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 Sp ace 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 Lin ear 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 a nd Replacement Commercial Refrigeration Equipment for Large and Small Food Sales Outlets, 2012-2042 (Base Case)

.................................................................................................................. 10-9 Table 10.4.2 Forecasted Shipments for Co mmercial 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

10-i10-iiCHAPTER 10. SHIPMENTS ANALYSIS

10.1 INTRODUCTION

Commercial refrigeration equipment (CRE) sh ipments estimates are a necessary input to the national energy savings (NES), net present value (NPV) calculations , and the manufacturer impacts analysis (MIA). This chapter desc ribes the U.S. Department of Energy’s (DOE) methodology for projecting annual shipments and presents results.

The Shipments Model results are driven prim arily by historical shipment data for the 15 categories of commercial re frigeration 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. Br oken equipment is repl aced. 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 Mi crosoft Excel spreadsheet form at that is accessible on the Internet at: http://www.eere.energy.gov/build ings/appliance_standards / commercial_products.html.

Further, chapter 11, section 11.5 of this T echnical Support Document (TSD), discusses how to access the Shipments Model spreadsheet a nd other related spreadsheets, and provides basic instructions for using them. The rest of this chapter explai ns 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 leve l scenario and discu sses the development of higher standard scenarios. The energy conservation standards for commercial refrigeration equipment will set the maximum rated energy consumption for all e quipment within an equipment class. DOE refers to each standard le vel 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.

10-1NE M S F o od Se rv ice s Bl d g
Constru c t i on ForecastForecast ARI Es timate of Sh i p m e n t s ( 2 005 ) % S h ip m e nt s b y Pr od uc t C l as s ( 2 0 05)

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 desc ription of commercial refrig eration 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 de finition of the different commer cial 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 diffe rent purchase decisions and, in the following section, provides a description of th e 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 sale s 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 ov er the estimated life of the equipment. Sales in each year are allocated to the 15 equipment classes in propo rtion to their relative historical sales.

10.2.1 Mathematical Formulation of the Shipments Model

DOE uses two commercial refrigeration eq uipment stock categories. The category U

0 (t,a) is the stock of existing units. Available information suggests that all units are assumed to have had normal repairs that do not a ffect the lifetime of the equipment.

In view of industry practice, available information suggests th at 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 suggest s that the initial existing stoc k 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

10-1U (t,a) = U 0 (t,a) Eq. 10.1

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

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

where:

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

0 ( 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., exis ting 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 co mmercial refrigeration equipment of age a from stock U 0 will break or will be repl aced using a Weibull surv ival distribution function PB 0 (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 lifetim e of about 13 years, consistent with industry comments). PB 0 (a)=W(8,16) for small food service outlets, i.e ., convenience stores with and without gas stations (which result s in an average lifetime of 15 years, with a minimum of about 9 years and a maximum of about 20 years, again c onsistent 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 . DOE defines the quantities of replaced equipment as

UB (t, a) = PB 0 (a) x UB 0 (t,a) Eq. 10.3

where:

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

10-2PB 0 ( a ) = probability that stock of existi ng units will break, or will be replaced, U

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

a = age of stock,

t = year.
All broken or obsolete units (removed duri ng 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 sugg ests 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 existi ng 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 A 0 x NFS (t)/ NFS (0) Eq. 10.5

where:

UN(t) = the number of units going into new buildings in year t, A 0 = an overall scale factor that accounts fo r the number of units covered by the standard, which are not used in all comme rcial building types; the default value for A 0 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 sh ipments 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 equi pment categorization and provide

10-3only an estimate of shipments based on valuatio n 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 s ubstantial variation in shipment valuations between the survey years, in dicative of large variations in overall shipments of commercial refrigeration equipment by y ear. 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 sa les 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 th e shipment analysis. The ARI shipment ranges and equipment categories are defined in a way th at allowed DOE to disaggregate the data into the 15 equipment classes of interest. For the pur pose 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 a ny 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 commercia l refrigeration equipment for use in the Shipments Model. This established the commercial refrigeration equipm ent 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 th e overall linear footage shipped for all commercial refrigeration equipmen t covered in this rulemaking.

