9

- i CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

9.1 INTRODUCTION .............................................................................................................. 9-2

9.2 SHIPMENTS MODEL EQUA TIONS ............................................................................... 9-2

9.2.1 Shipments Model .................................................................................................... 9-3

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

9.2.2.1 Replacing Equipment ............................................................................... 9-4

9.2.2.2 New Equipment ....................................................................................... 9-4

9.3 DATA INPUTS .................................................................................................................. 9-5

9.3.1 Historical Shipments ............................................................................................... 9-5

9.3.2 Historical Shipments and Projected Building Stock Additions .............................. 9-6

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

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

9.3.3.2 Market Shipments .................................................................................... 9-9

9.3.4 Equipment Utility

................................ ................................ .................................. 9-10

9.3.5 Equipment Price .................................................................................................... 9-10

9.3.5.1 Operating Costs ...................................................................................... 9-10

9.3.5.2 Discounted Costs ................................................................................... 9-10

9.4 RESULTS ......................................................................................................................... 9-10

REFERENCES .......................................................................................................................... 9-13

LIST OF TABLES

Table 9.3.1 Estimated Distribution of 2009 Linear Feet of Commercial Refrigeration Equipment Shipments Among New vs. Replacement Equipment ......................................... 9-7

Table 9.3.2 AEO2010 Forecast of New Food Sales and Foodservice Square Footage ............... 9-7 Table 9.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis ........................... 9-8 Table 9.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment ............... 9-8 Table 9.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration Equipment by Building Type, 2016

− 2045 (Base Case) .................................... 9-11 Table 9.4.2 Forecasted Shipments for Commercial Refrigeration Equipment, 2016

− 2045, by Equipment Type (Base Case)

................................ ............................................. 9-11

LIST OF F IGURES

Figure 9.1.1 Flow Chart Showing Inputs to the Shipments Model ............................................. 9-29

- 2 CHAPTER 9 . SHIPMENTS ANALYSIS

9.1 INTRODUCTION

Commercial refrigeration equipment shipment numbers are key inputs to the national energy savings

, net present value calculations , and the manufacturer impacts analysis. This chapter describes the U.S. Department of Energy ’s (DOE ’s ) methodology for estimating commercial refrigeration equipment shipments and annual equipment stocks for 2009 through

2045.

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

24 primary classes of commercial refrigeration equipment under consideration. 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 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).

Section 9.2 presents the mathematical formulation of the model

, section 9.3 describes the data input to the model, and section 9.4 presents the results for the base case energy conservation

standard level scenario and discusses the development of higher standard scenarios.

Figure 9.1.1 Flow Chart Showing Inputs to the Shipments Model

9.2 SHIPMENTS MODEL EQUA TIONS

The Shipments Model is a description of commercial refrigeration equipment stock flows as a function of year and age. Wh ile 24 equipment classes are examined in the model

, it is

assumed that there is no coupling between the shipments of the various equipment classes, so the equations are applicable to each equipment class independently

.

D OE formulated the Shipments Model equations as updates of the distribution of stock in

year t to year t+1 as a function of age a

. DOE first converted the equipment units to linear feet of refrigerator/freezer space using national statistics on sales of equipment and representative equipment size ( linear f ee t). DOE uses this calculation of existing stock, and the average age of 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 Shipments Estimates

Based on Historic
Shipments Data9

- 3 the equipment, as a basis for calculating replacement sales. Then, DOE subtracted replacement

sales from historical total sales statistics to calculate new sales of commercial refrigeration equipment. DOE forecasted new sales as a function of new construction of retail food sales and

foodservice space. Sales of new and replacement equipment we re recorded by the year sold, and each annual vintage is depreciated over the estim ated life of the equipment. Sales in each year

we re allocated to the 24 equipment classes in proportion to their relative historical sales

.

