Disruptive エイモリー B. ロビンス ロッキーマウンテン研究所 Electricity 共同創設者・主任科学者 Futures Amory B. Lovins Cofounder and Chief Scientist ⾰命的な電⼒事業の未来 東京、2016年09⽉09⽇ REF, Tōkyō, 9 September 2016
O Y M UN ARBON K T C C A I O N
R
I W N E A M STIT U T R R O O
© 2016 Rocky Mountain Institute Australia national electricity market Actual vs. forecast electricity demand 260 1.8 2010 2011
240 1.6
GDP (by calendar year) 2012 220 1.4 2013
200 2015 1.2 Historical 2014
Annual electricity use (TWh) 180 1 real GDP (billion 2011 Australian Dollars) real 160 0.8 2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024
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 Index of U.S. Primary Energy Per Dollar of Real GDP Heresy Happens U.S. energy intensity 0.25 0.75 1.25 0.5 0 1
1975 Actual
1990
Foreign Lovins, 1976 Fall , airs ff A
2005
1975 ~ Forecasts, Industry and Government
2020
Reinventing Fire 2011 , Reinventing 2035 2050 U.S. buildings: 3–4× energy productivity worth 4× its cost (site energy intensities in kWh/m2-y; U.S. office median ~293)
~277➝173 (–38%) 284➝85 (–70%) ...➝108 (–63%) ...➝≤50 (–83% to –85%) 2010 retrofit 2013 retrofit 2010–11 new 2015 new
Yet all the technologies in the 2015 example existed well before 2005! LED and PV
800 300 White LED Coal-fired steam turbine, fuel cost only Oil-fired condensing, fuel cost only 700 Natural gas CCGT, fuel cost only 250 Utility-scale solar PV, total cost 600 Onshore windpower, total cost German PV residential feed-in tariff 200 500 (Seattle-like climate)
400 150 Sodium-vapor lamp (lm/W) (lm/W) (lm/W) 1965 300 100
Fluorescent lamp 200 s efficacy s efficacy s efficacy 1938 50 Halogen lamp 100 Incandescent lamp 1959 1879 US$/MWh 2011 cost, fuel or price busbar Real Lumino u Lumino u Lumino u 0 1996 1900 1950 2000 0 Years 1990 1994 1998 2002 2006 2010 2014 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 Flexible demand
Integrative Customer design preferences
Distributed Efficiency $ renewables Utility revenues
Regulatory New financial and shifts business models
Storage (including EVs) Renewable Energy’s Costs Continue to Plummet Wind and photovoltaics: U.S. generation-weighted-average Power Purchase Agreement prices, by year of signing 250
utility-scale solar PPAs 200 U.S. wholesale power price range 150 lowest unsubsidized world bids
100 levelized 2014 US $/MWh 50 wind PPAs ** 2002 2004 2006 2008 2010 2012 2014 2016 0312 GW-y “Cathedral” Photovoltaics 1015212836450136 GW-y
Years 001000 14012365897 1 International Energy Agency global wind and solar forecasts Cumulative GW installed Wind Solar 3,000 3,000 WEO 2002 WEO 2004 WEO 2006 2,500 WEO 2008 2,500 WEO 2010 WEO 2012 5x upward 14x upward 2,000 WEO 2014 2,000 WEO 2015 revision since revision since actual 2000 2000 1,500 BNEF forecast 1,500
1,000 1,000
500 500
0 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2000 2005 2010 2015 2020 2025 2030 2035 2040
Source: IEA WEO, BNEF (forecast from June 2015), slide inspired by Michael Liebreich’s 2016 BNEF Summit keynote
Variable Renewables Can Be Forecasted At Least as Accurately as Electricity Demand French windpower output, December 2011: forecasted one day ahead vs. actual
5 4.5 4 3.5 3 2.5
GW 2 1.5 1 0.5 Source: Bernard Chabot, 10 April 2013, Fig. 7, www.renewablesinternational.n 0 et/wind-power-statistics-by-the- hour/150/505/61845/, data from French TSO RTE ! !
