Amory B. LovinsCofounder and Chief Scientist

© 2016 Rocky Mountain Institute

東京、2016年03⽉月09⽇日JREF, Tōkyō, 9 March 2016

RO

CKY MOUNTAIN

INSTIT UTE

WAR R O O M

CARBON

The Emerging Electricity Revolution

エイモリー B. ロビンスロッキーマウンテン研究所 共同創設者・主任科学者

Netherlands: community connection

Utility revenues

Efficiency Distributed renewables

Storage (including EVs)

Flexible demand

New financial and business models

Regulatory shifts

Customer preferences

Integrative design

$

Utility revenues

Efficiency

Integrative design

$

0.8

1

1.2

1.4

1.6

1.8

160

180

200

220

240

260

2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024

Annu

al e

lect

ricity

use

(TW

h)

Historical

2012

Australia national electricity marketActual vs. forecast electricity demand

20112010

2014

2013

2015

real

GDP

(billi

on 2

011

Aust

ralia

n Do

llars

)

Inspiration: M. Liebreich, keynote, Bloomberg New Energy Finance summit, April 2015. GDP data: International Monetary Fund, World Economic Outlook database, http://www.imf.org/external/pubs/ft/weo/2015/02/weodata/download.aspx Historical and forecast electricity use: Australian Energy Market Operator, National Electricity Forecasting Report 2010–2015, http://www.aemo.com.au/AEMO%20Home/Electricity/Planning/Forecasting

GDP (by calendar year)

Inde

x of

U.S

. Prim

ary

Ener

gy

Per D

olla

r of R

eal G

DP

Heresy HappensU.S. energy intensity

0

0.25

0.5

0.75

1

1.25

1975 1990 2005 2020 2035 2050

Government and Industry Forecasts, 1975

Reinventing Fire, 2011

Lovins, Foreign Affairs, Fall 1976

Actual

3-4x Energy Productivity in Buildings, 2x in IndustrySame or better services

U.S. buildings: 3–4× energy productivity worth 4× its cost (site energy intensities in kWh/m2-y; U.S. office median ~293)

284➝85 (–70%)2013 retrofit

~277➝173 (–38%) 2010 retrofit

...➝108 (–63%) 2010–11 new

...➝≤50 (–83% to –85%) 2015 new

Yet all the technologies in the 2015 example existed well before 2005!

Rocky Mountain Institute Innovation Center (50-person office, 90-person convening center)www.rmi.org/innovationcenter22830 Two Rivers Road, Basalt, Colorado 81621

Images by Tim Griffith, courtesy of ZGF Architects

1451-m2 2015 Rocky Mountain Institute office

100-year building at 2015 m elevation, 30 km WNW of Aspen, ColoradoAll-passive, no boilers/furnaces/chillers, net exporter of solar electricityEnergy performance increased capital cost 10.8% with <4-year payback

910-m2 Bavarian mixed-use building produces nearly 5× as much energy as it uses“House of Energy”, Kaufbeuren, 2013, world’s first Passive House Premium building: total use 21 kWh/m2y (including 8 for heating); 250 m2 PVs produce 103 kWh/m2y

Utility revenues$ Distributed

renewables

Storage (including EVs)

Flexible demand

50

100

150

Lum

inou

s ef

ficac

y (lm

/W)

Incandescent lamp1879

200

250

300

1900 1950 20000

Years

1996

LED and PV

50

100

150

Lu

min

ous e

ffic

acy (

lm/W

)

Fluorescent lamp

Incandescent lamp

Halogen lamp

Sodium-vapor lamp

1965

1938

1959

1879

200

250

300

1900 1950 20000

Years

1996

50

100

150

Lu

min

ous e

ffic

acy (

lm/W

)

