Quantifying potential savings from sustainable energy projects at a large public university: An energy efficiency assessment for texas state university

Sustainable Energy Technologies and Assessments 37 (2020) 100570

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Quantifying potential savings from sustainable energy projects at a large public university: An energy efficiency assessment for texas state university

T

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Milad Mohammadalizadehkorde , Russell Weaver Texas State University, United States

A R T I C LE I N FO

A B S T R A C T

Keywords: Sustainability Energy efficiency Sustainability in higher education University energy consumption Financial analysis CO2 emission Scope 2

At Texas State University (TSU) in the United States, “sustainability” is pursued within the context of (1) a nonbinding declaration in the University’s plan, and (2) a State legislative directive to reduce energy consumption. Grounded in these direct links between sustainability and energy use, this paper evaluates energy efficiency at TSU. The aim of the applied case study is to inventory current (business as usual) energy consumption levels at TSU, and to understand how those levels might change under a regime of more sustainable energy technology. The paper performs financial analysis to show that selected sustainable energy projects can not only reduce energy use at TSU, and thereby strengthen the University’s commitment to sustainability. Sustainable energy projects will also save the University money in the long run. The case study draws on a sample of the 13 oncampus buildings with the highest current levels of energy consumption. The approach of the paper is to determine the level of attractiveness of investing in new technology by calculating the Net Present Value (NPV) in terms of financial savings every year (simple payback) or a more extended period (cash flow model). The environmental impact is calculated in terms of CO2 emission based on Scope 2 methodology. We find that TSU could achieve annual electricity savings of 15,391,436 kWh (17% of its annual energy costs) from implementing selected projects and save more than $1,000,000 in annual costs. Overall, TSU could reduce CO2 emissions by 12,561.81 metric tons. The shortest payback period belongs to the pump replacement, and the most significant annual kWh saving is represented by the replacement of the lighting system. Solar panel installation has the highest upfront investment reaching more than $7 million, while its implementation will bring the highest environmental impact by avoiding 2926.81 metric tonnes of CO2 every year. However, the recommended minimum cost of energy at 14–16 (¢/kWh) for solar panel implementation cannot compete with the 8 cents per kWh paid for the electricity at San Marcos. The findings have immediate practical relevance for campus planning at TSU, and the methods are replicable and extendable for use by practitioners and researchers at other Universities or large institutions.

Introduction Most scientists agree that organizations, industries, and governments must adopt more ecologically sensitive practices to prevent further degradation of the environment [1]. While much of this literature focuses on integrating “sustainability” into business practices [2] and reconciling profitability with corporate social responsibility and sustainability [3], there is a thriving line of research on sustainability initiatives and practices at colleges and universities [4,1]. Among the reasons for this interest are that (1) academia plays a prominent role in the production of knowledge about sustainability and sustainable practices [5,6]. Also, more practically, (2) college and university campuses tend to function as their own spatially-based communities and

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might, therefore, offer scalable models for creating more sustainable neighborhoods, cities, and regions [4]. Nevertheless, while universities are recognized for their important role in research in and education on sustainability, in the main, they have not been successful in achieving institutional scale “sustainable” operating practices [1]. One potential reason for this outcome is that many sustainability-related initiatives in higher education are established within non-binding declarations. Crucially, signing a declaration will not necessarily lead to a successful environmental commitment [6–8], insofar as violating the terms of such declarations does not result in sanctions [8]. In that sense, the barriers to integrate sustainability into universities are mainly internal [1]. Apart from the lack of enforcement that accompanies non-binding

Corresponding author. E-mail address: [email protected] (M. Mohammadalizadehkorde).

https://doi.org/10.1016/j.seta.2019.100570 Received 6 May 2019; Received in revised form 8 October 2019; Accepted 7 November 2019 2213-1388/ © 2019 Elsevier Ltd. All rights reserved.

Sustainable Energy Technologies and Assessments 37 (2020) 100570

M. Mohammadalizadehkorde and R. Weaver

Nomenclature A AI Cu d dn dr E EF ER e fc F Fn Fm Hd hp hs HT L LI lb LLF Lf I i MF m n η PF Ph (hp) Ph (kW) ρI r Sf t T UF

CFL CH4 CO2 COE CREST DCF EAA EBITDA

Activity Rate Area Per Lamp in Squared Meter Coefficient of Utilization Discount Rate to Equate Cash Flow Nominal Discount Rate Real Discount Rate Emission Emission Factor Overall Emission Reduction Efficiency Constant Inflation Foot Candle Required number of Fixtures Constant Dollar Cash Flow Cash Flow in Current Dollars in a Year Suction Head Horsepower Discharge Head Total Head Required Lux Lumens per lamp Pound Light Loss Factor Lumen Per Fixture Illumination Interest Rate Maintenance Factor Year Number of Compounding Periods per Year Efficiency as Operated in % Power Factor Hydraulic Horsepower Hydraulic Power Three-Phase power in kW Discount rate Square Feet Converted to Square Meter Time, Number of Years Project’s Useful Life Utilization Factor

Es EGRID EPA ERCOT EUI FCF FCR FV FY GHG GSF Hr HVAC IAS ICC IRR ITC kWh LED LEED LCC LCR LLC MCF MWh N2O NPV NREL O&M Od P1kWh P2kWh PV REC SB SECO SI TSU VFD WAAC

Abbreviation AC AEP_net AOE ASHRAE BTU CAV CBECS DC

Alternating Current Net annual energy production (kWh/yr) Annual operating expenses American Society of Heating, Refrigerating and AirConditioning Engineers British Thermal Unit Constant Air Volume Commercial Buildings Energy Consumption Survey Direct Current

Compact Fluorescent Lamps Methane Carbon Dioxide Levelized cost of energy ($/kWh) Cost of Renewable Energy Spreadsheet Tool Discounted Cash Flow Equivalent Annual Annuity Earnings before Interest, Tax, Depreciation, and Amortization Energy saving Emission & Generation Resources Integrated Database United States Environmental Protection Agency Electric Reliability Council of Texas Energy Utilization Index Free Cash Flow Fixed charge rate (constant $) (1/yr) Future Value of Money Fiscal Year Greenhouse Gas Gross Square Feet Hours of operation Heating, Ventilation and Air Conditioning International Accounting Standard Initial capital cost ($) Internal Rate of Return Investment Tax Credit kilo Watt-hour Light Emitting Diodes Leadership in Energy and Environmental Design Life Cycle Cost Levelized replacement/overhaul cost (10.7/kW in Ref. [26]) Land lease cost One Thousand Cubic Feet Mega-Watt Hour Nitrogen Oxide Net Present Value National Renewable Energy Laboratory Operation and Maintenance Cost Operation days Power consumption of the current light bulb Power consumption of the suggested replacement (LED) Present Value of Money Renewable Energy Credit Senate Bill Texas State Energy Conservation Office International System of Units Texas State University Variable Frequency Drive Weighted Average Cost of Capital

long run, is arguably a necessary first step in breaking away from business as usual. Toward that end, the remainder of this paper presents an energy efficiency assessment case study for Texas State University (TSU). As expanded on below, TSU has a rhetorical institutional commitment to sustainability in its campus master plan. At the same time, TSU is required by state legislation to take measures that will reduce its future electrical energy consumption. This state mandate, coupled with the University’s internal commitment to sustainability, suggests that energy infrastructure might be a key leverage point at which institutional decision-makers can begin to make immediate interventions to become

declarations, perhaps the most significant impediments to sustainability initiatives at higher education institutions are financial constraints. Particularly, short term budgetary decisions often undermine the possibility of implementing sustainability projects, whose returns are generally realized on longer-term time horizons [1]. Along those lines, it is essential for researchers and practitioners to clearly—and quantitatively—document the fiscal benefits of investing in sustainability projects today. While some decision-makers may lack patience and prefer to continue making budgetary decisions that satisfy immediate needs at the expense of future gains, empirical evidence of “win–win” scenarios, in which energy consumption and costs both decrease, in the 2

