8-i

CHAPTER

8. LIFE- CYCLE COST A ND PAY BACK P ERIOD ANA

LYSES

TABLE OF CO NTENTS 8.1 INTRODUCTION

..................................................... 8-1 8.1.1 General Approach for L ife-Cycle Cost and Pay

back Period Analy ses ....... 8-1 8.1.2 The Bas eline Sce

nario

............................................ 8-2 8.1.3 Total Own

ing Cost

............................................... 8-3 8.2 LI FE-CYCLE COST METHOD

.......................................... 8-3 8.2.1 Definition

...................................................... 8-3 8.2.2 Life-Cy

cle Cost Spreadsheet Key Steps

............................... 8-4 8.2.2.1 Step 1: S elect A & B

..................................... 8-4 8.2.2.2 Step 2: Select Designs That Meet a Chosen Candidate Standard Level

.......................................... 8-6 8.2.2.3 Step 3: Load and Pr ice Prof ile

............................. 8-7 8.2.2.4 Step 4: Calculate Cost of Losses

............................ 8-8 8.2.2.5 Step 5: Project Losses and Costs into the Future

............... 8-8 8.2.2.6 Step 6: Sele ct Discou nt Rate

............................... 8-8 8.2.2.7 Step 7: Calculate Present Value of Future Cost of Losses ........ 8-8 8.2.2.8 Step 8: Results Reported

.................................. 8-9 8.2.2.9 Step 9: Results of Sample of Transformers

.................... 8-9 8.2.2.10 Step 10: Re sults for “ Average” Scenario

..................... 8-9 8.2.2.11 Repeat Pr

ocess .......................................... 8-9 8.3 LI FE-CYCLE COST I

NPUTS

............................................ 8-9 8.3.1 A and B Transformer Selection Parame ters and Usage Rates

............. 8-10 8.3.2 Database of Transformer De signs

.................................. 8-16 8.3.3 Markup a

nd In stallation Costs

..................................... 8-16 8.3.4 Transformer Loa

ding

............................................ 8-16 8.3.5 Electric ity Price Ana lys is

......................................... 8-17 8.3.5.1 Hourly Marg

inal Electricity Price Mode l for Liquid-I mmersed Transformers

.......................................... 8-17 8.3.5.2 Monthly Tariff-B ased Analysis for Dry-Ty pe Transformers

...... 8-21 8.3.5.3 Data Collection and Modeling

............................. 8-25 8.3.6 Load Growth Trends

............................................ 8-31 8.3.7 Electricity Cost and Price Tr ends

................................... 8-32 8.3.8 Discount R

ate
.................................................. 8-33 8.3.9 Effective Date of Standard

........................................ 8-38 8.3.10 Transformer Service Life

......................................... 8-38 8.3.11 Maintena

nce Costs

.............................................. 8-39 8.3.12 Power Factor

.................................................. 8-39 8.3.13 Default

Scenari o ................................................ 8-398-ii

8.4 LI FE-CYCLE COST RESULT S

......................................... 8-40 8.4.1 Design

Line 1 Results

........................................... 8-42 8.4.2 Design

Line 2 Results

........................................... 8-42 8.4.3 Design

Line 3 Results

........................................... 8-43 8.4.4 Design

Line 4 Results

........................................... 8-43 8.4.5 Design

Line 5 Results

........................................... 8-44 8.4.6 Design

Line 9 Results

........................................... 8-44 8.4.7 Design

Line 10 Results

.......................................... 8-45 8.4.8 Design

Line 11 Results

.......................................... 8-45 8.4.9 Design

Line 12 Results

.......................................... 8-46 8.4.10 Design

Line 13 Results

.......................................... 8-46 8.5 LIFE- CYC LE CO ST SE NS ITIVIT Y AN ALYS IS

........................... 8-47 8.5.1 Design

Line 1 Summary

Sensitivity

Results

.......................... 8-48 8.5.2 Design

Line 12 Summary

Sensitivity

Results

......................... 8-50 8.6 PAYBACK PERIOD

.................................................. 8-52 8.6.1 Payback Period

................................................. 8-52 8.6.2 Inpu

ts
........................................................ 8-53 8.6.3 Baseline Scenario Complications

.................................. 8-53 8.6.4 Pay

back Per iod Results

.......................................... 8-54 8.6.5 Design

Line 1 Results

........................................... 8-55 8.6.6 Design

Line 2 Results

........................................... 8-55 8.6.7 Design

Line 3 Results

........................................... 8-56 8.6.8 Design

Line 4 Results

........................................... 8-57 8.6.9 Design

Line 5 Results

........................................... 8-57 8.6.10 Design

Line 9 Results

........................................... 8-58 8.6.11 Design

Line 10 Results

.......................................... 8-59 8.6.12 Design

Line 11 Results

.......................................... 8-59 8.6.13 Design

Line 12 Results

.......................................... 8-60 8.6.14 Design

Line 13 Results

.......................................... 8-60 8.7 REBUTTABLE PRESUMPTION

........................................ 8-61 8.8 USER INSTRUCTION S FOR SPREADSHEETS

........................... 8-67 8.8.1 Startup

....................................................... 8-67 8.8.1.1 Sheet Overview

........................................ 8-68 8.8.2 Basic Instructions

.............................................. 8-70

LIST OF TABLE S Table 8.3.1 Distributions of A Values for Liquid-I mmersed Transformers: Three Scenar ios with Usage Percentage s .......................................... 8-12 Table 8.3.2 Distributions of A Values for Small-Capacity , Medium-Voltage, Dry -Type Transformers (DL

9 and DL 11): Three Sce narios with Usage Percentag es . . 8-138-iii

Table 8.3.3 Distributions of A Values for Large-Capacity , Medium-Voltage, Dry -Type Trans forme rs (DL 10 , DL 12, a nd DL 13) : Thre e Scen arios with Usage Percentages

.................................................... 8-14 Table 8.3.4 Genera

tion Capac ity C osts
....................................... 8-19 Table 8.3.5 Representative Cost Recovery Factors

............................... 8-20 Table 8.3.6 Percentage of All Commercial and I ndustrial Customers, by Subdivision, in the Utility Sample

................................................. 8-23 Table 8.3.7 Variables Used to Estimate Company Discount Rates

.................. 8-35 Table 8.3.8 Typical Owne rs of Different Ty

pes of Transformers

.................... 8-36 Table 8.3.9 Real Discount Rates by Tra nsformer Ownership Category

............... 8-37 Table 8.3.10 Transformer Ownership by Design Line

............................. 8-38 Table 8.4.1 Candidate Standard Levels Evalua ted For Each Design L

ine

............. 8-40 Table 8.4.2 Summary

Life -Cycle Cost Re sults for D esign L ine 1 Repr

esentat ive Unit

... 8-42 Table 8.4.3 Summary

Life -Cycle Cost Re sults for D esign L ine 2 Repr

esentat ive Unit

... 8-42 Table 8.4.4 Summary

Life -Cycle Cost Re sults for D esign L ine 3 Repr

esentat ive Unit

... 8-43 Table 8.4.5 Summary

Life -Cycle Cost Re sults for D esign L ine 4 Repr

esentat ive Unit

... 8-43 Table 8.4.6 Summary

Life -Cycle Cost Re sults for D esign L ine 5 Repr

esentat ive Unit

... 8-44 Table 8.4.7 Summary

Life -Cycle Cost Re sults for D esign L ine 9 Repr

esentat ive Unit

... 8-44 Table 8.4.8 Summary

Life -Cycle Cost Re sults for D esign L ine 10 Representa

tive Unit

. . 8-45 Table 8.4.9 Summary

Life -Cycle Cost Re sults for D esign L ine 11 Representa

tive Unit

. . 8-45 Table 8.4.10 Summary

Life -Cycle Cost Re sults for D esign L ine 12 Representa

tive Unit

. . 8-46 Table 8.4.11 Summary

Life -Cycle Cost Re sults for D esign L ine 13 Representa

tive Unit

. . 8-47 Table 8.5.1 Mean Life-Cy cle Cost Savings ($), Summary for Design Line

1 Represe ntative U nit

............................................. 8-49 Table 8.5.2 Mean Life-Cy cle Cost Savings ($), Summary for Design Line

12 Represe ntative U nit

............................................. 8-51 Table 8.6.1 Possible ) FC and ) OC

Combinations, for Pa

yba ck Period Analysis

...... 8-54 Table 8.6.2 Summary of Pay back Period Results for Design Line 1 Represe ntative U nit

............................................. 8-55 Table 8.6.3 Summary of Pay back Period Results for Design Line 2 Represe ntative U nit

............................................. 8-55 Table 8.6.4 Summary of Pay back Period Results for Design Line 3 Represe ntative U nit

............................................. 8-57 Table 8.6.5 Summary of Pay back Period Results for Design Line 4 Represe ntative U nit

............................................. 8-57 Table 8.6.6 Summary of Pay back Period Results for Design Line 5 Represe ntative U nit

............................................. 8-58 Table 8.6.7 Summary of Pay back Period Results for Design Line 9 Represe ntative U nit

............................................. 8-58 Table 8.6.8 Summary of Pay back Period Results for Design Line 10 Represe ntative U nit

............................................. 8-59 Table 8.6.9 Summary of Pay back Period Results for Design Line 11 Represe ntative U nit

............................................. 8-608-iv

Table 8.6.10 Summary of Pay back Period Results for Design Line 12 Represe ntative U nit

............................................. 8-60 Table 8.6.11 Summary of Pay back Period Results for Design Line 13 Represe ntative U nit

............................................. 8-61 Table 8.7.1 Average Transforme r Efficiency

................................... 8-63 Table 8.7.2 Average Transf ormer I nstalled C ost
................................ 8-64 Table 8.7.3 Average Marginal Electricity Cost

................................. 8-65 Table 8.7.4 First Year Operating Cost for Rebuttable Pre sumption, Based on DOE

Test Procedure

................................................. 8-66 Table 8.7.5 Rebuttable Payback f or Rebuttable Presumption Period

................. 8-67 LIST OF F IGURES Figure 8.2.1 Transformer Life -Cycle Cost Spreadshee t Model Flowchart

.............. 8-5 Figure 8.3.1 Map Showing the Division of the Continental United States into

17 Subdivisi ons ................................................ 8-22 Figure 8.3.2 Customer- Weighte d Avera ge of U tility Revenue Divided by Sa

les by Subdivision ($/kWh)

.......................................... 8-24 Figure 8.3.3 Effect of a Change in Customer Demand (Energy Consumption is Held Fixed) for a Block-By

-Demand Tariff

.............................. 8-27 Figure 8.3.4 Cumulative Load Growth at One Perc ent per Year for Liquid-Immersed

Transformers

.................................................. 8-32 Figure 8.3.5 Electricity Price Sce narios

........................................ 8-33 Figure 8.4.1 Design Load L osses (LL ) versus No-load Losses (N L) for TP 1-2002, Design Line 1

.................................................. 8-41 Figure 8.5.1 Design Line 1 Sensitivity Results by Candidate Standard Level

........... 8-50 Figure 8.5.2 Design Line 12 Sensitivity Results by Candidate Standard Level

.......... 8-528-1

CHAPTER

8. LIFE- CYCLE COST A ND PAY BACK P ERIOD ANA

LYSES 8.1 INTRODUC TION This chapter of the technical support document (TSD) pre sents the Department’s lifecycle c ost (LCC) and pay back period (PBP) analyses. It describes the method used f or analyzing the economic impacts of possible standards on consumers. The effe ct of standards on consumers includes a change in operating expense (usually decr

eased) and a change

in purchase price (usually increased). The LCC and PBP analy ses produce two basic outputs to describe the effect of standa rds on con sumers:

C LCC is the total (discounted) cost that a consumer pay s over the lifetime of the equipmen t, includin

g purchase pri ce, insta

llation co st, and ope

rating expenses.

C PBP measures the amount of time it takes consumers to recover the assumed higher purchas e expense

of more e

nergy -effic ient equi

pment thro

ugh lowe r opera ting costs. This chapter presents inputs and results for the L CC and PBP analyses, as we ll as key variables, current assumptions, and computational equations. The Depar tment performed the calcula tions discussed her

e using a series o f Microso ft Excel spreadshe ets, whic h are ac cessible on DOE's website. Section 8.7 of this document contains details and instructions for using the spreadsheets. There are five appendices to this chapter: 1) a complete set of results is prese nted in Append

ix 8A; 2) App endix 8B di scusses u ncerta inty and vari ability ; 3) the uti lity sample is fully detailed in Append

ix 8C; 4) a complete se

t of sensit ivity results f or desig n lines 1a nd 12 is present ed in Appe

ndix 8D; and

5) aver age baseline tr

ansformer desig

n proper ties are present ed in Appendix 8E. 8.1.1 General Approach for Life-Cycle Cost and Payback Period Analyses Recognizing that each transformer customer is unique, the Department calculated the LCC an d PBP for a

repres entative

sample (i .e., a distribution) of individ

ual tran sformers. In

this manner, the Department’s analy sis explicitly recognized that there is both var iability and uncertainty in its inputs. The Depa rtment used Monte Carlo simulations to model the distributions of inputs. The Monte Carlo process statistically captures input variability a nd distribution without testing all possible input combinations. The results are expressed as the number of transfor mers experien cing ec onomic impa

cts of va ry ing mag nitudes. T

he Depa rtment de veloped t he LC C model usin

g Excel sp

readshe ets combined with Cr yst al Ball, a commer

cially availab le add-i

n program. A detailed explanation of the Monte Carlo simulation process and the use of probabili ty distributio ns in thi s analysis is cont ained in App endix 8B. The LCC results are display ed as distributions of impacts compared to the baseline conditions. The Department presents tabular results at the end of this cha pter; they ar

e based ona

Because the Energy

Polic y Act

of 2005 es tabl ish ed ener gy con serv ati on st andards for low- volt age, dry- type distribut ion tr ansfor

mers, t he Department removed thi s ty pe of tr ansfor

mer (desi gn li nes 6, 7, and 8) fr om the noti ce of pro pos ed ru lema king (N OP R) stag e of its ana lysis. 8-2 10,000 samples per Monte Carlo simulation run. In addition, Appendix 8A contains gra phs that illustrate the following analysis results for each standard level of eac h design line:

C a cumula

tive prob ability

distributi on showing

the perc entage

of trans formers

that would have a net savings due to standards, and

C a frequency

chart depicting variation in L CC for each standard level considered in the analy sis. The Department developed two approache s for the LCC calculations: one for liquidimmersed transformers an

d one for medium-vo ltage, dry-ty

pe trans formers

. a Becaus e the l arge majority of liquid- immersed

transformer owners are

utilities, t

he liquid- immersed

LCC calculations used utility marginal costs and distribution markups that do not include a wholesaler and contractor markup. I n contrast, because the majority of dry-ty pe transformer owners are commerc ial and industrial e nterpris es, the D epartme

nt used the

monthly marginal electricity

costs an d c om pl et e d is tr ib ut io n m ar ku ps fo r t he dr y-t ype tr an sf or me r LC C c al cu la ti on . F or si mp li ci ty, the Department used only one type of L

CC calculation for each design line of transfor mer, based on the majority owner ty

pe of that category

. 8.1.2 The Baseline

Scenario In developing applianc e standards, the Department has traditionally used an existing standard level as a baseline from which it calcula tes the impact of any

candidate standard level. Because distribution transformers are not cur rently subject to a na

tional energy

-efficiency standard, the Department developed an alter native approach to determine an appropria te baseline against which to compare various candida te standard levels. That alternative approac h focused on the mix of s election

criteri a custome

rs are k nown to use

when pur

chasing transformers. T

hose criteria include first costs, as well as what is known in the transformer industry as total owning cost (TOC), used by some c ustomers as an alternative criterion to first costs. The TOC method combines first costs with the

cost of lo sses. Purc

hasers o f distribu

tion trans formers , especi ally in the utility sector, have long used the TOC method to determine which transformers to purchase

. 1, 2 To establish the LCC baseline scenario, the De partment used distributions of efficiencies and an estimated percent of transformers currently be ing purchased using the TOC method. That scenario represents the rang e of transformer costs and efficienc ies that transformer purchasers would likely experience without national ene rgy-efficiency

standards in place.8-3

8.1.3 Total Owning Co st The utility industry

developed TOC evaluation as an easy -to-use tool to reflect the unique financial environment faced by each transformer purchaser . To express variation in such factors as the cost of electric energ y, and ca pacity and fina

ncing costs, the utility industry developed a range of evaluation factors, called A and B values, to use in their calculations. A and Bare the equivalent first costs of the no-load and load losses (in $/watt), respectively. No-load losses refer to the core losses that are roughly constant once the transformer is energized; load losses are the coil losses that vary roug

hly with the square of the load on the transformer. The TOC transformer purchasers (i.e., those using the TOC method to determine which units to buy) assign an e conomic value to transformer losses: A and B para meters. Then they add these costs to the first cost of acquiring the transfor mer, to derive TOC. The equation for calcula ting tra nsforme r TOC is: TOC = FC + (A × NLL) + (B × LL) Eq. 8.1 where: FC = first cost of acquiring the transformer, including purchase price and installation cost (2004$), A = the no-load loss valuation parameter in dollars per watt ($/W), NLL = the no-load loss at nameplate load (W), B = the load loss valuation parameter ($/W), and LL = the load loss at nameplate load (W). Throug hout the LCC analy

sis, DOE expresses monetary values in units of y

ear 2004 real dol lars.

