Disruptive エイモリー B. ロビンス Electricity ロッキーマウンテン ... · 2017. 11....

Amory B. LovinsCofounder and Chief Scientist

© 2016 Rocky Mountain Institute

東京、︑､2016年09⽉月09⽇日 REF, Tōkyō, 9 September 2016

RO

CKY MOUNTAIN

INSTIT UTE

WAR R O O M

CARBON

Disruptive Electricity Futures ⾰革命的な電⼒力事業の未来

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

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

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!

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)

Utility revenues

Efficiency Distributed renewables

Storage (including EVs)

Flexible demand

New financial and business models

Regulatory shifts

Customer preferences

Integrative design

$

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 range

wind PPAs

utility-scale solar PPAs

leve

lized

201

4 U

S$/M

Wh

**

lowest unsubsidized world bids

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

International Energy Agency global wind and solar forecastsCumulative GW installed

0

500

1,000

1,500

2,000

2,500

3,000

2000 2005 2010 2015 2020 2025 2030 2035 2040

WEO 2002WEO 2004WEO 2006WEO 2008WEO 2010WEO 2012WEO 2014WEO 2015actualBNEF forecast

Wind Solar

0

500

1,000

1,500

2,000

2,500

3,000

2000 2005 2010 2015 2020 2025 2030 2035 2040

5x upward revision since

2000

14x upward revision since

2000

Source: IEA WEO, BNEF (forecast from June 2015), slide inspired by Michael Liebreich’s 2016 BNEF Summit keynote

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

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 (2015 peak 78%)

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

CHP

bulk storage

fossil-fueled

backup

distributed electricity storage

thermal storage

ability to accommodatereliably a large share ofvariable renewable power

!

Source: NERC 2009 LTRA p 72

Best resources far away, or adequate resources nearby?舍近求远还是就地取材

Best resources far away, or adequate resources nearby?

舍近求远还是就地取材

150 W/m2, 140m150 W/m2, 110m210–320 W/m2, 80m400 W/m2, 80m

2008 2013 2013 2015

2008–15: TWh/y +67%US Department of Energy,

Enabling Wind Power Nationwide, May 2015, DOE/EE-1218

Best resources far away, or adequate resources nearby?

舍近求远还是就地取材

US Department of Energy, Enabling Wind Power Nationwide,

May 2015, DOE/EE-1218

1980

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

2012

Source: Risø

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

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

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. The utility loses nearly all its windfall and most of its ordinary revenue.

AC

DHW

Dryer

Other

Solar PVAC

DHW

Dryer

Other

Solar PVEV-charging

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

Rapid Growth of Electrified Cars!

Source: Tom Randall (Bloomberg), “Here’s How Electric Cars Will Cause the Next Oil Crisis,” 25 Feb 2016, http://www.bloomberg.com/features/2016-ev-oil-crisis/; see also RMI, “Electric Vehicle Charging as a Distributed Energy Resource,” in press, spring 2016

U.S. EV sales flattened—but global sales are growing ~60%/y, and at least four ways to accelerate that growth are emerging

158%+$5T 0in savings(2009 $,net present value,private internal cost)

bigger GDP oil, coal, nuclear

trillio

n 20

09 $

14

15

16

17

2010 2011 2012 2013 2014 2015

RFActual

TWh/

y

0

200

400

600

2010 2011 2012 2013 2014 2015

RFActual

Renewable Electricity Generation

GDP

kg o

f Sta

ndar

d C

oal

Equi

vale

nt /

GD

P

0.19

0.21

0.23

0.25

2010 2011 2012 2013 2014 2015

RF Actual

Primary Energy Intensity

kWh

/ 200

9 $

GD

P0.21

0.23

0.25

0.27

2010 2011 2012 2013 2014 2015

RFActual

Electric Intensity

2010–2015 U.S. progress toward Reinventing Fire’s 2050 goalsActuals (USEIA) are not weather-adjusted. Reinventing Fire progression based on constant exponential growth rate.

Solutions to：

⾯面向2050年能源消费和⽣生产⾰革命路线图研究

587%+RMB22T 38%in savings经济节约

bigger GDP经济规模

less carbon碳排放减少

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

From the Age of Carbon to the Age of Silicon

Japan  can  lead  this  global  energy  hiyaku  (⾶飛躍)  

⽇日本は、︑､世界のエネルギー業界の⾶飛躍を牽引することができる

Japanese frogs jump too!⽇日本の蛙も⾶飛躍する！  

The old pondfrog jumps inplop

—Bashō, 1686, 松尾芭蕉

古池 蛙⾶飛び込む ⽔水の⾳音