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M. Mohammadalizadehkorde and R. Weaver

more “sustainable”—operationalized as energy efficient for present purposes (though, see Ref. [9] for a discussion of the many meanings of the sustainability concept). Following from the preceding paragraph, then, one potential way to catalyze intervention at this leverage point is to generate empirical evidence that new, comparably “sustainable” energy investments will allow the University to comply with the state mandate to reduce energy and will result in fiscal savings for TSU (i.e., a “win–win”). On the other hand, contrary evidence would seemingly provide decision-makers with a defense for the following business as usual practices and not investing in new energy technologies. Either way, then, financial analyses that document the (un)attractiveness of University investments into selected sustainable energy projects arguably hold the keys to moving the conversation forward. The remainder of this paper is an initial attempt to advance that discourse. Texas State University (TSU), in its non-binding campus master plan, has identified sustainability as one of its most important strategic goals [10]. Complementing that commitment, the State of Texas, in Senate Bill (SB) 898, has mandated that certain political subdivisions and public institutions—including TSU—reduce their electrical energy consumption by at least 5% each year for ten years, beginning September 1, 2011. Entities affected by SB 898 must submit annual reports to the Texas State Energy Conservation Office (SECO) regarding their progress and efforts to meet this goal. As part of the reporting process, any “political subdivision, an institution of higher education or state agency that does not attain the goals established “must provide justification” to SECO. The burden is therefore, on the entity to establish that non-attainment occurred after all cost-effective measures were taken (SB 898 [emphasis added]). Not unlike non-binding sustainability declarations that are critiqued for their failure to sanction violations [8], this clause from SB 898 provides a mechanism for institutions (e.g., TSU) to avoid compliance with the legislatively mandated energy reduction without penalty. That is, institutions need not meet the mandated 5% per annum reduction in electrical consumption if they offer compelling evidence that further action toward such ends would create cost burdens. With that in mind, recent technical reports show that TSU has been decreasing its electricity consumption by retrofitting buildings, upgrading equipment, and constructing new buildings based on LEED criteria (Table 1) (Texas State University, Fiscal Year 2016 Energy Conservation Accomplishments for SB 898 report). Moreover, the University did attain the legislatively mandated 5% reduction in electrical consumption for the first five years following the passage of SB 898—from 2012 to 2016. For these reasons, through retrofits, upgrades, and new construction, TSU is plausibly achieving internal (University master plan) and external (SB 898) goals of sustainable energy consumption. However, in the most recent fiscal year for which final data are available (2016), TSU’s natural gas consumption increased by 3.1%, even though the University’s total square footage footprint decreased from 721,248 square meters to 717,210 square meters (equal to −0.5%) (Table 2). The decrease in the area was the result of several demolitions of old buildings and dorms around campus. A potential weakness of SB 898 is that it only restricts electrical consumption. Indeed, gas consumption accounts for a significant portion of energy use at TSU (24%). Thus, while the Bill acts as somewhat of a regulatory mechanism for moving TSU’s commitment to sustainability beyond words and into action, it might not go far enough. Accordingly, financial analyses aimed at quantifying the attractiveness of investments into sustainable energy technologies could benefit from being more inclusive than SB 898 and incorporating additional forms of energy consumption into their calculations.

Electricity consumption constitutes 76% of all energy costs on campus, with the remaining 24% being attributed to natural gas. According to the EnergyCAP, an application used for reading energy consumption, the consumption period at TSU on readings from April 2015 to April 2016. The primary building activities are classrooms and labs (educational uses), residential units, offices, and health care facilities. Rather than evaluate the performance of all 266 buildings, this paper used these primary building functions as a starting point to select a sample of structures and determine their baseline of the Energy Utilization Index (EUI). This approach offers the possibility of conducting a comparison between the Commercial Buildings Energy Consumption Survey (CBECS 2012) and the actual energy consumption of each building, which would be cost- and time-prohibitive to do for 266 structures. U.S Energy Information Administration provides CBECS. This is a national sample survey that collects information on energy usage, including consumption and expenditures. Tables C21 and C14 in CBECS have been used to determine the baseline of electricity consumption at Texas State University. That being said, the sample for this case study consists of the 13 buildings on the main TSU campus that consume the most energy (Fig. 1). Table 3 describes the essential characteristics of these structures, which represent the range of building uses described above (educational, residential, industrial, office, and healthcare). The aggregate area of the 13 buildings surveyed is approximately 1,650,88 m2. Observe that total electricity consumed by the 12 buildings and Central plant (Table 3) reached 80,180,457 kWh in 2015, which is equivalent to the energy consumed by 7448 homes in 2016. This is based on the average annual electricity usage of a US single-family home equal to 10,764 kWh, determined by the 2016 Average Monthly Bill-Residential report published by U.S. Energy Information Administration (EIA). Buildings in the sample were first constructed between 1938 (Evans Liberal Arts) and 2006 (McCoy Hall), and one structure (Alkek Library) received significant upgrades and renovations in 2003 and 2016. Among other things, Table 4 shows the electricity costs and share of electricity consumption in the sample for the 13 buildings. Note that just one facility, Central Plant (CoGeneration), accounts for over threequarters of consumption in the sample. The reason for such high consumption is that the building is in charge of providing energy (cooling, heating) to 84 buildings. In addition to costs, Table 4 presents an EUI comparison based on the CBECS of 2012 (released in May 2016). The numbers for the CBECS’s EUI come from Table C21-Electricity Consumption and Conditional Energy Intensity by Building Size, retrieved from the CBECS of 2012. Based on CBECS Table C21, most TSU sample buildings report EUIs that indicate relatively controlled electrical consumption. A summary of electricity consumption in the sample buildings is presented in Table 4, which shows that almost all selected buildings recorded a lower EUI compared to the average presented in CBECS. The renovated buildings such as McCoy hall show the best output in terms of electricity consumption per square meter while Roy Mitte building exceeds the national average due to the existence of industrial labs. Using these baseline energy consumption characteristics as a point of departure, the following sections discuss the methodology and results of a financial analysis designed to quantify the attractiveness of selected new energy investments that might reduce energy consumption across Table 1 Electric consumption based on fiscal year and savings at Texas State University.

