REGULATORY IMPACT ANALYSIS FOR ENERGY 

CONSERVATION STANDARDS FOR 

DISTRIBUTION TRANSFORMERS 

July 2007 

U.S. Department of Energy 

Assistant Secretary 

Office of Energy Efficiency & Renewable Energy 

Building Technologies Program 

Appliances and Commercial Equipment Standards 

Washington, DC 20585 
REGULATORY IMPACT ANALYSIS FOR ENERGY 

CONSERVATION STANDARDS FOR ELECTRICAL DISTRIBUTION 

TRANSFORMERS 

TABLE OF CONTENTS 

1.0 INTRODUCTION .................................................. RIA-1


2.0 NON-REGULATORY POLICIES ..................................... RIA-2


2.1 Methodology	 ................................................ RIA-2


2.1.1 Modeling Method ....................................... RIA-2


2.1.2 Policy Assumptions ..................................... RIA-3


2.1.3 Policy Interactions ...................................... RIA-4


2.2 Non-Regulatory Policy Assumptions .............................. RIA-5


2.2.1 No New Regulatory Action ............................... RIA-5


2.2.2 Financial Incentives Policies .............................. RIA-5


2.2.3 Voluntary Energy-Efficiency Targets ...................... RIA-13


2.2.4 Early Replacement ..................................... RIA-14


2.2.5 Bulk Government Purchases ............................. RIA-14


2.3 Results Summary for Non-Regulatory Alternatives ................. RIA-15


APPENDIX RIA.A: 	USING IMPLEMENTATION CURVES TO ESTIMATE MARKET


PENETRATION OF NON-REGULATORY POLICIES ....... RIA-17


LIST OF TABLES 

........................................................... RIA-2


Table RIA.1 Policy Alternatives to Adopted National Distribution Transformer Standards


Table RIA.2 Adopted Standard Levels for Distribution Transformers ............... RIA-4


Table RIA.3 Benefit/Cost Ratios for Adopted Standard and Rebate Policy Cases ..... RIA-7


Table RIA.4 Market Share and Effective Market Share Increases for Consumer Rebates Policy


Case by Medium-Voltage, Dry-Type Product Class .................. RIA-9


Table RIA.5 Market Share and Effective Market Share Increases for Consumer Rebates Policy


Case by Liquid-Immersed Product Class ...................... RIA-10


Table RIA.6 Effective Market Share Increases for Consumer Tax Credits Policy Case by


Product Class ............................................... RIA-12


Table RIA.7 Effective Market Share Increases for Manufacturer Tax Credits Policy Case by


Product Class ............................................... RIA-13


RIA -i 
LIST OF FIGURES


Figure RIA.1 Market Penetration Curve for Design Line 13 of Medium-Voltage, Dry-Type


Transformers ................................................ RIA-8


Figure RIA.2 Market Penetration Curve for Design Line 1 of Liquid-Immersed 


Transformers ............................................... RIA-10


Figure RIA.A.1 Comparison of Exponential and Logistic Curves Showing External and Internal


Influences on Consumers ............................................ RIA-18


RIA -ii 
REGULATORY IMPACT ANALYSIS FOR ENERGY 

CONSERVATION STANDARDS FOR ELECTRICAL DISTRIBUTION 

TRANSFORMERS 

1.0 INTRODUCTION 

DOE of Energy (Department, or DOE) has determined that distribution transformer 

energy-efficiency standards constitute an “economically significant regulatory action” under 

Executive Order (E.O.) 12866 “Regulatory Planning and Review.” 58 FR 51735, October 4, 

1993. Therefore, the energy-efficiency standards require a regulatory impact analysis (RIA), 

which involves an evaluation of non-regulatory alternatives to the promulgated standards. This 

document evaluates several possible alternatives to the adopted standards, and compares the 

costs and benefits of each to the adopted standards. As described in section 2.0 of this report, the 

efficiency levels adopted by DOE are those in trial standard level (TSL) C for liquid-immersed 

distribution transformers and TSL 2 for medium-voltage, dry-type distribution transformers.a 

Under the Process Rule (Procedures, Interpretations and Policies for Consideration of 

New or Revised Energy Conservation Standards for Consumer Products, 10 CFR 430, Subpart 

C, Appendix A), DOE is committed to continually explore non-regulatory alternatives to 

standards. 62 FR 54817. DOE has prepared this regulatory analysis pursuant to E.O. 12866, 

which is subject to review under the Executive Order by the Office of Information and 

Regulatory Affairs (OIRA). 58 FR 51735. 

DOE identified six major, non-regulatory alternatives to standards as representing 

feasible policy options to achieve potentially similar improvements in distribution transformer 

energy efficiency. Table RIA.1 lists the six alternatives. DOE evaluated each of those 

alternatives that apply to the distribution transformers covered by this final rule in terms of its 

ability to achieve significant energy savings at a reasonable cost, and compared the effectiveness 

of each one to the effectiveness of the adopted standards. As discussed in section 2.2 below, 

DOE found that some of these policy alternatives would not have an impact on those 

transformers for which there are energy conservation standards and therefore did not analyze 

them further. 

a

 Because the Energy Policy Act of 2005 established energy conservation standards for low-voltage, dry-type 

distribu tion tran sform ers, D OE has rem ove d this type of transfo rmer from th e N OP R stag e of its ana lysis. 

