## 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.

http·ttwww.pcusa.org/ b!ogs/ eco-jou rney /2012/5 f 18/ reflection-womens-stories-mtr-and-climate-change-t/ 5/23/12 10·10 AM

.. 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
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<>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 5/23/12 10 10 AM

ARClllVES

Page2ofSEco-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

http://www. pcu sa .o rg J blog s 1 eco- JOUrney /2 0 12/5/18/ reflection-women s -stories -m tr-an d- climate-change- t/ 5/23;12 10:10 AM

Page 3 of 5Eco-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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I tl\1\lt "\ l

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Presbyterian Church (U.S.A.) Investment



### Et Loan Program (PILP) Office of the General Assembly (OGA)

Presbyterian Publishing Corporation (PPC)

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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 th at can help to improve society. CSI works to supp ort local and state efforts to advance the modernization of the electric system and protect the health of citizens and their communities throu gh advancing safe, sustainable, and affordable energy solutions.

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

r esearch, 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
environment al 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 P resident and Chief Executive Officer of Synapse. He has consulted on issues of energy economics an d electric indu stry 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 bu ilding technology at MIT.

Ezra Hausman , V ice 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

, wi th 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 econo mics 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 an d 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 SUM MARY

................................ ................................ .................. 1

2. METHODOLOGY

................................ ................................ ................................ ................ 6

A. AEO 2011 AND 

### B USINESS AS 

### U SUAL



### ................................ ................................ ............ 6

B. D EVELOPING THE 

### T RANSITION 

### S CENARIO



### ................................ ................................ ..... 7

C. C ALCULATING 

### C OSTS



### ................................ ................................ ................................ ..... 8

D. A IR 

### E MISSIONS AND 

### W ATER 

### U SE



### ................................ ................................ ................... 9

E. T RANSMISSION AND 

### S YSTEM 

### O PERATION



### ................................ ................................ .... 10

F. S AVINGS FROM 

### A VOIDED 

### E NVIRONMENTAL 

### R ETROFITS



### ................................ .............. 12

G. A VOIDED 

### H EALTH 

### I MPACTS FROM 

### C OAL



### - F IRED 

### G ENERATION



### ................................ .... 13

H. J OBS 

### A SSOCIATED WITH 

### N EW 

### P LANTS



### ................................ ................................ ........ 13

3. BUSINESS AS USUAL AN D THE TRANSITION SCE NARIO

................................ .. 14

A. E LECTRICITY 

### D EMAND



### ................................ ................................ ................................ .. 14

B. T HE 

### G ENERATING 

### F UEL 

### M IX



### ................................ ................................ ......................... 14

C. G EN ERATING 

### C APACITY



### ................................ ................................ ................................ 16

D. T RANSMISSION AND 

### S YSTEM 

### O PERATION



### ................................ ................................ .... 19

4. FINDINGS

................................ ................................ ................................ ........................... 22

A. A IR 

### E MISSIONS AND 

### W ATER 

### U SE



### ................................ ................................ ................. 22

B. A VOIDED 

### H EALTH 

### I MPACTS



### ................................ ................................ ........................... 25

C. N ATURAL 

### G AS 

### U SE



### ................................ ................................ ................................ ....... 26

D. N ET 

### C OSTS



### ................................ ................................ ................................ ................... 27

E. J OBS 

### A SSOCIATED WITH 

### N EW 

### P LANTS



### ................................ ................................ ........ 28

F. S ENSITIVITY 

### A NALYSES



### ................................ ................................ ................................ 29

APPENDIX A: TECHNOLO GY COST AND PERFORMA NCE ASSUMPTIONS

............. 33

A. F UEL 

### C OSTS



### ................................ ................................ ................................ .................. 33

B. E XISTING 

### P OWER 

### P LANTS



### ................................ ................................ ............................ 33

C. N EW 

### P OWER 

### P LANTS



### ................................ ................................ ................................ ... 37

Coal

- Fired P lants 37

Combined Cycle Combustion Turbines (CCCT) 38

Combustion Turbines 38

Nuclear Plan ts 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. E NERGY 

### E FFICIENCY



### ................................ ................................ ................................ .... 47

E. D EMAND 

### R ESPONSE



### ................................ ................................ ................................ ..... 51

APPENDIX B: DA TA TABLES

................................ ................................ ................................ .. 53

