Relative deployment rates of renewable and nuclear power: a cautionary tale of two metrics

Amory B. Lovins, Titiaan Palazzi, Ryan Laemel, and Emily GoldfieldRocky Mountain Institute (www.rmi.org)

22830 Two Rivers Road, Basalt, CO 81621, USA, ablovins@rmi.org

Supplementary materials

1. Spreadsheet with supporting data and analysis for our main paper’s Figs. 1 and 22. Global capacity and output additions3. Some other misleading statements in Cao et al.’s response 4. Additional conservatisms in our paper5. Graphical comparisons of technology deployment rates

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1. Spreadsheet with supporting data and analysis for our main paper’s Figs. 1 and 2

Fig. 1: The Excel spreadsheet presenting our analysis and documenting its sources is at

https://doi.org/10.1016/j.erss.2018.01.005, with six tabs:

1. Fig. 1’s 1971–2016 net output data (TWh/y) from what we consider the

best available data sources (listed) available at mid-September 2017. Coal-

(1) and gas-fired (2) net generation data before 2015 are from the

International Energy Agency’s (IEA’s) World Energy Balances 2015 and

2016, and for 2015–16 (for which IEA data are not yet available) from

Enerdata, which matches previous IEA data within 1% and lists 925 TWh

of 2016 ungraphed oil-fired generation. Renewable output comes from

Rocky Mountain Institute’s annually posted Micropower Database (3),

compiling the best industry sources and checking for any significant

discrepancies between them. We use BP data for wind and PV because

they agree well with the limited global data available (chiefly from trade

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associations). We use Bloomberg New Energy Finance’s online database

for the capacities and estimated capacity factors of geothermal, biomass/

waste, and small hydro (cross-checking geothermal against REN21 and

capacity factors against a variety of standard sources). Our pre-1999

hydropower data may not include some or all small hydro (≤50 MW),

since small and large hydro were not previously distinguished by any data

source known to us.

2. Fig. 1a’s (below) comparable data using Cao et al.’s BP data source (2017

edition to include 2016 data) wherever possible, i.e. for all renewables

except small hydro and for nuclear power throughput, but correcting

nuclear output from BP’s gross convention to net (production sent out to

the transmission grid) for comparability with renewable output, which is

expressed in net terms (as we confirmed by comparing BP with several

major producers’ government data, such as US and Germany). The 5.46%

adjustment is an average IAEA net / BP gross ratio sourced in cell A27.

3. Ratio of BP to best-data (Fig. 1a to 1) outputs for six sources.

4. Chart of data in tab 1.

5. Chart of data in tab 2.

6. Analysis underlying our main paper’s Fig. 2, citing sources—Cao et al.’s

BP data source (2017 edition) except the Chinese and Bloomberg sources

shown for small hydro, which BP aggregates with big hydro.

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The jump in renewable output in 2000 has two causes: the Bloomberg New Energy

Finance (BNEF) small-hydro data series begins, and there is apparently a greater

inclusion of some data in the geothermal/biomass/other renewables category starting in

2000. This slight rise can be seen in the spreadsheet’s orange, purple, and green bars by

toggling between tabs 4 and 5, both including the same aqua small-hydro BNEF data.

Figs. SM-1 (left) and SM-2 (right). On the left, repeated for convenient comparison, is

our main paper’s Fig. 1 using the best available data. On the right is the same graph

redrawn using Cao et al.’s data source (BP) except for the three curves BP doesn’t show

—small hydro, coal, and gas. As is visually apparent (data are in our spreadsheet), using

BP instead of our best available data sources decreases renewable output, while the

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nuclear net outputs are not materially different. Below we will compare 1-, 3-, and 10-y

maximum growth rates for these two sets of data sources.

Though we have been unable to determine the sources of BP’s nuclear (or other) data, the

International Atomic Energy Agency has advised us that its own PRIS database’s nuclear

output data should not be relied upon before 2005 due to incomplete data reporting by

Member States, so BP’s data, however sourced, at least offer the presumed virtue of

internal consistency pre-2005. Starting in 2005, nuclear output in Fig. SM-1 uses IAEA-

PRIS data and SM-2 uses BP data. Both graphs use BP nuclear output data before 2005,

identically corrected from gross to net output for fair comparison with other sources.