RIA -1 
Table RIA.1 Policy Alternatives to Adopted National Distribution Transformer Standards 

No New Regulatory Action 

Consumer Rebates


Consumer Tax Credits


Manufacturer Tax Credits


Voluntary Energy-Efficiency Targets


Early Replacement


Bulk Government Purchases


2.0 NON-REGULATORY POLICIES 

2.1 Methodology 

This section describes the approach DOE used to analyze non-regulatory policies for the 

appropriate distribution transformer product classes. DOE assumed that each policy would apply 

to one or both of the two transformer types: liquid-immersed and medium-voltage, dry-type. 

2.1.1 Modeling Method 

To calculate the national energy savings (NES) and the net present value (NPV) 

corresponding to each policy alternative, DOE used the national impact analysis (NIA) 

Spreadsheet Model. (See Chapter 10 of the technical support document (TSD)1

 for a description 

of the NIA Spreadsheet Model.) To compare each alternative to the adopted standards, DOE 

quantified the effect of each alternative on the purchase of distribution transformers meeting 

efficiency levels equivalent to those in the adopted standards. This report refers to these levels as 

target levels. Once it had made the quantitative assumptions for each alternative, DOE made the 

appropriate revisions to the inputs in the NIA Spreadsheet Model. The main model inputs that 

DOE revised were the market shares of equipment at the target efficiencies. 

The shipments for any given year comprise a distribution of efficiency levels. DOE 

assumed that the adopted standards would affect 100 percent of the shipments, while the 

non-regulatory policies affect a smaller percentage of the shipments. In each policy case, DOE 

made particular assumptions about the percentage of shipments (market shares) impacted by the 

policy under analysis. In the base case and the policy case, the impacted shipments enter the 

stock each year. Using the estimates of transformer losses from the life-cycle cost analysis 

(Chapter 8 of the TSD), DOE calculated the annual total energy use by the stock of transformers. 

For each year analyzed, the difference in source energy use between the adopted standards case 

and the policy case is the annual energy savings. 

RIA -2 
A shift in market share to higher-efficiency transformers may increase the average 

installed cost of distribution transformers. Operating costs will generally decrease due to a 

decline in energy consumption. Therefore, DOE was able to calculate an NPV for non-regulatory 

alternatives in the same way as for the adopted standard. In some scenarios, total installed cost 

increases are partially mitigated by government rebates or tax credits. DOE assumed that credits 

and rebates would be paid for by consumers in another form (such as additional taxes), and 

therefore did not include them as a benefit for the purposes of calculating the national NPV. 

The key measures of the impact of each alternative are: 

•	 National energy savings in quadrillion British thermal units (quads): Cumulative national 

primary energy savings for equipment bought in the period from the effective date of the 

policy case (2010) to the year 2038. 

•	 Net present value: The value of net monetary savings from equipment bought in the 

period from the effective date of the policy case (2010) to the year 2038. DOE calculated 

the NPV as the difference between the present value of equipment and operating 

expenditures (including energy) in the base case, and the present value of expenditures in 

each alternative policy case. DOE calculated capacity and operating cost savings through 

the year 2073 for transformers purchased in the period 2010 to 2038.a 

2.1.2 Policy Assumptions 

The impacts of non-regulatory policies are by nature uncertain, since they depend on 

program implementation and marketing efforts and the subsequent consumer behavior response. 

The projected impacts depend on the assumptions about the consumer participation rate and are 

therefore subject to more uncertainties than the impacts of mandatory standards, which DOE 

assumed would have full compliance. To increase the robustness of the analysis, DOE 

conducted a literature review on each non-regulatory policy and consulted with key experts to 

gather information on similar incentive programs that have been implemented in the U.S. By 

studying field experience with sample programs of each type, DOE sought to make credible 

assumptions of their potential market impacts. Section 2.2 below reports the conclusions from 

this research as they apply to the policy modeling assumptions and includes the corresponding 

literature citations. 

Each of the policy alternatives to the adopted standards that DOE considered improves 

the average efficiency of new distribution transformers relative to the base case (no new 

regulatory action). The analysis considered that each alternative policy would induce consumers 

to purchase units at the target levels, the same efficiency levels as required by the adopted 

a

 DOE used the same time period for NPV in the RIA as it did for the NIA in the advance notice of proposed 

rulemaking. The longer period for operating cost savings allows the policy impact analysis to account for the 

operating cost savings benefits for equipment purchased through the year 2035. 

RIA -3 
standards. In contrast to the adopted standards, however, the penetration rate in the alternative 

policy cases may not be 100 percent. 

The adopted standards are TSL C for liquid-immersed transformers, and TSL 2 for 

medium-voltage dry-type transformers, as shown in Table RIA.2. Section II of the final rule 

shows the efficiency levels for the adopted standard levels by product class and kilovolt-ampere 

(kVA) size. 

