10-i CHAPTER 10

. NATIONAL IMPACT ANALYSES

TABLE OF CONTENTS

10.1 INTRODUCTION ................................................................................................... 10-1
10.2 NATIONAL ENERGY SAVINGS ......................................................................... 10-2 10.2.1 PRIMARY ENERGY SAVINGS ............................................................................ 10-2 10.2.2 FULL

- FUEL

- CYCLE ENERGY SAVINGS .......................................................... 10-5 10.2.3 NATIONAL ENERGY SAVI NGS INPUTS .......................................................... 10-6 10.2.3.1 Shipments and Operating Stock Shipped during the Analysis Period ......... 10-6 10.2.3.2 Average Unit Energy Consumption ............................................................. 10-6 10.2.3.3 Site

- to -Power Plant Conversion Factor ....................................................... 10-8 10.2.3.4 Primary Energy to Full

- Fuel

- Cycle Multipliers ........................................... 10-8 10.2.3.5 Rebound Rate Factor .................................................................................... 10-9
10.3 NATIONAL NET PRESENT VALUE ................................................................... 10-9 10.3.1 DEFINITION ........................................................................................................... 10-9 10.3.2 NET PRESENT VALUE IN PUTS ........................................................................ 10-10 10.3.2.1 Total Annual Installed Cost Increases ....................................................... 10-10 10.3.2.2 Total Annual Operating Cost Savings ....................................................... 10-13 10.3.2.3 Discount Factor .......................................................................................... 10-16
10.4 RESULTS .............................................................................................................. 10-16 10.4.1 NATIONAL ENERGY SAVINGS RESUL TS ..................................................... 10-16 10.4.2 NET PRESENT VALUE RE SULTS ..................................................................... 10-20 10.4.3 ALTERNATIVE ANALYSES RESULTS ............................................................ 10-23 10.4.3.1 Overview .................................................................................................... 10-23 10.4.3.2 Alternative Scenario National Energy Savings Results ............................. 10-24 10.4.3.3 Alternative Scenario Net Present Value Results ........................................ 10-26

LIST OF TABLES

Table 10.1.1 Summary of NES and NPV Inputs .................................................................... 10-2 Table 10.2.1 Rebound Rate Scenarios for GSFL and IRL ...................................................... 10-9 Table 10.4.2 Cumulative NES for GSFLs and IRLs, for All CSCs, Best Estimate .............. 10-17 Table 10.4.3 Cumulative Net Present Value for GSFL and IRL (billion 2011$) ................. 10-20 Table 10.4.4 Cumulative Equipment Cost Increase, Best Estimate (billion 2011$) ............ 10-20 Table 10.4.5 Cumulative Energy Cost Savings, Best Estimate (billion 2011$) ................... 10-21 Table 10.4.6 Alternative Scenario Variables ........................................................................ 10-23 Table 10.4.7 Cumulative Full

- Fuel -Cycle NES, Alternative Scenarios (quads) .................. 10-25 Table 10.4.8 Cumulative NPV for Alternative Scenarios, 3% Discount Rate (billion 2011$) .............................................................................................................. 10-27 Table 10.4.9 Cumulative NPV for Alternative Scenarios, 7% Discount Rate (billion 2011$) .............................................................................................................. 10-2710- ii LIST OF FIGURES

Figure 10.2.1 Site

- to -Power Plant Conversion Factor for Electricity ...................................... 10-8 Figure 10.3.1 Annual Electricity Prices by Sector (2011$) ................................................... 10-15 Figure 10.4.1 NES for GSFL and IRL Combined, All CSL 1 and Max CSL, Best Estimate ............................................................................................................ 10-18 Figure 10.4.2 Full Fuel Cycle NES by Product Class Grouping, All CSL 1, Best Estimate ............................................................................................................ 10-19 Figure 10.4.3 Full Fuel Cycle NES by Product Class Grouping, Max CSL, Best Estimate .. 10-19 Figure 10.4.4 GSFL Net Present Value, All CSL 1, Best Estimate ....................................... 10-21 Figure 10.4.5 GSFL NPV, Max CSL, Best Estimate ............................................................. 10-22 Figure 10.4.6 IRL NPV, All CSL 1, Best Estimate ................................................................ 10-2210-1 CHAPTER 10. NATIONAL IMPACT ANALYS ES

10.1 INTRODUCTION
This chapter describes the method the U.S. Department of Energy ( DOE ) used to esti m ate the national impacts of candidate standards cases (CSCs) f or covered gen era l ser vic e fl uoresce n t la mps (GSFL s) and incandes ce n t re f le c tor l a mps (IRL s ). In the n a tio n al i m pact

an alysis (NIA ) , DOE assesses the cu mulative national energy savings (NES) of products shipped during a 30-year analysis period (2017 – 2046) and the net present value (NPV) of the total consumer economic impacts, by comparing the CSC to a base case, in which standards remain at the current level . As described in chapter 9 of this technical support document (TSD), a CSC is defined by setting the candidate standard level (CSL) for each prod uct class, and the impact on any given product class depends on the levels set for other substitutable products. The CSCs considered in this preliminary analysis were defined in chapter 9 of this TSD. In addition to NES and NPV, this chapter reports DOE’s estimate of the monetary value to the nation of the cumulative energy savings and the total cumulative change in equipment costs resulting for the CSCs.

DOE perfo rm s all NIA calculations u s ing a Microsoft Excel® spreadsheet which are

available on regulations.gov, docket number EERE–2011– BT

– STD

– 0006 at www.regulations.gov/#!docketDetail;D=EERE-2011- BT

- STD -0006

. Details regarding , and instructions for using, the NIA spreadsheet are provided in appendix 10 A.