Building sample for the energy assessment TSU spreads across 184.941 ha in the city of San Marcos, TX, and contains 266 main buildings that feature 706063 square meters of area. 3

Fiscal Year

Gross Area in m2

Consumption (kWh)

Consumption Per m2 (EUI)

% Savings

FY12 FY13 FY14 FY15 FY16

659,836 696,160 697,982 721,248 717,210

121,184,231 118,753,429 120,167,425 116,461,145 116,468,027

183.6 170.5 172.1 161.4 162.3

Base Year −7.11 −6.25 −12.08 −11.58

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M. Mohammadalizadehkorde and R. Weaver

Table 2 Gas consumption based on fiscal year and savings at Texas State University. Fiscal Year

Area in m2

Consumption m3

Consumption (BTU)Joule

% Saving

FY12 FY13 FY14 FY15 FY16

659,836 696,160 697,982 721,248 717,210

11,269,935 10,075,473 11,009,250 11,642,103 12,006,427

428,304,016,987,797 382,909,563,693,076 418,396,915,924,993 442,448,250,333,749 456,293,330,374,783

Base Year −15.26 −7.65 −5.49 −1.98

Fig. 1. Building Sample at Texas State University.

plausibly convince decision-makers to invest in sustainable energy projects using the same language of costs and benefits that tends to underwrite executive budgeting processes. For that reason, the energy efficiency assessment performed for TSU in this case study was based on a financial-economic approach. A financial analysis aims to identify the options with the highest economic returns from a set of alternatives. In this case, alternatives are business as usual technology versus selected, comparably sustainable energy investments that would reduce energy consumption. The goal of

the building sample. Methodology Cash flow, free cash flow, and discounted cash flow Research suggests that evidence of demonstrable financial savings can help to overcome internal barriers that stand in the way of sustainable energy initiatives [6]. More specifically, financial analyses can Table 3 Sample buildings with annual electricity consumption. Building Name

Year of Construction/Renovation

Principal Building Activity/CBECS Category

Square Meter

kW/hr 2014–2015

Alkek Library JC Kellam LBJ Student Center Jowers Center McCoy Hall Evans Liberal Arts Student Health Center Roy F. Mitte San Jacinto Hall Student Rec Center Supple Science East Chiller Plant

1990/2003/2016 1969/1973 1978/1997 1978/1996 2006 1938 2004 2003 2004 1994 1991 1969

Education Office Mix Education Education Education Health Care Education Residential – Education Industrial

29,132 19,465 20,531 13,425 11,833 10,328 2449 14,162 12,871 15,174 10,279 1116

3,154,484 1,842,136 2,171,532 1,685,760 691,518 689,123 239,140 3,339,883 865,159 684,039 174,000 2,373,841

4

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Table 4 Sample building baseline comparison between CBECS EUI and actual EUI. Building Name

Electricity Cost (2014–2015)

Electricity Consumed Based on the Sample Size

EUI (kW/hr)

CBECS EUI Based on Square Feet (Table C14 of CBECS)

CBECS's EUI by Building Size and Activity (Table C21)

CBECS's EUI by the Year of Construction (Table C21)

Alkek Library JC Kellam LBJ Student Center Jowers Center McCoy Hall Evans Liberal Arts Health Center Roy F. Mitte San Jacinto Hall Student Rec Center Supple Science Central Plant East Chiller Plant

$252,358.72 $147,370.88 $173,722.56 $134,860.80 $55,321.44 $55,129.84 $19,131.20 $267,190.64 $69,212.72 $54,723.12 $13,920.00 $4,981,587.36 $189,907.28

3.93% 2.30% 2.71% 2.10% 0.86% 0.86% 0.30% 4.17% 1.08% 0.85% 0.22% 77.66% 2.96%

10 9 10 12 5 6 9 22 6 4 2 1,336* 197.49*

16.9 16.9 16.9 15.3 15.3 15.3 12.8 15.3 15.3 15.3 15.3 12.8* 11.7*

10.8 19.4 NA 10.8 10.8 10.8 24.1 10.8 15 20 10.8 NA 17.1

17.8 16.4 NA 18.1 18.5 13.1 12.4 16.2 18.5 17.8 17.8 NA 12.6

*Not significant since it belongs to the industrial section.

Definitions of key terms and parameters used in the cash flow model

the analysis, therefore, is to determine the level of attractiveness of investing in new technologies—for example, replacing compact fluorescent lamps (CFL) with light-emitting diodes (LED)—in terms of money savings in a yearly basis (simple payback) or more extended period (e.g., 20 years) (cash flow model). Several studies have considered the economic output as an indicator of attractiveness, such as the study of Ayompe and Duffy (2014) [11], where a simple payback period and levelized cost of electricity generation were calculated for a range of capital costs and discount rates. This study takes a step further, calculating the amount of money made each year after the first year of investment. According to Ref. [12], there are numerous “ways to define cash flow and free cash flow resulting in problems of consistency and comparability. Several of the most common definitions are summarized in Table 5. Per all of the definitions in Table 5, cash flow is the measure of the ability to produce money from an investment. However, many factors can be subtracted from or added to the investment, which is why there are multiple definitions of the concept. Free cash flow (FCF) represents the available cash after meeting all current commitments. Similar to cash flow, in general, FCF lacks a unique definition. Some analysts argue that FCF should represent the availability of cash after subtracting the operations expenses [11]. Based on International Accounting Standard (IAS 7) (1992), “dividends and mandatory debt payments should not be subtracted to arrive at FCF” [11p.39].

A cash flow model differs depending on the type of analysis being undertaken (e.g., after-tax cash flows, before-tax cash flows, incremental cash flows, etc.). Since TSU is a public institution governed by the state of Texas, including a tax rate is not necessary—therefore tax rate can be set to zero. Next, a cash flow model can be thought in terms of three different activities performed by a company [13]: (1) operating, (2) investing, and (3) financing. Cash flows from operating activities include all revenues captured, minus operating, and maintenance expenses. Cash flows from investments are given by capital expenditure minus expenses, and financing cash flows include repayment of debt. The specific type of cash flow studied in this research is a discounted-investing cash flow model (DCF). Actual cash flows observed in the market are called current dollar cash flows, representing the actual number of dollars required in the year the cost is incurred [12]. Constant dollar cash flows are denoted Fn, where n refers to a base year. Cash flow in current dollars in year m is denoted Fm. Given this notation, and letting e stand for constant inflation, Fn is equal to:

Fn =

Fm (1 + e) m − n

(1)

DCF analysis discounts the future cash flows to the expenses to assess the attractiveness of an investment. The underlying assumption in DCF is that the value of DCF should be positive and higher than the initial investment discounted to the expenses (3):

Table 5 Cash flow definition in different sources. Adapted from Ref. [11]. Source

Definition

Station Casino Accounting for Dummies Barron’s Accounting Handbook

EBITDA plus operating leases Net income plus depreciation, plus or minus changes in short-term operating assets and liabilities Net income plus non-cash charges (such as depreciation) plus or minus changes in accounts receivable, inventory, repaid expenses, accounts payable, and accrued liabilities Net income plus depreciation, depletion, and amortization

Financial Accounting: An Introduction to Concepts, Methods, and Uses Handbook of Common Stocks Standard and poor’s Stock Report Forbes Magazine Harry Domash’s Winning Investing Investorama Money Magazine

Net income plus non-cash depreciation charges less preferred dividends Net income (before extraordinary items and discontinued operations and after preferred dividends) plus depreciation, depletion, and amortization Net income after taxes but before interest depreciation and rental expense Net income after taxes minus preferred dividends and general partner distributions plus depreciation, depletion, and amortization Net income after taxes plus non-cash charges Net income before depreciation, amortization and non-cash charges

