of the buildings’ chillers.

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The complete retrofit (lighting and chillers) had an estimated payback period of fifteen years. Presenting the two retrofit components as one packaged bundle enabled the team to persuade the CFO and Board to agree to retrofit the chiller system, avoiding a potential disaster a few years later if the critically outdated chiller system broke down. Without using the lighting system’s relatively high payback, it would have been much more difficult to do this. Given the benefits of plowback in persuading decision makers to proceed with complete retrofits, calculations that combine different retrofit components with various payoffs as one package is an important feature for a model to incorporate.

Funding

A component similar to the plowback theory is that of up-front funding for projects. An interesting resource leveraged for our research was the Harvard Green Campus Initiative (HGCI). The business model for HGCI is to continuously develop and sell a variety of services to schools and departments at Harvard that are interested in reducing cost outlays towards energy bill and reduce their environmental impacts. HGCI targets many campus divisions very similar to the Chicago City Colleges profile and thus shared and expanded on many of the qualities that perspective users of our research would be looking for regarding financial justification within energy cost saving models and tools. A key component of the HGCI offering was The Green Campus Loan Fund (GCLF). GCLF provides capital for campus design, operations, maintenance and occupant behavior projects. The Fund provides the up-front capital for projects, while applicant departments agree to repay the fund via savings achieved by project-related reductions in utility consumption, waste removal or operating costs. This service allows departments to upgrade the efficiency, comfort, and functionality of their facilities without incurring any up front capital costs. It is clear that the size and availability of this interest-free revolving loan fund has created an economic incentive for energy and resource conservation projects that would have otherwise been considered without access to sufficient funding. A key incentive for participation was the financial structure of 0% interest and the fact that it would not interfere with capital budget cycles.

Case for Acceleration of Investment

A common problem faced when persuading decision makers to proceed with retrofitting projects is the difficulty of persuading them to prioritize the retrofit above other possible uses of capital. There is a tendency among some high-level decision makers to be reluctant to prioritize the retrofit of a system that is not clearly in disrepair. This lack of urgency often leads to waiting too long to replace equipment, which can result in emergency situations such as a chiller breaking on a very hot, humid day. The theory of acceleration and its financial justification is a vital measure that a model must possess. It is the ability to engage managers in a retrofit project now, instead of to prioritize it

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behind several others deemed more imperative due to immediate need, that is crucial to any decision model created. Retrofit tools could assist managers in avoiding such emergency situations by including a feature that demonstrates to the CFO the clear-cut financial benefits of project acceleration. In particular, this feature of a tool might compare the financial benefits to the manager under several retrofit scenarios, each beginning at a different point in time.

Other needs

In addition to the categories above, some users indicate additional needs that may be more challenging to directly incorporate into a financial tool. These include ways to:

o Demonstrate to decision makers that retrofitted buildings will provide more comfortable work spaces for inhabitants, making people more productive and more positive

o Indicate the public relations or goodwill benefits that organizations can derive from being perceived as being at the forefront of the “green” movement

o Align incentives for decision makers in different groups within the same organization. For example, separate departments within a university do not have the incentives to risk their funds for projects that do not directly benefit their group’s budgets

Although these concerns are significant in persuading decision makers to pursue retrofits, they are not as critical or helpful in this regard as clear-cut financial metrics.

5. Current Retrof it Analys is Models and Tools

To start the process of identifying the elements of the ideal retrofit analysis model, our team evaluated the existing universe of models created to assist in retrofit decision making. Our goal was to study the attributes of these models and develop an understanding of the key inputs and decision criteria in retrofit projects. This background knowledge would, in turn, enable us to better understand the trade-offs inherent to various models as well as to better engage prospective end-users when discussing their needs from such a tool. We initiated this process by identifying as many publicly-available, retrofit-related tools and models as possible. Through dialogue with our network including our project host, faculty advisor, and colleagues, we developed a target list of organizations potentially offering tools to inform retrofit decisions. These organizations included energy services companies (ESCOs), government agencies, non-profits, financial institutions, and energy efficiency financiers. In addition we performed broad Internet searches to identify additional sources. This research proved insightful regarding the organizations that did and did not provide publicly available tools. To our surprise, we found that the companies with the most significant vested financial interests, namely ESCOs, offered little in the way of publicly available tools to perform a rough estimate one’s potential energy efficiency opportunities. Instead, they offered background on the value of energy services contracts, a variety of case studies, energy