REFERENCES

................................ ................................ ................................ ............................. 59Beyond 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 ene rgy 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 cont rols 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 ha ve 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 c ountry 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, c ost estimates for “next generation” nuclear units continue to climb, and lenders are un willing to finance these plants without taxpayer guarantee s

. 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 a nd 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 technologie s 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 h ave 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 lev els 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 i n 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 bas ed 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 coal

fired plants and a quarter of the nation’s nuclear plants are retired by 2050. Relianc e 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 natura l gas
use is lower than under BAU

. Importantly, t he 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 o f 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 car eful 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 anal yses 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 2 6 % increase. In the Transition Scenario, co al

- fired generation is eliminated by 2050.

 Natural gas

- fired gene ration grows from 1,010 to 1,84 0 TWh under BAU , while it rises to only 1,230 TWh in the Transition Scenario.

 Nuclear generation rises from 800 to 87 0 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 Transi tion 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 TW h 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 sa vings 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 ele ctric 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 k Wh.

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 coa l, 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 carbo n 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 hav e estimated some of the health benefits
of the Transition Scenario.

The benefits of the Transition Scenario include the following:

 By 2020, power sector CO 2 

### emissions fall 2 5 % below 2010 levels. By 2050 they are 81 % below 2010 levels

. Under BAU

, CO 2 

### emiss ions 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 imp acts of mining and coal transportation.

 Cooling water withdrawals at power plants fall fr om 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 c osts 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 incl ude 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 c onstruction and operation of the new power plants in the first decade of the
Transition Scenario creates r oughly 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 annua l 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.

 N atural gas use would be lower than BAU in all years of the study period. I n 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 inte nd 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 fo r 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 genera tion?

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 CO 2 

### 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 sequest ration.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 beg i n with data from the 2011 Annual Energy Outlook (AEO), released by the Energy
Information Admi nistration (EIA) in April 2011. Each year EIA uses the National Energy Modeling System (NEMS) to model a “Re ference Case” energy scenario. EIA then analyzes various policy proposals by modeling the policy under consideration and comparing t he 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 durin g 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 EMWBeyond 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 region s 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 1 8 ) As we extrapolate the AEO data, we continue this trend: under in the BAU, reserve margins in

mo st 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 flexi ble capacity to accommodate high levels of variable generation.



## B. Developing the Transition Scenario

To develop the Transition Scenario

, we f irst develop new forecasts of electricity consumption and peak load growth in each region. We
do this b y adjusting BAU demand to simulate the effects of more aggressive energy efficiency and demand response (DR) programs nationwide. 2 

### The energy use forecast in the AEO includes the effects of efficiency codes and standards in the near term; however
it does n ot 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 acr oss 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 pr ograms in recent

years

. (S everal states and utilities are currently targeting savings in excess of 2%.) T his 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 assum e that the average c ost 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 sav ings 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 MW h saved. This factor is an average based on a nalysis of state and uti lity 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% i n 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, consis tent 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 1 8 .) We expand DR capabilities most

aggress ively 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 le vels are achieved (see Appendix A, S ection 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

. T he trajectory of plant retirements and additions was developed in an iterative way. Plant
retirement and re newable 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 scenario s for any

new resource.
After a rough nationwide s cenario was ske tched 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 CO 2 

### 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 est imates 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 f ocused on consistency in the assumptions common to all technologies . Ho wever, for several technologies we find that data from other sources point to assumptions significantly different f rom 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 a re 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 Scenario s

. We do not include in this cost an alysis 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 i n 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 . W e also estimate the saving s the Transition Scenario would provide in avoided emission control costs.



