Comments by Grant Smith, representing the Civil Society Institute 

First of all, EPA is doing the right thing. It is critical that you and the Administration 

do not succumb to the sea of cash that the coal industry is going to put into the effort 

to derail these regulations. The politics are very tough, hut the consequences of not 

acting are grave. This is a critical point in history. We have a choice between utter 

human tragedy and the prospects for at least the hope of a more positive future. 

The heyday of coal is over in this country. We all know that. The load of campaign 

contributions in Congress is inhibiting a sustainable energy revolution in the US. 

But the economics are clear. Wind and solar and efficiency continue to drop in cost 

while the costs of coal-fired power increase. Indeed, a study commissioned by Civil 

Society Institute- Beyond Business as Usual- demonstrates that it is cheaper to 

phase out coal than to sustain or expand it. 

Clean coal cannot exist. The fuel cycle is devastating to human health, the global 

climate, and eco-systems in general and releases C02 or methane at every stage. 

Mountain top removal in WV is a prime example. I bring this up because one of the 

most important carbon sinks in the world -the Appalachian forests- is being 

systematically annihilated. People are dying of a variety of diseases from this socalled mining method. And MTR is only one aspect of a fuel cycle that is killing and 

impairing tens of thousands of Americans each year- hardly a patriotic pursuit as 

spun by the industry. 

We require public policies that create a sustainable economy, not those that enable 

continued speculation and destruction of our natural resources and public health. 

But the coal and utility industries expect US taxpayers and ratepayers to pick up the 

tab. They expect carbon capture, enhanced oil recovery (sequestration has been all 

but abandoned}, and pipeline construction to be fully subsidized and taxpayers to 

assume liability for pipeline failures. They expect ratepayers to pick up costs of 

their power plant experiments before they are even built. They expect to be able to 

freely contaminate water supplies with questionable mining and waste disposal 

practices. The idea is to shift financial, environmental and liability risks to the 

taxpayer and ratepayer to allow for continued speculation in power plant 

construction, carbon capture, and exploitation of coal resources. Indeed, coal-fired 

power can only survive wholly on the backs of taxpayers and ratepayers. 

The coal industry is far too expensive to maintain. By some accounts, externality 

costs range into the hundreds of billions of dollars, despite decades of 

environmental protection laws. The pollution control system simply cannot handle 

the vast quantities of waste, emissions, and discharges from the coal fuel cycle. And 

those costs are severe. Attempting to save the industry through carbon capture and 

enhanced oil recovery or sequestration only serves to divert billions of dollars from 

efficiency and renewab!es. 
Let the Chinese pay for developing carbon capture technology. They can snap their 

fingers and move a million people if they want. They clearly have the ability to move 

on carbon capture if they wish. 

We have better things to do. We can systematically invest in a sustainable electric 

grid and eventually maintain reliability without base-load power. Clamping down 

on C02 emissions will go a long way to enabling that to happen. Coal-fired power is 

already obsolete in terms of efficiency, renewables and grid-operational advances. 

It will just take us time to replace it. We can systematically phase it out with what 

we have available to us now. Throwing good money after bad to the coal industry is 

a total waste of time and effort. We should seriously start shifting investment to 

true clean technologies with the adoption and enforcement of the proposed 

regulations. 

As for jobs- because that's the mantra from the industry: Not all jobs are created 

equal. We should put a premium on sustainable efficiency, renewables, storage, and 

distributed power and work to assist those in non-sustainable industries like coal, 

natural gas fracking, and nuclear to move to clean tech over time. 

Also, the perception is that regional differences prohibit a national move to a 

sustainable grid. That simply is not the case. Efficiency measures are available in 

any region as are renewable, storage and distributed power opportunities. 

Moreover, the grid is interconnected and balancing areas, for purposes of 

maintaining reliability, cover multiple regions. 

But I understand the politics are very difficult. One Iowa Congressman working to 

extend the production tax credit noted that there is a war on renewables being 

waged in Washington DC. Others are working to throttle funding for DOD 

renewable and efficiency investments. The fossil fuel and nuclear industries appear 

to be working to eliminate all alternatives but their own. 

Of course, these regulations should be broader and apply to existing coal plants as 

well. And we know that this is only a piece of the puzzle. Fracking and our 

transportation system contribute substantially to global warming, for instance, and 

must be aggressively addressed. But please stay the course and adopt these 

regulations. This is a step in the right direction. 

That concludes my comments. 
Eco-journey- Presbyterian Church (U.S.A.) 

MAY18, 201Z 

REBECCA RAKNES-llAVIES 

R.eflrxtions and wor·ds ji·orn my trip to Chadeston. WV for the 

Centn.J/ Appuluchian Women's Tribunal on C/inwteJuMice 

The Central Appalachian VVomf'n's Tribunal on Climate Justice on May 10, 2012 was a powerful 

and meaningful ew·nt of local women lifting up their Yo ices and engaging in action to protect the 

health and integrity of their families, their communities, and their land. [ wus honored and. 

cnPrgized to be in thi~ gathering of powerful grassroots advocates vvho are working hard to take 

carL' of the things they lo'T. The speakers and leaders of this e\'cnt were loc1l residents who 

shu red their personal stories of \\itnessing to the de\·astating effects of Mountaintop Removal 

(MTR) Coal :-.1ining in their homeland of Appalachia. Some of these local women have won 

prestigious awards, gainE'd national recognition, and/or been interviewed in documentaries for 

their y;reat effort.'>. They come from a fom state area: TN, \VV, VA, and KY. 

Tht•st~ women's liw.s have been drastically impacted by MTR and I was convicted and inspired by 

their stories. Hearing their testimonies, I am ever more committed to continue to pray and \vork 

for an end to thl' dcstrueti\'e practice of MTR that is damaging this pa1i of God's creation. I hope 

you \\ill join me in the.-,e eff01is, both from reading these g!imp!>es ofloealresident!>' stories and 

from knowing our biblical, theologic:al, and denomination mandate to care tOr God's creation. 

People of faith ha\'e ew1:.· reason to eny;age this struggle as a core part of their Christian vocation 

and identit~·· A.-; Preshyicrian Church USA policy from 1990 says, "God's \mrk in creation is tuu 

wondl'rt'nl, too ancient, too beantiful, too good to be desecrated." God's work in the mountains 

of the southeustcrn United States is: the work of these pO\verful wumcn, this \ita] stand ugainst 

!\1TR, and the hcauty Lind health of Appalachian communities. 

This gathering last week was one in a series of global tribunals that help to lift up the particular 

\'ulncrability of women to, and strength in thE' face of, climate change. These trihunuls have 

giH•n \·uice and reeognition to women who live all around the world and ;ne fighting for justice 

in their environment. Rd1cctions from this Appalachian tribunal v,il\ go to the "Rio+zo" United 

Kations Conference on Sustainahle Development this June 20-22, 2012 in Rio de Janeiro, Brazil. 

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.. r•,· 

ABOUT TillS BLOG 

Eco-Joumey i.<; the b[og oft he 

of the Presb~1erian Chnrcb 

(L'.S.A.). It will include a wide array of 

emirunmental topie::;: upcoming 

environmental events, links tn interesting 

urtides aud studie::;, infom1atiou on 

ell\1ronmental advocacy, ceo-theology topit::;, 

and success stories from ehun~hes that are 

go1ug green. 

Author Rebecca Bames-Da\il's is the 

A.~sociate for Endmnmcntal Mini,.:;tdes at the 

PC(USA). She recently graduated hom 

LouisYille Prcsb}icriun Theological Semiuar;. 

with a M.Div. and Master of Arts in Religion 

(MAR) dual degree. 

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[co-journey- Presbyterian Church (U.S.A.} 

<>II! Ll~ <lL l!l~ L..Cll Jll ~>lllllllillll.~ p<tll \11 lll<C t>Vll~l '--'JCJJ]\.-ll \Jl \..lll!lllJ\.-,~ w._JLP:,Clll\JJJ, JlllU »l!l lA 

.~luring with Presb~1erian.s and others back home my .st~nse ofthr de\·clopnwnts there. This loeal 

Women's Tribunal -.vas a great first step to this important global conference and will influencP 

my participation there. 

Nearly twenty women shared their personal stories, testimonies, idea:>, and demands related to 

:-.-Iuuntaintop Remm·a] Coal Mining. VVhile nothin)'; can replacP being in person to hear 

someonc's story. here arc some of the words <mel stories I took awa~· \\·ith me from local residents 

that I \Hint to shun' \\ith you. I cannot verify that my hand-written notes captured. exact 

qllotation'3, .-.u althongh I \\ill represent them (for clarity) in qllotatiun marks. this is my 

disclaimer that the actuul wording may hu\T hPen slightly different! 

"rt 's not po~sible to destruy our mountains without destmying u.s. It's not possible to poison our 

streams \\ithout poisoning onr children ... For all the voices you hear todc1y, rem em her thrre arc 

otlwr;; who have brcn silenced or intimidated.· From a \mman who can remember watching the 

blasting on the mountains from her bedroom \\indow since she w<:~s 5 years old.. 

:\25 yenr old woman. who knows that the legacy of l'minmmental degradation in her mountain.-. 

is to "stunt Applachians' health before they're even born," wants MTR Mopped because .~he 

desires that it be ".safe to bir1h my future children in my hmneland ... li\·ing when· our fumilies 

hm-c liwd for generations. ' Knowing that in Appalachiu "we need health~· habie;; for a higgPr, 

brighter futll!'c," she argues that \VL must undo the "shackles around our good health." 

A nmse takrs note of''strangr and serious illnesses" in her horne tcnitory (after going <:~way for 

nur;;ing truining and then coming back home). She was p<.niicularly .-.tun ned. b~· an extt·emel~· 

rare illness that took the life of her cousin (an illness \\·ith which on!~· 20,000 pt>oplr han' ever 

been diagnosed) that is now thC' diagnosis for unother person in ht'I' commnnity and one more 

ncMby. She .says there is not one home located IWJJ' coal mines thott has ]wen untouched h~· 

st>riou.s illncs.~. 

,\\\·oman whose 12 year old daughter lost a classmate to eancer-the saml' daughter ha\ing 

sC\'t'I'C sinus troubles beeame of:VITR (including the mcmbmne in her no~trils being cut hythe 

lnse rock dust the family had to breathc)-shared her anger that her daughter's health was being 

sacrificed to the energy demands of cheap coal in this country. This \\'tJni<.tn's family sta~·cd .sick 

the Pntire time tht>y H·er-e blowing up the mountain a bow their home. To add insult to rnngy. 

the reports from tlw coal company discounted the health disparities in the.'><.' communitir,; 

affected by MTR coal mining becau~e the case studies didn't take into acmnnt "con.sanguinit}" 

(in-breeding)! (If anyone is /onking for· Wl example uf mvironmentu/justit'e (i.e. environmental 

roc ism cmd clussi;;m), here it is.' Outrageous.' J 

Coming from a family that has been in coal mining for genemtion:o, mw \HJtnan shared that in 

ht>r::>.o yC'ar saga of trying to protect her land, it has been an ongoing h<1ttlc' that takes a ton of 

\\·ork. and unforiunately "people here arc frightened oftlw indu.-;tr':\·· ·In man~· families, penplt' 

\I'll!'!'\ "they'll tuke rn~ pension ... hnrn dmYn my house" and she shrugs ilS she speuks, knowing 

tlwir fears arc realistic and part of the fabric of this struggle. She has fonght long and hard. 

pnshing politicians who often \n>n't do an}ihing, which she recognit:cs is hecausr "it is political 

.suicide tot!)' to do an}thing" against coal in thi.s p<ni of the country. Yrt she has hope, even as 

there's another round of fighting aheud (thr coal company has yet aguin filed permits for the 

land. near her home, permits that haYc hu•n denied multiple time,~). She smile.~ and. says, "Get all 

these ladies together and do what wnmcn do and that's h·in the battle.~!" 

Another woman whose male rcbtions are all in coal mining, and who herself was a sta_,·-at-home 

mnm. shared her story about being "thrust" into this mon·ment by the coul compan~· it.:;clf. Hrm 

could .she haYe a choice when thiA MTR coal mining "c,an turn lungs into concrete," and when 

''nn<:hlnth· "h,hiP« "''P "'"lu•n,rJ h" nni«P" <1nrl ,,·hr>n" tnd,lJ,,. in hi-: hr>d "'"" ,..,~,<:hf'd In·" 

l11tp / ,lwww.pcusa.orgl blogsl eco-journey /2012 I 51 181 reflection -womens-stories-mtr-and-climate-change-tl 

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ARClllVES 

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Eco-journey ~Presbyterian Church (U.S.A.) 

boul<kr falling into his house from the mountaintop above'? Sludge gets into the \Vater. She 

Lkl'lares. this is ··l'quiYalent to a war zom:." She wants her children to know that tlwy have 

ehoices. So whC'n her legislator, agreeing with her in principal but nervous to take action says 

"\ve hun· an <l\\tullot of coal" she retorts "\,·e also have a lot of sun and air." She is clear that 

'"they mine coal where we lin, nrJt we live where they mine coal."' Families and communities 

come first. And, besides, "Nothing else matters if we can't breathe the air and drink the water." 

Telling a story about an old preacher who laid a dollar over the sc1·iptun: selection about it heing 

hard for n rich person to get to heaYcn (and then asking someone who wasn't seeing the point, 

"well, c~1n you see it now?.''") another woman focm;ed on follo\,ing the money in this debate. She 

has seen the medical expenses in her community, the cost of roads (driven on by too-heavy mal 

trucks) go into the creek<;, the Hooding in her community and wants these economic costs to be 

part of the discussion. When people talk about the economic hoon of coal mining, do they 

consider these things that matter to local residents'? 

When diseus.'iing the effects that MTR rual mining has on the local community, one woman 

shares that the wal mines "after they ruin your community and quality of life, then they eo me• in 

and offer money to buy you out." She ha" seen 30 communities dry: up and disappear in hl~r 44 

years of living in the area. She say.s "you can't haw Mountaintop Removal and eommunitie.s ... it's 

one or the other." 

Another woman talks about the chemicaLs in \Vater, air, and land. One family reportedly has a 

continuous flame in their well because of the explosive methane that seeped into their \Vater 

supply from mining. Birds and fish are dying, she explained, and property values plummet 

because homes arc covered in coal dust. Mountain ginseng and mountain flowers are buried. 

Family cemetarie.s arc ~ometimes made inaccessible because of coal mining. One cemetery \vas 

pushed m·er hv a bulldozer. All of these things break the sense loc-al residents have of belonging 

to the land. 

A woman who stmted standing up to the coal company in her tov.TI started explaining how the 

fabric of community is torn by the coal company: "fear." If her tmck was in her neighbors' 

driwv·.:ay, her neighbors got in trouble for associating with her. She lost her best friend. She 

stopped being asked to serve on volunteer organizations because the coal company wouldn't giYc 

donations to any local organizations that activists, like her, were a pa11 of (e\·cn if they didn't 

hnve anything to do with the struggle against coal mining). People were afraid and felt 

controlled, and they got alienated from each other. 

The long-time custom of "porch .sitting" is another example of how communities are hnrn1ed by 

coal mining, says another woman. You can't sit on ynur porch \Vith the huge trucks going by, coal 

dust spewing, .she Pxplaincd. MTR coal mining also reduces the labor pool, so that LTCates 

lension. Drug use ha~ gone up, the more people get depressed and look for outlets to escape. 

A ".'itubborn holler dweller" (as she \vas called bv the EPA) stood up to the coal company in her 

area and received serious death threats. Encouraged to move to a hoh'l, she stood her ground. 

With a 6ft chain link fence, security cameras. and attack dog, this local woman would "not be 

put out of my grandfather's home," even \vhen people were caught sneaking into her property. It 

is her home and she has a right to stay there. 

""Mom and Dad's chimney was pulled away from the wall" and they "lost access to water" because 

of coal mining, another woman said. When her parents lost access, the coal company graciously 

brought a barrel of water over, pouring bleach in it when it \vas obviously full of things you could 

see floating around in it. This woman, not trusting anything, took a sample. Her sample shmved 

tht' water was not fit to drink This stmggle sometimes is just "too hard ... people decide to 

mow." Her parento; staved, but one huge blast and shaking of the house broul!;ht a hem1 attack to 

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Page 3 of 5 
Eco-journey- Presbyterian Church (U.S.A.) 

her Dad. A year later, after having been mmwl away, her Mum died "crying to go hack horne." 

This woman tells us "I feel like an orphan ... Pcople ha\·c no idea whnt we go through." 

A local pastor reports th<:~t the local river isn't one where you can put your feet in or catch tish 

fmm. "No baptisms in this rh·er," she says. Meanwhile the receking rhairs on her porch are 

cm·cred in coal ash. The prayer concern list at church has "so many henlth problems." She 

believe~ in the statement from :Vta11in Luther King, ,Jr. that the church should be the headlights. 

hut that in this ease, the church i.s the taillights in standing up for the people !n Appalachia 

<l)',ain.st coal mining tompanies. 

At first in denial on~r the devastation of MTR, ltm·ing bought land and built a dream house, 

annthPl" hw:1l woman was forced to accept it ,,•hen her well water turned bright orange. She 

shares resigned disbelief that the burden of proof was on her (and her pocketbook) to prnve that 

it was the coal company's fault. This was a "huge '"'ake-up call," she says. She quickly came to 

rea\i;:e that many state officials hat"e a kind of culture of '·customer relations" with miners that 

the~· don't have with residents. Meanvvhilc, she found that \vhen ~he sampled her water. she had 

to send it 70 miles away (refrigerating it that whole time) because the company·.s water tester 

\\ill '"st,iteh your samples for tap '"·ater" so again, ""the burden of proof is on me." 

These women are strong, wi~;e, 01nd e,ourageous. 1 wa~ honored tn be in their presence and hope 

that you will join me in prayer and. action to help them protect their homes. ln addition to the 

"!rong stance that the Presbyterian Church USA has long taken-that low-income eommuniti('S 

not be digproportionatcly impacted hy negatin' environmental prartiees-in 2006 the PCUSA 

General Assembly approved a l"esulution to abundon the use of monntaintnp remrwal coal 

mining. \Ve believe that the emih is God's, and all people and all pa11s of creation arc to be 

valued, respected, and tended \\ith care. I pray that we t\ill indeed join our hearts, minds. and 

bodies to this faithful call and work fnr an end to MTR. 

··nlf.'.I/[Jllt their hund to theJ1inty rock, and ot'erhLn! mountains hy the mots. They cutout 

chunnels in the rocks, and their eyes see every JWecious thing. The sm1rces r!f" the r·it•ers they 

flrobe; hidden things they hring to light. J3Jit tdwrc shall wisdom hefnund? And !L"her·e is the 

place <!!"understanding?" .Jnb 28:g~12 

Posted at 3:09p.m. Tweet 3 

1. I ,,-as there. Your acrnunt il-l nearly ai-l affecting as the real event. Thank you for your words. 

shared them. 

b\· Cynthia D. Ellis 

MAY21. 2012 

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Eco-Journey- Pres byte nan Church {U.S.A.l 

I tl\1\lt "\ l 

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Et Loan Program (PILP) 

Office of the General Assembly (OGA) 

Presbyterian Publishing Corporation 

(PPC) 

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Presbyterian Church (U.S.A.) Foundation 

Board of Pensions 

Middle Governing Bodies 

Page5of5 
Toward a Sustainable Future 

for the U.S. Power Sector:

Beyond Business as Usual 2011 

November 16, 2011

AUTHORS:

Geoff Keith, Bruce Biewald, Ezra Hausman, Kenji 

Takahashi, Tommy Vitolo, Tyler Comings and 

Patrick Knight

Prepared for the Civil Society Institute
The Civil Society Institute (www.CivilSocietyInstitute.org) is a nonprofit and nonpartisan action 

oriented research center that serves as a catalyst for change by creating problem-solving 

interactions among people, and between communities, government and business that can help 

to improve society. CSI works to support local and state efforts to advance the modernization of 

the electric system and protect the health of citizens and their communities through advancing 

safe, sustainable, and affordable energy solutions.

