CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CO NTENTS

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

9.2 METHODOLOGY .......................................................................................................... 9-1

9.3 DATA INPUTS AND MODEL DEV ELOPMENT ........................................................ 9-3

9.3.1 Historical Shipments ............................................................................................ 9-3

9.3.2 Markets ................................................................................................................ 9-7

9.3.2.1 New Co nstruction .............................................................................. 9-8

9.3.2.2 Replacements ................................................................................... 9-14

9.4 BASE

- CASE SHIPMENTS .......................................................................................... 9-14

9.5 STANDARDS CASE SHIPM ENTS ............................................................................. 9-17

LIST OF TABLES

Table 9.3.1 Historical Shipment Data .......................................................................................... 9-4

Table 9.3.2 MBI Data and DOE Estimates Used to Produce Historical Shipments .................... 9-5

Table 9.3.3 Historical SPVU Shipments...................................................................................... 9-7

Table 9.3.4 2005 New Construction Shipments (Units) .............................................................. 9-8

Table 9.3.5 Historical and Projected New Construction (million sf) .......................................... 9-9

Table 9.3.6 Saturation of SPVUs in New Construction Floor Space ........................................ 9-10

Table 9.3.7 Historical and Projected Telecom Establishments .................................................. 9-13

Table 9.3.8 Equipment Clas s Shipment Distribution

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

Table 9.4.1 Projected SPVU Shipments (Units) ........................................................................ 9-16

LIST OF FIGURE S

Figure 9.3.1 MBI Trend Used to Develop Floor Space Production ............................................ 9-6

Figure 9.3.2 County Business Pattern Establishment Data for NAICS 237130 Power and

Communication Line and Related Structures Construction ............................... 9-12

Figure 9.3.3 Survival Function .................................................................................................. 9-14

Figure 9.4.1 Projected Shipments by Equipment Class ............................................................. 9-15

Figure 9.4.2 Projected SPVU Shipments ................................................................................... 9-17

9-iCHAPTER 9. SHIPMENTS ANALYSIS

9.1 INTRODUCTION

The U.S. Department of Energy (DOE) analyzes shipments of affected equipment as part

of every rulemaking regarding new or amended energy efficiency standards for appliances or commercial and industrial equipment. Estimates of equipmen t shipments are a necessary input

for calculati ng national energy savings (NES) and net present value (NPV) of the investment,

which are required to justify potential new or amended energy efficiency standards . Shipments

also are a necessary input to t he manufacturer impact analysis

. This chapter describes DOE’s

method and results of projecting annual shipments for SPVUs

.

DOE used a computer model to predict shipments of SPVUs

. In estimating shipments,

the model considers specific market segments, the results for which are then aggregated to

estimate total SPVU shipments. DOE accounted for two market segments: (1) shipments to new

construction; and (2) replacement shipments going into existing building s.

The shipments models are prepared as Microsoft Excel spreadsheets that are accessible

on the Internet ( www.eere.energy.gov/buildings/appliance_standards/ ). The rest of this chapter

explains the shipments model in more detail. Section 9.2 describes the methodology that

underlies development of the model ; section 9. 3 descr ibes the data inputs and model

development ; section 9. 4 discusses the base

- case shipments ; and section 9.5 discusses the

standar ds- case shipments

.

9.2 METHODOLOGY

DOE developed a model of the national stock of in

- service SPVUs for estimating annual

shipments for this standards rulemaking. The model considers market segment s as distinct inputs

to the shipments projection . As represent ed by the following equation, the two primary market

segments are new installations and replacements.



### )()()( jNIjRpljShip

spvu spvu spvu 

### + =

Where:

Ship

spvu (j) = t otal shipments of SPVUs in year j

, Rpl

spvu (j) = SPVUs retired and replaced in year j , and

NI

spvu (j) = number of new installations of SPVUs in year j

.

9-1DOE’s shipments model takes an accounting approach, tracking the vintage of units in

the existing stock and expected construction trends. Rather than simply extrapolating a current

shipments trend, the analysis of the base case for each equipment class (i.e., the case without new

standards) uses input variables as drivers , including construction forecasts and equipmen t

lifetime distributions, to project sales in each market segment

.

To estimate shipments of replacement units, the model utilize s shipments data from

previous years and assumptions about the lifetime of each product. Estimated shipments of

replacement units in a given year are equal to the total stock of the equipment minus those uni ts

shipped in previous years that remain in the stock. DOE determined the useful service life of

each equipment class to estimate how many years it is likely to remain in stock. The following

equation shows how DOE estimated shipments of replacement units.