## D. Air Emissions and Water Use

The AEO reports power sect or emissions of CO 2 

### , sulfur dioxide (SO 2 

### ), oxides of nitrogen (NO X 

### )

, 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) regardi ng unit type, fuels , efficiency, air emissions an d 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

assum ptions 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 pr omulgated Clean Air Visibility R ule requires a large cohort of power plants that affect visibility in national parks
and other federal natural areas to reduce SO 2 

### , NO X 

### and particulate emissions. This rule is curr ently 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 NO X 

### and
SO 2 

### emissions in 2012 and 2014 across the eastern half
of the U

. S

. , e xcluding 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 schedu led in 2011 and 2012 to revise the current air quality standards for ozone,
SO 2 

### , NO 2 

### , 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 contr ols 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 t he 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

requ ired

. 

## 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 forward

going 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 ce rtainly 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 inst all these systems by 2020. T he other half install s them by 2030. On average, controlled plants achieve an SO 2 

### emission rate of 0.2 lb per mmBtu.

 Half of the coal

- fired units over 100 MW wit hout selective catalytic reduction (SCR) systems inst all these systems by 2020. T he other half install s them by 2030. On average, controlled plants achieve a NO X 

### emission rate of 0.15 lb per mmBtu.

 Half of the coal

- fired units over 100 MW without mercury c ontrols and fabric filters to capture particulate matter inst all these systems by 2020. T he other half install s 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 closed

loop systems by 2020

, and that the other half installs t hem 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 assumpt ions 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. C ontrols on smaller units are not required until after 2020. In the Transition Scenario we apply the same retrofit assumptions along
with the coal retir ement 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 h ealth 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 re gions 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 n eeded simply to move more energy, as under BAU

. However, investment within control areas would be needed to maintain and expand theBeyond 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 trans fer 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. I n t he Transition Scenario , however, there are increased tran sfers between several regions. We estimate the cost of the new transmission capacity needed to
accommodate the se transfers by translating energy transfers into MW of capacity needed and assuming that new capacity (high voltage DC lines) cost s $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 tran smission ca pacity each decade.
Therefore

, much less new transmission would be needed than in a
scenario in which renewables m et 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 d istribution systems would have to be upgraded to accommodate more complex energy flows, b ut m u ch of
this wor k is already being funded, so it would not be incremental spending in the Transition
Scenario. 3 

### Therefore , 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, w e have incorporated four other strategies t o increase the flex ibility 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 chang es 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 Trans ition Scenario

, demand falls slightly, and retired coal and nuclear plants would free up large amounts of existing transmission capacity.Beyond Business as Usual ▪ 12 

###  Seco nd, 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 r esponse 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 co ntin ue

. (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 Penns ylvania/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 marke t” 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 i n 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 w e target units for

retirement based on each unit’s forward

- going costs , including any
emission control costs the unit face s . 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 control s. 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 bo ards. Avoided annual carrying costs are $ 11 bill ion in 20 20, $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 ca lculate damages and premature mortality based on the emissions and location of each coal

- fired unit. We first estimate the air emissions (SO 2 

### , NO X 

### , PM 10 

### and PM 2.5 

### ) at each coal

- fired unit. Under BAU, emissions fall at many
units due to control retrofits. I n 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 f or 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 damag es are converted to stat istical lives u sing 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 A ssociated 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 pl ants ) using technology

- specific data from the National Renewable Energy Laboratory ’s ( NREL) Jobs and E conomic 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 estimat e the spin

- off effects of new industry

spec ific activity by estimating the activity of suppliers required for that activity (indirect impacts )

and the re

- spending of workers’ wages i n the economy (induced impacts ).

It is important to note that t here 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.
How ever, 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. T his is based on the AEO 2011 Reference Case, which includ es 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 roug hly 0. 1 % per year, as we simulate the impact of more aggressive utility and third

- part y 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

Fi gure 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 gen eration falls slightly, to 3, 960 TWh in 2050.

 Under BAU, coal

- fired generation grows from 1,860 to 2,340 TWh

– a 2 6 % increase. In the Transition Scenario, coal

- fired generation is eliminated by 2050.

 Natural gas

- fired gene ration grows from 1,010 to 1,840 TWh under BAU, while it rises to only 1, 23 0 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 TW h in the Transi tion Scenario, a reduction of

23 %.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 E ast C oast.

 PV generat ion grows from 4 to 24 TW h under BAU, and it grows to 842 TWh in the
Transition Scenario. The majority of this is distributed PV generation.