The size of the eligible market for the policies varies among the product classes. Table 

RIA.2 shows the percentages of the distribution transformer market that DOE projects will be 

below the target levels in 2010 (in the column labeled “Percent Non-Compliant”). Therefore, 

policies that aim for the target level will impact the non-complying portion of the distribution 

transformer market for each product class. Non-regulatory policies would thus impact some 

fraction of these portions of the market. 

DOE assumed that the non-regulatory policy impacts last from the effective date for 

adopted distribution transformer standards, 2010, through the end of the analysis period, 2038. 

Table RIA.2 Adopted Standard Levels for Distribution Transformers 

Distribution Transformer Type TSL Percent Non-Compliant 

Liquid-Immersed C 69.3 

Medium Voltage, Dry-Type 2 47.9 

DOE did not consider administrative costs for any of the non-regulatory policies in its 

analysis. Inclusion of such costs would decrease their NPV by a small amount. 

2.1.3 Policy Interactions 

DOE calculated the impacts of each regulatory policy separately from those of the other 

policies. In actual practice, certain policies are often most effective when implemented in 

combination to provide incentives. DOE attempted to make conservative assumptions to avoid 

double-counting policy impacts. Therefore, the policy impacts reported below are not additive; 

the combined impact of several or all of the policies may not be inferred from adding the results 

together. 

Section 2.3 below presents the results of the analysis of the non-regulatory policies for 

distribution transformers. 

RIA -4 
2.2 Non-Regulatory Policy Assumptions 

2.2.1 No New Regulatory Action 

The case in which no new regulatory action is taken with regard to distribution transformer 

efficiency constitutes the base case scenario described in Chapter 10 of the TSD. This case 

defines the basis of comparison for all other scenarios. By definition, no new regulatory action 

yields zero energy savings and a net present value of zero dollars. 

2.2.2 Financial Incentives Policies 

DOE considered scenarios in which the Federal government would provide two types of 

financial incentives: rebates and tax credits. The government could provide consumers with a 

cash rebate at the time of purchase. Tax credits could be granted to consumers who purchased 

target-level distribution transformers, or the government could issue tax credits to manufacturers 

to offset costs associated with producing such equipment. 

DOE’s evaluation of financial incentive policies used a comprehensive study of the 

potential for energy efficiency in California performed by Xenergy, Inc., which summarizes 

experience with various utility rebate programs.2

 Xenergy developed a re-parameterized, mixedsource, information-diffusion model to estimate market impacts induced by financial incentives 

for energy-efficient appliances. The basic premise of this mixed-source model is that information 

diffusion drives technology adoption. The model is formulated to characterize the influences of 

both internal and external sources of information on consumer behavior by superimposing two 

components in the equation, each capturing the effect of one of two different types of information 

source. The effects of these two types of information-diffusion mechanisms are different. 

Internal sources of information influence consumers to purchase new products, due mainly to 

word-of-mouth from early adopters, while external information sources influence consumers to 

change their adoption decisions as a result of marketing efforts and information coming from 

outside the consumer group. The mixed-source model describes a combined impact of the two 

information-source types, and specific parameterization determines consumer adoption behavior. 

(Appendix RIA.A contains further details.) 

Xenergy’s model combined these two information diffusion mechanisms and generated a 

set of “implementation curves,” which Xenergy calibrated using evaluation data from utility 

rebate programs conducted in the 1990s. Consumer response to rebate incentives appears to result 

from a combination of the two information-source types. The implementation curves illustrate the 

increased penetration of efficient equipment (i.e., increased market share) as a result of consumer 

response to benefit/cost (B/C) ratio changes induced by a specific rebate program. The 

implementation curves are used to depict various diffusion patterns based on perceived barriers to 

consumer purchase of high-efficiency equipment. There are implementation curves for varying 

levels of market barriers, from “no barriers” to “extremely high barriers.” These curves provide a 

means to study the impact on the consumer participation rate of changing the B/C ratio by 

reducing the initial equipment cost through financial incentives. 

RIA -5 
To further understand the impacts of financial incentives policies, DOE used studies on 

forecasting the impact of consumer tax credits.3, 4 This research differentiated the impact of tax 

credits into the “direct price effect,” which arises from the incremental equipment cost savings, 

and the “announcement effect,” which is independent of the rebate amount. The announcement 

effect derives from the credibility that a particular technology receives from its inclusion in an 

incentive program, as well as changes in product marketing strategy and the resulting 

modifications in markups and pricing. DOE assumed that the direct price effect and the 

announcement effect would also apply to rebate programs. It assumed that half of the increases in 

market penetration associated with rebates would be due to the direct price effect and half to the 

announcement effect. 

Consumer Rebates. DOE modeled the impact of the consumer rebate policy by 

determining the increase in market penetration of target-level equipment relative to the base case. 

It assumed that this policy would apply to medium-voltage, dry-type transformers. 