Synapse Energy Economics, the consulting company that prepared this report, provides

research, testimony and reports to regulatory commissions, consumer advocates, environmental 

organizations and state and federal agencies. The firm was founded in 1996 to specialize in 

consulting on energy, economic, and environmental issues. Synapse has a professional staff of 

twenty two.

Geoff Keith is a Senior Associate at Synapse. He holds an MA in environmental studies from 

Brown University and a BA from Tufts University. He began consulting on energy and 

environmental issues in 1996. Prior to Synapse, he worked at M.J. Bradley & Associates and the 

Rhode Island Division of Public Utilities and Carriers.

Bruce Biewald is President and Chief Executive Officer of Synapse. He has consulted on 

issues of energy economics and electric industry restructuring since 1980 and has testified in 

more than one hundred regulatory proceedings in twenty four states and two Canadian 

provinces. Prior to founding Synapse, Bruce worked at the Tellus Institute. He studied 

architecture and building technology at MIT.

Ezra Hausman, Vice President and Chief Operating Officer of Synapse, has consulted on 

energy and environmental issues since 1998. He holds a PhD in earth and planetary sciences, 

an SM in applied physics from Harvard University, an MS in civil engineering from Tufts 

University, and a BA from Wesleyan University. Prior to his work at Synapse, he worked with 

Tabors Caramanis & Associates.

Kenji Takahashi is an Associate at Synapse. He holds an MA in urban affairs and public policy,

with a concentration in energy and environmental policy, from the University of Delaware and a 

BA in law, with a concentration in public administration, from Kansai University in Osaka, Japan.

Tyler Comings is an Associate at Synapse. He holds an MA in economics from Tufts University 

and a BA in mathematics and economics from Boston University. Prior to joining Synapse, he 

served as a senior associate at Ideas42, a think tank specializing in behavioral economics 

research.

Tommy Vitolo is an Associate at Synapse. He holds a PhD in systems engineering from Boston 

University, an MS in financial and industrial mathematics from Dublin City University, Ireland, 

and BS degrees in applied mathematics, computer science, and economics from North Carolina 

State University.

Patrick Knight, a Research Associate at Synapse, holds an MA in urban and environmental 

policy and planning from Tufts University and a BS in geophysics from Boston College.
Synapse wishes to thank the Civil Society Institute for funding this work, and all of our 

colleagues who have contributed ideas and feedback. Responsibility for errors and omissions 

rests entirely with Synapse and not with the Civil Society Institute. 
TABLE OF CONTENTS

1. INTRODUCTION AND SUMMARY..................................................................................1

2. METHODOLOGY................................................................................................................6

A. AEO 2011 AND BUSINESS AS USUAL ............................................................................6

B. DEVELOPING THE TRANSITION SCENARIO .....................................................................7

C. CALCULATING COSTS .....................................................................................................8

D. AIR EMISSIONS AND WATER USE...................................................................................9

E. TRANSMISSION AND SYSTEM OPERATION....................................................................10

F. SAVINGS FROM AVOIDED ENVIRONMENTAL RETROFITS..............................................12

G. AVOIDED HEALTH IMPACTS FROM COAL-FIRED GENERATION ....................................13

H. JOBS ASSOCIATED WITH NEW PLANTS ........................................................................13

3. BUSINESS AS USUAL AND THE TRANSITION SCENARIO..................................14

A. ELECTRICITY DEMAND ..................................................................................................14

B. THE GENERATING FUEL MIX.........................................................................................14

C. GENERATING CAPACITY................................................................................................16

D. TRANSMISSION AND SYSTEM OPERATION....................................................................19

4. FINDINGS...........................................................................................................................22

A. AIR EMISSIONS AND WATER USE.................................................................................22

B. AVOIDED HEALTH IMPACTS...........................................................................................25

C. NATURAL GAS USE.......................................................................................................26

D. NET COSTS ...................................................................................................................27

E. JOBS ASSOCIATED WITH NEW PLANTS ........................................................................28

F. SENSITIVITY ANALYSES ................................................................................................29

APPENDIX A: TECHNOLOGY COST AND PERFORMANCE ASSUMPTIONS .............33

A. FUEL COSTS..................................................................................................................33

B. EXISTING POWER PLANTS............................................................................................33

C. NEW POWER PLANTS ...................................................................................................37

Coal-Fired Plants 37

Combined Cycle Combustion Turbines (CCCT) 38

Combustion Turbines 38

Nuclear Plants 39

Wind Plants 40
Photovoltaics 42

Direct-Fired Biomass Plants 45

Geothermal Plants 45

Concentrating Solar Power (CSP) 46

End-Use Generation using Natural Gas 47

D. ENERGY EFFICIENCY ....................................................................................................47

E. DEMAND RESPONSE .....................................................................................................51

APPENDIX B: DATA TABLES..................................................................................................53

REFERENCES .............................................................................................................................59
Beyond Business as Usual ▪ 1

1. Introduction and Summary

In 2010 the Civil Society Institute released Beyond Business as Usual, a study evaluating a 

strategy for the U.S. electric industry that would provide large-scale public health and 

environmental benefits at a reasonable cost. The strategy, built around energy efficiency and 

renewable resources, would also provide substantial reductions in carbon emissions. Since then, 

the debate has continued over the best way forward for the electric industry. Advocates of a future 

based on coal with new environmental controls and carbon capture continue to make their case, 

as do advocates of nuclear power.

Away from this debate, new evidence has emerged that major changes in this industry are 

needed. Several mining tragedies globally have underscored the human toll of the coal supply 

chain. New EPA initiatives targeting air toxics, coal ash, and effluent releases highlight the 

environmental impacts of coal and the cost of addressing them with control technologies. The use 

of fracking in natural gas exploration is coming under scrutiny, with evidence of groundwater 

contamination and greenhouse gas emissions. Concerns are increasing about the vast amounts of 

water used at coal-fired and nuclear power plants, particularly in regions of the country facing 

water shortages. Events at the Fukushima nuclear plant have renewed doubts about the ability to 

operate large numbers of nuclear plants safely over the long term. 

Further, cost estimates for “next generation” nuclear units continue 

to climb, and lenders are unwilling to finance these plants without 

taxpayer guarantees.

In addition to these troubling events, however, information has 

emerged over the past year suggesting that the cost of replacing 

coal with clean energy is falling. The current and projected price of 

coal has increased, and the price of photovoltaic (PV) systems has 

fallen sharply since 2009, a result of unprecedented growth in this 

sector globally. Further, the financial sector is increasingly placing 

risk premiums on technologies with carbon emissions, making 

renewable energy and efficiency more attractive in comparison. 

Given these trends, a revision of last year’s study seemed 

especially timely.

For this revision, we have incorporated the price changes 

mentioned above, and we have revised several other assumptions based on feedback received on 

last year’s study. We have lowered our assumed capacity factors for wind generators and 

increased the assumed cost of wind energy. We have increased the assumed cost of sustaining 

high levels of efficiency savings over the study period and revised our estimate of the cost savings 

that would accrue from retiring coal-fired plants rather than retrofitting them with new 

environmental controls. 

Our methodology remains essentially the same as in the 2010 study. We use the U.S. Energy 

Information Administration’s annual modeling work to establish a reference case, or “business as 

usual” (BAU) scenario. We compare this to a “Transition Scenario” in which the country moves 

toward a power system based on efficiency and renewable energy. In this scenario all coal-fired 

power plants are retired, along with nearly a quarter of the nation’s nuclear fleet, by 2050. 

The study compares a 

“business as usual” future to 

a scenario in which all coalfired plants and a quarter of 

the nation’s nuclear plants 

are retired by 2050. 

Reliance on energy 

efficiency and renewable 

resources is increased, 

while natural gas use is 

lower than under business 

as usual. 
Beyond Business as Usual ▪ 2

Reliance on energy efficiency and renewable energy is significantly increased, while natural gas 

use is lower than under BAU. Importantly, the Transition Scenario does not rely on hoped-for 

breakthroughs; nearly all of demand is met throughout the study period with technologies that are 

commercial today. 

We estimate the net costs and benefits of the Transition Scenario relative to BAU using a 

spreadsheet model that accounts for generating capacity, energy, fuel use, costs, emissions, and 

water use. We perform the analysis on a regional basis, with the country divided into ten regions. 

We are careful to ensure that there is sufficient generating capacity in both scenarios and that 

there is a reasonable mix of energy sources in each region from the perspective of power system 

operation. For most of our technology cost and performance assumptions we rely on the Annual 

Energy Outlook (AEO) 2011 data. For some resources, however, we believe that other sources 

provide a more accurate picture of current and expected costs, and 

we base our assumptions on those sources. Finally, we perform 

sensitivity analyses around a number of important input 

assumptions. 

The Transition Scenario compares to BAU as follows.

 Total U.S. electricity use grows by 0.9% per year under 

BAU to 5,590 Terawatt-hours (TWh) in 2050. In the 

Transition Scenario, more aggressive energy efficiency 

programs across the country reduce electricity use by 

about 0.1% per year to 3,760 TWh in 2050.

 Under BAU, coal-fired generation grows from just over 

1,860 TWh in 2010 to 2,340 TWh in 2050 – a 26% 

increase. In the Transition Scenario, coal-fired generation 

is eliminated by 2050.

 Natural gas-fired generation grows from 1,010 to 1,840 TWh under BAU, while it rises to 

only 1,230 TWh in the Transition Scenario.

 Nuclear generation rises from 800 to 870 TWh under BAU, due to uprates at existing 

plants across the country and the addition of new units totaling 6,200 MW in the 

Southeast. Nuclear generation falls to 618 TWh in the Transition Scenario, a reduction of 

23%.

 Wind energy grows from 92 to 189 TWh under BAU, while it grows to 611 TWh in the 

Transition Scenario. This includes over 60 TWh from offshore wind farms.

 PV generation grows from 4 to 24 TWh under BAU, and it grows to 842 TWh in the 

Transition Scenario.

The results of this analysis are encouraging. We find that a transition to efficiency and renewable 

energy in the power sector is likely to be less expensive than BAU. Table 1 shows the net costs of 

the Transition Scenario relative to BAU at four points in time. These are annual costs, not 

cumulative. The net present value of the 40-year stream of savings and costs is a savings of $83

billion, discounted at 4.8%.

We perform the analysis on 

a regional basis with the 

country divided into ten 

regions. We are careful to 

ensure that there is 

sufficient capacity in each 

region and that regions 

have a reasonable mix of 

resources from the 

perspective of power 

system operation.
Beyond Business as Usual ▪ 3

The net annual cost impacts range from savings of $18 billion in 2050 to costs of $9 billion in 

2040. To put this in perspective, $18 billion is about 5% of total electric industry revenues in 2010, 

assuming 3,730 TWh sold at an average price of ¢10 per kWh. As seen in Table 1, when spread 

over all kWhs sold in the relevant year, the annual savings in 2020 are ¢0.4 per kWh consumed, 

and the costs in 2040 are ¢0.3 per kWh.

Table 1. The Net Annual Costs of the Transition Scenario (billion 2010$)

2020 2030 2040 2050

Net Cost of Generation ($23) ($50) ($49) ($58)

Energy Efficiency $19 $53 $58 $31

Demand Response $0.1 $0.7 $2.2 $4.0

Incremental Transmission $0.0 $0.0 $0.2 $1.1

New Energy Storage Costs $0.0 $0.0 $0.8 $3.6

Avoided Environmental Controls ($11) ($12) ($3.2) $0

Total ($16) ($8.2) $9.0 ($18)

Total (¢/kWh of electricity use) (¢0.4) (¢0.2) ¢0.3 (¢0.4)

We present several sensitivity analyses to gauge the range of uncertainty around these net 

savings. The variables with the largest impacts on the results are the cost of energy saved through 

efficiency measures, the cost of coal, and the cost of new PV capacity. However, in all of the 

sensitivity analyses, the Transition Scenario provides savings on an NPV basis relative to BAU.

The idea that we could capture the kind of benefits this scenario provides while also saving money 

is a significant change in our thinking about this industry. It reflects a fundamental shift in the cost 

of renewable energy relative to fossil-fueled and nuclear energy. 

These findings are particularly striking, given that the BAU 

scenario includes no carbon costs or carbon reductions. If the 

cost of carbon reductions were included under BAU, the savings 

provided by the Transition Scenario would grow dramatically. We 

also have not included externalized costs of pollution in our cost 

analysis, although we have estimated some of the health benefits 

of the Transition Scenario.

The benefits of the Transition Scenario include the following: 

 By 2020, power sector CO2 emissions fall 25% below 

2010 levels. By 2050 they are 81% below 2010 levels. 

Under BAU, CO2 emissions grow by 28% through 2050.

 Other environmental and health impacts of coal-fired 

electricity are dramatically reduced and, by 2050, 

eliminated altogether. This includes the air and water impacts of generation, coal ash and 

other solid waste, and the impacts of mining and coal transportation.

 Cooling water withdrawals at power plants fall from 55 to 0.6 trillion gallons per year in the 

Transition Scenario. In 2050 they are more than 90% below BAU levels. Water 

consumption at power plants (via evaporation) falls from 1.5 to 0.6 trillion gallons per year, 

76% below BAU levels.

The results of this study are 

encouraging. We find that a 

transition to efficiency and 

renewable energy is likely to 

be less expensive than 

business as usual. This is 

particularly striking given that 

our business as usual 

scenario includes neither 

carbon costs nor carbon 

reductions. 
Beyond Business as Usual ▪ 4

 Over $450 billion in health effects related to air pollution would be avoided over the study 

period, based on damage factors developed by the National Research Council. (We do 

not include these costs in calculating the net cost of electricity production for the 

Transition Scenario.) This translates into roughly 55 thousand fewer premature deaths in 

the Transition Scenario than under BAU. 

 The construction and operation of the new power plants in the first decade of the 

Transition Scenario creates roughly 3.1 million new job-years – the equivalent of 310,000 

people employed for the entire decade.

 Over $100 billion would be saved by retiring coal-fired plants rather than retrofitting them 

with new environmental controls.

 The annual production of high-level radioactive waste would be reduced by nearly a 

quarter, and the risks associated with nuclear power 

generation and the nuclear fuel cycle would be reduced as 

well.

 Natural gas use would be lower than BAU in all years of the 

study period. In 2050, gas use would be below BAU by 3.7

quadrillion Btu per year, or 28%. 

It is important to note that this scenario seeks to address a wide 

range of problems, and we have had to make tradeoffs among 

competing benefits. The study does not intend to lay out an optimized 

or detailed roadmap for the industry. Rather, it explores a 

fundamental change in direction. The intent is to challenge 

assumptions and inform the debate about U.S. energy policy. CSI 

expects to continue adjusting this Transition Scenario as more information becomes available, and 

we hope that other groups will explore variations on it as well. In terms of further research, the 

study points to the following areas of uncertainty. 

1. What is the most reliable and cost effective way for system operators to integrate high 

levels of variable generation into regional power systems? How much variable generation 

can a balancing area accommodate when the other resources are predominantly flexible 

ones rather than inflexible, baseload plants?

2. How will developments in the transportation sector affect the electric industry? Will 

transportation move to electricity on a large scale or to other fuels? If that sector does 

move toward electricity, how much power will it require and what kind of energy storage 

resource will electric vehicles offer?

3. What are the risks and carbon emissions associated with drilling in shale formations? 

What technologies and practices do we need to develop to minimize the use of natural 

gas as we phase out coal-fired generation?

Work in these areas is already underway at research labs, utilities, and government agencies 

globally. We hope that this study adds momentum to this and other work focused on the transition 

to a sustainable electric industry. 

The study does not lay out 

an optimized or detailed 

roadmap for this industry. 

Rather, it explores a 

fundamental change in 

direction. The intent is to 

challenge assumptions and 

inform our energy policy 

debate.
Beyond Business as Usual ▪ 5

Finally, the fact that CO2 emissions increase in our BAU scenario is important. While BAU is a 

useful baseline against which to compare alternative scenarios, it is not a tenable future. We must 

achieve significant carbon reductions over the next several decades. Therefore, the net costs and 

benefits of the Transition Scenario should be compared to those of other proposals that provide 

meaningful carbon reductions. To date we have not seen cost benefit analyses of futures built 

around new nuclear power or coal with carbon sequestration.
Beyond Business as Usual ▪ 6

2. Methodology

The methodology of the study is laid out below, and specific input assumptions are presented in 

Appendix A.

A. AEO 2011 and Business as Usual

We begin with data from the 2011 Annual Energy Outlook (AEO), released by the Energy 

Information Administration (EIA) in April 2011. Each year EIA uses the National Energy Modeling 

System (NEMS) to model a “Reference Case” energy scenario. EIA then analyzes various policy 

proposals by modeling the policy under consideration and comparing the results to the Reference 

Case. The AEO 2011 simulates U.S. energy production and use through 2035. The nation’s power 

sector is divided into the 22 NERC subregions for analysis.

We make several adjustments to the AEO 2011 Reference Case in creating our BAU scenario. 

First, to reduce the data requirements of the study, we aggregate the 22 regions used in the AEO 

into ten regions, as shown in Figure 1. Alaska and Hawaii are not included in this analysis.

Figure 1. Aggregating the AEO Regions

Second, because the AEO extends only through 2035, we extrapolate the AEO data to 2050. This 

includes data on electricity demand, generation, capacity retirements and additions, and fuel use. 

We extrapolate demand and generation in each region based on the regional trends in the AEO 

data during the period 2025 through 2035 (the last ten years for which the AEO provides data). 

Thus, the resources that NEMS selected to meet load growth during this period continue to meet 

CA

NW

AZ/NM

RM

WMW

TX

SC

SE

EMW

NE

NE

SC

SE SE

SE

SE

WMW

EMW

WMW

CA – California

AZ/NM – Arizona/New Mexico

NW – Northwest

RM – Rockies

WMW – Western Midwest

SC – South Central

TX – Texas

SE – Southeast

EMW - Eastern Midwest

NE - Northeast

EMW
Beyond Business as Usual ▪ 7

load growth through 2050. We report annual results for the years 2010, 2020, 2030, 2040, and 

2050.

In extrapolating the AEO data to 2050, we add or retire capacity necessary to maintain reasonable 

reserve margins. Most regions of the nation currently have excess generating capacity, and the 

AEO 2011 projects that this excess will shrink between now and 2030. (See Table 2 on page 18) 

As we extrapolate the AEO data, we continue this trend: under in the BAU, reserve margins in 

most regions fall to 15% by 2040, and we maintain reserve margins of at least 15% through 2050.1

In the Transition Scenario, reserve margins tend to fall to 15% faster than under BAU, but then 

they rise again in some regions in order to maintain enough flexible capacity to accommodate high 

levels of variable generation.