 Large

- scale b iomass generation under BAU grows from 11 to 33 TWh, with all of the

increase due to co

- firing at coa l

- 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 s cenario s 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 distribute d 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 distri buted PV generation grows far more. Overall, distributed generation grows faster in the Transition Scenario.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 Fue l 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 ar e 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

BA U, utility

- scale biomass generation grows to 33 TWh in 2050, while in the Trans i tion Sc enario 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

F igure 4 below shows generat ing capacity in both scenarios. Notable aspects of the scenarios are
as follows.

 In the Transition Scenario a ll coal

- fired plants are retired as well as all oil

- and gas

- fired steam plants and oil

- fired combustion turbines

.

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

 Under BAU, gas

- fired combin ed cycle capacity grows from 198 GW in 2010 to 2 62 GW in

2050. In the Tra nsition Scenario it grows to only 219 GW.

 Gas

- fired CT c apacity under BAU grows from 1 39 to 230 GW, while it grows to 200 GW in
the Transition Scenario.

 Under BAU, ons hore wind capacity grows from 38 to 6 4 GW, and offshore capacity grows
from 0 to 0.2 GW. In the Transition Sc enario

, onshor e 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 1 4 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 capac ity 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 c ompiled 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 histori cal 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 cap acity 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 region s , reserve margin s rise again in the last decade, as additional gas

- fired and storage capacity is added to support high level s of wind and solar generation.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 program s

. 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 sho ws 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 sce narios to the D R 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 n ew transmission capacity would be needed to move additional energy between regions in the Transition Scenario.

 In the W est ern Interconnect , we e n vision 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 t o 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, a n 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

b illion. We include the annualized cost of this capacity (recovered over 30 years) in our cost analy sis ( see Table 5 ).

A s discussed above, we have paid careful attention to the
amount of variable generation in each region. B y the later
decades of the Transition Scenario there is considerably less
coal

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

- fir ed 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 f lexible generation and capacity; adding storage capacity in regions with high levels of wind generation;

a nd 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 informa tion sharing and cooperation among balancing areas.

4 For comp arison, 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 varia ble 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 ene rgy 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. H owever, 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 capacit y (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, wo uld 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 s ome regions hydro would provide considerable additional flexibility. )

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



### Energy s torage 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

.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 m ade 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 ha s 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.Beyond Business as Usual ▪ 22



# 4. Findings

A. Air Emissions and Water Use

It is important to note that o ur calculations of air emissions and water use in the two scenarios are dependent on our assumptions about emission contro l retrofits under BAU (see Section 2.D) , and

t here 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 CO 2 

### emissions rise by 28 % to 3 .3 billion tons per year in 2050. In the
Transition Scenario

, CO 2 

### emissions fall to just under 0.5 billion tons per year. This is a reduction of

81 % from 2010 levels.

Figure 7

. CO 2 Emissions in the Two Scenarios



### Mercury emissions f all considerably u nder 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 a re virtually
elim inated by 2050 with the elimination of coal

- fired generation

.Beyond Business as Usual ▪ 23 Figure 8 . Mercury Emissions in the Two Scenarios



### Under BAU

, SO 2 

### 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, SO 2 

### emissions are virtually eliminated by 2050 with the
retirement of all coal

- and oil

- fired pl ants.

Figure 9 . SO 2 Emissions in the Two Scenarios



### Widespread SCR retrofits reduce NO X 

### emissions under BAU by 36 % by 2050. Overall reductions are achieved despite a considerable increase in gas

- fired generation under BAU. Emiss ions of
NO X 

### 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

.Beyond Business as Usual ▪ 24 Figure 10 . NO X Emissions in the Two Scenarios



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

. W ater 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

- f ired plants w e 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 ScenariosBeyond Business as Usual ▪ 25



### In both scenarios, w ater withdrawals fall sharply between 2010 and 2030 due to retrofits of closed

loop cooling systems at coal

- fired and nuclear plants. After 2030 withdrawals begin rising again
under BAU , with rising coal

- fired generation. In the Transition Scen ario, 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 los e more wa ter 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 c onsumption at plants with new, closed

loop 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 plant

specific 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 st atisti cal 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 .)Beyond Business as Usual ▪ 26

Table 4. Avoided Damages or Premature Mortality from Coal

- Fired Plants in the Transiti on Scenario

201 1

- 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 3 4,000 3 1,000 3 2,000 14 9,000
Transition 51, 000 2 6,000 11, 000 3, 000 91, 000
Difference 1,000 8,00 0 20,000 2 9,000 5 8,000 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 Scen ario 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, wh ile there
are far fewer contro l 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 the se de cades.