5

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M. Mohammadalizadehkorde and R. Weaver

DCF =

CF1 CF2 CFn + +⋯ (1 + r)1 (1 + r)2 (1 + r) n n

NPV(i, N) =

CF

∑ (1 + r)t

Recall that an energy assessment of this type aims to document financial (un)attractiveness and potential energy savings. For the remainder of the paper, the calculation of emissions driven by electricity consumption is based on the Scope 2 method. The Scope 2 represents a “policy-neutral, collaborative solution guided by GHG Protocol principles” [15]. There are two methods included in Scope 2: (1) Locationbased method which reflects the average emission intensity of grids (Emission & Generation Resources Integrated Database (EGRID)), calculated by the emission factor provided by the distributor of electricity which in Texas is Electric Reliability Council of Texas (ERCOT); and (2) Market-based method which calculates the emission from electricity distributed from a third party (company). The emission factors in the second method are provided by a contract, which includes attributes about the energy generation. The new GHG Protocol states that companies shall report both location-based and the market-based method for Scope 2 GHG emissions. The calculation of market-based GHG emission is dependent on the possibility of obtaining a market base emission factor. Since it was not possible to gather this information for Texas State University (TSU), the first method (location-based) is used to calculate the emissions for the study sample. Emission factors are necessary to create and control inventories of GHG emissions and eventually for air quality management. According to the U.S. Environmental Protection Agency (EPA), an emissions factor: is a representative value that attempts to relate the quantity of a pollutant released to the atmosphere with an activity associated with the release of that pollutant. These factors are usually expressed as the weight of pollutant divided by a unit weight, volume, distance, or duration of the activity emitting the pollutant (e.g., kilograms of particulate emitted per megagram of coal burned). Such factors facilitate estimation of emissions from various sources of air pollution. In most cases, these factors are simply averages of all available data of acceptable quality, and are generally assumed to be representative of long-term averages for all facilities in the source category (i.e., a population average) (from www.EPA.gov retrievable in https://goo.gl/9kI9BS). On that backdrop, emissions (E) are equal to:

(2)

− investment (3)

t=0

Time value is another crucial factor which assumes that the value of money possessed today is higher than the value of money made in the next year. This is because the money earned today can be invested as soon as possible to make interest:

i FV = PV ⎛1 + ⎛ ⎞ ⎞ ⎝ n ⎠⎠ ⎝ ⎜

(n ∗ t)

⎟

(4)

The discount rate acts as a measure of time value and central to calculate the present value. Also, the discount rates are often used to account for the risk inherent in an investment [12]. There are debates about the appropriate discount rate for discounting the future costs of mitigating climate change [14]. A range of discount rates used in the literature varies from 5% to 10% [14]. When it comes to assessing the future value of investments, it is common to use the Weighted Average Cost of Capital (WACC) as the discount rate. In the case of Texas State University, the discount rate has been fixed for 5% in all projects, which according to the Environmental Defense Fund, is common in higher education systems. Conferring to Short et al. [12], “real discount rates and dollars cash flows exclude inflation” and nominal discount rates include inflationary effects, and they can be calculated by the following formula:

(1 + dn) = (1 + dr )(1+e) dn = [(1 + dr )(1+e)] − 1 dr = [(1 + dn)/(1+e)] − 1

(5)

The Internal Rate of Return (IRR) is the rate at which the NPV equals zero (no loss and no profit). IRR should always exceed the discount rate: N

0 = NPV =

∑ [Fn ÷ (1+d)n]

(6)

n= 0

The emissions factors for location-based calculations for TSU are provided by the electricity emission factors on EPA web portal (https:// goo.gl/gP8Idw), where Table 5 provides the needed factor for CO2, CH4, and N2O. The ERCT (ERCOT ALL) emissions are shown in Table 6. Finally, then, Scope 2 Emissions are given by:

• Costs during the operation • Variable O&M costs • Fixed costs

Scope 2 Emissions = Electricity Consumption (MWh)*Emission Factor (9)

Energy costs are typically variable costs, and labor costs are frequently fixed O&M costs. Both tend to increase since the system gets older, and more maintenance is required [12]. The Equivalent Annual Annuity (EAA) is calculated based on this formula:

EAA =

(8)

E= A*EF*(1 − ER/100)

According to Ref. [12] “there is no absolute standard as to which costs are included in operation and maintenance (O&M) costs.” However, O&M costs can be broken into the following categories:

WACC(NPV) 1 − (1 + WACC)−T

Although the Scope 2 method to calculate GHG emission provides a reliable way of emission calculation, it is not free of flaws. According to the EPA, “the simplest form of an emission factor is a ratio of the mass of pollutants emitted per unit of activity generating the emissions (e.g., pounds of particulate matter (PM) emitted per ton of coal burned).” Some researchers object to the calculation of emissions associated with production and refining of the oil altogether known as production emission [16]. Total emission is another indicative parameter given by the emission from extraction to end use [16]. This study, for example, is not taking into account the possible emission from producing units (solar panel, motors, light bulbs, etc.) and transportation of them, which, if incorporated in the analysis, might reduce the amount of

(7)

Greenhouse gas calculation Whereas the preceding section defined financial concepts and parameters that feature in the case study, this section defines emissions. Table 6 Electricity emission factors in Texas. Total Output Emission Factors

Non-Baseload Emission Factors

eGRID Subregion

CO2 (lb CO2/MWh)

CH4 (lb CH4 MWh)

N2O (lb N2O /MWh)

CO2 (lb C2/MWh)

CH4 (lb CH4 MWh)

N2O (lb N2O /MWh)

ERCT (ERCOT ALL)

1,143.04

0.01

0.01

1,280.59

0.02

0.01

6

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recommended for all the buildings. In the total 1651551 m2 of the area considered in this study, more than 89094 m2 are dedicated to educational purposes. The majority of lighting systems in these buildings are linear fluorescent systems using T8 bulbs and 32 Watts of electricity consumption. Each fixture often contains two bulbs and in some cases, with three lamps, such as the area dedicated to food services at LBJ Center. LEDs can provide the same amount of Lumens needed with lower electricity consumption, and their expected life on average equals 50,000 h. Illuminance is referred to as a unit of measurement for the amount of light measured on a plane surface. Illuminance is measured in foot candles (ftcd, fc, fcd) or lux (metric system) in the international system of units (SI). A foot-candle is equal to one lumen of light per square foot, and one lux is one lumen per square meter. The outdoor light level is approximately 1000. There has been a rapid change in recommended illuminance levels since the 1930s [17]. The needed amount of lumens varies based on the main activity of the space used for lighting, the proximity to the window during the day, and the physical properties of the building and office. However, illumination can be calculated as:

Table 7 Factors and assumptions for the lighting system (Alkek Library). Building Details Type of Building Recommended Number of Fixtures

Normal Office Work, PC Work, Study Library, 4848

Current Lighting Type of Existing Light Technology Power Consumption (Watts) Total Number of Fixtures Total Number of T8

T8 32 4848 9696

Proposed Lighting Type of Proposed Light Technology Equivalent Watts of LED Expected Life of LED (Hours) Actual Useful Life (Years)