Table 10.1.1 summarizes the inpu ts to the NIA spreadshee t model. A brief description of the data is given for each input.10-2 Table 10.1.1 Summary of NES and NPV Inputs Input Data D e scription
Sh ipm en ts A nn u al shipments fr om the G SFL an d I RL sh ipm ents m ode l (see cha p ter 9 of this TSD )
St o ck of lamps Modeled from historical data and shipments projections (see chapter 9 of this TSD ) Effecti v e date o f stan d ard 2 017
An alysis per i od For products shipped from 2 017 through 2046 Lamp and ballast characteristics Wattage, first cost, installation cost, disposal cost (see chapter 9 of this TSD )

Lamp Prices Annual price of lamps adjusted for price learning (see chapter 9 of this TSD )
Projected electricity prices From AEO 2012 to 2035 an d extr a polated be yond 2035 (see chapter 9 of this TSD ) Sit e- to

- primary electricity

co nv ersion Ge nera te d by the NEMS version corresponding to the 2 012 AEO (to 2035) and extrapolated b eyond 2 035

R eb ou n d e f fe ct 0 percent of tot al ene rgy s av in gs in the co mm erc i al and residential sec t or in the reference case

D iscou n t r ate Real 3 an d 7 percent
Pres ent ye ar Fu tu re cost s an d sav in g s are discounted to th e year 2013

The following sections describe in detail the methodology and inputs for the NIA. Section 10.2 discusses DOE’s calculation of national energy consumption in the base- case and standar d s case, and t h e resulting N ES between these cases. Section 10.3 discusses the NPV calculation. Section 10.4 presents the NES and NPV r esults for the different CSCs, and under various scenarios.

10.2 NATIONAL ENERGY SAVINGS

This section describes DOE’s calculation of the NES for the two categories of lamps (GSFL and IRL) under the fo ur CSCs considered in this preliminary analysis.

10.2.1 Primary Energy Savings

The annual NES quantifies the difference in energy use between the base case and a candidate standards case in a given year:

NES ( y ) = � AEC base ( y )

− AEC std ( y ) � × RF Eq. 10.1 Where:10-3 NES ( y ) = national energy savings in year y a AEC base ( y ) = base case annual national energy cons umption at the power plant for all product classes combined in year y ( quads), (quads),

AEC std ( y ) = standards case annual national energy cons umption at the power plant for all product classes combined in year y ( quads), and RF = rebound rate factor = 1 - rebound rate (see appendix 10C).

Positive values of NES correspond to a net energy savings following standards implementation, in other words , annual energy consumption ( AEC ) in the standards case is less than AEC in the base case b

. As discussed in chapter 9 of this TSD, for the purpose of computing the N ES , it is not necessary to compute the total installed stock

, S ( y ) , of lamps and lamp- and

- ballast systems in the United States. The only portion of the stock that is relevant to this calculation is the operating stock shipped during the analysis period (OSSDAP) , denoted S ′ ( y )

, wit h the assumption that S ′ ( y rule − 1 ) = 0 , where y rule = 2017, the compliance year of the new rule, is the first year of the analysis period. Eq. 10 .1 can therefore be expressed as follows:

NES ( y ) = ( AE C ′ base ( y )

− AE C ′ std ( y ) ) × RF Eq. 10.2 Where:

AE C ′ base ( y ) = base case annual national energy cons umption of the OSSDAP at the power plant for all product classes combined in year y ( quads), and AE C ′ std ( y ) = standards case annual national energy cons umption of the OSSDAP at the power plant for all product classes combined in year y ( quads).

The c um ulative national energy sa vin gs is th e s u m of each NES(y) for all operating stock shipped during the 30-year analysis period (2017 – 2046) . The analysis tracks the energy use of the stock shipped during the analysis period until the last unit is assumed to be retired, in 2080. The cumulative NES is co mputed as follows:

NES cum = � NES ( y )

y Eq. 10.3 Where:

NES cum = cumulative national energy savings (quads)

.

a Note that the time variable y is a discrete variable representing any year between 2017

- 2080 and is not continuous. For quantities that depend on y , t he notation f ( y ) is used , instead of f y , to avoid confusion with other subscripts.
b Following the example of the 2011 fluorescent lamp ballast f inal r ule and for reasons given therein, DOE is assuming that heating, ventilati ng , and air conditioning ( HVAC ) interactions on NES are negligible

.10-4 DOE computes the AEC for IRLs by summing over the OSSDAP of each lamp option, as reflected in the following equation:

AE C IRL ′ ( y ) = �� S

l

, IRL ′ ( y ) × UE C l

, IRL ( y )

l �

× SP ( y )

Eq. 10.4 Where:

S l

, IRL

′ ( y ) = the OSSDAP of IRL option l in year y (number of units), UE C l

, IRL ( y ) = the annual unit energy consumption of IRL option l in year y , as described in section 10.2.3.2 (kWh), and SP ( y ) = time variable site

- to

- power

- plant energy con version factor that converts site electricity use (k Wh) to primary energy consumed at the power plant (quads /k W h).

As discussed in chapter 9 of this TSD, DOE computes shipments and stock of GSFLs disaggregated according to a set of national- average ballast types, to which the lamps are coupled. Each GSFL product class grouping in the model is com po se d of one or several ballast types. DOE calculated the AEC for GSFL by summing over all of the ballast types:

AE C GSFL ′ ( y ) = � AE C j

, GSFL ′ ( y )

j Eq. 10.5 Where:

AE C j

, GSFL ′ ( y ) = the annual energy consumption by the OSSDAP of GSFLs that are installed on ballasts of type j in year y (quads).

The AEC of GSFL s installed on each ballast type is computed in turn by summing over the energy consumption of the various lamp options that are installed on that ballast, as shown by the following equation:

AE C ′ j

, GSFL ( y ) = �� S

′ j ( y ) × φ l

, j ( y ) × UEC l

, j

, GSFL ( y )

l �
× SP ( y )

Eq. 10.6 Where:

S ′ j ( y ) = the OSSDAP of GSFL installed on ballasts of type j , in year y, calculated by the shipments model (number of units),10-5 φ l

, j ( y ) = the fraction of the OSSDAP of GSFL installed on ballast type j that is represente d by lamp option, l

, c UEC l

, j

, GSFL ( y ) = average unit energy consu mption of lamp option l installed on ballast type j in year y, as described in section calculated by the shipments model,

10.2.3.2 (kWh), and SP ( y ) = time variable site

- to

- power

- plant energy conversion factor that converts site electricity use (kWh) to primary energy consumed at the power plant (quads /kW h).

10.2.2 Full

- Fuel -Cycle Energy Savings
DOE has historically presented the NES computed based on the primary energy savings at the power plant, as described in the previous section. Per DOE’s 2011 Statement of Policy for Adopting Full Fuel Cycle Analyses , DOE now uses full- fuel

- cycle (FFC) measures of energy use and emissions in its energy conservation standards analyses. 1 In addition to the primary energy used at the power plant to supply electricity to the site of use and account for transmission and distribution losses, t he FFC analysis also accounts for energy consumed up

- st r eam of the power plant in extracting, processing, and transporting or distributing the primary fuels to the power plant, as described in appendix 10 B.

