CHAPTER 10. SHIPMENTS ANALYSIS 

TABLE OF CONTENTS 

10.1 INTRODUCTION ......................................................................................................... 10-1 

10.2 SHIPMENTS MODEL EQUATIONS .......................................................................... 10-1 

10.2.1 Mathematical Formulation of the Shipments Model ......................................10-1 

10.2.2 Stock Events.................................................................................................... 10-2 

10.2.2.1 Replacing Equipment.................................................................... 10-2 

10.2.2.2 New Equipment ............................................................................ 10-3 

10.3 DATA INPUTS ............................................................................................................. 10-3 

10.3.1 Historical Shipments....................................................................................... 10-3 

10.3.2 Historical Shipped Linear Feet ....................................................................... 10-4 

10.3.3 Commercial Grocery Display Space and Market Saturation.......................... 10-6 

10.3.3.1 Floor Space – New Construction .................................................. 10-6 

10.3.3.2 Market Shipments ......................................................................... 10-7 

10.3.4 Equipment Utility............................................................................................ 10-7 

10.3.5 Equipment Price.............................................................................................. 10-7 

10.3.5.1 Operating Costs............................................................................. 10-8 

10.3.5.2 Discounted Costs .......................................................................... 10-9 

10.4 RESULTS ...................................................................................................................... 10-9 

REFERENCES ........................................................................................................................ 10-11 

LIST OF TABLES 

Table 10.3.1 Estimated Distribution of Linear Feet of CRE Shipments among New vs. 

Replacement Equipment and Large vs. Small Food Sales Outlets in 2005*..... 10-4 

Table 10.3.2 AEO 2007 forecast of New Food Sales Square Footage ................................... 10-5 

Table 10.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis.................... 10-5 

Table 10.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment.......... 10-6 

Table 10.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration 

Equipment for Large and Small Food Sales Outlets, 2012-2042 (Base 

Case) .................................................................................................................. 10-9 

Table 10.4.2 Forecasted Shipments for Commercial Refrigeration Equipment, 

2012-2042, Level 1 (Base Case) .................................................................... 10-10 

LIST OF FIGURES 

Figure 10.1.1 Flow Chart Showing Inputs to the Shipments Model........................................ 10-1 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
10-ii 

EERE-2006-BT-STD-0126 COMMENT 52.2 
CHAPTER 10. SHIPMENTS ANALYSIS 

10.1 INTRODUCTION 

Commercial refrigeration equipment (CRE) shipments estimates are a necessary input to 

the national energy savings (NES), net present value (NPV) calculations, and the manufacturer 

impacts analysis (MIA). This chapter describes the U.S. Department of Energy’s (DOE) 

methodology for projecting annual shipments and presents results. 

The Shipments Model results are driven primarily by historical shipment data for the 

15 categories of commercial refrigeration equipment under consideration. The flow chart 

presented in Figure 10.1.1 outlines the structure of the Shipments Model. 

The model assumes that, in each year, the existing commercial refrigeration equipment 

stock either ages by 1 year or breaks. Broken equipment is replaced. In addition, new 

equipment can be shipped into new commercial floor space, and old equipment can be removed 

through demolitions (not shown in the diagram). 

The Shipments Model is in a Microsoft Excel spreadsheet format that is accessible on the 

Internet at: http://www.eere.energy.gov/buildings/appliance_standards/ 

commercial_products.html. 

Further, chapter 11, section 11.5 of this Technical Support Document (TSD), discusses 

how to access the Shipments Model spreadsheet and other related spreadsheets, and provides 

basic instructions for using them. The rest of this chapter explains the Shipments Model in more 

detail. Section 10.2 presents the mathematical formulation of the model, section 10.3 describes 

the data input to the model, and section 10.4 presents the results for the base case 

energy-conservation standard level scenario and discusses the development of higher standard 

scenarios. The energy conservation standards for commercial refrigeration equipment will set 

the maximum rated energy consumption for all equipment within an equipment class. DOE 

refers to each standard level considered as a “candidate standard level.” 

Shipment forecasts were determined for all of the candidate standard levels for which 

NES and NPV are required. DOE is considering up to five trial standard levels for each of the 15 

equipment classes. 