Fluorescent lamp

Incandescent lamp

Halogen lamp

Sodium-vapor lamp

White LED

1965

1938

1959

1879

200

250

300

1900 1950 20000

Years

1996

Sources: L: courtesy of Dr. Yukio Narukawa (Nichia Corp., Tokushima, Japan) from J. Physics. D: Appl. Phys. 43(2010) 354002, doi:10.1088/0022-3727/43/35/354002, updated by RMI with CREE lm/W data, 2015, www.cree.com/News-and-Events/Cree-News/Press-Releases/2014/March/300LPW-LED-barrier;. R: RMI analysis, at average 2013 USEIA fossil-fueled generation efficiencies and each year’s real fuel costs (no O&M); utility-scale PV: LBNL, Utility-Scale Solar 2013 (Sep 2014), Fig. 18; onshore wind: USDOE, 2013 Wind Technologies Market Report (Aug 2014), “Windbelt” (Interior zone) windfarms’ average PPA; German feed-in tariff (falls with cost to yield ~6%/y real return): Fraunhofer ISE, Cost Perspective, Grid and Market Integration of Renewable Energies, p 6 (Jan 2014); all sources net of subsidies; graph inspired by 2014 “Terrordome” slide, Michael Parker, Bernstein Alliance

0

100

200

300

400

500

600

700

800

1990

1994

1998

2002

2006

2010

2014

Coal-fired steam turbine, fuel cost onlyOil-fired condensing, fuel cost onlyNatural gas CCGT, fuel cost onlyUtility-scale solar PV, total costOnshore windpower, total costGerman PV residential feed-in tariff

Real

bus

bar p

rice

or fu

el c

ost,

2011

US$

/MW

h

(Seattle-like climate)

2002 2004 2006 2008 2010 2012 2014 2016

Renewable Energy’s Costs Continue to PlummetWind and photovoltaics: U.S. generation-weighted-average Power Purchase Agreement prices, by year of signing

250

200

150

100

50

U.S. wholesale power price

wind PPAs

utility-scale solar PPAs

leve

lized

201

4 U

S$/M

Wh

Cap

acity

add

ition

s (G

W)

Global power generation capacity additions, 2012–30

0

100

200

300

2012 2013 2015 2020 2025 2030

CoalGasOilNuclear

0

100

200

300

2012 2013 2015 2020 2025 2030

WindSolarHydroBiomass and wasteOther

10687 78

6452

39

Forecast

93 100

146

181

225

290Forecast

Source: Bloomberg New Energy Finance, redrawn from Michael Liebreich’s Summit Keynote, 7 April 2014

Cheaper renewables and batteries change the gameIn Westchester, NY, 60% of residential consumption in the next decade could come more cheaply from PV

Load control + PVs = grid optional

0"

2"

4"

6"

8"

10"

12"

kW#

Uncontrolled: ~50% of solar PV production is sent to the grid, but if the utility doesn’t pay for that energy, how could customers respond?

EV-charging

!"!!!!

!2.00!!

!4.00!!

!6.00!!

!8.00!!

!10.00!!

!12.00!!

kW#

Unc!Load! Smart!AC! Smart!DHW! Smart!Dryer!

0"

2"

4"

6"

8"

10"

12"

kW#

Controlled: flexible load enables customers to consume >80% of solar PV production onsite.

AC

DHW

Dryer

Other

Solar PVAC

DHW

Dryer

Other

Solar PVEV-charging

Source: RMI analysis “The Economics of Load Flexibility,” 2015

0 10 10 91 0Years

“Cathedral” Photovoltaics

0 10 20 30 40 50 60 70 8

0 GW-y1 GW-y3 GW-y6 GW-y10 GW-y15 GW-y21 GW-y28 GW-y36 GW-y45 GW-y0 GW-y3 GW-y1 GW-y2 GW-y

French windpower output, December 2011: forecasted one day ahead vs. actual

Variable Renewables Can Be Forecasted At Least as Accurately as Electricity Demand

Source: Bernard Chabot, 10 April 2013, Fig. 7, www.renewablesinternational.net/wind-power-statistics-by-the-hour/150/505/61845/, data from French TSO RTE

GW

0

0.51

1.52

2.53

3.54

4.55

!10% Downtime

!12% Downtime

0

10

20

30

40

50

60

⽇日

1 2 3 4 5 6 7

テキサス電⼒力信頼度協議会（ERCOT）電⼒力プール、テキサス州における2050年夏の1週間、（RMI  による時間ごとのシミュレーション）

変動する再⽣生可能エネルギーの計画的発電  

地熱など

冷暖房空調HVAC ice/EV貯蔵

バイオマス・バイオガス

貯蔵リカバリデマンドレスポンス

太陽 (25 GW)⾵風⼒力 (37 GW)

損失電⼒力(~5%)

GW

当初負荷量効率向上後の負荷

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

Wind (37 GW)

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

Solar (25 GW)Wind (37 GW)

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

Solar (25 GW)Wind (37 GW)

Geothermal etc.