Toggling between tabs 4 and 5 shows an [immaterial] difference between BP and IAEA

data in 2009–10 but not otherwise.

One material adjustment to the BP data in all years is necessary for proper comparison

between nuclear and renewable outputs. BP reports gross nuclear generation, as stated in

its methodology and confirmed with its statisticians some years ago. Typical US nuclear

plants use ~4.1% of their own gross output (4); that should be globally fairly represen-

tative because most reactors are of US or derivative design. However, based on year-by-

year comparisons with net output to grid from the IAEA-PRIS database (as stated in its

User’s Handbook) for the 12 years in which the latter is completely reported (2005– ),

BP’s adjustment from net to gross generation fluctuates slightly around a mean of

1.0546%. We apply this factor throughout (dividing gross output by 1.0546) to convert

the BP data to net output, so 237 TWh of 1984–5 growth in global gross nuclear output at

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the busbar (5) would correspond to 225 net TWh sent out to the grid. In contrast, modern

renewables’ output is conventionally expressed net-to-grid; the difference is negligible

except in biomass and waste combustion, which are small terms. We could not estimate

any small potential gross-to-net adjustments in BP’s biomass-and-waste terms because

those are aggregated both with each other and with geothermal output. Instead, we

confirmed from official national data (e.g. for the US and Germany) that our “best data”

sources in Fig. 1 do show net output for all renewables, and that those net figures closely

match the BP data. Indeed, the BP dataset tends if anything to understate its aggregated

geothermal/biomass/waste term compared to other authoritative sources.

In 2016, modern renewables achieved a global share of 10.6%, vs. nuclear’s 10.5%, of

BP gross generation; Bloomberg New Energy Finance (BNEF) and UNEP give the

former figure as 11.3% of net generation (6) (1.06× nuclear), and at mid-2017, 12% (7).

Fig. 2: The 2015 BP data shown in our spreadsheet were published 53 days before our

main paper’s ref. 9, whose second graph’s data stop at 2014. The 2016 BP data shown

here, published ten months after ref. 9, differ immaterially from official national sources:

BP’s German renewable output, 188.4 TWh, is 0.1 TWh above the official total including

BP’s and EBAG’s 21.0 of hydropower (8). BP reports 403.2 TWh of gross generation by

adding a nominal 5.0% to the official French nuclear net generation of 384 TWh (9,10).

BP’s 213.2 TWh of Chinese [gross] nuclear output is 0.5 TWh above the official 212.7

TWh (11). BP’s Chinese nonhydro renewable [gross] output of 641.6 TWh (wind 241

TWh and central plus distributed solar 66.2 TWh) matches the official data (id.) and

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includes biomass, wastes, and geothermal gross generation of 73.5 TWh not officially

reported, but does not include small hydro (using the now-widely-used Chinese definition

of ≤50 MW), which we obtained from Bloomberg New Energy Finance’s subscriber

database, estimating 2016 output by applying BNEF’s 2016/2015 capacity growth to

BNEF’s 2015 reported output. “Modern renewables” include small hydro, which BP

doesn’t differentiate from big (>50 MW) hydro; for 2016 we adjust 2015 output for

2016/15 capacity growth, both from BNEF.

Some small countries do show steeper growth in percentage or per-capita terms (e.g.

Belgian or Swedish nuclear vs. Danish or Portuguese renewables), but we graph absolute,

not per-capita, TWh/y to fit global decarbonization goals. For comparison, France’s

renewable generation passed fossil-fuel generation in 2014 and in 2016 was 19.6% of

weather-normalized consumption, 17.5% of total generation, or half the German

renewable output graphed. Germany’s nuclear generation peaked at 171 TWh in 2001

and fell to <100 after 2010 (85 in 2016), heading for zero by 2023. German hydropower

is 5.4 GW pumped storage, 1.1 GW >50 MW, the rest small.