10-1
 

EERE-2006-BT-STD-0126 COMMENT 52.2 
NEMS Food Services
 

Bldg
 

Construction ForecastForecast ARI Estimate of 

Shipments (2005) 

% Shipments by Product 

Class (2005) 

Initial Replacement

Shipments 

Initial Shipments to New 

Construction

Initial CRE Stock

Estimated Lifetime

of CRE Stock

Shipments to New 

Construction

Replacement 

Shipments

Total

Shipments By

Product Class

CRE Stock 

by Product

Class

Initial Replacement 

Shipments 

Initial Shipments to New 

Construction 

Initial CRE Stock 

Estimated Lifetime 

of CRE Stock 

Shipments to New 

Construction 

Replacement 

Shipments 

Total 

Shipments By 

Product Class 

CRE Stock 

by Product 

Class 

Figure 10.1.1 Flow Chart Showing Inputs to the Shipments Model 

10.2 SHIPMENTS MODEL EQUATIONS 

The Shipments Model is a description of commercial refrigeration equipment stock flows 

as a function of year and age. While there are 15 equipment classes, no coupling is assumed 

between them, so the equations describe each type of equipment independently. 

This section begins with a definition of the different commercial refrigeration equipment 

stock categories. DOE formulates the equations as updates of the distribution of stock in year t 

as a function of age a to year t+1. Then, DOE presents the different purchase decisions and, in 

the following section, provides a description of the data sources. In the equations below, DOE 

first converted the equipment units to linear feet of display space cooled by those units by taking 

the national statistics on sales of equipment and calculating equipment capacity per linear foot of 

retail grocery building display space. DOE uses this calculation of existing stock, and the 

average age of the equipment, as a basis for calculating replacement sales. Then, DOE subtracts 

replacement sales from historical total sales statistics to calculate new sales of commercial 

refrigeration equipment. DOE forecasts new sales as a function of new construction of retail 

food sales space. Sales of new and replacement equipment are recorded by the year sold, and 

each annual vintage is depreciated over the estimated life of the equipment. Sales in each year 

are allocated to the 15 equipment classes in proportion to their relative historical sales. 

10.2.1 Mathematical Formulation of the Shipments Model 

DOE uses two commercial refrigeration equipment stock categories. The category 

U0(t,a) is the stock of existing units. Available information suggests that all units are assumed to 

have had normal repairs that do not affect the lifetime of the equipment. 

In view of industry practice, available information suggests that the lifetime of a unit is 

10 years in large food retailers and about 15 years in small retailers, such as convenience stores. 

Also, available information suggests that the initial existing stock of equipment had an average 

age of 5 years, based on the 10-year lifetime of a unit of equipment, and annual replacements 

going back 10 years. The total stock of age a in a given year t is represented by 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
U(t,a) = U0 (t,a) Eq. 10.1 

and the average age of the stock in year y is defined as 

StockAge(t) = ∑aU( t, a) x a / ∑(U( t,a)) Eq. 10.2 

where: 

U(t,a) = total stock of age a in a given year y, 

U0(t,a) = stock of existing units, 

StockAge(t) = average age of stock in year y, 

a = age of stock, 

t = year. 

The shipments of new stock in a given year are Uship(t). By definition, the age of the 

equipment is zero in the year that it is shipped, so that Uship(t) = U(t,0). 

10.2.2 Stock Events 

In the transition from year t to year t+1, two things could happen to the stock of 

commercial refrigeration equipment: 

•	 existing equipment could break or be removed during a store renovation and be 

replaced 

•	 the stock could simply age by one year. 

In the model, early replacements (i.e., existing equipment that is replaced before it has 

broken) are not considered, and all broken equipment are assumed to be replaced. The following 

sections present the equations used to represent each possible event. 

10.2.2.1 Replacing Equipment 

DOE determines the probability that commercial refrigeration equipment of age a from 

stock U0 will break or will be replaced using a Weibull survival distribution function 

PB0(a)=W(8,10.62) for large food sales (which results in a 10-year average lifetime, a minimum 

lifetime of about 7 years, and a maximum lifetime of about 13 years, consistent with industry 

comments). PB0(a)=W(8,16) for small food service outlets, i.e., convenience stores with and 

without gas stations (which results in an average lifetime of 15 years, with a minimum of about 9 

years and a maximum of about 20 years, again consistent with industry comments). Similarly, 

the probability that equipment of age a from stock U1 will break is given by the same function 

PB1(a). These probabilities do not depend on the model year t. DOE defines the quantities of 

replaced equipment as 

UB(t, a) = PB0(a) x UB0(t,a) Eq. 10.3 

where: 

UB0(t,a) = stock of existing units, 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
 

 

PB0(a) = probability that stock of existing units will break, or will be replaced, 

U0(t,a) = stock of existing units, 

a = age of stock, 

t = year. 