Table 10.3.1 summarizes DOE’s estimated division of historical annual shipments into the new, replacement, and large food sa les versus small food sales.

10-4Table 10.3.2 shows the forecasted square foot age 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

10-1Table 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 fo r each of 15 smaller equipment classes, based on 10 possible equipm ent families, two possible equipment operating modes (remote condensing or self-c ontained), and three rated temp erature 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 e quipment class. The premises below include data for some CRE equipment classe s, 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 Class a Assumed Length (ft) Basis VOP.RC.M 10 Avera g e of 8 ft and 12 ft

, Manufacture r Interviews VOP.RC.L 10 Avera g e of 8 ft and 12 ft

, Manufacture r Interviews VOP.SC.M 4 Baseline E q ui p men t used for En g ineerin g Anal y sis SVO.RC.M 10 Avera g e of 8 ft and 12 ft

, Manufacture r Interviews SVO.SC.M 4 Baseline E q ui p men t Used for En g ineerin g Anal y sis HZO.RC.M 10 Avera g e of 8 ft and 12 ft

, Manufacture r Interviews HZO.RC.L 10 Avera g e of 8 ft and 12 ft

, Manufacture r Interviews HZO.SC.M 4 Baseline E q ui p men t Used for En g ineerin g Anal y sis HZO.SC.L 4 Baseline E q ui p men t Used for En g ineerin g Anal y sis VCT.RC.M 10 Avera g e of 3 door and 5 door ( 30" p er door ), MFG Interviews VCT.RC.L 10 Avera g e of 3 door and 5 door ( 30" p er door ), MFG Interviews VCT.SC.I 5 Baseline E q ui p men t Used for En g ineerin g Anal y sis VCS.RC.M 5 En g ineerin g Esti m ate VCS.RC.L 5 En g ineerin g Estimate VCS.RC.I 5 En g ineerin g Estimate VCS.SC.I 5 Baseline E q ui p men t Used for En g ineerin g Anal y sis HCT.RC.M 5 En g ineerin g Estimate HCT.RC.L 5 En g ineerin g Estimate HCT.RC.I 5 En g ineerin g Estimate HCT.SC.I 3.4 Baseline E q ui p men t Used for En g ineerin g Anal y sis HCS.RC.M 5 En g ineerin g Estimate SOC.RC.M 8 Avera g e of 4 ft

, 8ft

, 12 ft

, all common e q ui p men t len g ths SOC.RC.L 8 Avera g e of 4 ft

, 8ft

, 12 ft all common e q ui p men t len g ths

* 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, VC S=vertical solid doors, HCT=horizontal tran sparent doors, HCS=horizontal solid doors, or SOC=se rvice over counter), an opera ting mode code (RC=remote condensing or SC=self-conta ined), and a rating temperature code (M=medium temperature (38°F), L=low temp erature (0°F), or I=ice-cream temperature (-15°F)). For exam ple, "VOP.RC.M refers to the "vertical open, remo te condensing, medium temperature" equipmen t class. See chapter 3, market and tech nology assessment, for a more detailed explana tion of the equipment class terminology

10-2design 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 analyz ed 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 sh ipped 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 footag e 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 th e basic inputs into the Shipments Model. As discussed in section 10.2.2, the m odel divides commercial display space into two components: display space from new construction floor space (N FS), and existing display floor space (EFS).