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assessment tools requiring significant custom integration, and calls to further engage their salespeople. In addition, financial institutions and energy efficiency financiers offered little in the way of tools or templates for organizations to evaluate their potential energy savings opportunities. The sources most likely to provide tools turned out to be government agencies (particularly the Department of Energy’s Energy Efficiency and Renewable Energy (EERE) division), academic researchers, and software companies specializing on the tools for building design. In total we identified approximately 50 tools and models focused on building retrofit opportunities. Within this pool, we found great variation in terms of the objectives of each tool. We developed the following broad classification system for the models:

Building Design: These tools enable architects and engineers to design building, often using CAD tools, with elements of energy efficiency analysis incorporated into the tools. Energy Simulation / Auditing / Usage Modeling: These tools enable engineers and contractors to project and audit the energy consumption of buildings based on their design and equipment installed. These tools vary from basic (targeting laymen) to highly advanced (required deep knowledge of building energy auditing) and cover a wide rage of granularity of output data provided. Specialized Retrofit Analysis: These tools assist a range of target audiences with specialized retrofit decisions based primarily on technology / equipment type (e.g. lighting) or building type (e.g. schools). Retrofit Financial Analysis: These tools are targeted towards facilities manager, financial analysts, and business managers who would make decisions regarding retrofit projects in their organizations. The tools provide a combination of estimates of the savings achievable, recommendations of projects to implement, and/or analysis of financing options.

Our team identified several models in each category. For the purposes of this research project, we chose to focus on models in the last category (noting that models occasionally overlapped multiple categories), Retrofit Financial Analysis, as they are most comparable to the Clinton Climate Initiative’s end objective for this project.

Summary of Existing Retrofit Analysis Tools of Interest

A survey of publicly available Retrofit Financial Analysis tools yields a number of tools that are relevant to this project’s objective. Although none of these models are ideally suited to this project, many have certain components that can be particularly helpful, including user-friendly interfaces, screening capabilities, useful financial metrics, and engineering focus. The following section summarizes relevant models and how our team, CCI, City Colleges of Chicago, and Shedd Aquarium can benefit from each. Our overall goal for this phase of project was to

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extract the best practices from each of these existing sources that pertain specifically to CCI’s needs. This analysis gave our team a solid understanding of the existing models and what we as a team could leverage from each. Our primary source of information for this section was a section of model overviews on the U.S. Department of Energy’s Energy Efficiency and Renewable Energy website.1 This website contains summaries of each tool examined with direct links to the tool which we used for further analysis. We categorized some of the more helpful tools into those with a user-friendly interface, those that are effective screening tools, tools that are thorough but heavily focused on engineering, and tools that provide a variety of financial metrics. This analysis demonstrated the breadth of industry best practice examples available. Based on the specific needs expressed by potential users of our model, we have concentrated our analysis specifically on the models that are based financial metric decision criteria. Some of the models we reviewed contain financial metrics that are particularly salient to this project. CCI’s partner organizations are concerned with understanding the full financial implications of their energy retrofit options. Accordingly, models that incorporate a range of financial metrics will be useful in this project. Two such models, Energy Star and Life Cycle Cost Analysis, are described below. The remaining categories of tools are described in Appendix A.

Energy Star Building Upgrade Value Calculator2 The Energy Star tool provides an assessment of building upgrade options for commercial real estate properties. The user inputs data regarding general building characteristics and plans for upgrades. The tool performs a financial analysis and provides the user with calculations of net investment, reduction in operating expense, energy savings, return on investment (ROI), internal rate of return (IRR), net present value (NPV), net operating income (NOI), and impact on asset value. The variety of financial metrics incorporated into this tool may be of particular interest to potential clients as it provides a solid breadth of financial justification for projects.

Life Cycle Cost Analysis3

The Federal Energy Management Program (FEMP) provides software, training, publications, and guidance on how to apply Life Cycle Costing (LCC) to evaluate the cost-effectiveness of energy and water investments. FEMP’s Building Life Cycle Cost (BLCC) software programs calculate life-cycle costs, net savings, savings-to-investment ratio, internal rate of return, and payback period for Federal energy and water conservation projects funded by agencies or alternatively financed. The BLCC programs also estimate emissions and emission reductions. An energy escalation rate calculator (EERC) computes an average escalation rate for ESPC contracts when payments are based on energy cost savings.