12% Downtime 10% Downtime
Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency
30
GW
20
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30
GW
20
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW)
GW
20
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW) Geothermal etc. GW
20
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW) Geothermal etc. GW Biomass/biogas 20
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW)
GW Geothermal etc. Biomass/biogas HVAC ice/EV storage 20
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW)
GW Geothermal etc. Biomass/biogas HVAC ice/EV storage 20 Storage recovery
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW)
GW Geothermal etc. Biomass/biogas HVAC ice/EV storage 20 Storage recovery Demand response
10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation ERCOT power pool, Texas summer week, 2050 (RMI hourly simulation)
60
50
40 Original load Load after efficiency Wind (37 GW) 30 Solar (25 GW)
GW Geothermal etc. Biomass/biogas HVAC ice/EV storage 20 Storage recovery Demand response Spilled power (~5%) 10
0 1 2 3 4 5 6 7
Day Choreographing Variable Renewable Generation Europe, 2014 renewable % of total electricity consumed
50% Scotland 59% Denmark (33% wind; 2013 windpower peak 136%—55% for all December) 27% Germany (2015 peak 78%) 64% Portugal (peak 100% in 2011; 70% for the whole first half of 2013, incl, 26% wind & 34% hydro; 17% in 2005) 46% Spain (including 21% wind, 14% hydro, 5% solar) Grid flexibility supply curve (all values shown are conceptual and illustrative) cost distributed electricity storage thermal storage fossil- dispatchable bulk fueled diversify renewables and storage backup renewables by CHP type and location
efficient use ability to accommodate accurate reliably a large share of demand forecasting variable renewable power response of wind + PV Best resources far away, or adequate resources nearby?
! 舍近求远还是就地取材
Source: NERC 2009 LTRA p 72 Best resources far away, or adequate resources nearby? 舍近求远还是就地取材
2008 2013 2013 2015
400 W/m2, 80m 210–320 W/m2, 80m 150 W/m2, 110m 150 W/m2, 140m
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 Denmark’s transition to distributed electricity, 1980–2012
1980 Central thermal 2012 Other generation Wind turbines
Source: Risø Cheaper renewables and batteries change the game In 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
12" !12.00!!12" AC Dryer EV-charging Solar PV AC Dryer EV-charging Solar PV 10" !10.00!!10" DHW Other DHW Other 8" !8.00!!8"
6"
6" !6.00!!kW# kW# kW#
4" !4.00!!4"
2" !2.00!!2"
0" !"!!!!0"
Unc!Load! Smart!AC! Smart!DHW! Smart!Dryer! Uncontrolled: ~50% of solar PV Controlled: flexible load enables production is sent to the grid, customers to consume >80% of but if the utility doesn’t pay for solar PV production onsite. The that energy, how could utility loses nearly all its windfall customers respond? and most of its ordinary revenue.
Source: RMI analysis “The Economics of Load Flexibility,” 2015 Rapid! Growth of Electrified Cars
U.S. EV sales flattened—but global sales are growing ~60%/y, and at least four ways to accelerate that growth are emerging
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
$5T +158% 0 in savings bigger GDP oil, coal, nuclear (2009 $, net present value, private internal cost) TWh/y trillion 2009 $ 200 400 600 14 15 16 17 2010–2015 U.S.progress toward ReinventingFire’s 2050goals 0 Actuals (USEIA)are notweather-adjusted. ReinventingFire progression basedonconstantexponentialgrowth rate. 2010 2010 Renewable ElectricityGeneration 2011 2011 Actual RF Actual RF 2012 2012 GDP 2013 2013 2014 2014 2015 2015
kg of Standard Coal kWh / 2009 $ GDP Equivalent / GDP 0.21 0.23 0.25 0.27 0.19 0.21 0.23 0.25 2010 2010 2011 2011 Primary EnergyIntensity Primary Actual RF Actual RF Electric Intensity 2012 2012 2013 2013 2014 2014 2015 2015
Solutions to： 2050⾯向 年能源消费和⽣产⾰命路线图研究 RMB22T +587% 38% in savings bigger GDP less carbon 经济节约 经济规模 碳排放减少 Value > Price > Cost Easter Parades on Fifth Avenue, New York, 13 years apart
1900: where’s the first car? 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/ A new and old utility 8 SolarCity 7 6 5 $6b market cap 4 3 (13 December 2012 = 1)
Indexed stock market price 2 Exelon 1 $34b market cap 0 May 2015 12 December 2012 (SolarCity’s IPO) A new and old automaker 14 50 thousand 12 cars per year $30b market 10 cap Tesla 8 6 (30 June 2010 = 1) 4 8 million Indexed stock market price General Motors cars per year 2 $57b market cap 0 29 June 2010 May 2015 (Tesla’s IPO) From the Age of Carbon to the Age of Silicon Japan can lead this global energy hiyaku (⾶躍) ⽇本は、世界のエネルギー業界の⾶躍を牽引することができる
Japanese frogs jump too! ⽇本の蛙も⾶躍する！ 古池 The old pond frog jumps in 蛙⾶び込む plop ⽔の⾳ —Bashō, 1686, 松尾芭蕉