B. Developing the Transition Scenario

To develop the Transition Scenario, we first develop new forecasts 

of electricity consumption and peak load growth in each region. We 

do this by adjusting BAU demand to simulate the effects of more 

aggressive energy efficiency and demand response (DR) programs 

nationwide.2The energy use forecast in the AEO includes the 

effects of efficiency codes and standards in the near term; however 

it does not include the effects of future adjustments to codes and 

standards or the much larger impact of utility or third-party efficiency 

programs. Therefore, we adjust the AEO demand forecast based on 

data from efficiency programs currently being implemented across 

the nation and on a number of studies of energy efficiency potential. 

Specifically, we assume that by 2020 all regions are achieving 

savings equivalent to 2% of the previous year’s sales, consistent 

with the results of the most aggressive efficiency programs in recent 

years. (Several states and utilities are currently targeting savings in 

excess of 2%.) This level of savings is sustained throughout the study period. Each region begins 

the ramp up to 2% from its current average level of savings. We assume that the average cost of 

efficiency rises from ¢4.7 per kWh saved in the 2011-20 period to ¢7.0 per kWh in the 2040-50 

period, as it becomes more expensive to maintain this level of savings over time.

To develop peak load forecasts for the Transition Scenario, we adjust the AEO regional peak 

loads to account for the effects of energy efficiency and DR programs. The effect of efficiency 

programs are simulated by reducing peak loads by 0.15 kW for each MWh saved. This factor is an 

average based on analysis of state and utility efficiency program reviews.

We simulate the growth of DR programs by reducing peak loads in each region by an increasing 

amount over time and attributing costs to this reduced load. We estimate the relative potential of 

DR in different regions based on a study performed for the Federal Energy Regulatory 

Commission (FERC) in 2009 (Brattle Group et al., 2009). This study includes several DR potential 

 

1

The Rocky Mountain region is an exception to this rule, as NEMS allows the reserve margin to fall to 10% in 2030.

2

Demand response programs pay customers to reduce electricity demand during peak periods. 

To simulate a strong 

national commitment to 

energy efficiency, we 

assume that, by 2020, all 

states are achieving 

savings equivalent to 2% 

of sales, consistent with 

the results of the most 

aggressive programs in 

recent years. 
Beyond Business as Usual ▪ 8

estimates for each region, based on the type of loads and generation in each region. While the 

study includes some very aggressive estimates of regional DR potentials, we add DR resources 

over time in a fairly conservative way. (See Table 3 on page 18.) We expand DR capabilities most 

aggressively in regions where capacity is needed most, and we expand capabilities less where 

capacity is not needed. The cost of DR rises in each region as higher penetration levels are 

achieved (see Appendix A, Section E).

In the Transition Scenario, generation from retired coal and nuclear plants is replaced with

generation from the remaining power plants, new renewable resources and new gas-fired plants. 

The trajectory of plant retirements and additions was developed in an iterative way. Plant 

retirement and renewable energy development scenarios were sketched out for each region 

based on: the region’s mix of existing power plants; electricity demand growth; historical energy 

transfers into and out of the region; the renewable resources available in the region; and 

renewable technology cost data. Coal-fired capacity was retired as rapidly as possible, while 

maintaining adequate reserve margins and avoiding unrealistic development scenarios for any 

new resource.

After a rough nationwide scenario was sketched out, we explored ways to reduce the cost of the 

scenario or increase the benefits by adjusting plant retirements and additions in the various 

regions. This process required us to make tradeoffs. For example, retiring coal-fired units faster 

would reduce the net savings of the Transition Scenario, but it would increase the near-term 

environmental and health benefits as well as CO2 reductions.

C. Calculating Costs

Our technology cost and performance assumptions are based on a review of a number of sources, 

including work done by government agencies, engineering firms, utilities, financial researchers 

and non-governmental organizations. Wherever possible, we have compared these estimates to 

data from actual recent projects. As a default, we use the assumptions used in the AEO 2011. An 

advantage of using these data is that EIA has focused on consistency in the assumptions common 

to all technologies. However, for several technologies we find that data from other sources point to 

assumptions significantly different from those used in the AEO, and for these resources we have 

not used the AEO assumptions. A discussion of our cost and performance assumptions and the 

sources on which they are based appears in Appendix A.

To cost out the two scenarios, we first use the input assumptions presented in Appendix A to 

calculate the levelized cost of energy from each plant type in the BAU and Transition Scenarios. 

We do not include in this cost analysis the effects of direct subsidies, such as grants and tax 

incentives. For existing coal plants, gas-fired combined cycle plants, and combustion turbines, we 

calculate region-specific levelized costs based on the average capacity factor of the plants in each 

region and decade. For most new plants, we calculate costs with a single, nationwide capacity 

factor for each plant type. For new solar and wind facilities we use region-specific capacity factors. 

We then apply these levelized costs to the total generation from each resource type to determine 

total costs under BAU and in the Transition Scenario. To estimate the net cost or savings from 

pursuing the Transition Scenario, we subtract the total cost of generation under BAU from that of

the Transition Scenario.
Beyond Business as Usual ▪ 9

In addition to the cost of generation, we also calculate the cost of energy efficiency and DR, new 

energy storage capacity, and new inter-regional transmission capacity. We also estimate the 

savings the Transition Scenario would provide in avoided emission control costs.

D. Air Emissions and Water Use

The AEO reports power sector emissions of CO2, sulfur dioxide (SO2), oxides of nitrogen (NOX),

and mercury in each region through the analysis period. In addition, Synapse maintains a 

database of over 1,000 U.S. coal-fired generating units. This database includes information

reported by unit owners to EIA and the Environmental Protection Agency (EPA) regarding unit 

type, fuels, efficiency, air emissions and emission controls, cooling system, and operating costs. 

We use this database and the emissions reported in the AEO to estimate emissions and water use 

under BAU and in the Transition Scenario. An important step in this process is the development of 

assumptions about the new environmental controls that existing units will be required to install 

over the next 10 to 20 years. 

The EPA’s current work includes five major programs that are 

likely to affect emissions and water use at coal-fired power plants 

over the next several decades. Some of these programs include 

regulations that are currently in force, while other regulations are 

in various stages of development. These five programs are as 

follows.

 The promulgated Clean Air Visibility Rule requires a large 

cohort of power plants that affect visibility in national parks 

and other federal natural areas to reduce SO2, NOX and 

particulate emissions. This rule is currently in force, and is 

currently impacting plants across the Western U.S.

 The promulgated Cross State Air Pollution Rule (formerly 

the proposed Clean Air Transport Rule) will cap NOX and 

SO2 emissions in 2012 and 2014 across the eastern half 

of the U.S., excluding New England.

 The proposed Air Toxics rule will limit mercury, acid gases, and other toxic pollution from 

coal- and oil-fired power plants in 2015. Given the status of this proposal, we assume that 

the rule will be in force under BAU.

 EPA is scheduled in 2011 and 2012 to revise the current air quality standards for ozone, 

SO2, NO2, and fine particulate matter. The Agency’s drafts of these standards indicate that 

they will be substantially lower than the current standards, and will thus require controls in 

counties and regions that will be out of compliance. 

 The proposed Water Intake Structures rule under the Clean Water Act section 316(b) may 

require steam plants that use once-through cooling to reduce water withdrawals, thus 

effectively requiring the conversion of most plants to a recirculating cooling tower. While 

the details of the final rule are not yet certain, there is mounting pressure for reducing both 

withdrawals and thermal discharge, and it seems likely that numerous retrofits will be 

required.

Environmental control 

retrofits and unit retirements 

are simulated using a 

database of over 1,000 U.S. 

coal-fired generating units. 

Units with the lowest 

estimated retrofit costs per 

MW are retrofitted first. In the 

Transition Scenario, units 

with the highest forwardgoing costs, including retrofit 

costs, are retired first. 
Beyond Business as Usual ▪ 10

There is considerable uncertainty in predicting the results of these regulatory proceedings in terms 

of the pace and scope of retrofits at coal-fired plants. Faced with lawsuits and industry pressure, 

delays relative to EPA’s current timeframe are certainly possible. However, over the next several 

decades, it seems likely that EPA’s commitment to large-scale public health initiatives, along with 

court mandates the agency faces, will result in substantial emission reductions from coal-fired 

plants. Therefore, for the purposes of this study we assume that under BAU these reductions will 

be realized, but that they will be realized over a longer timeframe than EPA is currently planning. 

Specifically, we assume that:

 Half of the coal-fired units over 100 MW in size and without flue-gas desulfurization (FGD) 

systems install these systems by 2020. The other half installs them by 2030. On average, 

controlled plants achieve an SO2 emission rate of 0.2 lb per mmBtu.

 Half of the coal-fired units over 100 MW without selective catalytic reduction (SCR) 

systems install these systems by 2020. The other half installs them by 2030. On average, 

controlled plants achieve a NOX emission rate of 0.15 lb per mmBtu.

 Half of the coal-fired units over 100 MW without mercury controls and fabric filters to 

capture particulate matter install these systems by 2020. The other half installs them by 

2030. On average, mercury is reduced by 90% at controlled plants.

 Implementation of EPA’s proposed rule on water intake structures will eventually require 

all large power plants in the country to have closed-loop cooling systems. We assume that 

half of the coal-fired plants over 100 MW with once-through cooling systems install closedloop systems by 2020, and that the other half installs them by 2030.

 Units under 100 MW in size and gas-fired CCCTs and CTs are unaffected by these rules.

To estimate air emissions under BAU, we apply these control assumptions to the emissions from 

coal-fired plants. We assume that the units with the lowest per-MW retrofit costs are retrofitted first 

(between 2011 and 2020). These are generally the larger units. Controls on smaller units are not 

required until after 2020. In the Transition Scenario we apply the same retrofit assumptions along 

with the coal retirement strategy. Units that are retired in the same decade that they would have 

been retrofitted are not required to install the controls.

Total power sector emissions based on these assumptions are shown in Section 4.A. In Section 

4.B we report estimated health benefits of the emission reductions achieved in the Transition 

Scenario relative to BAU. And in our cost analysis we include the savings realized in avoided 

emission control investments in the Transition Scenario.

E. Transmission and System Operation

We address the cost of new transmission and system operation constraints in the following ways. 

First, we consider transmission within power control areas. The NEMS model (the basis of the 

BAU scenario) does not recognize transmission constraints within regions or simulate power flows 

within regions. To approximate the cost of transmission system upgrades within regions, NEMS 

applies regional cost factors to peak loads. In the Transition Scenario, loads do not grow, so 

transmission investment would not be needed simply to move more energy, as under BAU. 

However, investment within control areas would be needed to maintain and expand the 
Beyond Business as Usual ▪ 11

transmission system to accommodate more variable generation and allow new renewable energy 

to reach all parts of a regional grid. We make the simplifying assumption that this would cost 

roughly the same as the transmission investment estimated based on load growth in AEO 2011.

Turning to inter-regional transmission, the NEMS model includes transfer limits between regions,

and it simulates economic power transfers within those limits. It does not simulate the addition of 

new transmission capacity between regions. Therefore, under BAU there is little growth in energy 

transfers between regions. In the Transition Scenario, however, there are increased transfers 

between several regions. We estimate the cost of the new transmission capacity needed to 

accommodate these transfers by translating energy transfers into 

MW of capacity needed and assuming that new capacity (high 

voltage DC lines) costs $1 million per MW on average. (See 

Section 3.D.)

Regarding transmission, it is important to remember that most 

studies of aggressive renewable energy development envision load 

growth and continued operation of coal and nuclear capacity on a 

large scale. In the Transition Scenario demand falls slightly over the 

study period, and retired coal and nuclear plants would free up 

large amounts of existing transmission capacity each decade. 

Therefore, much less new transmission would be needed than in a

scenario in which renewables met growing loads on top of existing 

generation. 

At the distribution level, the same dynamic would occur: less 

energy would be delivered, and most of the energy from new, 

distribution-connected PV systems would be replacing coal and 

nuclear energy in those distribution systems. Of course distribution 

systems would have to be upgraded to accommodate more complex energy flows, but much of 

this work is already being funded, so it would not be incremental spending in the Transition 

Scenario.3Therefore, we add a $2 per MWh charge to all PV energy to contribute to the

distribution system work needed to accommodate the higher levels of distributed generation. By 

2050 this amounts to roughly $1.7 billion annually.

We have also focused on developing flexible and robust regional power systems that can 

accommodate minimum and maximum load conditions and the load swings between them. On this 

point, note that the retirement of large amounts of inflexible capacity – coal and nuclear units – will 

in itself create regional power systems that can accommodate more variable generation. In 

addition, we have incorporated four other strategies to increase the flexibility of regional power 

systems. 

 First, we ensure that regions with high levels of wind and PV generation also have large 

amounts of flexible generating capacity (primarily CCCTs and CTs) to accommodate rapid 

changes in wind and solar generation. 

 

3

Over the past several years, utilities have been authorized to collect and spend billions on distribution upgrades 

and other “smart grid” work.

Most studies of aggressive 

renewable energy 

development envision load 

growth and continued 

operation of coal and 

nuclear capacity on a large 

scale. In the Transition 

Scenario, demand falls 

slightly, and retired coal and 

nuclear plants would free 

up large amounts of 

existing transmission 

capacity.
Beyond Business as Usual ▪ 12

 Second, in regions with high levels of wind generation we augment this flexible generation 

with energy storage capacity.

 Third, the growing DR capacity and costs that we incorporate into the Transition Scenario 

also increase system flexibility. Demand response programs with “dispatchable” 

components such as direct load control help to provide intra-day and intra-hour ramping 

capability to support greater levels of variable generation output. The introduction of 

dynamic pricing and potentially greater customer response to system ramping 

requirements also increases the flexibility of the system to respond to variable generation.

 And finally, we expect that current trends toward larger energy balancing areas and 

increased coordination across balancing areas will continue. (Larger balancing areas 

support the reduction of aggregate wind variability by capturing the spatial diversity of the 

wind resource base.) For example, the Midwest ISO region consolidated its numerous 

balancing areas into a single balancing area in 2009, and this has allowed for integration 

of wind resources without significantly increasing operating reserve requirements. The 

Southwest Power Pool is planning to consolidate its member utilities into a single 

balancing region in this decade. The Pennsylvania/New Jersey/Maryland ISO (PJM) 

operates as a single balancing area, as do the northeastern ISOs (NY and NE), the 

California ISO and ERCOT (Texas). The Western Electricity Coordinating Council is also 

working toward a broader “energy imbalances market” to increase coordination across 

much of the Western Interconnect.

F. Savings from Avoided Environmental Retrofits

We assume that multiple new EPA rules result in widespread pollution control and cooling system 

retrofits at existing coal-fired units. Specifically, we assume that by 2030 all units over 100 MW in 

size have flue gas desulfurization (FGD) systems, selective catalytic reduction (SCR) systems, 

fabric filters, activated carbon injection systems, and closed-loop cooling systems. We assume 

that this retrofit strategy is implemented in both BAU and the 

Transition Scenario. However, in the Transition Scenario any unit 

that is retired in the same decade that it would have been required 

to install new controls does not install the controls. Therefore, a 

number of retrofits are avoided in the Transition Scenario. 

To target units for retrofits, we assume that the units with the 

lowest retrofit costs (generally the largest units) are required to 

install controls between 2011 and 2020 and that smaller units are 

controlled between 2020 and 2030. In general we target units for 

retirement based on each unit’s forward-going costs, including any 

emission control costs the unit faces. However, regional energy 

and capacity needs override this rule in some cases. For retrofit 

costs, we use the cost curves developed for EPA’s modeling with the Integrated Planning model. 

These curves, developed for EPA by Sargent & Lundy, reflect the fact that costs per MW are 

considerably higher at smaller units than at larger units.

This analysis yields a total avoided investment of $70 billion during the period 2011 through 2020,

and $41 billion during the period 2021 through 2030. We amortize these costs over a 15-year 

Many of the units retired in 

the first two decades of the 

Transition Scenario would 

have been required to 

install new environmental 

controls. We estimate the 

savings from avoided 

control retrofits at over $100 

billion.
Beyond Business as Usual ▪ 13

period, consistent with cost recovery requests in a number of recent cases before utility boards. 

Avoided annual carrying costs are $11 billion in 2020, $12 billion in 2030 and $3.2 billion in 2040.

These costs are shown in Table 5.

G. Avoided Health Impacts from Coal-Fired Generation

To estimate the health benefits of the Transition Scenario, we calculate damages and premature 

mortality based on the emissions and location of each coal-fired unit. We first estimate the air 

emissions (SO2, NOX, PM10 and PM2.5) at each coal-fired unit. Under BAU, emissions fall at many 

units due to control retrofits. In the Transition Scenario emissions fall due to control retrofits at 

some units and retirement of other units. 

We then calculate damages from each unit using a unit-specific value for damages per ton of 

pollution from the National Research Council’s report The Hidden Costs of Coal (NRC, 2010). 

Where the NRC does not provide a value for a specific generating unit, a regional average is used 

in its place. These damages are converted to statistical lives using the value of a statistical life 

used in the NRC study ($8.2 million per life, adjusted from $2000 to $2010) and summed across 

all units in the nation. The difference in premature mortality between the two scenarios is the net 

benefit of the Transition Scenario.

H. Jobs Associated with New Plants and Energy Efficiency

Finally, we estimate the new jobs associated with the energy efficiency and new power plants in 

the Transition Scenario. First, we estimate the direct jobs (associated with building and operating 

new power plants) using technology-specific data from the National Renewable Energy 

Laboratory’s (NREL) Jobs and Economic Development Impacts models. Second, we estimate 

“indirect” and “induced” jobs using the IMPLAN (IMpact analysis for PLANning) model. IMPLAN is 

an input-output model that relies on data sets describing the purchases of consumers and 

industries as well as flows of goods and services between regions. Using these relationships, and 

calibrating them for each region, IMPLAN is able to estimate the spin-off effects of new industryspecific activity by estimating the activity of suppliers required for that activity (indirect impacts) 

and the re-spending of workers’ wages in the economy (induced impacts). 

It is important to note that there would be other economic impacts as well: jobs created by lower 

cost electricity; jobs created in dismantling coal and nuclear plants and remediating the sites; and 

jobs lost in operating coal and nuclear plants, mining coal, and other associated activities. 

However, assessing all of these dynamics was beyond the scope of this work.
Beyond Business as Usual ▪ 14

3. Business as Usual and the Transition Scenario

A. Electricity Demand

Electricity demand grows under BAU at about 0.9% per year. This is based on the AEO 2011 

Reference Case, which includes the effects of current efficiency codes and standards, but not 

utility and third-party efficiency programs or any future changes to codes and standards. In the 

Transition Scenario, demand falls by an average of roughly 0.1% per year, as we simulate the 

impact of more aggressive utility and third-party efficiency programs. Figure 2 shows total U.S.

electricity generation in both scenarios.

Figure 2. Total Electricity Generation in the Two Scenarios

B. The Generating Fuel Mix

Figure 3 below shows the generating fuel mixes in the two scenarios. The key differences 

between the two scenarios are as follows.

 Total electricity generation under BAU grows to 5,930 TWh in 2050. In the Transition 

Scenario generation falls slightly, to 3,960 TWh in 2050.

