9

- i CHAPTER 9. SHIPMENTS ANALYSIS

TABLE OF CONTENTS

9.1 INTRODUCTION

................................ ................................ ................................ ........... 9

- 2

9.2 TOTAL SHIPMENTS

................................ ................................ ................................ ..... 9

- 3

9.2.1 Distribution across Equipment Class Groups

................................ ................................ .. 9

- 3

9.2.2 Distribution across Horsepower

................................ ................................ ....................... 9

- 3

9.2.3 Distribution across Pole Configurations and Enclosures

................................ ................. 9

- 4

9.2.4 Distribution across Equipment Classes, Sectors and Applications

................................ .. 9

- 5

9.3 SHIPMENTS PROJECTION

................................ ................................ .......................... 9

- 5

9.3.1 Shipments Model

................................ ................................ ................................ ............. 9

- 5

9.3.2 Shipments in Standards Cases

................................ ................................ ......................... 9

- 7

9.3.3 Shipments Data

................................ ................................ ................................ ................ 9

- 7

LIST OF TABLES

Table 9.2.1 Share of Motors by Equipment Class Group in Percent

................................ ...... 9

- 3

Table 9.2.2 Share of Motors by Horsepower Range

................................ ............................... 9

- 3

Table 9.2.3 Share of Motors by Horsepower Rating

................................ .............................. 9

- 4

Table 9.2.4 Share of Motors by Pole Configuration an d Enclosure (All Equipment Class Groups)

................................ ................................ ................................ ....... 9

- 5

Table 9.3.1 Annual and Cumulative Shipments Projection

................................ .................... 9

- 8

LIST OF FIGURE S

Figure 9.3.1 Shipments Index vs. Private Fixed Investment Index in Selected Equipment and Structure

................................ ................................ ...................... 9

- 6 Figure 9.3.2 Shipments Projection by Scenario Case

................................ ................................ 9

- 79

- 2 CHAPTER 9. SHIPMENTS ANALYSIS

9.1 INTRODUCTION

The U.S. Department of Energy (DOE) analyzes shipments of affected equipment as a part of its rulemakings about new or amended energy efficiency standards for equipment that impact national energy use. Estimates of shipments are a necessary input to calcul ating national energy savings (NES) and net present value (NPV) of the investment in more efficient equipment; both of these calculations are required to analyze the impact of proposed new or amended energy efficiency standards. Shipments also are a necess ary input to the manufacturer impact analysis (MIA), which DOE conducts to prepare its notice of proposed rulemaking (NOPR). The MIA estimates the impact of potential efficiency standards on manufacturers of the affected equipment, in this case electric mo tors, and assesses the direct impact of such standards on employment and manufacturing capacity. This chapter describes the method DOE used to project annual shipments for electric motors under base

- and standards

- case efficiency levels and

the results obt ained.

DOE developed a shipments model to predict shipments of electric motors covered in this analysis . The core of the shipments analysis is a model that DOE developed to simulate how future purchases are incorporated into an in

- service stock of aging motors that are gradually replaced. DOE’s motors shipments projections are based on forecasts of economic growth and do not incorporate a distinction within shipments between replacements and purchases for new applications.

To formulate its total shipmen ts estimates, DOE began with shipments data from a market research report 1 , input from interested parties, and responses to the Request for Information (RFI) published in the Federal Register (76 FR 17577 (March 30, 2011)). Based on

a database of motor field data 2 , U.S. C ensus Bureau’s Current Industrial Reports 3

, 4 , and stakeholder input, DOE then developed a distribution of shipments across each of the three equipment class group (NEMA Design A and B, NEMA Design C, and fire pump motors).

Within each ca tegory, motor shipments were split into several horsepower ratings, rotation speeds (corresponding to 2

- pole, 4

- pole, 6

- pole, and 8

- pole motors), and two enclosure types (open or enclosed) to arrive at shipments at the equipment class level.

The shipment s model is prepared as a Microsoft Excel spreadsheet that is accessible on the Internet ( http://www.eere.energy.gov/buildings/appliance_standards/ ). Appendix 10

- A

discusses how to ac cess the shipments model and other related spreadsheets and provides basic instructions for using them. The rest of this chapter explains the shipments model in more detail. Section 9.2 provides a summary of the data DOE used to develop estimates of the sh ipments of covered electric motors by equipment class and for each sector and applications. Section 9.3 describes the methodology that underlies development of the model and presents the shipments projection

.9

- 3 9.2 TOTAL SHIPMENTS

Based on a market research re port 1 and stakeholder input and responses to the RFI

, annual shipments of covered motors were estimated to total 4.56 million units in 20 11

.

DOE drew upon two data sources to develop a distribution of the total shipments across the 510 equipment classes: input from interested parties, and data from extensive field measurements collected by the Washington State University Extension Energy Progra m (WSU), Applied Proactive Technologies and the New York State Energy Research and Development Authority (NYSERDA) 2 (“WSU/NYSERDA database”).