As shown in Eq. 10.7 , the FFC national energy savings ( NES FFC ) are obtained by multiplying the primary energy savings ( Eq. 10.2 ) by the FFC multiplier computed for the same
year , μ (y) :

NES FFC ( y ) = ( AE C ′ base ( y )

− AE C ′ std ( y ) ) × RF × μ ( y ) Eq. 10.7 Where:

μ ( y ) = the FFC multiplier and all other variables were defined in Eq. 10.1 and Eq. 10.2

.

T he cumulative FFC energy savings are calculated by summing the annual savings from 2017 through 2080:

NES′ FFC

, cum = � NES′
FFC ( y ) Eq. 10.8

c The lamp options include all lamp types for all CSLs (see chapter 9 of this TSD).10-6 10.2.3 National Energy Savings Inputs
As described in the preceding sections, the following inputs are used for calculating the national energy savings:

**•** shipments and operating stock shipped during the analysis period,

**•** average unit energy consumption ( UEC ),

**•** site -to-power-plant conversion fact or ( SP )

,

**•** primary energy to full fuel cycle multipliers ( μ ), and

**•** rebound rate factor ( RF).

These inputs are further discussed in the following sections.

10.2.3.1 Shipments and Operating Stock Shipped during the Analysis Period The shipments model, described in chapter 9 of this TSD , calculated the shipments of the representa tive product class groupings for each year of the 30-year shipments analysis (2017 through 2046). Based on that analysis, the model developed a description of the OSSDAP and of the surviving stock shipped during the analysis period through to the end of its lifetime.

10.2.3.2 Average Unit Energy Consumption

DOE calculates the average annual UEC for each GSFL and IRL option by multiplying the average lamp power consumption by the average annual hours o f use for that lamp in the
sector under consider ation

. For IRL s , this is simply the rated lamp wattage multiplied by the annual hours of use:

UE C l

, IRL = W l

, IRL × u � IRL 1000 Eq. 10.9 Where:

UE C l

, IRL = the annual UEC of IRL option l (kWh), W

l

, IRL = the rated wattage of IRL option l , corrected for the impact of dimmers, as discussed in chapter 9 of this TSD (W)

, and u� IRL = the average annual hours of use for an IRL in the sector bei ng considered (hours), as presented in c hapter 6 of this TSD

. For GSFL, the UEC depends also on the average ballast factor for lamps in the product class grouping being considered:

UE C l

, j

, GSFL = W l

, GSFL × BF j × u � GSFL 1000 Eq. 10.10 Where:10-7 UE C l

, j

, GSFL = the annual UEC of GSFL option l , when it is coupled to a ballast of type j (kWh)

, W

l

, GSFL = the rated wattage of GSFL option l (W)

, BF j = the national average ballast factor of ballasts of type j , as presented in chapter 9 of this TSD , and u� GSFL = the average annual hours of use for a GSFL in the sector bei ng considered (hours), as presented in c hapter 6 of this TSD.

To compute the average hours of use for GSFL and IRL, DOE computed the averages of the sector

- specific hours -of-use distributions presented in chapter 6 of this TSD . When analyzing GSFLs in the combined commercial and industrial sectors, DOE weighted these sectors’ distributions using weighting factors computed as described in chapter 9 of this TSD

.

DOE assumed that lighting controls are installed on an increasing fraction of lamps in the commercial and industrial sectors as a result of building codes (se e appendix 9A of this TSD)

, and assumed a 75 percent compliance rate . To account for the impact of lighting controls

on the NES, DOE reduced the UEC by a fixed 30 percent in the stock of lighting in which switching

- based controls were assumed to operate, where the savings estimate was based on a
meta

- analysis of field measurements of energy savings from commercial lighting controls by Williams et al. (2012). 2 DOE’s projection of the penetration of lighting controls was described in appendix 9 A.

DOE inclu ded two projections of controls adoption. In the reference case , which is DOE’s best estimate, controls penetration grows year- by

- year in the commercial and industrial sector, as driven by building codes and shown in appendix 9A. In the second case, contro ls penetration wa s assumed to remain fixed at the same level as the first year in the analysis period. The latter was included to determine the impact of controls on the estimated energy savings from the rulemaking; DOE does not consider the fixed case sce nario realistic given the strong driving factors for controls adoption.

For each lamp option (whether IRL or GSFL and regardless of ballast type), the lighting controls impact wa s computed in the following way:

UEC l ( y ) = UEC l × �1 − LC adopt ( y ) + LC adopt ( y ) × LC effect � Eq. 10.11 W here:

UEC l ( y ) = weighted average annual electricity consumption (kWh) of the lamp option, UEC l = annual unit electricity consumption (kWh) of lamp option l, computed using the previous equations, LC adopt ( y ) = the lumen capacity fraction of lighting estimated to be operating under switch

- based lighting controls in year y, and10-8 LC effect = a parameter describing the effect of switch

- based lighting controls on energy consumption, taken to be 0.7.

10.2.3.3 Site

- to -Power Plant Conversion Factor To estimate the energy used at the po wer plant in order to supply the electricity used onsite by the two categories of lamps, DOE multiplie d the site electricity, UEC l ( y )

, by a site

- to

power-plant conversion factor, d which accounts for average losses associated with the generation, transmission, and distribution of electricity from the fleet of U.S. power plants to the point of use. DOE used annual site- to -source conversion factors based on the version of the National Energy Modeling System (NEMS) that corresponds to the Energy Information Administration ’s Annual Energy Outlook 2012 ( AEO 2012 ). 3

Figure 10.2.1 The factor changes over time in response to projected changes in generation sources (the types of power plants projected to provide electricity to the country). shows how the site

- to -power plant conversion factor is ex pected to change during the NES and NPV analysis period.

Figure 10.2.1 Site

- to

- Power Plant Conversion Factor for Electricity

10.2.3.4 Primary Energy to Full- Fuel

- Cycle Multipliers For this preliminary analysis, DOE calculated FFC energy savings using a methodology described in appendix 10B. As discussed previously , the FFC energy savings are obtained by

d In previous rulemakings the site

- to

- power

- plant conversion factor has been referred to as the site

- to

- source conversion factor. The terminology is modified here to clarify that the analysis only accounts for the energy used at the power plants, but not energy used upstream of the power plants to provide that service. The latter is incorporated in the full

- fuel

- cycle analysis.10-9 multiplying the primary energy savings at the power plant by the FFC multiplier. The estimated FFC multiplier ( μ ) is essentially constant

, rang ing between 1.040 and 1.045 from 2017 to 2080.