Improper selection of countries in graph S2

The 13 countries (plus California) selected for Cao et al.’s per-capita analysis and shown

in their graph S2 omit others inconsistent with their case. Illustrating this, we examined

five small countries well-known as world leaders in deployment of nonhydro renewables:

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Portugal was 47% renewably powered in 2015 (and 57% in 2016) (12). Cao et

al.’s BP data source shows that Portugal’s nonhydro renewables added ~1,180

kWh/capita-y (13). That’s 10× greater than their graph S2’s highest (Danish) so-

lar-plus-wind output growth per capita. It even exceeds their highest nuclear out-

put growth per capita (Sweden 1976–86, adding 54 TWh/y or 640 kWh/capita-y).

Even more strikingly, Scotland, 58% renewably powered in 2015, grew its non-

hydro renewable output from 1.874 TWh in 2005 to 16.166 TWh in 2015 (14) as

population grew from 5.01 to 5.37 million. That increase of 2,641 kWh/capita-y

dwarfs Cao et al.’s best renewable and nuclear cases by 22.3× and 4.1× respec-

tively.

Ireland similarly grew its windpower output alone by 5.458 TWh during 2005–15

(15), or 1,137 kWh/capita-y—9.1× and 1.8× Cao et al.’s best renewable and

nuclear cases respectively.

Costa Rica in 2015 was 99% renewably powered, including 44% by modern

renewables, which have grown impressively (16). In the 9-year interval 2006–

2015 shown by BNEF’s subscriber database, Costa Rica added 0.56 TWh/y of

nonhydro renewable output (37% growth), or 76 kWh/capita-y using Cao et al.’s

population data source (their ref. S5). That would rank in the middle of their

renewable examples. But small-hydro output growth was even larger (0.85 TWh/y

or 135 kWh/capita-y), exceeding large-hydro growth of 0.53 TWh/y. Modern

renewable growth was thus 1.9 TWh or 211 kWh/capita-y, exceeding all of Cao et

al.’s renewable examples and six of their nine nuclear examples.

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Iceland (17) in 2015 was 99.8% renewably powered (27% without hydro), and in

2016 had the world’s highest nonhydro renewable capacity per person. It achieved

2005–15 per-capita nonhydro renewable growth of 9.6 kWh/capita-y, at the small

end of Cao et al.’s Fig. S2 renewable growth examples—similar to China, with a

population as vast (1.4 billion) as Iceland’s is tiny (0.3 million).

These five examples reveal two things. First, it’s hard to discern why Cao et al. included

in their graph S2 four other European renewable examples (Denmark, Spain, Germany,

Italy) but not Portugal, Scotland, and Ireland—probably the countries with the most dra-

matic nonhydro renewable progress in Europe if not in the world—nor Costa Rica. (The

authors seem to have had no trouble ferreting out as obscure a nuclear growth example as

Slovakia, which wasn’t even an independent country until four years after the period they

graph.) Second, our Iceland example reemphasizes that the per-capita metric says more

about societies than technologies. Cao et al.’s per-capita metric ranks China—which in

2016 added ~45% of the world’s new solar and wind capacity—alongside Iceland,

>4,000× smaller both in population and in added nonhydro renewable TWh/y, and China

9× behind Denmark. This simply shows how irrelevant the per-capita metric is to global

decarbonization, and how remote the per-capita logic is from a useful way to compare the

speeds of different technologies.

Sources for the milestones beneath Fig. 2

Germany renewables:

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1991: The Feed-in Act (Stromeinspeisungsgesetz), adopted under Chancellor Helmut

Kohl’s coalition of the conservative Christian Democrats and the libertarian Free

Democrats, provides the first feed-in tariffs and gives renewable power grid-access

priority over nonrenewable power. 2000: Chancellor Schröder’s Red-Green coalition

government passes the Renewable Energy Act (Erneubare-Energien-Gesetz), replacing

the 1991 Act’s feed-in tariff values with new ones based on capital cost and fair return.

(Its legality under EU no-state-aid rules was upheld in the European Court of Justice in

2001, since it involves no general tax revenues.) (18)

China renewables:

1996: Implementation of the 9th Five-Year Plan (19), 2005: The Renewable Energy Law’s

first chapter explicitly prioritizes the development and the usage of renewable energy

(20).

China nuclear: 1984: Set-up of nuclear safety regulator. 1985: First commercial reactor

(Qinshan 1) ordered. 1991: Same commissioned. 2011: Major government acceleration

(December policy of National Energy Administration) (21,22).