9.2.1 Dis tribution across Equipment Class Groups

DOE derived the distribution by equipment class group from the WSU/NYSERDA database ( Table 9.2

. 1 ).

Table 9.2

. 1 Share of Motors by Equipment Class Group in Percent NEMA Design A and B NEMA Design C Fire Pump

99. 68 0.2 0 0.1 2

9.2.2 Distribution across Horsepower

Shipments were first distributed by horsepower range, based on U.S. C ensus Bureau’s Current Industrial Reports 3 , 4 and input from interested parties ( Table 9.2

. 2 ).

Table 9.2

. 2 Share of Motors by Horsepower Range

Range hp 2011 Shipments ( 1,000 ) Percentage of Total ( % )

1

– 5 2,668 58. 5 %

6

– 20 1,368 30. 0 %

21

– 50 342 7. 5 %

51

– 100 114 2.5%

101

– 200 46 1

. 0 %

201

– 500 23 0. 5 %

Total 4,560 100.0%

DOE then split shipments by individual horsepower rating, based on the distribution observed in the WSU/NYSERDA database ( Table 9.2

. 3 ).9

- 4 Table 9.2

. 3 Share of Motors by Horsepower R ating Horsepower rating

hp Percentage of

Total

( % )

1 6.2%

1.5 5.6%

2 10.2%

3 14.5%

5 22.1%

7.5 9.1%

10 8.2%

15 8.1%

20 4.5%

25 2.1%

30 2.0%

40 2.1%

50 1.3%

60 0.8%

75 0.9%

100 0.8%

125 0.4%

150 0.4%

200 0.3%

250 0.3%

300 0.1%

350 0.04%

400 0.1%

450 0.02%

500 0.03%

9.2.3 Distribution across Pole Configurations and Enclosures

DOE derived the distribution by pole configuration and enclosure from the WSU/NYSERDA database ( Table 9.2

. 4 ).9

- 5 Table 9.2

. 4 Share of Motors by Pole Configuration and Enclosure (All Equipment Class Groups)

Enclosure Open Enclosed
Range hp 2 poles 4 poles 6 poles 8 poles 2 poles 4 poles 6 poles 8 poles

1

– 5 0.7% 8.1% 1.1% 0.1% 5.0% 19.6% 2.6% 1.4%

6

– 20 1.0% 6.2% 0.6% 0.1% 6.6% 17.0% 1.5% 0.2%

21

– 50 0.3% 2.3% 0.2% 0.1% 2.7% 8.1% 1.6% 0.1%

51

– 100 0.1% 0.9% 0.4% 0.1% 0.7% 4.1% 1.0% 0.1%

101

– 200 0.0% 0.4% 0.1% 0.1% 0.2% 2.3% 1.0% 0.2%

201

– 500 0.1% 0.1% 0.1% 0.1% 0.1% 0.4% 0.1% 0.1%

DOE then combined the distribution by horsepower and the share of motors by pole and enclosure configuration to estimate the shipment distribution per equipment class.

9.2.4 Distribution across Equipment Classes, Sectors and Applications

DOE used the data presented in Table 9.2

. 1

, Table 9.2

. 2

, Table 9.2

. 3 , and Table 9.2

. 4 to produce market shares for each of the 510 equipment classes. Further, DOE developed a model of the applications and sectors for which motors covered in this analysis are used . These distributions are presented in chapter 7, Energy Use Characterization

.

9.3 SHIPMENTS PROJECTION

9.3.1 Shipments Model

DOE projected shipments of covered motors throughout the 30

- year analysis period,

which stretches from 2015 (the effective date of the standard) to 2044. DOE projects total shipments using a model driven by forecasted economic growth. DOE assumed that motors sales are driven by economic growth and machinery production growth for equipment including

mot ors

.

Based on historical data for the period 1993

- 2011 on U

. S

. shipments provided by the U.S.

Census Bureau 3

, 5 and NEMA 6

, 7 and private fixed investment data from the Bureau of Economic Analysis’s (BEA) 8

, 9 , DOE assumes that annual shipments growth rate correlate to the annual growth rate of private fixed investment in selected equipment and structures 10

, a including motors ( Figure 9.3

. 1 ).

a Heating, ventilation, and air conditioning (HVAC) equipment which incorporates motors is typically included in “structures” and not in equipment. Based on RSMeans, DOE estimates that 9 percent of investments in structures are related to HVAC equipment.9

- 6 Figure 9.3

. 1 Shipments Index vs. Private Fixed Investment Index in Selected Equipment

and Structure

DOE developed a relationship betwee n shipments and private fixed investment in equipment and structures including motors (indexed to 2001). The relation, derived from a linear regression (R 2 =0. 9 1), is expressed by the following equation:

S h ipments index ( y ) = 1

. 15126

∙ FixInvest index ( y )

− 15

. 17265 Shipments index ( y ) =
1

. 15126

∙ FixInvest index ( y )

- 15

. 17265 [Equation 1 , Step 0]

Where:

S h ipments index ( y ) is the shipments index based in 2001 in year y , and

FixInvest index ( y ) is the private fixed investment index based in 2001 for selected equipment and structure including motors in year y

.