10.2.3.5 Rebound Rate Factor

DOE generally accounts for the direct rebound effect in its estimates of the NES. As discussed in chapter 2 of this TSD , DOE received public comment regard ing the rebound rates proposed in the framework and performed additional analyses to reevaluate the proposed rates based on the most recent available data. Presented in a ppendix 10 C, that analysis reveals no current evidence for lighting rebound in the Uni ted States . Therefore, for its best estimate , DOE assumes no lighting rebound. However, DOE conducted sensitivity analyses for two additional scenarios to determine the potential impact of alternative assumptions on the rulemaking. In the first alternative scenario, DOE conducted the analysis using the assumptions for rebound rates proposed in the framework document. In its second alternative scenario, DOE assumed the values used for lighting rebound in NEMS. As described in appendix 10C , the latter were based on an estimate of the average rebound rate for a suite of appliances, and the lighting data contained therein were from the early 1990s. The values used in the different best estimate and alternative scenarios are summarized in Table 10.2.1

.

Table 10.2.1 Rebound Rate Scenarios for GSFL and IRL Rebound Scenario Commercial Rebound Rate Residential Rebound Rate Best Estimate 0% 0% Framework assumption 1% 8.5% NEMS 15% 15%

10.3 NATIONAL NET PRESENT VALUE

10.3.1 Definition

The NPV is the difference between the present value of savings (PVS) in operating cost resulting from the use of more efficient appliances under the standard and the present value of increased total installed costs (PVC) of those appliances. The NPV is described by the following equation:

NPV = PVS

− PVC Eq. 10.12 Where:

PVS = present value of savings in operating cost (including costs for energy, repair, and maintenance in 2011$ ); and PVC = present value of increase in total installed cost (including costs for equipment and installat ion in 2011$ ).10-10 DOE determined the PVS and PVC according to the following expressions:

PVS = � OCS ( y ) × DF ( y )

y Eq. 10.13

PVC = � ECI ( y ) × DF ( y )

y Eq. 10.14

Where:

OCS ( y ) = total annual operating cost savings realized in the OSSDAP in year y, relative to the base case (2011$), ECI ( y ) = total annual equipment cost increase for shipments in year y , relative to the base

case (2011$), and DF ( y ) = discount factor in each year (defined in section 10.3.2.3 ).

DOE calculated PVC from 2017 to 2046 (the duration of the shipments analysis period), and PVS from 2017 to 2080 (to account for the full lifetime off all stock shipped during the analysis period). T he co nt rib u tions to PVC and PV S for each year were d iscounted to 2013. The following sections describe how DOE derives the variables in Eq. 10.13 and Eq. 10.14

10.3.2 N et Present Value Inputs
The inputs to DOE’s calculation of the NPV of costs and savings for the n ation are:

**•** total annual installed cost ( TIC ) in the base case and the standards cases,

**•** total annual operating cost ( TOC ) for the OSSDAP in the base case and the standards

cases, and

**•** discount factor (DF).

The computation of these inputs from the outputs of upstream analyses is detailed in the following sections.

10.3.2.1 Total Annual Installed Cost Increases

DOE calculated the total annual equipment cost increase of using more efficient lamps in the standards cases relative to the base case as the difference between the TIC in the standards case and the base case:

ECI ( y ) = TI C std ( y )

− TI C base ( y ) Eq. 10.15 W here:10-11 TI C std ( y ) = the total installed cost of equipment shipped in year y in the standards case (2011$), and TI C base ( y ) = the total installed cost of equipment shipped in year y in the base case (2011$).

Due to the higher cost of more efficacious products in the standards case versus the base

case, cost increases appear as negative values in the NPV.

For IRLs, the per- unit installed cost i n clu d es the lamp first cost and the lamp inst a ll ation cost. Thus, t he TIC is given by the followin g equation:

TI C IRL ( y ) = � s
IRL

, l ( y ) × �p IRL

, l ( y ) + IC IRL �

l Eq. 10.16

Where:

s IRL
, l ( y ) = total shipments of IRL option l in year y (number of units)

, p IRL
, l ( y ) = purchase price of IRL option l in year y , including corrections for learning (2011$/unit), and IC IRL = installation cost of IRLs (2011$/unit).

The comp utation of the variables in Eq. 10.16 is described in chapter 9 of this TSD

.

For GSFL s , the t o tal annual installed cost is described by summing over the ballast types:

TI C GSFL ( y ) = � TI C GSFL

, j ( y )

j Eq. 10.17

Where:

TI C GSFL
, j ( y ) = total installed cost for l lamps and ballasts shipped for installation in lamp

and

- ballast systems of ballast type j , in year y (2011$).

Eq. 10.17 is used to compute either the TIC for all GSFLs, by summing over all ballast types, or to compute the TIC for GSFLs in a particular product class grouping, by summing only over the ballast ty pes within that grouping.

In the case of GSFL s, for lamps installed on new ballasts, DOE accounts for the first cost of the lamp, the first cost of the ballast, and the ballast installation cost. For ballast replacements,10-12 DOE also accounts for the disposal cost of the retired lamp e . For lamp replacements on existing ballasts, DOE accounts for the disposal cost of the retired lamp and the first cost of the new lamp. For each product class grouping j , the to tal annual installed cost is descri bed by the following equation:

TI C j ( y ) = s B

, j ( y ) × �p B

, j ( y ) + IC B

, j � +

s GSFL

, j ( y ) × �� [ MS l

, j ( y ) ×

l p GSFL

, l

, j ( y ) ] + IC GSFL

, j � + DC GSFL

, j

Eq. 10.18 Where:

s B
, j ( y ) = total shipments of ballasts of type j in year y (number of units),
p B
, j ( y ) = purchase price of ballasts of type j in year y, including corrections for learning (2011$/unit),

IC B

, j ( y ) = installation cost of ballast type j (2011$/unit),

s GSFL
, j ( y ) = shipments of GSFLs coupled to ballasts of type j in year y (number of units), MS l

, j ( y ) = market share of lamp option l among new lamps coupled to ballasts of type j in year y , p GSFL
, l

, j ( y ) = purchase price of lamp option l in year y, including co rrections for learning and any rare earth oxide price impacts (2011$/unit), IC GSFL
, j = installation cost of GSFLs coupled to ballasts of type j (2011$/unit), and DC GSFL
, j = disposal cost of GSFLs coupled to ballasts of type j (2011$/unit).

