CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

9.1 INTRODUCTION...............................................................................................................9­1

9.2 SHIPMENTS MODEL EQUATIONS................................................................................9­2

9.2.1 Mathematical Formulation of the Shipments Model............................................9­2

9.2.2 Stock Events.........................................................................................................9­3

9.2.2.1 Replacing Equipment..............................................................................9­3

9.2.2.2 New equipment.......................................................................................9­3

9.3 DATA INPUTS...................................................................................................................9­4

9.3.1 Historical Shipments............................................................................................9­4

9.3.2 Historical Shipped Linear Feet.............................................................................9­4

9.3.3 Commercial Grocery Display Space and Market Saturation ...............................9­5

9.3.3.1 Floor Space – New Construction............................................................9­5

9.3.3.2 Market Shipments...................................................................................9­7

9.3.4 Equipment Utility.................................................................................................9­7

9.3.5 Equipment Price ...................................................................................................9­7

9.3.5.1 Operating Costs ......................................................................................9­7

9.3.5.2 Discounted Costs....................................................................................9­8

9.4 RESULTS............................................................................................................................9­9

9.5 REFERENCES..................................................................................................................9­10

LIST OF TABLES

Table 9.3.1 Equipment Linear Dimensions Assumed for Shipments Analysis........................9­6

Table 9.3.2 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment............9­6

Table 9.4.1 Forecasted Shipments for Commercial Refrigeration Equipment, 2012­2042,

Level 1 (Base Case) ...............................................................................................9­9

LIST OF FIGURES

Figure 9.1.1 Flow Chart Showing Inputs to the Shipments Model............................................9­1

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CHAPTER 9. SHIPMENTS ANALYSIS

9.1 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 9.1.1 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 10, section 10.5 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 9.2 presents the mathematical formulation of the model, section 9.3 describes the

data inputs to the model, and section 9.4 presents the results for different minimum

energy­conservation standard level 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 Sales 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 9.1.1 Flow Chart Showing Inputs to the Shipments Model

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9.2 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.

9.2.1 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. Also, available information suggests that the initial existing stock of equipment has 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. 9.1

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

StockAge(t) = ∑aU( t, a) x a / ∑(U( t,a)) Eq. 9.2

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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9.2.2 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.

9.2.2.1 Replacing Equipment

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

stock U0 will break or will be replaced using a known function PB0(a)=0.1 (based on a ten year

life). Similarly, the probability that equipment of age a from stock U1 will break is given by a

known 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. 9.3

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.

9.2.2.2 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. 9.4

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 9.3.3),

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DFS(t) = the square footage demolished in year t (described in section 9.3.3.1).

The linear footage of units going into new buildings is

UN(t) = UN(t) x A0 x NFS(t)/ NFS(0) Eq. 9.5

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.

9.3 DATA INPUTS

9.3.1 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 ANOPR, DOE has used the ARI

data as a starting estimate for its shipments analysis.

9.3.2 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.

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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 9.3.3.2. 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.

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 9.3.1 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

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. Table 9.3.2 shows the fraction of the

linear footage shipped by each of these 15 equipment classes.

9.3.3 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 9.2.2, 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.

9.3.3.1 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 2006

(AEO 2006).2 AEO 2006 lists the projections for years 2005, 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,

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

demolished.

Table 9.3.1 Equipment Linear Dimensions Assumed for Shipments Analysis

Equipment Assumed

Classa 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

Table 9.3.2 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment

Equipment Class Percentage of Shipped Units

Vertical Open.Remote Condensing.Medium (VOP.RC.M) 26.2%

Vertical Open.Remote Condensing.Low (VOP.RC.L) 0.0*

Vertical Open.Self Contained.Medium (VOP.SC.M) 1.8

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

Vertical Closed Transparent.Remote Condensing.Low (VCT.RC.L) 26.1

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) 20.0

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) 9.7

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%

* Estimated shipments of this class were zero. The industry requested that this equipment class be included in the rulemaking

Sources: ARI and CRE framework meeting comments

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9.3.3.2 Market Shipments

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

commercial refrigeration equipment 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 Table 9.3.1.

MKTSHIP(t.y) = MKT(y) x (UN(t) + UB(t)) Eq. 9.6

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.

9.3.4 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.

9.3.5 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 10, section 10.2.2.1.

9.3.5.1 Operating Costs

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

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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, a placeholder assumption was

entered into the analysis of $200/year/ unit (2006$) for maintenance. Whereas maintenance cost

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

potentially a function of both. Thus, projections for maintenance costs remain constant both in

the base and energy efficiency standards cases. However, repair costs are projected to increase

with increasing energy­efficiency standards levels. Both maintenance and repair costs are

discussed in detail in chapter 10, section 10.3.2.2.

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 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

10, section 10.2.2.1. 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 10,

section 10.2.2.1 also.

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

energy costs in 2006 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 2006 to

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

the year 2006 equals 1.0).

9.3.5.2 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, usually

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based on the fact that grocery stores are either renovated or the refrigeration equipment is

replaced for aesthetic reasons at about 10­year intervals (see chapter 8 for further details).

9.4 RESULTS

Table 9.4.1 shows the shipments forecast for the commercial refrigeration equipment

classes for the base case energy consumption level (or Level 1). 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 ANOPR analysis, DOE presumes

that the shipments do not change in response to candidate standard levels.

Table 9.4.1 Forecasted Shipments for Commercial Refrigeration Equipment, 2012­2042,

Level 1 (Base Case)

Equipment Thousands of Linear Feet Shipped by Year and Equipment Class

Class 2012 2015 2020 2025 2030 2035 2040 2042 Cumulative

VOP.RC.M 423 446 490 538 591 649 714 742 17574

VOP.RC.L* 0 0 0 0 0 0 0 0 0

VOP.SC.M 28 30 33 36 40 44 48 50 1182

VCT.RC.M 30 32 35 38 42 46 51 53 1255

VCT.RC.L 420 443 487 535 587 645 709 737 17456

VCT.SC.I 10 11 12 13 14 16 17 18 430

VCS.SC.I 3 3 3 3 4 4 4 5 107

SVO.RC.M 323 340 374 411 451 495 545 566 13405

SVO.SC.M 43 45 49 54 59 65 72 75 1769

SOC.RC.M 81 86 94 104 114 125 137 143 3379

HZO.RC.M 50 52 57 63 69 76 84 87 2060

HZO.RC.L 156 164 181 198 218 239 263 273 6476

HZO.SC.M 4 4 4 5 5 6 6 6 152

HZO.SC.L 8 8 9 10 11 12 13 13 315

HCT.SC.I 34 35 39 43 47 52 57 59 1397

* Estimated shipments of this class were zero. The industry requested that this equipment class be included in the rulemaking

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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). 2006. Annual Energy Outlook 2006. DOE/EIA0383(2006). U.S. Department of Energy, Energy Information Administration, Washington

D.C.

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