### )( )1( )( 

# ∑ ∑

0 1

__ _ 

### ageprob Ship jStockjRpl

Rtr ageMax

age j

Nj j spvu spvu 

### × =

= =

Where:

Stock

spvu (j -1) = total stock of SPVUs in year j-1

, prob Rtr (age) = probability that a unit of a particular age will be retired, and

N = year in which the model begins its stock accounting.

Stock accounting provides an estimate of the age distribution of equipment stocks for all

years, using equipmen t shipments, a retirement function, and initial equipment stock as inputs.

The age distribution of equipment stocks is a key input to both the NE S and NPV calculations

because the operating costs for any year depend on the age distribution of the stock. Operating

cost is dependent on the equipment age distribution under a standards case scenario that produces

increasing efficiency over time, where older, less efficient units may have higher operating costs,

while younger, more- efficient units will have lower operating costs. As units are added to the inservice stock, some older ones are retired and exit the stock.

DOE calculated total stock of each equipment class by integrating historical shipments

data beginning with a specific year. The start year depended on the historical data available for

the equipment. To estimate future shipments, DOE developed a series of equations that define

the dynami cs and accounting of stocks. For new units, the equation is:



### )1()1,(

_ 

### jShip agejStock

==

Where:

Stock(j, age) = number of units of a particular age,

j = year for which the stock is being estimated, and

Ship (j) = number of units purchased in year j

.

9-2The above equation states that the number of one- year -old units is simply equal to the

number of new units purchased the previous year. Slightly more complicated equations, such as

the following equation, describe how the model accounts for the existing stock of units.



# [ ] )(1),()1,1(

_ 

### ageprob agejStock agejStock

Rtr 

### × =++

In this equation, as the year is incremented from j to j+1 , the age is also incremented

from age to age+1 . Over time, a fraction of the stock is removed; that fraction is determined by a

retirement probability function, prob Rtr (age) , which is described in chapter 8

.

9.3 DATA INPUTS AND MODEL DEVELOPMENT

As noted above, shipments are driven primarily by the two market segments of new construction and replacements. DOE used two approaches to estimate shipments driven by new

construction depending on the commercial building type. For shipments to the office and

education sectors, DOE combined new construction forec asts with a constant market saturation

of the equipment in new construction. For shipments to the telecom sector, DOE projected future

shipments based on an extrapolated and indexed growth trend in the telecom sector

. DOE

estimated replacements using an eq uipment retirement function that it developed based on

equipment lifetimes. The retirement function is described in detail in chapter 8.

DOE designed its shipments model for SPVUs by developing a single model for all

SPVACs and a single model for all SPVHPs. DOE then disaggregated the shipments into the

equipment classes within each broader category

.

9.3.1 H istorical Shipments

DOE used data on historical shipments and industry trends to develop initial stock for the

shipments model. It relied on two sources to establish historical shipments: (1) shipments data

AH RI provided to DOE for 2005 1 and (2) floor space production data from the Modular Building

Institute (MBI) for 1994 to 2005. 2

DOE began with historical shipments data for only one year, 2005, for four out of five

equipment classes modeled. DOE used a manufacturer- provided estimate of the market share for

units greater than 65,000 Btu/h (3%) to estimate the 2005 shipments for the fifth equipment

class. Table 9.3.1 shows these data. Note that DOE does not set different standards for the one

phase and three phase equipment, but they are disaggregated here owing to historical precedent

and difference in shipments.

9-3Table 9.3.1 Historical Shipment Data

Equipment Class 2005 Shipments

SPVAC <65,000 Btu/h 1 Phase 31,976

SPVAC <65,000 Btu/h 3 Phase 14,301

SPVHP <65,000 Btu/h 1 Phase 13,125

SPVHP <65,000 Btu/h 3 Phase 6,129

SPVAC ≥ 65 ,000 and < 135 ,000 Btu /h 1,966*

*Estimated based on 3% market share for this equipment class.

Source: AHRI (2006 TSD)

In order to develop historical shipments prior to 2005, DOE examined historical modular

building floor space production data and expanded the historical trend. Each step is described

below and shown in Table 9.3.2 :

• Produced Floor Space Reported t o MBI : The MBI reports show the produced floor

space as reported to MBI for 1994 to 2004. Only a fraction of the industry reports to

MBI.