All broken or obsolete units (removed during store renovations) are assumed to be 

replaced. 

10.2.2.2 New Equipment 

New commercial refrigeration equipment will be purchased to replace the units described 

above. Available information suggests that the purchase of new equipment that would go into 

new buildings is driven by the rate of construction of grocery floor space. 

By definition: 

EFS (t+1) = EFS(t) + NFS (t) - DFS(t) Eq. 10.4 

where: 

EFS(t) = the square footage of existing grocery floor space in year t, 

NFS(t) = the square footage of new grocery floor space added in year t 

(described in section 10.3.3), 

DFS(t) = the square footage demolished in year t (described in section 10.3.3.1). 

The linear footage of units going into new buildings is 

UN(t) = UN(t) x A0 x NFS(t)/ NFS(0) Eq. 10.5 

where: 

UN(t) = the number of units going into new buildings in year t, 

A0	 = an overall scale factor that accounts for the number of units covered by the 

standard, which are not used in all commercial building types; the default value 

for A0 is 1.0, but values of 0.5 and 1.5 are used for sensitivity testing. 

DOE has no information on the variation in the market saturation of commercial 

refrigeration equipment by building type or over time. Therefore, in the model, the purchase of 

new equipment is driven by the construction of new floor space and that broken or removed 

equipment is replaced on a one-for-one basis. 

10.3 DATA INPUTS 

10.3.1 Historical Shipments 

Historical shipments are necessary to calibrate a shipments model to the existing market. 

DOE’s primary source of historical data for shipments of refrigeration equipment is a market 

study by Freedonia, Inc.1 Commercial Refrigeration Equipment to 2008. The data provided in 

this report are aggregated at a high level with regard to equipment categorization and provide 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
only an estimate of shipments based on valuation data and estimated prices (valuation data 

similar to the U.S. census bureau data shown in chapter 3, Market and Technology Assessment). 

As discussed in chapter 3, the available Census Bureau data showed substantial variation in 

shipment valuations between the survey years, indicative of large variations in overall shipments 

of commercial refrigeration equipment by year. The Air-Conditioning and Refrigeration 

Institute (ARI) provided DOE with shipments data broken out by specific CRE equipment class 

for 1 year (2005) that allowed DOE to allocate sales of equipment to equipment classes. These 

data are also shown in chapter 3. 

Within each of the equipment categories, the shipments data must be disaggregated into 

detailed equipment and temperature ranges for the shipment analysis. The ARI shipment ranges 

and equipment categories are defined in a way that allowed DOE to disaggregate the data into 

the 15 equipment classes of interest. For the purpose of the NOPR, DOE has used the ARI data 

as a starting estimate for its shipments analysis. 

10.3.2 Historical Shipped Linear Feet 

Historical linear feet of shipped units depicts the annual amount of commercial 

refrigeration equipment capacity shipped and is an alternative way to express shipments data. 

DOE determined the linear feet shipped for any given year by multiplying each unit shipped by 

its associated average length, and then summing all the linear footage values. 

DOE converted the ARI data on shipped units in each equipment class to percent of total 

shipped linear feet of commercial refrigeration equipment for use in the Shipments Model. This 

established the commercial refrigeration equipment market share attributed to each equipment 

class. The market share calculation, and its use in forecasting shipments, is explained in 

section 10.3.3.1. DOE calculated the percent of shipped linear footage by dividing the linear 

footage shipped for each equipment class by the overall linear footage shipped for all 

commercial refrigeration equipment covered in this rulemaking. 

Table 10.3.1 summarizes DOE’s estimated division of historical annual shipments into the 

new, replacement, and large food sales versus small food sales. 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
 

Table 10.3.2 shows the forecasted square footage of new construction used to scale 

annual new CRE shipments. Square footage of additions to stock goes up and down from year to 

year. The year 2009 value was assumed to be the same as in 2006. 