France nuclear:

1945: Creation of the Commissariat à l'Énergie Atomique (CEA) (ÉdF came in 1946)

(23). 1959: First commercial >100 MW plant (Chinon A2) ordered (24). 1965: First

commercial >100 MW plant (Chinon A2) becomes operational. 1974: Messmer Plan

(‘tout-éléctrique, tout-nucléaire’) adopted administratively (25–28).

Jacobson (29) estimates that nuclear planning-to-operation intervals globally are typically

10–19 years—far longer than the commonly reported 4–9 years of direct construction

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time, and also far longer than the typical 2–5 years planning-to-operation time of solar

and wind projects. Plant-specific data often discussed, e.g. in ref. 31, typically omit both

these project-level preparatory lead times and the institutional “windup time” required to

launch national programs as shown beneath Fig. 2. Including both further strengthens the

conclusion that Cao et al.’s comparison of relative deployment speeds is unconservative.

2. Global capacity and output additions

During 2000–16, worldwide operational nuclear generating capacity rose 42 GW to total

392 GW (30). (IAEA includes ~35 “operational” GW in Japan that by the end of 2016

had been shut down for a capacity-weighted average of 5.2 y, many with dubious restart

prospects. The authoritative independent digest (31) reclassifies these into a long-term

outage category that fits IAEA definitions but Japan rejects, so IAEA counts “operation-

al” capacity at 23 Aug 2017 as 391 rather than 356 GW.) Actually operating global

nuclear capacity was ~8 GW lower in 2016 than in 2000 if long-term-outage capacity is

excluded. Even including it, though, WNISR 2017 (32) (p. 182) finds 2000–16 capacity

growth was 36 GW nuclear, 301 solar, and 451 wind.

Gross nuclear capacity additions must not be confused with net additions because, as of

23 Aug 2017, 65 GW of nuclear capacity, equivalent to 18% of actually operational

capacity, have already been permanently closed, as this World Nuclear Association graph

shows:

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Fig. SM-3. Global 1980–2016 nuclear grid connections and shutdowns according to the

World Nuclear Association (33). WNA assumes that the >30 GW of units now in long-

term shutdown, chiefly in Japan, remain operable (as does IAEA) but are “not

generating.”

There is no material parallel in closures of nonhydro renewables, though considerable

wind repowering (replacing old turbines with better and taller ones) is now underway

(34), analogously to the 7.4-GW total authorized upratings of older nuclear capacity.

Some old US hydroelectric dams are also being deconstructed, partly for safety reasons,

though their total capacity keeps rising. DOE reports that 1.4 GW of the 80.0 GW of US

hydropower capacity was retired during 2002–17, mostly as part of repowering projects

that maintained or increased capacity, while 52 relatively small generators totaling 283

MW were retired without replacement (35).

World nuclear capacity grew fastest in 1985, adding 31 net GW (less 4 GW of long-term

shutdowns and closures). Yet in their peak years so far, modern renewables added up to

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4.5× more new capacity—using BNEF data, 91 GW in 2012, 93 in 2013, 106 in 2014,

128 in 2015, 136 in 2016 (later revised (36) to 138.5 GW or 55.3% of global additions).

In 2016, wind added 55 and PV 77 GW—respectively 6× and 9× the 2016 nuclear

capacity net addition.

Vendors, utilities, and investors tend to compare additions of generating capacity, but

decarbonization depends on TWh generated—typically less per kW of capacity for

modern renewables. Their global capacity factor (output divided by full-time, full-power

theoretical potential) averaged 44% in 2016 (ref. 3), vs. 76% for nuclear power (IAEA-

PRIS), or ≥90% for the best modern reactors. (The World Nuclear Association calculates

80.5% (37) by omitting all reactors inoperable for the year, notably the >30 GW on long-

term if not permanent shutdown in Japan.) Thus 2016 wind-plus-PV net output growth

was 6× nuclear net output growth, rising to 6.8× if other modern renewables are included.