1 http://www.eere.energy.gov/buildings/tools_directory/subjects.cfm/pagename=subjects/pagename_ menu=whole_building_analysis/pagename_submenu=retrofit_analysis 2 http://www.energystar.gov/index.cfm?c=comm_real_estate.building_upgrade_value_calculator 3 http://www.wbdg.org/resources/lcca.php

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6. Test of Se lect Current Tools

In order to test the utility of the analysis from existing models, we developed specifications for a sample building retrofit energy efficiency project. This sample project is based on data from a past energy efficiency project provided by a Clinton Climate Initiative partner organization. This sample project data was then input into two separate models in order to 1) compare the outputs of the models to see if they made similar recommendations and 2) to evaluate opportunities to improve the insights delivered by the model outputs. Sample Project Profile The background and key project specs are as follows: The project host is a non-profit higher education institution based in the Midwest U.S. It has facilities totaling 5,000,000 square feet with annual energy costs (electricity and natural gas) totaling $7.5M. The retrofit project is divided into two phases, with each phase consisting of lighting and HVAC upgrades to different sets of buildings. Total savings would thus be the sum of the savings across each phase of the project.

Phase 1 of the project has a capital cost of $14.6M with annual electricity savings of $685K, $744K, and $769K in years 1-3 and annual operational and maintenance (O&M) savings of $1.1M. Installation is expected to take 13 months with the equipment then having a guaranteed life of at least 10 years. Phase 2 of the project has a capital cost of $14.7M with annual electricity savings of $394K and $628K in years 1-2 and annual operational and maintenance (O&M) savings of $1.3M. Installation is expected to take 14 months, with the equipment then having a guaranteed life of at least 10 years. Input and Output of Existing Models The sample project scenario described above was then plugged into the two models we previously identified as providing the most sophisticated financial analysis at present, the Energy Star Building Upgrade Value Calculator and the Building Life-Cycle Cost (BLCC) Program. The output from these models is then examined and recommendations on improvements for our own proposed model follow in the subsequent section.

Energy Star Building Upgrade Value Calculator

Figures 1a and 1b below display the input and output pages respectively of the model. Regarding inputs, the essential financial elements that this model includes are the project capital cost, the annual energy cost savings, the annual operations and maintenance (O&M) savings, rebates/subsidies, length of project (limited to 10 years), discount rate, loan period,

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and loan interest rate. For outputs, this model calculates essential metrics including payback period, return on investment (ROI), net present value (NPV), Internal Rate of Return (IRR), and Change in Net Operating Income. In addition, the model offers a very basic annual operating expense analysis which includes energy and O&M cost savings versus the status quo scenario and repayments of any new debt (principal and interest) used to fund the project. Figure 1a: Energy Star Building Upgrade Value Calculator Input Page

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Figure 1b: Energy Star Building Upgrade Value Calculator Output Page

● Reduce annual operating expense by: (659,813)$

● Improve net operating income by: (659,813)$

● Enhance asset value by: #DIV/0!

Net Investment Cost 29,300,000$

Net Investment Cost per SF 5.86$

Simple Payback Period (SPP) 0

Return On Investment (ROI) -2%

Net Present Value (NPV) ($33,354,268)

Internal Rate of Return (IRR) 0%

Potential Impact on Net Operating Income (NOI) (659,813)$

Potential Impact on Asset Value #DIV/0!

Before Upgrade After Upgrade Estimated Savings

ENERGY STAR Rating 50 64 14 points

Annual Energy Cost 7,500,000$ 6,256,461$ 1,243,539$

Annual Energy Cost per SF 1.50$ 1.25$ 0.25$

Phase 1 Phase 2 Labor and

Supplies

Savings

Net Operating

Expense

Reduction

Operating

Exense

Reduction per

SF

###########

Year 1 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 2 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 3 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 4 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 5 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 6 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 7 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 8 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 9 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Year 10 $732,381 $511,158 $2,362,526 ($659,813) ($0.13)