9.2.1 Shipments Model

DOE uses two commercial refrigeration equipment stock categories . T he category U 0 (t ,a) is the stock of existing units . All units are assumed to have had normal repairs that do not affect

the lifetime of the equipment.

As discussed in chapter 7 of the preliminary technical support document (TSD), the

lifetime of a unit is estimated to be 10 years in large food retailers and in all foodservice categories (full service restaurants, limited service restaurants, and other foodservice), and about 15 years in small retailers

, such as convenience stores . Also, t he average age of the initi al existing stock of equipment is assumed to be 5 years, based on the 10- year lifetime of a unit of equipment and an nual replacements going back 10 years. The total stock of age a in a given year

t is represented by

U (t ,a) = U 0 (t ,a) Eq. 9.1

W here:

U

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

, U

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

a = age of stock (year) , and

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)

.

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:

1. existing equipment could break or be removed during a store renovation and be replaced

,

or

2. the stock could simply age by 1 year.

In the model, early replacements ( i.e. , existing equipment that is replaced before it is broken) are not considered, and all broken equipment is assumed to be replaced. The following

sections present the equations used to represent each possible event.9

- 4 9.2.2.1 Replacing Equipment

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

stock U 0 will break or will be replaced using a Weibull survival distribution function

PB 0 (a) = W( 8,10.62) for large food sales and for foodservice applications. This results in a 10- year average lifetime, a minimum lifetime of about 7 years, and a maximum lifetime of about 13

year s, consistent with industry comments . The function PB 0 (a)=W(8,1 6) was used for small food

sales outlets

, i.e.

, convenience stores with and without gas stations. This 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

U

1 will break is given by the same function PB 1 (a) . These probabilities do not depend on the model year t . D OE defines the quantities of replaced equipment as

UB ( t

, a ) = PB 0 ( a ) × U 0 ( t

, a ) Eq. 9.2

W here:

UB ( t,a ) = quantity of replacement units of age a in year t

, PB 0 ( a ) = probability that stock of existing units of age a will break or will be replaced

, U

0 ( t,a ) = stock of existing units of age a in year t

,

a = age of stock (years) , and

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 broken units

described above. Available information suggests that the purchase of new equipment for use in new buildings is driven by the rate of construction of food sales and foodservice floor space.

By defini tion , for each type of building:

EFS ( t

+1) = EFS ( t ) + NFS ( t )

- DFS ( t ) Eq. 9.3

W here:

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

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

, and

DFS (t) = the square footage demolished in year t

.

The linear footage of units installed in new buildings is

UN (t ) = UN (t -1 ) × A 0 × NFS (t)/ NFS (t-1) Eq. 9.49

- 5 W here:

UN(t) = the number of units installed in new buildings in year t

, and

A 0 = an overall scale factor that accounts for the number of units covered by the standard , which are not used in all commercial building types ; t he default value for A 0 is 1.0.

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 the assumption th at broken or removed equipment is replaced on a one- for

- one basis.

9.3 DATA INPUTS

9.3.1 Historical Shipments

Shipments data for commercial refrigeration equipment could not be obtained in a complete form from any one source ; therefore, DOE used data from multiple sources to estimate shipments. The major sources were 2005 shipments data provided by the Air -Conditioning, Heating, and Refrigeration Institute ( AHRI ) as part of its comments to the 2009 rulemaking

F ramework Document (ARI, No. 7 Exhibit B at p. 1, Docket # EERE –2006– BT

– STD – 0126); Commercial Refrigeration Equipment to 2014 by Freedonia Group , Inc. ( the Freedonia 2010 report) ; 1 2008 Size and Shape of Industry by the North American Association of Food Equipment Manufacturers (NAFEM 2008 report); 2 and Energy Savings Potential and R&D Opportunities for Commercial Refrigeration prepared by Navigant Consulting, Inc

., for DOE (NCI 2009 report). 3 Further details about these data sources can be obtained from chapter 3.