8.2 LIFE-CY CLE COST METHO D 8.2.1 Definition The basis for both the LCC analy sis and the spreadsheet model is the LCC equation. The LCC equation reflects both the first costs of a tra nsformer and the present value of the oper ating costs over the service life of the transformer

. The L CC equation is:
Eq. 8.2 where: FC = the first cost (2004$), n = the index for the year of operation (y

r),8-4

Lifetime = the service life of the transformer, OC n = the operating cost in y ear n , including the value of the losses and maintenance costs (2004$/y r), and Drate = the discount rate applied to the calculation (%). 8.2.2 Life-Cycl e Cost Spr eadsheet Key Steps While the LCC is a simple equation , the Dep artment' s LCC spreadshe et model ta kes into account the dy

namic nature of a variety

of inputs over the service life of a transformer . A simplified

flowcha rt (Fig ure 8.2. 1) illustr

ates the key steps imple

mented in the L CC spreadsheet: the main in

puts, the k

ey computat ional step s, and the

important

outputs. The LCC s

preadsheet is available as a Excel file on the DOE website at http://www.eere.energy .gov/buildings/appliance_standards/commercial/distribution_transformers .html Sections 8.2.2.1 through 8.2.2.11 describe the computational flow of the LCC model as shown in the flowchart. Following this explanation of the analy tical steps in the model, the Department pres ents the s pecific inputs tha

t it develo ped and then used in

the L CC model for this rulemaking. Next, DOE presents the results of the LCC model runs for the various design lines. Finally , the Dep artment presents the key sensitivit ies to those

results. The LCC process is a means of de termining the financial impact resulting from the imposition of energy-efficiency standards for distribution transformers, from the perspective of the consu mer, or owner, of

the tran sformer . Severa

l typ es of inf

ormation a

re nece ssary

for this calculation: the first costs of transformers with and without standards, the opera ting costs of the transformers with and without standards, the y ear the standard is to become effec tive, and the lifetime of transformers. For ease of c omparison, DOE presents all costs in present values, which requires using discount rates. The Depar tment’s methods for determining these inputs are explained in more detail in the LCC Inputs sec tion (section 8.3). 8.2.2.1 Step 1: Select A & B Step 1: Select cust omer choice A an d B parameters fro m the choices on the “A & B Dist” worksheet. The purpose of this step is to establish the current purchasing decision environment. For liquid-immersed transformers, based on Na tional Electrical Manufacturers Associat ion (NEMA

) commen

ts, the Depa

rtment assumed that 25 percent are purchase d based on lowest first cost and 75 percent are purchased using TOC evaluation. 3 Commercial and industrial (C&I) e ntities can also apply an A - and B-based evaluation proces s for d ry-type trans forme r purch ase eva luati on. W hile t he anal ytic proc ess fo r deter mini ng8-5

Figure 8.2.1 Transformer Life-Cycle Cost Spreadsheet Model Flowcharta

In th is cha

pt er of th e TSD, LCC r es ul ts ar e de sc ri bed in t er ms o f c and id at e s ta nda rd l eve ls (CS Ls) . I n the NOPR itself, LCC results are desc ribed in terms o f trial standa rd leve ls (TS Ls). T he T SLs a re the e fficiency lev els used in post-LCC analyses and they are al so used to describe the standard level s considered by the Department for the proposed standard. T SLs are based on the CSLs selected for the LCC. How ever, because of special consi derations concern ing manufacturer im pacts and design lines (DL s) contained w ithin the same prod uct class, efficiency levels— and therefore CSLs— do not change for some standard level increments f or DL1 and DL4 . See TSD chapter 10 for a more detailed explanation. The following t able shows the mapping from the design line CSLs to the TSLs. T he analy sis reported i n thi s chapte r and in the NOPR is the s ame, but i s report ed in sl ight ly di ffe rent f ormats i n the t

wo documents, according to this CSL-to-TSL mapping.
M app ing o f the C and idate Stan dar d Le vels to Tria l Stan dar d Le vels

DL1 DL2 DL3 DL4 DL5 DL9 DL10 DL11 DL12 DL13 TSL1 CSL1 CSL1 CSL1 CSL1 CSL1 CSL1 CSL1 CSL1 CSL1 CSL1 TSL2 CSL1 CSL2 CSL2 CSL2 CSL2 CSL2 CSL2 CSL2 CSL2 CSL2 TSL3 CSL1 CSL3 CSL3 CSL3 CSL3 CSL3 CSL3 CSL3 CSL3 CSL3 TSL4 CSL2 CSL4 CSL4 CSL3 CSL4 CSL4 CSL4 CSL4 CSL4 CSL4 TSL5 CSL3 CSL5 CSL5 CSL5 CSL5 CSL5 CSL5 CSL5 CSL5 CSL5 TSL6 CSL6 CSL6 CSL6 CSL6 CSL6 CSL6 CSL6 CSL6 CSL6 CSL6

8-6 A and B values used by

C&I purchase

rs is different from that used by electric utilities, the fundame ntal mean ings of A and B ar e the same for bot

h group s of tran sformer

purchas ers. The L CC spreadsheet simu lates dif ferent transformer pur

chase e valuation scenar

ios with two different A and B distributions. All liquid-immersed transformer desig n lines use a common set of scenarios, and medium-voltage, dry -type desig

n lines also use a different but common set of scenarios. The specific inputs used in these two scenar ios are shown in se ction 8.3 o f this TSD, as well as in the “A & B Dist” worksheet of the LCC spreadsheets. These sc enarios can be se le ct ed us in g t he “T ra ns fo rm er Cu st om er A’ s a nd B’ s” pu ll -d ow n m en u o n t he “S um ma ry” worksheet. Step 2 below explains the application of these A & B distributions when actua l transformer designs are selec ted. 8.2.2.2 Step 2: Select Designs That Meet a Chosen Candidate Standard Level Step 2: Select de signs an d a cand idate sta ndard le vel. The purpose o f this step

is to select a candida te standa rd level and its as sociate d transf

ormer de signs to e

valuate with the LCC spreadsheet. The Department used NEMA’s TP 1-2002 1 as the first possible candidate standard level to evaluate, and developed five additional candida te standard levels based on information obtained from the e

nginee ring analy sis. a The additional candidate standard levels are se lected based on the properties of the distribution of engineering designs. The highest candidate standar d level is the highest efficiency for which there are at least 10 compliant desig ns from the engine ering an alysis. The nex t high est st andard level is th at lev el whi ch has the grea test e nergy8-7

savings, and y

et has approximately the same or lower LCC as the avera

ge baseline transformer. The next highest standard level is that level with the minimum LCC, and the next two lower levels are equally

spaced in efficiency

between the minimum LCC efficiency level and the TP 1- 2002 efficiency . The engineering ana lysis y ielded a cost-efficiency

relationship in the form of manufacturer se lling pr

ices, no- load losse s, and loa d losses f or a wide range of real istic transformer designs. This set of data provided the L CC model with a distribution of transformer design choices. (See the “Desig n Table” worksheet, a condensed version of the engineering analysis output.) After the user chooses a candidate standard leve l, the spreadsheet selects from its database of designs the subset of designs that satisfy the selected candidate standard level and another set of designs that satisfy the baseline scenario. In addition to the economic value of losses, other factors may

affect design selection. The Department acc ounted for such fa ctors by adding a random cost factor to the t

ransfor mer’s fi rst costs. Usi

ng this f actor, t he Depa rtment ca ptured the rang e of ty

pical re al-worl d cost var

iation in the first cost of the transf

ormer. T he Depa rtment mod

eled this r andom cost factor

as a unif ormly distribute d random n

umber tha

t can either raise

or lower the first cost of the transf

ormer by up to 15 percent. The spreadsheet selects the transformer design that has the lowest TOC (including the random cost factor) for the customer. F or each iteration cy cle, a design is chosen based on A and B distributions from Step 1. Step 2a: Calculat

e markup and insta llation co sts. For l iquid-imme rsed tra nsforme rs, which are ty

pically purchased directly by the utilities from manufacturer representatives, DOE considered the transformer purchase price to be the manufacturer selling pr ice plus a distributor markup, the shipping cost, and sales tax. It adde d installation costs separately. F or dry-ty pe transformers, the distribu tion chan nel inclu des vari ous inter

mediarie s who add t

heir own costs to the manufacturer selling price. The se costs include a manufacturer markup, distribution markup, contractor markup, shipping cost, installation costs, and sales tax. Key inputs for

this step in

clude ma rkup and installat ion costs. The Depa

rtment pr esents its specific values for these inputs in Chapter 7. 8.2.2.3 Step 3: Loa d and Pric e Profil e Step 3: The spre adsheet

model dy namicall y se lects a sa

mple tran sformer

load prof ile from distributions derived from available data. To estimate the impact of transf ormer losses on commerc ial and industrial c ompanies ’ electr icity bills, the D epartme

nt modele d the rel ationship between monthly transf

ormer load characteristics and customer de mand and usage. The Department derived distributions of load parameters from hourly load data available to it. For liquid-immersed transformers, the Department developed a n hourly transforme

r load simulation model to c apture t

he dy namics a nd economics of tr

ansformer loads

. The load profiles and cha racter istics ar e provide d in the “L

oad & Pri ce Para

meters” worksheet of the LCC spreadshe et for liquid-immersed transformers and in the “Demand & Usage ” worksheet of the LCC s preadsheet for

dry-ty pe trans formers

.8-8

For the cost of electricity, the Department used the marginal cost of ele ctricity for liquidimmersed transformers. For dry -type transf

ormers, it developed a method to calculate customer monthly bills. For

both tran sformer

typ es, the D epartme

nt calcu lated the total cost of electricity both with and without transformer losses and took the difference to ca lculate the incremental electricity c osts. Section 8.3.5 provides a detailed discussion of the electricity price analy sis. 8.2.2.4 Step 4: Calculate Cost of Losses Step 4: The spreadsheet model calculates the cost of losses by combining the incremental impacts of no-load and load losses with the loss coefficients of the design, the monthly customer load characteristics (demand and usage), and the cost of electricity . In this step, the spreadsheet combines the no-lo ad losses , load loss es, and e lectric ity p rice inf ormation f

or each transformer in the base line sce

nario an d in the ca

ndidate standards scenar

io. Subseq

uent step s extend the se costs of lo sses into the future and then c onvert them back t o presen t values. 8.2.2.5 Step 5: Project Losses and Costs into the Future Step 5: The spreadsheet model projects losses and costs into the future, base d on load growth assumptions and a forecast of future changes in electricity

price. Spreadsheet users can select different load growth and f uture electricity

price scenarios or use the medium assumptions of one percent load growth and DO E's Energy Information Administration (EI A) reference scenarios from the Annual Energy Outlook 2005 ( AEO2005 ). 4 The model applies the selected options for load growth and price trends to the curr ent cost of losses that were calculated in Step 4. Step 5 results in a projection of those losses and costs into the future. The Department presents its specific load growth and electr icity price tre

nds in the LCC inputs section (section 8.3) of this chapter. 8.2.2.6 Step 6: Select Discount Rate Step 6: To discount the future stream of costs into a present value, the sprea dsheet model selects a discount r

ate from the disco

unt rate distributi on. The LCC spreadsheet se lects a discount rate from a weighted sample of discount ra te inputs derived from financing costs of transformer pur

chasers. The De

partmen t presen ts its spec ific disc ount rate s in the LCC inputs section (section 8.3) of this chapter. 8.2.2.7 Step 7: Calculate Present Value of Future Cost of Losses Step 7: The spreadsheet model calculates the pre sent value of future operating costs and losses and the present worth per watt of no-load and load losses. This step applies the discount rate selected in Step 6 to the future costs of losses from Step 5 to produce a single, present-valued number. In addition to the costs from Step 5 above, the c alculation uses as inputs the effective date of the standard, the transformer lifetime, maintena nce costs, and a power factor.8-9

8.2.2.8 Step 8: Results Reported Step 8: The spreadsheet model records the LCC, LCC savings, pay back period, and other results for inclusion in the distribution of results. This is a reporting step. The model uses the inputs in a set of calculations and reports the results. Depending on the application, different kinds of results can be reported, e.g., L CC savings, payba

ck periods, or equivalent A and B values. The default report includes LCC savings for each candidate standar d level over the baseline scenar io; it reports the me an value , plus the p ercent age of purchas ers with p ositive LCC sa vi ng s. Pa yba ck pe ri od s a re re po rt ed se pa ra te ly. 8.2.2.9 Step 9: Results of Sample of Transformers Step 9: The spreadsheet model repeats the ca lculation until reaching the specified maximum number of iterations. When applying a Monte Car lo simulation process, the model performs a user-defined number of iter ations and reports the results as distributions. Based on the Department’s experience with expressing results of prior r ulemakings as distributions, 10,000 it er at io ns in a M on te Ca rl o s im ul at io n c ap tu re su ff ic ie nt va ri ab il it y. 8.2.2.10 Step 10: R

esults for “Average ” Scenario Step 10: The spreadsheet model reports the results of the ca lculation for the “Average” scenario on the “Summary ” worksheet of the LCC sprea dsheet. The “Average”

scenario allows users to produce provisional answers without performing aMonte Carlo simulation. For liquidimme rsed t ransfo rmers , the D epartm ent ex tract ed the margin al dem and co st and margin al ener gy cost used in the average scena rio calculation from a representative LCC Monte Carlo simulation. Similarly, for dry

-type transf

ormers, the Department extracted an avera ge marginal demand and energy rate from a sample dry

-type Monte Carlo simulation. 8.2.2.11 Repeat P rocess The specific number of iterations required for the Monte Carlo simulation is implemented through the <Repeat Process> decision box. When the desired number of iterations has been reache d, the mode l ends the simulation

process and ge nerate s result r

eports. 8.3 LIFE-CY CLE COST INPUTS This section presents the specific LCC inputs used in the sprea dsheet model and provides definitions and da

ta sourc es for e ach comp onent. Th is section also ela borates on how the

LCC spreadsheets apply

certain user-chosen inputs to the L CC model. The specific inputs to the model, in the order in which they appear on the left-hand side of the LCC flowchart (Figure 8.2.1), are:8-10

C A and B transformer selection para meters and usage rates

C Database of transformer desig ns
C Markup a

nd installa

tion costs

C Transformer loading

C Electricity costs and pr ices

C Load growth tre

nds

C Electricity cost and pr ice trends

C Discount r

ate
C Effective date of standard

C Transformer service life

C Maintena

nce costs
C Power factor 8.3.1 A and B Transformer Selection Parameters and Usage Rates The A and B transformer selection parameters that DOE used in the formal TOC calculation can also be used more ge nerally to cha

racterize the value that transformer purc hasers place on reducing no-load and load losses in tra nsformers. This is because the A and B parameters expre ss a meas ure of the economic value of loss re duction in

terms of d

ollars pe r watt of reduced losses. The ability to measure the economic value of loss reduction in units of dollars per watt is independent of the actual method for estimating tha t value. The main assumption implicit in using A and B values to represent customer transfor mer choice decisions is that the value of loss redu ction is pr oportiona l to the amo

unt by which loss es are r

educed . Given th

is wider applicability of the TOC formulation to the expression of loss valuations, the Department used A and B parameters to formulate a transformer customer choice model. To represent the potential range of purchaser valuations given to transformer no-load and load losse s, the De

partmen t developed three A and B distributions to represent three customer choice scenarios for each L CC calculation. The key dif ference among the three

scenarios is the fraction of purc

hasers w ho are e stimated t

o place a value on r

educing transformer loss es. Those who plac e a value

on reduc ing such

losses ar e descr ibed as evaluato rs , while those who do not consider transformer losses during a purc hase are termed non-eva luators . The sce nario repres enting n

on-eval uation for all purc

hases ha s 0 perce

nt evalua tors, whil e the sce

nario representing evaluation for all purc hases has 100 percent evaluators. For liquid-immersed transformers, many purchases are evaluated, so the De partment’s default scenar io is an evaluation

rate of 75 perce nt, which is approxima

tely consiste nt with dat

a provided by N EMA 3 regarding the fra

ction of transformers that are TP 1-compliant. As the voluntary industry

standard for transformer efficie ncy, TP 1 has its compliance tra cked by NEMA. NEMA express es the da ta that is a

vailable regar ding cu rrent ma rket ef ficienc ies in ter

ms of TP1 compliance, rather than as an effic iency distribution. The Depa rtment extrapolated this TP 1 compliance data to an estimated distribution of market efficiencie s. Table 8.3.1 provides the evaluat ion usag e rates , for the

three e valuation scenar

ios just des cribed, for a ra nge of differe nt A values for liquid-immersed transformers. For medium-voltage, dry-ty pe transformers, the8-11

Department assumed 50 percent evaluators for small-capacity

transformers—design line (DL ) 9 and DL 11 (Table 8.3.2)—a nd 80 percent for large-c apacity tra nsformers—DLs 10, 12, and 13 (Table 8 .3.3). These def

ault sce narios pr oduced r esults rou ghly consiste nt with NEM

A data regarding the fra

ction of transformers compliant with TP 1 in the current market. The Depa rtment use d the 0 per

cent and 100 perc ent eval

uation sc enarios

to test the

LCC sensitivity to change s in the percentage of transfor mers purchased using evaluation. I t estimated the mean value of A for evaluators from va lues provided by stakeholde rs and collected from public tra nsforme r purchase bids available on the I nternet
. 5, 6, 7, 8, 9, 10, 11 Then, recognizing that there is substantial variability in the value tha t transformer purchasers may place on reducing losses, the Depar

tment cre ated a di stribution that represente d this var

iability, as illustr

ated in Tables 8.3.1 through 8.3.3. For liquid-immersed transformers, the Department estimated an average A value of $3.85/wa tt for evaluated purchases from the available data. The Department used a slightly smaller

average A value of $2.50/wa tt for dry-ty

pe transformers, based on stakehol der comm

ents.8-12

Table 8.3.1 Distributions of A Values for Liquid-Immersed Transformers: Three

Scenarios with Usage Percentages 0% Non-Evaluati ng 75% M edium- Evaluati ng 100% High-Evaluat ing A $ Proba bility

% A

$ Proba bility

% A

$ Proba bility

% 0.00 100.00 0.00 25.00 0.00 0.00 0.39 0.64 0.39 0.85 0.77 1.28 0.77 1.71 1.16 2.24 1.16 2.99 1.54 3.20 1.54 4.27 1.93 4.27 1.93 5.70 2.31 5.34 2.31 7.12 2.70 6.01 2.70 8.01 3.08 6.68 3.08 8.90 3.47 6.68 3.47 8.90 3.85 6.68 3.85 8.90 4.24 6.12 4.24 8.16 4.62 5.56 4.62 7.42 5.01 4.77 5.01 6.36 5.39 3.97 5.39 5.30 5.78 3.23 5.78 4.30 6.16 2.48 6.16 3.31 6.55 1.93 6.55 2.58 6.93 1.38 6.93 1.84 7.32 1.03 7.32 1.38 7.70 0.69 7.70 0.92 8.09 0.50 8.09 0.67 8.47 0.31 8.47 0.42

Table 8.3.2 Distributions of A Values for Small -Capacit y, Medium-Voltage , Dry-Typ e8-13 Transformers (DL 9 and DL 11): Three Scenarios with Usage Percentage s 0% Non-Evaluati ng 50% M edium- Evaluati ng 100% High-Evaluat ing A $ Proba bility

% A

$ Proba bility

% A

$ Proba bility

% 0.00 100.00 0.00 50.00 0.00 0.00 0.25 0.93 0.25 1.86 0.50 1.86 0.50 3.72 0.75 2.79 0.75 5.57 1.00 3.72 1.00 7.43 1.25 4.34 1.25 8.67 1.50 4.95 1.50 9.91 1.75 4.95 1.75 9.91 2.00 4.95 2.00 9.91 2.25 4.46 2.25 8.92 2.50 3.96 2.50 7.93 2.75 3.30 2.75 6.61 3.00 2.64 3.00 5.29 3.25 2.08 3.25 4.15 3.50 1.51 3.50 3.02 3.75 1.13 3.75 2.27 4.00 0.76 4.00 1.51 4.25 0.55 4.25 1.09 4.50 0.34 4.50 0.67 4.75 0.23 4.75 0.47 5.00 0.13 5.00 0.27 5.25 0.09 5.25 0.18 5.50 0.05 5.50 0.108-14

Table 8.3.3 Distributions of A Values for Large -Capacit y, Medium-Voltage , Dry-Typ e Transformers (DL 10, DL 12, and DL 13): Three Scenarios with Usage Percentages 0% Non-Evaluati ng 80% M edium- Evaluati ng 100% High-Evaluat ing A $ Proba bility

% A

$ Proba bility

% A

$ Proba bility

% 0.00 100.00 0.00 20.00 0.00 0.00 0.40 1.49 0.40 1.86 0.80 2.97 0.80 3.72 1.20 4.46 1.20 5.57 1.60 5.95 1.60 7.43 2.00 6.94 2.00 8.67 2.40 7.93 2.40 9.91 2.80 7.93 2.80 9.91 3.20 7.93 3.20 9.91 3.60 7.13 3.60 8.92 4.00 6.34 4.00 7.93 4.40 5.29 4.40 6.61 4.80 4.23 4.80 5.29 5.20 3.32 5.20 4.15 5.60 2.42 5.60 3.02 6.00 1.81 6.00 2.27 6.40 1.21 6.40 1.51 6.80 0.87 6.80 1.09 7.20 054 7.20 0.67 7.60 0.38 7.60 0.47 8.00 0.21 8.00 0.27 8.40 0.15 8.40 0.18 8.80 0.08 8.80 0.10
For each value of A that a transf ormer purchaser may

have, there is a range of

possible B values that are consistent with the particular A value. (Bvalues relate to the value associated with the load losses.) In gene ral, the ratio of B to A is a measure of the re lative importance of load losses and no-load losses. For a transformer that is constantly loaded at 100 percent of rated ca pa ci ty, th e v al ue of

B a nd A s ho ul d b e t he sa me , s in ce bo th lo ad an d n o- lo ad lo ss es wi ll al wa ys be at their rated values. L oad losses increase with the square of the loading , and transformer mean loadings are almost alway s below 100 percent. Therefore, in pra ctice, B is always less than A, and is approximately equal to A times the square of the expected loading (when peak loads ar e not considered). The Department characterized the re lationship between customer selection of B and A8-15

values by selec

ting five possible values for the B:A ratio. For liquid-immerse d transformers, the Department sele cted a B :A ratio o f 0.30 (a pproximate ly the square

of 50 per cent) a s a reas onable median value, based on the evaluation parameter data for utilities available to the Department. For dry-type transf

ormers, the Department estimated the median ratio of B :A as the square of the transformer efficiency

standard evaluation loading. To model variability in the ratio of B:A, the Department selected four other values for the ratio between 0 and 1: 0.6 × MedianBA , 0.8 × MedianBA , 0.15 + 0.85 × MedianBA , and 0.35 + 0.65 × MedianBA , where MedianBA is the median value of the B:A ratio. These four va lues of the ratio provide a distribution between 0 and 1 that has the estimated median value for the B:A ra tio and that matches the properties of the evaluat ion para meter da ta availa ble to the Department. As described above, the Department selected slightly differ ent median B:A ratios for liquid-immersed and dry-ty pe transformers. The higher B :A ratio for liquid-immersed transformers reflects the more ca reful evaluation of peak load impacts of load losses on the part of utilities. The B:A ratio for dry -type customers r

eflects an assumption that commercial and industrial customers will tend to value their load losses with an average e lectricity price