The calculation of the variables in Eq. 10.18 is described in chapter 9 of this TSD.

The annual disposal cost in product class j, DC GSFL
, j ( y )

, is calculated using the following equation:

DC GSFL

, j ( y ) = ADC GSFL

, j × � [ s GSFL

, j ( v ) y−1

v=y 0 × P LBR

, j ( y − v ) ]

Eq. 10.19

Where:

AD C GSFL
, j = average disposal cost for retired GSFLs installed on ball asts of type j , which is taken to be 30 percent of the individual lamp disposal cost, since DOE assumes

e As discussed in chapt er 9, DOE assumes that old lamps are disposed of upon ballast replacements so that all new ballasts are coupled with new lamps when they are installed.10-13 that 30 percent of consumers pay this cost, as discussed in chapter 8 of this TSD (2011$/unit),

s GSFL
, j ( v ) = shipments of GSFLs installed on ballasts of type j

, in vintage year v (number of units), and P

LBR
, j ( y − v ) = the probability that a lamp or its ballast is retired in year y − v of the lamp’s life, for lamp

- and

- ballast systems of ballast type j, as prese nted in chapter 9 of this TSD.

To establish the per -unit installed cost, DOE based installation costs on nationally representative values f o r each la mp design or each la mp- and

- ballast system. See chapter 8 of this TSD for further description s of installation costs , and chapter 7 of this TSD and appendix 7A of this TSD for lamp and ballast prices.

10.3.2.2 Total Annual Operating Cost Savings

DOE expresses savings in operating costs as cost reductions associated with the lower energy consumption of products shipped in the standards case compared to the base case. DOE calculated the total annual operating cost savings as the difference between the TOC in the standards case and the base case. As for the computation of the NES, the TOC need not be computed for the total stock S , but only for the OSSDAP, S′ :

OCS ( y ) = TO C ′ base ( y )

− TO C ′ std ( y ) Eq. 10.20

Where:

OCS ( y ) = the total operating cost saving of OSSDAP in year y (2011$), TO C base ′ ( y ) = the total operating cost of the OSSDAP in year y in the base case (2011$), and TO C std ′ ( y ) = the total operating cost of the OSSDAP in year y in the standards case (2011$).

The only component of annual operating cost for lam ps is th e c o st of electricity consumption. As described in the life

- cycle cost (LCC) and payback period (PBP) analysis (chapter 8 of this TSD) , DOE calculates total annual operating costs based on national average elec t ricity prices. DOE used the reference

- case, sector

- specific electricity price projections from AEO2012 to establish all electricity prices

. As AEO2012 only projects prices through 2035,

e lectricity prices in later years were extrapolated based on the 2025 th rough 2035 sector- specific trend s, up through 2060, after which prices were assumed to remain constant. As discussed in chapter 9 of this TSD , w hen jointly analyzing lamps in the commercial and industrial sectors

, DOE used a weighted average of the comme rcial and industrial electricity price projections, based on the fraction of the total stock that is installed in the industrial sector for each ballast type

.10-14 DOE calculated annual TOC for IRL s by summing over the operating costs of all lamp options in the OSSDAP, according to the following expression:

TO C′ IRL ( y ) = p E ( y ) × � [ S ′ l

, IRL ( y ) × UEC l

, IRL ( y )]

l Eq. 10.21 Where:

p E ( y ) = the price of electricity , in year y , as forecasted in the AEO 2012 reference scenario (2011$/kWh),
S l

, IRL

′ ( y ) = the OSSDAP of IRL type l in year y (number of units)

, and
UE C l

, IRL ( y ) = the average unit energy consumption of IRL type l in year y, as computed using Eq. 10. 11 (kWh/unit).

For IRL s , DOE uses the forecast of national -av erage com mer cial and re si dentia l electricity p r ic e s f or its an aly sis in the commercial and resi d ential s ec t ors, respectively.

To compute the annual TOC for GSFLs , DOE sums the operating costs of lamps installed on all ballast types from the shipments analysis:

TO C′ GSFL ( y ) = � TO C j

, GSFL ( y )

j Eq. 10.22

Where:

TO C j

, GSFL ( y ) = the annual total operating costs of lamps installed on ballasts of type j in
year y (2011$)

. The TOC for lamps installed on a particular ballast type is given by a sum over the OSSDAP fractions of the lamp options that can be installed on that ballast:

TO C′ j

, GSFL ( y ) = S j

, GSFL ′ ( y ) × p E ( y ) × � [ φ l

, j ( y ) × UE C l

, j

, GSFL ( y ) ]

l Eq. 10.23 Where:

S

j

, GSFL ′ ( y ) = the OSSDAP of GSFL s installed on ballasts of type j in year y (number of units)

, p E ( y ) = the price of electricity , in year y , as forecasted in the AEO 2012 reference scenario (2011$/kWh),10-15 φ l

, j ( y ) = the fraction of the OSSDAP of lamps installed on ballasts of type j that are lamp option l, and UE C l

, j

, GSFL ( y ) = the annual unit energy consumption of lamp option l installed on ballast type j , as computed using Eq. 10.11 (kWh/unit).

For 4 -foot medium bipin (MBP) lamps installed on residential ballasts , DOE used the projection of national average residential electricity prices. For all other GSFLs in the stock, DOE used a weighted average of the electricity price projections in the commercial and industrial sectors , as descri bed in chapter 9 of this TSD

. To understand the importance of uncertainty in these projections, DOE performed sensitivity analys es using the high- and low-economic growth scenarios from AEO2012 to establish electricity prices. Figure 10.3.1 shows annual electricity price projections used as inputs for the high

- , reference -, and low-economic growth scenarios, for all sectors. Note that there is not a consistent relationship over time between the economic growth scenario and its impact on electricity prices. In the early year s of the analysis period, the low-economic growth scenario in the residential sector results in high er electricity prices than the high growth scenario. The opposite is true in later years.

Figure 10.3.1 Annual Electricity Prices by Sector ( 2011$)10-16 As discussed in section 10.2.3.5 , DOE has included in this preliminary analysis scenarios that include rebound effects to adjust its estimates of NES. In principle, the rebound effect also affects the energy costs to consume rs in the standards case. However, the take -back in energy consumption associated with the rebound effect provides consumers with increased value ( e.g., improved lighting quality ). As describe d in the 2012 residential furnace fan NIA 4

10.3.2.3 Discount Factor , DOE believes that, i f it were able to monetize the increased value to consumers of the rebound effect, this value would be similar in value to the foregone energy savings. Therefore, the economic impacts on consumers with or without the rebound effect are the same, so DOE does not adjust operating cost savings in the NIA, based on rebound effects.