These are rough estimate s, 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 re newable energy and thus minimize the amount of natural gas needed for the transition away from coal and nuclear power . A s seen in Figure 13, a nnual power sector gas use is lower in the Transition Scenario than under BAU in all years of the stu dy period. In 202 0, it is

0.3 qu adrillion 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 sa vings of $8 3 billion, discounted at 4 .8%.

The net annual i mpacts 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 k Wh. 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 progra ms. 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 lo sses from storage is included in the Net Cost of Generation. Avoided

emission control costs are the cost s avoided by retiring coal

- fired 

## We explore severa l 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 T ransition 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 y ears 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 S ection 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. T otal direct jobs are
calculated usin g 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
Sc enario. 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 decommis sioning of retired power plants . There would also be significant job loss due to the retire ment 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 Transm ission 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 cons truction, roughly 444,000 job

- years are created, equivalent to 44,4 00 construction workers working fu ll 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 o ver time.

I n the first year there are nearly zero jobs

, because no projects have been completed. However, assuming a roughly linear rate of construction over th e decade, the l ast 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 em ployment impact of the se project s

. Th ey require materials and additional people to design, man ufactur e, and deliver those materials. Those materials in turn may require materials for t heir production, and so forth. These are “indirect” jobs. Further , all the workers building and operating the projects

– as well as the workers manufacturing the ingr edients to the projects

– spend th eir 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

crea tion 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 chan ge the n et costs much. We performed sensitivity analyses around the assumptions that have a larger impact . Analyses of the following input assumptions are presented
below:

 T he cost of energy efficiency,

 C oal and natural gas prices,

 T he cost of PV systems, and

 T he 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 i nput assumption and observe d 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 a nd 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 b rings the NPV savings down to $2 5 billion, while the low

- cost case in creases the savings to $12 5 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 se en in Table 8

, higher gas prices result in higher net savings from the Transitio n Scenario, because less gas is burned in this scen ario than under BAU.
The h igher assumed gas prices increase NP V savings to $103 billion, while lower gas prices reduce NPV savings to $63 billion.

Table 8 . Results of Gas Price Sensitivities (2010$)

Annu al Net Cost of Transition Scenario ( billion ) NPV (billion$) 2020 2030 2040 2050 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 , h igher coal prices increase the savings provided by the Transition Scenario,

and lo wer coal prices decrease them

.

Table 9 . Results of Coal Price Sensitivities (2010$)

Annual N et Cost of Transition Scenario (billion ) NPV (billion$) 2020 2030 2040 2050 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 cost s used in our main analysis and in each sensitivity . InstalledBeyond 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 W DC 

### ($1.20 per W AC 

### )

some time between 2030 and 2040. This is t en years earlier than in the base case but ten to fifteen

years later than the current go al of the DOE’s SunShot program . The cost of large projects does not fall further after reaching $1.20 per W AC 

### . The costs of comme rcial and residential projects continue to fall over the entire period, though at a diminishing rate, and they do not reach $1.20 per W AC



### . The high PV cost case has costs falling more slowly from 2011 levels, and large systems do not reach $1.20 per W AC 

### during the study period.

These two sensitivity analyses are not symmetric around the base case . In the later decades, the high cost case is fart her from base case than the low cost case . This is because in both the base
case and the low cost case , we assu me that PV technology hits maturity and diminishing cost reductions per y e a r during the study period. It simply hits this point sooner in the low cost case

. T hus, t his assumed point of maturity

, at $1.20 per W AC 

### for large projects, provides a lower bound
f or 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 t he high

- cost PV case the NPV savings fall t o $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 ($/W AC ) 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 $1.20
Commercial Installations ($/W AC ) 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 ($/W AC ) 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 N et 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 use s the cost of energy derive d 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 the se changed assum ptions is pronounced in the early years ofBeyond 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 Sensi tivities (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 resourc e. However

, it is very difficult to remove the effect of indirect subsidies from the cos t of new plants.