 Under BAU, coal-fired generation grows from 1,860 to 2,340 TWh – a 26% increase. In 

the Transition Scenario, coal-fired generation is eliminated by 2050.

 Natural gas-fired generation grows from 1,010 to 1,840 TWh under BAU, while it rises to 

only 1,230 TWh in the Transition Scenario.

 Nuclear generation rises from 800 to 870 TWh under BAU, due to uprates at existing 

plants across the country and the addition of new units totaling 6,200 MW in the 

Southeast. Nuclear generation falls to 618 TWh in the Transition Scenario, a reduction of 

23%.

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

2010 2020 2030 2040 2050 Terawatt-hours

BAU Transition
Beyond Business as Usual ▪ 15

 Wind energy grows from 92 to 189 TWh under BAU, while it grows to 611 TWh in the 

Transition Scenario. This includes over 60 TWh from offshore wind farms in the Great 

Lakes and off the East Coast.

 PV generation grows from 4 to 24 TWh under BAU, and it grows to 842 TWh in the 

Transition Scenario. The majority of this is distributed PV generation. 

 Large-scale biomass generation under BAU grows from 11 to 33 TWh, with all of the 

increase due to co-firing at coal-fired plants. In the Transition Scenario, large-scale 

biomass generation grows from 11 to 24 TWh, with the growth coming at new plants 

burning biomass only.

 In both scenarios there is substantial growth in “end-use” biomass generation, as 

discussed below.

Figure 3. The Generating Fuel Mix in the Two Scenarios

While it is not evident in Figure 3, there is a shift to distributed generation in both scenarios. Under 

BAU, the largest increase in distributed generation is at gas-fired CHP plants; however there is a 

significant increase in cogeneration using biofuels as well (see below). In the Transition Scenario 

gas-fired CHP grows less than under BAU, but distributed PV generation grows far more. Overall, 

distributed generation grows faster in the Transition Scenario. 

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

2010 BAU 2030 TS 2030 BAU 2050 TS 2050 Terawatt-hours

Other

Solar

Geotherm.

Wind

Biomass

Hydro

Nuclear

Gas CHP

"Utility" Gas

Coal
Beyond Business as Usual ▪ 16

The two scenarios are the same in the growth of cogeneration using biofuels. In the AEO, strong 

demand for biofuels is driven by the Renewable Fuel Standard (RFS) established in the Energy 

Independence and Security Act of 2007. As the refining infrastructure to meet the RFS is 

developed, the AEO envisions increasing use of the refinery byproducts for cogeneration. By 

2035, roughly 75 TWh per year are generated using these residual biofuels. We include this 

generation in both BAU and the Transition Scenario. Aside from this cogeneration with biofuels, 

there is little growth in biomass power generation in either BAU or the Transition Scenario. Under 

BAU, utility-scale biomass generation grows to 33 TWh in 2050, while in the Transition Scenario it 

grows to only 24 TWh.

The environmental impacts of biomass generation are an important consideration, and more work 

is needed to understand the implications of the RFS.

C. Generating Capacity

Figure 4 below shows generating capacity in both scenarios. Notable aspects of the scenarios are 

as follows.

 In the Transition Scenario all coal-fired plants are retired as well as all oil- and gas-fired 

steam plants and oil-fired combustion turbines.

 Nuclear capacity is reduced by 22,600 MW, or 23%.

 Under BAU, gas-fired combined cycle capacity grows from 198 GW in 2010 to 262 GW in 

2050. In the Transition Scenario it grows to only 219 GW.

 Gas-fired CT capacity under BAU grows from 139 to 230 GW, while it grows to 200 GW in 

the Transition Scenario.

 Under BAU, onshore wind capacity grows from 38 to 64 GW, and offshore capacity grows 

from 0 to 0.2 GW. In the Transition Scenario, onshore wind grows to 162 GW, and 

offshore capacity grows to 16 GW (4 GW in the Great Lakes and 12 GW off the East 

Coast).

 PV capacity grows from 2 to 14 GW under BAU, while it grows to 384 GW in the 

Transition Scenario.

 Direct-fired biomass capacity grows in the Transition Scenario from 2 to 4 GW. End-use 

biomass capacity grows in both cases from 5 to 24 GW.
Beyond Business as Usual ▪ 17

Figure 4. Generating Capacity in the Two Scenarios

To ensure that we are maintaining sufficient capacity in each region, we perform a rough reserve 

margin check in each decade of the study period. We estimate reserve margins by first derating 

wind and PV capacity and then dividing installed capacity in excess of peak load by peak load. 

Wind capacity is derated to 15% of its nameplate capacity, and PV is derated based on regional 

data compiled in Perez, et al., 2006. Table 2 below shows the results for both scenarios. As seen 

in the 2010 data, all regions currently have excess generating capacity relative to historical 

reserve margins – typically in the range of 12% to 18%. The amount of excess capacity shrinks 

between 2010 and 2030, based on the AEO 2011. As we extrapolate the BAU beyond 2030, we 

continue this trend of falling reserve margins, with margins in most regions reaching 15% by 2040. 

We then add or retire capacity to maintain reserve margins of at least 15%, except in the Rocky 

Mountains. In this region we follow the AEO and maintain a 10% margin there.

In the Transition Scenario, reserve margins fall faster than under BAU, due to aggressive 

retirement of coal-fired capacity. In several regions, reserve margins rise again in the last decade, 

as additional gas-fired and storage capacity is added to support high levels of wind and solar 

generation.

0

200

400

600

800

1,000

1,200

1,400

2010 BAU 2030 TS 2030 BAU 2050 TS 2050

Gigawatts

New Storage

Other

Solar

Geotherm.

Wind

End-Use Biomass

Direct-Fire Biomass

Hydro

CT

Nuclear

Gas CHP

Gas CCCT

Oil & Gas Steam

Coal
Beyond Business as Usual ▪ 18

Table 2. Reserve Margins in the Two Scenarios

Case 2010 2020 2030 2040 2050

AZNM BAU 50% 29% 17% 15% 15%

Transition 50% 25% 16% 15% 15%

RMPA BAU 37% 17% 10% 10% 10%

Transition 37% 15% 10% 10% 10%

NWPP BAU 92% 69% 51% 39% 33%

Transition 92% 80% 59% 49% 42%

CAMX BAU 31% 25% 27% 15% 15%

Transition 31% 33% 16% 15% 18%

NE BAU 43% 26% 21% 15% 15%

Transition 43% 31% 15% 15% 15%

SE BAU 34% 32% 29% 18% 15%

Transition 34% 21% 15% 15% 15%

EMW BAU 36% 34% 30% 21% 15%

Transition 36% 19% 15% 15% 15%

WMW BAU 38% 31% 27% 19% 15%

Transition 38% 22% 15% 16% 26%

SC BAU 27% 18% 19% 15% 15%

Transition 27% 15% 15% 17% 21%

ERCT BAU 34% 25% 24% 15% 15%

Transition 34% 15% 15% 17% 15%

We simulate the growth of DR programs by reducing peak loads in each region by an increasing 

amount over time and attributing costs to this reduced load to represent the payments made to 

customers enrolled in the programs. We estimate the relative potential of DR in different regions 

based on a study done for FERC in 2009 (Brattle Group et al., 2009). Table 4 shows three 

scenarios developed in this study, with increasing levels of DR achieved by 2019. The scenarios 

are called the “Expanded BAU” case (EBAU), the “Achievable Participation” case (AP), and the

“Full Participation” case (FP). Table 3 compares these scenarios to the DR penetration levels in 

the Transition Scenario. In all regions, our assumed DR penetration in 2050 is at or below the 

2019 level in the FERC study’s Achievable Participation scenario. 

Table 3. Demand Response Penetration Compared to 2009 FERC Study of Potential

FERC DR Study Transition Scenario

2019

(EBAU)

2019

(AP)

2019

(FP) 2020 2030 2040 2050

Arizona/New Mexico 4% 16% 24% 1% 4% 10% 15%

Rocky Mountains 2% 9% 14% 2% 4% 7% 9%

Northwest 5% 11% 16% 1% 1% 1% 1%

California 1% 7% 11% 1% 3% 5% 7%

Northeast 3% 7% 10% 1% 3% 5% 7%

Southeast 6% 12% 19% 1% 4% 8% 10%

Eastern Midwest 5% 9% 14% 1% 4% 7% 9%

Western Midwest 4% 8% 11% 1% 3% 5% 7%

South Central 7% 13% 17% 2% 5% 10% 12%

Texas 7% 14% 20% 1% 5% 9% 14%

Note: the data from the FERC study have been adjusted to match the regions used in our analysis.
Beyond Business as Usual ▪ 19

D. Transmission and System Operation

There are three areas of the country in which new transmission capacity would be needed to 

move additional energy between regions in the Transition Scenario. 

 In the Western Interconnect, we envision an increase of roughly 27 TWh per year moving 

from the Northwest into the Rockies. The new transfer capacity would be needed in the 

final two decades of the study period. We estimate the total cost of the capacity needed to 

be $5 billion. 

 We also envision 9 TWh per year moving from the Texas region to the Southeast by 2050. 

This would require a new HVDC line, added between 2040 and 2050, at an estimated cost 

of $1.7 billion.4

 After 2040, transfers would also increase from the Western Midwest to the Eastern 

Midwest. By 2050, an additional 27 TWh would be moving into the Eastern Midwest, and 

the estimated cost of the new transfer capacity is $5 

billion. 

These cost estimates are made based on an assumed cost of $1 

million per MW of increased transfer capacity. This assumption is 

based on information developed for the Eastern Wind Integration 

and Transmission Study (EnerNex 2010), the Eastern 

Interconnection Planning Collaborative, and on recent cost 

estimates from the developers of proposed transmission projects. 

The total cost of the new transfer capacity listed above is $11.7 

billion. We include the annualized cost of this capacity (recovered 

over 30 years) in our cost analysis (see Table 5).

As discussed above, we have paid careful attention to the 

amount of variable generation in each region. By the later 

decades of the Transition Scenario there is considerably less 

coal-fired capacity operating, and by 2050 there is no coal-fired 

capacity and 23% less nuclear. The removal of this inflexible 

capacity would make regional systems much better able to 

integrate variable generation than today’s systems. But in addition, we have taken steps to ensure 

that we end up with resource mixes that can respond to all load conditions. These steps include: 

ensuring that regions with high levels of variable generation also have high levels of flexible 

generation and capacity; adding storage capacity in regions with high levels of wind generation; 

and including the cost of robust DR programs. We also note that current trends in system 

operation are likely to facilitate the integration of variable resources even under BAU. These 

trends include the consolidation of balancing areas and increased information sharing and 

cooperation among balancing areas. 

 

4

For comparison, developers of the “Southern Cross” line, a proposed HVDC line connecting Texas to the 

Southeast, estimate project costs at “well over $1 billion.”

Systems with little coal and 

nuclear capacity and large 

amounts of flexible capacity 

will be able to accommodate 

more variable generation than 

today’s systems. Modeling 

and statistical analyses are 

needed to determine what 

kind of constraints will 

emerge in such systems and 

ultimately how much PV and 

wind generation can be 

accommodated.
Beyond Business as Usual ▪ 20

Figure 5 shows the 2050 energy mix in each region. The Arizona/New Mexico region, the South 

Central region and Texas have the highest levels of variable generation, all slightly above 50%. In 

the southwest this is primarily PV generation, while in the central regions there are high levels of 

wind energy too. However, all three of these regions are generating considerable amounts of 

energy at flexible gas-fired units (CCCTs and CTs). More importantly, Figure 6 shows that both of 

these regions have large amounts of flexible capacity. In Figure 6, flexible capacity (gas CCCTs, 

CTs and storage capacity) appears in various shades of grey. In all three of these regions, these

resources account for over 65% of installed capacity. This capacity, most of it gas-fired units 

operating at relatively low capacity factors, would be available to respond quickly to steep ramping 

conditions and unexpected renewable generation levels. (We have not included hydro as flexible 

generation, because we have not determined how much hydro capacity in each region is flexible. 

However, in some regions hydro would provide considerable additional flexibility.)

Figure 5. The Regional Generating Mixes in 2050 in the Transition Scenario

Energy storage capacity begins to come on line between 2030 and 2040. We have added this

capacity primarily in regions with high levels of wind generation (the Western Midwest, South 

Central and Texas) to provide ancillary services and to store wind energy. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

AZ/NM Rockies Northwest California Northeast Southeast E. Midwest W. Midwest S. Central Texas Percentage of Generation

Other

Solar

Wind

Gas CC & CT

Hydro

Gas CHP

Biomass

Geotherm.

Nuclear
Beyond Business as Usual ▪ 21

Figure 6. Installed Capacity in 2050 in the Transition Scenario

By 2050 there is 8 GW of storage capacity in the Western Midwest, 3 GW in the South Central 

region, 4 GW in Texas and just under 3 GW in the Northeast. (The Western Midwest, South 

Central and Northeast regions also have existing pumped storage capacity, included in “Other” in 

Figure 6.) We use an average cost of $1,200 per kW for new storage capacity (in 2040) reflecting 

a mix of battery, flywheel, and compressed air storage, with cost projections based on EPRI-DOE, 

2004.

While we have made a number of adjustments to ensure that we have flexible and operable 

resource mixes, more work is needed to understand how resource mixes like these would respond 

to different load and generation conditions. Most of the research to date in this area has focused 

on adding renewable resources to regional systems that already have large amounts of inflexible 

baseload capacity (i.e., coal and nuclear units). Systems with little coal and nuclear capacity and

large amounts of flexible capacity will be able to accommodate more variable generation. 

Modeling and statistical analyses are needed to determine what kind of constraints will emerge in 

such systems and ultimately how much PV and wind generation can be accommodated.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

AZ/NM Rockies Northwest California Northeast Southeast E. Midwest W. Midwest S. Central Texas Percentage of Installed Capacity

Other

Solar*

Wind*

New Storage

CT

Gas CCCT

Hydro

Baseload

*Wind and PV capacity has been derated.
Beyond Business as Usual ▪ 22

4. Findings

A. Air Emissions and Water Use

It is important to note that our calculations of air emissions and water use in the two scenarios are 

dependent on our assumptions about emission control retrofits under BAU (see Section 2.D), and 

there is considerable uncertainty around the pace at which control retrofits will be required in the 

first two decades of the study period. As EPA’s regulatory initiatives progress, it will be important 

to revise these emissions estimates if necessary. 

Under BAU, power sector CO2 emissions rise by 28% to 3.3 billion tons per year in 2050. In the 

Transition Scenario, CO2 emissions fall to just under 0.5 billion tons per year. This is a reduction of 

81% from 2010 levels.

Figure 7. CO2 Emissions in the Two Scenarios

Mercury emissions fall considerably under BAU as we assume that the entire coal fleet is 

controlled by 2030 and any new plants added are controlled. Emissions nationwide in 2050 are 

just under 5 tons under BAU. In the Transition Scenario, mercury emissions are virtually 

eliminated by 2050 with the elimination of coal-fired generation.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2010 2020 2030 2040 2050

Billion Tons

BAU Transition
Beyond Business as Usual ▪ 23

Figure 8. Mercury Emissions in the Two Scenarios

Under BAU, SO2 emissions fall sharply by 2030, the result of widespread FGD retrofits, and then 

begin rising again as coal-fired generation continues to increase. Total emissions are reduced by 

40% by 2050. In the Transition Scenario, SO2 emissions are virtually eliminated by 2050 with the 

retirement of all coal- and oil-fired plants.

Figure 9. SO2 Emissions in the Two Scenarios

Widespread SCR retrofits reduce NOX emissions under BAU by 36% by 2050. Overall reductions 

are achieved despite a considerable increase in gas-fired generation under BAU. Emissions of 

NOX fall by 83% in the Transition Scenario relative to 2010 levels, as coal-fired generation is 

phased out and natural gas use remains lower than under BAU.

0

5

10

15

20

25

30

35

40

45

2010 2020 2030 2040 2050

Tons

BAU Transition

0

1

2

3

4

5

6

2010 2020 2030 2040 2050

Million Tons

Reference Case Alternative Case
Beyond Business as Usual ▪ 24

Figure 10. NOX Emissions in the Two Scenarios

Figures 11 and 12 show total power sector water withdrawals and consumption in the two

scenarios. Water used for cooling and then returned to a body of water is classified as a 

“withdrawal,” and water not returned is classified as “consumption.” For coal-fired plants we 

estimate withdrawals and consumption using the same database of generating units used to 

estimate emissions and health impacts. This database includes information reported to EIA on the 

cooling system type for each coal-fired unit in the U.S. For other plant types, average water use 

assumptions were developed based on information reported by plant owners to EIA and on 

Stillwell, et al., 2009. Regarding cooling system retrofits, we assume that half of the coal-fired units 

under 100 MW in size and lacking closed-loop cooling systems install such systems by 2020. We 

assume that the other half installs them by 2030. (No retrofits are required at units smaller than

100 MW.) Similarly, we assume that half of the nuclear units lacking closed-cycle cooling install 

these systems by 2020 and the other half installs them by 2030.

Figure 11. Water Withdrawals at Power Plants in the Two Scenarios

0.0

0.5

1.0

1.5

2.0

2.5

2010 2020 2030 2040 2050

MIllion Tons

BAU Transition

0

10

20

30

40

50

60

2010 2020 2030 2040 2050

Trillion Gallons

BAU Transition
Beyond Business as Usual ▪ 25

In both scenarios, water withdrawals fall sharply between 2010 and 2030 due to retrofits of closedloop cooling systems at coal-fired and nuclear plants. After 2030 withdrawals begin rising again 

under BAU, with rising coal-fired generation. In the Transition Scenario, withdrawals continue to 

fall after 2030 due to coal and nuclear plant retirements.

Figure 12. Water Consumption at Power Plants in the Two Scenarios

Water consumption rises under BAU, because closed-loop cooling systems lose more water via 

evaporation than open-loop systems. (However, note that overall consumption is an order of 

magnitude lower than withdrawal.) Consumption remains stable over the first decade in the 

Transition Scenario, as retirements offset the increased consumption at plants with new, closedloop systems. After 2020, consumption falls steadily in the Transition Scenario, the result of coal

and nuclear plant retirements.

B. Avoided Health Impacts 

We estimate health effects avoided via reduced air pollution in the Transition Scenario using plantspecific damage factors developed by the National Research Council in the report The Hidden 

Costs of Energy (NRC, 2010). These damage factors represent the monetary value of statistical 

premature mortality due to air pollution (in monetized dollars per ton of pollutant); In Table 4 

below, we show the monetized values for both scenarios as well as the estimates of statistical 

premature mortality. We convert monetized damages to premature mortality using the value of 

statistical life utilized by the NRC of $8.2 million (adjusted from $2000 to $2010.)

0.0

0.5

1.0

1.5

2.0

2.5

2010 2020 2030 2040 2050

Trillion Gallons

BAU Transition
Beyond Business as Usual ▪ 26

Table 4. Avoided Damages or Premature Mortality from Coal-Fired Plants in the Transition Scenario

2011-2020 2021-2030 2031-2040 2041-2050 Cumulative 

Total

Billion dollars

 BAU 427 276 251 260 1,215

 Transition 421 210 93 28 752

 Difference 6 66 158 232 463

Statistical Lives

 BAU 52,000 34,000 31,000 32,000 149,000

 Transition 51,000 26,000 11,000 3,000 91,000

 Difference 1,000 8,000 20,000 29,000 58,000

Figures may not sum due to rounding.