The AHRI 2005 shipments data was a compilation of shipment numbers provided by

AHRI members , and as such did not represent the entire commercial refrigeration equipment

market. However, the AHRI 2005 shipments data contained shipments explicitly broken down by DOE equipment class. The Freedonia 2010 report provided shipments data in terms of total

dollar sales and number of units shipped. Shipments we re split by market type ( e.g. , foodservice industry and food & beverage retail industry) and by certain equipment types such as open display cases, reach -ins, and beverage refrigeration. The NAFEM 2008 report provided shipment numbers and dollar sales values for refrigeration and ice machines used in the foodservice industry. Reach- in refrigerators and freezers, chest freezer s, milk coolers, and ice- cream storage and dipping cabinets make up the majority of the commercial refrigeration equipment used in the foodservice industry.

Because c omplete shipments data could not be obtained from a single source, DOE compiled data from all of the aforementioned sources and developed the 2009 shipment numbers using some basic assumptions. The Freedonia 2010 report contains historical data used to derive

a year -to- year percentage change in the total commercial refrigeration equipment sales. DOE

assumed that subsequent years’ shipments of the equipment reported in the 2005 AHRI summary grew at the year -to- year growth rates reported by Freedonia, and used the percentage changes from the Freedonia 2010 report to derive the 2009 AHRI shipment estimates from the AHRI reported shipments for the year 2005.9

- 6 The 2009 shipment numbers derived from the 2005 AHRI shipments data were modified for certain equipment classes using shipments data obtained for the other sources. (Chapter 3 of the preliminary TSD de fines the acronym s used for the equipment classes in this section. ) Shipments for equipment classes VCS.SC.M and VCS.SC.L were obtained from estimates from the NAFEM 2008 report. Shipments for equipment classes HZO.SC.I, HCT.SC.I, and HCS.SC.I

were obtained based on estima tes from the Freedonia 20 10 report. Shipments for equipment class

PD.SC.M were obtained based on estimates from the NCI 2009 report. As mentioned above, shipments by equipment class were available only from the 2005 AHRI data. T o allocate the shipments to different equipment classes from the other sources, DOE made assumptions about

the definition s of the equipment types and the market share split for certain equipment classes. Shipments numbers and assumptions have been withheld because the sources cited above are not public documents and are available only for purchase.

9.3.2 Historical Shipments and Projected Building Stock Additions

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 estimated 200 9 shipments data in each equipment class to
percent ages of total shipped linear feet of commercial refrigeration equipment for use in the Shipments Model. This establish ed the commercial refrigeration equipment market share

attributed to each equipment class. 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 9.3.1 summarizes DOE’s estimated division of historical annual shipments into

new and replacement categories by building type. The distributions shown in Table 9.3.1 result from several discrete steps. First, equipment types were identified by the type of business they generally serve. For example, vertical open cases with remote compressors are associated with large grocers and multi

- line retail stores . R emote condensing equipment is generally associate d with large food sales stores, while self contained units are associated with food service and

convenience or small food sales stores. When there was no strong association between the building type and equipment class, equipment was distributed across bro ader classes. Second, a ratio of new versus replacement was developed based on commercial floor space estimates ( floor space estimates are discussed below)

. Using the expected useful life of commercial refrigeration equipment and commercial floor space stock, additions, and retirements, ratios were developed that yielded a ratio of new versus replacement stock for use in this analysis. Using these and related factors (e.g., the division of foodservice into the three building types – limited service

restaura nts, full service restaurants, and other), DOE distributed commercial refrigeration equipment shipments among building types and new versus replacement shipments as shown in

Table 9.3.1

.9

- 7 Table 9.3.1 Estimated Distribution of 2009 Linear Feet of Commercial Refrigeration Equipment Shipments A mong New vs. Replacement Equipment