In their respective greatest growth years, modern renewables’ net output rose 48% more

(by ~336 TWh/y in 2016) than nuclear’s (by ~226 TWh in 1985, though in 2015, they

tied as modern renewables grew 227 TWh); in their respective fastest decades (2006–16

vs. 1979–89), by ~44% more. Three-year periods behaved similarly. (We elaborate these

various timescales graphically below.) Even from 1997—the year of the Kyōto Protocol

—through 2015, Cao et al.’s last data year, their ref. S1’s gross global annual output rose

830 TWh from windpower, 375 from geothermal, biomass, and other nonhydro renew-

ables (chiefly waste combustion), 252 from solar, and an unstated but large amount for

small hydro, vs. just 186 from nuclear power.

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According to the most authoritative market data (38), big hydro (>50 MW) meanwhile

rose 308 GW to 946 GW, and all other (“modern”) renewables rose 933 GW to 1,100

GW, comprising 466 GW new wind, 311 GW new PV, and 156 GW others —solar-

thermal-electric (5 GW), geothermal (7 GW), small hydro (72 GW), and biomass/waste

(72 GW). Natural-gas-fired net capacity rose 563 GW to 1,461 GW through 2015. BNEF

projects a further modern-renewables addition of 307 GW in 2017–18.

3. Some other problematic statements in Cao et al.’s response (ref. 11 in our main

paper)

a. In 1983–84 (with emphasis added), “almost twice as many kilowatt-hours per capita

were added by nuclear power as were added by wind and solar combined in 2015—the

peak year [so far]….” Globally, 1983–4 nuclear output rose 212 TWh/y net (from BP’s

224 gross), vs. 2015 wind and solar’s combined net 175 or, says BNEF, 240 for all

modern renewables. Why adjust these figures for 57% global population growth that

occurred meanwhile but that says nothing about the relative speed of technologies?

b. “[D]uring the peak decade for nuclear construction, 1979 to 1989, the world was

adding low-carbon [kWh] at a faster annual rate on average than the largest amount

added in a single year so far by either wind or solar.” True (just) through 2015, but

misleading. The 1979–89 average annual nuclear addition rate was 130.7 TWh/y gross or

124 net. In 2015 (2016), net additions were 119 (132) wind, 60 (77) solar, and 179 (209)

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for both together (BP), rising to 240 (346) for all modern renewables (BNEF). Thus in

2015, modern renewables’ output grew 2.0× as much as nuclear averaged in its peak

decade; in 2016, 2.8×. Counting modern renewable technologies singly rather than

collectively only makes them look smaller.

c. [I]n 2015, China, which has just begun a major nuclear scale-up program, added almost

as much nuclear electricity as wind and solar combined.” Sort of (~36 vs. 45 net TWh/y),

but modern renewables added 58 (and in 2016, 91, vs. nuclear’s 40 net). China launched

only 2 GW of nuclear projects in 2016 (of 3 GW worldwide, the other 1 GW being a

Chinese project in Pakistan) and none in 2017 (except a year-end construction-start

ceremony for the proposed 600-MWe Xiapu 1 demonstration fast breeder reactor, which

may or may not ever generate grid power). And while the 13th Five Year Plan’s 2020

nonhydro-renewables goal of 341 installed GW seems likely to be surpassed, the 58-GW

nuclear goal exceeds the 50.7 GW installed (31.4 including 5 connected in 2016) or under

construction (19.3, many late) at mid-2017, making that goal unachievable (main paper,

refs. 38–39). Similarly in India, windpower has outproduced nuclear since 2012 and the

Energy Minister predicted that 60–65% of total capacity will be renewable by 2023.

d. Cao et al. criticize “results for a single year,” but are responding to a critique based on

three- as well as one-year comparisons. Please see the graphical comparisons below.

e. Their Supplementary Materials (ref. 9 in our main paper) also refer to rapid recent

renewable growth “in several countries, including Germany, Denmark, and the United

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States, with the help of subsidies and other policy incentives,” but don’t mention that

such help was much larger and longer for nuclear energy (except in Denmark).

f. Cao et al. state that “Nuclear power growth in Germany during 1975–85 added low-

carbon electricity more than twice as fast as solar and wind power growth during the past

decade [to 2015].” Their BP data source, matching Energibilanzen AG’s authoritative

online “Bruttostromerzeugung in Deutschland ab 1990 nach Energieträgern” (11 Aug

2017, http://www.ag-energiebilanzen.de, Strommix), shows 2005–15 growth of 52.0 net