Table 10.3.1 Estimated Distribution of Linear Feet of CRE Shipments among New vs. 

Replacement Equipment and Large vs. Small Food Sales Outlets in 2005* 

 Replacements New Total 

Large Food Retail 

Small Retail 

Total 

69.2% 

12.2% 

81.3% 

15.9% 

2.8% 

18.7% 

85.0% 

15.0% 

100.0% 

* Calculated from ARI data 

10-1
 

EERE-2006-BT-STD-0126 COMMENT 52.2 
 

 

 

 

 

 

 

Table 10.3.2 AEO 2007 forecast of New Food Sales Square Footage 

New Construction 

Year (Million Square Feet) 

2009 30.234 

2010 30.679 

2015 32.968 

2020 34.979 

2025 39.723 

2030 42.073 

Annual Growth Factor, 

2030-2042 1.86% 

DOE used the ARI shipment data to derive shipped linear footage for each of 15 smaller 

equipment classes, based on 10 possible equipment families, two possible equipment operating 

modes (remote condensing or self-contained), and three rated temperature applications (medium, 

low, and ice cream). Table 10.3.3 presents the typical equipment class lengths used for the 

conversion of per-unit shipments to linear footage within each equipment class. The premises 

below include data for some CRE equipment classes, which were not explicitly analyzed in the 

life-cycle cost analysis, but for which shipments were reported by ARI, including small-shipment 

Table 10.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis 

Equipment 

Classa 

Assumed 

Length (ft) Basis 

VOP.RC.M 10 Average of 8 ft and 12 ft, Manufacturer Interviews 

VOP.RC.L 10 Average of 8 ft and 12 ft, Manufacturer Interviews 

VOP.SC.M 4 Baseline Equipment used for Engineering Analysis 

SVO.RC.M 10 Average of 8 ft and 12 ft, Manufacturer Interviews 

SVO.SC.M 4 Baseline Equipment Used for Engineering Analysis 

HZO.RC.M 10 Average of 8 ft and 12 ft, Manufacturer Interviews 

HZO.RC.L 10 Average of 8 ft and 12 ft, Manufacturer Interviews 

HZO.SC.M 4 Baseline Equipment Used for Engineering Analysis 

HZO.SC.L 4 Baseline Equipment Used for Engineering Analysis 

VCT.RC.M 10 Average of 3 door and 5 door (30" per door), MFG Interviews 

VCT.RC.L 10 Average of 3 door and 5 door (30" per door), MFG Interviews 

VCT.SC.I 5 Baseline Equipment Used for Engineering Analysis 

VCS.RC.M 5 Engineering Estimate 

VCS.RC.L 5 Engineering Estimate 

VCS.RC.I 5 Engineering Estimate 

VCS.SC.I 5 Baseline Equipment Used for Engineering Analysis 

HCT.RC.M 5 Engineering Estimate 

HCT.RC.L 5 Engineering Estimate 

HCT.RC.I 5 Engineering Estimate 

HCT.SC.I 3.4 Baseline Equipment Used for Engineering Analysis 

HCS.RC.M 5 Engineering Estimate 

SOC.RC.M 8 Average of 4 ft, 8ft, 12 ft, all common equipment lengths 

SOC.RC.L 8 Average of 4 ft, 8ft, 12 ft all common equipment lengths * Equipment class designations consist of a combination (in sequential order separated by periods) of a equipment family code (VOP=vertical 

open, SVO=semivertical open, HZO=horizontal open, VCT=vertical transparent doors, VCS=vertical solid doors, HCT=horizontal transparent 

doors, HCS=horizontal solid doors, or SOC=service over counter), an operating mode code (RC=remote condensing or SC=self-contained), and 

a rating temperature code (M=medium temperature (38°F), L=low temperature (0°F), or I=ice-cream temperature (-15°F)). For example, 

"VOP.RC.M refers to the "vertical open, remote condensing, medium temperature" equipment class. See chapter 3, market and technology 

assessment, for a more detailed explanation of the equipment class terminology 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
design classes as well as equipment designed to operate at 45°F, 20°F, and 10°F product 

temperatures. DOE presumed that equipment designed to operate at these latter design 

temperatures would have similar dimensions as for the medium, low, and ice cream temperature 

categories, respectively. DOE was then able to estimate the annual linear footage shipped for 

each of the 15 equipment classes and the entire set of commercial refrigeration equipment. Total 

linear footage shipped within the 15 equipment classes analyzed accounted for 99.9 percent of 

the total linear footage shipped in the medium, low, and ice cream temperature categories and 

98.7 percent of the linear footage shipped at all temperatures. The shipments analysis relies on 

the 15 equipment classes to represent the CRE market. Error! Not a valid bookmark selfreference. shows the fraction of the linear footage shipped by each of these 15 equipment 

classes. 