For medium-voltage, dry-type distribution transformers, DOE estimated the impact of 

increasing the B/C ratio via a rebate that paid 70 percent of the incremental equipment cost 

between a distribution transformer meeting the base case efficiency levela

 and a unit meeting the 

target efficiency. DOE based the 70 percent rebate amount on existing utility rebate programs for 

low-voltage, dry-type distribution transformers that require TP1-2002 efficiency levels to qualify.5, 

6, 7, 8 DOE studied each of these programs and found that the average rebate amounted to about 70 

percent of the incremental equipment cost for low-voltage, dry-type transformers. It then assumed 

that the consumer rebate policy would reduce the incremental equipment costs for mediumvoltage, dry-type transformers during the analysis period by the same percentage. 

DOE assumed the rebates would remain in effect until they had transformed the market, so 

that the shift in market share efficiencies seen in the first year of the program would be maintained 

throughout the forecast period (2010–2038). Section 2.3 below presents the results of the analysis 

for the consumer rebate policy. 

To estimate the B/C ratios, DOE first calculated the B/C ratio for each design line with an 

efficiency meeting the target level relative to the base case design line with no rebate (see Ch.8 of 

the TSD for details on transformer design lines). It then calculated another B/C ratio for each 

design line meeting the target level, with a rebate reducing its incremental equipment cost, relative 

to the base case unit. Because of the incremental cost reduction due to the rebate, the B/C ratio 

for the rebate policy unit is larger. Table RIA.3 shows the inputs to these calculations and the 

resulting B/C ratios for each design line (DL). See Chapter 8 of the TSD for a detailed discussion 

of design lines. 

a

 The b ase case is a ma rket weighted-avera ge of units at several efficiency levels. 

RIA -6 
Table RIA.3 Benefit/Cost Ratios for Adopted Standard and Rebate Policy Cases 

Design 

Linea 

Benefit (Lifetime 

Operating Cost 

Savings) 

($) 

Incremental 

Installed Cost 

($) 

B/C 

Ratio 

with No 

Rebate 

Rebate 

Amount 

($) 

Incremental 

Equipment C ost 

after Rebate 

($) 

B/C Ratio 

for Rebate 

Policy Case 

DL 1 385 364 1.1 226 139 2.8 

DL 2 149 284 0.5 182 102 1.5 

DL 3 5,131 1,394 3.7 1,057 338 15.2 

DL 4 1,407 1,472 1.0 958 515 2.7 

DL 5 7,986 5,869 1.4 3,952 1,917 4.2 

DL 9 3,490 480 7.3 326 154 22.7 

DL 10 17,333 8,641 2.0 5,820 2,821 6.1 

DL 11 7,235 1,790 4.0 1,219 571 12.7 

DL 12 15,326 4,942 3.1 3,382 1,560 9.8 

DL 13 9,297 5,756 1.6 3,929 1,828 5.1 

Note:	 Design lines 1 though 5 represent liquid-immersed transformers. Design lines 9 though 13 represent 

medium -voltage, dry-type transformers. 

DOE then used the implementation curves discussed above to estimate the increased 

percentage of consumers who would purchase units that meet the policy target levels if given a 

rebate incentive. DOE assumed that medium-voltage, dry-type transformers would fit the 

“moderate barriers” curve, since they are typically purchased by industrial entities that analyze the 

economics of the purchase and, therefore, have some incentive for energy 

efficiency. 

Figure RIA.1 shows an implementation curve with the penetration rates (market shares) of 

target-level units for an example design line of medium-voltage, dry-type transformers as a 

function of B/C ratios. Using this method, DOE estimated that, for design line 13 (one of the 

medium-voltage, dry-type design lines), the penetration rate increase, as shown, would be about 

32 percent. 

To estimate the impacts of this rebate policy on medium-voltage, dry-type transformers, 

DOE calculated the weighted average of the resulting market share increases by product class, 

using the market shares of the design lines. DOE applied these market share increases to the 

portion of shipments affected by the standards (non-compliant) in each product class, generating 

effective market share increases of distribution transformers meeting the target levels by product 

a

 Because the Energy Policy Act of 2005 established energy conservation standards for low-voltage, dry-type 

distribution transformers, DOE has removed from this Final rule its analysis of design lines 6, 7, and 8. 

RIA -7 
class. In the RIA model, DOE adjusted the base case shipments projection to reflect these 

percentage increases in effective market share. 

Figure RIA.1 Market Penetration Curve for Design Line 13 of MediumVoltage, Dry-Type Transformers 

Table RIA.4 lists the market share increases of the affected shipments, the percentage of 

the product class (PC) affected by the standards, and the effective PC market share increases, for 

each medium-voltage, dry-type transformer product class. 

RIA -8 
Table RIA.4 Market Share and Effective Market Share Increases for Consumer Rebates 

Policy Case by Medium-Voltage, Dry-Type Product Class 

Product 

Class 

Increased Market Share 

(Percentage of Affected Market 

Segment) 

(%) 

Percent Affected 

by Adopted 

Standard 

(%) 

Increased 

Effective Market 

Share 

(%) 

PC 5 31.2 67.5 21.1 

PC 6 31.2 67.5 21.1 

PC 7 32.9 44.3 14.6 

PC 8 32.9 44.3 14.6 

PC 9 30.2 44.8 13.5 

PC 10 30.2 44.8 13.5 

Although DOE assumed that the rebate policy would not apply to utilities, and therefore 

liquid-immersed transformers, it did analyze the impacts of consumer and manufacturer tax 

credits on liquid-immersed transformers. Therefore, DOE needed to calculate the impacts of a 

hypothetical rebate-type incentive for liquid-immersed transformers, assuming that such rebates 

would reduce the incremental installed cost of these transformers by the same percentage as they 

would for the medium-voltage, dry-type transformers. Using this assumption, DOE calculated the 

changes in B/C ratios for the liquid-immersed representative units, as shown above in Table 

RIA.3. 