TWh/y windpower plus 37.4 PV, a total of 89.4. BP shows a 1975–85 increase of 114.6

gross TWh/y for German nuclear power, equivalent to 108.7 net TWh/y. Using either

nuclear figure, the output growth ratio for nuclear/(wind+PV) is not >2 as claimed but

1.28 (or 1.62 if one assumed that “the most recent decade” meant 2004–14 in a paper

whose graph S1 used the 2015 German data).

g. The authors similarly state that “nuclear additions in the U.S. in 1981–1991 added low-

carbon electricity more than twice as fast as solar and wind power growth during the past

decade.” Their BP data source shows [net] output growth in 2005–15 was windpower

174.6 + PV 38.7 = 213.3 TWh/y (or, using subsequent 2006–16 data, wind 201.9 + PV

56 = 257.9 TWh/y). BP shows 1981–91 US nuclear gross output growth of 367.8 TWh/y,

equivalent to 348.6 net TWh/y. Thus the net-output growth ratio for nuclear/(wind+PV)

is not >2 as claimed but 1.63 through 2015 (or 1.76 through 2014 or 1.35 through 2016).

4. Additional conservatisms in our paper

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a. Distributed units (<1-MW projects were about one-fourth of global 2015 and one-sixth

of 2016 renewable investments) may arguably scale faster than big ones, at least outside

China.

b. Distributed capacity and output are often undercounted, because behind-the-meter

rooftop PV is often not reported to utilities. The 21 Aug 2017 US solar eclipse was their

first opportunity (within its path) to infer that output, but the results aren’t yet reported

except by PJM, which saw rooftop solar output drop 1.7 GW, utility-scale 0.52 GW (39).

c. Modern renewables’ cost advantage (especially for PV and wind) is rapidly widening,

and their applicable scale and geography is rapidly expanding. For example, RMI’s

SHINE program, by applying its proven whole-system cost-reduction methods to

distribution-connected community-scale ~0.5–1-MW PV “power blocks,” can match or

beat utility-scale (~5–10-MW) levelized costs, ~3¢/kWh unsubsidized, in most of the US,

and can cut African minigrids’ power cost to half the best or one-fourth the average (40),

suggesting an unexpectedly large global potential.

d. Modern renewables are accelerated by forces other than cost, such as resilience,

monopoly vs. choice and local control, climate, and other environmental concerns.

e. Modern renewables are augmented by both a comparable carbon-free resource (end-

use efficiency, which in 2000–16 saved an eighth of global electricity or >1,000 GW

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(41), more than nuclear power generated) and an even larger low-carbon resource (fossil-

fueled cogeneration, ~17.8% of 2016 global generation). Together, therefore, these three

low- or no-carbon competitors to central stations—together lately winning ~$0.6 trillion

of annual global investment—outpace central thermal plants by a far wider margin than

do modern renewables alone.

f. Our analysis conservatively excludes the energy (nearly all fossil fuels) used to produce

and deliver the fossil fuels that renewable supplies displace. Jacobson et al., via

calculations based on the IEA Global Energy Balances, find this second-order term adds

~12.65% to the direct fossil-fuel displacement. However (42, p. 17, Table S3), that

intensity is considerably lower for coal—the main fuel displaced by renewable electrical

sources—than for natural gas, let alone for oil (which generates only a few percent of

global electricity but is the largest global fuel term in an all-sectors assessment). A cor-

responding second-order reduction, though different in net terms, would also need to be

calculated for fossil fuels displaced by nuclear power. We are therefore more comfortable

omitting such second-order adjustments as an explicit conservatism, along with third-

order effects from energy embodied in both renewable and nuclear energy equipment.

Fortunately, our main comparison between renewables and nuclear need not be corrected

for the IEA’s odd convention of counting renewable (primary) electricity only at its direct

heat content of 3.6 MJ/kWh but nuclear electricity at roughly three times that value—the

amount of heat produced by burning fuel in a typical fossil-fueled plant, not the resulting

output of nuclear electricity. We need not make this adjustment because the BP database

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(as noted on the last page of each year’s spreadsheet version) already incorporates it by

converting renewable electricity into oil-equivalent terms not at its direct heat content but

at its power-plant fuel-input equivalent (assuming ~37% conversion efficiency) of 4.4

MWh per metric ton oil equivalent. Cao et al.’s Fig. S1 adopts this conversion. The

question doesn’t arise elsewhere because their Fig. S1 and our analyses express

renewable and nuclear electricity in TWh, not converted to its oil primary equivalent.