Building Type Replacement New Total Large Grocery / Multi

- Line Retail 39.8% 9.3% 49.1% Small Grocery / Convenience 11.8% 2.7% 14.5%

Limited Service Restaurants 9.3% 3.4% 12.7%

Full Service Restaurants 14.9% 5.5% 20.4%

Other 2.4% 0.9% 3.3%

Total 78.2% 21.8% 100.0%

Table 9.3.2 shows the forecasted square footage of new construction used to scale annual new commercial refrigeration equipment shipments. As the data on Table 9.3.2 shows,

forecasted s quare footage additions to the building stock s vary from year to year , with the first few years exhibiting lower levels of growth due to the lingering impacts of the U.S. economic

recession

. The forecasted commercial refrige ration equipment shipments therefore show some variability as well, tracking the forecasted square footage floor space additions. The growth rates

over the last 10 years of the Annual Energy Outlook (

AEO ) forecast (2026 through 2035) were

used to extend th e AEO forecast out until the year 2045 in order to develop the full 30- year forecast needed for the n ational i mpacts a nalysis (see TSD chapter 10)

.

Table 9.3.2 AEO2010 Forecast of New Food Sales and Foods ervice Square Footage

Year New Construction

m illion ft 2

Food s ervice Food Sales

2009 44.525 31.931

2011 31.597 22.412

2016 49.933 35.990

2020 57.774 41.825

2025 61.521 44.524

2030 65.707 47.469

2035 69.711 50.255

Annual Growth Factor, 2026

- 2035 2.65% 2.77%

Source: U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 2010, data file kdbou

DOE used the AH RI shipments data to derive shipped linear footage for each of the 24 primary equipment classes

. Table 9.3.3 presents the representative equipment class lengths used for the conversion of per-unit shipments to linear footage wit hin each equipment class.9

- 8 Table 9.3.3 Equipment Linear Dimensions Assumed for Shipments Analysis

Equipment

Class Assumed Length ft Basis

VOP.RC.M 10 Average of 8 ft and 12 ft, m anufacturer i nterviews

VOP.RC.L 10 Average of 8 ft and 12 ft, m anufacturer i nterviews

VOP.SC.M 4 Baseline e quipment used for engineering a nalysis

SVO.RC.M 10 Average of 8 ft and 12 ft, m anufacturer i nterviews

SVO.SC.M 4 Baseline e quipment used for engineering a nalysis

HZO.RC.M 10 Average of 8 ft and 12 ft, m anufacturer i nterviews

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 in. per door), manufacturer interviews

VCT.RC.L 10 Average of 3

- door and 5

– door (3 in. per door), manufacturer interviews

VCT.SC.M 4 Engineering estimate

VCT.SC.L 3.5 Average of 1

- door and 2

- door freezer

VCT.SC.I 5 Baseline equipment used for engineering analysis

VCS.SC.M 4 Engineering estimate

VCS.SC.L 3.5 Average of 1

- door and 2

- door freezer

VCS.SC.I 5 Baseline equipment used for engineering analysis

HCT.SC.M 3.0 Engineering estimate

HCT.SC.L 3.0 Engineering estimate

HCT.SC.I 3.4 Baseline equipment used for engineering analysis

HCS.SC.M 4.0 Engineering estimate

HCS.SC.L 5.0 Engineering estimate

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

PD.SC.M 2.5 Baseline equipment used for engineering analysis

DOE then e stimate d the annual linear footage shipped for each of the 24 equipment

classes. The shipments analysis relies on the 24 equipment classes to represent the commercial refrigeration equipment market. Table 9.3.4 shows the fraction of the linear footage shipped by

each of these 24 equipment classes.