LED 18 50,000 10

Savings and Cost Economics Number of LED Installed Number of Lamp Delamped Cost of LED Installation Charges ($/ LED) Ballasts Number of LED per Ballast Total Number of Ballasts Cost of Ballast ($/Ballast)

4247 5,449 $10.00 $0.30 Yes 1 4247 $10.00

Annual Savings Energy Savings per LED ($) Demand Savings per LED ($)

$5.88 $0.00

I= LIC u LLf /AI

The illumination assumptions for different types of spaces are taken from the Environmental Defense Fund. The next important step consists of calculating the fixture number with maintenance factor set to 0.63, and utilization factor set to 0.69 by EDF, which is given by:

F= L*S f /MF*UF*L f Project Cash Flow Years 0 Investment Capital Outlay

Operating Expenses/Savings Operating Income Taxes Net Income Cash Flows: Free Cash Flow Cumulative Cash Flow NPV IRR Payback Period Profitability Ratio EAA

(86214) (86214)

(11)

1

2

3

4

5

Energy savings per LED is calculated by the difference between the power consumption of current light bulb and proposed light bulb (LED), multiplied by daily hours of operation, number of days in a year, and the price paid for each kWh and finally divided by 1000:

99,189 8621

100,181 8621

101,183 8621

102,195 8621

103,216 8621

Es = P1kWh − P 2kWh ∗ Hr ∗ Od ∗ PrkWh/1000

90,568

91,559

92,561

93,573

94,595

Assumptions and factors

0 90,568

0 91,559

0 92,561

0 93,573

0 94,595

99,189 12,975

100,181 113,156

101,183 214,338

102,195 316,533

103,216 419,749

Different studies have considered an upgraded lighting system to assess the electricity savings in residential and commercial sections [18–20]. “Electricity savings over time is significant enough to not only pay for the new lighting but also produce a return on the investment” [18]. Typically, each square foot (0.09 m2) needs 50 lm for desks and task lighting. The Alkek Library building at TSU requires almost 7,283,2500 lm. When accounting for the building’s area, this means 550 Lumens on average for each square meter (the unit used in the formula 13). An 18 Watts LED bulb can provide sufficient light for four square meters. These calculations are based on the assumption that LEDs can be installed on linear fluorescent fixtures. However, it is possible to calculate the cost of new fixtures for LED bulbs and ballast as well. If the variable fixture is included in the analysis, the payback period will extend over three years. The ballast price has been introduced to the formula with an average price of $10.00, which is the price paid by the utilities for ballast in summer 2016. the cost of LEDs is also set to $10.00 which is the price paid by utilities in summer 2016. Also, the $0.30 is the price paid for installation charges on behalf of the management for the implementation of LEDs. The lighting system at TSU is in operation 364 days a year, with 14 h of average operation daily. The assumption is that there is no need to remodel the distance between each fixture. Table 7 shows all the assumptions and factors needed to run the calculation for Alkek Library.

86,214

Savings Energy Savings Depreciation

(10)

$711,905 116% 0.87 9.26 $92,194.92

avoided emission. Sustainable energy projects To perform a financial analysis of sustainable energy projects, the remainder of this paper considers five specific projects into selected energy-saving technologies. As stated above, the objective is to generate empirical evidence related to the (un)attractiveness of these investments and the potential for emissions reductions associated with each investment.

(12)

Lighting system replacement Solar panel installation Linear fluorescent lighting is the primary detected lighting system in many of the surveyed buildings at Texas State University. The T8 bulb with 32 Watts of electricity consumption is the most used type of lamp in the observed areas. Therefore, replacement of T8 bulbs and highpressure sodium with Light Emitting Diodes (LED) is strongly

Much of the recent literature on the “Anthropocene” epoch of history implicates a need to curb large-scale fossil fuel consumption all over the world [21]. “Among renewable energy sources, solar energy is the most promising due to its tremendous potential” [22]. Indeed, only 7

Sustainable Energy Technologies and Assessments 37 (2020) 100570

M. Mohammadalizadehkorde and R. Weaver

solar panels, it is possible to mention that PV is a mature technology with a dropping price per kWh, and it is easily connectable to battery chargers and lighting systems running on DC electricity [25]. It also needs little maintenance with the possibility of being certified for 25 years [25]. Disadvantages are more consistent in tropical climate:

one hour of solar radiation is comparable to the annual global energy consumption [23]. Solar power has received remarkable attention and growth in recent years. Tax incentives have a remarkable role in this process, and projections show that the solar PV industry continues to experience a significant cost reduction [24]. Among the advantages of Table 8 Factors and assumptions for solar panel installation (Alkek Library). Renewable Energy Cost Recommended Minimum Cost of Energy(¢/kWh) Cost of Energy (¢/kWh) Cost-Based Tariff Escalation Rate (%)

14.75 16 2.0

Production Capacity Generation Capacity (kWDC) PV Watts Net Capacity Factor (State Average) Capacity Factor (%) Production (kWh) Annual Degradation Factor (%) Project Useful Life (Years)

703 Texas 16.2 995,082 2.0 20

Installation and O&M Expenses Total Installed Cost ($/WattDC) Fixed O&M Expense ($/kWDCYr) Variable O&M Expense (¢/kWh) Inflation Rate (%)

$2.50 $20.00 0.00 2.0

Financing Debt (%) Cost of Debt (%) Term (Years) Tax Rate (%) Equity (%) Cost of Equity (%) Project Discount Rate – WACC (%) Debt Equity

50 3 15 0 50 10 6.50 $878,000 $878,000

Rebate and Tax Incentives Rebate Type Type of Incentive

Cost-Based Investment Tax Credit 30 $527,250

ITC or Cash Grant Amount (%) ITC or Cash Grant Amount Project Valuation Years Capital Outlay

1

2

3

4

5

6

7

8

9

10

Production: Energy Production (kWh)

995,082

955,279

917,068

880,385

845,169

811,363

778,908

747,752

717,842

689,128

Project Revenue: Revenue from Tariff ($) Rebate/Incentive ($) Total Revenue

159,213 0 159,213

155,901 0 155,901

152,659 0 152,659

149,483 0 149,483

146,374 0 146,374

143,330 0 143,330

140,348 0 140,348

137,429 0 137,429

134,571 0 134,571

131,772 0 131,772

Project Expense: Fixed O&M Expense Total Expense EBITDA (Operating Income) Depreciation Taxable Income Taxes Net Income

14,060 14,060 145,153 61,513 83,641 0 83,641

14,341 14,341 141,560 61,513 80,048 0 80,048

14,628 14,628 138,031 61,513 76,518 0 76,518

14,921 14,921 134,563 61,513 73,050 0 73,050

15,219 15,219 131,155 61,513 69,643 0 69,643

15,523 15,523 127,806 61,513 66,294 0 66,294

15,834 15,834 124,514 61,513 63,002 0 63,002

16,151 16,151 121,279 61,513 59,766 0 59,766

16,474 16,474 118,097 61,513 56,585 0 56,585

16,803 16,803 114,969 61,513 53,456 0 53,456

Tax Credit Cash Grant/Investment Tax Credit Performance Tax Credit Total Tax Credit