10.3.3 Commercial Grocery Display Space and Market Saturation 

The amount of commercial floor space is the main driver for commercial refrigeration 

equipment shipments and is appropriately one of the basic inputs into the Shipments Model. As 

discussed in section 10.2.2, the model divides commercial display space into two components: 

display space from new construction floor space (NFS), and existing display floor space (EFS). 

For this analysis, commercial square footage with commercial refrigerated display space 

refers to both new and existing stock of food sales buildings. 

Table 10.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment 

Equipment Class Percentage of Shipped Units 

Vertical Open.Remote Condensing.Medium (VOP.RC.M) 25.9% 

Vertical Open.Remote Condensing.Low (VOP.RC.L) 1.3 

Vertical Open.Self Contained.Medium (VOP.SC.M) 1.7 

Vertical Closed Transparent.Remote Condensing.Medium (VCT.RC.M) 1.9 

Vertical Closed Transparent.Remote Condensing.Low (VCT.RC.L) 25.7 

Vertical Closed Transparent.Self Contained. Ice Cream (VCT.SC.I) 0.6 

Vertical Closed Solid.Self Contained.Very Low (VCS.SC.I) 0.2 

Semi-Vertical Open.Remote Condensing.Medium (SVO.RC.M) 19.8 

Semi-Vertical Open. Self Contained.Medium (SVO.SC.M) 2.6 

Service Over Counter.Remote Condensing.Medium (SOC.RC.M) 5.0 

Horizontal Open.Remote Condensing.Medium (HZO.RC.M) 3.1 

Horizontal Open.Remote Condensing.Low (HZO.RC.L) 9.5 

Horizontal Open.Self Contained.Medium (HZO.SC.M) 0.2 

Horizontal Open.Self Contained.Low (HZO.SC.L) 0.5 

Horizontal Closed Transparent.Self Contained.Ice Cream (HCT.SC.I) 2.1 

100.0% 

Sources: ARI and CRE framework meeting comments 

10.3.3.1 Floor Space – New Construction 

DOE took the projected floor space construction after the year 2003 from the National 

Energy Modeling System (NEMS) projection published in the Annual Energy Outlook 2007 

(AEO 2007).2 AEO 2007 lists the projections for years 2009, 2010, 2015, 2020, 2025, and 2030. 

For unlisted years in this range, DOE derived NFS data by linear interpolation of the existing 

years. Beyond 2030, DOE extrapolated NFS from the 10-year trend of NEMS projected data 

between 2020 and 2030. 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
 

 

The total of new display space is the estimated total shipments in linear feet for 2006, 

times an index of new construction of square feet of food sales buildings for each future year, 

divided by its 2006 value. All existing display space is presumed to be replaced when 

demolished. 

10.3.3.2 Market Shipments 

DOE used the above shipments data to estimate the market shipments in year t of each 

commercial refrigeration equipment class y, MKTSHIP(t,y), defined in terms of linear feet of 

display space occupied by the new and replacement shipments of equipment class y. Because 

the percent of shipments in each class is relatively constant over time and the lifetime of each 

class is the same, the ratio of shipments to a class is indicative of the market share for that class, 

MKT(y). DOE estimated the MKT(y) for a particular equipment class to be a constant value 

equal to the average of the yearly percent historical shipments to that class. These percentages 

are reported in Error! Reference source not found.. 

MKTSHIP(t.y) = MKT(y) x (UN(t) + UB(t)) Eq. 10.6 

Where: 

MKTSHIP(t,y) = total market shipments, in linear feet of display space, of equipment class y 

in year t, 

MKT(y) = percentage of total market shipments in equipment class y, 

UN(t) = total shipments to new buildings in year t, 

UB(t) = total replacement shipments in year t. 