DOE multiplied monetary values in future years by a discount factor to determine the present value. The DF is described by the equation:

DF = 1 (1 + r ) ( y−y p ) Eq. 10.24 Where:

r = discount rate,
y = year of the monetary value, and
y P = year for which the present value is being determined.

DOE estimated NPV using both a 3- percent and a 7 -percent real discount rate, in accordance with the Office of Management and Budget’s guidance to Federal agencies on the development of regulatory analysis, particularly section E therein: Identifying and Measuring Benefits and Costs . DOE defined the present year as 2013.

10.4 RESULTS

Th is section summarizes the NES and NPV modeling results for the four candidate standards cases and the results of the alternative analyses used to determine uncertainties and the impacts of key variables.

10.4.1 National Energy Savings Results

Table 10.4.2 presents DOE’s best estimates of the cumulative NES relative to the base

case for GSFLs and IRLs, for the four CSCs . Results are shown for both full

- fuel

- cycle NES and prima ry (at the power plant) NES

.10-17 Table 10.4.1 Cum ulative N ES for GSFL s and IRL s, for All CSCs , Best Estimate National Energy Savings* (quads)

Analysis Type Scenario All CSL1 All CSL1 Except T5=Baseline Max CSL Max CSL Except T5=Baseline

Standard Best Estimate GSFL 0.94 ( 0.9 0) 0.61 (0.59 ) 4. 52 (4.34 ) 4. 21 (4.05 )

IRL 0.14 (0.13 ) 0.14 (0.13 ) 0.14 (0.13 ) 0.14 (0.13 )

* Results shown are for full

- fuel

- cycle NES. Results in parenthes e s are for primary NES

.
As discussed in chapter 9 of this TSD, the shipments a nalysis implements a consumer choice model to project shipments. Therefore, a fraction of the NES ( and NPV ) of each CSC derives from consumer product switching in response to the new standard. GSFL s offer a significantly larger potential for energy savings than IRL s for both All CSL 1 and Max CSL . This is expected as the base case electricity consumption for GSFL s is much greater than t he IRL electricity consumption and, therefore , has a higher poten tial for energy savings. Note that

, b ecause IRL s have only one CSL, and no product switching occurs, the NES for IRL s is the same for all considered CSCs.

The CSCs in which T5 efficacy standards are held at their baseline levels , while T8 standards are u pdated to All CSL 1 or to Max CSL

, lead to a reduced NES relative to the CSCs in which updated standards are applied to both T8s and T5s. In the All CSL 1 standards case, the NES reduction is substantial, at approximately 30 percent. The reduction is more modest in the Max CSL standards case, at the level of a few percent. Because standards that exclude T5s do not save additional energy, DOE did not pursue th ese options further in the NES of this preliminary analysis.

Figure 10.4.1 shows the combined (GSFL and IRL) best estimate of annual site NES for the All CSL 1 CSC and Max CSL CSC

. The NES for b oth CSCs show an increase during the first years of the analysis period but are later reduced as incursion of lighting using light

- emitting diodes (LEDs) into the GSFL and IRL markets reduces energy use and , thus, energy savings. The modeling of the incursion of LEDs into the GSFL and IRL market is described in chapter 9 of this TSD. Energy savings also go down after 2046 as the stock of lamps installed during the 30- year shipments analysis period diminishes due to lamp retirements.10-18 Figure 10.4.1 N ES for GSFL and IRL Combined , All CSL 1 and Max CSL, Best Estimate

Figure 10.4.2 and Figure 10.4.3 show the FFC NES by product class grouping, for both GSFL and IRL, for All CSI 1 an d Max CSL

, respectively. The NES derived from 4 -foo t MBP lamps far outweighs savings from any other product class grouping, as these products have the largest market share and base energy consumption. Negative energy savings are seen in a few product class groupings ( e.g., T5 standard output ( SO )), because the standard drives increased shipments of such lamps in the standards case as consumers switch away from less efficacious products ( e.g., 4-foot MBP T8s). This switching yields an overall energy savings, even though the savings for individual product class groupings may be negative.10-19 Figure 10.4.2 Full Fuel Cycle NES by Product Class Grouping , All CSL 1, Best Estimate

Figure 10.4.3 Full Fuel Cycle NES by Product Class Grouping, Max CSL, Best Estimate10-20 10.4.2 Net Present Value Results

Table 10.4.3 shows the cumulative NPV for GSFLs and IRL s for the four CSCs

, calculated assuming both a 3 - percent and a 7 - percent discount rate. T he CSCs that exclude T5s lead to a reduced NPV, compared to their corresponding All CSL 1 and Max CSL standard levels

, because of the reduced NES described in the previous section. Therefore, DOE did not pursue these options further in this preliminary analysis.

Table 10.4.2 Cumulative Net Present Value for GSFL and IRL (billion 2011$)

Table 10.4.4 and Table 10.4.5 show estimated cumulative equipment cost increase s and the cumulative energy cost sav ings, respectively, for GSFLs and IRLs shipped during the analysis period , for the two remaining CSCs.

Table 10.4.3 Cumulative Equipment Cost Increase , Best Estimate (billion 2011$)
All CSL 1 Max CSL 3% Discount Rate 7% Discount Rate 3% Discount Rate 7% Discount Rate
GSFL Equipment Cost Increase 3. 1 1.9 2.0 1.2 IRL Equipment Cost Increase 0.51 0.52 0.51 0.52 Total Equipment Cost Increase 3.6 2.4 2.5 1.7 3% Discount Rate

Analysis

Type ScenarioProduct ClassGroupingAll CSL 1GSFLAll CSL1 ExceptT5=BaselineMax CSLMax CSLExceptT5=Baseline

Standard Best Estimate GSFL 2.0 1. 3 23 22

IRL 0.0 40 0.0 40 0.0 40 0.0 40

Total * 2.0 1.3 23 22

7% Discount Rate

Standard Best Estimate GSFL 0.83 0.5 8 13 13

IRL

- 0. 17

- 0. 17

- 0. 17 0.17

Total * 0.65 0.40 13 12

* Totals may not add due to rounding10-21 Table 10.4.4 Cumulative Energy Cost Savings, Best Estimate (billion 2011$)
All CSL 1 Max CSL 3% Discount Rate 7% Discount Rate 3% Discount Rate 7% Discount Rate
GSFL Energy Cost Savings 5 .0 2.7 2 5 14 IRL Energy Cost Savings 0.55 0. 34 0.55 0. 34 Total Energy Cost Savings * 5 .5 3.0 25 1 4 *Totals may not add due to rounding

Figure 10.4.4 and Figure 10.4.5 show the estimated annual NPV at All CSL 1 and Max CSL for GSFL s, respectively

. The solid lines represent NPV assuming a 3- percent discount rate, while the dashed lines represent NPV assuming a 7- percent discount rate.