. The Department calculated present wor th factors for no-load and load losses so that stakehol ders cou

ld compar

e the De partmen t’s LC C results w

ith the A a

nd B valu es that some purchasers use in their TOC evaluation. The Depar tment defines the present worth factor for transformer losses as the present value of the c ost of losses per unit rated loss. Rated losses are measured in watts at the rated load. There a re distinct present worth factors for no-load and load losses. The prese

nt worth f actors a re diffe rent from the A and

B value s that a pu

rchase r may use for TOC evaluation because the reg ulatory context is different. Ty pically, the A and Bvalues used for TOC evalu

ation ar e calcu lated ba sed on the

economic

assumption s inhere

nt in electric utility rate re gulation, and ar

e specif ied by the I nstitute of

Electric al and Ele ctronic s Engine ers' Draft Guide for Distribution Transformer Loss Evaluation. 2 In contrast, the methods for calcula ting L CC values f

or ener gy-effic iency

regula tions are specifie d by

EPCA. The e conomic assumptions of the LCC calculation differs slightly from rate regulation in the sense that it is not based on the principal of cost recovery for all associated expenses, but it is instead based on a cost accounting for the use of a spec ific appliance or piece of equipment. To summar

ize, the De

partmen t chara cterized transformer pur

chases w ith respe ct to efficiency in terms of two economic valuation parameters. The par ameter A expresses the value that a customer gives to reducing no-loa d losses in dollars per watt, while the parameter B expresses the value given to reducing load losses a t rated load. The Department described purchase behavior in terms of evaluators who plac e a value on reducing losses, and nonevaluators who place no value on reducing losses in their purchase behavior. The Department investigated three scenarios as sensitivities. For liquid-immersed tra nsformers, the scenarios are 0 p er ce nt ev al ua to rs , 7 5 p er ce nt ev al ua to rs , a nd 10 0 p er ce nt ev al ua to rs . F or sm al l- ca pa ci ty, medium-voltage, dry

-type transf

ormers, the scenarios are 0 perc ent evaluators, 50 percent evaluators, and 100 percent evaluators. F or large-capacity , medium-voltage, dry

-type transformers, the scenarios are 0 pe rcent evaluators, 80 percent evalua tors, and 100 percent evaluat ors. The Department sele cted eva luation pe rcenta ges tha t are ro ughly consiste nt with8-16

NEMA data regarding

the fraction of transformers compliant with TP 1 in the current marke t. For eva luators, the Depa

rtment use s a distrib

ution of A a

nd B valu es to cha racter ize their behavior . The mea

n of the di stribution

of A values is dete

rmined fr om stakeholder an

d public data re gardin

g evalu ation par ameters availab le to the D epartme nt. Once the Depa rtment chose the A value, it then chose a value for B of le ss than A, using a B:A ratio. The Department based the B:A ratio on the statistical characteristics of the eva luation parameter data that are available

. 8.3.2 Database

of Transform er Desig ns Establishing a relationship between cost and efficie ncy is an integ

ral part of the rulemaking process. For transfor mers, DOE derived this relationship from an enginee ring analy sis datab ase of se lling pr

ices, no- load losse s, and loa d losses f or a wide range of real istic transformer designs contained in the LCC spreadsheets. The Department used a commerc ial transformer de sign sof

tware c ompany, Optimized Progra m Service

Inc ., and its s oftware

to crea te the database of designs. The database consists of a wide range of ef ficiencies and manufacturer sale prices (including a predeter mined manufacturer markup) to represe nt the variability of designs in the marketplace. The engineering analysis (see Chapter 5) provides more detail on the databas e structu

re and the method u sed to ge nerate this datab ase of tr

ansformer desig

ns. 8.3.3 Markup and Installation Costs Markups, shipping

costs, sa les tax, and installa

tion costs a

re the c osts assoc iated wit h bringing a manufactured tr ansformer into service as an installed piece of e lectrical equipment. For liquid-immersed transformers, which utilities ty pically purchase directly fr om manufacturers, DOE considered the tra nsformer purchase price to be the manuf acturer selling price plus a distributor markup, the shipping cost, and sales tax. I nstallation costs were added separately . For dry-type transf ormers, the distribution channel includes various intermediaries who add their own costs to the manufacturer selling pr ice. These costs include a manufacturer markup, distribution markup, contractor markup, shipping cost, installation costs, and sales tax. See Chapt

er 7 for a detaile d discussi on of the markup ca lculation s. 8.3.4 Transform er Loading To estimate the economic burdens and benefits of eff iciency improveme

nts, the Department characterized the ener gy use and losses of the equipment being analy zed, by estimating the loads on them. Because the applica tion of distribution transformers varies signific antly

by t ype of trans former (liquid-imme rsed or d ry-ty pe) and o wnership (electr ic utilities ow

n liquid-im

mersed 9 5 perce

nt of the ti

me, comme

rcial/in dustrial e ntities use

mainly dry-ty pe), the Department performed two sepa rate load analyses to evaluate distribution transformer efficiency : one for liquid-immersed transformers and a second for dry-ty pe transformers. Chapter 6 d escribe s these two separa te load a nalyses.8-17

8.3.5 Electri city Pr

ice Analy sis This section describes the electricity price analy ses the Department used to determine the energy portion of the annual operating expenses for distribution transformers. The electric power industry is currently

in a state of transition between two different business models, from reg ulated monopoly utilities providing bundled service to a ll customers in their service area, to a sy stem of deregulated, independent suppliers who compe te for customers. While it is unclear if and when this transition will be completed, it is possible that, in the near future, customers will see a very different pricing structure for e lectricity. To account for the impacts of this situation on the LCC, the Depa rtment performed two typ es of loa

d analy sis to eva luate dist ribution tr

ansformer eff

iciency. The first ty

pe of ana lys is investig ated the

nature o f hourly

transformer loa

ds, their correl ation with

the over all utility system load, and their cor relation with hourly elec

tricity costs and price s. The second type of analysis estimated the impacts of tr ansformer loads and the resultant transformer losses on the monthly electricity

usage, demand, and electricity bills of C&I customers. The Depa rtment refers to the two a

nalyses as hourly

and monthly

analyses, re spectively. The D epartment used the hourly analy

sis for the economic analysis of liquid-immersed transformers, which are predominantly owned by

utilities whose costs vary by the hour. The Department used the monthly analysis to eval uate dry-type transformers, wh ich are typically owned by C&I establishments that receive monthly e lectricity bills. 8.3.5.1 Hourly Marginal Electricity Price Model for Liquid-Imme rsed Transformers For liquid-immersed transformers, the Department used ma rginal electricity

prices. Marginal electricity

prices are the prices experienced by utilities for the last kilowatt-hour (kWh) of electricity

produced. A utility’s marg inal price can be higher or lowe r than its average price, depending on the relationships between capa city, ge neration, transmission, and distribution costs. The ge neral str ucture o f the hour

ly ma rginal cost equa tion divide s the cost s of electricity into capacity components and energy

cost components. The capacity components include generation capacity , transmission capacity, a nd distribution capacity. Capac ity components also include a reserve margin neede d to ensure system re liability. Energy cost components include a marginal cost of supply that varies by the hour, factors that account for losses, and cost re covery of associated marginal expenses. The Depar tment applied Equation 8.3 to calculate the marginal cost of supply of elec

tricity to cover tra

nsformer losses. MEC = (1 + CM) × (GC × IGC + TC× ITC + DC × IDC ) + (LAF × EC(hour) + RF) × IEU(h our) Eq. 8.3 where: MEC = marginal electricity cost (2004$), CM = sys te m c ap ac it y ma rg in re qu ir ed fo r r el ia bi li ty,8-18

GC = unit cost of generation capacity ($/kW), IGC = incremental system c apacity re quired by the load ( kW), TC = unit cost of transmission capacity ($/kW), ITC = incremental transmission capacity required by

the load (kW), DC = unit cost of (non-transformer) distribution capacity ($/kW), IDC = incremental distribution capacity required by

the load (kW), LAF = load adju stment fa ctor, wh ich is one plus the e stimated syst

em losses, EC(hour ) = hourly cost of elec trical energy, either from a market or from fuel and operating cost data ($/kWh), RF = additional cost recovery factor ($/kWh), and IEU(h our) = incremental energy use (kWh). The Depa rtment ca lculated the vari ous inputs o f this equation as f ollows: Capacity Margin (CM). This is the fraction of extra or reserve capac ity needed to ensur e system reliability

per unit of additional capacity requirement. The Department used the industry standar d of 15 pe rcent. Unit Generation Capacity Cost (GC). This is the annualized cost of unit generating capacity for the particular load being serve d. It includes the cost of capital during the construction period, and the loss adjustment factor to account for losses betwe en the generator and end-use load. The EI A's AEO2003 provides forecasts of such costs for differe nt generation technolo gies. 12 The capacity cost depends on the type of load being served and the source of the electri city . For ba se load, D OE used the capac ity c ost for a pulverize d coal pla

nt, since this is curren tly t he least-cost, base-load

technolo gy . For pe ak loads, such as those assoc iated wit h transformer peak-load losses, it used conventional combustion turbine capa city costs as the releva nt marginal cap acity

cost. The

Department obtai

ned its estimates f

or generation

capaci ty costs from data and estimates contained in the AEO2003 forecast and adj usted the values to 2004$ usin

g the g ross dome stic prod

uct (GDP)

price de flator f

rom AEO2005

. 4 These costs are shown in Table 8.3.4 as reported in the AEO2003 forecast in 2000$.8-19

Table 8.3.4 Generation Capacity Costs Technology Year Cost 2000$/kW Conventional Pulverized Coal 2001 1,119 2010 1,083 2020 1,056 Conventional Gas Combined Cy cle 2001 456

2010 448 2020 438 Conventional Gas Combustion Turbine 2001 339 2010 333 2020 326 Incremental G

eneration C

apacity Re

quirement (

IGC ) . This is the amount of generation capacity required by

a load. For the core-loss component, this is equal to the core losses times the loss adjustment factor (see LAF below). For the load-loss component, DOE estimated this by multiplying the peak re sponsibility factor (PRF) by the transformer peak load and fee ding the result to the load-loss equation. PRF is the fraction of the transformer pea k that is coincident with the sy

stem pea k. The De

partmen t calcula ted a first-y

ear PRF. Note that

there is a multi-year dela

y betwee n the time when new capacity is contracted and when it becomes available. AEO2003 capaci ty c ost fore casts ar

e express ed in ter

ms of when

the capa city is contracted. The Department translated this cost into the cost at first y ear of service by

adding capital costs as determined by the discount rate. The Department annualized costs by applying the capital recovery

factor to capacity

costs, assuming that such capacity has a 30-ye ar lifetime. Unit Transmission Capacity Cost (TC). This is the annualized cost per unit for an increme nt of new transmiss ion capa

city . The Dep artment o

btained t ransmissi on capa

city costs from the estimates made by EIA for eac

h of 13 transmission regions in the AEO2003 for eca st . It used the value of $166/kW, which is the average mar ginal transmission capacity cost for all 13 transmission regions in 2000$, and adjusted it to 2004$ using the GDP price deflator fr om AEO2005

. Incremental Transmission C apacity Requirement (ITC). This is the amount of transmission capacity re quired by an incr emental load. The Department assumed that the transmiss ion capa

city require ment is the

same as the gene

ration c apacity

require ment. Unit Distribution Capacity Cost (DC). This is the cost per unit of distribution capacity. The Department used distribution capacity costs from the U.S. Federal Energy Regulatory Commission (FERC) Form 1 data on the investment in transformers, substations, lines, and feeders per unit of system peak, 13 as analyzed and published by the Regulatory

Assistance Project. 14 The Department used the average cost of distribution capacity per kilowatt of system8-20

peak, and assumed that the real price of distribution capa city is constant (i.e., has no tre nd up or down). The estimated distribution capacity cost for the analy sis is $276/kW in 2000$, which DOE adju sted to 200 4$ using the GDP pr

ice def lator fr om AEO2005

. Incremental Distribution Capacity Requirem ent (IDC). This is the amount of distribution capacity requir ed by an incr

emental load. The Department assumed this to be the same as the peak incremental energ y use. Loss Adjustment Factor (LAF). The loss a djustment f

actor is t he fact or that one must multiply with an end-use load to estimate the amount of sy stem electricity ne eded to supply that load. It is one plus the fractional losses in the sy stem. The Department assumed it to have a constant value of 1.08. Hourly Energy Cost (EC). This is the hourly marginal energy cost that DOE obtained from utility system lambda data or market data. Since DOE obtained this cost from marke t data, it assumed it to include generation capacity effects and the gener

ation capacity

cost to be zero. Additional Cost Recovery Factor (RF). This is a f actor that DOE ad

ded to the hourly energy cost to account for costs besides energy losses that are associated with supply ing that energy . The Department obtained the per-kWh additional cost recove ry fac tors in Table 8.3.5 using real-time pricing formulas from the utilities listed in the table. Such fac tors are necessary for marking up the cost of gene ration to account for other costs that scale with ge neration, but that are not includ

ed in such

costs. Suc

h costs ma

y include ac counts pa

ya ble, acc ounts receivable, an

d operat ing cap ital costs , which wi ll have a componen

t that sca les with the volume of electricity

sales. Table 8.3.5 Representative Cost Recovery F actors Utility Recovery Factor Illinois Power Company 0.5 cents /kWh (five -year con

tract) Pacific Gas and Electric Co. 0.346 cent s/kWh PSI Energy

Inc. 10% to 25% of EC(hour ) × LAF Carolina Power and Lig

ht 20% of EC(hour ) Union Light, Heat, and Power Company 10% of EC(hou r) × LAF Based on this ran

ge of o bserved cost-re covery

factors, DOE as sumed tha t the cost recovery factor is approximately 0.15 (i.e., 15 pe rcent) of the cost of energ y. Incremental Energy Use (IEU). This is the incremental hourly e nergy use calculated from the t ransfor mer load ing that is obtaine d from the

formula f

or the tra nsforme r losses.8-21

8.3.5.2 Monthly Tariff-Based Analysis for Dry-Type Transformers This section gives an overview of the tariff- based analy sis of electricity pric es for dry-type transformers. The Department updated the utility tariffs used in the monthly ana lysis to 2004. Although the electricity

prices were updated, the Depar tment used the same distribution of utilities as it used in the advance notice of proposed rulemaking (A NOPR) analysis, which was derived from year 2000 data. Selection of the Sample Utilities

. The Department used three main criteria in de veloping the utility sample for the utility tariff formulas: 1) The sample of utilities should reflect the distribution of population across the country, with more utilities drawn from more populated areas; 2) the sample should reflect the proportion of c ustomers served by pr

ivately owned e

ntities (i.e., investor-owned utilities (IOUs) a nd power marketers) versus publicly owned utilities (i.e., municipals, cooperatives, State, and Federal); and 3) the sample should cover as many customers as possibl e. Data

on utilitie s are available f rom the EI

A throug h their F orm 861 fi lings. 15 This form is filed annually by

every utility

that sells power to final consumers, and includes information on the total sales in megawatt-hours (MWh), total revenues, a nd the numbers of customers. Utilities supply this information separately for the residential, commercial, and industria l sectors . The Dep artment u sed data from the y

ear 2000 in this ana

lys is. The Depa rtment fi rst scre ened the

set of util ities in the

EIA d atabase to conside

r only those with customers in all three sectors (residential, commercial, industrial). I t then computed, for each subdivision, the percentage of customers served by

public versus private utilities. The Department chose the sample utilities to reflect the relative population of the subdivision and the proporti on of publi c-to-pr ivate cu stomers. I

n most are as, the D epartme nt include d the lar

gest utilities in the sample to maximize the number of customers represented, but it also included smaller private utilities and public utilities of all sizes. The final set of sampled utilities included 49 privat ely owned an

d 41 public ly owned com panies. The EI A data for 2000 show that power mark eters a nd other providers of unbun dled ret ail services serve approximately two percent of the commercial customers in the country. Power marketers have the large st market share in New England, so the Depa rtment included one such company in its sampl e for this

region . Appendi

x 8C contains

a list of the sample

utilities. Subdivision o

f the Country . Beca

use of the wide var iation in e lectric ity usage p atterns, wholesale costs, and retail rates across the countr y, it is important to consider regional differences in models of electricity pr ices. For this reason, the Department divided the continental United States into 17 regions or subdivisions as illustrated in Figure 8.3.1. To make maximum use of the location information in DOE’s Commercial Building Energ y Consumption Survey (CBECS), 16 the breakdown started with the nine U.S. Census divisions. The Department further subdivided these to take into account significant climate variation and the e xistence of different electri city market or grid structure s. The De partmen t based c limate div

isions on the nine cl imate regions defined for the continental U.S. by the National Climatic Data Center. 17 In a ddition, it separated out Texas, Florida, New York, and California because their electric gr

ids are operated8-22

Figure 8.3.1 Map Showing the Division of the Continental United States

into 17 Subdivi sions independently. F igure 8.3.1 illustrates the results. In the figure, the subdivision numbers use the CBECS U.S. Census Division code as the first digit. For example, U.S. Census Division 8 (Mountain) has been separated into two subdivisions, 8.1 and 8.2.

