CHAPTER 10. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

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

10.2 SHIPMENTS MODEL EQUATIONS .......................................................................... 10­2
 

10.2.1 Mathematical Formulation of the Shipments Model ...................................... 10­2
 

10.2.2 Stock Events.................................................................................................... 10­3
 

10.2.2.1 Replacing Equipment.................................................................... 10­3
 

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

10.3 DATA INPUTS ............................................................................................................. 10­4
 

10.3.1 Historical Shipments....................................................................................... 10­4
 

10.3.2 Historical Shipped Linear Feet ....................................................................... 10­5
 

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

10.3.3.1 Floor Space – New Construction .................................................. 10­7
 

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

10.3.4 Equipment Utility............................................................................................ 10­8
 

10.3.5 Equipment Price.............................................................................................. 10­8
 

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

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

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

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

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....... 10­5
 

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

Table 10.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis.................... 10­6
 

Table 10.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment........ 10­7
 

Table 10.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration
 

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

Case) ................................................................................................................ 10­10

Table 10.4.2 Forecasted Shipments for Commercial Refrigeration Equipment,

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

LIST OF FIGURES

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

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CHAPTER 10. SHIPMENTS ANALYSIS
 

10.1 INTRODUCTION
 

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

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

manufacturer impacts analysis (MIA). This chapter describes the U.S. Department of Energy

(DOE)’s methodology for projecting annual shipments and presents results.

The Shipments Model results are driven primarily by historical shipments 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 one 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 inputs to the model, and section 10.4 presents the results for the base case

energy­conservation 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.”

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

NES and NPV are required. DOE is considering up to eight candidate standard levels for each of

the 15 equipment classes.

NEMS Food Services

Bldg

Construction Forecast ARI Estimate of

Shipments (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

% Shipments by Product

Class (2005)

CRE Stock

by Product

Class

NEMS Food Services

Bldg

Construction Forecast ARI Estimate of

Shipments (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

% Shipments by Product

Class (2005)

CRE Stock

by Product

Class

Figure 10.1.1 Flow Chart Showing Inputs to the Shipments Model
 

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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(y,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 five years, based on the 10­year lifetime of a unit of equipment, and annual replacements

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

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).

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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, or

•	 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 ten­year average lifetime, a minimum

lifetime of about seven 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 y. 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,
 

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

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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 which 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 one­for­one 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 is aggregated at a high level with regard to equipment categorization and provides

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 Air­Conditioning and Refrigeration

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

for one year (2005) that allowed DOE to allocate sales of equipment to equipment classes. This

data is 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.

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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. 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 69.2% 15.9% 85.0%

Small Retail 12.2% 2.8% 15.0%

Total 81.3% 18.7% 100.0%

* Calculated from ARI data

Table 10.3.2	 AEO 2007 forecast of New Food Sales Square Footage

New Construction

Year (Million Square Feet)

2009 42.9

2010 43.3

2015 45.8

2020 47.9

2025 54.1

2030 57.4

Annual Growth Factor,

2030­2042 1.8%

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 self­contained), 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

life­cycle cost analysis, but for which shipments were reported by ARI, including small­shipment

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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=self­contained), and

a rating temperature code (M=medium temperature (38°F), L=low temperature (0°F), or I=ice­cream 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

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.

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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

Semi­Vertical Open.Remote Condensing.Medium (SVO.RC.M) 19.8

Semi­Vertical 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 10­year trend of NEMS projected data

between 2020 and 2030.

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:

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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 linear­foot­cooled based on the length of the

equipment class.

As discussed in the engineering analysis (chapter 5) and the life­cycle 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)

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 $156/year/ unit (2006$) 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 energy­efficiency

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

section 11.3.2.2.

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

life­cycle 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 shipment­weighted 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 discussed in detail in chapter 11,

section 11.2.2.1 also.

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 2007 to

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

the year 2007 equals 1.0).

10.3.5.2 Discounted Costs

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

energy­conscious 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 one 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. Table 10.4.2 shows total shipments by

equipment type.

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Table 10.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration

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

246

43

1,265

188

1,742

251 262 296 314 343 376 390 9,471

44 46 52 55 61 66 69 1,671

1,195 1,243 1,264 1,360 1,447 1,599 1,661 41,858

192 188 179 188 198 204 211 5,941

1,682 1,739 1,791 1,918 2,049 2,245 2,330 58,941

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

Level 1 (Base Case)

Equipment

Class 2012

Thousands of Linear Feet Shipped by Year and Equipment Class

2015 2020 2025 2030 2035 2040 2042 Cumulative

VOP.RC.M 451 436 451 464 497 531 582 604 15,270

VOP.RC.L 23 22 23 23 25 27 29 30 763

VOP.SC.M 30 29 30 31 33 36 39 41 1,027

VCT.RC.M 32 31 32 33 35 38 42 43 1,091

VCT.RC.L 448 433 448 461 494 527 578 600 15,167

VCT.SC.I 11 11 11 11 12 13 14 15 374

VCS.SC.I 3 3 3 3 3 3 4 4 93

SVO.RC.M 344 332 344 354 379 405 444 460 11,647

SVO.SC.M 45 44 45 47 50 53 59 61 1,537

SOC.RC.M 87 84 87 89 96 102 112 116 2,936

HZO.RC.M 53 51 53 54 58 62 68 71 1,790

HZO.RC.L 166 161 166 171 183 196 214 222 5,627

HZO.SC.M 4 4 4 4 4 5 5 5 132

HZO.SC.L 8 8 8 8 9 10 10 11 274

HCT.SC.I 36 35 36 37 39 42 46 48 1,214

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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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/Commercial­Refrigeration­Equipment.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.

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 EE-2006-STD-0126 COMMENT 23.2