527,250 0 527,250

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

0 0 0

672,403

141,560 943,537

138,031 805,506

134,563 670,943

131,155 539,788

127,806 411,982

124,514 287,467

121,279 166,189

118,097 48,092

114,969 66,877

Cash Flows: Free Cash Flow Cumulative Cash Flow NPV IRR Payback Period Profitability Ratio Equivalent Annual Annuity

0 1,757,500

(1757500) (1757500) $66,635 7% 9.42 1.04 $6,048

8

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M. Mohammadalizadehkorde and R. Weaver

provided in Ref. [26]:

performance may decline more rapidly when exposed to humidity and high temperature. “The DC/AC inverter is also the weak link of photovoltaic installation, even though it is certified for up to 10 years” [25]. Also, the Solar Investment Tax Credit (ITC) is one of the federal policies to support the deployment of solar energy. Solar panel installation at Texas State University has been studied only for a few buildings with a significant flat and even roof. Many of the roofs on Texas State University’s campus have no shadow area and can absorb sunlight for the entire day, and panels can point toward the south without any obstacles (best direction). On the other hand, in some cases, the roof would not support the additional weight of the panels, such as the case of the Central Plant, where it is not possible to install additional weight. Usable roofs should be able to support the addition of 25–27 kg per square meter to avoid substantial construction costs. The average cost of electricity purchased from the local utility is $0.08 per kWh while producing electricity through solar panels costs more. The criteria for converting DC (produced by panels) to AC have been applied to the calculations. It is necessary to bear in mind that the installation can be a grid-connected system to benefit from Renewable Energy Credit (REC) in the case of excess in electricity production. However, Texas State University does not benefit from any rebate (common in other projects), and the realization of on-site energy production is currently implausible. The installation of photovoltaic panels depends on many factors. The calculation is based on the Cost of Renewable Energy Spreadsheet Tool (CREST) version 1.4 (See Table 8). This project has been measured for five buildings. Realizing an onsite electricity production system is the most expensive among all the energy efficiency measures with a $7,434,000 initial investment, and the average payback period is 8.5 years. These factors might affect negatively the enthusiasm towards the realization of renewable energy plants. Tariff escalation rate is the projected increase or decrease in the cost of renewable energy in the future throughout the project: It can be between 2 and 5 percent. The generation capacity has been calculated using the PV Watts calculator, an on-line toolkit provided by National Renewable Energy Laboratory (NREL) accessible at http://www. pvwatts.nrel.gov. It is necessary to bear in mind that the roof tilt and sun azimuth cannot be automatically determined from the aerial imagery, and consequently, the estimated system capacity may not reflect what is possible. The solar photovoltaic capacity factor is taken from https://www.eia.gov/electricity/data/eia860. The capacity factor is the percentage of actual energy produced after removing all the losses. The percentage of degradation of production is due to the natural aging of mechanical components, and it can be between 0 and 2 percent. The system capacity in kW of direct current per square meter (kW (DC)/m2) has been used as input for other calculations. The recommended cost of energy is calculated based on the formula

COE =

(FCR × ICC ) + AOE AEPnet

(13)

The following formula calculates annual operating expenses (AOE):

AOE = annual operating expenses = LLC +

(O&M + LRC ) AEPnet

(14)

Motors Most motors installed around the Texas State University campus exceed 90 percent of the National Electrical Manufacturers Association (NEMA) nominal efficiency at full-load capacity, which means a reasonably good performance. As a matter of fact, the amount of kW saved by replacing motors is not a significant number compared to the other projects, which confirms the good performance of the motors. However, most of the motors are in the second half of their expected life and are frequently replaced rather than fixed due to the cost and the evidence that rewinding may reduce the motor’s efficiency [27]. “A motor’s efficiency tends to decrease dramatically below about 50% load” [28]. If the energy efficiency motor is still in a serviceable condition, there is no need to change the motors. The Department of Energy (DOE) indicates that even the best rewinding causes a loss of efficiency of the motor, and motors with less than 70 HP should not be rewound but replaced. The high volume of the motor duty cycle is an essential factor in the process of retrofitting. The Texas State University HVAC system is running 24/7 with lower demand during the night. That means a faster depreciation and a lower rate of lifespan for motors that run fans, pumps, and chillers. When existing motors meet the end of usability, they should be replaced with high-efficiency models. The nameplate of the motor includes factors needed to apply the energy efficiency calculation. In cases where it was not possible to read the factors, the vendor or producer was contacted to obtain information. The NEMA definition of energy efficiency is given by the ratio of its useful power output to its total power input, shown in percentage [28]:

η=

0.7457 ∗ hp ∗ Load ρI

(15)

Power factor is calculated by:

PF = (Volt∗Current ∗ 1.732)/((HP) ∗ 0.7457 ∗ 1000)

Fig. 2. Comparison of power consumption in fans. 9

(16)

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M. Mohammadalizadehkorde and R. Weaver

Variable frequency drive installation

Results

One of the best ways to meet energy efficiency measures is to apply variable frequency drives on the motors with constant speed induction. The output flow in the case of fans and pumps changes following seasonal change and hours of operation of the buildings. Several buildings at Texas State University have an HVAC system with constant air volume (CAV). This means that the air handlers provide the same amount of air, regardless of cooling and heating load in the space. The installation of VFD is proposed for centrifugal fans and pumps (Central Plant has already applied VFDs for pumps) with a higher level of electricity consumption, but this technology can be used all over the campus. VFD can be applied in two levels: first, at thermal plants where the needed flow rate is produced and secondly in HVAC systems inside each building in order to optimize the output of components. Moreover, the installation of VFDs for the HVAC system has been done in 10 buildings before this study, which means a lower load on electricity and chilled water supply at Central Plant. Fig. 2 compares the power consumption between fans with VFDs and fans without it.

Several sustainable energy projects were evaluated for Texas State University (TSU) to determine the potential reduction in energy consumption (kWh), CO2 emissions, and associated cost savings at the institution. A summary table of recommended projects is shown in Table 9. The total electricity cost of 13 sampled buildings on TSU’s main campus equals $6,414,436.56. These identified projects, once implemented, can save 17% on TSU’s annual energy costs. The replacement of the current lighting system has the most significant carbon dioxide reduction and the most attractive NPV. The shortest payback period belongs to the pump replacement, and the replacement of the lighting system represents the most significant annual kWh savings. Tables 10–14 provide a summary of the financial and environmental output of implementations in different buildings. Pilot studies have shown that lighting system replacement with proper electronic ballasts has been improving energy consumption with short payback periods [29]. The same result is achieved by this study and with the best LED technology in 2016 while the advance in LED lighting is so vertiginous that the courses on LED implementation must change every year [30]. Although LED light bulbs show a significant energy efficiency improvement by consuming 85% less electricity, they are categorized as hazardous due to excessive levels of lead (Pb) leachability, the content of copper, and zinc [31]. This fact pushes researchers towards the adaption of new technologies with less rare metals in the next generation of LEDs [30]. The global lighting market is expected to grow by 3–5% per year until 2020, with LED sales accounting for more than 80% of the market [30]. Also, the lighting system replacement can be applied not only to the sample size in this study but to all buildings around campus. Although we have focused on the energy efficiency aspect of indoor lighting in an incomplete perspective, it is known that the evolution of different lighting techniques has been improving photometrical performance and personal well-being of users as well [30]. Therefore, there is a need to incorporate results from a human impact perspective, including the non-visual effects of light. In the case of solar panel installation, the assumption is that no battery energy storage system (BESS) is included in the system since the production capacity is always lower than the usage. For instance, Alkek library potential reaches 995,082 kWh of electricity while the average annual consumption is about 3,154,484 kWh (Table 3). In both residential and commercial settings, solar panels require a considerable investment, which makes it a non-attractive investment despite its positive environmental impact [32]. Also, bigger is the size of implementation, bigger is the payback period, which is confirmed in other studies as well [32]. The net present value and discounted payback period in a grid-connected system will lead to a better investment option [33] while this study excludes the possibility of a grid-connected system. While in the case of lighting system replacement, all the NPVs were more significant than the initial investment (except Alkek library), a low solar panel NPV was confirmed in all 5 cases, compared to the needed initial investment. In other studies, such as [33] it is observed