Represe ntativene ss of the Sample . For this rulemaking, the Department defined the representativeness of the sample by the percentage of the total number of C&I customers that were covered. I

t is relatively easy

to get good representation for I OUs, because in most regions there are a few large companies serving many customers. It is more difficult to repre sent the publicly owned companie s, as these tend to be much smaller; to obtain the same level of customer representation, DOE would need to include many more utilities. The sampled utilities serve 60 percent of the C&I customers of private utilities, and 14.4 percent of C&I customers of public util ities. The

combined

total for the U.S. is

48.5 per cent of a ll C&I customers. Table 8.3.6 gives the percentage of customers by subdivision, broken down by ownership type.8-23

Table 8.3.6 Perc entage o f All Comm ercial a nd Industrial C ustome rs, by Subdivis ion, in

the Utili ty Sample

Subdivi sion U.S. Cens us

Divis ion Region Pu blic Customers in Sa mple % Private

Customers in Sa mple % Percent age

of Total Customers in Sa mple % Number of

Customers in Sa mple

1 New E ngland New E ngland 3.7 43.9 40.3 310,505 2.1 M iddle Atlantic New Y ork 88.2 72.4 74.7 671,407 2.2 M iddle Atlantic PA, NJ 7.9 50.6 49.4 504,466 3 East North Cent ral WI, I L, I N, OH, MI 8.5 43.5 39.1 831,124 4.1 W est North

Central MN, I A, MO 5.4 27.0 12.4 44,823 4.2 W est North

Central ND,S D,NE ,KS 9.8 59.0 46.5 387,603 5.1 Sou th Atlan tic DE , MD, VA , WV 13.4 72.9 67.5 552,058 5.2 Sou th Atlan tic NC, SC, GA 11.8 88.9 64.3 778,500 5.3 Sou th Atlan tic Flori da 15.1 72.0 58.4 530,513 6.1 East SouthCentral KY, TN 11.5 47.2 20.6 128,694 6.2 East SouthCentral MS,AL 9.9 68.5 42.9 217,970 7.1 W est Sout

h Central OK,AR,LA 3.5 60.4 44.1 265,412 7.2 W est Sout

h Central Texas 18.2 23.8 22.2 272,077 8.1 M ounta in MT, I D, WY 10.5 52.2 39.6 70,323 8.2 M ounta in NV,U T,C O,A Z, NM 5.9 71.8 46.2 310,765 9.1 Pac ific WA,OR 16.5 47.9 38.1 243,271 9.2 Pac ific Califo rnia 20.3 97.4 75.8 1,050, 862

Na tional S amp le USA 14.4 60.0 48.5 7,170, 373 The ratio of total revenues to total energy sales—which reflects, on average, the amount of money collecte d for ea

ch kWh sold—

also var ies sign ificantl y be tween uti lities and

across different regions. Figur

e 8.3.2 illustrates the degree of varia tion. The figure plots the customer-weighted average of utility revenue s divided by sales (in units of $/kWh) within each subdivision. The vertical bars show the average value, plus or minus one standard deviation, for all the utilities in the EIA data. The points show the customer-we ighted average r evenues divided by s ales for

the sample d utilities only . There is a large sprea

d in the EI

A data, a nd sample averages are within this range.8-24

Figure 8.3.2 Custom er-Wei ghted Ave rage of Ut ility Rev enue Divide d by Sales by Subdivi sion ($/kWh)
Utility We

ights

. The way in whic

h the Department assigned weights to the utilities depended on the application. As will be discussed in more detail below, the marg inal rate seen by a particu lar customer depe

nds both on

the tarif f and on that custome

r’s ene rgy use characteristics. The appropriate weight for a utility is the number of customers it has divided by the number of customers in the subdivision. The weights for all the utilities in a given subdivision thus add up

to one. B ecause

the leve l of customer representa tion for p ublic utili ties is much less than for private ones, the Department included an a dditional factor to account for the differenc e, so that the

total wei ght of the sample ’s public utilities e quals the

fraction of public

customers in that subdivision. Th e w ei gh t f

or ut il it y k

is: Weight(k, own_ type) = ( n (k,own _type )/n(own _type

) ) × ( N(own_ type)/

N), Eq. 8.4 where own_type = pub (public) or priv (private). By

definition, 3 (own_type) 3 (k) W

eight(k,own_type) = 1. Eq. 8.5 where:8-25

n(k,pub ) = nu mb er of cu st om er s s er ve d b y pu bl ic ly o wn ed sa mp le ut il it y k, n(k,priv) = nu mb er of cu st om er s s er ve d b y pr iv at el y ow ne d s am pl e u ti li ty k, n(pub) = sum(k) n(

k,pub) = total customers se rved by publicly owned sa mple utilities, n(priv ) = sum(k) n(

k,priv) = total customers se rved by private ly owned sam

ple utilities, N(pub) = total customers served by all publicly owned utilities in the subdivision, N(pri v) = total customers served by all privately owned utilities in the subdivision, and N = N(pub) + N(priv) = total customers in the subdivision. 8.3.5.3 Data Coll ection and Modeling This section describes the data collection method, the selection of tariff s for a given utility , and how D OE modele d the tar iffs. Web Search . The Dep artment c ollected the vast ma

jority of the ta riff doc uments dir

ectly from utility web sites. Almost every privately owned utility

in the sample makes its whole tariff structure available on the web, although not alwa ys in easily

readable form. I

n many case s, the full tariff, as approved by the relevant State public utility commission, is published and the actual customer rates ha ve to be tr

acked d own within

this document. Many

public util ities also

put their rate information on the web. I n cases where web documents were not available, the Department contacted the utilities directly. The list of utilities in Appendix 8C also includes a uniform re so ur ce lo ca to r ( UR L) f

or ea ch co mp an y. Selection of Tariff

s for Each U

tility . Utility

companie s have ma

ny t ariffs, separa

ted into residential, non-residential, and special-use—such as public stre et-lighting or agricultura l. For the non-residential category , some utilities use the commercial-industrial distinction, but many do not. Therefore, in its tariff database, the De partment combined these into one customer categor y. The goal in collecting the tariffs was to cover the full range of C&I customer types for

each utility. I n most cases, the Department assigned customers to a spe cific tariff based on their peak demand over the previous 12 months. In a f ew cases, the assignment was based on the maximum monthly electricity

consumption. Customers are not generally moved from one tariff to another. Most utilities offer only one tariff f or each customer size. Some of the larger utilities offer o ptional time-of-u se (TOU) or real -time-pr

icing (RTP) tarif

fs. Occ asionally

, utilities w

ill offer different tariffs for diff erent business types. I

n all of the cases checked, although the tariffs had different names, the rates were in fact the same. Some utilities do not specify r ates for very large customers whose pe ak deman d is on the order of

thousands

of kWs; inste ad they

negotia te them on a case-by

-case basis. For the L CC calculation, the Department used only tariffs that depend on usage and demand data ( not TOU nor RTP tariffs), because the energ y consumption data it used in its analysis included only monthly demand and usage. The Department’s sampling strategy was to take the default tariff for eac h customer class.8-26

The Depa rtment exc luded “c losed” ta riffs; these are

tariffs that are being phased ou

t by the utility and so are not available to new customers. This suggests that such tariffs do not reflect rates that will be seen by the major ity of customers in the future

. Utilities do not generally

make information available on how many customers are on each tariff; however, this infor mation is not actuall

y ne eded for

the L CC. In stead, w

hat is impor

tant to know is the relative numbers of customers who use the distribution transformer equipment covere d by

the stand ard who a re on dif ferent tariffs . The CBE CS data on t he buildin

g weig hts define the relative proportion of customers of differ ent sizes (here size refers to the customer’s peak load), and the building monthly load data provide the annual peak load—which DOE use d to assign a customer to a tariff. The Tariff Model . To calc ulate a c ustomer’ s electr

icity bill requi res two se ts of inputs : the rates charged as de fined by the tar iff, and information on the customer’s energy use. The customer data consist of the billing demand (i.e., the customer’s pe ak demand over the billing month) and total energy

consumption for the current billing period. I n its analysis, the Department assumed the billing period to be one calenda r month. While the formulae determining the actual bill can be quite complex, they are based on three ty

pes of charges: fixed, energy, and deman d. Fix ed char ges are t hose p aid eac h mon th regar dless of the level of ener gy use. They do not contribute to c ustomer marginal rates and so do not have any impact on the oper ating cost s avings us ed in

the LCC. Energ

y c harges ar e spe cifi ed in

unitsof ce

nts (¢ )/kWh and depe nd on the c

ustomer’ s total ene

rgy consumpti on. Dema

nd charges are s

pecifie d in units of $/kW and depend on the customer’s monthly billing demand. For most of the utilities in the sa mp le , c ha rg es al so va ry s ea so na ll y. Energy and demand charges are

typically applied in blocks. This means the customer pays one rate for e nerg y u se or dema nd up t o a ce rtai n lev el, a second ra

te for usa ge u p to the next leve l, and so on . For

examp le, in

a tar iff with th ree b lock s, the

ener gy char gesmay be 10 ¢/kWh for th e firs t 200 kWh, then 8 ¢/kW h for t he nex t 1,0 00 kW h, and 6¢/k Wh fo r all r emain ing ene rgy use. T his i s an ex ample of decl inin g block rates , where the en ergy charge de crease s as th e energy used increases. One may also see inclining block rates. As a variation on this scheme, the bloc k limits may depend on the customer' s energy consumption and demand. As an examp le of one

such tar iff, Fig ure 8.3. 3 shows a b lock-by -demand tariff, which is representative of about 20–30 percent of the utilities sampled. This figure is illustrative and does not reflect any

particular utility. The first block has a rate of 10¢/kWh for the first 200 kWh of energy used. The second block rate is 6¢/kWh for energ y consumption up to 100 times the billing demand. The multiplier 100 is a tariff component with units of kWh/kW, which defines the width of the second block. The third block rate is 3¢/kWh for all subsequent energ y use. Beside s increasing the

complexity

of the ca lculation of the cu stomer bil l, this ty pe of var iable block size

introduc es a depe

ndence of the energy

charg es on the b illing de mand. Two

cases in Figure 8.3.3 illustrate this: in each case, the over all energy use is 3,200 kWh, but the billing demand is different (20 kW versus 21 kW).8-27

Figure 8.3.3 Effect of a Change in Customer Demand (Energy

Consu mpt

ion is H eld F ixed)

for a B lock-By-D ema nd Tariff In Case 1, the customer ene rgy use is 3200 kWh, and the monthly peak demand is 20 kW. Th e w id th of

th e s ec on d b lo ck is 10 0× 20 = 2 00 0 k Wh . In do ll ar s, th e c us to me r w il l p ay: (0.10)×200 + (0.06)×2000 + (0.03)×1000 = 20 + 120 + 30 = $170. In Case 2, the customer ene rgy consumption is also 3200 kWh, but the demand is 21 kW. Now the length of the second block is 2100 kWh, so the bill is: (0.10)×200 + (0.06)×2100 + (0.03)×900 = 20 + 126 + 27 = $173. Even though the tariff specifies only energy charges, a change in the customer demand of one kW has increased the bill by $3. This is because 100 kWh of consumption have been shifted from the third, less expensive, block to the second, more expensive, block. Note that increasing the dema nd while holding the energ y c onsumption

fixed lowe

rs the cu stomer loa

d factor, and in this case increases the effective ma rginal rate. This is a gener ic observation of the sampled tariffs.

The important point to take from this is that both demand and energy use contribute to the marginal rates seen by

a customer, and often in ways that are not immediately obvious from reading the tariff. For the L CC, the energy

cost savings due to the standard depend on the decrement to the total energy consumption, the decrement to the peak demand, and the ratio of the two. The effective margina l rate can vary

substantially even for a

set of customers on the same tariff. Approximations Used in Modeling the Tariffs . In cases wher e the available information on the full set of charges seen by the customer is incomplete, the Department made the following approxima

tions:

C Riders and

adders : Some tariffs, particularly in deregulated areas, include a dditional charg es as rid

ers whic h may not be expli citly

defined . The most s ignific ant are the fuel

cost-recovery

adders. These are additional charges passed on to the customer when the utility must spend more than anticipated for f uel. These costs were included in the8-28

Department’s analysis when they wer e given explicitly; howeve r, they ar e sometimes represented as a formula based on the utility 's expenditures and so could not be modeled within the

Department’s fr

amework . This res

ulted in a possible u

nderest imation of

costs for some customers.

C Customer classes : In a few cases, the utility specifies tariff s for “small” and “large” customers, without giving an explicit definition of these terms. I n its review of the tariffs in the sample, the Department found that small customers ty pically have a

peak demand on the order of 10 kW, medium customers have a demand on the order of 100 kW, and large customers have peak de mands on the order of 1000 kW. The Department used a median va

lue of 50 k

W to separ

ate cust omers into

the “sma ll” and “ large ” classe s.

C Ratchets : Ratchet s refer to situations where

the billing

demand f

or the cu rrent mon th is computed from a formula incorporating the monthly demand over the previous 12 months. For example, the billing demand may be set equal to either the current month’s demand, or 80 percent of the maximum demand over the previous 12 months. A ratche t may also be seasonal. For example, the billing demand may be the greater of the cur

rent monthly demand or the pea k demand in the most recent summer months. The Department did not include this type of rate f ormula in its tariff model. Instead, it assumed that the billing demand is the current monthly demand. The rationale behind ratchets is that demand charges are me ant to cover capacity costs, and the actual capacity needed to serve a customer is better represented by their peak demand over a y ear rather than a month. New capacity

is needed to serve a customer only when that customer contributes to the total sy stem pea k load, so o

ne would e

xpect that s

ummer-pe aking u

tilities wo uld tend to implement

ratche ts that dep end on summer dema nd. I n these c ases, the

tariff model will underestimate the savings due to standards, since the billing de mand decrement in each month will b e somewhat less tha n the dec rement f or the sum

mer months . The dat

a collecte d on system loads show that a

ll areas except the

Northwe st are su

mmer-pe aking in an aver age y ear. The souther

n states ma

y ha ve high loads dur ing an e special ly c old win ter , so th ese are as m ay im pl eme nt rat che ts th at d epe nd o n t he a nnu al d ema nd. In these cases, buildings with electric heat may have their peak demand occurring in the winter and, if the tariff includes a ratchet, the D epartment’s model may over-estimate the savings due to sta

ndards. Monthly Bill Ca

lculations . The Department used the calendar month as the billing period. For each building, the Depa rtment used the peak demand and total energ y consumption data fr om CBECS 199 5 for 12 c alendar months. 16 The Department kept the customer on the same tariff for both the base and the standards c ases. It calculated the monthly bills, adding the distribution transformer losses for both the base and the standards case s. The difference between the annual bills for each standard level ga ve the associated operating cost saving s. The Department calculated the customer marg inal demand and energy

prices as the net change in the total bill, divided by the net chang e in demand or energy , respectively

. To represent the full range of ta riffs in the LCC spreadsheet, the De partment created a8-29

Tariff Data Model (TDM). The TDM is a data structure used to store all of the tariff information in a format that is consistent across utilities. Briefly , the TDM divides each tariff into a collection of components. A component is defined by a set of parameters that include a rate , a range of values under which the rate applies, and indicator variables that specify if and when the rate should be applied. Using this component format, one can r econstruct the structure of any tariff from the set of components, and then apply the customer data used to determine whether conditions are met for a particular rate. The Depa rtment use d the TDM t

o store a ll of the ta

riff inf ormation. Its ob

jective was to create a database structure that captured the complexity of a specific rate schedule (e.g ., seasonal rates, variable

block ra tes, mixture s of blocks, time-of -use tar iffs) wit h suffic ient acc

uracy to model any utility

tariff In principle, each ta

riff is simply a list of rates. Howe ver, a complete tariff is, in practice, often very

complex. Typically, certain rules and conditions must be met for a particular ra te to be applied. To capture this complexity, the TDM divides ea ch tariff into a collection of component TDM Rates . Each ta

riff com ponent ha s a rate

parameter. The

rate stor ed in the TDM is a dimensionless, real, numbered value. The “charge type” indica tor specifies the units for a particu lar comp onent. TDM Indicators
. Charge Type. The charge-ty pe indicator specifies the units for each component. The indicator is also used to keep track of charg es as bills are calculated. There ar e three basic ty

pes of char ges inc luded in th

is sample: fixed cha

rges, e nergy charg es, and d

emand charges .

C Fixed charges ($/month) – These are ty pically monthly

customer charges. Fixed rates ar e also used as minimum customer charges.

C Energy

charges (¢/kWh) – These are the basic per-kWh charges associate d with a tariff.

C Demand charges ($/kW) – These a re the charges driven by

peak consumption. Larg er customers are ty

pically subject to

tariffs that incorporate

demand c

harge s. Block Type . A block i s the ran ge in wh ich a par ticular r ate is ap plied. I n gene ral, the se blocks are based on user consumption and demand. To deter mine these ranges, utilities use a variety of f

unctions. In addition, a particular tarif f may use diff

erent block functions for each block. However, at the component level, there is a small set of f unctions that can be used to set the limits of a range. I

n general, these limits are functions of kW of demand and kWh consumed ( Limit = f {kW, kW

h} ). The block type

indicates which limit function should be applied to each componen

t. The De partmen t modeled severa l functions.8-30

C Fixed Block – This is the most common block type. The De partment based the minimum and maximum limits on a predetermined kWh level.

C Block-By

-Demand – This is also a common type , though less so then the fixed block. The maximum limit equals a Demand Multiplier × User Demand . In th

is case, the limit is not known until run time, when the user demand is known. (This ty pe of block structure essentia lly i ncorpor ates a de mand cha rge int o an ene rgy charg e.) The

minimum limit i s set to the p

revious maximum.

C Mix Block T

ype 1 – The ma

ximum limit is se

t by the maximum (

kWh , demand multiplier ×kW). The

minimum limit i s set to the previous maximum.

C Mix Block T

ype 2 – The ma

ximum limit is se

t by the minimum

( kWh, demand multiplier ×kW). The

minimum limit i s set to the previous maximum.

C Mix Block T

ype 3 – The ma

ximum limit is se

t by the sum ( kWh , demand multiplier ×kW). The minimu

m limit is set t

o the pre vious maximum

. TDM Range

s. The quantities that are used to determine limits are stored as ranges. The Department currently

has ranges for seasonal limits and block limits.

C kWh Ranges – Minimum and maximum ranges for blocks are stored in units of kWh.

C kW Range s – Minimum a nd maximum ra

nges fo r blocks a re store d in dimens ionless units. The

block ty pe indica tor dete rmines the

unit for th

is rang e. Fixed b locks ar e in units of kW, other block types are the demand multiplier units, sometimes referenced by utilities as “Hours” or “kWh/kW.”

C Month Range – Each utility de fines the winter and summer months differently . The winter and summer start and end months are stored here

.

C Season Type – The

season type indica

tes in which season the component charge c an be applied. The Bill Calculator. The bill c alculator (BC) is a set of a ccountin g prog rams, implement

ed as fun ctions, wh

ich can b e acce ssed from within an Excel spre adsheet . These functions produce monthly bills for a use r given the consumption, demand, and month. There are two functions of int

erest: GetTariffs, and GetCharges

.

• GetTariffs

. For a given utilit y, a customer is ty pically assigne d to one of

severa l tariff s. GetTariffs determines the tariff to which the user is assigned, g iven the peak consumption and pea k demand l evels.8-31

Figure 8.3.4 Cumulat

ive Load Growth at One Perc ent per Y ear for Liqu idImmersed Transforme rs • GetCharge

s. GetCharges returns a monthly bill, given the tariff, consumption, and demand. This is the core function that reconstructs a tariff from the TDM. The function reads da ta from the TDM and

evaluat es which charg es should b e applie d. It t allies the se charg es and re

turns the monthly bill in dolla

rs.
8.3.6 Load Growth Trends The LCC analy

sis looks at a cross-section of transformers. The Depa rtment applied a load growth trend to each new transf ormer. Spreadsheet users have the choice of three scenarios using the Transformer Load Growth/Year drop-box on the “Summary ” worksheet. The three scenarios for load growth are : no growth, one-percent-per-year g rowth, and two-percent-per-y ear growth. The Department used as the def ault scenario a one-percent-pe r-yea r load growth for liquid-immersed transformers, i.e., a medium rate, as identified in the Determination Analysis of Energy Conservation Standards for Distribution Transformers, Report ORNL-6847. 18 The onepercen t annual l oad-g

rowth tre nd from OR

NL-6 847 is cons istent with the aver age e lectric ity use growth per customer during the 1990s, as determined by EIA. The Department applied a onepercent-per-y

ear load-growth trend to eac h new liquid-immersed transformer beginning in 2010, the expected eff

ective d ate of the standa

rd (see section 8 .3.9). F or dry

-ty pe trans formers , installation of new circuits and transformers often acc ompanies new demand. The Department therefore expects load growth for dr y-ty pe transformer to be lower than for liquid-immersed transformers. For dry

-type transf

ormers, the Department used the no-grow th scenario. Figure 8.3.4 shows the cumulative grow th for the default scenario of one-per cent-per-y

ear load gr owth that t

he Depa rtment use d for liqu

id-immersed tran sformers.8-32

8.3.7 Electri city Cost

and Pric e Trends For the relative change

in electricity cost a

nd prices for future y

ears, the Department used the pric e trends

from three AEO2005 forecast scenarios from EIA. 4 LCC spreadsheet users have the choic e of thes e four sc enarios : 1. AEO2005 Low Growth scenar io, 2. AEO2005 Reference scenario, 3. AEO2005 High Growth scenario, 4. Constant Real Prices Figure 8.3.5 shows the trends for the three AEO2005 price pr ojection s. Beca

use AEO2005 does not forecast bey ond 2025, the Department extrapolated the values in later y ears (i.e., after 2025) from their relative sourc es. To arrive at values for these later y ears, the Department used the price trend of the fore cast from 2015 to 2025 to establish prices in the years 2026 to 203 5. This met

hod of extr

apolation is in line w

ith methods

curren tly used by

the EI A to forecast fuel prices for the F ederal Energy Management Program (F EMP). The default electricity

price trend scenario that DOE used in the L CC analysis is the trend from the AEO2005 Reference case. Spreadshe ets used in calculating the L CC have the capability to analy

ze the other electricity

price trend scenarios, namely the AEO2005 High and Low G rowth pri ce tren

ds.8-33

Figure 8.3.5 Electricity Price Scenarios

8.3.8 Discount Rate The disco unt rate is the rat e at whic h future expenditur

es are d iscounte d to estima

te their present value. T he Depa rtment de rived the discount r

ates sele cted for

the tran sformer

LCC analysis from estimates of the cost of capital for companies that purchase tra nsformers. Following financial theory, the cost of capital can be interpreted in three ways: 1) I

t is the discount r ate that should be u sed to re duce the future value of c ash flows to be der ived from a typical company

project or investment; 2) it is the economic cost to the firm of attracting and retaining capital in a competitive environment; and 3) it is the return that investors r equire from th ei r i nv es tm en t i n a fi rm ’s de bt or eq ui ty. 19 The Depa rtment pr imarily used the f

irst interpre tation. Mo st compan

ies use both debt an

d equity capital t o fund inve stments; f

or most companie s, there fore, the cost of capital i s the weig

hted ave rage o f the cost to the fir

m of equity and de bt fin ancin g. 20 The Department estimated the cost of equity financing using the Capital Asset Pricing Model (CA