10.3.4 Equipment Utility 

The equipment utility is a measure of the economic value of a linear foot of commercial 

refrigeration equipment to the customers. This is the value associated with energy savings. 

Because there are not enough historical data available on the commercial refrigeration equipment 

market to develop and calibrate a full demand and supply model, economic factors are used to 

calculate annualized cost and calibrate market shares for the Shipments Model and are discussed 

below. 

10.3.5 Equipment Price 

Equipment price is the price paid by the customer for a unit of commercial refrigeration 

equipment. It includes both the purchase price of the equipment and installation costs. DOE 

converts the equipment price to a price per linear-foot-cooled based on the length of the 

equipment class. 

As discussed in the engineering analysis (chapter 5) and the life-cycle cost and payback 

period analysis (chapter 8), equipment prices in this analysis are a function of energy 

consumption level). DOE based equipment price projections on energy consumption level, but 

did not develop estimates of market trends in efficiency. DOE developed a mix of energy 

consumption levels for the base case (i.e., the case without new energy conservation standards) 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
and for each candidate standard level envisioned. The efficiency mixes are discussed in detail in 

chapter 11, section 11.2.2.1. 

10.3.5.1 Operating Costs 

Operating costs consist of maintenance costs, repair costs, and energy costs. 

Maintenance and Repair Costs. Each unit of commercial refrigeration equipment incurs 

yearly routine maintenance and standard repair costs. DOE converted these costs to a cost per 

unit and per linear foot of cooling capacity for each equipment class. Because DOE has very 

little information on either current or potential maintenance costs, an assumption was entered 

into the NOPR analysis of $156/year/ unit (2007$) for basic maintenance from R S Means Cost 

Works, to which is added a figure for lighting maintenance, which varies with the amount of 

efficient LED lighting added (see chapter 8, section 8.2.3.4) Whereas basic maintenance cost is 

assumed independent of refrigeration equipment class and energy efficiency, repair costs are 

potentially a function of both (see chapter 8, section 8.2.3.3). Thus, both projections for 

maintenance costs and repair costs are projected to increase with increasing energy-efficiency 

standards levels. Both maintenance and repair costs are discussed in detail in chapter 11, 

section 11.3.2.2. 

Energy Costs. The annual energy costs for a single CRE unit depend on the annual 

energy use per linear foot given the energy consumption level of the unit (energy use intensity or 

EUI), and the price of electricity. The determination of the EUI for an individual CRE unit is 

discussed in chapters 6 and 7, and the development of electricity prices is discussed in the 

life-cycle cost and payback period analysis (chapter 8, section 8.2.3.1). Coupling the EUI with 

electricity price data enables DOE to derive the annual per unit energy cost for each energy 

consumption level. Chapter 8 discusses how the EUI data are combined with the electricity price 

data to derive annual electricity costs. 

Available information suggests that the average annual energy costs for any given year 

change as the average efficiency of the shipped units improves. In any given year, there is a 

distribution of energy consumption levels for shipped equipment and the Shipments Model uses 

the shipment-weighted average efficiency for that given year. DOE based its projections of 

annual energy cost for each equipment class on the mix of energy consumption levels projected 

within that class, the total shipments for the equipment class, and future electricity prices. DOE 

developed a mix of energy consumption levels representative of the base case (i.e., the case 

without new efficiency standards) and for each candidate standard level. As noted earlier, the 

mix of energy consumption levels within each equipment class is discussed in detail in 

chapter 11, section 11.2.2.1. The impact of the mix of energy consumption levels on the average 

per unit energy costs for shipments within an equipment class is also discussed in detail in 

chapter 11, section 11.2.2.1. 

The mix of energy consumption levels allow for the determination of projected annual 

energy costs in 2007 dollars as a function of candidate standard level. To factor in the impact of 

future electricity prices, DOE used electricity price projections from the AEO 2008 to 

appropriately scale the above projected energy costs (for scaling purposes, the scaling factor for 

the year 2007 equals 1.0). 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
10.3.5.2 Discounted Costs 

When a decision is made to purchase commercial refrigeration equipment, an 

energy-conscious purchasing agent will consider the total lifetime cost of the equipment. 