Pump replacement In many cases, at Texas State University, pumps currently have a negative Life Cycle Cost (LCC) due to the depreciation and imminent end of life expectancy. According to the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), even though pumps have been under a scheduled maintenance plan, they are at the end of their lifespan of 15–20 years. Using more efficient pumps during the replacement process will be an important step in reducing energy consumption. The combination of new energy-efficient pumps with VFD will improve energy efficiency in two ways: (1) It reduces chilled water pumping energy in each building and (2) It reduces chilled water pumping at the Central Plant. Furthermore, it improves building Delta T, which the difference in temperature gives Delta T before and after a cooling coil in the HVAC system, keeping it above 15 F° of difference and improving efficiency at the Central Plant. The main proposed measure consists of replacing of the oversized standard pump with energy efficiency pumps. The nameplate provides factors to apply calculations. In the case of nonexistence, the vendor or producer was contacted to obtain the needed information. The calculation of efficiency is similar to the calculation of efficiency in motors and VFDs, and other parameters for flow rate are retrievable through charts provided by vendors. Total head (given by the maximum height (pressure) a liquid (water) should be delivered) in feet is often provided by the plot of total head vs. flow. However, it is possible to calculate the total head by: (17)

HT = Hd − −h s Pump hydraulic power is calculated as:

Ph (hp) = Ph (kW )/0.746

(18)

Table 9 Summary of all projects. Project

NPV of cost savings

Up Front Investment

Annual Cost Savings ($)

Annual kWh savings

CO2 reduction (metric tons/yr)

Payback average (yrs)

Replacement of Lighting system with LED Replacement of Motors VFD Pump Replacement Solar Panel Installation

$5,201,804

$1,916,199

$739,775

9,247,195

5,387.00

1.19

$71,320 $816,867 $2,529,808 $1,495,143

$46,616 $161,750 $115,300 $7,434,000

$15,152.56 $138,519 $337,655

111.00 831.00 2,459.00 2,926.81

5.56 1.95 0.99 8.5

Totals

$13,217,848

$12,173,865

$1,231,102

189,407 1,734,141 4,220,693 5,027,783 (kWh production not included in total number) 15,391,436

12,561.81

18.19

10

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M. Mohammadalizadehkorde and R. Weaver

Table 10 Summary of lighting system replacement project. Name of the Building

Annual kWh saved

NPV

Annual Cost Savings

CO2 reduction (metric tons)

Payback (year)

Investment

Jowers Center Central Plant (office) Health Center Rec Center Alkek library Central Plant (Industrial) Evans Liberal Art JCK LBJ McCoy Hall Roy Mitte San Jacinto Supple Science Totals Average

550,800 11,691 380,880 1,326,000 1,227,587 170,382 414,000 991,440 2,154,065 453,600 480,000 755,550 331,200 9,247,195

$367,867 $5,172 $205,080 $724,603 $711,905 $56,725 $228,163 $554,675 $1,262,939 $242,409 $265,823 $397,733 $178,331 $5,201,425

$44,064 $935 $30,470 $106,080 $98,207 $13,631 $33,120 $79,315 $172,325 $36,288 $38,400 $60,444 $26,496 $739,776

321 7 222 772 715 99 241 578 1255 264 280 440 193 5387.00

0.70 2.19 1.38 1.28 0.87 1.08 1.22 1.12 0.79 1.43 1.19 0.86 1.38 15.49 1.19

$35,000 $2,050 $42,550 $137,500 $1,227,587 $14,820 $41,000 $89,910 $137,532 $52,500 $46,250 $52,500 $37,000 $1,916,199

CO2 reduction (metric tons)

Payback (year)

Investment

174.0 964.0 544.0 654.8 590.0 2926.81

8.72 9.05 9.42 8.07 7.17 42.43 8.5

$423,800 $2,340,000 $1,650,000 $1,588,200 $1,432,000 $7,434,000 $1,486,800

Table 11 Summary of the solar panel installation project. Name of the Building

Annual kWh production

NPV

Annual Cost Savings

Central Plant Jowers Center Alkek Library LBJ Center Mathews Garage Totals Average

299,940 1,656,111 934,217 1,124,032 1,013,483 5,027,783

$131,066 $369,661 $62,560 $370,072 $561,784 $1,495,143

Not Not Not Not Not Not

applicable applicable applicable applicable applicable applicable

Table 12 Summary of the pump replacement project. Name of the Building

Annual kWh saved

NPV

Annual Cost Savings

CO2 reduction (metric tons)

Payback (year)

Investment

Central Plant Alkek Library LBJ Center Totals Average

3,053,871 1,020,055 146,767 4,220,693

$1,808,995 $656,192 $64,621 $2,529,808

$244,309.68 $81,604 $11,741 $337,655

1779.00 594.00 86.00 2459.00

0.32 0.08 2.58 2.98 0.99

$77,500 $7,000 $30,800 $115,300

Table 13 Summary of the motor replacement project. Name of the Building

Annual kWh saved

NPV

Annual Cost Savings

CO2 reduction (metric tons)

Payback (year)

Investment

Central Plant Alkek Library LBJ Center Totals Average

160,667 8126 20,614 189,407

$67,250 −$1117* $5187 $71,320

$12,853 $650 $1649 $15,153

94.00 5.00 12.00 111.00

2.49 9.35 4.84 16.68 5.56

$32,000 $6400 $8216 $46,616

Note: *The only negative value for NPV among all the projects. Table 14 Summary of VFD installation. Name of the Building

Annual kWh saved

NPV

Annual Cost Savings

CO2 reduction (metric tons)

Payback (year)

Investment

Central Plant Central Plant Condenser Water Pump VFD Alkek Library LBJ East Plant East Plant Condenser Water Pump VFD Totals Average