DOE assumed liquid-immersed transformers would fit the “low barriers” curve, because 

the utilities that purchase them usually evaluate the economics of the purchase. In 1996, Oak 

Ridge National Laboratory (ORNL) stated in its determination analysis that 90 percent of the 

liquid-immersed transformer purchases were evaluated.9 Data submitted by the National 

Electrical Manufacturers Association (NEMA) for years after 1996 showed that about 65 percent 

of utilities still evaluated their distribution transformer purchases. 

For liquid-immersed transformers, DOE estimated the market-weighted averages of the 

penetration rates from the design line at the product class level. DOE then used implementation 

curves to estimate the increased percentage of consumers who would purchase units that meet the 

policy target levels, if given hypothetical rebates covering 70 percent of incremental costs. For 

example, as shown in Figure RIA.2, for design line 1 the penetration rate (market share) would 

increase by almost 17 percent. Table RIA.5 lists the market share increases of the affected 

shipments, the percentage of the product class impacted by the adopted standards, and the 

effective product class market share increases, for each liquid-immersed transformer product 

class. DOE used these values to calculate the impacts of the tax credit policies on liquidimmersed transformers, as explained in the sections below. 

RIA -9 
Figure RIA.2 Market Penetration Curve for Design Line 1 of LiquidImmersed Transformers 

Table RIA.5	Market Share and Effective Market Share Increases for Consumer Rebates 

Policy Case by Liquid-Immersed Product Class 

Product Class Increased Market Percent Impacted Increased Effective 

Share (Percentage of by Adopted Market Share 

Affected Market Standard (Percentage of Product 

Segment) Class) 

PC 1 21.4 74.3 15.9 

PC 2 24.2 65.1 15.8 

Consumer Tax Credits. DOE assumed that a tax credit policy would apply to mediumvoltage, dry type transformers, as well as those liquid-immersed transformers that are purchased 

by investor-owned utilities (IOUs). 

DOE assumed a consumer tax credit equivalent to the amount covered by rebates (i.e., 70 

percent of the incremental cost between distribution transformer base case equipment and 

equipment meeting the policy target levels). 

DOE estimated that, for both transformer types, the consumer participation rate would be 

lower than that for consumer rebates. Research on tax credits has shown that the time delay to the 

RIA-10 
consumer in receiving a reimbursement via tax credit, plus the added transaction costs in taxreturn preparation, make the tax credit incentive less effective than a rebate received at the time of 

purchase. Based on previous analysis,10 DOE assumed that only 60 percent as many consumers 

would take advantage of the tax credit as would take advantage of a rebate. 

Using a similar approach as for the rebate policy, DOE estimated that the market share of 

target efficiency distribution transformers would increase due to consumer tax credits over the 

base case by the percentages shown in Table RIA.6. For both transformer types, these percentage 

market share increases are 60 percent of the market increases estimated for the rebate policy 

(which are shown in Tables RIA.4 and RIA.5). For liquid-immersed transformers product classes 

1 and 2, DOE adjusted the effective market shares to reflect the percentage of those transformers 

owned by IOUs, as shown in Table RIA.6. DOE used data on transformer ownership by design 

line to estimate the percentage of liquid-immersed transformers owned by IOUs. Refer to 

Chapter 8 of the TSD for more information. 

DOE assumed the impact of this policy would be to permanently transform the market so 

that the shipment-weighted efficiency gain seen in the first year of the program would be 

maintained throughout the forecast period. Section 2.3 below presents the results of the analysis 

for the consumer tax credit policy. 

RIA-11 
Table RIA.6 Effective Market Share Increases for Consumer Tax Credits Policy Case by 

Product Class 

Product Classa Percent Owned by IOUs 

(%) 

Increased Effective Market Share 

(Percentage of Product Class) 

(%) 

PC 1 72.3 9.6 

PC 2 50.7 9.5 

PC 5 0 12.6 

PC 6 0 12.6 

PC 7 0 8.7 

PC 8 0 8.7 

PC 9 0 8.1 

PC 10 0 8.1 

Manufacturer Tax Credits. DOE assumed that tax credits could be given to 

manufacturers of liquid-immersed and medium-voltage, dry-type transformers. It assumed that 

this incentive policy would help reimburse manufacturers for retooling costs. Because these tax 

credits would go to manufacturers instead of consumers, DOE assumed that manufacturers would 

pass on the reduced costs, causing a direct price effect. However, DOE assumed that the 

announcement effect would not occur because the program would not be visible to owners of 

distribution transformers. Since the direct price effect is approximately equivalent to the 

announcement effect,3

 DOE assumed that half of the consumers assumed to take advantage of 

consumer tax credits would purchase more-efficient products with a manufacturer tax credit 

program. As a result, DOE estimated the percentage by which market shares of efficient 

distribution transformers would increase due to manufacturer tax credits over the base case, as 

shown in Table RIA.7. 

a

 Because the Energy Policy Act of 2005 established energy conservation standards for low-voltage, dry-type 

distribution transformers, DOE has removed from this Final rule its analysis of product class 3 (low-voltage, 

dry-type, single-phase) and product class 4 (low-voltage, dry-type, three-phase). 