Net damages are fairly small during the first decade because most of the existing coal-fired 

capacity without controls is controlled in both the BAU and Transition Scenario during this decade. 

The difference in mortality is due to a number of large units that are retired rather than controlled 

in the Transition Scenario and some smaller units that are retired in the Transition Scenario and 

not controlled under BAU. The health benefits of the Transition Scenario grow in the second 

decade because unit retirements continue on a large scale in the Transition Scenario, while there 

are far fewer control retrofits under BAU than in the first decade. After 2030 there are no further 

retrofits in either scenario, but the retirements continue in the Transition Scenario. Therefore, 

health benefits continue to increase in these decades.

These are rough estimates, and they are heavily dependent on our assumptions about the pace of 

control retrofits under BAU and about which coal-fired units are controlled and retired in each 

decade. Regarding controls, we assume that the largest uncontrolled units are controlled first –

units where the cost of control is likely to be lowest in terms of dollars per MW. Regarding 

retirements, we assume that the least economic units are retired first, considering fuel, operating,

and retrofit costs. Different assumptions about which units are controlled first and retired first 

would yield different estimates of avoided mortality. 

C. Natural Gas Use

A key goal in our development of the Transition Scenario was to maximize our reliance on 

efficiency and renewable energy and thus minimize the amount of natural gas needed for the 

transition away from coal and nuclear power. As seen in Figure 13, annual power sector gas use 

is lower in the Transition Scenario than under BAU in all years of the study period. In 2020, it is 

0.3 quadrillion Btu (4%) lower than under BAU, and by 2050 it is 3.7 quadrillion Btu (29%) lower 

than BAU. 

Figure 13 shows gas use from both “central station” plants (steam units, CCCTs and CTs) and 

“end-use” (CHP) facilities. The NEMS model selects from a variety of CHP equipment. We 

represent CHP plants with the characteristics of the equipment selected most by the NEMS model 

in the 2011 AEO: a 10 MW CT with an overall efficiency of 76%. We allocate 40% of the cost, fuel 

use and emissions from this plant to electricity production and 60% to steam production. 

Therefore, 40% of the gas use at CHP plants is included in Figure 13, and 60% would be reported 

as commercial or industrial gas use.
Beyond Business as Usual ▪ 27

Figure 13. Power Sector Natural Gas Use in the Two Scenarios

It will be important to revisit the resource mix in the Transition Scenario as more information 

becomes available. Information about the cost and potential of efficiency, renewables and energy 

storage technologies could warrant changes to this scenario, as could information on the 

greenhouse gas emissions and health risks of gas drilling.

D. Net Costs

Table 5 (below) shows the net costs of the Transition Scenario relative to BAU at four points in 

time. Note that these are annual costs, not cumulative. Over the study period, significant savings 

in the cost of generating electricity offset incremental costs such that the scenario provides net 

savings over much of the study period. The net present value of the 40-year stream of savings 

and costs is a savings of $83 billion, discounted at 4.8%. 

The net annual impacts range from savings of $18 billion in 2050 

to costs of $9 billion in 2040. To put this in perspective, $18 billion 

is about 5% of total electric industry revenues in 2010, assuming 

3,730 TWh sold at an average price of ¢10 per kWh. As seen in 

Table 5, when spread over all kWhs sold in the relevant year, the 

savings are ¢0.4 per kWh consumed in 2020, and the costs are 

¢0.3 per kWh in 2040.

Demand response costs represent the payments to customers 

enrolled in demand response programs. Incremental transmission 

represents the cost of increasing transfer capabilities between 

regions to accommodate the increased power exchanges in the 

Transition Scenario. Energy storage is the cost of building and 

operating storage facilities. The cost of the energy losses from 

storage is included in the Net Cost of Generation. Avoided 

emission control costs are the costs avoided by retiring coal-fired 

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

2010 2020 2030 2040 2050

Quadrillion Btu

BAU Transition Scenario

We explore several 

sensitivity analyses to gauge 

the range of uncertainty 

around these net savings. 

The variables with the 

largest impacts are the cost 

of energy efficiency, the cost 

of coal and the cost of new 

PV capacity. However, in all 

of the sensitivity analyses 

the Transition Scenario 

provides savings on an NPV 

basis relative to BAU.
Beyond Business as Usual ▪ 28

plants rather than adding the controls expected under BAU. We assume 15-year cost recovery on 

emission control investments (compared to 30 years for all other investments).

Table 5. The Net Annual Net Costs of the Transition Scenario (billion 2010$)

2020 2030 2040 2050

Net Cost of Generation ($23) ($50) ($49) ($58)

Energy Efficiency $19 $53 $58 $31

Demand Response $0.1 $0.7 $2.2 $4.0

Incremental Transmission $0.0 $0.0 $0.2 $1.1

New Energy Storage Costs $0.0 $0.0 $0.8 $3.6

Avoided Environmental Controls ($11) ($12) ($3.2) $0

Total ($16) ($8.2) $9.0 ($18)

Total (¢/kWh of electricity use) (¢0.4) (¢0.2) ¢0.3 (¢0.4)

In Section 4.F we present a number of sensitivity analyses to gauge the range of uncertainty 

around these net savings. The variables with the largest impacts on the results are the cost of 

energy efficiency, the cost of coal and the cost of new PV capacity. However, in all of the 

sensitivity analyses the Transition Scenario provides savings on an NPV basis relative to BAU.

E. Jobs Associated with New Plants

Table 6 shows the new jobs associated with the expanded energy efficiency programs and the 

construction and operation of new power plants in the Transition Scenario. Data in this table are 

reported in job-years, the equivalent of one new worker employed for a year. Total direct jobs are 

calculated using technology specific factors from NREL’s Jobs and Economic Development 

Impacts models. Indirect and induced jobs are calculated using the IMPLAN model.

It is important to note that this is a limited analysis of the employment effects of the Transition 

Scenario. A wider analysis would be needed to assess the full, net effects of the scenario. For 

example, there would be additional jobs created in the Transition Scenario as a result of lower 

expenditures on electricity across the economy and in the decommissioning of retired power 

plants. There would also be significant job loss due to the retirement of coal and nuclear plants. 

More work is needed to develop a full picture of the economic impacts of the Transition Scenario.

Employment impacts are shown only for the first decade of the study period, because advances in 

technology will change not only the cost of new resources but also the amount of labor needed to 

install and operate them. Thus, the uncertainty around employment impacts becomes quite large 

in later decades. 
Beyond Business as Usual ▪ 29

Table 6. Employment Impacts of New Plants and Energy Efficiency in the Transition Scenario 

2011-2020 (job-years)

Technology Direct 

Construction Direct O&M Total Direct, Indirect, and Induced

Wind 138,000 22,000 932,000

CSP 5,000 1,000 18,000

Photovoltaic 130,000 55,000 1,533,000

Geothermal 5,000 4,000 26,000

Biomass 30,000 9,000 284,000

Gas CHP 2,000 0* 16,000

Energy Efficiency 134,000 0* 299,000

Total 444,000 90,000 3,108,000

*Direct O&M job-years associated with Transmission are less than 500. This is shown as zero 

here as figures are rounded to the nearest thousand job-years. We assume no jobs associated 

with operation and maintenance of efficiency measures.

For direct construction, roughly 444,000 job-years are created, equivalent to 44,400 construction 

workers working full time for the entire decade. Similarly, roughly 90,000 O&M job-years are 

created, equivalent to about 9,000 full time workers employed over the decade. Whereas in 

construction the number of jobs is roughly the same each year, the O&M jobs ramp up over time. 

In the first year there are nearly zero jobs, because no projects have been completed. However, 

assuming a roughly linear rate of construction over the decade, the last year would require roughly 

18,000 people full time to perform the O&M activities for the completed new projects.

Direct jobs aren’t the only employment impact of these projects. They require materials and 

additional people to design, manufacture, and deliver those materials. Those materials in turn may 

require materials for their production, and so forth. These are “indirect” jobs. Further, all the 

workers building and operating the projects – as well as the workers manufacturing the ingredients 

to the projects – spend their wages in the local economy. These expenditures create “induced” 

jobs. It is this multiplier effect, both from indirect and induced jobs, which results in a total job-year 

creation in excess of 3.1 million between 2011 and 2020.

F. Sensitivity Analyses

Looking at Table 5 (above), one can identify several assumptions that do not have a large impact 

on the cost results. For example, doubling or tripling the cost of DR, new transmission or energy 

storage would not change the net costs much. We performed sensitivity analyses around the

assumptions that have a larger impact. Analyses of the following input assumptions are presented 

below:

 The cost of energy efficiency,

 Coal and natural gas prices,

 The cost of PV systems, and

 The cost of new nuclear plants.

The Transition Scenario provides the highest net present savings ($144 billion) in the high coal 

price sensitivity. Savings are lowest ($21 billion) in the high PV cost scenario. 
Beyond Business as Usual ▪ 30

In doing these analyses, we simply changed the input assumption and observed the change in the 

net savings and costs of the Transition Scenario over time. We did not develop new BAU and 

Transition Scenarios based on the changed assumption.

To assess the cost of energy efficiency, we developed the high and low cost cases shown in the 

top portion of Table 7. The bottom portion shows the impact of these assumptions on the net cost 

of the Transition Scenario. The high-cost efficiency case brings the NPV savings down to $25

billion, while the low-cost case increases the savings to $125 billion. 

Table 7. Results of Efficiency Cost Sensitivities (2010$)

Energy Efficiency Cost Assumptions ($/MWh)

2020 2030 2040 2050

High EE Case $47 $60 $75 $90

Base EE Case $47 $52 $60 $70

Low EE Case $47 $47 $50 $50

Annual Net Cost of Transition Scenario (billion$) NPV (billion$)

High EE Case ($16) ($3) $20 ($4) ($25)

Base EE Case ($16) ($8) $9 ($18) ($84)

Low EE Case ($16) ($12) $2 ($29) ($125)

We evaluated the impact of fuel prices by raising and lowering coal and gas prices (separately) by 

20% relative to the base case prices. Prices reach the 20% difference by 2020 and remain there 

for the remainder of the study period. As seen in Table 8, higher gas prices result in higher net 

savings from the Transition Scenario, because less gas is burned in this scenario than under BAU. 

The higher assumed gas prices increase NPV savings to $103 billion, while lower gas prices 

reduce NPV savings to $63 billion.

Table 8. Results of Gas Price Sensitivities (2010$)

Annual Net Cost of Transition Scenario (billion) NPV

2020 2030 2040 2050 (billion$)

High Gas Case ($16) ($10) $6 ($24) ($103)

Base Gas Case ($16) ($8) $9 ($18) ($84)

Low Gas Case ($15) ($7) $12 ($11) ($63)

As shown in Table 9, higher coal prices increase the savings provided by the Transition Scenario, 

and lower coal prices decrease them.

Table 9. Results of Coal Price Sensitivities (2010$)

Annual Net Cost of Transition Scenario (billion) NPV

2020 2030 2040 2050 (billion$)

High Coal Case ($17) ($14) ($0) ($31) ($144)

Base Coal Case ($16) ($8) $9 ($18) ($84)

Low Coal Case ($14) ($3) $18 ($5) ($23)

Table 10 shows the input assumptions and results of our analysis of PV costs. The top portion of 

the table shows the installed costs used in our main analysis and in each sensitivity. Installed 
Beyond Business as Usual ▪ 31

costs are shown because levelized energy costs vary across regions based on the solar resource. 

The low PV price case has the cost of large PV projects hitting $1.00 per WDC ($1.20 per WAC) 

sometime between 2030 and 2040. This is ten years earlier than in the base case but ten to fifteen

years later than the current goal of the DOE’s SunShot program. The cost of large projects does 

not fall further after reaching $1.20 per WAC. The costs of commercial and residential projects 

continue to fall over the entire period, though at a diminishing rate, and they do not reach $1.20 

per WAC. The high PV cost case has costs falling more slowly from 2011 levels, and large systems 

do not reach $1.20 per WAC during the study period.

These two sensitivity analyses are not symmetric around the base case. In the later decades, the 

high cost case is farther from base case than the low cost case. This is because in both the base 

case and the low cost case, we assume that PV technology hits maturity and diminishing cost 

reductions per year during the study period. It simply hits this point sooner in the low cost case. 

Thus, this assumed point of maturity, at $1.20 per WAC for large projects, provides a lower bound 

for the low cost case, while the high cost case is not similarly constrained. 

The bottom portion of Table 10 shows the impact of the two PV cost sensitivities on the total net 

cost of the Transition Scenario. In the high-cost PV case the NPV savings fall to $21 billion, and in 

the low-cost case savings rise to $136 billion.

Table 10. Inputs and Results of PV Cost Sensitivities (2010$)

Adjustments to PV Capital Costs for Sensitivity Analyses

2020 2030 2040 2050

Large Installations ($/WAC)

High PV Case $3.55 $2.65 $2.06 $1.56

Base PV Case $3.30 $2.30 $1.58 $1.20

Low PV Case $3.05 $1.95 $1.20 $1.20

Commercial Installations ($/WAC)

High PV Case $4.60 $3.68 $3.25 $2.85

Base PV Case $4.30 $3.20 $2.50 $2.20

Low PV Case $4.00 $2.72 $1.76 $1.70

Residential Installations ($/WAC)

High PV Case $5.55 $4.71 $4.23 $3.77

Base PV Case $5.30 $4.10 $3.25 $2.90

Low PV Case $5.05 $3.50 $2.30 $2.24

Annual Net Cost of Transition Scenario (billion$) NPV (billion$)

High PV Case ($15) ($5) $20 $3 ($21)

Base PV Case ($16) ($8) $9 ($18) ($84)

Low PV Case ($16) ($11) ($1) ($32) ($136)

Finally, Table 11 shows the impact on net costs of different assumptions about the cost of energy 

from new nuclear plants. In all cases, the trend of increasing energy costs from new nuclear plants 

is the result of increasing fuel prices. We hold the installed cost of new nuclear plants constant

through the study period. The low nuclear cost case uses the cost of energy derived from the AEO 

2011 cost assumptions ($114 per MWh). The high-cost case is calculated using an installed cost 

of $8,000 per kW. Because the new nuclear plants in the BAU scenario are added early, and only 

6.2 GW are added, the effect of these changed assumptions is pronounced in the early years of 
Beyond Business as Usual ▪ 32

the study period and it diminishes over time. The high nuclear costs increase the NPV savings to 

$100 billion, and the low costs decrease the NPV savings to $70 billion.

Table 11. Results of New Nuclear Cost Sensitivities (2010$)

New Nuclear Cost Assumptions ($/MWh)

2020 2030 2040 2050

High Nuclear Cost $178 $180 $182 $183

Base Nuclear Cost $143 $145 $146 $148

Low Nuclear Cost $114 $116 $118 $119

Annual Net Cost of Transition Scenario (billion$) NPV (billion$)

High Nuclear Cost ($17) ($10) $7 ($18) ($100)

Base Nuclear Cost ($16) ($8) $9 ($18) ($84)

Low Nuclear Cost ($14) ($7) $11 ($18) ($70)
Beyond Business as Usual ▪ 33

Appendix A: Technology Cost and Performance

Assumptions

The goal of our cost analysis is to compare the cost of generating electricity under BAU to the 

same cost in the Transition Scenario. We do not include the effects of direct subsidies such as 

grants and tax credits in the cost of resources. Consumers pay some costs through electricity 

rates and pay other costs (subsidies) through tax dollars, but either way they pay the full cost of 

each plant built. So it is important, wherever possible, to include the full cost of each resource. 

However, it is very difficult to remove the effect of indirect subsidies from the cost of new plants. 

These subsidies include R&D funding; subsidies for exploration, drilling, and mining; federal loan 

guarantees; and externalized costs of pollution. We have not attempted to remove these subsidies

from our quantitative analysis, but they should be borne in mind as we compare these two 

scenarios.

We use cost assumptions from the AEO 2011 for all existing technologies. We use the AEO for 

many new technologies as well; however for PV, wind, and nuclear plants we have used 

assumptions based on other sources, as discussed below. Because of the considerable changes 

in PV costs and pricing over the past 24 months, we have been careful to base our PV 

assumptions on the most current information possible. In addition, given the wide range of 

possible PV price trajectories over the next several decades, we present a sensitivity analysis

around our PV cost assumptions.

Plant cost and performance assumptions change in each decade of the study period based on: 

technology improvements for immature technologies, fuel costs, and increasing O&M costs to 

represent aging equipment. All costs are reported in 2010 dollars. Dollars have been converted 

from source documents where necessary.

A. Fuel Costs

In both the BAU and Transition Scenario we use the fuel costs from the AEO 2011, shown in 

Table 12. These figures have been adjusted from 2009 dollars in the AEO documentation.

Table 12. AEO 2011 Fuel Prices (2010$/mmBtu)

2010 2020 2030 2040 2050

Coal $2.29 $2.17 $2.35 $2.51 $2.69

Natural Gas $5.13 $5.07 $6.28 $7.47 $8.82

Distillate Fuel Oil $16.57 $20.01 $22.57 $23.98 $25.83

Residual Fuel Oil $11.56 $14.93 $17.06 $17.13 $17.61

Biomass $1.93 $2.58 $3.04 $3.02 $2.95

Nuclear $0.76 $0.83 $1.03 $1.18 $1.36

B. Existing Power Plants

We include in our cost analysis all existing generating units (existing in 2010) that operate 

differently under BAU versus the Transition Scenario. A unit might operate differently in the two 

scenarios because it is retired in the Transition Scenario or because it produces more or less 
Beyond Business as Usual ▪ 34

energy at some point. We do not analyze the costs of existing resources that operate in exactly 

the same way in the two scenarios, because our cost analysis focuses on the net cost of the 

Transition Scenario. For resources that operate in exactly the same way, the net cost in the 

Transition Scenario is zero. We analyze the costs of the following existing resources:

 Coal-fired plants,

 Gas-fired combined-cycle plants,

 Gas- and oil-fired combustion turbines,

 Gas- and oil-fired steam plants, and

 Nuclear plants.

To cost out energy from existing plants we use a fleet average approach. For existing coal units, 

combined cycle units, and combustion turbines we use the average capacity factor of the units in 

each region to calculate the average levelized costs in each region. For nuclear units and oil and 

gas steam units, we use a single capacity factor to calculate levelized costs that are applied to all 

plants nationwide. Fleet average heat rates for each plant type were developed based on AEO 

data and information reported to EIA and EPA.

EIA has developed assumptions for capital additions at fossil and nuclear plants based on 

historical data. For a given plant type, different costs are applied to units 30 years old or younger

versus units over 30. Synapse has also reviewed data reported to FERC on capital additions and

found the data for different plant types to be similar to the AEO assumptions. Therefore, we have 

used the AEO capital additions for fossil and nuclear units. 

It is not clear from the AEO documentation how fixed and variable O&M costs increase as a given

plant ages. We have treated O&M in the same way as capital additions, developing separate cost 

assumptions for units 30 years old or younger and units over 30. We apply these two cost factors 

to each regional fleet based on generating unit on-line dates.

The tables below show the cost assumptions for each existing plant type included in our cost 

analysis. Table 13 shows the input assumptions for existing coal-fired units. Again, regional 

average levelized costs were calculated using regional average capacity factors from the AEO. 