These subsidies include R&D funding ; subsi dies for exploration, drilling

, and minin g ; federal loan guarantees ; and externalized costs of pollution. W e 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 technologi e s as well; however for PV, wind

, and nuclear plants we have used

assu mptions 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 o n 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 e ach 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 n ecessary.



## 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 lessBeyond Business as Usual ▪ 34



### energy at some point. We do not analyze the costs of ex isting 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 exact ly the same way, the net cost in the
Transition Scenario is zero. W e 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 cost s in each region. For nuclear units and oil and gas steam units

, we use a single capacity factor to calculate levelized costs that are ap plied 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 ap plied 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 assumption s. 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 include d in our cost analysis. Table 1 3 shows the input assumptions for existing coal

- fired units. Again, regional average levelized costs were calculated using regional average capaci ty 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 E xistin g 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) $2 2.25 AEO 2011 Heat Rate (Btu/kWh) 10,500 Synapse Range of 2010 Energy Costs ($/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

- yea r 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 , t he 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 Existin g Gas

- and Oil

- Fi red Combustion Turbine s (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 CalculatedBeyond Business as Usual ▪ 36 Table 16 . Assumptions for Existing Oil

- an d 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 f actor 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 facto r 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 substantia l 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 l ess 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 1 9 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 saving s 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 charg e rates were developed using a co st of capital represent ative 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 prem ium to new plants that produce CO 2 

### , and w e also add risk premiums to nuclear, biomass, and offshore wind. In sizing thes e risk premiums, we are guided by the levelized costs reported for the AEO, by other credible estimates of new plant costs

, and by our o wn research

.
For each technolo gy 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 W estern E lectricity Coordinating Council’s (WECC) Transmission Expansion Planning Policy Committee (E3 Analytics, 2010) . Data labeled “Lazard” w ere r eleased in May 2010 by the Lazard Co mpany , a global investment bank (Lazard, 2010)

. Data labeled “ EIA ” are from the AEO 2011 assumptions (EIA, 2010) , and d ata labeled “ Bl ack & 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

technolo gies 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 c onsistent with Bla ck & Veatch’s range, slightly higher than the E3 Analytics ’ assumption

, and at the lower end of Lazard’s range.

Note that al l 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) $3,7 93 $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) $3.0 3 $2.02

- $5.97 $4.25 $4.25 Capital Additions ($/kW

- yr) $16.18 $16.18

H eat R ate (Btu/kWh) 8,960

- 12,000 8,800 8,800
C apacity F actor (%) 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 fa ctor 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 pric e 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 fa ctor 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 Co st 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) $1,3 15 $968

- $1,1 84 $1,000

- $1,600 $1,153 Fixed Charge Rate (%) 11% FOM ($/kW

- yr) $8.09 $5.56

- $6.2 7 $14.62 $14.62 VOM ($/MWh) $4.96 $2.02

- $3.5 4 $3.11 $3.11 Capital Additions ($/kW

- yr) $0.00 $0.00

H eat R ate (Btu/kWh) 7,000 6,800

- 7,220 6,430 6,430
C apacity F actor (%) 90% 40%

- 93% 87% 70%

- 90% 60%
Fuel Cost ($/mmBtu) $6.07 $4.76 $4.76 Energy Cost ( $/MWh ) $68

- $9 7 $6 4 $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 capacityBeyond Business as Usual ▪ 39



### factors of new CTs in the Transition Scenario are driven by the need for energ y 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) $1,1 13 $809

- $1,0 12 $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

H eat R ate (Btu/kWh) 9,300 10,200

- 10,830 10,850 10,850
C apacity F actor (%) 10% 30% 5%

- 25% 8% Fuel Cost ($/mmBtu) $6.07 $4.76 $4.76 Energy Cost ( $/MWh ) $234

- $2 60 $12 5 $167

- $361 $236

Direct subsidies excluded. Figures converted to 2010 dollars from source documents where necessary.



