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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