• Total Produced Floor Space Estimated by MBI : The MBI reports show the estimated

total floor space produced by the enti re industry based on the fraction of

manufacturers reporting and the average floor space they report, for 1997 through

2005.

• Total Produced Floor Space Estimated by DOE :

o For 1994 to 1997, DOE used the produced floor space reported to MBI and

the average percent of industry reporting from 1997 to 2001 (16 %) to estimate

total floor space production.

o For 1981 to 1993, DOE extrapolated the trend derived from plotting estimates

of total floor space produced from 1994 to 2005. (See Figure 9.3.1 .)

• Floor Space Production Trend Index : DOE set 2005 estimated total floor space

production to 1.0, and indexed all the preceding estimates of total floor space

production.

DOE applied the index to the 2005 shipments data to construct historical shipments from

1981 to 2004 (see Table 9.3.3 ).

9-4Table 9.3.2 MBI D ata and DOE Estimates Used to Produce Historical Shipments

Year Produced Floor

Space R eported to

MBI (million s.f. ) Total Produced

Floor Space

Estimate by MBI

(million s.f. ) Total Produced

Floor Space

Estimated by DOE

(million s.f. ) Floor Space

Production Trend

Index

1981 18.8 0.21

1982 21.3 0.24

1983 23.8 0.27

1984 26.3 0.30

1985 28.8 0.32

1986 31.3 0.35

1987 33.8 0.38

1988 36.3 0.41

1989 38.8 0.44

1990 41.3 0.46

1991 43.8 0.49

1992 46.3 0.52

1993 48.8 0.55

1994 7.0 42.4 0.48

1995 8.8 53.4 0.60

1996 9.0 54.7 0.62

1997 12.4 49.5 0.56

1998 10.4 97.2 1.09

1999 9.7 58.1 0.65

2000 8.8 74.8 0.84

2001 12.4 67.5 0.76

2002 6.7 61.2 0.69

2003 4.3 54.8 0.62

2004 7.2 77.3 0.87

2005 89 1.00

Source: MBI; DOE estimates

9-5Figure 9.3.1 MBI Trend Used to Develop Floor Space Production y = 2.4964x

- 4926.6

R2 = 0.2948

0.0 20.0 40.0 60.0 80.0 100.0 120.0

1992 1994 1996 1998 2000 2002 2004 2006MBI Estimated New Floor Space Produced (million squarefeet)

Year

9-6Table 9.3.3 Historical SPVU Shipments

Year SPVAC <65 1

Phase SPVAC <65 3

Phase SPVHP <65 1

Phase SPVHP <65 3

Phase SPVAC 65

-

135

1981 6757 3022 2774 1295 415

1982 7654 3423 3142 1467 471

1983 8551 3824 3510 1639 526

1984 9448 4226 3878 1811 581

1985 10345 4627 4246 1983 636

1986 11242 5028 4614 2155 691

1987 12139 5429 4982 2327 746

1988 13036 5830 5351 2499 801

1989 13933 6231 5719 2671 857

1990 14829 6632 6087 2842 912

1991 15726 7033 6455 3014 967

1992 16623 7435 6823 3186 1022

1993 17520 7836 7191 3358 1077

1994 15248 6819 6259 2923 937

1995 19168 8573 7868 3674 1179

1996 19669 8797 8074 3770 1209

1997 17784 7954 7300 3409 1093

1998 34922 15619 14334 6694 2147

1999 20874 9336 8568 4001 1283

2000 26874 12019 11031 5151 1652

2001 24251 10846 9954 4648 1491

2002 21974 9828 9019 4212 1351

2003 19689 8806 8081 3774 1211

2004 27772 12421 11400 5323 1708

2005 31976 14301 13125 6129 1966

Note: 2005 data for equipment classes less than 65,000 Btu/h are from AHRI (2006 TSD).

9.3.2 Markets

As described in section 9.2, t he market for SPVUs comprises replacement units for

equipment that has been retired and units for new construction. Total SPVUs shipments are

represented by the following equation :



### )()()( j NI j Rpl j Ship

spvu spvu spvu 

### + =

The following sections discuss both the new construction and replacement markets in

further detail.

9-79.3.2.1 New Construction

SPVUs are shipped to three primary market sectors

– small office, education, and

telecom. DOE used two different approaches to project shipments; one for the office and

education sectors, and one for the telecom sector.