### Nuclear Plants

T he 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 es timate 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 o ne U.S. nuclear project has received a federal loan guarantee , the Vogtle project

in Georgia. The deve loper’s current estimate for this project is $14 billion, or roughly $ 6,400 per kW.

The cost estimates at some other projects remain lower. T he latest from the expansion of the Sumner plant in South Carolina is $9.1 billion or $4,100 per k W. However, the escalating costs of the other p rojects 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 addition s. With aBeyond 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 lo w given the installed costs assumed. We
conclude that there is either a subsidy included in the calculation of ene rgy 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

H eat R ate (Btu/kWh) 10,400 10,450 10,450
C apacity F actor (%) 85% 90% 90% 70%

- 90% 90% Fuel Cost ($/mmBtu) $0.51 $0.81 $0.81 Energy Cost ( $/MWh ) $78

- $11 5 $11 5 $100

- $158 $14 2

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

h igher 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. W e use t his 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 begu n t o 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 RET I process in California includes an installe d 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 improvement s 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. W e 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 Esti mates 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

- $2,6 30 $ 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
C apacity F actor (%) 33% 30%

- 40% 34% 32%

- 42 % 33%

- 41 % Energy Cost ( $/MWh ) $86

- $13 1 $9 7 $ 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

- $5,0 58 $5,938 Fixed Charge Rate (%) 10.5% FOM ($/kW

- yr) $91 .00 $61.00

- $101. 00 $53.33 $53.33 VOM ($/MWh) $0.00 $13.15

- 18. 21 $0.00 $0.00
C apacity F actor (%) 32%

- 45% 34% 44% Energy Cost ( $/MWh ) $134

- $25 8 $24 7 $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 2 2 . The capacity f actors we use here
are based on data from the Eastern Win d Integration and Transmission Study (EnerNex, 2010 )

a nd other regio nal 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 w e 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

- 3 0 2031

- 4 0 2041

- 5 0
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 W AC 

### , and

th e assumption for small PV is $6.05 per W AC



### . Based on other data, we believe that these figures

overstate the near

- term cost of P V

. Large project costs in the AE O fall to roughly $3.05 per W AC 

### 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 reduct ion opportunities, utility

- scale system costs are expected to reachBeyond Business as Usual ▪ 43



### $2.20 per W DC 

### by 2016 ” (U

. S

. DOE 2010, p. 1). This is equivalent to rou ghly $2.65 per W AC



### . Our PV price forecast, laid out below, is more conser vative than this forecast ; h owever
, the difference in these two forecasts from the same agency underscores the range of uncertainty around long

term 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 lar ge (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
W AC 

### . An offer by the Sacramento Municipality Utility District to buy renewable energy res ulted 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 cre dit (ITC) available to these projects, these levelized energy costs are consistent with installed costs in the range of $4.00 to $4.50 per W AC



### .
The 2010 energy bids cited above are also roughly consiste nt 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 W AC 

### , considerably higher than the other three sources. In May of 2011, however, WECC revised this estimate to a rang e of $4.00 to $4.70 per W AC 

### , more in line with the other estimates (WECC, 2011). The AEO 2011 assumptio n (cited as EIA 2010 in Table 2 5 ) 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 W DC $3.50

- $3.75 $3.04 $ per W AC $4.0 0

- $4.7 0 $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, module s 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 W DC 

### 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 W DC 

### (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 M Wh (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 W DC 

### by

2016.

However, a supply and demand imbalance is clearly driving much o f 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 th ey 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 whi ch: a) by 2015 panel prices ha ve fallen to a sustainable $1.20 per W DC 

### ( “ 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 i s based on a panel cost of $1.45 per W AC 

### and BOS costs of $1.85 per W AC



### . Over the long term, w e assume that large PV projects achieve DOE’s target of $1.00 per W DC 

### ($1.20 per W A C 

### ) sometime between

2040 and 2050

. This is a less aggressive forecast than DOE’s current cost reduction g oal ($1.20 per W AC 

### before 2020); however it is consistent with our e fforts 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 ($/

W AC ) Large (≥5 MW) $3.30 $2.30 $1.58 $1.20
Com mercial (@ 1 MW) $4.30 $3.20 $2.50 $2.20