DOE projects private fixed investment in selected equipment and structure from 2015 through 20 35 based on the r eal “g ross d omestic p roduct ” (GDP) growth from the Energy Information Administration Annual Energy Outlook for 2011 ( AEO2011 ) for the period 2015

– 2035. DOE then extrapolat ed the GDP growth trend from 2035 to 2044. The steps for the

calculation are :

1) Based on historical data from the BEA, DOE project ed private fixed investment
in equipment and structure including motors as a share of total private fixed
investment in equipment and structure for 2015 to 2044.

2) For 2015 to 2035, DOE used total private fixed investment in equipment and
structures data ( private domestic investment data ) from AEO2011 to project
private fixed investment in equipment and structure including motors

. 0 20 40 60 80 100 120 140 160 180Index 2001=100

Shipments Index

Private Fixed Investment Index in Selected Equipment and Structure (PPI, 2001=100)9

- 7 3) From 2035 to 2044, DOE used AEO 2011 data to estimate a trend for private

domestic investment as a share of GDP using a linear regression (R 2 >0.99). DOE
then projected the GDP for 2035 to 20 44 using a quadratic regression based on

AEO 2011 data (R 2 >0.99). Using the GDP projection, DOE projected private

domestic investment and e stimated private fixed investment in equipment and
structure including motors

. 4) DOE used the data on project ed private fixed investment in equipment and
structure including motors and Equation 1 to estimate shipments growth over the
analysis period (2015

– 2044).

Following the same methodology, DOE estimated shipments projections for the Reference Economic Growth Case, the High Economic Growth Case, and Low Economic

Growth Case available in AEO 2011

.

9.3.2 Shipments in Standards Cases

Sales of electr ic motors may be sensitive to increases in the installed cost that may result from efficiency standards . Increased motor prices could affect the repair v ersus replace decision that the user makes and could lead to increasing the longevity of less efficient motors and decreased shipments. However, DOE did not find sufficient data to quantitatively estimate the impact of increased efficiency levels on shipments and therefore used a price elasticity equal to

zero as a default.

9.3.3 Shipments Data

Figure 9.3

. 2 shows the annual shipments for each scenario case between 2015 and 2044.

Figure 9.3

. 2 Shipments Pro jection by Scenario Case 0 5000 10000 15000 20000 25000Shipments (Unit: 1,000)

Reference Case Hight Growth Case Low Growth Case9

- 8 Table 9.3

. 1 shows the annual and cumulative shipments for each equipment class grouping for Reference Case

Table 9.3

. 1 Annual and Cumulative Shipments Projection Annual Shipments

thousand units

Equipment Class Grouping 2015 2025 2035 2044 Cumulative

2015

– 2044

NEMA Designs A & B 5,07 2 7,25 4 9,9 58 13,00 5 256,8 46

NEMA Design C 10 15 20 26 515

Fire Pump 6 9 1 2 1 6 309

Total* 5,089 7,278 9,990 13,047 257,671

*Total may not sum up because of rounding.

There are t wo major assumptions inherent in the shipments model:

1) The relative market shares of the different equipment classes are constant over

time.

2) U.S. production, imports, exports, and therefore shipments (i.e. apparent
consumption) have the same growth rate as described by the shipments index
provided by NEMA 6 , 7 (see section 9.3.1 ).9

- 9 REFERENCES

1 IMS Research (February 2012), The World Market for Low Voltage Motors

, 2012 Edition

, Austin.

2 Database of motor nameplate and field measurements compiled by the Washington State University Extension Energy Program (WSU) and Applied Pr oactive Technologies (APT) under contract with the New York State Energy Research and Development Authority (NYSERDA) . 2011.

3 U.S. Census Bureau (November 2004), Motors and G enerators

– 2003.MA335H(03)

- 1

. http://www.census.gov/manufacturing/cir/historical_data/discontinued/ma335h/index.html

4 U.S. Census Bureau (August 2003), Motors and Generators

– 2002.MA335H(02)

- 1 . at http://www.census.gov/manufacturing/cir/historical_data/discontinued/ma335h/ma335h02.xls

5 U.S. Census Bureau, Current Industrial Report: Manufacturing Profiles, 1994

- 1998.

6 NEMA ( 2007 ), Motor Shipments Slip in Third Quarter of 2007

, NEMA News, on 05 Dec

2007

.

7 NEMA ( 201 1 ), Motors Shipments on the Upswing in First Half of 2011

, NEMA News, on 18 Aug 201 1.

8 Bureau of Economic Analysis (March 01, 2012), Private Fixed Investment in Equipment and Software by Type

. http://ww w.bea.gov/iTable/iTable.cfm?ReqID=12&step=1

9 Bureau o f Economic Analysis (March 01, 2012), Private Fixed Investment in Structures by Type

. http://www.bea.gov/iTable/iTable.cfm?ReqID=12&step=1

10 RSMeans (2011), RSMeans Facilities Construc tion Cost Data 201 , Norwell.