413,530 140,000 788,094 224,420 28,396 138,293 1,732,733

$212,954 $74,912 $315,969 $124,908 $3212 $84,912 $816,867

$33,080 $11,000 $63,042 $17,952 $2271 $11,174 $138,519

241 – 459 131

1.26 1.34 0.99 1.16 6.47 0.45 11.67 1.95

$42,500 $15,000 $63,000 $21,000 $15,250 $5000 $161,750

11

– 831

Sustainable Energy Technologies and Assessments 37 (2020) 100570

M. Mohammadalizadehkorde and R. Weaver

It is more appropriate to establish the base year in 2013 with a more significant amount of area. Also, there is a need to calculate the coefficient of growth in the number of students and another coefficient for added space to the total area to better understand future energy consumption. In terms of adhering to declarations or environmental commitments, Senate Bill 898 is exclusively focused on electricity consumption. However, achieving sustainability goals on energy use clearly demand a broader mandate, including investments into renewable, affordable, and modern sources of energy (see, e.g., [30]). The Senate Bill applies to political subdivisions, institutions of higher education, and state agency facility, which also in the 41 non-attainment or near nonattainment counties in Texas (SB 898). Texas State University is in Hays County, one of the 41 non-attainment or near non-attainment counties in Texas (Clean Air Act Amendments, 1970–1977). Considering the non-satisfactory air quality in Hays County, it is strongly recommended to take the energy efficiency measurements in action, bringing the university beyond the binding bill and presenting a good example of social responsibility. Also, there is a need to study gas consumption to understand future energy consumption better since the average rate of consumption has increased each year since 2013 (Fig. 3). While Texas is rich in petroleum, studies have shown that the state has the potential to produce 20% of total U.S solar power [30]. Currently, the city of San Marcos does offer a rebate for the implementation of renewable energy (installation of solar panels) for single-family homes. This support comes from a federal policy consisting of 30 percent tax credit for residential and commercial solar projects where there is no direct reference to universities. As mentioned in previous chapters, universities can be considered as commercial units since their energy consumption fits the commercial and industrial sections in many aspects. Above all, this study suggests that there are many cost-effective projects that TSU can take immediately to reduce energy consumption and save money. The replacement of its lighting system is one of the best choices in terms of (1) quick payback and (2) a relatively small investment for individual units (except Alkek Library). Even when there is a need to invest more money, the payback period can show a short time to recoup the investment. This case has been proven in several projects like the case of Alkek Library, where replacing T8 bulbs demands more than $1 million of the initial investment. This amount of money can be returned to the university budget in 0.87 years. However, the replacement of the lighting system has been applied only on the first floor due to the need for reconstructions. As mentioned before, resistance to change can lead to institutional inertia. However, higher education organizations such as Texas State University have a responsibility to take leadership roles in sustainability practice. Specifically, due to their prominent role in creating and

that the cost of electricity generated by the PV system is less than the cost charged by distribution companies. However, this is highly dependent on the geographical factor: In India due to the high rate of electricity cost a PV system is a feasible choice from the financial point of view but in San Marcos, Texas the rate of electricity is low, and as shown in the study the proposed cost of installing one kWh is almost double of the price paid to the distribution company in 2016. Another significant and positive NPV is given by the possibility of VFD installation on motors, pumps, and fans. the installation cost of VFDs is often high and ranges from $3000 for a 5 Hp motor to $45000 for a custom engine with 300Hp [34]. Payback periods in other studies are reported to be between a few months to less than three years for 25–250 Hp [34]. The same condition is verified at TSU, where all the payback periods are less than 1.5 years except the case of East Plant with more than six years of payback period (Table 14). Each VFD is also capable of driving more than one motor [34]. Therefore, their implementation in Central Plant, where multiple motors and pumps are installed close to each other, will lead to some cost consolidation [35]. Reducing the fan speed with VFDs results in a reduction of the airflow and significant energy consumption [36]. While this study does not include the airflow measurements, it confirms that the implementation of VFDs will lead to better energy efficiency. Also, the implementation of VFDs can reduce the risk of mechanical failure [35].

Discussion There are promising paths towards decreasing energy consumption at Texas State University; however, to take these paths will require going against business as usual. For instance, while several buildings have recently been retrofitted or upgraded with energy-efficient equipment—and new buildings are being constructed according to LEED criteria—compared to 2015, total energy consumption failed to experience a significant reduction. More precisely, due to a reduction in reportable gross area from 2015 to 2016, a relatively small reduction can be expected on total electricity consumption. Nevertheless, this expectation was not borne out in the preceding analysis. Moreover, the projections show an increase of electricity utilization index (EUI) due to the increase of enrollment and a growing rate of square meter in the newly constructed buildings. All these facts point to a likely increase in energy consumption on electricity, gas, and water. It would be a challenging assignment to keep electricity consumption at a flat rate (if not increased) given the 2015 and 2016 consumption when the electricity usage did not decrease despite the area dropped by 3716 square meters. On the other hand, several buildings in the base year (2012) were not included for usage reading. This fact led to the creation of a baseline with assumptions which eventually decreased the accuracy of calculations for the total amount of kWh saved. 1,00,000 90,000 TOTAL BTU/GSF

80,000 70,000 60,000

57,157

52,784

54,017

56,021

FY14 FISCAL YEAR

FY15

FY16

48,433

50,000 40,000 30,000 20,000 10,000 FY12

FY13

Fig. 3. Natural gas consumption comparison at Texas State University. 12

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disseminating sustainability knowledge, it is only natural for higher learning institutions to lead by example and play an equally prominent role in sustainability practice.

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Conclusion During recent years, universities across the U.S. and globally have made public declarations regarding their commitments to sustainability. One large public university, Texas State University, has been committed to improving the energy consumption across the campus. This study used the Discounted Cash Flow Model and the related positive and significant Net Present Value to assess energy efficiency at Texas State University's main campus. The two goals of saving money and improving the environmental condition (avoided CO2) form a “proper coupling” [37]. Like many large public institutions of higher education, Texas State University is facing rapid growth in its student population, which creates an upward demand on area and energy consumption. Undertaking feasible energy efficiency measures is essential for growing the university in an energy-efficient way. However, these measures can be expensive and not easy to implement in many cases. This study used a sample size of 13 buildings with the highest energy expenditure on campus. The only project applied to all the buildings was the replacement of the lighting system. The average payback period is relatively short for many individual projects, especially in the case of the lighting systems and pump replacement. The ratio of payback compared to the invested money can be considered as another proper coupling to overcome the difficulties in financial terms because cumulative cash flow will be increased along the years after the implementation of the proposed project. The positive outcomes of this study indicate that extrapolating the results to all university buildings with 7,719,991 gross area will increase savings, reduce emissions, and constitute a sound financial investment. Based on the limitations of this study, it is recommended that future studies repeat the experience with a larger sample size and in different university campuses with the same characteristics. Assessing energy consumption and efficiency in light of the growing student and surrounding population will continue to be a necessary step to reach the sustainable development of Texas State University, now and in the future. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.seta.2019.100570. References [1] Ralph M, Stubbs W. Integrating environmental sustainability into Universities. J Higher Educ 2014;67(1):71–90. [2] Bocken NM, Short SW, Rana P, Evans S. A literature and practice review to develop sustainable business model archetypes. J Cleaner Prod 2014;65:42–56. [3] Wheeler D, Colbert B, Freeman RE. Focusing on value: reconciling corporate social responsibility, sustainability and a stakeholder approach in a network world. J General Manage 2003;28(3):1–28. [4] Norton RK, Brix A, Brydon TE, Davidian E, Dinse K, Vidyarthi S. Transforming the university campus into a sustainable community. J Plann Higher Educ 2007;35:22–39. [5] Alshuwaikhat HM, Abubakar I. An integrated approach to achieving campus sustainability: assessment of the current campus environmental management practices. J Cleaner Prod 2008;16(16):1777–85. [6] Elliott H, Wright T. Barriers to sustainable universities and ways forward: A

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