Solid lines : 3% discount rate ; dashed lines : 7% discount rate Figure 10.4.4 GSFL N et P resent Value, All CSL 1, Best Estimate10-22 Solid lines: 3% discount rate; dashed lines: 7% discount rate Figure 10.4.5 GSFL NPV, Max CSL, Best Estimate

Figure 10.4.6 shows the estimated annual NPV for IRLs at All CSL 1 . The reduction in equipment cost savings and NPV in the beginning of the analysis period is due to p urchases of high -priced, long-lived lamps for CSL 1, relative to the base- case.

Solid lines: 3% discount rate; dashed lines: 7% discount rate Figure 10.4.6 IRL NPV, All CSL 1, Best Estimate10-23 10.4.3 Alternative An alyses Results

10.4.3.1 Overview To gauge the importance of various assumptions and uncertainties in the NIA, DOE carried out the NIA for several alternative scenarios and compared the NES and NPV results to the best

- estimate scenario. Table 10.4.5 summarizes the model inputs used to: a) conduct uncertainty analyses based on rare earth oxide (REO) prices and economic growth scenarios, b) determine the impact of different rebound rate assumptions, c) determine the impact of growing LEDs and controls penetration into the GSFL and IRL lighting markets, and d) test the effect of manufacturers meeting an IRL standard at CSL 1 using short- li fe lamps.

These alternative analyses, listed in Table 10.4.6

, are discussed below. The scenario variables are described in chapter 9 of this TSD

.

Table 10.4.5 Alternative Scenario Variables

Scenario Variables

Analysis Type ScenarioAEO2012EconomicGrowthReboundRateRareEarthPriceLEDControlsAdoptionShort IRLLife

(a) Uncertainty Analyses REO High Ref Ref * High Ref Ref No

REO Low Ref Ref Low Ref Ref No High Economic Growth High Ref Ref Ref Ref No

Low Economic Growth Low Ref Ref Ref Ref No

(b) Rebound

Scenarios Framework Rebound Ref Framework ** Ref Ref Ref No

NEMS Rebound Ref NEMS † Ref Ref Ref No

(c) Impact Determination Fixed Controls Ref Ref Ref Ref Fixed No

No LED Ref Ref Ref Fixed Ref No

(d) Alternative

Technology

Scenario IRL Short Life Ref Ref Ref Ref Ref Yes

* Reference rebound rates are as follows: Commercial 0% and Residential 0%.

** Framework rebound rates are as follows: Commercial 1% and Residential 8.5% † NEMS rebound rates are as follows: Commercial 15%, Residential 15%.

Uncertainty Analyses

. As discussed in chapter 9 of this TSD , DOE developed alternative scenarios for high and low REO prices reflecting the highest price observed during the 201110-24 spike in REO prices and the much lower prices that had been common prior to that spike. Uncertainty in the future price of REOs leads directly to uncertainty in the NPV of an updated standard, because these prices impact the first cost of GSFLs. Such price uncertainty can also lead indirectly to uncertainty in the NES and NPV, because the different first costs, and operation and maintenanc e ( O&M ) costs of lamps and lamp- and

- ballast systems will lead to different projected market shares for lamps and lamp- and

- ballast systems. Note that REO price uncertainty is not applicable to IRLs, because IRLs do not contain REOs.

Economic growth uncer tainty , reflected by uncertainty in future electricity prices

, leads
to uncertainty in the NPV of an updated standard, as discussed in section 10.3.2.2

.

Rebound S cenarios

. The rebound rate scenarios are discussed in section 10.2.3.5 and appendix 10 C. As explained earlier in this chapter, rebound rates are assumed to affect NES, but not operating cost savings, therefore the NPV is not sensitive to rebound rate.

Impact Determination

. Regarding the penetration of LED lighting products and lighting controls into the GSFL and IRL lighting markets, as discussed in chapter 9 of this TSD, DOE made two key assumptions about changes in the market and usage patterns for lamps ove r the analysis period

. Solid

- state lighting products ( such as LEDs) were assumed to capture an increasing fraction of the current market for GSFL and IRL products, rising to roughly 70 percent of the market by the end of the analysis period. Similarly, an increasing fraction of lamps were assumed to be subject to automatic lighting controls in the commercial and industrial sectors, owing to building codes requiring such controls. Both of these assumptions will reduce the NES and NPV outputs from the NIA because they reduce the number of covered lamps and their energy consumption, respectively. DOE determined the impact of these two assumptions by running two shipments and NIA scenarios in which the LED market share and prevalence of lighting controls were ea ch held fixed in turn at their present-day values.

Alternative Technology Scenario

. DOE investigated an alternative technology scenario for IRLs meeting CSL 1 . This scenario , discussed in chapter 9 of this TSD

, represents a situation in which, rather than eliminating baseline technologies in favor of more efficacious ones, lamp manufacturers modify baseline IRL s to be more efficacious in a manner that reduces lamp lifetimes and increases lumen output.

10.4.3.2 Alternative Scenario N ational Energy Savings Results

Table 10.4.6 presents the cumulative full

- fuel

- cycle NES estimate s for the alternative analyses that affec t NES . In each CSC , the scenario result for the alternative analys e s sh ould be compared to the best

- estimate CSC to determine the impact. The main results are summarized below:

**•** The uncertainty introduced by volatile REO prices is small given the assumed p rice bounds. F ractional deviations from the reference

- scenario NES were at or below 5 percent in all CSCs

.10-25 **•** The impact on the NES of the different rebound assumptions is straightforward: there is a fractional reduction in energy savings equal to the rebound rate in each sector. As GSFLs are used mostly in the c ommercial and industrial sector and IRLs are used mo stly in the

r esidential sector, 5 the overall impact of the framework rebound assumptions is greater for IRL s than for GSFLs; GSFLs see a redu ction in NES of approximately 1 percent, while the reduction in NES for IRLs is closer to the residential rate of 8 .5 percent . In the case of NEMS rebound assumptions, the NES reduction is 15 percent for both products.