Typically, these lifetime costs are discounted to represent the present value of these costs. DOE 

discounted the total operating costs (i.e., maintenance, repair, and energy costs) over the full 

lifetime of the equipment. Commercial refrigeration equipment lifetimes range from 1 to as 

many as 20 years, but based on discussions with industry, the typical value is 10 years in large 

food retailers and 15 years in small retailers, usually based on the fact that large grocery stores 

are either renovated or the refrigeration equipment is replaced for aesthetic reasons at about 

10-year intervals, but that small food retailers usually try to make their equipment last longer and 

update less frequently (see chapter 8 for further details). 

10.4 RESULTS 

Table 10.4.1 shows the shipments forecast for the commercial refrigeration equipment 

classes for the base case energy consumption level (or Level 1) divided into 

new and replacement units for large and small food sales outlets. 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
 

 

 

 

 

 

 

 

 

 

 

Table 10.4.2 shows total shipments by equipment type. 

Table 10.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration 

Equipment for Large and Small Food Sales Outlets, 2012-2042 (Base Case) 

Division 2012

Thousands of Linear Feet Shipped by Year and Equipment Class 

 2015 2020 2025 2030 2035 2040 2042 Cumulative 

New Large 

New Small 

Replacement Large 

Replacement Small 

Total 

249 

44 

1,269 

188 

1,750 

256 271 308 327 358 393 407 9830 

45 48 54 58 63 69 72 1,735 

1,201 1,254 1,282 1,385 1,480 1,641 1,708 42,535 

193 189 181 191 202 210 217 6,027 

1,694 1,763 1,826 1,960 2,103 2,313 2,404 60,125 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10.4.2 Forecasted Shipments for Commercial Refrigeration Equipment, 2012-2042, 

Level 1 (Base Case) 

Equipment Class 

Thousands of Linear Feet Shipped by Year and Equipment Class 

2012 2015 2020 2025 2030 2035 2040 2042 Cumulative 

VOP.RC.M 453 439 457 473 508 545 599 623 15,576 

VOP.RC.L 23 22 23 24 25 27 30 31 779 

VOP.SC.M 30 30 31 32 34 37 40 42 1,047 

VCT.RC.M 32 31 33 34 36 39 43 44 1,112 

VCT.RC.L 450 436 454 470 504 541 595 619 15,472 

VCT.SC.I 11 11 11 12 12 13 15 15 382 

VCS.SC.I 3 3 3 3 3 3 4 4 94 

SVO.RC.M 346 335 348 361 387 416 457 475 11,881 

SVO.SC.M 46 44 46 48 51 55 60 63 1,568 

SOC.RC.M 87 84 88 91 98 105 115 120 2,995 

HZO.RC.M 53 51 54 55 60 64 70 73 1,826 

HZO.RC.L 167 162 168 174 187 201 221 230 5,740 

HZO.SC.M 4 4 4 4 4 5 5 5 135 

HZO.SC.L 8 8 8 8 9 10 11 11 280 

HCT.SC.I 36 35 36 38 40 43 48 49 1,238 

Total 1,750 1,694 1,763 1,826 1,960 2,103 2,313 2,404 60,125 

As equipment purchase price increases with lower energy consumption levels, a drop in 

shipments could be expected relative to the base case. Although there is a provision in the 

spreadsheet for a change in shipments as the efficiency level increases (or energy consumption 

level decreases), DOE has no information with which to calibrate such a relationship. Therefore, 

for the NOPR analysis, DOE presumes that the shipments do not change in response to candidate 

standard levels. 

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EERE-2006-BT-STD-0126 COMMENT 52.2 
REFERENCES 

1. Freedonia. 2004. Commercial Refrigeration Equipment to 2008. Study 1849. Freedonia 

Group, Inc, Cleveland, Ohio, October 2004, 204 pp. available at 

http://www.freedoniagroup.com/Commercial-Refrigeration-Equipment.html 

2. EIA (Energy Information Administration). 2007. Annual Energy Outlook 2007. DOE/EIA0383(2007). U.S. Department of Energy, Energy Information Administration, Washington 

D.C. 

3. EIA (Energy Information Administration). 2008. Annual Energy Outlook 2008. DOE/EIA0383(2008). U.S. Department of Energy, Energy Information Administration, Washington 

D.C. 

10-9
 

EERE-2006-BT-STD-0126 COMMENT 52.2