PM). The CA

PM, among

the most wi dely

used mode ls to estima

te the co st of equi

ty financi ng, ass umes that t

he cost of equity is propor tional to the amount o f sy stematic risk8-34

associated with a firm. For example, the cost of equity financing tends to be high when a fir m faces a large degre e of sy

stematic risk, and the cost te

nds to be low when the

firm fac es a small degree of sy

stematic risk. The degree of sy

stematic risk facing a firm and the subsequent c ost of equity financing are determined by se

veral variables, including the risk coeff icient of a firm (beta, or B ), the expected return on risk-fr

ee asse ts ( R f ), and the additional return expected on assets facing average market risk (whi ch is know

n as the e quity

risk pre mium, or ERP) . The bet

a indica tes the de gree o f risk associated with a given firm, relative to the level of risk (or price variability

) in the overall stock market. Betas usually

vary betwe en 0.5 and 2.0. A firm with a beta of 0.5 faces half the risk of other stocks in the market; a firm with a beta of 2.0 face s twice the overall stock market risk. Following this approach, the cost of equity financing for a particular c ompany is given by the equa tion: k e = R f + (B × ERP) Eq. 8.6 where: k

e = th e c os t o f e qu it y fo r a co mp an y, R f = the expected retu rn of the risk-fr ee asse t, B = the beta of the company stock, and ERP = the expected equity risk pre mium, or the amount by which investors expect the futur e retur n on equiti es to exce ed that on the riskle ss asset. The cos t of de bt fin ancin g ( k d ) i s t he yie ld or in te re st ra te pa id on mo ne y bo rr ow ed by a company (r

aised, for example, by se lling bonds). As defined here, the cost of debt includes compensa tion for d efault r isk and exc ludes ded

uctions f or taxes. The Department estimated the cost of debt for companies by adding a risk adjustment factor to the cur

rent y ield on lon

g-ter m corpor ate bonds (the risk -free rate). This proc edure is used to estimate current (and future) company costs to obtain debt financing. The adjustment factor is based on indicators of company risk, such as credit rating or variability of stock returns. The discount rate of companies is the weighted a verage cost of debt and equity financing, less expected inflation. The Department estimated the discount rate using the e quation: k = (k

e × w e ) + (k

d × w d ) Eq. 8.7 where: k = the (nomin al) cost o f capita

l, k e and k d = the expected rates of return on equity and debt, respectively , and w e and w d = th e p ro po rt io n o f e qu it y an d d eb t f in an ci ng , r es pe ct iv el y.a

The D epartment estimated percent debt f or firms in the property-owning cat egory using data f rom Bloo mberg Pro fessiona l. 24 The D epartme nt took the cost o f debt for pub licly owned utilities from FER C Fo rm 1 filings. 13
8-35 The real discount rate deducts expected inflation from the nominal rate

. The expected retu

rn on risk -free assets, or the risk

-free rate, is d efined by the curre

nt y ield on long-term governmen

t bonds. 21 The ERP represents the difference be tween the expected (average) stock marke

t return and the risk-free rate. As shown in Ta ble 8.3.7, the Department used an ERP estimate

of 5.5 pe rcent, w hich it took

from the D amodara

n Online si

te (a pr ivate website, associated with New York University ’s Stern School of Business, that aggregates information on corporate finance, investment, and valuation). 22 The Department calculated an expected inflation of 2.3 pe rcent from the average

of the last five quarters’ change in GDP pr ices. 23 The Department obtained the cost of debt, perce nt debt financing, and systematic firm risk from information provided at the Damodaran Online website. a Table 8.3.7 shows average value s across all private companies. However, the c ost of debt, percen t debt finan cing, a nd system atic f irm ri sk var y by sector. Fo r exam ple, a verage systematic f

irm risk of

all priva te firms in

the indust

rial sector is clos e to 1.0, w hile systematic firm risk in the utility sector avera ges close to 0.6. Table 8.3.7 Variables Used to Estimate Company Discount Rates Variable Symbol Average Value Source
Risk-free asset return R f 5.5% Bloomberg Professional 24 Equity risk premium ERP 5.5% Damodaran Online 22 Expected inflation r 2.3% U.S. Bur eau of E conomic A

nalysis 23 Cost o f debt (af

ter tax) k d 9.0% Damodar an Online ; FERC For

m 1 13 Percent debt financing w d 27% Damodaran Online Syst ematic f irm risk B 0.99 Damodaran Online Transformers are purchase d and owned by e lectric utilities (publicly and investor-ow ned), C&I companies, the owne rs of commercial buildings (property owners), and the government. Table 8.3.8 shows the typica l owners of transformers, grouped by transformer ty

pe owned (represented by

the design lines DOE used in the engineer ing analy sis). The Department used a sample of 4,294 companies drawn from these owner c ategories to represent transfor mer purchasers. It took the sample f rom the list of companies included in the Value Line inve stment survey

25 and listed

on the Da

modaran Online we

bsite. The

Department obtai

ned the c ost of debt, the firm b eta, the

percen t of debt a

nd equity financi ng, the risk-fr ee retu rn, and the equity

risk8-36

premium from Damodaran Online. The Dep artme nt est imat ed the cost o f debt finan cing fo r thes e comp anies from t he lon gterm government bond rate and the standar d deviation of the stock price. 22 Publicly owned utilities, i ncluding municipa ls and coo

peratives, do not i ssue stock and tend to be fina

nced with debt. The Department obtained the cost of debt for these c ompanies from information provided in FERC Form 1 filing s. Finall y, f or gove rnment-o ffice- typ e owners, the disc ount rate repres ents an average of the F ederal rate and the State and local bond ra te. The Department drew the Federal rate directly

from the U.S. Office of Manage ment and Budget discount rate for in ve st me nt s i n g ov er nm en t b ui ld in g e ne rg y ef fi ci en cy. 26 The Department estimated the State and local discount rate from the interest rate on State and local bonds be tween 1977 and 2001. 27 The Department used t

his information to e stimate the weig hted-average

cost of c apital for the samp le of co mp an ie s i nc lu de d i n t he co mm er ci al pr op er ty o wn er , c om me rc ia l a nd in du st ri al co mp an y, and utility database.

Table 8.3.8 Typical Owners of Different Types of Transformers Design Line Typical Ownership Categories 1, 2, 3, 4 Electric utilities, both publicly owned and investor- owned 5 Electric utilities, commercial property owners, commercial and industrial companies, government offices 9, 10, 11, 12, 13 Commercial and industrial companies As previously mentioned, the cost of c apital may be viewed as the discount rate that should be used to reduce the future value of ty pical company pr

oject cash flows. It is a nominal discount rate, since anticipated future inflation is included in both stock and bond expected returns. Deducting expected inflation from the cost of ca pital provides estimates of the real discount r ate by ownersh ip category

(see Ta ble 8.3.9 ). The me an real discount r

ate for these companies varies between 3.3 perce nt (government offices) and 7.5 per cent (industrial companies).a

This i s the average cos t of ca pital , af ter deduct ing 2. 3 percent infl ation, for t he set of investor -owned ut ili ties sampled in this analysis. The D epartment obtained this es timate f rom the Bloom berg Professional service, during December, 2001. 24
8-37 Table 8.3.9 Real Discount Rates by Transformer Ownership Category
Ownership Category SIC Codes * Mean Real Discount Rate % Standard

Deviation % Number of

Observat ions Industrial Companies 1 - 4 7.5 3.2 2409 Commercial Companies 5 - 8 7.3 4.7 1773 Commercial Property Ow ners 6720 4.5 0.9 8 Utilities, Investor-Owned 49 4.2 1.5 63 Utilities, Publicly Owned n/a 4.3 1.1 16 Government Offices n/a 3.3 2.1 25

* SIC Co des re fer to the U.S . Stand ard In dustria l Classifica tion system

. Source: Lawr ence Berkeley National Laboratory

(LBNL) calculations bas ed on fir ms sampled f

rom the Damodaran Online webs ite. Because investor-owned utilities purchase the bulk of ma ny transforme

r design lines evaluat ed here , the disc ount rate s calcul ated for that sector (see

Table 8. 3.9) are

particu larly important . The Dep artment e stimated t hat the a verag e investor-owne d utility real disc ount rate

is 4.2 percent. The 4.2 percent fig ure is an after-tax discount rate, representing the return required by such utilities to attract financing . Private financial data companies, including I bbotson Associates and Bloomberg Professional, offe r similar estimates. The Bloomberg Professional online se rvice e stimates the cost of investor -owned u tility capital t o be 4.4 pe

rcent. a Ibbotson Associates estimates the cost of capital in this sector—SIC (Standa rd Industrial Classification) 49—afte r deduct ing 2.3 p ercent

inflation , to be 5.0

percen t. 28 The Department’s approach for e stimating the cost of capital provides a measure of the discount rate spread as well as the avera ge discount rate. The Department infe rred the discount rate spread by

ownership category

from the standard deviation, which ranges be tween 0.9 percent and 4.7 percent (Table 8.3.9). Publicly owned utility and property owner discount rates are narrowly c oncentrated around their mean value. B y contrast, C&I company discount ra

tes are dispersed across a broader range. Different combinations of commercial property owners and commercial, industrial, and utility buyers purc

hase the differe nt transf ormer de sign line s include d in the en gineer ing ana lys is (Chapter 5). Accordingly , the Department constructed the discount rates associate d with any given d esign li ne from d iffere nt combina

tions of c ommercia

l proper ty owner, c ommercia

l,8-38

industrial, and utility discount rates. For e xample, transformer design line 9 is purchased by commercial property

owners, C&I compa

nies, and the government. Roughly 19 percent of customers are commercial property owners, 19 percent are industrial companies, 54 per cent are commercial companies, and 7.9 percent ar e government offices (Table 8.3.10). 29 The Depa rtment estimated di scount ra te distrib utions for the diffe rent des ign line s as a weighted average

of the distributions for the different ownership ty pes. Table 8.3.10 Transform er Ownersh ip by Design Line Transformer Design Line Property

Owners % Industrial Companie s % Commercial Companies % InvestorOwned Utilities % Publicly Owned Utilities % Govern ment Offices % 1 0.4 0.5 0.9 72.0 26.0 0.2 2 0.4 0.5 0.9 72.0 26.0 0.2 3 2.1 2.4 4.5 80.0 10.0 1.0 4 0.4 0.5 0.9 72.0 26.0 0.2 5 9.5 9.5 27.0 35.0 15.0 4.0 9 19.0 19.0 54.0 0 0 7.9 10 19.0 19.0 54.0 0 0 7.9 11 19.0 19.0 54.0 0 0 7.9 12 19.0 19.0 54.0 0 0 7.9 13 19.0 19.0 54.0 0 0 7.9 Source : DO E con tractors. 8.3.9 Effective Date of Standard The eff ective d ate of the new energy

-effic iency

standar d for distr ibution tra

nsforme rs is three ye ars after the Department issues the final rule. The Department assumed that it will issue the final rule in 2007, so the new standard will take effect in 2010. The Department calculated the LCC for all users as if eac h new distribution transformer purchase occurs in the y ear the standard takes effect. I

t based the cost of the equipment on that y ear; however, as stated above, the Department expresses all dollar values in 2004$. 8.3.10 Trans form er Se rvic e Life The Department defined distribution transformer service life as the age at which the transformer retires from service. The Department assumed, based on ORNL -6847, Determi nation Ana lysis of En ergy Cons ervationStandards f or Distribu tion Transfo rmers , 18 that8-39

the aver age lif e of distr ibution tra

nsforme rs is 32 y ears. Th is lifetime

assumption

includes a constant failure rate of 0.5 perc ent/y

ear due to lightn ing and other ra ndom failu

res unre lated to transformer age, and an a dditional corrosive failure rate of 0.5 perce nt/year starting

at year 15. The Depa rtment ad justed the retirement distri

bution to ma

intain an average life of

32 years. 8.3.11 Maintenance Costs The maintenance cost is the cost to the consumer of maintaining e quipment operation. The maintenance cost is not the cost associated with the replace ment or repair of components that have failed. Rather, it is associated with gener al maintenance. The Department assumed that the cost for gener al mainte nance w ill not cha nge wit h increased eff

iciency. In practice , there i s little schedule d maintenance for transf ormers. Maintena

nce con sists of br

ief annu al checks for dust buildup, vermin infestation, and accident or lightning damage. 8.3.12 Power Factor The powe r factor is the re al power

divided by

the appa rent power. Rea

l power is the time average of the instantaneous produc t of voltage and current. Appare nt power is the product of the root mea n square (RMS) volta

ge time s the RMS cu

rrent. T ransfor mer eff iciency specific ations, such as NEMA's TP 1-2002, assume a power fa ctor of 1.0. 1 Therefore, the Department used a power factor of 1.0, both in calculating the e fficiency levels in the engineering ana lysis and when preparing candidate standar d levels for the notice of proposed rulemaking ( NOPR). However, in real-world installations, the loads experienced by distribution transformers are likely to have

power factors of less than 1.0. Beca use the LCC analy

sis models transformers that are installed and oper ating in the field , DOE cr

eated the LCC s

preadsheet with a

n adjusta ble power factor, enabling the LCC to run at lower power factor values. I n the absence of any specific data or g uidance on the app

ropriate power f actor, t he Depa rtment use d 1.0 for t

his LCC analysis. 8.3.13 Default Sce nario The Dep art men t d eve lo ped di st in ct s cen ari os f or s eve ral key i npu t p ara met ers . It describes these distinct scenarios as low, medium, and high. For each of the key

inputs, the Department chose

the mediu

m designation as the defau lt scena rio. The overall d

efault sc enario used in the

LCC analy sis has the

following

values:

C transformer load growth/y ear: medium (one percent) for liquid-immersed, low (zero percent) for dry

-type
C transformer loa

ding (r elative t o curre nt estimat e): mediu

m (zero pe

rcent)

C electri city

prices ( relative to curre nt estimat e): mediu

m (zero pe

rcent)

C transformer customer As and Bs: medium8-40

C future e

nergy price tr end: AEO2005 reference Other scenarios can readily be used to explore sensitivities to variations of these key variabl es. 8.4 LIFE-CY CLE COST RESUL TS This sect ion prese nts LCC results f or the ef ficienc y imp rovemen t levels e valuate d for all 13 design lines. Table 8.4.1 provides an overview of the six candidate standa rd levels the Department eval

uated for each o f the 10 de sign line s examined . The lowe st effic iency candida te standard level is NEMA’s TP 1-2002 and the highest is the most efficient desig n identified in the engineering analy

sis. The remaining four efficiency levels are spread between these two bounds. The Department expresses all the candidate standard le vels in terms of efficiency, with no explicit or implicit technology assumed. The c olumn labeled “TP 1+” shows by how much the given st andard l evel exce eds TP 1-2 002. The D epartme nt based t he resul ts prese nted in this section on the inputs described in section 8.3. Table 8.4.1 Candidate Standard Levels Evaluated For Each Design Line

Design Line Lev el 1

TP 1 Lev el 2 Lev el 3 Lev el 4 Lev el 5 Lev el 6

TP 1 1/3 of Diff.

bet ween T P 1 and Min LCC 2/3 of Diff.

bet ween T P 1 and Min LCC Min LCC M ax Energy Sav in gs wit h No Chan ge i n LCC M ax Energy Savings

TP 1+ % Effic 'y % TP 1+ % Effic 'y % TP 1+ % Effic 'y % TP 1+ % Effic 'y % TP 1+ % Effic 'y

% TP 1+ % Effic 'y

% 1 0.00 98.9 0.14 99.04 0.29 99.19 0.43 99.33 0.59 99.49 0.69 99.59 2 0.00 98.7 0.03 98.73 0.06 98.76 0.09 98.79 0.26 98.96 0.76 99.46 3 0.00 99.3 0.08 99.38 0.16 99.46 0.24 99.54 0.44 99.74 0.45 99.75 4 0.00 98.9 0.18 99.08 0.36 99.26 0.55 99.45 0.68 99.58 0.71 99.61 5 0.00 99.3 0.06 99.36 0.12 99.42 0.17 99.47 0.41 99.71 0.41 99.71 9 0.00 98.6 0.22 98.82 0.44 99.04 0.66 99.26 0.81 99.41 0.81 99.41 10 0.00 99.1 0.12 99.22 0.23 99.33 0.35 99.45 0.41 99.51 0.41 99.51 11 0.00 98.5 0.17 98.67 0.34 98.84 0.51 99.01 0.59 99.09 0.59 99.09 12 0.00 99.0 0.12 99.12 0.23 99.23 0.35 99.35 0.40 99.40 0.40 99.40 13 0.00 99.0 0.15 99.15 0.30 99.30 0.45 99.45 0.55 99.55 0.55 99.55 One of the primary

impacts of an energy

-efficiency

standard is the change in the set of transformer designs available for pur chase and their corresponding loss cha racteristics, i.e., load losses (L L) a nd no-loa d losses ( NL). This impact is illustra ted in the LL versus N L gr aph (fou rth from right worksheet in the L CC spreadsheet). Figur e 8.4.1 pr ovides an illustrati on of the L

L versus NL

graph taken fr om the L CC8-41

Figure 8.4.1 Design Load Losses (LL) versus No-load Losses (NL) for TP 1-

2002, Design Line 1 spreadsheet for

design l ine 1, usin

g the TP 1 -2002 sta

ndard le vel. Since

each de sign line

has a unique set of engineering constra ints, the LL-versus-NL gr aph for each design will be differ ent. This gra ph plots an

example of

a Crystal Bal l LCC ru

n (limited to 50 itera

tions for l egibilit

y in this gra phic for mat). I t shows dif

ferent sets of de signs by

their loa d losses a t rated lo ad, and their no-load losses. Potential designs are shown as both small dots and small squares. The standard level is il lustrate d by

a thick line (those

designs that satis fy

the stand ard are to the lef t of this line). The selected designs not subject to standard constra ints are plotted as triangles. The designs subject to standards constraints are plotted as dots. As the standard le vel increases, the thick line moves parallel to the left (to the area of the g raph with lower losses), and so does the set of constrained designs. The standard leve l is selected with the corresponding pull-down menu on the “Su

mmary ” sheet. Some of the

selecte d design s meeting the stand ard (es pecially those with higher load losses) are plotted to the right of the line. This is bec ause the efficiency rating and design assumptions use different percenta ge loading definitions. The efficienc y level rating is defined at 50 percent (liquid-immersed and medium-voltage , dry-ty pe), while the load and no-load losses for the design assumptions are defined by nameplate loading (100 percent). F or those designs with higher load losses, the heating f rom losses causes the actual efficiency to drop, shifting the design to the right.