**•** The impact of growth in the LED market was substantial by all measures. For all CSCs, LED incursion into the market roughly halved the potential NES of an updated GSFL standard and reduced it by approximately 80 percent for IRL s.

**•** The impact of lighting controls was generally more modest. Growth of lighting controls reduced the potential NES for GSFL standards by approximately 14 percent in all CSCs

. The impact of controls on the NES for IRL s was negligible, because most use of IRLs occurs in the residential sector , where DOE assumed the use of controls to be constant over the analysis period.

**•** Finally, t he alternative IRL lifetime s cenario reduces th e calculated NES at CSL 1 for IRLs by more than 50 percent.

Table 10.4.6 Cu mulative Full

- Fuel

- Cycle N ES, Alternative Scenarios (quads) National Energy Savings

Analysis Type Scenario All CSL 1 Max CSLIRLGSFLTotalRulemakingIRLGSFLTotalRulemaking

Standard Best Estimate 0.1 38 0.938 1.0 8 0.138 4.5 2 4.6 5

Uncertainty Analyses REO High 0.138 0.925 1.06 0.138 4.30 4.44
REO Low 0.138 0.941 1.0 8 0.138 4.5 9 4.7 3

Rebound Scenarios Framework Rebound Rate 0.127 0.928 1.06 0.127 4.4 7 4.59

NEMS Rebound 0.118 0.797 0.915 0.118 3.83 3.9 6 Impact Determination Fixed Controls 0.138 1.09 1.2 3 0.138 5.2 8 5.4 2
No LED 0.689 1.79 2.48 0.689 7.78 8.47

Alternative Technology Scenario IRL Short Life 0.054 3 0.938 0.992 0.0543 4.5 2 4.5 710-26 10.4.3.3 Alternative Scenario Net Present Value Results This section presents the alternative analyses that affect the NPV. Table 10.4.8 and Table 10.4.9 document the estimated cumulative NPV for the alternative scenarios, assuming a 3- an d 7- percent discount rate, respectively

. The main results are summarized below.

**•** Similar to the NES alternative scenario results, REO prices hav e an impact of less than 2 percent on the NPV for all CSCs.

**•** Uncertainties in electricity prices resulting from differences in AEO economic growth projections have a small effect on the NPV of a GSFL energy conservation standard : the high -economic growth scenario increases NPV and the low-economic growth scenario

re duces NPV by less than 10 percent in any of the considered CSCs . The effect of economic growth uncertainty on the NPV of an IRL standard is similar, at 11 percent or less. f

**•** Reductions in NPV from LED incursion were significant for GSFLs , at roughly 35 to 50 and percent when assuming a 3-percent discount rate, and roughly 30 to 40 percent when assuming a 7- percent discount rate. For IRL s, the impact of LED incursion on NPV was even larger: the NPV of an updated standard was significantly negative in the absence of LED incursion , regardless of the assumed discount rate. In the reference scenario, by contrast, the NPV for an IRL standard is near zero but barely positive at a 3- percent discount rate and more modestly negative at a 7-percent discount rate.

**•** L ighting controls growth led to a reduc tion in NPV for GSFLs by about 10 to 30 percent, but to a minimal NPV reduction for IRLs.

**•** Finally, in the alternative IRL lifetime scenario, due to increased relamping costs from lamps with shorter lifetimes , the NPV of an IRL standard in this scenario is substantially negative, regardless of whether the assumed discount rate is 3 or 7 percent.

f Notably, however, the NPV of an energy conservation standard for IRLs is increased over the best esti mate in both the high and the low economic growth scenarios . An increased NPV is possible in the low

- economic growth scenario

, because, as shown in Figure 10.2.1 , although electricity prices are lower than the reference scenario in the long term, they are higher in the near term. I f most of the energy savings are realized early in the analysis period

, the NPV of an energy conservation standard can increa se

.10-27 Table 10.4.7 Cum ulative NPV for Alternative Scenarios, 3% Discount Rate ( billion 2011$)

Analysis Type Scenario All CSL 1 Max CSL

IRL GSFL Total Rulemaking IRL GSFL Total Rulemaking

Standard Best Estimate 0.0403 1.95 1.99 0.0403 22.9 22.9

Uncertainty

Analyses REO High 0.0403 1.97 2.01 0.0403 22.5 22.6

REO Low 0.0403 1.94 1.98 0.0403 23.0 23.0 High Economic

Growth 0.0449 2.12 2.16 0.0449 23.7 23.7

Low Economic

Growth 0.0408 1.80 1.84 0.0408 22.2 22.3

Impact Determination Fixed Controls 0.0409 2.66 2.70 0.0409 26.8 26.8

No LED

- 0.00398 3.80 3.79

- 0.00398 35.5 35.5

Alternative Technology

Scenario IRL Short Life - 0.352 1.95 1.59

- 0.352 22.9 22.5

Table 10.4.8 Cumulative NPV for Alternative Scenarios, 7% Discount Rate ( billion 2011$)

Analysis Type Scenario All CSL 1 Max CSL

IRL GSFL Total Rulemaking IRL GSFL Total Rulemaking

Standard Best Estimate - 0.177 0.832 0.655

- 0.177 12.8 12.6

Uncertainty

Analyses REO High

- 0.177 0.850 0.673

- 0.177 12.7 12.6

REO Low

- 0.177 0.829 0.652

- 0.177 12.8 12.6 High Economic

Growth - 0.175 0.904 0.729

- 0.175 13.1 13.0

Low Economic

Growth - 0.175 0.774 0.599

- 0.175 12.5 12.3

Impact Determination Fixed Controls - 0.177 1.17 0.996

- 0.177 14.7 14.5

No LED

- 0.600 1.42 0.823

- 0.600 17.6 17.0

Alternative Technology

Scenario IRL Short Life - 0.341 0.832 0.491

- 0.341 12.8 12.410-28 REFERENCES

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3 Energy Information Administration, Annual Energy Outlook 2012 with Projections to 2035

, 2012. Washington, DC. Report No. DOE/EIA-0383(2012). < http://www.eia.doe.gov/oiaf/aeo/ >

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