For this analysis, commercial square footag e 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.Remo te Condensing.Medium (VCT.RC.M) 1.9 Vertical Closed Transparent.Re mote Condensing.Low (VCT.RC.L) 25.7 Vertical Closed Transparent.Self Contained. Ice Cream (VCT.SC.I) 0.6 Vertical Closed Solid.Self Co ntained.Very Low (VCS.SC.I) 0.2 Semi-Vertical Open.Remote Co ndensing.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 Cont ained.Medium (HZO.SC.M) 0.2 Horizontal Open.Self Co ntained.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 N FS data by linear interp olation of the existing years. Beyond 2030, DOE extrapolated NFS from the 10-year trend of NEMS projected data between 2020 and 2030.

10-3The 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 displa y 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 replacem ent 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 ec onomic 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 avai lable 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 sh ares for the Shipments Model and are discussed below.

10.3.5 Equipment Price

Equipment price is the price paid by the cu stomer for a unit of co mmercial refrigeration equipment. It includes both the purchase pri ce of the equipment and in stallation costs. DOE converts the equipment price to a price per linear-foot-cooled base d on the length of the equipment class.

As discussed in the engineering analysis (cha pter 5) and the life-cycle cost and payback period analysis (chapter 8), e quipment prices in this analys is are a function of energy consumption level). DOE based equipment pric e 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., th e case without new energy conservation standards)

10-4and 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 co sts, repair costs, and energy costs.

Maintenance and Repair Costs. Each unit of commercial refrigeration equipment incurs yearly routine maintenance and standard repair co sts. DOE converted these costs to a cost per unit and per linear foot of coo ling 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 $156/year/ un it (2007$) for basic maintenance from R S Means Cost Works , to which is added a figure for lighting main tenance, 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 refriger ation 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 th e unit (energy use intensity or EUI), and the price of electricit y. The determination of the EU I for an individual CRE unit is discussed in chapters 6 and 7, a nd the development of electricity prices is discussed in the life-cycle cost and payback peri od analysis (chapter 8, secti on 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 EU I 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 sh ipped equipment and the Shipments Model uses the shipment-weighted average efficiency for th at 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 equi pment class, and future electricity prices. DOE developed a mix of energy consumption levels repr esentative of the base case (i.e., the case without new efficiency standards) and for each candi date 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 imp act of the mix of energy consumption levels on the average per unit energy costs for shipments within an equi pment 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 fa ctor in the impact of future electricity prices, DOE used el ectricity price projections from the AEO 2008 to appropriately scale the above proj ected energy costs (for scaling purposes, the scaling factor for the year 2007 equals 1.0).

10-510.3.5.2 Discounted Costs

When a decision is made to purchase co mmercial 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 presen t value of these costs. DOE discounted the total operating cost s (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 valu e is 10 years in large food retailers and 15 years in small retailers, usua lly based on the fact th at large grocery stores are either renovated or the refrigeration equipmen t is replaced for aesthetic reasons at about 10-year intervals, but th at small food retailers us ually 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 refri geration 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.

10-6Table 10.4.2 shows total shipments by equipment type.

Table 10.4.1 Forecasted Shipments of New an d Replacement Commercial Refrigeration Equipment for Large and Small Food Sales Outlets, 2012-2042 (Base Case)

Division 2012 Thousands of Linear Feet Shippe d 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

10-7Table 10.4.2 Forecasted Shipments for Commerc ial Refrigeration Equipment, 2012-2042, Level 1 (Base Case)

Equipment Class Thousands of Linear Feet Shippe d 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 ba se case. Although there is a provision in the spreadsheet for a change in shipments as the e fficiency level increases (or energy consumption level decreases), DOE has no information with whic h to calibrate such a relationship. Therefore, for the NOPR analysis, DOE presumes that the sh ipments do not change in response to candidate standard levels.

10-8REFERENCES

1. Freedonia. 2004. Commerci al Refrigeration Equipment to 2008. Study 1849. Freedonia Group, Inc, Cleveland, Ohio, Oct ober 2004, 204 pp. available at http://www.freedoniagroup.com/Commerc ial-Refrigeration-Equipment.html

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

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

10-9