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

Solar (25 GW)Wind (37 GW)

Geothermal etc.Biomass/biogas

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Geothermal etc.

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

HVAC ice/EV storageBiomass/biogas

Solar (25 GW)Wind (37 GW)

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Geothermal etc.

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

HVAC ice/EV storageBiomass/biogas

Storage recovery

Solar (25 GW)Wind (37 GW)

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Geothermal etc.

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

HVAC ice/EV storageBiomass/biogas

Storage recoveryDemand response

Solar (25 GW)Wind (37 GW)

Original loadLoad after efficiency

0

10

20

30

40

50

60

GW

Day

1 2 3 4 5 6 7

Geothermal etc.

Choreographing Variable Renewable GenerationERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)

HVAC ice/EV storageBiomass/biogas

Storage recoveryDemand response

Solar (25 GW)Wind (37 GW)

Spilled power (~5%)

Europe, 2014 renewable % of total electricity consumed

Choreographing Variable Renewable Generation

27%Germany (2013 peak 70%)

59%Denmark (33% wind; 2013 windpower peak 136%—55% for all December)

50%Scotland

46%Spain (including 21% wind, 14% hydro, 5% solar)

64%Portugal (peak 100% in 2011; 70% for the whole first half of 2013, incl, 26% wind & 34% hydro; 17% in 2005)

Grid flexibility supply curve cost

efficient use

demand response

(all values shown are conceptual and illustrative)

accurate forecasting

of wind + PV

diversify renewables by

type and location

dispatchable renewables and

cogeneration

bulk storage

fossil-fueled

backup

distributed electricity storage

thermal storage

ability to accommodatereliably a large share of variable renewable power

1980

Denmark’s transition to distributed electricity, 1980–2012Central thermalOther generationWind turbines

2012

Source: Risø

Utility revenues$

New financial and business models

Regulatory shifts

The German exampleSh

are

pric

e ($

/sha

re),

Euro

pean

Util

ities

Sha

re P

rice

50

70

90

110

130

150

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Source: Morgan Stanley Capital International

European utilities lost $500

billion market cap in 6 years

The German example

Price > CostValue >

1900: where’s the first car?

Easter Parades on Fifth Avenue, New York, 13 years apart

1913: where’s the last horse?

Images: L, National Archive, www.archives.gov/research/american-cities/images/american-cities-101.jpg; R, shorpy.com/node/204. Inspiration: Tona Seba’s keynote lecture at AltCar, Santa Monica CA, 28 Oct 2014, http://tonyseba.com/keynote-at-altcar-expo-100-electric-transportation-100-solar-by-2030/

?

0 1 2 3 4 5 6 7 8

May 2015

SolarCity

Exelon

A new and old utilityIn

dexe

d st

ock

mar

ket p

rice

(13

Dece

mbe

r 201

2 =

1)

12 December 2012(SolarCity’s IPO)

$6b market cap

$34b market cap

29 June 2010(Tesla’s IPO)

May 2015

Tesla

0

2

4

6

8

10

12

14 A new and old automaker

General MotorsInde

xed

stoc

k m

arke

t pric

e(3

0 Ju

ne 2

010

= 1)

$30b market cap

$57b market cap

50 thousand cars per year

8 million cars per year

33

WHERE WOULD YOU INVEST YOUR MONEY?

OR

34

WHERE WOULD YOU INVEST YOUR MONEY?

OR

From the Age of Carbon to the Age of Silicon

Japanese frogs jump too!⽇日本の蛙も飛躍する！  

The old pondfrog jumps inplop

—Bashō, 1686

Japan  can  lead  this  global  energy  hiyaku  (飛躍)  

⽇日本は、世界のエネルギーの飛躍を牽引することができる