DOE allocated the 2005 new construction shipments a into market sectors based on

information provided by manufacturers regarding the overall market share of the office,

education, and telecom sectors . However, DOE assumed that SPVHPs were not shipped to the

telecom industry, as t elecom structures would be unlikely to require heating. As a result, DOE

developed separate estimates of shipments to each industry sector for SPVACs and SPVHPs.

The overall percentage of SPVAC and SPVHP shipments (71% vs. 29%) is based on the 2005

AHRI shipment data. Table 9.3.4 shows the market shares and shipments breakdowns.

Table 9.3.4 2005 New Construction Shipments (Units)

Market Share New Construction Shipments

Small

Office Education Telecom Small

Office Education Telecom Total

SPVAC 71% 23% 27% 49% 5,64 5 6,586 11,891 24,122

SPVHP 29% 46% 54% 0% 4,443 5,184

- 9,627

Overall 100% 30% 35% 35% 10,088 11,770 11,891 33,749



### Office and Education

As described previously, to develop shipments to the office and education sectors, DOE

combined new construction forecasts with a constant market saturation of the equipment in new

construction. DOE reviewed the new construction forecasts for the small office and education

secto rs from the DOE Energy Information Administration (EIA)’s Annual Energy Outlook 2013

( AEO20 13 ) for 2005 –2040. 3 Table 9.3.5 presents these forecast s. The data for 2041 through

2048 are based on an extrapolation of the trend from 2030 through 2040.

a In 2012, manufacturers reported that shipments were approximately 50% new construction and 50% replacement.

DOE originally adjusted that split for 2005 until the result from the shipments model was 50 /50 in 2012. This

resulting 2005 split was 84% new construction and 16% replacement. However, this led to a steep shipments

increase in the model from 2005 to 2006. Instead, DOE used the 50/50 split directly in 2005, which resulted in a

much steadier shipm ents trend. Therefore 2005 new construction shipments are derived using 50% of the total 2005

historical shipments.

9-8Table 9.3.5 Historical and Projected New Construction (million sf)

Year Small Office Education Year Small Office Education

2005 144.70 350.81 2027 171.67 169.44

2006 159.03 355.67 2028 158.09 174.50

2007 167.22 374.33 2029 148.11 181.98

2008 173.25 359.43 2030 144.31 190.54

2009 165.77 352.15 2031 147.58 199.24

2010 116.60 336.50 2032 158.30 207.96

2011 97.38 277.00 2033 173.52 214.79

2012 107.54 270.11 2034 191.96 222.27

2013 96.56 247.20 2035 209.82 228.13

2014 110.20 232.60 2036 224.04 234.03

2015 135.69 222.37 2037 229.34 238.76

2016 166.40 215.84 2038 226.91 243.11

2017 189.67 211.66 2039 218.88 247.80

2018 207.90 208.30 2040 207.37 252.34

2019 221.59 204.19 2041 215.03 259.53

2020 227.85 197.01 2042 222.97 266.92

2021 230.20 189.76 2043 231.20 274.53

2022 226.08 183.01 2044 239.74 282.35

2023 218.86 176.27 2045 248.59 290.39

2024 210.09 172.40 204 6 257.77 298.67

2025 198.82 169.16 2047 267.28 307.18

202 6 185.15 167.53 204 8 277.15 315.93

Source: AEO 2013; data for 2041-2048 are extrapolated.

Table 9.3.6 shows the saturation of SPVUs in new construction, derived by dividing the

2005 new construction shipments by the 2005 new construction floor space. DOE then applied

the saturation to the new construction forecasts starting in 2006 to create projections of

shipments through 2048.

9-9Table 9.3.6 Saturation of SPVUs in New Construction Floor Space

SPVAC SPVHP

Small Office Education Small Office Education

2005 New Construction

Shipments (units) 5,645 6,586 4,443 5,184

2005 New Construction

Floor Space (million sf) 144.7 350.8 144.7 350.8

Saturation (units per

million sf) 39.0 18.8 30.7 14.8

In response to the April 2014 NODA, AHRI and Lennox International suggested that the

SPVU projected shipment trend was “optimistic” and did not reflect the economic downturn.