Loan Amount 29,300,000$

Loan Period 10

Scheduled Payment 355,490$

Number of Payments 120

Interest Rate 8%

Monthly Utility Bill Savings $103,628

Period Total Payments Total Principal Total Interest

Year 1 4,265,878$ 1,993,937$ 2,271,941$

Year 2 4,265,878$ 2,159,433$ 2,106,446$

Year 3 4,265,878$ 2,338,664$ 1,927,214$

Year 4 4,265,878$ 2,532,772$ 1,733,106$

Year 5 4,265,878$ 2,742,991$ 1,522,887$

Year 6 4,265,878$ 2,970,658$ 1,295,220$

Year 7 4,265,878$ 3,217,221$ 1,048,657$

Year 8 4,265,878$ 3,484,249$ 781,629$

Year 9 4,265,878$ 3,773,440$ 492,438$

Year 10 4,265,878$ 4,086,634$ 179,244$

TOTAL 42,658,782$ 29,300,000$ 13,358,782$

According to the U.S. EPA, investing in energy performance can improve the financial performance of commercial real estate.  For

the energy efficiency measures you entered, EPA estimates that if all the benefits were to flow to the bottom line, your property

would:

Financial Summary

Building Upgrade Value CalculatorFinancial Results

Energy Project Summary

Annual Energy Savings Summary

Financing Summary

Payment Summary

Back

Print

Glossary

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Building Life-Cycle Cost (BLCC) Program

Figures 2a and 2b below display the input and output pages respectively of the model. Relative to the Energy Star model, this model allows for more flexibility in calculating the annual costs/benefits of efficiency project; however, it is significantly less sophisticated in how it considers capital funding of the project. Regarding the inputs the model collects, essential financial elements that we observed include variable cost savings (energy only) over the project life, phasing of capital costs, equipment life, and residual value. Relevant financial outputs from this model included side-by-side PV comparisons of project alternatives, IRR and payback period. Figure 2a: Building Life-Cycle Cost (BLCC) Program Input Page

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Figure 2b: Building Life-Cycle Cost (BLCC) Program Output Page

Analysis and Summary of Existing Models In reviewing these two models, clear differences emerge regarding their evaluation techniques. The Energy Star model concludes that this project has a negative NPV while the BLCC model suggests that the project has a positive PV. The key difference between these two analyses is that the BLCC model does not allow for user-defined costs of capital while the Energy Star model incorporates the concept of time value of money and discounted cash flows, an essential element as a company or organization considers a range of funding sources. If one discounts the future cash flows input into the BLCC model, a similar conclusion as the Energy Star model emerges. The Energy Star model offers room for improvement as well, however. It looks at the economics of efficiency retrofit projects on an absolute basis. This approach makes sense if one is considering replacing otherwise well-functioning equipment. However, if one is making an investment decision regarding equipment being replaced (or soon in need of replacement), then a comparative analysis must be performed instead where the relative economics of the two options are considered. After all, a building will always need lighting, HVAC etc and thus the decision cannot always be looked at from an absolute NPV standpoint. In fact, in our conversations with various building owners, we found that efficiency projects often made the

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most economic sense to organizations when they were replacing equipment already at the end of its useful life. This insight offers us a further opportunity to enhance current financial model frameworks.

7. Gaps in Existing Tools

The testing of the performance of the financial tools above provides great insight into opportunities to improve upon their foundations. As we consider the user needs from the perspective of a CFO who would be making a financial decision, several additional requirements become clear. These models can be refined both on the input side and the output side, or in other words, by broadening the scope of what factors are considered as well as expanding upon the resulting analysis and insights provided. On the input side, we see a clear need from the feedback that we have received for more sophisticated financial modeling than we see across these two models. Users want to understand the cash flow impacts on these projects as the budgeting and funding issues are often key sticking points for these investments. In order to develop a true picture of these cash flows, additional inputs are required including:

Extension of business as usual scenarios to include any prospective replacement costs for existing equipment

Differential timing of investment outlays and the start of efficiency savings

Mixed capital funding sources (e.g. loans, grants, capital reserves)

Tax shields (for for-profit entities) resulting from increased depreciation

Variable annual savings (energy and O&M) over the project life Regarding the analysis a financial tool would perform and the presentation of results, we once again see opportunities to improve the baseline offered by these existing models. As cash and budgeting impacts are a central consideration of efficiency projects, the most value added analysis would be clear annual comparison of the total impacts to cash flow. This cash flow summary should include three scenarios—business-as-usual, accelerated project investment (via lending), and delayed project investment (via capital reserves)—in order to offer a useful comparison for financial decision makers. In addition, many decision makers lose sight of the energy savings that are permanently lost by delaying or indefinitely putting off projects. A metric which highlights the energy savings that would be permanently forgone would help decision makers to understand the value of using loans to finance projects instead of waiting to accrue adequate capital reserves.