RIA-12 
Table RIA.7 Effective Market Share Increases for Manufacturer Tax Credits Policy Case 

by Product Class 

Product Class Increased Effective Market Share 

(Percentage of Product Class) 

(%) 

PC 1 4.8 

PC 2 4.7 

PC 5 6.3 

PC 6 6.3 

PC 7 4.4 

PC 8 4.4 

PC 9 4.1 

PC 10 4.1 

DOE assumed that the impact of this policy would be to permanently transform the 

market so that the shipment-weighted efficiency gain seen in the first year of the program would 

be maintained throughout the forecast period. Section 2.3 below presents the results of the 

analysis for the manufacturer tax credit policy. 

2.2.3 Voluntary Energy-Efficiency Targets 

DOE assumed that this policy would apply only to low-voltage, dry-type distribution 

transformers. For the RIA, DOE would model the voluntary efficiency target policy assuming 

some form of enhancement of the existing Energy Star program conducted by the Environmental 

Protection Agency (EPA) and DOE.11 The Energy Star program sets minimum energy-efficiency 

specifications for various products. Energy Star encourages consumer adoption of these products 

through marketing to promote consumer label recognition, adoption of the specifications by 

various efficiency incentive programs, and manufacturer production and promotion of Energy 

Star-compliant appliances. 

Energy Star has a modest program for low-voltage, dry-type transformers, with efficiency 

specifications at the NEMATP 1-2002 standard level. Energy Star does not have specifications 

for medium-voltage, dry-type transformers.a

 While the Energy Star website states that “utility 

transformers” (i.e., liquid-immersed) are included in its program, EPA staff indicate that there 

a

 The only programs that DOE found that include medium-voltage, dry-type transformers are Oregon’s equipment 

standard and Minnesota’s building code. 

RIA-13 
has been very little program activity on liquid-immersed transformers in recent years.12 Thus, 

DOE concluded that there is no historical basis to project the impact of a voluntary efficiency 

program on the market for medium-voltage, dry-type or liquid-immersed transformers, and 

assumed that voluntary programs would have no impact during the forecast period. The flat or 

declining market share of TP 1-compliant medium-voltage, dry-type transformers observed in the 

shipment data is consistent with this conclusion. 

Therefore, since this policy would apply only to low-voltage, dry-type transformers, 

which are no longer part of this rulemaking, DOE did not analyze the impacts of this policy. 

2.2.4 Early Replacement 

Early replacement refers to the replacement of distribution transformers before the end of 

their useful lives. The purpose of this policy is to replace old, inefficient equipment with higherefficiency units. 

In 1995, ORNL performed a study of savings potential for early replacement of 

distribution transformers.13 This study found that early replacement would be practical only at 

the time of routine transformer maintenance and would be cost-effective for just 13 percent of 

transformers as an alternative to refurbishment. As discussed in Chapter 10 of the TSD, in 

discussions with DOE, transformer owners stated that refurbishment was uncommon in current 

practice. Thus, the RIA analysis assumed that owners would replace their transformers rather 

than refurbishing them. Therefore, DOE concluded that an early replacement policy for this 

equipment would have minimal impact and did not further analyze it. 

2.2.5 Bulk Government Purchases 

DOE assumed that this policy would apply only to low-voltage, dry-type distribution 

transformers. For the RIA, DOE assumed that a bulk government purchase policy would 

encourage Federal, State, and local governments to purchase distribution transformers meeting 

the target levels. Aggregating public sector demand could provide a market signal to 

manufacturers and vendors that some of their largest customers seek suppliers with products that 

meet an efficiency target at competitive prices. This program could also induce “market pull” 

impacts through the effects of manufacturers and vendors achieving economies of scale for highefficiency products. DOE assumed that government agencies, such as the U.S. General Services 

Administration (GSA), would administer such a program. A bulk purchasing program could 

impact government purchases of low-voltage, dry-type transformers. However, while 

government entities own medium-voltage, dry-type and liquid-immersed transformers, they are 

typically purchased on a custom basis rather than for inventory. Thus, DOE concluded that a 

bulk purchasing program would not be appropriate for MV dry-type or liquid-immersed 

distribution transformers. 

Therefore, because low-voltage, dry type transformers are no longer part of this 

rulemaking, DOE did not analyze the impacts of this policy. 