For the year 2010, these capacity factors range from 53% to 85%. As seen in Table 13, the 2010 

levelized cost of energy from existing coal units ranges from $38 to $43 per MWh in different 

regions.

Table 13. Assumptions for Existing Coal-Fired Units (2010$)

Assumption Value Source

Fixed O&M ($/kW-yr) $35.97 AEO 2011

Over 30 Fixed O&M ($/kW-yr) $48.00 Synapse

Variable O&M ($/MWh) $4.25 AEO 2011

Over 30 Variable O&M ($/MWh) $4.68 Synapse

Capital Additions ($/kW-yr) $16.18 AEO 2011

Over 30 Capital Additions ($/kW-yr) $22.25 AEO 2011

Heat Rate (Btu/kWh) 10,500 Synapse

Range of 2010 Energy Costs ($/MWh) $38-$43 Calculated

AEO data have been converted to 2010 dollars where necessary.
Beyond Business as Usual ▪ 35

The 2010 levelized cost of energy from existing combined-cycle units ranges from $46 to $53 per 

MWh, based on capacity factors ranging from 17% to 51%. The AEO does not appear to include 

capital additions for CCCTs, even units over 30 years old. We include capital additions of $15.00 

per kW-year to units over 30 years old.

Table 14. Assumptions for Existing Gas-Fired CCCTs (2010$)

Assumption Value Source

Fixed O&M ($/kW-yr) $14.62 AEO 2011

Over 30 Fixed O&M ($/kW-yr) $16.08 Synapse

Variable O&M ($/MWh) $3.11 AEO 2011

Over 30 Variable O&M ($/MWh) $3.42 Synapse

Capital Additions ($/kW-yr) $0.00 Synapse

Over 30 Capital Additions ($/kW-yr) $15.00 Synapse

Heat Rate (Btu/kWh) 7,700 Synapse

Range of 2010 Energy Costs ($/MWh) $46-$53 Calculated

AEO data have been converted to 2010 dollars where necessary.

As seen in Table 15, the 2010 levelized cost of energy from existing combustion turbines ranges 

from $88 to $235 per MWh, based on capacity factors ranging from 0.6% to 21%.

Table 15. Assumptions for Existing Gas- and Oil-Fired Combustion Turbines (2010$)

AEO data have been converted to 2010 dollars where necessary.

For oil and gas steam units, we use the fixed and variable O&M data for coal units from the AEO. 

The costs of capital additions, also from the AEO, are specific to gas and oil steam units. As 

noted, for oil and gas steam units we use single capacity factor and heat rate assumptions to 

calculate a levelized energy cost that is applied to all units nationwide. The 2010 levelized cost of 

energy from gas steam plants is $72 per MWh, and the cost from oil steam plants is $143.

Assumption Value Source

Fixed O&M ($/kW-yr) $6.98 AEO 2011

Over 30 Fixed O&M ($/kW-yr) $7.68 Synapse

Variable O&M ($/MWh) $14.70 AEO 2011

Over 30 Variable O&M ($/MWh) $16.17 Synapse

Capital Additions ($/kW-yr) $0.00 AEO 2011

Over 30 Capital Additions ($/kW-yr) $0.00 AEO 2011

Heat Rate (Btu/kWh) 13,500 Synapse

Range of 2010 Energy Costs ($/MWh) $88-$235 Calculated
Beyond Business as Usual ▪ 36

Table 16. Assumptions for Existing Oil- and Gas-Fired Steam Plants (2010$)

Assumption Value Source

Fixed O&M ($/kW-yr) $35.97 AEO 2011

Over 30 Fixed O&M ($/kW-yr) $48.00 Synapse

Variable O&M ($/MWh) $4.25 AEO 2011

Over 30 Variable O&M ($/MWh) $4.68 Synapse

Capital Additions ($/kW-yr) $8.09 AEO 2011

Over 30 Capital Additions ($/kW-yr) $14.16 AEO 2011

2010 Energy Cost for Gas ($/MWh) $72 Calculated

2010 Energy Costs for Oil ($/MWh) $143 Calculated

AEO data have been converted to 2010 dollars where necessary.

As with oil and gas steam plants, single capacity factor and heat rate assumptions are used to 

estimate the levelized cost of nuclear energy at all plants nationwide. For nuclear plants we use a 

capacity factor of 90%, and the levelized cost of energy from existing nuclear units is $27 per 

MWh.

Table 17. Assumptions for Existing Nuclear Plants (2010$)

Assumption Value Source

Fixed O&M ($/kW-yr) $88.75 AEO 2011

Over 30 Fixed O&M ($/kW-yr) $100.00 Synapse

Variable O&M ($/MWh) $2.04 AEO 2011

Over 30 Variable O&M ($/MWh) $2.24 Synapse

Capital Additions ($/kW-yr) $21.24 AEO 2011

Over 30 Capital Additions ($/kW-yr) $53.61 AEO 2011

Heat Rate (Btu/kWh) 10,700 Synapse

2010 Nuclear Energy Cost ($/MWh) $27 Calculated

AEO data have been converted to 2010 dollars where necessary.

In addition to these costs, we include capital costs of $3,000 per kW at all nuclear units that 

operate longer than 60 years (the period covered by the original license and a 20-year extension). 

This cost represents the substantial rebuilding of the unit that we assume will be necessary to 

obtain a new operating license. 

Little work is publicly available about the costs that would be associated with relicensing a 60-

year-old nuclear facility. The $3,000 per kW figure is slightly less than half of the cost we assume 

for a new “greenfield” nuclear unit. This assumption, however, has a relatively small impact on the 

overall results, because most units are assumed to operate past 60 years in both BAU and the 

Transition Scenario. Only 19 units are retired in the Transition Scenario before they reach age 60.

To discern the impact of this assumption, we evaluated scenarios with the cost of a 60-year 

rebuild at $1,000 per kW and $5,000 per kW. Assuming $1,000 per kW decreases the NPV 

savings of the Transition Scenario from $74 billion to $61 billion. Assuming $5,000 per kW 

increases the net savings to $86 billion.
Beyond Business as Usual ▪ 37

C. New Power Plants

As in the AEO, we calculate levelized costs for all new technologies using a fixed charge rate to 

determine the annual carrying costs of capitalized equipment. However, the AEO includes interest 

during construction and other factors in its fixed charge rates, while we use these rates simply to 

annualize capital costs. Our fixed charge rates were developed using a cost of capital 

representative of a roughly equal mix of utility, merchant, and public projects. Our base fixed 

charge rate is 9.5%, and this is applied to the lowest risk projects (e.g., onshore wind, solar and 

geothermal). As in the AEO, we add a risk premium to new plants that produce CO2, and we also 

add risk premiums to nuclear, biomass, and offshore wind. In sizing these risk premiums, we are 

guided by the levelized costs reported for the AEO, by other credible estimates of new plant costs,

and by our own research. 

For each technology we compare our cost assumptions to four recent estimates of new project 

costs. The estimates labeled “E3 Analytics” were developed by this firm for the Western Electricity 

Coordinating Council’s (WECC) Transmission Expansion Planning Policy Committee (E3 

Analytics, 2010). Data labeled “Lazard” were released in May 2010 by the Lazard Company, a 

global investment bank (Lazard, 2010). Data labeled “EIA” are from the AEO 2011 assumptions 

(EIA, 2010), and data labeled “Black & Veatch” are from that company’s work for California’s 

Renewable Energy Transmission Initiative and for the company’s “Gencost” model (Black & 

Veatch, 2011). Data labeled “BBAU” are the assumptions used in this study. In addition, for certain 

technologies we compare estimates from these four sources to information from actual recent 

projects.

Note that some of the sources report “overnight costs,” which do not include interest during 

construction, while others report “installed costs,” which do include this interest. 

Coal-Fired Plants

The overnight cost of new coal-fired plants in AEO 2011 is $3,167 per kW for a single unit plant 

and $2,844 for a dual unit plant. We use the AEO data for a single unit plant. As seen in Table 18, 

this figure is roughly consistent with Black & Veatch’s range, slightly higher than the E3 Analytics’

assumption, and at the lower end of Lazard’s range.

Note that all the estimates in Table 18 are for plants that burn coal directly. No coal gasification 

plants are added under either BAU or the Transition Scenario.
Beyond Business as Usual ▪ 38

Table 18. Comparison of Cost Estimates for New Coal-Fired Units (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $3,167 $3,167

Installed Cost ($/kW) $3,793 $3,035-$8,497 $3,000-$4,000 $4,196

Fixed Charge Rate (%) 13%

FOM ($/kW-yr) $50.58 $20.63-$31.96 $35.97 $35.97

VOM ($/MWh) $3.03 $2.02-$5.97 $4.25 $4.25

Capital Additions ($/kW-yr) $16.18 $16.18

Heat Rate (Btu/kWh) 8,960-12,000 8,800 8,800

Capacity Factor (%) 87% 93% 85% 70% to 90% 85%

Fuel Cost ($/mmBtu) $2.53 $2.15 $2.15

Energy Cost ($/MWh) $70-$154 $110 $86-$115 $105

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

For new coal we assume a construction period of 5 years and a construction loan at 13%. Using a 

capital recovery factor of 13%, we get a levelized cost of energy of $105 per MWh for the period 

2011-20. We report levelized costs here using the 2016 fuel price to be consistent with EIA 2010.

All new coal-fired plants operate at an 85% capacity factor.

Combined Cycle Combustion Turbines (CCCT)

Table 19 compares the estimates for new CCCTs. For gas-fired combined cycle units we use the 

AEO cost assumptions for an advanced unit. We assume a construction period of 3 years and a 

construction loan at 10%. Table 20 shows our levelized costs with a capacity factor of 60%. The 

cost of energy is calculated with the 2016 fuel price to be consistent with EIA 2010. The capacity 

factors of new CCCTs in the Transition Scenario are driven by the need for energy versus 

capacity in each region.

Table 19. Comparison of Cost Estimates for New Gas-Fired Combined Cycle Plants (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $1,003 $1,003

Installed Cost ($/kW) $1,315 $968-$1,184 $1,000-$1,600 $1,153

Fixed Charge Rate (%) 11%

FOM ($/kW-yr) $8.09 $5.56-$6.27 $14.62 $14.62

VOM ($/MWh) $4.96 $2.02-$3.54 $3.11 $3.11

Capital Additions ($/kW-yr) $0.00 $0.00

Heat Rate (Btu/kWh) 7,000 6,800-7,220 6,430 6,430

Capacity Factor (%) 90% 40%-93% 87% 70%-90% 60%

Fuel Cost ($/mmBtu) $6.07 $4.76 $4.76

Energy Cost ($/MWh) $68-$97 $64 $95-$109 $64

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

Combustion Turbines

For gas-fired combustion turbines we use the AEO cost assumptions for an 85 MW unit. We 

assume no interest during construction. Table 20 shows costs with a capacity factor of 8%. The 

cost of energy is calculated with the 2016 fuel price to be consistent with EIA 2010. The capacity 
Beyond Business as Usual ▪ 39

factors of new CTs in the Transition Scenario are driven by the need for energy versus capacity in 

each region.

Table 20. Comparison of Cost Estimates for New Gas-Fired Combustion Turbines (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $974 $974

Installed Cost ($/kW) $1,113 $809-$1,012 $600-$900 $974

Fixed Charge Rate (%) 11%

FOM ($/kW-yr) $14.16 $6.88-$27.31 $6.98 $6.98

VOM ($/MWh) $5.06 $4.75-$28.32 $14.70 $14.70

Heat Rate (Btu/kWh) 9,300 10,200-10,830 10,850 10,850

Capacity Factor (%) 10% 30% 5%-25% 8%

Fuel Cost ($/mmBtu) $6.07 $4.76 $4.76

Energy Cost ($/MWh) $234-$260 $125 $167-$361 $236

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

Nuclear Plants

The new nuclear projects under development continue to struggle with delays and cost overruns.

 Progress Energy’s two-reactor project in Levy County, Florida was originally scheduled to 

be online by 2016 at a cost of $17 billion. The latest estimate is an online date of 2021

and a cost of $22.5 billion, or $10,000 per kW.

 Finland’s Olkiluoto project was originally scheduled to be online in 2009 for $4.3 billion. It 

is now scheduled to be operating in 2013 at a cost of $8.6 billion, or $5,400 per kW.

 In late 2010, Constellation Energy scrapped plans for a new reactor at Calvert Cliffs after 

finding terms the U.S. Government offered for a loan guarantee unacceptable.

 The effort to develop two new reactors at the South Texas plant was scrapped in April 

2011. The project was a partnership including Toshiba, and the disaster at Fukushima 

was cited as the key reason for the decision. However, cost escalation had put the project 

in a precarious position. Cost estimates had risen to $18 billion, or $6,700 per kW, and 

another partner, CPS Energy, had already reduced its share from 50% to 7.6%.

 To date one U.S. nuclear project has received a federal loan guarantee, the Vogtle project 

in Georgia. The developer’s current estimate for this project is $14 billion, or roughly 

$6,400 per kW.

The cost estimates at some other projects remain lower. The latest from the expansion of the 

Sumner plant in South Carolina is $9.1 billion or $4,100 per kW. However, the escalating costs of

the other projects cast some doubt on this estimate. Florida Power and Light has estimated the 

cost of a one-year delay for a nuclear project to be between $800 million and $1.2 billion (Scroggs, 

2007).

Table 21 compares several estimates of new nuclear plant costs. The installed costs from AEO 

2011 are the lowest of them – even below the low end of Lazard’s considerable range. We use an 

installed cost of $6,584, along with the AEO assumptions for O&M and capital additions. With a 
Beyond Business as Usual ▪ 40

90% capacity factor, these assumptions yield a levelized energy cost of $142 per MWh. This is 

within the range estimated by Black & Veatch, but well above the AEO energy cost. It is worth 

noting that Lazard’s range of energy costs appear quite low given the installed costs assumed. We 

conclude that there is either a subsidy included in the calculation of energy costs or there is an 

error.

Table 21. Comparison of Cost Estimates for New Nuclear Plants (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $5,335 $6,000

Installed Cost ($/kW) $7,586 $5,447-$8,293 $6,000-$8000 $6,584

Fixed Charge Rate (%) 14%

FOM ($/kW-yr) $71.00 $12.95 $88.75 $88.75

VOM ($/MWh) $6.07 $0.00 $2.04 $2.04

Capital Additions ($/kW-yr) $21.24 $21.24

Heat Rate (Btu/kWh) 10,400 10,450 10,450

Capacity Factor (%) 85% 90% 90% 70%-90% 90%

Fuel Cost ($/mmBtu) $0.51 $0.81 $0.81

Energy Cost ($/MWh) $78-$115 $115 $100-$158 $142

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

The fact that no “next-generation” nuclear project has been successfully completed makes any 

estimate of costs highly uncertain, and we believe that costs could ultimately be significantly 

higher than our assumption here. For example, the current estimates for two of the projects 

discussed above (Progress Energy and South Texas) are above our new nuclear costs, and 

another of the estimates (Vogtle) is essentially at our assumed cost. We use this assumption for 

new nuclear in order to be somewhat conservative in assessing the savings from not building new 

nuclear plants.

Wind Plants

The cost of onshore, utility-scale wind projects reached very low levels in the middle part of the 

last decade, with total installed costs well below $2,000 per kW. However, strong global demand 

increased turbine prices late in the decade, and prices have only recently begun to come down. 

Table 22 compares recent estimates of wind costs. The Black & Veatch estimate takes into 

account the recent softening in turbine prices; the company’s May 2011 estimate for the RETI 

process in California includes an installed cost range of $2,000 to $2,500 per kW, down from their 

assumptions for Phases I and II of that project. We believe that the other estimates, from 2010, do 

not take this recent trend into account, and therefore we use an installed cost at the midpoint of 

the Black & Veatch range. We use the AEO 2011 O&M costs. 

Onshore wind is a fairly mature technology; however, there are likely to be moderate 

improvements over the next several decades. In particular, we expect onshore wind projects to 

continue to benefit from offshore R&D, leading to small cost reductions and capacity factor 

improvements. We reduce installed costs by 2% for the second decade of the study and another 

2% for the third decade. We do not reduce installed wind costs after that.
Beyond Business as Usual ▪ 41

Table 22. Comparison of Cost Estimates for Onshore Wind Projects (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $2,438 $2,250

Installed Cost ($/kW) $2,377 $2,276-$2,630 $2,000-$2,500 $2,475

Fixed Charge Rate (%) 9.5%

FOM ($/kW-yr) $50.58 $61.00 $28.07 $28.07

VOM ($/MWh) $0.00 $0.00 $0.00 $0.00

Capacity Factor (%) 33% 30%-40% 34% 32%-42% 33%-41%

Energy Cost ($/MWh) $86-$131 $97 $75-$115 $74-$93

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

For offshore wind we assume an installed cost of $5,938, in line with E3 Analytics and higher than 

Lazard’s range, but slightly lower than AEO 2011. We use the AEO O&M costs. (We have not 

seen offshore wind estimates from Black & Veatch.)

Table 23. Comparison of Cost Estimates for New Offshore Wind Projects (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 BBAU

Overnight Cost ($/kW) $5,975 $5,600

Installed Cost ($/kW) $6,069 $3,793-$5,058 $5,938

Fixed Charge Rate (%) 10.5%

FOM ($/kW-yr) $91.00 $61.00-$101.00 $53.33 $53.33

VOM ($/MWh) $0.00 $13.15-18.21 $0.00 $0.00

Capacity Factor (%) 32%-45% 34% 44%

Energy Cost ($/MWh) $134-$258 $247 $181

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

We have revised our wind capacity factors downward significantly since the 2010 study. In that 

study we used data developed by Black & Veatch for the DOE’s 20% Wind by 2030 study (US 

DOE, 2008). The capacity factors used in that study are significantly above the factors used in 

most other studies, including the four studies cited in Table 22. The capacity factors we use here

are based on data from the Eastern Wind Integration and Transmission Study (EnerNex, 2010) 

and other regional data sources. Figure 14 shows EnerNex’s estimated capacity factors at 

developable U.S. wind sites as a function of cumulative capacity. 
Beyond Business as Usual ▪ 42

Figure 14. Capacity Factor Data from EnerNex 2010

Table 24 shows the capacity factors we apply to onshore wind plants in both the BAU and 

Transition Scenario. These capacity factors increase by two percentage points between the first 

and second decades. After 2030, capacity factors improve by half a percentage point per decade. 

Table 24. Capacity Factors Used for Wind Projects

2011-20 2021-30 2031-40 2041-50

Arizona/New Mexico 37.0% 39.0% 39.5% 40.0%

Rocky Mountains 37.0% 39.0% 39.5% 40.0%

Northwest 37.0% 39.0% 39.5% 40.0%

California 33.0% 35.0% 35.5% 36.0%

Northeast 34.0% 36.0% 36.5% 37.0%

Southeast 33.0% 35.0% 35.5% 36.0%

Eastern Midwest 34.0% 36.0% 36.5% 37.0%

Western Midwest 41.0% 43.0% 43.5% 44.0%

South Central 41.0% 43.0% 43.5% 44.0%

Texas 38.0% 40.0% 40.5% 41.0%

All Offshore 44.0% 46.0% 46.5% 47.0%

Photovoltaics

The AEO 2011 assumption for the capital cost of large PV installed in 2016 is $4.75 per WAC, and 

the assumption for small PV is $6.05 per WAC. Based on other data, we believe that these figures 

overstate the near-term cost of PV. Large project costs in the AEO fall to roughly $3.05 per WAC in 

2035, and we believe this forecast is also significantly too high. As one point of comparison, a 

2010 white paper written by a different office within the U.S. DOE projects that “with current 

market trends and cost reduction opportunities, utility-scale system costs are expected to reach 
Beyond Business as Usual ▪ 43

$2.20 per WDC by 2016” (U.S. DOE 2010, p. 1). This is equivalent to roughly $2.65 per WAC. Our 

PV price forecast, laid out below, is more conservative than this forecast; however, the difference 

in these two forecasts from the same agency underscores the range of uncertainty around longterm PV prices. Given this uncertainty, we examine the impact of high and low PV price scenarios 

on the results of this study.