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8. Suggested Addit ions to Ex isting Models

An ideal tool will incorporate many of the financial metrics and plowback options included in current tools, but will also address the gaps in current tools. Incorporating a feature that calculates the benefit of project acceleration would make a tool more useful. Project acceleration has been shown to create real economic benefits in areas outside of building retrofits. For example, the U.S. Department of Transportation has used financial tools to calculate the benefits of accelerating highway improvement projects.4 The average amount of time saved per project for the sixty accelerated highway improvement projects was 2.2 years. Accelerating these projects allowed the Department of Transportation to avoid maintenance and repair costs associated with maintaining an out-of-date highway system. Similar to the highway projects, retrofitting buildings sooner rather than later results in avoidance of maintenance and repair costs. Retrofitting of buildings also provides other benefits, including energy savings. A suggested model demonstrating these benefits is below.

Suggested Model

The suggested model to be used by CFOs would simulate cash flow changes over a given period (e.g. 10 years) to demonstrate ongoing savings. The model would show various scenarios, such as: doing nothing, starting the retrofit project now, and starting the retrofit project in three years. A comparison of cash flow changes for the various scenarios will clearly distinguish the expected outcome of investment decisions. The input fields include:

- Scenario: - For-Profit/Non-Profit - Implementation period (year) - Annual energy cost ($M) - Size of facility (square ft) - Existing equipment replacement period (in x yrs) - New equipment life (years) - Financing type (interest free, loans) - Interest rate - Payback period - Tax rate - Subsidies - Rebates - Inflation (%/year)

4 http://www.fhwa.dot.gov/innovativefinance/eval-es.htm

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Below are sample inputs for three scenarios: do nothing, implement now, and implement in year three.

Scenario 1: Do Nothing

This scenario assumes no retrofit project will be implemented and equipment will need to be replaced at the end of its useful life, which is in year 3. The cash flow includes continued depreciation from capital equipment as well as loans to purchase replacement equipment. There is no savings in energy or operational maintenance. Figures 3a and 3b illustrate this scenario. Figure 3a. Scenario 1 (Do Nothing) Calculation of Net Cash Flow

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Figure 3b. Scenario 1 (Do Nothing): Graphs of Change in Cash Flow

The graph for net change in cash flow shows depreciation costs and cost of equipment replacement. The graph for cumulative change in cash flow indicates a continuous cash outflow due to depreciation and cost of replacement equipment

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Scenario 2: Implement Now

In this scenario, funds for the retrofit project are spent in year 1 and savings in both electricity cost and operational & maintenance costs begin to be realized in year 2, and thereafter. Cash outflow is incurred by financing activities for capital equipment. Figures 4a, 4b, and 4c illustrate this scenario. Figure 4a. Scenario 2 (Implement Now): Calculation of Net Cash Flow

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Figure 4b. Scenario 2 (Implement Now): Graphs of Change in Cash Flow

The graph for net change in cash flow shows an increase in cash flow due to energy and operations & maintenance savings at an increasing rate. The graph for cumulative change in cash flow indicates an initial dip in cumulative change in cash flow. However, as savings from retrofit project are realized, the cumulative change in cash flow becomes positive at an increasing rate. The graph in energy savings illustrates exponential electricity cost savings.

Figure 4c. Scenario 2 (Implement Now): Annual Savings

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Scenario 3: Implement in Year 3

In this scenario, the retrofit project is implemented three years later than it was implemented in Scenario 2. Cash flow and annual savings are illustrated in Figures 5a, 5b, and 5c below. Figure 5a. Scenario 3 (Implement in Year 3): Calculation of Net Cash Flow

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Figure 5b. Scenario 3 (Implement In Three Years): Graph of Change in Cash Flow

Figure 5c shows that energy savings do not being until year 4. Thereafter, savings are incurred at an exponential rate. Figure 5c. Scenario 3 (Implement In Three Years): Annual Savings

The graph for net change in cash flow shows a delayed increase in cash flow due to energy and operations & maintenance savings that starts in year 4 when energy savings are being realized one year after retrofit project implementation. The graph for cumulative change in cash flow indicates a downward dip until around year seven.