The following 10 tables present the summary results from the Department’s LCC ana lysis.8-42

For each evaluated desig

n line and each candidate standard leve l, the Department presents the percent efficiency

, the percent of evaluated transforme r purchases that would experience negative, zero, and positive LCC saving s when subject to the candidate standard level, and the mean LCC savings. The De partment presents these summary results for consideration; it has not selected any

specific candidate standard level for a ny design line. G

raphical representations of these re sults, whic

h provide a clear er indic ation of the full dist ributions,are inc luded in A ppendix 8A. 8.4.1 Design Line 1 Results Table 8.4.2 presents the summary of the LCC analy

sis for the representative unit from design l ine 1, a 50

kVA, liqui d-immers ed, single-phas e, pad-m ounted tr ansformer. For

this unit, the average effic iency of the baseline transformers selected during the L CC analysis was 98.97 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 98.56 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $1,382.00. Table 8.4.2 Summa ry Life-Cycle Cost Results for

Design Line

1 Repres entative

Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 98.90 99.04 99.19 99.33 99.49 99.59 Tr an s f orme rs wi t h N et

LC C C os t ( %) 4.9 16.6 52.8 27.7 57.9 90.5 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 65.2 50.9 14.7 4.6 2.1 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 29.9 32.5 32.5 67.7 40.0 9.5 Mean LCC Savin gs ( $) 93 98 5 180 3 -688 8.4.2 Design Line 2 Results Table 8.4.3 presents the summary of the LCC analy

sis for the representative unit from design l ine 2, a 25 kVA, liqui d-immers ed, single-phas e, pole-mounted tr ansformer. For

this unit, the average effic iency of the baseline transformers selected during the L CC analysis was 98.74 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 98.23 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $737.00. Table 8.4.3 Summa ry Life-Cycle Cost Results for

Design Line

2 Repres entative

Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 68-43

Ef f i ci en cy ( %) 98.70 98.73 98.76 98.79 98.96 99.46 Tr an s f orme rs wi t h N et

LC C C os t ( %) 1.4 3.0 5.2 8.6 43.9 98.9 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 66.6 64.3 60.8 56.3 25.4 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 32.0 32.7 34.0 35.1 30.7 1.1 Mean LCC Savin gs ( $) 69 70 72 71 7 -953

8.4.3 Design Line 3 Results Table 8.4.4 presents the summary of the LCC analy

sis for the representative unit from design l ine 3, a 50 0 kVA, liqu id-immersed, single-phas e distribu tion trans former. For this u nit, the average effic iency of the baseline transformers selected during the L CC analysis was 99.36 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 99.07 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $5,428.00. Table 8.4.4 Summa ry Life-Cycle Cost Results for

Design Line

3 Repres entative

Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 99.30 99.38 99.46 99.54 99.74 99.75 Tr an s f orme rs wi t h N et

LC C C os t ( %) 0.2 1.4 6.1 39.9 66.3 70.8 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 73.7 65.2 49.5 4.0 0.1 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 26.1 33.4 44.4 56.1 33.6 29.2 Mean LCC Savin gs ( $) 1,746 2,267 2,775 2,876 627 -410 8.4.4 Design Line 4 Results Table 8.4.5 presents the summary of the LCC analy

sis for the representative unit from design l ine 4, a 15 0 kVA, liqu id-immersed, thre e-phase distributi on transf

ormer. F or this unit , the average effic iency of the baseline transformers selected during the L CC analysis was 98.91 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 98.42 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $3,335.00. Table 8.4.5 Summa ry Life-Cycle Cost Results for

Design Line

4 Repres entative

Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 68-44

Ef f i ci en cy ( %) 98.90 99.08 99.26 99.45 99.58 99.61 Tr an s f orme rs wi t h N et

LC C C os t ( %) 3.3 16.8 41.0 31.2 64.4 74.5 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 63.7 40.8 11.3 9.7 0.8 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 33.0 42.4 47.7 59.1 34.8 25.5 Mean LCC Savin gs ( $) 556 629 450 767 56 -572 8.4.5 Design Line 5 Results Table 8.4.6 presents the summary of the LCC analy

sis for the representative unit from design l ine 5, a 15 00 kVA, liq uid-immersed, thre e-phase distributi on transf

ormer. F or this unit , the average effic iency of the baseline transformers selected during the L CC analysis was 99.36 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 99.13 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $11,931.00. Table 8.4.6 Summa ry Life-Cycle Cost Results for

Design Line

5 Repres entative

Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 99.30 99.36 99.42 99.47 99.71 99.71 Tr an s f orme rs wi t h N et

LC C C os t ( %) 0.3 1.5 10.2 15.9 57.1 57.2 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 71.7 62.8 40.0 24.2 0.0 0.1 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 28.0 35.7 49.8 59.9 42.9 42.7 Mean LCC Savin gs ( $) 3,957 5,463 6,504 7,089 4,431 3,902

8.4.6 Design Line 9 Results Table 8.4.7 presents the summary of the LCC analy

sis for the representative unit from design l ine 9, a 30 0 kVA, med ium-volta ge, dr y- typ e, three -phase t

ransfor mer with a

45 kilovolt (kV) basic impulse insulation level (BIL). For this unit, the average efficiency of the baseline transformers selected during the L CC analysis was 98.77 perc ent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.41 percent. The consumer equipmen t cost bef ore insta llation, w hich incl udes the manufacturer se lling pr ice, ship ping co sts, distributor markup, and retail markup, was $7,510.00.8-45

Table 8.4.7 Summa ry Life-Cycle Cost Results for

Design Line

9 Repres entative

Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 98.60 98.82 99.04 99.26 99.41 99.41 Tr an s f orme rs wi t h N et

LC C C os t ( %) 0.6 1.1 5.3 25.7 56.3 55.0 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 57.8 46.3 29.7 0.5 0.0 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 41.6 52.6 65.0 73.8 43.7 45.0 Mean LCC Savin gs ( $) 988 1,968 3,103 3,532 1,181 1,274 8.4.7 Design Line 10 Results Table 8.4.8 presents the summary of the LCC analy

sis for the representative unit from design line 10, a 1500 kVA, medium-voltage, dry -type, three -phase transformer with a 45kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 99.17 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.79 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $33,584.00. Table 8.4.8 Summa ry Life-Cycle Cost Results for

Design Line

10 Repre sentativ e Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 99.10 99.20 99.30 99.39 99.51 99.51 Tr an s f orme rs wi t h N et

LC C C os t ( %) 4.4 5.1 8.9 21.0 66.3 66.2 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 63.3 56.9 44.4 23.2 0.0 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 32.3 37.6 46.7 55.8 33.7 33.8 Mean LCC Savin gs ( $) 4,041 5,227 6,818 7,699 1,279 1,124 8.4.8 Design Line 11 Results Table 8.4.9 presents the summary of the LCC analy

sis for the representative unit from design line 11, a 300 kVA, medium-voltage, dry -type, three -phase transformer with a 95kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 98.42 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.05 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $10,945.00.8-46

Table 8.4.9 Summa ry Life-Cycle Cost Results for

Design Line

11 Repre sentativ e Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 98.50 98.67 98.84 99.01 99.09 99.09 Tr an s f orme rs wi t h N et

LC C C os t ( %) 2.4 3.9 9.8 22.0 34.2 33.2 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 42.5 34.6 18.7 2.3 0.0 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 55.1 61.5 71.5 75.7 66.8 66.8 Mean LCC Savin gs ( $) 2,491 3,621 4,313 4,845 4,186 4,289 8.4.9 Design Line 12 Results Table 8.4.10 presents the summary of the LCC analy

sis for the representative unit from design line 12, a 1500 kVA, medium-voltage, dry -type, three -phase transformer with a 95kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 99.18 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.81 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $33,590.00. Table 8.4.10 Summa ry Life-Cycle Cost Results for

Design Line

12 Repre sentativ e Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 99.00 99.12 99.23 99.35 99.51 99.51 Tr an s f orme rs wi t h N et

LC C C os t ( %) 1.4 1.5 5.8 18.2 70.6 70.1 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 75.1 71.9 56.9 28.2 0.0 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 23.5 26.6 37.3 53.6 29.4 29.9 Mean LCC Savin gs ( $) 2,600 3,973 5,485 6,812 -650 -655 8.4.10 Design Line 13 Results Table 8.4.11 presents the summary of the LCC analy

sis for the representative unit from design line 13, a 2000 kVA, medium-voltage, dry -type, three -phase transformer with a 125kV BIL . For this

unit, the a

verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 99.26 per

cent and the minimum efficiency of the baseline transformers selected during the LCC analy

sis was 98.97 percent. The consumer equipment cost before installation, which inc ludes the

manufacturer se lling pr

ice, ship ping co sts, distri

butor mar kup, and r

etail8-47

markup, was $41,873.00.8-48

Table 8.4.11 Summa ry Life-Cycle Cost Results for

Design Line

13 Repre sentativ e Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6
Ef f i ci en cy ( %) 99.00 99.15 99.30 99.45 99.55 99.55 Tr an s f orme rs wi t h N et

LC C C os t ( %) 3.8 1.5 4.4 42.6 75.8 75.7 Tr an s f orme rs wi t h N o C ha ng e i n L CC (% ) 76.0 72.9 58.9 5.4 0.0 0.0 Tr an s f orme rs wi t h N et

LC C Be ne f

i t ( %) 20.2 25.6 36.7 52.0 24.2 24.3 Mean LCC Savin gs ( $) 662 3,125 5,430 6,435 -5, 303 -5, 218

8.5 LIFE-CY CLE COST SENSITI VITY ANALYSIS The Depa rtment re cognize s that ther e is alwa ys s ome unce

rtainty associa ted with engine ering a

nd economic analy

ses. To min

imize that u

ncerta inty , the Dep artment strives to u se the best techniques and the best data at its disposal. To cover the widest possible set of sce narios in this ana

lys is, the De

partmen t used distr

ibutions of

values f or key inputs. For some va

riables, the Depa rtment we

nt one ste p furthe r by including

in the ana

lys is tool, i.e ., the L CC spreadsheet, the ability to repeat the ve ry same L CC analysis using values diff erent from the default set used to produce the Department’s results. Detailed descriptions of all of the LCC input variables a re included in the discussion of inputs in section 8.3, with additional information in Chapters 6 and 7. This section focuses on five key va

riables and the impact on the LCC results of assig ning them a range of diffe rent values. T he five variable s and the l ocation o f their de scriptive materia ls are a s follows: 1. percentage of transfor mers purchased using A & B evaluation (see section 8.3.1); 2. transformer loa

ding (se e Chapte

r 6); 3. electricity pr

ice trends (see section 8.3.7); 4. load growth trends (see section 8.3.6); and 5. equipmen

t price sc enarios (see Appendix 5E). This sensitivity analy

sis examines how sensitive the LCC results are to change s in key DOE assumptions. For the NOPR, DOE conducted the sensitivity analysis on desig

n lines 1 and 12. This a

nalysis treat s each va

riable in depende ntly , i.e., de fault va

lues rema in in effe ct for a

ll variables except the one being examined. Sensitivity results should always be c ompared to the8-49

default results. Each of the five variables has thre e values—low, medium, and high—that are described in more detail in the individual input variable sections. The variable that characterizes the per centage of transformers purchased using A and B evaluation uses the same set of low and high values for both liquid-immersed and dry-ty pe transformers, but different medium values for the diffe rent types of tra

nsformers. The low value represents a scenario where no transformer purchases are e valuated, i.e., a non-evaluating scenario. The high value repre sents a scenario where all transformer purchases are evaluated. The medium value for liquid-immersed transformers repre sents a scenario where 75 perce nt of the purchases are evaluated. The medium value for small-capacity, medium-voltage, dry -type transformers represents a scena rio where 50 percent of purchase s are evaluated. The medium value for large-ca

pacity, medium-voltag e, dry-ty pe transformers represents a sce nario where 80 percent of purchases are e valuated. For transformer loading, the medium scena rio represents the output of the load simulation described in Chapter 6. The low scenario decr eases the medium scenario load by 15 percent and the high scenario increases the medium sce nario load by 15 per

cent. For load growth, the low, medium, and high annual scenarios are zero pe rcent, one percent, and two perce nt, respectively. Electricity price

trends use the AEO2005 low, reference, and high g rowth scenarios. For equipment price scenarios, the medium scenario repr esents the five-y

ear average ma

terial prices described in Appendix 5E. The high and low price scenarios are also described in Appendix 5E. 8.5.1 Design Line 1 Summary Sensitivity Results The representative unit from design line 1 is a 50 kVA, liquid-immersed, single-phase, pad-mounted transformer. For this unit, the average efficiency of the baseline transformers selected during the L CC analysis was 98.97 perc ent and the minimum efficiency of the baseline transformers se lected d

uring the LCC a

nalysis was 98. 56 perce

nt. The c onsumer e quipment c ost before installation, which includes the manufacturer se lling price, shipping costs, distributor markup, and retail markup, was $1,382.00. Table 8.5.1 and Figure 8.5.1 illustrate the LCC sensitivity to changes in the five userselectable variables. Each of the sensitivity runs for all the variables causes some change in the LCC results. However, for desig n line 1, only the change in percentage of transf ormers purchas ed using

A & B evaluation

results in signific ant chan

ges in the results

for all c andidate standard levels examined. The Department found that the variable la beled A & B D istribution stands significantly a

part from the other variables for most candidate standa rd levels. The reason that the A & B distribution is so important is that it describes whether or not the transformer purchasers place an economic va lue on losses even without a standard. If transformer purchasers alread y pl ace an e conomic value on lo sses, the n standar ds will have a small i

mpact on p

urchase behavior, and the impact of a candidate standar d level will be small. If no purchaser s place an economic value on l osses without a standard, then a standard can have a large beneficial impact from decreased energ

y costs. The A &

B distribution options describe the full range of possibl e purchas e behavior scenarios.8-50

At the higher efficiency

levels represented by

candidate standard levels 5 and 6, equipmen t price has a sig

nifican t impact. A

t level 6, equipmen

t price sh ows the la

rgest differe nce from the def

ault assu mptions, be cause of

the limited

materia l options a

vailable to produce such high-efficienc y transforme

rs. For this design line, the remaining sensitivities have increasing difference s from the default assumptions as efficiency level increases, but these are always sig

nificantly smaller than A & B evaluation and material price in differ ence from the default assumptions.

Table 8.5.1 Mean Life-Cycle Cost Savings ($), Summary for Design Line 1

Represe ntative U nit
Scenario Candidate Standard Level 1 (TP 1) 2 3 4 5 6 Baseline 93 98 5 180 3 -688 Non-Evaluating A & B Distribution 342 375 246 446 241 -457 High-Evaluating A & B Distribution 10 7 -72 90 -66 -754 Low L oading 84 76 -53 155 -62 -790 High Loading 101 130 73 213 87 -560 Low Electricity

Price 77 73 -39 120 -87 -798 High Electricity

Price 107 122 52 245 91 -575 Low L oad Grow th 86 65 -63 151 -79 -809 High Load Grow

th 100 112 32 192 36 -633 Low E quipment Pr

ice Scenario 96 109 65 278 164 -399 High Equ ipment Pric e Scena

rio 86 75 35 202 -56 -9248-51

Figure 8.5.1 Design Line 1 Sensitivity Results by Candidate Standard Level

8.5.2 Design Line 12 Summary Sensitivity Results The representative unit from design line 12 is a 1500 kVA, me dium-voltage, dry-type, three-phase transformer with a 95kV B IL . For this unit, the average effic iency of the baseline transformers selected during the L CC analysis was 99.18 perc ent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.81 percent. The consumer equipmen t cost bef ore insta llation, w hich incl udes the manufacturer se lling pr ice, ship ping co sts, distributor markup, and retail markup, was $33,590.00. Table 8.5.2 and Fig ure 8.5.2 illustrate the LCC sensitivity to cha

nges in the five user-selectable va riables for design line 12. Each of the sensitivit y r uns for a ll the var iables c auses some change in the LCC results. The cha nges in results tend to increase with the efficiency of the candidate standard level. For de sign line 12, the chan ge in pe rcenta ge of tr ansformers purc

hased usi ng A & Bevaluat

ion resul ts in signific antly

large r changes in the L

CC saving s than do the other variable s for all b ut the hig hest two candidate standard levels examined. As with design line 1, this outcome occurs be cause the purchase behavior described by A & B evaluation strongly affects how much energy is used when there is no s tandard, and thus affects the potent ial savings. The high savin gs from the lo w A & B distribution case result from the fact that the Department assumes that fe w purchasers place an economic value on l osses in that scena rio withou

t standar ds. For mo st candid

ate standard levels, the variable labeled A & B D istribution stands sig nifican tly a part from the othe

r varia bles. L CC savings tend to increase as efficie ncy level incr

eases up to candidate standard level 4, and drop off for levels 5 and 6. At the higher ef ficiency le

vels of 5 and 6, low loading, high material8-52

prices, low A & B evaluat ion, and h igh ele ctricity

prices a ll result in

signific ant drops

in LCC savings

. Table 8.5.2 Mean Life-Cycle Cost Savings ($), Summary for Design Line 12

Represe ntative U nit
Scenario Candidate Standard Level 1 (TP 1) 2 3 4 5 6 Baseline 2,600 3,973 5,485 6,812 -650 -655 Non-Evaluating A & B Distribution 11,033 15,868 19,944 22,607 15,289 15,436 High-Evaluating A & B Distribution 424 877 1,646 2,732 -4,641 -4,699 Low L oading 2,145 3,238 4,046 4,578 -5,234 -5,091 High Loading 2,713 4,481 6,051 8,125 1,947 1,790 Low Electricity

Price 2,063 3,254 4,186 5,153 -3,705 -3,500 High Electricity

Price 2,917 4,748 6,340 8,458 2,232 2,044 Medium Load Grow

th 2,783 4,370 6,270 8,598 2,642 2,386 High Load Grow

th 2,984 4,436 6,497 9,108 4,525 4,184 Low E quipment Pr

ice Scenario 2,496 3,725 4,993 6,410 1,319 1,596 High Equ ipment Pric e Scena

rio 2,534 4,279 5,906 7,091 -5,842 -5,7978-53

Figure 8.5.2 Design Line 12 Sensitivity Results by Candidate Standard

Level

8.6 PAYBAC K PERI OD The PBP analysis is a common tec hnique used to evaluate investment decisions. A more energy-effi cient devic e will usual ly cost m ore to purch ase th an a dev ice of s tanda rd ener gy efficiency . However, the more efficient device will usually cost less to operate, due to the reducti on in ener

gy use. The pay back pe riod is the time (usua

lly e xpressed i

n ye ars) it ta

kes to recove r the add itional fi rst cost of the eff icient de vice, thr ough its e nergy cost savi ngs. Be cause the LCC analysis uses distributions of inputs, DOE gives results such as pay back periods in the form of d istributions. 8.6.1 Payback Period The PB P is t he rati o of th e incre ase in purch ase ex pense (i.e. , from a less effici ent de sign to a more efficient design) to the decr ease in annual operating expenditures. This ty pe of calculation is known as a simple pay back pe riod bec ause it do es not tak e into ac count cha

nges in operating expense over time. Payback pe

riod is found using the equation:8-54 Eq. 8.8

where: ) FC

= installed

purchas e price

(first c ost) of a

transformer sat

isfy ing the c andidate standard level minus the installed purchase price (first cost) of a transformer in the absence of the standard (assumes the transf ormer meeting the standard is more expensive than the transformer not subject to the standard) (2004$), and ) OC = operating cost of the transformer not subject to the standa rd minus the operating cost of the transformer subject to the standard (assumes the trans forme r meet ing th e candi date s tanda rd lev el has lower energy consumption, and hence lower operating cost, than the transformer not subject to the standard). Because ) OC is expresse d in annua

l terms, PB P is expressed in years. 8.6.2 Inputs The inputs to PBP are: 1) the purchase expense, otherwise known as the total installed consumer cost, or first cost, for each selecte d design; and 2) the annual (first y ear) operating expenditures for each selected design. The inputs to the purchase expense are the equipment price and the installation cost with appropriate markups. The inputs to the operating costs are the annual (first ye ar) energy

consumption and the electricity price. The distributional PBP uses the same inpu

ts as the LCC analy

sis descr ibed in se ction 8.3, except tha t, since th is is a simple pay back, the electri city

price the Depar

tment used

is only for the y ear the standar d takes e ffect, assumed here to be 2010. 8.6.3 Baseline Sc enario Co mplicat ions Since dist ribution tr

ansformers are

not curr ently subject to

energ y- efficie ncy standar ds, the Department developed the baseline scena rio to estimate transformer purchase behavior in the curren t market. The Depa

rtment’s default assumption s for the

baseline scenar io were t hat some portion of transformer purchase decisions are based on TOC-type

evaluations. Specifically , the default assumptions for the use of TOC-ty pe evaluation are 75 percent for liquid-immersed transformers and 50 percent for medium-voltage, dry-ty pe transformers, all using distributions of A and B evaluation factors. Especially at the lower candidate standard levels eva luated by the Department, the transformer purchase s based on TOC may not satisfy the basic PBP assumptions of highe r purchase price

and lowe r opera ting costs for the

transformers sub

ject to the

candida te standar d. When the se basic

assumption s are not

satisfie d, the tra

ditional PB P calcula

tion loses i

ts va li di ty. For example, a current (i.e., not subject to standards) tra nsformer purchase decision based on TOC may

have ide ntical fi rst cost ( ) FC

= 0) to a transformer just meeting TP 1, i.e.,8-55

candidate standard level 1. I n addition, the transformer meeting the standard may have a different operating cost from the transformer pur chased without the standard. In suc h a situation, PBP = 0. In another example, a curr ent transformer purchase decision based on T OC may result in a transformer costing more to purchase a nd install and consuming less electricity than a transformer tha

t just meet s TP 1. I

n this cas e, the PB P calcula tion for the standa

rds case is nonsensical, since it would imply a negative payba ck period. The Department’s method of calculating PB P is shown below. ) FC = FC(Standard) - FC(Baseline)