(AHRI, No. 24 at p. 6; Lennox International Inc., No. 15 at p. 7) After reviewing the available

AEO data, DOE examined literatu re related to the modular building industry to better understand

whether new construction trends for the overall small office and education sectors would be

applicable for the modular building industry. While comprehensive modular building industry

informa tion is not available, data from the below 4

, 5 , shown in Table 9.3.7 and Table 9.3.8

, indicate s that new inventory of modular buildings seems to have dropped more precipitously

than the total new construction shown in AEO. In addition, 2005, the year for which we have

actual shipments data, was a peak year for utilization 5 , and dealers have been pruning old units

from their fleets in order ot improve utilizat ion. 6 The estimated utiliziation for 2011 only slightly

improved, to around 63%, and nearly 64% for the first quarter of 2012. 5 In 2013, many

companies indicated they were making minimal to no equipment additions. 6 Furthermore, there

has been a movement from temporary to permanent modular construction that is lower cost and

quick to install compared to traditional permanent building. 7

Table 9.3.7 Dealer Fleet Composition and Utilization Rates

Relocatable Classroom Mobile Office

Unit Count Change

from

previous

year Utilization Unit Count Change

from

previous

year Utilization

2004 30,286 N/A 84% 41,548 N/A 78%

2005 31,356 1,070 84% 42,117 709 83%

2006 30,964 (392) 78% 45,111 (2,002) 83%

2007 28,951 (2,013) 79% 51,412 (1,474) 83%

2008 35,811 6,860 71% 64,013 2,758 76%

2009 32,981 (2,830) 71% 61,576 (2,234) 74%

2010 30,087 (2,894) 57% 58,589 (6,083) 61%

Source: Modular Building Institute Relocatable Buildings 2012 Annual Report

9-10Table 9.3.8 Selected State/Regional Labels Issued by Year

Maryland Industrialized

Building

Commission

(NJ, RI, MN,

ND) Texas Washington California

(HCD) Total

2005 2

, 636 3

, 603 4

, 390 1

, 311 4

, 643 16

, 583

2006 2

, 422 3

, 275 5

, 099 765 5

, 285 16

, 846

2007 2

, 739 3

, 210 5

, 745 1

, 121 4

, 025 16

, 840

2008 1

, 538 2

, 520 4

, 234 727 2

, 733 11

, 752

2009 602 867 2

, 136 N/A 1

, 749 5

, 354

2010 777 763 2

, 143 410 1

, 557 5

, 650

Notes: One label is issued for each module manufactured for use in the state.

Source: Modular Building Institute Relocatable Buildings 2011 Annual Report

All of this information generates uncertainty in the shipments estimates, but there are no

independent forecasts of modular building inventory. As a result, DOE decided to hold

shipments to new office construction constant at 2005 levels, which may have been a peak ye ar as indicated by the high utiliziation rate. DOE does not believe that the increasing trend in AEO

for the small office sector adequately represents the modular building industry. The future trend

may in fact be declining rather than constant, but DOE does not have quantitative data to support

this for offices. On the other hand, the AEO trend for the education sector shows an overall

decline through 2040. DOE has decided to use this trend for shipments to new construction in the

education sector.



### Telecom

For the telecom industry, DOE used County Business Pattern data on total establishments

from 2003 to 2011 8 to develop a trend (see Figure 9.3.2 ) that it extrapolat ed through 2048 . DOE

then indexed the total establishments to 2005 (see Table 9.3.9 ), and used this index to project

new construction telecom shipments based on shipments to telecom in 2005. DOE did not see

any information regarding the modular building industry that allowed it to assess this sector

separately.

9-11Figure 9.3.2 County Business Pattern Establishment Data for NAICS 237130 Power and

Communication Line and Related Structures Construction y = 46.117x

- 86961

R2 = 0.5435

5000 5200 5400 5600 5800 6000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012Total Establishments