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Comparison of Different Scenarios

Based on the input from different scenarios, our model framework simulates cash flow changes and plots the graphs for the various scenarios. Most importantly, it shows the relative differences in annual cash flow as well as cumulative cash flow as illustrated below in Figures 6a and 6b. As the graph clearly illustrates, by implementing a retrofit project now, savings can start incurring in year two and positive net change in cash flow begins around year 5. The later a retrofit project is implemented, the later the savings begin to incur. And in comparison, in the do nothing scenario, net change in cash flow remains negative. A similar pattern is shown in the cumulative net change in cash flow graph. Figure 6a.Comparison of Scenarios 1, 2, and 3: Annual Net Change in Cash Flow

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Figure 6b.Comparison of Scenarios 1, 2, and 3: Cumulative Net Change in Cash Flow

The sample outputs above clearly demonstrate savings from implementing retrofit projects as soon as possible. This model may be used in conjunction with a net present value (NPV) calculation as shown in Figure 2b: Building Life-Cycle Cost (BLCC) Program Output Page to justify accelerating funding for building retrofit projects.

9. Conclus ion and Areas for Future Explorat ion

This paper has outlined a framework for an innovative model used by decision makers regarding an assortment of retrofit projects of existing buildings for a variety of different building types. Our paper and accompanying model framework have been focused most notably on the financial metrics and decision points that make retrofit initiatives plausible and desirable for companies.

There are, however, a variety of other considerations that were not specifically discussed in our report. To begin, the human resource cost and capacity that accompany a major design renovation of an existing building will most likely be quite substantial both on a time and cost basis and must be considered. Additionally, the carbon pricing environment will need to be thoroughly examined, including potential taxes levied against carbon emissions, and effects that may have on retrofit decision making, as well as cap and trade arrangement that may exist in the carbon market. Another very important area to examine in complement with our proposed tool is that of asset appreciation. It will be important for decision makers to understand not only the cost savings derived from project acceleration and decreases in energy usage, but also the increased net present value of retrofit projects and accompanying fixed assets of the firm upon completions of each retrofit project.

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Additionally, the Clinton Climate Initiative should consider what partnerships could be formed through the creation of our proposed tool. CCI could team with FEMP’s Building Life Cycle Cost (BLCC) software, leveraging their in-depth financial project justification output calculations as well as their estimate of emissions and emission reductions tools, and combine that with the case for project acceleration outlined in our model to provide a complete proposal to potential clients. A similar arrangement could be beneficial with the U.S. Department of Energy’s (DOE) Energy Efficiency and Renewable Energy division. The DOE's Building Technologies Program works in partnership with states, industry, and manufacturers to improve the energy efficiency of US buildings. Our model for acceleration could be coupled with the DOE’s well established systems-engineered building practices to form an enticing proposal for partial or complete design retrofit of existing buildings around the country.

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10. Appendix A: Bui lding Retrof it Tools by Category

User-friendly interface

The following three tools, AUDIT, Energy Profile Tool, and EZ Sim, all provide user-friendly analyses of the financial benefits of energy conservation methods. Understanding the structure, format, and interface of each tool and the reasons users find them manageable will be of particular use in this project. Although the three tools vary in their approaches to user-friendliness (i.e., AUDIT’s monthly bin method, EPT’s benchmarking approach, and EZ Sim’s use of case study examples), each can prove helpful in some way to City Colleges of Chicago and/or Shedd Aquarium. In general, these models’ weaknesses are the lack of in-depth analysis that City Colleges of Chicago and Shedd Aquarium will ultimately seek. AUDIT (http://www.elitesoft.com) The AUDIT tool requires minimal input data for obtaining HVAC operating costs. It can serve as an excellent sales tool for demonstrating the benefits of using high efficiency equipment. However, the simple and easy to use monthly bin method of energy usage calculation does not allow the simulation sophistication provided by hourly energy analysis methods and may be too high level for the particular needs of the clients of this project. This tool is made available through EERE website, but not free of charge. This tool calculates monthly and annual heating and cooling costs for residential and light commercial buildings. Virtually any type of cooling and heating system can be simulated by AUDIT including standard DX, evaporative, air source heat pumps, water source heat pumps, and all types of fossil fueled furnaces and boilers (both modulating and on/off controlled). AUDIT uses monthly bin weather data and full load cooling hours in its calculations. Weather data for hundreds of cities throughout the world are built-in to AUDIT and additional weather data can be easily added. Along with calculating energy costs, AUDIT also performs an economic analysis that allows you to compare system types and costs over any given study period. There is also a loan and lease analysis report designed to demonstrate affordability of better systems by showing that the effective net monthly cost is often very low when monthly energy savings are considered. To make system comparisons easy, AUDIT allows you to manually enter equipment data or automatically look it up for you from ARI and GAMA equipment data files. AUDIT provides a wide selection of nicely formatted color charts, graphs, and reports. AUDIT shares data with Elite's RHVAC, CHVAC, and Quick Quote programs. Energy Profile Tool (http://www.energyprofiletool.com) EPT is a customizable, commercially available energy analysis tool. Users enter information about their facilities to receive detailed profiles of the energy use, as well as benchmark comparison results. The tool helps identify opportunities to reduce energy and costs, and take the next steps to long-term savings. It is intended for entry-level analysis and is not detailed enough to assess very specific energy management scenarios that City Colleges of Chicago and Shedd Aquarium may be more interested in. EPT users supply information about their building type, weather region, floor area and general HVAC system. Our clients for the CCI project should also provide billing data for benchmarking