Table 9.3.4 Percent of Shipped Linear Feet of Commercial Refrigeration Equipment

Equipment

Class * Percentage of Linear Feet Shipped Equipment

Class Percentage of Linear Feet Shipped

VOP.RC.M 10.81% SVO.SC.M 1.28%

VOP.RC.L 1.91% SOC.RC.M 2.45%

VOP.SC.M 0.86% HZO.RC.M 1.49%

VCT.RC.M 0.91% HZO.RC.L 4.69%

VCT.RC.L 12.64% HZO.SC.M 0.11%

VCT.SC.M 5.77% HZO.SC.L 0.23%

VCT.SC.L 2.93% HCT.SC.M 0.07%

VCT.SC.I 2.27% HCT.SC.L* 0.00%

VCS.SC.M 17.30% HCT.SC.I ** 1.01%

VCS.SC.L 8.80% HCS.SC.M 5.22%

VCS.SC.I 0.08% HCS.SC.L 0.67%

SVO.RC.M 9.70% PD.SC.M 7.16%

* No shipments were estimated for HCT.SC.L

** HCS.SC.I was not analyzed as a primary class.9

- 9 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 space i nto two componen ts: space from new construction floor space (NFS), and existing floor space (EFS).

For this analysis, commercial square footage with commercial refrigerat ion equipment refers to both new and existing stock of buildings.

9.3.3.1 Floor Space

– New Construction

DOE took the projected floor space construction after the year 2009 from the National Energy Modeling System projection underlying AEO2010

. 4 DOE extracted annual estimates of new floor space additions from an AEO2010 data file (kdbout) for the 2009 through 2035 period. As stated earlier, the last 10 years of the AEO forecast were used to develop growth rates used to

extend the forecast to 2045.

The total of new length of display case area is the estimated total shipments in linear feet for 2009, divided between the food sales and foodservice sectors and multiplied by index es of new construction of square feet for each building type. The index for each building type was developed by dividing floor space projections in each future year by the corresponding 2009

value. All existing display space is presumed to be replaced when demolished.

9.3.3.2 Market Sh ipments

DOE used the above shipments d ata 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

remains same , the ratio of shipments of a specific equipment class indicates 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 th at class. These percentages are reported in Table 9.3.4

.

MKTSHIP ( t

, y ) = MKT ( y ) × ( UN ( t ) + UB ( t ) ) Eq. 9.5

W here:

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

, and

UB (t) = total replacement shipments in year t

.9

- 10 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 customer. This is the value associated with energy savings.

Because there are insufficient historical data available on the commercial refrigeration equipment market to develop and calibrate a full supply and demand model, economic factors

are used to calculate annualized cost and to calibrate market shares for the Shipments Model.

These economic factors 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 the 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 efficiency

level

. DOE based equipment price projections on energy consumption level, but did not develop

estimates of market trends in efficienc y. 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.

9.3.5.1 Operating Costs

Operating costs consist of maintenance, repair, and energy costs. A d etailed description of all the operating costs can be found in chapter 8.

9.3.5.2 Discounted Costs

When purchas ing commercial refrigeration equipment, an energy conscious customer will consider the total lifetime cost of the equipment . T ypically, 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 . However, based on discussions with industry, the typical lifetime of commercial refrigeration equipment is 10 years in large food retailers and 15 years in small retailers . This is because large grocery stores either undergo renovat ion or replace the refrigeration equipment for aesthetic reasons at roughly

10- year intervals, but small food retailers usually try to make their equipment last longer and update it less frequently (see chapter 8 for further details).

9.4 RESULTS

Table 9.4.1 shows the shipments forecast for th e commercial refrigeration equipment

classes at the base case energy consumption level (or Level 1 ) divided into new and replacement units for large and small food sales and foodservice outlets

. Table 9.4.2 shows total shipments by equipment type.9

- 11 Table 9.4.1 Forecasted Shipments of New and Replacement Commercial Refrigeration Equipment by Building Type, 2016

− 2045 (Base Case)

Building Type Thousands of Linear Feet Shipped by Year and Equipment Class

2016 2020 2025 2030 2035 2040 2045 Total Large Grocery

– New 291 338 360 384 406 435 467 11,564

– Replacement* 1,042 1,169 1,224 1,395 1,502 1,685 1,833 42,279 Small Grocery

– New 86 100 106 113 120 128 138 3,414

– Replacement* 301 294 323 338 352 385 411 10,276

Food s ervice

– New 303 351 373 399 423 452 485 12,026

– Replacement* 699 848 920 1,114 1,240 1,444 1,613 33,869

Total 2,722 3,099 3,307 3,742 4,043 4,530 4,947 113,429
* Replacement includes equipment replaced from original stock (installed before the standards set by the current rulemaking takes effect ) and the standards level equipment replaced in subsequent years.

