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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