( ) FC is normally positive) ) OC = OC(Standard) - OC(Baseline)

( ) OC is normally neg ative) PBP = - ) FC / ) OC

(For the normally

positive ) FC

and the normally negative ) OC , PBP is positive) Because ) FC

can also be zero or negative, and be cause ) OC can also be zero or negati ve, ther e are ni ne possibl e cases

that can be gro uped into f

ive compu

tational c ases. Ta

ble 8.6.1 shows these nine possible relationships between ) FC and ) OC

and the resultant effect on PBP. Table 8.6.1 Possible ) FC and ) OC

Combinat

ions, for P ayback P eriod Anal ysis Case # Possible Cases Effect on PBP Calculation 1 ) FC

> 0 and ) OC

< 0 Well-defi ned PBP 2 ) FC

= 0 and ) OC

= 0 Unaffected by the standard 3 ) FC

< 0 and ) OC

= 0 ) FC > 0 and ) OC

= 0 Division by zero: PBP is undefined 4 ) FC

= 0 and ) OC

> 0 ) FC = 0 and ) OC

< 0 PBP = 0 5 ) FC

< 0 and ) OC

< 0, or ) FC > 0 and ) OC

> 0, or ) FC < 0 and ) OC

> 0 Not valid: negative or double negative

PBPa

For simplicit

y of presentat ion, Cases 3, 4, and 5 in Table 8.6.1 have been grouped together int o the “Transformers having Und efined Payb ack P eriod ” cate gory in T ables 8.6.2 throug h 8.6 .14. 8-56 8.6.4 Payback Period Results Tables 8. 6.2 throug

h 8.6.11 ill

ustrate, for eac

h of the 10

design l ines and t

heir 6 ca ndidate standard levels, the mean PBP and the percentage of the 10,000 Monte Carlo simulations where the PBP calculation applies. For each candida te standard level for each desig n line, the sum of the categories “Transfor

mers Unaffected by

the Standard,” “Transformers having Well-Defined Payback Period,”

and “Transformers having Unde fined Paybac k Period” should equal 100 percen t. a As the ef

ficienc y of the cand idate sta ndard le vels incr eases, t he perc entage

of purchase decision s where

the PBPs a

re well- defined

increa ses. A complete se t of PBP histogram s for all cases presented in these tables is included in Appendix 8A. 8.6.5 Design Line 1 Results Table 8.6.2 presents the summary of the PBP analysis for

the representative unit from design l ine 1, a 50

kVA, liqui d-immers ed, single-phas e, pad-m ounted tr ansformer. For

this unit, the average effic iency of the baseline transformers selected during the L CC analysis was 98.97 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 98.56 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $1,382.00.

Table 8.6.2 Summa ry of Pay back Per iod Results

for Design L ine 1 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 11.4 21.9 36.0 15.5 24.4 45.0 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 65.2 50.9 14.7 4.6 2.1 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 34.0 47.6 81.8 95.1 97.7 99.3 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 0.8 1.5 3.5 0.3 0.2 0.7 Mean Incr ement al Fi rst Cost ( $) 166 312 494 509 878 1679 Mean Operating Cost

Savi ngs ( $) 22 24 23 36 43 46 8.6.6 Design Line 2 Results Table 8.6.3 presents the summary of the PBP analysis for

the representative unit from design l ine 2, a 25 kVA, liqui d-immers ed, single-phas e, pole-mounted tr ansformer. For

this unit, the average effic iency of the baseline transformers selected during the L CC analysis was 98.748-57

percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 98.23 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $737.00. Table 8.6.3 Summa ry of Pay back Per iod Results

for Design L ine 2 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 4.8 6.8 8.8 12.0 31.7 66.6 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 66.6 64.3 60.8 56.3 25.4 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 28.3 34.4 37.2 40.9 71.3 100 .0 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 5.1 1.3 2.0 2.8 3.3 0.0 Mean Incr ement al Fi rst Cost ( $) 32 49 59 76 239 1,475 Mean Operating Cost

Savi ngs ( $) 13 13 12 12 12 25 8.6.7 Design Line 3 Results Table 8.6.4 presents the summary of the PBP analysis for

the representative unit from design l ine 3, a 50 0 kVA, liqu id-immersed, single-phas e distribu tion trans former. For this u nit, the average effic iency of the baseline transformers selected during the L CC analysis was 99.36 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 99.07 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $5,428.00.8-58

Table 8.6.4 Summa ry of Pay back Per iod Results

for Design L ine 3 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 1.4 4.3 10.4 19.8 29.3 32.3 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 73.7 65.2 49.5 4.0 0.1 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 16.8 34.4 50.1 93.5 99.8 100 .0 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 9.6 0.4 0.5 2.6 0.0 0.0 Mean Incr ement al Fi rst Cost ( $) 131 628 1,302 1,871 8,287 9,332 Mean Operating Cost

Savi ngs ( $) 292 303 290 212 397 398 8.6.8 Design Line 4 Results Table 8.6.5 presents the summary of the PBP analysis for

the representative unit from design l ine 4, a 15 0 kVA, liqu id-immersed, thre e-phase distributi on transf

ormer. F or this unit , the average effic iency of the baseline transformers selected during the L CC analysis was 98.91 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 98.42 per

cent. The consumer equipment cost before installation, which includes the manufacturer selling price, shipping costs, distributor markup, and retail markup, was $3,335.00. Table 8.6.5 Summa ry of Pay back Per iod Results

for Design L ine 4 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 8.5 18.1 21.5 17.0 29.2 34.9 Tr an s f orme rs Un af

f ec t edbyt he St an da rd( %) 63.7 40.8 11.3 9.7 0.8 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 35.4 58.3 88.4 90.3 99.0 99.9 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 1.0 0.9 0.3 0.0 0.3 0.1 Mean Incr ement al Fi rst Cost ( $) 484 898 1,543 1,948 3,336 4,195 Mean Operating Cost

Savi ngs ( $) 93 88 102 136 158 166

8.6.9 Design Line 5 Results Table 8.6.6 presents the summary of the PBP analysis for

the representative unit from design l ine 5, a 15 00 kVA, liq uid-immersed, thre e-phase distributi on transf

ormer. F or this unit , the average effic iency of the baseline transformers selected during the L CC analysis was 99.36 percen t and the m

inimum eff

iciency of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 99.13 per

cent. The consumer equipment cost before installation, which includes the8-59

manufacturer selling price, shipping costs, distributor markup, and retail markup, was $11,931.00. Table 8.6.6 Summa ry of Pay back Per iod Results

for Design L ine 5 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 3.4 6.1 12.7 14.1 25.6 26.1 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 71.7 62.8 40.0 24.2 0.0 0.1 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 28.3 37.1 59.1 75.0 99.9 99.9 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 0.0 0.1 1.0 0.8 0.1 0.1 Mean Incr ement al Fi rst Cost ( $) 1,489 2,581 3,066 4,439 19,736 19,728 Mean Operating Cost

Savi ngs ( $) 638 707 569 574 1,064 1,037

8.6.10 Design Line 9 Results Table 8.6.7 presents the summary of the PBP analysis for

the representative unit from design line 9, a 300 kVA, medium-voltage, dry -type, three -phase transformer with a 45kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 98.77 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.41 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $7,510.00.

Table 8.6.7 Summa ry of Pay back Per iod Results

for Design L ine 9 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 1.5 2.4 5.4 12.4 21.7 21.5 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 57.8 46.3 29.7 0.5 0.0 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 33.0 53.4 69.6 98.6 99.7 99.7 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 9.1 0.3 0.7 0.8 0.3 0.3 Mean Incr ement al Fi rst Cost ( $) 169 396 996 2,528 6,528 6,510 Mean Operating Cost

Savi ngs ( $) 174 263 350 397 503 5088-60

8.6.11 Design Line 10 Results Table 8.6.8 presents the summary of the PBP analysis for

the representative unit from design line 10, a 1500 kVA, medium-voltage, dry -type, three -phase transformer with a 45kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 99.17 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.79 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $33,584.00. Table 8.6.8 Summa ry of Pay back Per iod Results

for Design L ine 10 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 7.7 8.3 10.0 13.4 28.7 29.4 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 63.3 56.9 44.4 23.2 0.0 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 35.9 41.8 55.3 75.7 99.7 99.7 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 0.8 1.2 0.3 1.1 0.3 0.3 Mean Incr ement al Fi rst Cost ( $) 4,085 5,161 6,858 8,382 18,989 19,021 Mean Operating Cost

Savi ngs ( $) 1,000 1,141 1,236 1,199 1,316 1,315

8.6.12 Design Line 11 Results Table 8.6.9 presents the summary of the PBP analysis for

the representative unit from design line 11, a 300 kVA, medium-voltage, dry -type, three -phase transformer with a 95kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 98.42 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.05 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $10,945.00.8-61

Table 8.6.9 Summa ry of Pay back Per iod Results

for Design L ine 11 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 3.8 4.9 7.9 11.8 15.1 14.8 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 42.5 34.6 18.7 2.3 0.0 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 57.2 64.5 80.1 96.3 99.6 99.6 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 0.4 0.8 1.1 1.4 0.4 0.4 Mean Incr ement al Fi rst Cost ( $) 733 1,263 1,991 3,058 4,399 4,412 Mean Operating Cost

Savi ngs ( $) 332 445 484 525 556 567 8.6.13 Design Line 12 Results Table 8.6.10 presents the summary of the PBP analysis for

the representative unit from design line 12, a 1500 kVA, medium-voltage, dry -type, three -phase transformer with a 95kV BI L. For this u nit, the a verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analy sis was 99.18 percent and the minimum efficiency of the baseline transformers selected during the LCC analysis was 98.81 percent. The consumer equipment cost before installation, which includes the manufacturer selling price , shipping costs, distributor markup, and retail markup, was $33,590.00. Table 8.6.10 Summa ry of Pay back Per iod Results

for Design L ine 12 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 4.6 4.7 8.3 12.7 29.3 29.3 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 75.1 71.9 56.9 28.2 0.0 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 24.7 27.9 42.3 69.9 99.7 99.9 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 0.2 0.2 0.8 1.8 0.3 0.2 Mean Incr ement al Fi rst Cost ( $) 2,125 3,204 4,500 6,356 20,409 20,440 Mean Operating Cost

Savi ngs ( $) 827 1,127 1,129 1,051 1,290 1,286 8.6.14 Design Line 13 Results Table 8.6.11 presents the summary of the PBP analysis for

the representative unit from design line 13, a 2000 kVA, medium-voltage, dry -type, three -phase transformer with a 125kV BIL . For this

unit, the a

verag e effic iency

of the ba seline tr

ansformers sele cted dur

ing the L CC analysis was 99.26 per

cent and the minimum efficiency of the baseline transformers selected during the LCC analy

sis was 98.97 percent. The consumer equipment cost before installation,8-62

which inc ludes the

manufacturer se lling pr

ice, ship ping co sts, distri

butor mar kup, and r

etail markup, was $41,873.00.

Table 8.6.11 Summa ry of Pay back Per iod Results

for Design L ine 13 Repr esentat ive Unit Candidate Standard Level 1 (TP 1) 2 3 4 5 6

M ean Pa yback P eriod (Y ears) 9.7 5.8 8.0 19.5 32.5 32.4 Tr an s f orme rs Un af

f ec t ed byt he St an da rd( %) 76.0 72.9 58.9 5.4 0.0 0.0 Tr an s f orme rs ha vi ng Wel l

- De f i ne d P ay ba ck Pe ri od ( %) 23.6 27.0 40.2 93.6 99.8 99.8 Tr an s f orme rs ha vi ng Un de f

i ne d P ay ba ck Pe ri od ( %) 0.4 0.1 1.0 1.1 0.2 0.2 Mean Incr ement al Fi rst Cost ( $) 1,230 3,614 5,668 10,087 29,292 29,128 Mean Operating Cost

Savi ngs ( $) 265 987 1,240 1,107 1,562 1,556

8.7 REBUTTABLE PRESUMP TION The reb uttable presumption is a simpli fied method of dete rmining the econ omic justification of a proposed energy -efficiency

standard. In evaluating

the rebuttable presumption, the Department estimates the additional cost of purchasing a more efficient, standard-compliant product, and compares this cost to the value of the energ y savings dur

ing the first ye ar of operati on of the product a s determi ned by the appli cable te st proce dure. If the add itional fi rst cost is les s than thr

ee times t he value of the energy

savings , then the

re shall b e a rebu

ttable presumption that such a standard level is economically justified. The Department evaluates the rebuttable pre sumption by calculating a rebuttable pay

back period, which is the ratio of the value of the first y ear's energy

savings, determined from the applicable test procedure, to the increase in purchase price. When the rebuttable pay back period is less than three ye ars, the rebuttable presumption is satisfied; when it is equal to or more than three ye ars, the rebuttable presumption is not satisfied. The rebuttable pay

back period differs from pay back periods presented in other parts of this chapter in two

important

ways:

• The rebuttable pay

back period uses test procedure loading levels to evaluate losses, rather than the D epartme

nt’s estimate of in-servic e loading condition s.

• Other pa

yba ck perio ds may

consider total ope rating costs, whereas t

he rebut table presumption paybac

k period considers only the value of energy

savings. In the case of8-63

distribution transformers, however, the Department estimates that the cha nge in operating costs is sol ely

due to ene

rgy savings

.
There a re thr ee key inpu ts in to th e rebut table payback cal culat ion: (1) th e average effici ency; (2) t he aver age ins tall ed cos t; and (3) th e cost of elec trici ty. Given the av erage efficiency of the transformer, the Department calc ulated the losses on the transformer assuming the loadi ng cond itions fro m the test procedur

e. Multiply

ing the l osses time s the cost of electricity provided the operating cost, and then dividing incre mental operating costs into incremental installed cost provided the estimate of the rebuttable pay back period. Tables 8.7.1 through 8.7.4 show the different inputs into the rebuttable pre sumption paybac k period calculation. Table 8.7.1 shows the average transformer efficiency as a function of design line and standard level. This is the average efficiency as determined by

the customer choice model of the LCC calcula tion. The customer choice model provides a rang e of transformer de sign ef

ficienc ies that de

pends on a

distributi on of cust

omer cho ices with

respect to the value that customers place on reducing transformer design losses. Table 8.7.2 shows the average transf

ormer pu rchase price a s a funct

ion of both

design l ine and st

andard l evel. Ta

ble 8.7.3 shows the average marginal cost of electricity as a function of both design line and standard level. There is a substantial difference be tween the marginal cost of electric ity for liquidimmersed and dry-type transfor mers because liquid-immersed transformers tend to be owne d by utilities, which pay the wholesale ( rather than retail) cost of electricity . Table 8.7.4 shows the first-yea r operating cost, which is the annual losses calculate d from the test procedure assumptions times the average marginal c ost of electricity. Table 8.7.5 shows the rebuttable pay back period as a function of design line and sta ndard level. The table records how the rebuttable pr esumption is not satisfied for any ca ndidate level for desi gn lines

1, 2, 4, 10, and 13. F or desig n line 5, it i s satisfie d for ca ndidate standard

level 1 only. For desig

n lines 3, 11, and 12, it is satisfied for candidate standard levels 1 and 2. For design line 9, it is satisfied for levels 1 through 3. Assuming

the desig n line re sults are

repres entative

of the correspon

ding ra ted capa city ranges as specified in the engineering chapter (Chapter 5) , the rebuttable presumption results by product class are as follows: The rebuttable pre sumption condition is not satisfied for product class 1 for any

candidate standard level for the small size categories of pad-mounted transformers while it is satisfied for the pole-mounted transformers for candidate standard level 1. For the larger rated capa

cities for product class 1, the rebuttable presumption is satisfied for levels 1 and 2. For pr oduct class 2 (thre e-phase , liquid-im mersed tr ansformers), the rebutt

able pre sumption is satisfie d for only

candida te standa rd level 1 for the large r rated capaci ties. For product c lasses 5 and 6, the rebuttable presumption is satisfied for candidate standard le vels 1 through 3 for the smaller r ated ca pacities , and not sa

tisfied a t all for t he larg er tran sformers. For pr oduct classes 7 and 8, the rebuttable presumption is satisfied for levels 1 and 2 for all rate d capacities. And for product classes 9 and 10, the rebuttable presumption is not satisfied for any candidate standard level.8-64

Table 8.7.1 Average Transformer Efficiency Design Line Rated

Capaci ty kVA Base

% CSL 1 (TP 1) % CSL 2

% CSL 3

% CSL 4

% CSL 5

% CSL 6

% 1 50 98.97 99.06 99.12 99.23 99.39 99.50 99.59 2 25 98.74 98.84 98.86 98.87 98.88 98.99 99.47 3 500 99.36 99.43 99.46 99.49 99.55 99.74 99.75 4 150 98.91 99.06 99.16 99.33 99.48 99.59 99.61 5 1,500 99.36 99.41 99.44 99.46 99.49 99.71 99.71 9 300 98.77 98.86 98.96 99.08 99.26 99.41 99.41 10 1,500 99.17 99.26 99.30 99.35 99.41 99.51 99.51 11 300 98.42 98.66 98.76 98.89 99.03 99.11 99.11 12 1,500 99.18 99.24 99.27 99.30 99.37 99.52 99.52 13 2,000 99.26 99.27 99.31 99.36 99.46 99.56 99.568-65

Table 8.7.2 Average

Transform er Instal

led Cost Design Line Rated

Capaci t y kVA Base

$ CSL 1 (TP 1) $ CSL 2

$ CSL 3

$ CSL 4

$ CSL 5

$ CSL 6

$
1 50 2,884 2,943 3,036 3,307 3,366 3,742 4,565 2 25 1,877 1,886 1,894 1,901 1,910 2,056 3,350 3 500 7.889 7,927 8,096 8,564 9,691 16,135 17,234 4 150 5,784 5,957 6,321 7,148 7,547 9,094 9,977 5 1,500 18,125 18,522 19,137 19,993 21,566 37,779 37,781 9 300 9,721 9,778 9,932 10,413 12,209 16,248 16,244 10 1,500 33,454 34,805 35,667 37,244 39,811 52,502 52,498 11 300 13,554 13,986 14,363 15,164 16,512 17,951 17,950 12 1,500 36,477 37,029 37,396 38,274 40,962 56,915 56,940 13 2,000 45,191 45,507 46,127 47,488 54,602 74,433 74,4408-66

Table 8.7.3 Average

Marginal E lectric

ity Cost Design Line Rated

Capaci ty k VA Base

$ CSL 1 (TP 1) $ CSL 2

$ CSL 3

$ CSL 4

$ CSL 5

$ CSL 6

$ 1 50 0.044 0.045 0.044 0.043 0.048 0.046 0.043 2 25 0.043 0.043 0.043 0.043 0.043 0.043 0.043 3 500 0.043 0.043 0.043 0.043 0.043 0.044 0.043 4 150 0.043 0.043 0.043 0.045 0.045 0.043 0.043 5 1,500 0.042 0.042 0.042 0.042 0.042 0.042 0.042 9 300 0.067 0.067 0.067 0.067 0.066 0.066 0.066 10 1,500 0.066 0.066 0.066 0.066 0.066 0.065 0.065 11 300 0.067 0.068 0.067 0.067 0.067 0.067 0.067 12 1,500 0.066 0.066 0.066 0.066 0.065 0.064 0.064 13 2,000 0.065 0.065 0.066 0.066 0.065 0.064 0.0648-67

Table 8.7.4 First Year Oper ating Cost for Rebutt able Pr esumption, Based on D OE Test Procedure Design Line Rated

Capaci ty kVA Base

$ CSL 1 (TP 1) $ CSL 2

$ CSL 3

$ CSL 4

$ CSL 5

$ CSL 6

$ 1 50 101 92 86 74 65 51 39 2 25 60 55 55 54 53 48 25 3 500 610 537 514 479 423 247 237 4 150 311 267 238 197 155 119 109 5 1,500 1,782 1,628 1,555 1,495 1,399 799 799 9 300 1,090 1,012 930 816 646 512 512 10 1,500 3,614 3,197 3,037 2,816 2,564 2,081 2,081 11 300 1,419 1,205 1,108 994 858 794 794 12 1,500 3,564 3,322 3,191 3,027 2,716 2,058 2,057 13 2,000 4,264 4,200 3,981 3,710 3,114 2,515 2,5158-68

Table 8.7.5 Rebuttable Payback for Rebuttable Presumption Pe riod Design Line Rated Capacity kVA CSL 1

(TP 1) yrs CSL 2

yrs CSL 3

yrs CSL 4

yrs CSL 5

yrs CSL 6

yrs 1 50 7.0 10.1 16.0 13.6 17.21 27.2 2 25 2.1 * 3.6 4.3 5.2 15.2 42.4 3 500 0.5 * 2.2 * 5.1 9.7 22.7 25.1 4 150 3.9 7.4 12.0 11.3 17.2 20.7 5 1,500 2.6 * 4.5 6.5 9.0 20.0 20.0 9 300 0.7 * 1.3 * 2.5 * 5.6 11.3 11.3 10 1,500 3.2 3.8 4.8 6.1 12.4 12.4 11 300 2.0 * 2.6 * 3.8 5.3 7.0 7.0 12 1,500 2.3 * 2.5 * 3.3 5.3 13.6 13.6 13 2,000 5.0 3.3 4.1 8.2 16.7 16.7
* Values les s than 3 i ndicate arebut tabl e pres umpti on th at t he st andard leve l i s econ omical lyjus ti fi ed.