Year 

## County Business Pattern NAICS 237130 Power

and Communication Line and Related Structures

Construction

9-12Table 9.3.9 Historical and Projected Telecom Establishments

Year Total Telecom

Establishments INDEX Year Total Telecom

Establishments INDEX

2005 5527 1.0 0 2027 6517 1.18

2006 5750 1.04 2028 6563 1.19

2007 5729 1.04 2029 6609 1.20

2008 5629 1.02 2030 6655 1.20

2009 5853 1.06 2031 6702 1.21

2010 5621 1.02 2032 6748 1.22

2011 5732 1.04 2033 6794 1.23

2012 5825 1.05 2034 6840 1.24

2013 5871 1.06 2035 6886 1.25

2014 5918 1.07 2036 6932 1.25

2015 5964 1.08 2037 6978 1.26

2016 6010 1.09 2038 7024 1.27

2017 6056 1.10 2039 7071 1.28

2018 6102 1.10 2040 7117 1.29

2019 6148 1.11 2041 7163 1.30

2020 6194 1.12 2042 7209 1.30

2021 6240 1.13 2043 7255 1.31

2022 6287 1.14 2044 7301 1.32

2023 6333 1.15 2045 7347 1.33

2024 6379 1.15 2046 7393 1.34

2025 6425 1.16 2047 7439 1.35

2026 6471 1.17 2048 7486 1.35

Note: All establishments starting in 2012 are estimated based on the trend from 2003-2011.



### Overall

DOE totaled shipments for SPVACs for each year (office, education, and telecom) and

distributed them into the individual equipment classes using the 2005 split. DOE did the same for

SPVHPs (office and education only). Table 9.3. 10 shows the splits.

Table 9.3.10 Equipment Class Shipment Distribution

SPVAC SPVHP

SPVAC <65

1 Phase SPVAC <65

3 Phase SPVAC 65

-

135 SPVHP <65 1

Phase SPVHP <65 3

Phase

2005

Shipments 31

, 976 14

, 301 1

, 966 13

, 125 6

, 129

Percent 66% 30% 4% 68% 32%

9-139.3.2.2 Replacements

To determine shipments to the replacement market , DOE used an accounting method that

tracks the total stock of units by vintage. DOE estimated a stock of SPVUs by vintage by

integrating estimated historical shipments starting from 1981 . Over time, some units are retired

and removed from the stock, triggering the shipment of a replacement unit. Depending on the

vintage, a certain percentage of unit s will fail and need to be replaced. To estimat e how long a

unit will function before fail ing, DOE used a survival function based on the distributions of

equipment lifetime . The survival function that DOE used had an average lifetime of 15 years. For a more complete discussion of SPVU lifetimes, refer to section 8.2.3 of chapter 8. Figure

9.3.3 shows the survival function DOE used to estimate replacement shipments.

Figure 9.3.3 Survival Function

9.4 BASE

- CASE SHIPMENTS

Figure 9.4.1 shows the projected shipments of SPVUs in the base case ( i.e. , the case

without new energy efficiency standards) and the historical shipments DOE used to develop the

initial stock that drove the replacement shipment projection. Table 9.4.1 shows the actual

shipments starting in 2006. Figure 9.4.2 shows total shipments (aggregated from individual 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0 5 10 15 20 25 30 35 40 45 50SPVU

Years % Surviving

% Retiring

9-14equipment classes) broken into new construction and replacement shipments. This figure starts in

2005, as historical shipments are not disaggregated into new construction and replacements.

Figure 9.4.1 Projected Shipments by Equipment Class

9-15Table 9.4.1 Projected SPVU Shipments (Units)