RIA-14 
2.3 Results Summary for Non-Regulatory Alternatives

 Table RIA.8 shows the NES and NPV of each of the applicable non-regulatory 

alternatives. The results are reported for liquid-immersed and medium-voltage, dry-type 

transformers, as well as in total. The case in which no regulatory action is taken with regard to 

distribution transformers constitutes the base case (or “No Action”) scenario. Since this is the 

base case, energy savings and NPV are zero by definition. For comparison, the table includes 

the impacts of the adopted energy conservation standards. The NPV amounts shown in Table 

RIA.8 refer to the NPV based on two discount rates (seven percent and three percent real). Note 

that, for three of the policy alternatives, no results are reported; as discussed above, DOE found 

that those policies would not impact the distribution transformers covered by this energy 

conservation standard. 

None of the alternatives DOE examined would save as much energy or have an NPV as 

high as the adopted standards. Also, several of the alternatives would require new enabling 

legislation, such as consumer or manufacturer tax credits, since authority to carry out those 

alternatives does not presently exist. 

RIA-15 
Table RIA.8 Non-Regulatory Alternatives and the Adopted Standard 

Policy Alternatives Type 

Primary 

Energy Savings 

(quads) 

Net Present Value* 

(billion $2006) 

7% discount rate 3% discount 

rate 

No New Regulatory Action 0.0 0.0 0.0 

Consumer Rebates 

Liquid 0.196 0.154 0.655 

MV** Dry 0.021 0.045 0.135 

Total 0.217 0.199 0.790 

Consumer Tax Credits 

Liquid 0.218 0.101 0.597 

MV Dry 0.013 0.027 0.081 

Total 0.231 0.128 0.678 

Manufacturer Tax Credits 

Liquid 0.108 0.046 0.293 

MV Dry 0.006 0.013 0.040 

Total 0.114 0.059 0.333 

Voluntary Energy-Efficiency Targets NA NA NA 

Early Replacement NA NA NA 

Bulk Government Purchases NA NA NA 

Adopted Standards 

Liquid 2.605 1.106 6.951 

MV Dry 0.131 0.283 0.851 

Total 2.736 1.389 7.802 

* DOE determined the NPV discounted to 2004 in billion 2004$. 

** MV = medium-voltage 

RIA-16 
APPENDIX RIA.A: USING IMPLEMENTATION CURVES TO ESTIMATE 

MARKET PENETRATION OF NON-REGULATORY POLICIES 

There is extensive economic literature on the diffusion process of new products as 

technologies evolve. Some of the literature focuses primarily on the development of analytical 

models of diffusion patterns of new products for individual consumers or for technologies from 

competing firms.14, 15, 16, 17 One study records researchers’ attempts to investigate underlying 

factors that drive diffusion processes.16 Because of distinct characteristics of the diverse new 

products, few studies are conclusive in terms of developing a universally applicable model. 

Some key findings, however, seem to have gained wide recognition in academia and industry. 

First, new technologies may not be adopted by all potential users, regardless of their 

economic benefits and technological merits. Therefore, a ceiling of adoption rate exists for many 

products. Second, not all adopters purchase new products at the same time; some act earlier to 

purchase new products, while others respond slowly, waiting for products to become more 

mature. Third, diffusion processes can be approximately characterized by asymmetric S-curves, 

depicting three stages of the diffusion: starting, accelerating, and decreasing as the adoption 

ceiling is being reached. 

An important diffusion model, the epidemic model, is widely used in marketing and 

social studies on diffusion. It assumes a) that consumers value the benefits of a new product 

identically, and b) that the cost of a new product is constant or declines monotonically over time. 

What induces a consumer to purchase the new product is information about the availability and 

the benefits of the product. In other words, it is information diffusion that drives new product 

adoption by individual consumers.16 The model embraces information diffusion from both 

internal sources (news spread by word of mouth from early adopters) and external sources (the 

announcement effect by government or commercial advertising programs) by superimposing a 

logistic function with an exponential function.14, 17 

The degree of relative dominance of influence by internal or external sources will 

determine the general shape of the diffusion curve of a specific product.14, 17 For instance, if the 

adoption of one particular product is more influenced by external sources of information 

diffusion (announcement effect) than by internal sources (word of mouth among earlier adopters 

to prospective adopters), the rate of diffusion at the beginning stage of the diffusion process is 

much higher. This reflects the immediate information exposure to a significant number of 

prospective adopters brought about by external sources, in contrast to the more gradual exposure 

to internal sources such as news propagation by earlier adopters, a small proportion of the 

population, to other prospective adopters. 

Graphically speaking, a relatively dominant external source of information diffusion will 

give an immediate jump-start to the adoption of a new product in the first years, forming a 

concave curve with respect to the Y axis (see the exponential curve in Figure RIA.A.1). 

Adoption of a new product with a stronger influence by internal sources of information diffusion 

(such as a socially tightened network formed by prospective adopters) may start with a few early 

RIA-17 
adopters and gradually increase as the number of adopters grows Once a critical mass 

accumulates, the growth appears to accelerate very rapidly and thus forms a convex curve with 

respect to the Y-axis during the starting and acceleration stages (see the logistic curve in Figure 

RIA.A.1). 

Figure RIA.A.1 Comparison of Exponential and Logistic Curves Showing 

External and Internal Influences on Consumers 

RIA-18 
REFERENCES 

1.	 U.S. Department of Energy-Office of Building Technologies. Technical Support 

Document: Energy Conservation Program for Commercial and Industrial Equipment: 

Electrical Distribution Transformers - NOPR Version. 2005. U.S. Department of Energy. 