8.8 USER INSTRU CTIONS FO R SPREAD SHEETS

To execute the LCC spreadsheet, it is nece ssary for the user to have the appropr iate har dware a nd softwa re tools. The Depa

rtment as sumed the

user has a reasonably current computer operating under the Windows operating system. The development team uses relative ly new systems and has not de fined the

minimum sy

stem requ irements . At a minimu

m, users need Microsoft Excelto execute the spre adsheet . For fu

ll functionality

in running

Monte Carlo simulations, users will need a copy of a spreadsheet add-in called Cry stal Ball, in addition to Excel . Without Cry

stal Bal l , one ca

n still use t

he LC C spreadsheet mod el, but wil l not be ab le to examine inputs and outputs as distributions. Approximate results are provided through a sample calculation that uses average values for the inputs and outputs, as displaye d in the “Summary

” worksheet.

8.8.1 Startup The LCC spreadsheet is a stored Excel file. I t can be found on the DOE website at http://www.eere.energy .gov/buildings/appliance_standards/commercial/distribution_transformers .html Open the file. (Each computer system will have a unique setup for loading a file. Users should refer to their software manuals if they have problems loading the spreadsheet file.) For8-69

users new to Excel and/or Cr yst al Ball , section 8.7.2 contains basic instructions for operating the LCC spr eadshee ts. 8.8.1.1 Sheet Overview Each of the LCC spreadshe ets for the five liquid-immersed transformer design lines contains the follow

ing 17 worksheet s:

C Options

C Description

C Summary

C A & B Distribution

C Design

Table

C Load & Price Para

meters
C Utilities

C Discount R

ate
C Hourly Loads

C Hourly Prices

C Annual Energy

Price Forecast
C Baseline LCC

C Design

Option LCC

C Life time

C Load -Price Charts
C Results - LLvN

L

C LL vs NL Each of the LCC spreadshe ets for the eight dry -type transf

ormer design lines contains the following 17 worksheets:

C Description

C Summary

C A & B Distribution

C Design

Table

C Deman d & Usage

C Utilities

C Discount R

ate
C Annual Energy

Price Forecast
C Baseline LCC

C Design

Option LCC

C Life time

C Load -Price Charts
C Results - LLvN

L8-70

C LL vs NL

C Tariffs

C Component s
C Options Most of the worksheets consist of the data inputs used in the spreadsheet calc ulations. To ensure functionality in the spr eadsheet model while maintaining reasonable size, DOE preprocessed some variables into a representa tive equation. “Hourly L oads” and “Hourly

Prices” are the two be st examples

of using an equa tion (Fou rier tra nsform) t o express a

complex set of data in an equation. The “Load- Price Charts” worksheet provides a gra phical expression of the “Hourly L

oads” and “Hourly

Prices.” The spreadsheet/user interface is centered in the “Summary ” worksheet. This worksheet contains a number of user-selectable options. These options, ea ch with its own pull-down menu, are:

• Candidate Standard Level

• Transformer Loa

d Growth/Year

• Transformer Loa

ding

• Electricity Prices

• Transformer C ustomer As & Bs

• Future Energy

Price Trend

• Eq ui pm en t P ri ce Sc en ar io (l iq ui d- im me rs ed on ly)

• Efficie

ncy Standard Effect ive Date Changing user-selectable options will produce average results shown on the “Summary ,” i.e., results using the mean inputs. Because of the ve ry nature of Monte Carlo mathematics, the average results

will not be

identica l to the mea

n of the di stribution

produce d from Mon

te Carlo Cry stal Bal l simulation s, but will provide qu ick fee dback re flecting

nominal re sults to spreadsheet use

rs. The D epartme

nt conducted an exa

mple Monte

Carlo run

of 100 ite

rations to produce “Results-LL

vNL” which is shown gr

aphically as “LL

vs NL.” Selecting diff

erent st and ard lev els in th e “S um mar y” wo rks hee t wi ll pro duc e a d iff ere nt gra phi cal res ul t o n t he “ LL vs NL ” sheet, as well a s differ ent aver age re sults on the

“Summary

” worksheet.a

Bec ause o f the natur e of the p rogra m, there is some variatio n in resu lts due to rand om s amp ling whe n M onteC arlo or Lat in Hypercube sampl ing is used. 8-71 8.8.2 Basic Instructions for Operating the Life-Cycle Cost Spreadsheets 1. Once you ha

ve downloaded the LCC file from the Web, open the file using Excel . At the bottom, click on the tab for sheet “Summary .” 2. Use Excel ’s View/Zoom commands at the top menu bar to chang e the size of the display to make it fit your monitor. 3. You can interact with the spreadsheet by clicking choices or entering da ta using the graphical interface that c omes with the spreadsheet. Select choices from the various userselecta ble option s. To produc e sensitiv

ity r esults usin

g Crystal Bal l, select Run from the Run menu (on the menu bar). To make basic chang es in the Run sequenc e, includ ing alte ring the number of

trials, select Run Preferences from the Run menu. After each simulation run, the user needs to select Reset (also from the Run menu) before Run can be se lected a gain. Once Cry

stal Bal l has completed its run sequence, it will produce a series of distributions. Using the menu ba rs on the distributi on result s, it is possi ble to obta

in furthe r statistic al information. The time take n to complete a run seq uence c an be re duced by

minimizing

the Cry stal Bal l window in Excel. A step-by-step summary

of the procedure for running a distribution analysis is outlined below: 1. Find the Crystal B all toolbar (at top of screen). 2. Click on Run from the menu bar. 3. Select Run Preferencesand choose either Monte Carlo or L atin Hyperc ube. a Select number of Trials (the Department suggests 10,000). 4. To run the simulation, choose the following sequence (on the Cry stal Ball toolbar) Run Reset Run 5. Now wait until the program informs y ou that the simulation is completed. The Department provides the following instructions to view the output ge nerated by Cry stal Bal l: 1. After the simulation has finished, click on the Windows tab bar labeled Crystal Ball to see the distri bution cha

rts.

2. The L CC saving s and pay backs ar e define d as Forecas t

cells. The frequ

ency charts8-72

display the results of the simulations, or trials, perf ormed by Cry

stal Ball. Click on any chart to bring it into view. The charts show the low and hig h endpoints of the forecasts. The Viewselection on the Crystal B all toolbar can be used to specify whether cumulative or frequency

plots are to be shown.

2a. To calculate the probability that a particular value of L CC savings will occur, either ty pe 0 in the

box by the left a rrow, or move the a

rrow ke y with the cu

rsor to 0 on the scale. The value in the Certainty box shows the

likelihood

that the LCC savings will occur. 2b. To calculate the certainty of the payba

ck period being below a certa in number of ye ars, inser

t that value in the far

-rig ht box. 3. To gene

rate a printed re

port, sel ect Create Re

port from the Run menu. The toolbar choice of Forecas t Wind

ows allows you to select the c harts and statistics in which you ar e interested. For further information on Cry stal Ball outputs, refer to Understanding the Forecas t Chart

in the Cry

stal Bal l manual.8-73 REFEREN CES

1. National Electrical Manufacturers Associa tion. NEMA Standards Publication TP 1-2002; Guide for Determini

ng Energy

Efficienc y for Distr

ibution Tran

sformers. 2002. National Electrical Manufacturers Association. Rossly n, VA. Report No. TP 1-2002. 2. Institute of Electrical and Elec tronics Engineers I

nc. Draft Guide for Distribution Transformer Loss Evaluation. October, 2001. 345 East 47th Street, New York, NY. Report No. IEEE PC57.12.33/D8. 3. Gray, E. Energy Conservation Program for Consumer Products: Energy Conservation Standards for Distribution Transformers, DOE Docket Number EE-RM/ST-00-550, comment No. 26. October 25, 2002. National Electrical Manufactur ers Association. 4. U.S. Department of Energy - Energy Information Administration. Annual Energy Outlook 2005: With Projections Through 2025. January, 2005. Washington, DC. Report No. DOE/EI A-0383(2005). <

http://www .eia.doe .gov/oia f/aeo/in dex.html> 5. Saint, R. - Principa l Engine er Resea

rch & Te chnical

Service s Nationa

l Rural Ele ctric Cooperative Association (NRECA). E-mail to Antonio Bouza, DOE, Distribution Transformer Purchases by Co-op. Personal communication. March 8, 2005. 6. University of Alaska - Fairbanks. Request for Proposals No. 04P0016DH - High Voltage Transformer. 2005. (Last accesse d March 9, 2005.) This material is available in Docket #83. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energ y, Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://www.uaf.edu/purch/04_solicitations/04P0016DH.pdf> 7. Sandia National Laboratories. Specification 16464 (SE-US-83-2), Spe cifications for Power Transformer, Substation 37, 115/12.47kV 12/16/20MVA Transformer. 5/1/91. (La st accessed March 9, 2005.) This material is available in Docket #83. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy , Building Technologies Program, Mailstop EE2J, 1000 Independence Avenue , SW, Washington, DC, 20585-0121, telephone (202) 586- 2945 for more information. <http://www.sandia.gov/engstds/ConstSpecs/Special/Miscellaneous/Div_16/16464_Power _Transformer.doc> 8. ATCO Electric Ltd. Phase II Distribution Tariff Application: Application No. 1349514. Information Responses. 2004. (La st acce ssed Mar ch 3, 2005 .) This ma

terial is availab le in Docket #83. Contact Ms. Brenda Edwards-Jones, U.S. Department of E nergy , Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information.8-74

<http://www.atcoelectric.com/B_Regulatory/1349514_Responses/EX_02-006_AE_REAAAMDC_Responses_2004-09-23.pdf> 9. Greenville Utilities. Advertisements for Bids for Padmount Transformers. 2005. (La st accessed March 9, 2005.) This material is available in Docket #83. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy , Building Technologies Program, Mailstop EE2J, 1000 Independence Avenue , SW, Washington, DC, 20585-0121, telephone (202) 586- 2945 for more information. <http://www.guc.com/doing_business/PDF/05-08.pdf> 10. City of Dover - De laware. Specifications for Three Phase Pad-Mounted Distribution Transformers. (Last accesse d March 9, 2005.) This material is available in Docket #83. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energ y, Building T echnologies Program, Mailstop EE-2J, 1000 Independenc e Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://www.cityofdover.c om/media/bids/12-4%20KV%20Transformer%20Spec.pdf> 11. Brownsville Public Utilities Board. Legal Notice and Invitation to Bid for Polemount Transformers: B #033-05. 2005. (La st acce ssed Mar ch 9, 2005 .) This ma

terial is availab le in Docket #83. Contact Ms. Brenda Edwards-Jones, U.S. Department of Ene rgy , Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://www.brownsville-pub.com/bids/specs/2003/B03305.doc> 12. U.S. Department of Energy - Energy Information Administration. Annual Energy Outlook 2003: With Projections Through 2025. January, 2003. Washington, DC. Report No. DOE/EIA-0383(2003). < http://www.eia.doe.gov/oiaf/aeo> 13. U.S. Department of Energy - Federal Energy

Regulatory

Commission. Form No. 1 - Electric Utility Annual Report. 2002. (La st acce ssed Fe bruary 11, 2005.)

This mate

rial is av ai la bl e i n D oc ke t # 86 . C on ta ct Ms . B re nd a E dw ar ds -J on es , U .S . D ep ar tm en t o f E ne rg y, Buil ding Tech nolog ies Pr ogr am, Ma ilsto p EE- 2J, 100 0 I

ndep ende nce A venue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://www.ferc.gov/docs-filing/efor ms/form-1/form1_blank.pdf> 14. Shirley, W. Simplified Distribution System Cost Methodologies for Distributed Generation. February 2001. Regulatory

Assistance Project. (Last ac cessed June, 2002.) Discussion Draft. T his mater ial is ava ilable in D ocket #86 . Contact M s. Bren da Edwar ds-Jones, U .S. Department of Energy

, Building Technologies Progra m, Mailstop EE-2J, 1000 Independence

Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. Final, published version of paper is at:. < http:// www.raponli ne.org/Pubs /DRSeries /DistCo st.PDF> 15. U.S. Department of Energy - Energy Information Administration. Form EIA-861: Annual Electric Utility Data. 2001. (Last accesse d July, 2005.) This material is available in Docket8-75

#86. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energ y, Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://ww

w.eia.d oe.gov /cneaf /electr icity /page/ eia861.h tml> 16. U.S. Department of Energy -Energy Information Administration. 1995 Commercial Building Energy Consumption and Expenditures (CBECS). 1995. (Last accesse d May 19, 2005.) Pub lic Use D ata, Microdata f ile on EI A website . This mate

rial is available i

n Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. Department of E nergy , Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://ww

w.eia.d oe.gov /emeu/cb ecs/micr

odat.html> 17. National Oceanic & Atmospheric Administration - National Climactic Da ta Center. U.S. Standard Regions for Temperature & Pre cipitation. (La st acce ssed June 8, 2005.) Th is material is available in Docket #86. Contact Ms. Brenda Edwa rds-Jones, U.S. Department of Energy, Building Technologies Progra m, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://www.ncdc.noaa.gov/img/climate/resea rch/usrgns_pg.gif> 18. Barnes, P. R., J. W. Van Dyke, B . W. McConnell, and S. Das. Determination Analysis of Energy Co nservati

on Standar

ds for Distr

ibution Tran

sformers. 1996. Oak Ridge National Laboratory . Oak Ridge, TN. Report No. ORNL -6847. 19. Ibbotson Associates. Stocks, Bonds, Bills, and Inflation . 1999. I bbotson As sociate s: Chicago, IL

. 20. Modigliani, F. and M. Miller. The Cost of Capital, Corporation Finance and the The ory of Investment. American Economic Review . 1958. (June): pp. 261-297. 21. Bondsonline Group Inc. Bonds Online. 2003. (La st acce ssed Fe bruary 22, 2003.)

This material is available in Docket #86. Contact Ms. Brenda Edwa rds-Jones, U.S. Department of Energy, Building Technologies Progra m, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://ww

w.bondson

line.com > 22. Damodaran, A. Damodaran Online. 2003. St er n S ch oo l o f B us in es s, Ne w Y or k U ni ve rs it y. (La st acce ssed Fe

bruary , 2003.) T

his mater ial is ava ilable in D ocket #86 . Contact M s. Brenda Edwards -Jones, U. S. Depar tment of E

nergy , Building Technol ogies Pr

ogram, Mailstop EE-2J, 1000 Independence Avenue , SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://www.stern.nyu.edu/~ada modar/New_Home_Page/data.html.> 23. U.S. Department of Commerce - Bureau of Economic Analysis. GDP price change: Q3,8-76

2000 - Q3, 2001. 2002. (La st acce ssed Fe bruary , 2003.) T

his mater ial is ava ilable in Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. Department of E nergy , Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585- 0121, tele

phone (2 02) 586-2 945 for more infor mation. Note: this qua

rterly report is no longe r acce ssible fr

om the BE

A site. <h ttp://www. bea.doc .gov/be a/glan ce.htm>

24. Bloomberg, L. P. Bloomberg Professional. 2003. (La st acce ssed Fe bruary , 2003.) T

his material is available in Docket #86. Contact Ms. Brenda Edwa rds-Jones, U.S. Department of Energy, Building Technologies Progra m, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://a bout.bloom

berg. com/prof

essional /profse rvice.h tml> 25. Value Line. Value Line Investment Survey. 2003. (La st acce ssed Janua ry , 2003.) T

his material is available in Docket #86. Contact Ms. Brenda Edwa rds-Jones, U.S. Department of Energy, Building Technologies Progra m, Mailstop EE-2J, 1000 Independence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://ww

w.value line.com

> 26. U.S. Office of Management and Budget. Circular No. A-94. Appendix C. 2002. (La st accessed November, 2002.) This material is ava ilable in Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. Department of Energy , Building Technologies Program, Mailstop EE2J, 1000 Independence Avenue , SW, Washington, DC, 20585-0121, telephone (202) 586- 2945 f or mor e inf orma tion. <http ://ww

w.whiteho

use. gov/ omb/c ircu

lars/a09 4/a9 4_ap

pxc.html> 27. Federal Reserve Boar d. Statistics : Releas es and His torical Da ta - Selected Int erest Rat es - State and Local Bonds. 2002. (La st acce ssed Fe bruary , 2003.) T

his mater ial is ava ilable in Docket #86. Contact Ms. Brenda Edwards-Jones, U.S. Department of E nergy , Building Technologies Program, Mailstop EE-2J, 1000 I ndependence Avenue, SW, Washington, DC, 20585-0121, telephone (202) 586-2945 for more information. <http://ww

w.fede ralrese rve.g ov/rele ases/h15 /data/m/s lbond.txt> 28. Ibbotson Associates. Cost of Capital 2001 Yearbook . 2001. Ibbotson Associates: Chicago, IL

. 29. HVOLT Consultants I nc., P. Hopkinson, and J. Puri. Distribution Transformer Market Shipment Estimates for 2001. Februa ry 17, 2003. 3 704 High

Ridge Roa

d, Charlotte, NC, 28270, tel: (704) 846-3290, e-mail: P.Hopkinson@hotmail.com. Prepared for Naviga nt Consulting, Inc., Washington DC.