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to be most relevant. However, specifying general shell, HVAC, lighting and equipment, and DHW information provide for a more accurate analysis. The tool provides a quick, initial estimate on building energy performance and benchmarking, including relative greenhouse gas emission levels. The tool helps identify opportunities to reduce energy and costs, which is intended to act as early decision-making tool to empower the user to take the next steps to securing energy savings. EZ Sim (http://www.ezsim.com) EZ Sim lets clients use their existing utility bills to calibrate a simulation of a commercial facility in an interactive graphic window. Once it matches your bills, the simulation model can provide reliable estimates of potential conservation savings. The calibration process reveals how energy is used within the facility, helping diagnose why there is excessive consumption or poorly functioning building components. Potential users can review case study examples on the web site that closely resemble their specific facility. The model also provides precision and confidence limits of savings estimates consistent with IPMVP performance verification protocol. The simulation is easily tuned to match the actual bills of a client, and provides performance targets to compare against post-retrofit bills. EZ Sim is a simplified model, and is not easy to use with more than one heating or cooling plant.

Screening: Narrowing down options for further analys is

The following tools, FRESA and FEDS, provide a way for users to narrow down a range of energy-saving options into one or two options that provide the greatest potential for cost savings. These tools can be useful in this project. However, similar to the previously discussed models, the shortcomings of these models are the lack of depth of analysis of any one energy-saving approach. FRESA (http://www1.eere.energy.gov/femp/information/access_tools.html) FRESA (Federal Renewable Energy Screening Assistant) provides life-cycle cost calculations to determine which energy-saving approaches are most likely to provide cost savings. FRESA is a screening tool, and does not provide the depth of analysis that will ultimately be required for this project. However, it provides an interesting starting point for further, more detailed analysis. This tool can be applied in a variety of locations, with a variety of building uses. FRESA was designed for use by building energy auditors, and requires some knowledge of energy audits. It requires some basic data input, including energy load use, building occupancy, and ZIP code. Other required inputs, such as biomass and solid waste resource data, may be more complicated to obtain. The tool uses the inputs to calculate a life-cycle cost comparison between using an energy-saving approach and not using the approach. It also uses comparisons of savings-to-investment ratios and feasibility for a variety of energy-saving approaches, to determine which approach is most promising. Energy-saving approaches included in the model are: active solar heating, active solar cooling, solar hot water, daylighting with windows or skylights, photovoltaic, solar thermal electric, wind electricity, small hydropower, biomass electricity (wood, waste, etc.), and

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cooling load avoidance (multiple glazing, window shading, increased wall insulation, infiltration control). FEDS (http://www.pnl.gov/feds) FEDS (Facility Energy Decision System) provides a comprehensive method for quickly and objectively identifying energy improvements that offer maximum savings to existing buildings. FEDS makes assessments and analyzes energy efficiency of single buildings, multiple buildings, or all buildings of an entire facility. It provides an easy-to-use tool for identifying energy efficiency measures, selecting minimum life-cycle costs, determining payback periods. Additionally, it enables users to prioritize retrofit options and compare alternative financing options (site funding, leases, loans, ESPCs). This could be a particularly useful component for our clients during this project.