Washington, DC. 

<http://www.eere.energy.gov/buildings/appliance_standards/commercial/distribution_tran 

sformers.html> 

2.	 Rufo, M. and F. Coito. California's Secret Energy Surplus: The Potential for Energy 

Efficiency. 2002. Xenergy Inc. Oakland, CA. Prepared for The Energy Foundation and 

The Hewlett Foundation. 

3.	 Koomey, J. G. Avoiding "The Big Mistake" in Forecasting Technology Adoption. 

Technological Forecasting and Social Change. 2002. 69(2002): pp. 511-518. LBNL45383. <http://enduse.lbl.gov/info/LBNL-45383.pdf> 

4.	 Lawrence Berkeley National Laboratory - End-Use Forecasting Group. Analysis of Tax 

Credits for Efficient Equipment. (Last accessed June 10, 2005.) This material is available 

in Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy, 

Building Technologies Program, Mailstop EE-2J, 1000 Independence Avenue, SW, 

Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. 

<http://enduse.lbl.gov/Projects/TaxCredits.html> 

5.	 Tacoma Power. Transformer Rebate Program. Transformer Rebates: For commercial 

and industrial customers. (Last accessed August 10, 2005.) This material is available in 

Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy, Building 

Technologies Program, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, 

DC, 20585-0121, telephone (202) 586-2945 for more information. 

<http://www.ci.tacoma.wa.us/power/Business/transformer_rebates.htm> 

6.	 Efficiency Vermont. ENERGY STAR® Three-Phase, Low-Voltage Transformer Incentive 

Application. (Last accessed August 10, 2005.) This material is available in Docket #86. 

Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy, Building Technologies 

Program, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585­

0121, telephone (202) 586-2945 for more information. 

<http://www.efficiencyvermont.com/Docs/Transformer.pdf> 

7.	 Public Service of New Hampshire. New Equipment and Construction Program. (Last 

accessed August 10, 2005.) This material is available in Docket #86. Contact Ms. 

Brenda Edwards-Jones, U.S. Department of Energy, Building Technologies Program, 

Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585-0121, 

telephone (202) 586-2945 for more information. 

<http://www.psnh.com/Energy/Business_Efficiency/newequipment.asp> 

RIA-19 
8.	 Narragansett Electric (National Grid). Design Plus2000. (Last accessed August 10, 2005.) 

This material is available in Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. 

Department of Energy, Building Technologies Program, Mailstop EE-2J, 1000 

Independence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for 

more information. 

<http://www.nationalgridus.com/narragansett/non_html/energy_eff_d2_dry_trans_pif.pdf 

> 

9.	 Barnes, P. R., J. W. Van Dyke, B. W. McConnell, and S. Das. Determination Analysis of 

Energy Conservation Standards for Distribution Transformers. 1996. Oak Ridge 

National Laboratory. Oak Ridge, TN. Report No. ORNL-6847. 

10.	 U.S. Department of Energy-Office of Codes and Standards. Technical Support 

Document: Energy Efficiency Standards for Consumer Products: Refrigerators, 

Refrigerator-Freezers, and Freezers, including Environmental Assessment and 

Regulatory Impact Analysis. July, 1995. Washington, DC. Report No. DOE/EE-0064. 

<http://www.osti.gov/bridge/product.biblio.jsp?osti_id=90266> 

11.	 U.S. Environmental Protection Agency and U.S. Department of Energy. Energy Star 

Program. (Last accessed June 10, 2005.) This material is available in Docket #86. 

Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy, Building Technologies 

Program, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585­

0121, telephone (202) 586-2945 for more information. <http://www.energystar.gov> 

12.	 Ryan, S. Personal communication. U.S. Environmental Protection Agency, Climate 

Protection Partnerships Division. E-mail to Rich Brown, Lawrence Berkeley National 

Laboratory. July 14, 2005. 

13.	 Barnes, P. R., J. W. Van Dyke, B. W. McConnell, S. M. Cohn, and S. L. Purucker. The 

Feasibility of Replacing or Upgrading Utility Distribution Transformers During Routine 

Maintenance. 1995. Oak Ridge National Laboratory. Oak Ridge, TN. Report No. ORNL6804/R1. < http://www.ornl.gov/~webworks/cpr/v823/rpt/78562.pdf> 

14.	 Geroski, P. A. Models of Technology Diffusion. Research Policy. 2000. 29: pp. 603-625. 

15.	 Hall, B. H. and B. Khan. Adoption of New Technology. 2003. Department of Economics, 

University of California, Berkeley, CA. Working Paper No. E03-330. 

16.	 Lekvall. P and C. Wahlbin. A Study of Some Assumptions Underlying Innovation 

Diffusion Functions. Swedish Journal of Economics. 1973. 75: pp. 362–377. 

17.	 Van den Bulte, C. Want to Know How Diffusion Speed Varies Across Countries and 

Products? Try a Bass Model. PDMA Visions. 2002. 26(4): pp. 12-15. 

RIA-20