The installed cost of large (ground mounted) PV systems has been falling since late 2009. In 

2010, prices bid for large PV projects (≥5 MW) in the U.S. were in the range of $4.00 to $4.50 per 

WAC. An offer by the Sacramento Municipality Utility District to buy renewable energy resulted in 

bids from projects totaling 100 MW at a price in the range of $140 per MWh. In 2011, an offer by 

Southern California Edison resulted in bids for 250 MW of PV at a price in the range of $130 per 

MWh. Factoring in the 30% grant or investment tax credit (ITC) available to these projects, these 

levelized energy costs are consistent with installed costs in the range of $4.00 to $4.50 per WAC. 

The 2010 energy bids cited above are also roughly consistent with the estimates by the U.S. DOE, 

Black & Veatch, and Lazard that came out in mid-2010 and 2011. E3 Analytics’ estimate, in its 

January 2010 study for WECC, was between $4.50 to $5.70 per WAC, considerably higher than the 

other three sources. In May of 2011, however, WECC revised this estimate to a range of $4.00 to 

$4.70 per WAC, more in line with the other estimates (WECC, 2011). The AEO 2011 assumption 

(cited as EIA 2010 in Table 25) is above all the other estimates.

Table 25. Comparison of Installed Cost Estimates for Large PV Projects (2010$)

WECC 2011 Lazard 2010 EIA 2010 US DOE 

2010

Black & Veatch 

2011

$ per WDC $3.50 - $3.75 $3.04

$ per WAC $4.00-$4.70 $4.22 - $4.52 $4.75 $4.09 $3.60 - $4.00

As yet there is little publicly available information on 2011 project costs, but module price data 

suggests that costs have continued to fall.5 Historically, modules have been the largest component 

of project costs, representing about half of total installed costs. Trends in module prices show 

significant declines through 2010 and 2011. At the end of 2010, both Barclay’s Capital and 

Macquarie Capital projected module prices in the range of $1.45 per WDC by the end of 2011. 

However, by July 2011 module prices had fallen faster than these predictions, and at least one 

financial research firm had reduced their fourth-quarter 2011 average module price forecast to 

$1.25 to $1.30 per WDC (Jeffries & Co., 2011). These module prices support anecdotal evidence 

from California suggesting that many spring 2011 bids for large systems were in the range of $120 

per MWh (Shugar 2011, Kirkpatrick 2011). If panel prices continue to fall from summer 2011 

levels, this could put total installed costs on a path to reach DOE’s forecast of $2.20 per WDC by 

2016. 

However, a supply and demand imbalance is clearly driving much of the recent module price 

reductions. A considerable amount of both silicon and module production capacity has been 

added in recent years in response to strong European demand. This demand has been driven 

primarily by subsidies, which are now being reduced. It is likely that a number of module 

 

5 Module manufacturers include audited cost data as part of the information they provide to financial analysts.
Beyond Business as Usual ▪ 44

manufacturers will not survive at current prices and there will be a significant consolidation in the 

market. Therefore, we believe that module prices are not likely to continue falling in the near term 

at the rate they have fallen over the past two years. 

The PV prices used for this study are shown in Table 26. These 2011-20 prices are consistent 

with a scenario in which: a) by 2015 panel prices have fallen to a sustainable $1.20 per WDC

(“sustainable” meaning priced at cost plus margin); and b) BOS cost reductions are not realized as 

fast as panel cost reductions have been realized recently. Our 2011-20 average price is based on 

a panel cost of $1.45 per WAC and BOS costs of $1.85 per WAC. Over the long term, we assume 

that large PV projects achieve DOE’s target of $1.00 per WDC ($1.20 per WAC) sometime between 

2040 and 2050. This is a less aggressive forecast than DOE’s current cost reduction goal ($1.20 

per WAC before 2020); however it is consistent with our efforts to be conservative in assessing the 

costs of phasing out coal-fired electricity. 

Table 26. Assumed Costs of PV Systems (2010$)

2011-2020 2021-2030 2031-2040 2041-2050

Installed Cost ($/WAC)

 Large (≥5 MW) $3.30 $2.30 $1.58 $1.20

 Commercial (@ 1 MW) $4.30 $3.20 $2.50 $2.20

 Residential (≤5 kW) $5.30 $4.10 $3.25 $2.90

Levelized Cost – California ($/MWh)

 Large (≥5 MW) $146 $102 $73 $57

 Commercial (@ 1 MW) $244 $179 $141 $123

 Residential (≤5 kW) $306 $232 $186 $165

Levelized Cost – Northeast ($/MWh)

 Large (≥5 MW) $179 $124 $88 $69

 Commercial (@ 1 MW) $285 $206 $162 $142

 Residential (≤5 kW) $356 $268 $214 $190

Like all costs in this study, these costs do not include direct subsidies. This is important to note 

when comparing these numbers to current market data. For example, pricing for large projects in 

the 2010 California market was in the range of $130 to $140 per kWh with the 30% grant or ITC. 

For our average 2011-20 cost of energy from California projects ($146), we assume significant 

cost reductions from 2010 and we do not include the subsidy. 

Our near-term costs for small systems are based on discussions with companies marketing these 

systems. Current costs for residential scale systems appear to be in the range of $5.70 per WAC

(though these systems are being marketed for far less than this due to subsidies). Current costs 

for commercial scale systems appear to be in the range of $5.00 per WAC.

The capacity factors we use for the 2011-20 period were developed using NREL’s PV Watts tool. 

For large systems, we assume ground mounted, single axis tracking systems, and for residential 

and commercial we assume roof mounted fixed tilt systems. After the first decade, we assume that 

capacity factors increase by 2 percentage points over the study period. We use the same capacity 

factors for commercial and residential PV (labeled “small” in Table 27).
Beyond Business as Usual ▪ 45

Table 27. Capacity Factors Used for PV Projects

2011-20 2021-30 2031-40 2041-50

Large Small Large Small Large Small Large Small

Arizona/New Mexico 32.0% 24.0% 33.0% 25.0% 33.5% 25.5% 34.0% 26.0%

Rocky Mountains 28.0% 22.0% 29.0% 23.0% 29.5% 23.5% 30.0% 24.0%

Northwest 27.0% 21.0% 28.0% 22.0% 28.5% 22.5% 29.0% 23.0%

California 27.0% 21.0% 28.0% 22.0% 28.5% 22.5% 29.0% 23.0%

Northeast 22.0% 18.0% 23.0% 19.0% 23.5% 19.5% 24.0% 20.0%

Southeast 24.0% 19.0% 25.0% 20.0% 25.5% 20.5% 26.0% 21.0%

Eastern Midwest 22.0% 17.0% 23.0% 18.0% 23.5% 18.5% 24.0% 19.0%

Western Midwest 25.0% 19.0% 26.0% 20.0% 26.5% 20.5% 27.0% 21.0%

South Central 27.0% 21.0% 28.0% 22.0% 28.5% 22.5% 29.0% 23.0%

Texas 25.0% 20.0% 26.0% 21.0% 26.5% 21.5% 27.0% 22.0%

We assume the same prices under BAU and in the Transition Scenario, based on the assumption 

that most of the learning and technology development will be driven by global supply and demand 

dynamics. That is, we assume that a scenario with higher PV penetration in the U.S. will not 

create dramatically lower prices than one with much lower penetration. This assumption is likely to 

understate the cost of PV under BAU, as the various parts of the U.S. supply chain would no 

doubt become more competitive and efficient in the Transition Scenario than under BAU.

Direct-Fired Biomass Plants

The four sources we compare are relatively consistent in their estimates for new biomass plants. 

The estimates from E3 Analytics and Lazard are for a stoker boiler, and the AEO estimate is for a 

bubbling fluidized bed boiler. This difference accounts for AEO’s lower heat rate. We use the 

assumptions from the AEO, along with a fixed charge rate of 11.5%. This fixed charge rate is 

based on our research, which indicates that lenders view biomass, with its fuel cost risk, as 

considerably more risky than wind or solar.

Table 28. Comparison of Cost Estimates for New, Direct Fired Biomass Plants (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $3,860 $3,860

Installed Cost ($/kW) $4,299 $3,035-4,046 $3,500-$5,000 $4,362

Fixed Charge Rate (%) 11.5%

FOM ($/kW-yr) $157.00 $96.09 $100.50 $100.50

VOM ($/MWh) $4.05 $15.17 $5.00 $5.00

Heat Rate (Btu/kWh) 14,800 14,500 13,500 13,500

Capacity Factor (%) 85% 85% 83% 70%-90% 83%

Fuel Cost ($/mmBtu) $1.01-$3.34 $2.20 $2.20

Energy Cost ($/MWh) $92-$148 $114 $105-$160 $128

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

Geothermal Plants

For geothermal, we focus only on the resources in the western U.S. that can be developed with 

binary or flash technology. Enhanced geothermal systems, in which fracking is used to create a 
Beyond Business as Usual ▪ 46

usable thermal resource, remain quite expensive, and they are not developed in either the AEO 

2011 or in the Transition Scenario. 

The cost of new conventional geothermal plants is highly site specific and can vary widely. Key 

variables include the depth of the resource, how rocky the soil is, and whether the resource is 

amenable to binary or flash technology. Petty and Porro 2007 provide a supply curve based on 

analysis of many potential sites across the western U.S. This work is useful in that it identifies the 

technology likely to be used at each site. However, Petty and Porro’s estimates of project costs 

are considerably lower than most other sources. Table 29 compares estimates of new geothermal 

plant costs. The assumptions shown for the AEO 2011 are for binary systems. None of the other 

sources identify the technology assessed, but it seems likely that the low end of Lazard’s range is 

binary and the high end flash. 

Our cost assumptions yield levelized costs very close to AEO 2011 and at the low end of Lazard 

and Black & Veatch’s ranges. Note that in both the AEO 2011 and the Transition Scenario, a 

relatively small amount of new geothermal resources is developed for electricity. In the AEO, 5.4 

GW of new capacity is developed by 2050, and in the Transition Scenario 2.7 GW is developed. 

Thus, our cost assumption is intended to reflect the average cost of developing the most attractive 

sites.

Table 29. Comparison of Cost Estimates for New Geothermal Plants (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $4,141 $4,000

Installed Cost ($/kW) $5,563 $4,653-$7,333 $4,000-$6,000 $5,800

Fixed Charge Rate (%) 9.5%

FOM ($/kW-yr) $182.00 $0.00 $84.27 $84.27

VOM ($/MWh) $5.06 $30.34-$40.46 $9.64 $9.64

Capacity Factor (%) 90% 80%-90% 91% 80%-90% 85%

Energy Cost ($/MWh) $96-$160 $101 $87-$160 $96

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.

Concentrating Solar Power (CSP)

For a long time trough technology was the dominant CSP technology. However, the costs of 

trough projects have not come down as hoped, and tower projects now appear to be the 

technology of choice. Several companies are developing tower technology today, including 

BrightSource Energy and SolarReserve. These companies have aggressive cost reduction goals, 

but there is no information available about costs from actual projects. 

Moreover, CSP projects face several significant challenges that PV does not face. First, CSP 

requires large amounts of land, and a better solar resource than PV. This makes it more difficult to 

site CSP near the grid, and adds transmission costs to projects. Second, CSP requires far more 

water than PV. All new CSP projects are likely to be required to use “dry” cooling systems, and 

even projects cooled in this way use much more water than PV projects. Given the global 

momentum behind PV today, and the projected cost reductions, it seems unlikely that CSP will 

play a large role in the country’s energy future. However, it will be important to monitor the CSP 

projects under development today, and revise input assumptions as necessary.
Beyond Business as Usual ▪ 47

Table 30 shows the estimates for new trough projects without storage. The addition of thermal 

energy storage capacity to a CSP plant does not appear to be cost effective today. We use the 

AEO assumptions with a higher capacity factor, consistent with the solar resource in the 

southwestern U.S.

Table 30. Comparison of Cost Estimates for Concentrating Solar Plants (2010$)

E3 Analytics 

2010 Lazard 2010 EIA 2010 Black & Veatch 2011 BBAU

Overnight Cost ($/kW) $4,692 $4,692

Installed Cost ($/kW) $5,350 $5,000-$5,300 $5,300-$5,600 $6,100

Fixed Charge Rate (%) 10.5%

FOM ($/kW-yr) $65.00 $66.00 $64.00 $64.00

VOM ($/MWh) $0.00 $0.00 $0.00 $0.00

Capacity Factor (%) 28% 26%-29% 18% 22%-27% 27%

Energy Cost ($/MWh) $161-$188* $312 $194-$245* $304

*These estimates of energy costs include the effects of the 30% federal grant or ITC, while the others do not.

End-Use Generation using Natural Gas

There are eight different gas-fired technologies available to the NEMS model for end-use 

generation, including two internal combustion engines, five combustion turbines, and a combined 

cycle system. We represent all end-use gas-fired generation with the characteristics of the 

equipment selected most often by the model in the AEO 2011: a 10-MW combustion turbine. The 

installed cost of this equipment is $1,090 per kW, and this cost is quite close to the weighted 

average of the gas-fired CHP technologies selected by the model. We also use the AEO heat rate 

(10,945 Btu/kWh) and O&M assumptions for this turbine. To estimate the cost of electricity and 

gas used for electricity generation, we allocate 40% of the costs and fuel use to electricity and 

60% to steam. With the 2016 gas price of $4.76 per mmBtu, this yields a levelized cost of 

electricity of $35 per MWh.

D. Energy Efficiency 

Table 31 compares the results of several recent energy efficiency potential studies. These studies 

estimate the “achievable potential” over the indicated study period. Achievable potential is a 

subset of economic potential. Economic potential typically includes all technically viable energy 

efficiency measures below the avoided cost of electricity. Achievable potential further screens the 

economic potential based on policy, infrastructure, funding, and consumer response limitations. 

Table 31 shows the achievable potential divided by the total sales forecast over the study period. 

For example, in the first row of the table, GDS estimates that forecasted residential electricity 

sales in 2031 could be reduced by 34% with achievable energy efficiency measures. Note that all 

of these studies factor into their sales forecasts the lighting standards established in the Energy 

Independence and Security Act (EISA) of 2007. That is, the potential savings estimated are in 

addition to the savings associated with that standard. This is important, because the AEO 2011 

Reference Case also includes the effects of that standard. 
Beyond Business as Usual ▪ 48

Table 31. Comparison of Efficiency Potential Studies

Author State/region Analysis Period Period

(yrs.) Sector

Achievable 

Potential over 

Sales Forecast

GDS 2011 VT 2012 - 2031 20 RES 34%

GDS 2011 VT 2012 - 2031 20 C&I 19%

GDS 2011 VT 2012 - 2031 20 Combined 25%

VEIC 2011 VT 2012 - 2031 20 RES 37%

VEIC 2011 VT 2012 - 2031 20 C&I 31%

VEIC 2011 VT 2012 - 2031 20 Combined 33%

KEMA 2010 CT 2009 - 2018 10 RES 27%

KEMA 2010 CT 2009 - 2018 10 C&I 34%

KEMA 2010 CT 2009 - 2018 10 Combined 31%

NWPCC 2010 Northwest by 2030 20 All 27%

ACEEE 2011 AR 2009 - 2025 17 All 22%

ACEEE 2009a PA 2008 - 2025 18 All 18%

McKinsey 2009 US 2009 - 2020 20 RES 22%

McKinsey 2009 US 2009 - 2020 20 C&I 26%

Average of all studies

RES 30%

C&I 27%

Combined 26%

A key difference in these studies is in their treatment of new technologies. Some efficiency 

potential studies, including the two ACEEE studies cited in Table 31, hold technology constant. All 

of the other studies in the table factor in emerging technologies and/or assume technology 

improvement over time, and these studies found significant additional potential in lighting, primarily 

with emerging LED lighting. This difference in assumptions explains much of the difference in 

estimated potential between the ACEEE studies and the other studies.

For the Transition Scenario we assume that more aggressive efficiency programs nationwide 

reduce electricity use by 33.5% below BAU levels by 2050. Compared to the achievable potentials 

listed in Table 31 – in the range of 18% to 33% over 20 years or less – this is not a particularly 

aggressive assumption. Clearly, the technology will be available over the 40-year period to 

achieve this. However, there is wide variation among the states today in terms of the rate at which 

efficiency opportunities are being captured, and getting the entire country up to the level of the 

most aggressive states today would require a strong national commitment.

Another metric often used to measure efficiency progress is savings as a percentage of the 

previous year’s sales. In the Transition Scenario, we assume that by 2020 the entire country is 

saving energy each year equal to 2% of the previous year’s sales. Several years ago, this seemed 

like an aggressive target, as only a few utilities nationwide were capturing savings at this level. 
Beyond Business as Usual ▪ 49

Today, however, a broad range of states and utilities have established targets or mandates that 

will result in savings of at least 2% of the previous year’s sales.

6

The cost of saved energy from utility and third party efficiency programs has been well below the 

cost of new supply-side resources for some time. In 2009, ACEEE reviewed the cost of saved 

energy in utility and third party programs from fourteen leading states and concluded that average 

“utility costs” ranged from ¢1.5 to ¢3.4 per kWh, an average value of ¢2.5 per kWh (ACEEE 

2009b). The study also found that the utility typically bears about 55% of the total energy efficiency 

cost, and customers bear about 45%. This implies that the total cost of energy efficiency 

measures, including participants’ costs, is around ¢4.5 per kWh.

Another study, summarized in Figure 15, compares a number of efficiency program cost estimates 

from states with very aggressive programs (Synapse 2008). The average is ¢2.6 per kWh 

(adjusted to $2010). Again, this is the utility cost only, so total estimated costs would be in the 

range of ¢4.7 per kWh (again adjusted to $2010).

Figure 15. Comparison of Utility Program Efficiency Costs from Synapse 2008

The data in Figure 15 also suggest that there are economies of scale associated with more 

aggressive efficiency efforts: the highest cost savings per kWh came from programs achieving 

smaller overall savings, and the lowest cost savings came from the most aggressive programs. 