Thorough, but Engineering -Focused

Market Manager (http://www.abraxasenergy.com/marketmanager.php) Executive Summary: Market Manager can analyze any type of commercial, institutional, industrial, and residential facility and determine the energy and cost impact of nearly any type of energy conservation measure. The tool determines the cost-effectiveness of improving the building envelope (windows, walls, etc.), HVAC controls, motors, lighting systems, heating and cooling equipment and thus could be applicable to the client’s needs for this project. However, the tool analyzes energy savings in depth in addition to cost savings, and therefore requires an understanding of HVAC for effective model construction. Market Manager: This tool requires data regarding building walls and windows, occupancy, lighting and internal equipment, and HVAC system information. It allows users to shortcut certain inputs, and use default values, templates, or values from an included data library. The tool compiles the input data and analyzes it to produce a cost-effectiveness analysis for the energy conservation measure indicated by the user. Users can either perform a full-building analysis, or select specific energy-saving measures to analyze. For example, users can compare multiple "what if" scenarios (i.e., replacing existing lighting with more efficient fixtures, comparing electric and gas-fired equipment, or comparing standard and incentive rate schedules.) All energy-using equipment is modeled on an hourly basis. The tool evaluates the cost impacts of system changes, including demand charges, load factors, ratchets, and time-of-use variation.

Residentia l Models with Some Applicabi l ity

Two models designed for use in residential buildings, Energy Aide and Rehab Advisor, provide some insights that may not be directly applicable, but still a valuable reference point for this project. Although the client organizations are not residential in nature, there may be some overlap between an analysis appropriate for the clients and an analysis appropriate for a residential building.

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Energy Aide (http://www.eere.energy.gov) – Energy New England Energy Aide is designed for residential energy audits, and is therefore not directly applicable to this project. However, the tool’s user-friendly, efficient approach to calculating energy savings costs from retrofitting buildings make it an interesting starting point for our analysis. This tool could provide a method for simplifying complex retrofitting analysis into a model that is usable for a wide range of users. Required input includes square footage of envelope measures, heating system characteristics, and temperature settings. The tool’s calculation of cost savings from different energy saving measures relies on cost and savings assumptions and climatic data. The tool’s output is a twenty-page report with easy-to-follow graphs and charts. Although Energy Aide does not perform a full simulation or calculate full building loads, it is manageable for users without extensive technical knowledge. Rehab Advisor (http://rehabadvisor.com) Designed for homeowners, contractors, architects, housing authorities, development agencies, facility managers and others to improve energy efficiency in existing residences during renovation and remodeling. The tool is very high-level, and through “six clicks” the Rehab Advisor provides recommendations for cost-effectively increasing the energy efficiency of a typical renovation project in single-family or multifamily housing. These recommendations are based on the building type, location, and specific projects. The tool may be somewhat applicable for City Colleges of Chicago, but obviously less so for Shedd Aquarium. Rehab Advisor is a very simple tool for estimating the costs and savings of incorporating cost-effective energy efficiency improvements into remodeling projects. The user does not have to do any computer modeling or other calculations.

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References:

User-friendly Interface Models:

AUDIT (http://www.elitesoft.com)

Energy Profile Tool (http://www.energyprofiletool.com)

EZ Sim (http://www.ezsim.com)

Screening Models:

FRESA (http://www1.eere.energy.gov/femp/information/access_tools.html)

FEDS (http://www.pnl.gov/feds)

Financial Metric Models:

Energy Star Building Upgrade Value Calculator

(http://www.energystar.gov/index.cfm?c=comm_real_estate.building_upgrade_value_calculator)

Life Cycle Cost Analysis (http://www.wbdg.org/resources/lcca.php)

Market Manager (http://www.abraxasenergy.com/marketmanager.php)

Residential Models

Energy Aide (http://www.eere.energy.gov)

Rehab Advisor (http://rehabadvisor.com)

Other References Used:

U.S. Department of Energy’s Energy Efficiency and Renewable Energy (http://www.eere.energy.gov/buildings/tools_directory/subjects.cfm/pagename=subjects/pagename_menu=whole_building_analysis/pagename_submenu=retrofit_analysis)

Harvard Green Campus Initiative (http://www.greencampus.harvard.edu/)

MIT Green Fund http://sustainability.mit.edu/Green_Fund

Duke Environmental Alliance http://www.duke.edu/web/env_alliance/campaigns.html

Conversations with CCI personnel, personnel from CCI’s partner organizations, Johnson Controls, and NStar