Res idential (≤5 kW) $5.30 $4.10 $3.25 $2.90
Levelized Cost

– California ($/MWh) Large (≥5 MW) $ 146 $102 $ 73 $ 57
Com mercial (@ 1 MW) $2 44 $1 79 $1 4 1 $ 1 23
Res idential (≤5 kW) $3 06 $ 2 32 $ 186 $ 1 65
Levelized Cost

– Northeast ($/MWh) Large (≥5 MW) $ 1 79 $1 24 $ 88 $ 69
Com mercial (@ 1 MW) $2 85 $ 206 $1 6 2 $1 42
Res idential (≤5 kW) $3 56 $2 68 $ 2 14 $ 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 w ith companies marketing these systems. Current costs for residential scale systems appear to be in the range of $5.70 per W AC 

### (though these systems are being marketed for far less than this due to subsidies). Current costs for commercial scale systems appe ar to be in the range of $5.00 per W AC



### . The capacit y 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 ro of 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 scen ario 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 becom e 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 estimate s from E3 Analytics and Lazard are for a st oker 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, whi ch 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

- 4,0 46 $ 3,500

- $5,000 $ 4,362 Fixed Charge Rate (%) 11 .5% FOM ($/kW

- yr) $157 .00 $9 6.09 $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
C apacity F actor (%) 85% 85 % 83 % 70 %

- 90% 83 % Fuel Cost ($/mmBtu) $1.01

- $3.3 4 $2.20 $2.20 Energy Cost ( $/MWh ) $92

- $14 8 $ 11 4 $ 105

- $160 $ 1 28 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 aBeyond 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 est i mates of project costs are considerably lower th an 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 techn ology assessed, but it seems likely that the low end of Lazard’s range is binary and the high end flash.

Our cost assumption s yield levelized costs very close to AEO 2011 and at the low end of Lazard and Black & Veatch’s range s

. 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, ou r 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
C apacity F actor (%) 90% 80%

- 90% 91% 80%

- 90% 85 % Energy Cost ( $/MWh ) $ 96

- $1 60 $10 1 $87

- $160 $9 6 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 aggressiv e 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 P V. 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 w ay 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 projec ts 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 tod ay. We use t he 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 $ 5,0 00

- $ 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
C apacity F actor (%) 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 e ight 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 selec ted 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 AE O heat rate (10,945 Btu/kWh) and O&M assumptions for this turbine. To estimate the cost of electricity and

gas use d 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, t his 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. A chievable 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 polic y, 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 electri city 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 A R 2009

- 2025 17 All 22%
ACEEE 20 09a PA 2008

- 2025 18 All 18%

McKinse y 2009 US 2009

- 2020 20 RES 22%
McKins ey 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 c onstant

. 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 achievab le potentials
listed in Table 31

– in the range of 1 8% 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
eff iciency 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 nationwi de 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 pa rty 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

2009 b ). The study also found that the utility typically bear s about 55 % of the total energy efficienc y
cost

, and customers bear about 45 %. This implies that the total cost of energy efficiency

m easures, 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 k Wh (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



### T he 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 a ggressive 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 g rowing 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 sh ows 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

3 1 above, this stu dy 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 s aved (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 cost s only: they do not include program delivery cost s 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, w e 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 hist orical 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 inter est of a conservative assessment of the costBeyond Business as Usual ▪ 51



### of the Transition Scenario, we assume a rising cost of saved energy over the study period. Table

3 2 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. T herefore, 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 mo re capacity. T echnologies available today, such as ice

- based energy storage, allow customers to shift summer cooling loads to off

- peak periods (see, for example, www.ice

energy.com) . It is not clear exactly how much consumers would need to be paid to invest in these

sys tems, 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 i n Arizona/New Mexico by 2050.)Beyond Business as Usual ▪ 52 Figure 17 . Demand Response Supply Curve Used in Transition ScenarioBeyond 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

, 919Beyond Business as Usual ▪ 54

Table 34 . Generation in the Tr ansition 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

, 927Beyond 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 1,314Beyond 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 1,265Beyond 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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