 

6

Note that savings equal to 2% of the previous year’s sales do not reduce load by 2% per year. While these 

efficiency programs are operating, load is growing due to new buildings and increased plug loads in existing 

buildings. So if load were growing at 2% per year, then capturing efficiency savings of 2% per year would result in 

zero net load growth. If load were growing at 1% per year, these savings would result in load reductions of roughly 

1% per year.
Beyond Business as Usual ▪ 50

While both the Synapse and ACEEE studies are backward looking, the data compiled for Vermont 

by GDS show that a considerable amount of low-cost savings remain even in a state that has 

been aggressively pursuing efficiency. Figure 16 shows the energy efficiency supply curve for the 

Vermont residential sector from GDS 2011. The cost of saved energy ranges from close to zero to 

nearly $1.00 per kWh, but the majority of the savings are under ¢10 per kWh. As shown in Table 

31 above, this study estimated an achievable potential for the residential sector of 34% of 

forecasted sales by 2031. The weighted average cost of achieving this potential is about ¢5.5 per 

kWh saved (2010$). For the commercial sector, the weighted average cost is ¢2.5 per kWh 

(2010$) to capture the achievable potential of 19%. Together, the cost of capturing all achievable 

savings in Vermont is ¢3.7 per kWh (2010$).

However, the costs presented in Figure 16 are measure costs only: they do not include program 

delivery costs such as operating and technical support. Efficiency Vermont’s 2010 annual report 

indicates that 35% of the total program costs are spent for program delivery services. Based on 

this, the total cost of capturing the achievable potential would be about ¢5.7 per kWh (2010$).

Figure 16. Residential Efficiency Supply Curve for Vermont from GDS, 2011 ($2011)

Again, this estimate of ¢5.7 per kWh is the average cost of reducing statewide energy use in 2031 

by 25% below the current forecast. Program administrators will no doubt target the lower cost 

measures first, so savings in the initial years would cost considerably less than this. Based on this 

and the other data presented above, we attach a total cost of ¢4.7 per kWh to the energy saved 

during the first decade of the Transition Scenario. This is intended to include both provider costs 

(“utility costs”) and customer costs (“participant costs”).

Regarding the longer term, we tend to agree with studies, like the GDS study for Vermont, that 

assume improving technology will allow for deep savings without steep increases in the cost of 

saved energy. The technologies emerging today support this idea, as do many historical case 

studies. The cost of refrigerators, for example, has been falling steadily since about 1975, while 

the weighted average efficiency of the refrigerators sold has increased considerably over the 

same period (Goldstein 2011). However, in the interest of a conservative assessment of the cost 
Beyond Business as Usual ▪ 51

of the Transition Scenario, we assume a rising cost of saved energy over the study period. Table 

32 shows the levelized cost of saved energy in each decade of the study. Costs are recovered 

and levelized over a 15-year period.

Table 32. Assumed Cost of Saved Energy in the Transition Scenario (¢/kWh)

2011-20 2021-30 2031-40 2041-50

¢4.7 ¢5.3 ¢6.0 ¢7.0

In Section 4.F we discuss our sensitivity analysis around these efficiency cost assumptions.

E. Demand Response

At low levels of demand response (DR) penetration, we use costs based on current payments and 

enrolled DR capacity in New England. At higher levels, we estimate costs based on discussions 

with vendors of technologies that enable shifting of cooling loads, the primary driver of summer 

peak loads. 

Currently, capacity resources in New England are being paid $3.21 per kW-month, and 1,500 MW 

of DR cleared in the last capacity auction (ISO New England, 2011). This is roughly 5% of the 

peak load in New England. Therefore, the low end of our DR supply curve is based on a peak load 

reduction of 5% for a payment of roughly $3.00 per kW-month. 

Our discussions with energy management companies indicate that higher payments would attract 

significantly more capacity. Technologies available today, such as ice-based energy storage, allow 

customers to shift summer cooling loads to off-peak periods (see, for example, www.iceenergy.com). It is not clear exactly how much consumers would need to be paid to invest in these 

systems, but vendors estimate that a price well under $10 per kW-month would result in significant 

market penetration.

Our supply curve for DR capacity resources is shown Figure 17. (The maximum DR resource 

achieved in any region in the Transition Scenario is a 15% reduction in peak load in Arizona/New 

Mexico by 2050.)
Beyond Business as Usual ▪ 52

Figure 17. Demand Response Supply Curve Used in Transition Scenario

$0.00

$1.00

$2.00

$3.00

$4.00

$5.00

$6.00

$7.00

$8.00

$9.00

1 % 2 % 3 % 4 % 5 % 6 % 7 % 8 % 9 % 10% 11% 12% 13% 14% 15%

Payment ($/kW-month)

Peak Load Reduction
Beyond Business as Usual ▪ 53

Appendix B: Data Tables

 

Table 33. Generation under BAU, from Figure 3 (TWh)

2010 % 2020 % 2030 % 2040 % 2050 %

Utility-Scale

 Coal 1,841 44.6% 1,874 42.3% 2,058 41.9% 2,141 39.8% 2,231 37.7%

 Oil Steam 23 0.6% 23 0.5% 23 0.5% 24 0.4% 24 0.4%

 Oil CT 2 0.0% 2 0.0% 2 0.0% 2 0.0% 2 0.0%

 Other Oil 7 0.2% 6 0.1% 6 0.1% 7 0.1% 9 0.1%

 Gas Steam 93 2.2% 91 2.1% 91 1.9% 91 1.7% 91 1.5%

 Gas CCCT 764 18.5% 699 15.8% 794 16.2% 1,022 19.0% 1,261 21.3%

 Gas CT 46 1.1% 47 1.1% 47 1.0% 52 1.0% 61 1.0%

 Nuclear 803 19.4% 877 19.8% 877 17.9% 873 16.2% 870 14.7%

 Pumped Storage -7 -0.2% -7 -0.1% -7 -0.1% -7 -0.1% -7 -0.1%

 Other 0 0.0% 2 0.0% 4 0.1% 6 0.1% 17 0.3%

 Hydropower 239 5.8% 300 6.8% 307 6.2% 309 5.7% 309 5.2%

 Geothermal 17 0.4% 25 0.6% 42 0.9% 49 0.9% 51 0.9%

 Waste Gases 15 0.4% 15 0.3% 15 0.3% 15 0.3% 15 0.2%

 Biomass (Direct) 9 0.2% 9 0.2% 9 0.2% 9 0.2% 9 0.2%

 Biomass (Co-Fire) 2 0.0% 28 0.6% 24 0.5% 24 0.5% 24 0.4%

 Solar Thermal 1 0.0% 3 0.1% 3 0.1% 3 0.1% 3 0.1%

 Utility PV 0 0.0% 1 0.0% 1 0.0% 2 0.0% 3 0.1%

 Wind 91 2.2% 142 3.2% 156 3.2% 167 3.1% 185 3.1%

 Offshore Wind 0 0.0% 1 0.0% 1 0.0% 1 0.0% 1 0.0%

Utility Subtotal 3,946 4,137 4,453 4,789 5,161

End-Use Sited

 Liquified Fuels 23 0.6% 32 0.7% 79 1.6% 111 2.1% 111 1.9%

 Petroleum 5 0.1% 5 0.1% 5 0.1% 5 0.1% 5 0.1%

 Gas CHP 103 2.5% 160 3.6% 211 4.3% 297 5.5% 427 7.2%

 Other 12 0.3% 16 0.4% 16 0.3% 16 0.3% 17 0.3%

 Hydropower 3 0.1% 3 0.1% 3 0.1% 3 0.1% 3 0.1%

 Geothermal 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Municipal Waste 3 0.1% 3 0.1% 3 0.1% 3 0.0% 3 0.0%

 Biomass CHP 31 0.7% 60 1.3% 122 2.5% 139 2.6% 170 2.9%

 Wind 0 0.0% 2 0.1% 2 0.0% 3 0.0% 3 0.0%

 End-Use PV 3 0.1% 14 0.3% 16 0.3% 18 0.3% 21 0.4%

End-Use Subtotal 184 295 458 594 758

Total Generation 4,130 4,432 4,911 5,383 5,919
Beyond Business as Usual ▪ 54

Table 34. Generation in the Transition Scenario, from Figure 3 (TWh)

2010 % 2020 % 2030 % 2040 % 2050 %

Utility-Scale

 Coal 1,841 44.6% 1,481 36.8% 1,016 27.0% 488 12.8% 0 0.0%

 Oil Steam 23 0.6% 11 0.3% 0 0.0% 0 0.0% 0 0.0%

 Oil CT 2 0.0% 1 0.0% 0 0.0% 0 0.0% 0 0.0%

 Other Oil 7 0.2% 5 0.1% 2 0.1% 1 0.0% 0 0.0%

 Gas Steam 93 2.2% 46 1.2% 0 0.0% 0 0.0% 0 0.0%

 Gas CCCT 764 18.5% 746 18.5% 788 20.9% 944 24.8% 1,046 26.6%

 Gas CT 46 1.1% 47 1.2% 50 1.3% 51 1.3% 54 1.4%

 Nuclear 803 19.4% 822 20.4% 757 20.1% 690 18.1% 618 15.7%

 Pumped Storage -7 -0.2% -7 -0.2% -7 -0.2% -7 -0.2% -7 -0.2%

 Other 0 0.0% 2 0.0% 4 0.1% 6 0.2% 17 0.4%

 Hydropower 239 5.8% 300 7.4% 307 8.1% 309 8.1% 309 7.9%

 Geothermal 17 0.4% 22 0.5% 26 0.7% 31 0.8% 36 0.9%

 Waste Gases 15 0.4% 19 0.5% 22 0.6% 23 0.6% 24 0.6%

 Biomass (Direct) 9 0.2% 10 0.2% 14 0.4% 19 0.5% 24 0.6%

 Biomass (Co-Fire) 2 0.0% 1 0.0% 1 0.0% 0 0.0% 0 0.0%

 Solar Thermal 1 0.0% 2 0.0% 2 0.0% 2 0.1% 3 0.1%

 Utility PV 0 0.0% 44 1.1% 84 2.2% 259 6.8% 495 12.6%

 Wind 91 2.2% 210 5.2% 296 7.9% 436 11.4% 545 13.9%

 Offshore Wind 0 0.0% 10 0.2% 22 0.6% 43 1.1% 63 1.6%

Utility Subtotal 3,946 3,770 3,383 3,297 3,229

End-Use Sited

 Liquified Fuels 23 0.6% 23 0.6% 23 0.6% 23 0.6% 23 0.6%

 Petroleum 5 0.1% 5 0.1% 5 0.1% 5 0.1% 5 0.1%

 Gas CHP 103 2.5% 110 2.7% 118 3.1% 123 3.2% 126 3.2%

 Other 12 0.3% 16 0.4% 16 0.4% 16 0.4% 17 0.4%

 Hydropower 3 0.1% 3 0.1% 3 0.1% 3 0.1% 3 0.1%

 Geothermal 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Municipal Waste 3 0.1% 3 0.1% 3 0.1% 3 0.1% 3 0.1%

 Biomass CHP 31 0.7% 60 1.5% 122 3.3% 139 3.6% 170 4.3%

 Wind 0 0.0% 2 0.1% 2 0.1% 3 0.1% 3 0.1%

 End-Use PV 3 0.1% 34 0.9% 89 2.4% 196 5.1% 348 8.9%

End-Use Subtotal 184 256 382 510 698

Total Generation 4,130 4,026 3,765 3,807 3,927
Beyond Business as Usual ▪ 55

Table 35. Capacity under BAU, from Figure 4 (GW)

2010 % 2020 % 2030 % 2040 % 2050 %

Utility-Scale

 Coal 318 30.3% 318 29.3% 318 27.2% 318 26.2% 318 24.2%

 Oil & Gas Steam 114 10.8% 93 8.6% 93 7.9% 89 7.3% 89 6.8%

 CCCT 198 18.9% 204 18.8% 235 20.1% 244 20.2% 262 20.0%

 CT/Diesel 139 13.2% 143 13.2% 166 14.2% 175 14.5% 230 17.5%

 Nuclear 101 9.6% 110 10.2% 110 9.4% 110 9.1% 110 8.4%

 PS/Other 22 2.1% 22 2.0% 22 1.9% 23 1.9% 25 1.9%

 Other Storage 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Fuel Cells 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Distributed Gen 0 0.0% 1 0.1% 2 0.2% 3 0.3% 4 0.3%

 Hydropower 77 7.3% 78 7.2% 79 6.8% 80 6.6% 80 6.1%

 Geothermal 2 0.2% 3 0.3% 6 0.5% 7 0.5% 7 0.5%

 MSW/LFG 3 0.3% 3 0.3% 3 0.3% 3 0.3% 3 0.3%

 Biomass DF 2 0.2% 2 0.2% 2 0.2% 2 0.2% 2 0.2%

 Solar Thermal 1 0.1% 1 0.1% 1 0.1% 1 0.1% 1 0.1%

 Utility PV 0 0.0% 0 0.0% 0 0.0% 1 0.1% 1 0.1%

 Wind 37 3.6% 49 4.5% 53 4.5% 57 4.7% 62 4.7%

 Offshore Wind 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Utility Subtotal 1,014 1,028 1,091 1,113 1,195

End-Use Sited

 Liquified Fuels 4 0.4% 5 0.5% 12 1.0% 16 1.3% 16 1.2%

 Petroleum 1 0.1% 1 0.1% 1 0.1% 1 0.1% 1 0.1%

 Gas CHP 18 1.7% 26 2.4% 32 2.8% 44 3.6% 60 4.6%

 Other 2 0.2% 3 0.2% 3 0.2% 3 0.2% 3 0.2%

 Hydropower 1 0.1% 1 0.1% 1 0.1% 1 0.1% 1 0.1%

 Geothermal 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Municipal Waste 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Biomass CHP 5 0.5% 9 0.9% 17 1.5% 20 1.6% 24 1.8%

 Commercial PV 1 0.1% 5 0.4% 5 0.4% 6 0.5% 6 0.5%

 Residential PV 1 0.1% 5 0.4% 5 0.4% 6 0.5% 6 0.5%

 Wind 0 0.0% 2 0.2% 2 0.1% 2 0.2% 2 0.2%

End-Use Subtotal 34 56 78 97 119

Total Capacity 1,048 1,084 1,170 1,210 1,314
Beyond Business as Usual ▪ 56

Table 36. Capacity in the Transition Scenario, from Figure 4 (GW)

2010 % 2020 % 2030 % 2040 % 2050 %

Utility-Scale

 Coal 318 30.3% 215 21.9% 137 14.5% 66 6.1% 0 0.0%

 Oil & Gas Steam 114 10.8% 57 5.8% 0 0.0% 0 0.0% 0 0.0%

 CCCT 198 18.9% 198 20.2% 199 21.1% 206 19.1% 219 17.3%

 CT/Diesel 139 13.2% 143 14.5% 158 16.7% 182 16.9% 200 15.8%

 Nuclear 101 9.6% 104 10.6% 96 10.2% 88 8.1% 78 6.2%

 PS/Other 22 2.1% 22 2.2% 22 2.3% 23 2.1% 25 2.0%

 Other Storage 0 0.0% 0 0.0% 0 0.0% 2 0.2% 23 1.8%

 Fuel Cells 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Distributed Gen 0 0.0% 1 0.1% 2 0.2% 3 0.3% 4 0.3%

 Hydropower 77 7.3% 78 7.9% 79 8.4% 80 7.4% 80 6.3%

 Geothermal 2 0.2% 3 0.3% 4 0.4% 4 0.4% 5 0.4%

 MSW/LFG 3 0.3% 4 0.4% 4 0.5% 5 0.4% 5 0.4%

 Biomass DF 2 0.2% 2 0.2% 3 0.3% 4 0.3% 4 0.3%

 Solar Thermal 1 0.1% 1 0.1% 1 0.1% 1 0.1% 1 0.1%

 Utility PV 0 0.0% 19 1.9% 37 3.9% 114 10.6% 193 15.3%

 Wind 37 3.6% 73 7.5% 99 10.4% 129 11.9% 160 12.6%

 Offshore Wind 0 0.0% 3 0.3% 6 0.6% 11 1.0% 16 1.2%

Utility Subtotal 1,014 922 846 916 1,013

End-Use Sited

 Liquified Fuels 4 0.4% 4 0.4% 4 0.4% 4 0.4% 4 0.3%

 Petroleum 1 0.1% 1 0.1% 1 0.1% 1 0.1% 1 0.1%

 Gas CHP 18 1.7% 19 1.9% 20 2.1% 21 2.0% 22 1.7%

 Other 2 0.2% 3 0.3% 3 0.3% 3 0.2% 3 0.2%

 Hydropower 1 0.1% 1 0.1% 1 0.1% 1 0.1% 1 0.1%

 Geothermal 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Municipal Waste 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

 Biomass CHP 5 0.5% 9 1.0% 17 1.9% 20 1.8% 24 1.9%

 Commercial PV 1 0.1% 13 1.3% 32 3.4% 72 6.7% 125 9.9%

 Residential PV 1 0.1% 7 0.7% 18 1.9% 39 3.6% 70 5.5%

 Wind 0 0.0% 2 0.2% 2 0.2% 2 0.2% 2 0.2%

End-Use Subtotal 34 59 99 163 252

Total Capacity 1,048 981 945 1,078 1,265
Beyond Business as Usual ▪ 57

Table 37. Regional Average Capacity Factors at Coal-Fired Plants under BAU

2010 2020 2030 2040 2050

Northeast 53% 44% 67% 73% 80%

Southeast 63% 65% 71% 75% 80%

Eastern Midwest 63% 64% 72% 76% 80%

Western Midwest 68% 65% 75% 78% 80%

South Central 72% 72% 75% 78% 80%

Texas 73% 80% 80% 80% 80%

Arizona/New Mexico 78% 77% 78% 79% 80%

Rockies 79% 80% 80% 80% 80%

Northwest 78% 74% 77% 79% 80%

California 85% 88% 89% 89% 89%

Table 38. Regional Average Capacity Factors at Coal-Fired Plants in the Transition Scenario

2010 2020 2030 2040 2050

Northeast 53% 65% 75% 85% --

Southeast 63% 78% 85% 85% --

Eastern Midwest 63% 78% 85% 85% --

Western Midwest 68% 78% 85% 85% --

South Central 72% 80% 85% 85% --

Texas 73% 80% 85% 85% --

Arizona/New Mexico 78% 85% 85% 85% --

Rockies 79% 85% 85% 85% --

Northwest 78% 85% 85% -- --

California 85% 85% 85% -- --

Table 39. Regional Average Capacity Factors at CCCTs under BAU

2010 2020 2030 2040 2050

Northeast 47% 49% 52% 58% 56%

Southeast 46% 36% 24% 38% 48%

Eastern Midwest 40% 37% 27% 37% 46%

Western Midwest 18% 16% 5% 32% 60%

South Central 51% 53% 44% 47% 48%

Texas 51% 53% 60% 63% 66%

Arizona/New Mexico 43% 38% 24% 29% 27%

Rockies 17% 9% 5% 38% 49%

Northwest 48% 4% 38% 60% 65%

California 37% 36% 39% 53% 66%
Beyond Business as Usual ▪ 58

Table 40. Regional Average Capacity Factors at CCCTs in the Transition Scenario

2010 2020 2030 2040 2050

Northeast 47% 34% 33% 33% 45%

Southeast 46% 51% 52% 61% 66%

Eastern Midwest 40% 55% 57% 70% 70%

Western Midwest 18% 54% 54% 63% 62%

South Central 51% 49% 53% 67% 66%

Texas 51% 52% 42% 39% 35%

Arizona/New Mexico 43% 23% 23% 32% 22%

Rockies 17% 18% 15% 42% 26%

Northwest 48% 15% 37% 44% 45%

California 37% 16% 35% 36% 37%
Beyond Business as Usual ▪ 59

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