Table 9.4.2 Forecasted Shipments for Commercial Refrigeration Equipment, 2016

− 2045, by Equipment Type (Base Case)

Equipment Class Thousands of Linear Feet Shipped by Year and Equipment Class *

2016 2020 2025 2030 2035 2040 2045 Cumulative

VOP.RC.M 294 335 358 405 437 490 535 12,265

VOP.RC.L 52 59 63 71 77 86 94 2,164

VOP.SC.M 23 27 28 32 35 39 42 970

VCT.RC.M 25 28 30 34 37 41 45 1,031

VCT.RC.L 344 392 418 473 511 572 625 14,333

VCT.SC.M 157 179 191 216 233 261 285 6,539

VCT.SC.L 80 91 97 110 119 133 145 3,329

VCT.SC.I 62 70 75 85 92 103 112 2,573

VCS.SC.M 471 536 572 647 699 783 856 19,618

VCS.SC.L 240 273 291 329 356 399 436 9,986

VCS.SC.I 2 2 3 3 3 3 4 88

SVO.RC.M 264 301 321 363 392 440 480 11,007

SVO.SC.M 35 40 42 48 52 58 63 1,453

SOC.RC.M 67 76 81 92 99 111 121 2,775

HZO.RC.M 41 46 49 56 60 68 74 1,691

HZO.RC.L 128 145 155 175 190 212 232 5,318

HZO.SC.M 3 3 4 4 4 5 5 125

HZO.SC.L 6 7 8 9 9 10 11 259

HCT.SC.M 2 2 2 3 3 3 4 81

HCT.SC.L

- - - - - - - - HCT.SC.I 28 31 33 38 41 46 50 1,147

HCS.SC.M 142 162 173 195 211 237 258 5,924

HCS.SC.L 18 21 22 25 27 31 33 765

PD.SC.M 195 222 237 268 290 324 354 8,123

Total 2,677 3,048 3,253 3,680 3,977 4,455 4,865 111,562

* Table 9.4 .2 values include only equipment classes modeled in the e ngineering, l ife -c ycle c ost, and n ational i mpact a nalyses.

Numbers do not add to the totals shown i n Table 9.4 .2 due to existence of small quantities shipped to other equipment classes.

As equipment purchase price increases with lower energy consumption levels, a drop in shipments could be expected re lative to the base case. Although there is a provision in the Shipments Model spreadsheet for a change in shipments as the efficiency level increases (or9

- 12 energy consumption level decreases), DOE has no information with which to calibrate such a relationship. Therefore, for the p reliminary analysis, DOE presumes that the shipments do not change in response to the higher efficiency level s that form potential candidate standard levels.9

- 13 REFERENCES

1. Freedonia Group, Inc

. Commercial Refrigeration Equipment to 2014 . 2010. Cleveland, Ohio. Study 2261. < http://www.freedoniagroup.com/Commercial- Refrigeration -Equipment.html >

2. North American Association of Food Equipment Manufacturers. 2008 Size and Shape of Industry . 2008. Chicago, IL.

3. Navigant Consulting, Inc. Energy Savings Potential and R&D Opportunities for Commercial Refrigeration

. 2009. Prepared by Navigant Consulting, Inc. for the U.S. Department of Energy, Washington, DC.

4. U.S. Department of Energy, Energy Information Administration. Annual Energy Outlook

2010 . 2010. Washington D.C. DOE/EIA -0383(2010).