Year SPVAC <65 1

Phase SPVAC <65 3

Phase SPVHP <65 1

Phase SPVHP <65 3

Phase SPVAC 65

- 135

2006 31,677 14,167 12,910 6,029 1,948

2007 32,703 14,626 13,409 6,262 2,011

2008 33,117 14,811 13,518 6,312 2,036

2009 34,415 15,392 14,073 6,572 2,116

2010 35,591 15,918 14,482 6,763 2,188

2011 36,460 16,307 14,479 6,761 2,242

2012 37,729 16,874 14,911 6,963 2,319

2013 38,288 17,124 15,000 7,004 2,354

2014 38,389 17,169 14,942 6,977 2,360

2015 38,593 17,260 14,948 6,980 2,373

2016 39,222 17,541 15,146 7,073 2,411

2017 40,208 17,983 15,498 7,237 2,472

2018 41,476 18,550 15,969 7,457 2,550

2019 42,865 19,171 16,484 7,697 2,635

2020 44,258 19,794 16,984 7,931 2,721

2021 45,621 20,403 17,468 8,157 2,805

2022 46,911 20,980 17,901 8,359 2,884

2023 48,128 21,525 18,279 8,536 2,959

2024 49,284 22,042 18,623 8,696 3,030

2025 50,328 22,509 18,907 8,829 3,094

2026 51,245 22,919 19,136 8,936 3,151

2027 52,087 23,296 19,353 9,036 3,202

2028 52,902 23,660 19,578 9,142 3,252

2029 53,748 24,038 19,838 9,263 3,305

2030 54,665 24,448 20,144 9,407 3,361

2031 55,687 24,906 20,502 9,574 3,424

2032 56,828 25,416 20,915 9,767 3,494

2033 58,052 25,964 21,353 9,972 3,569

2034 59,366 26,551 21,830 10,194 3,650

2035 60,710 27,152 22,302 10,414 3,732

2036 62,068 27,759 22,771 10,633 3,816

2037 63,393 28,352 23,210 10,838 3,898

2038 64,667 28,922 23,616 11,028 3,976

2039 65,888 29,468 23,994 11,204 4,051

2040 67,044 29,984 24,344 11,367 4,122

2041 68,182 30,494 24,702 11,535 4,192

2042 69,292 30,990 25,058 11,701 4,260

2043 70,399 31,486 25,422 11,872 4,328

2044 71,531 31,992 25,808 12,051 4,398

2045 72,710 32,519 26,222 12,245 4,470

2046 73,949 33,073 26,668 12,453 4,547

2047 75,253 33,657 27,145 12,676 4,626

9-16Year SPVAC <65 1

Phase SPVAC <65 3

Phase SPVHP <65 1

Phase SPVHP <65 3

Phase SPVAC 65

- 135

2048 76,616 34,266 27,646 12,909 4,710

Figure 9.4.2 Projected SPVU Shipments

9.5 STANDARDS CASE SHIPMENTS

As equipment purchase price and repair costs increase with efficiency, higher first costs

and repair costs can result in a drop in shipments. In manufacturer interviews, manufacturers

expressed concern that an increase in first cost could lead customers to switch to split- system or

rooftop units. However, manufacturers did not provide any information on the cost at which this

switch might occur , and DOE had no basis for estimating the elasticity of shipments for SPVUs

as a function of first costs, repair costs, or operating costs. In addition, DOE notes that SPVUs

serve a specific niche market and that a switch from SPVUs to another type of equ ipment would

require significant changes in the market such as installation on site rather than at the modular

building manufacturer, the use of a mechanical contractor with their markups, and potential

changes to needed ductwork and other infrastructure. Therefore, DOE assumed that the

shipments projection does not change under the considered standard levels. 0 20000 40000 60000 80000 100000 120000 140000 160000 180000

2005 2010 2015 2020 2025 2030 2035 2040 2045Total Units Shipped

Year

New Construction Replacements

9-17REFERENCES

1. U.S. Department of Energy, Technical Support Document: Energy Efficiency Program

for Commercial and Industrial Equipment: Efficiency Standards for Commercial

Heating, Air-Conditioning, and Water Heating Equipment Including Packaged Terminal

Air -Conditioners and Packaged Terminal Heat Pumps, Small Commercial Packaged

Boiler, Three- Phase Air -Conditioners and Heat Pumps <65,000 Btu/h, and SinglePackage Vertical Air Conditioners and Single-Package Vertical Heat Pumps < 65,000

Btu/h , March 2006. Washington, DC.

2. Modular Building Institute. Commercial Modular Construction Reports

. http://www.modular.org/HtmlPage.aspx?name=analysis

3. U.S. Department of Energy/Energy Information Administration. 2013. Annual Energy

Outlook 2013. DOE/EIA0383(2013), DOE/EIA, Washington, D.C.

4. Modular Building Institute. Relocatable Buildings: 2011 Annual Report.

http://www.modular.org/documents/document_publication/2011relocatable.pdf

5. Modular Building Institute. Relocatable Buildings: 2012 Annual Report.

http://www.modular.org/documents/2012- RB -Annual-Report.pdf

6. Gaudosi, Bob. Five Reasons to Lend to the Mobile and Modular Sector Now. ABL

Advisor. 2013. http://www.abladvisor.com/articles/3102/five- reasons

- to -lend- to -themobile

- and -modular- sector -now

. Accessed April 14, 2014.

7. McGraw Hill Construction. Prefab rication and Modularization: Increasing Productivity

in the Construction Industry. 2011.

http://www.nist.gov/el/economics/upload/Prefabrication -Modularization- in -theConstruction-Industry- SMR -2011R.pdf

8. U.S. Census Bureau. County Business Patterns.

http://www.census.gov/econ/cbp/index.html

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