5. Graphical comparisons of technology deployment rates

The variety of unjustifiable assumptions and methods in Cao et al.’s article (ref. 9 in our

main paper) makes it helpful to dissect step-by-step the discrepancies between the data in

their ref. S1 and their conclusions in our main paper’s refs. 9 and 11. Restricting

ourselves initially to their first graph’s dataset ending in 2015, rather than to their second

graph’s truncation to 2014 (42), we first compare nuclear vs. renewable technologies’

fastest 1, 3, and 10 years of deployment according to Cao et al.’s ref. S1 (BP), using

global totals that make their selected-country per-capita comparisons in their graph S2

irrelevant. Let’s start by temporarily adopting Cao et al.’s BP convention of gross nuclear

output (which we’ll correct later) in case they were unaware of it. We also end with 2015

data, the latest they had and used in their graph S1, although they inexplicably stopped

with 2014 in their graph S2, distorting its conclusions as explained in our main paper.

(Their original paper’s and Supplementary Materials’ bibliography cite BP’s 2015

database, which ends in 2014, but their graph S1 evidently used the 2016 edition, ending

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in 2015, and their response—ref. 11 in our main paper—cites the 2016 edition for a

different purpose. Below we use some later 2016 data but don't rely on them.)

The following analysis calculates the period of fastest renewable growth from the total

for the modern renewables category. Some types within that category grew faster in

particular periods that did not always coincide, so an artificial composite combining the

fastest historic growth period for each renewable technology could grow faster than the

aggregate conservatively shown.

Cao et al.’s BP database includes hydropower of all sizes combined (Fig. SM-3):

SM-3. Comparing gross nuclear output with all renewables’ net output using entirely BP

data and including both big and small hydropower.

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However, Cao et al. don’t include hydropower of any size, big or small (only BNEF

systematically distinguishes small from big hydro, and only since 2000), reducing peak

renewable growth (Fig. SM-4) by 34% over the fastest single year, 36% over the fastest 3

y, and 44% over the fastest 10 y. These large reductions cast doubt on Cao et al.’s

rationale for omitting hydropower because it has “not generally scaled as rapidly as wind

and solar and [is] not expected to do so in the future”:

SM-4. Same graph as Fig. SM-3 but excluding all hydropower. BP’s “geothermal,

biomass, and other” renewables are still included.

By omitting small and big hydro, and overstating nuclear output 5.5% through the gross-

net confusion corrected below, Cao et al. can claim that nuclear outpaces renewable

deployment on all three timescales through 2015—though barely. To try to justify their

claim of decisive and robust margins, their second graph S2 further omits the

“geothermal, biomass, and other” (chiefly combustion of industrial, agricultural, and

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municipal wastes) renewables that their graph S1 includes. This means their generic use

of “renewables” includes only the two fastest-growing major kinds of nonhydro

renewables, namely solar and windpower, and makes nuclear’s apparent slight speed

advantage become material (Fig. SM-5). That is the cramped basis for their graph S2’s

conclusion that nuclear power deploys “far faster” than generic “renewables.” (They

didn’t employ this omission in their graph S1, presumably because that graph was meant

to show what a small fraction of total energy use is met by renewables even when all

their nonhydro kinds are included.)

SM-5. Further excluding “geothermal, biomass, and other” renewables, so “renewables”

includes only net solar and wind output, makes gross nuclear output growth look faster.

Next, still using global totals for a pure comparison of technologies without getting con-

fused by national per-capita metrics, we apply successive corrective steps. These show

how the nuclear advantage shown in Fig. SM-5 shrinks and reverses as we successively

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include two omitted nonhydro renewable categories and correct the nuclear gross-net

confusion, then optionally note the further-strengthened results of including subsequent

2016 data and counting all renewables.

First, all authoritative compilations of modern renewable output (e.g., BNEF, REN21,

UN) include not only geothermal, biomass, wastes, and other terms (which are still

minor, such as the emerging marine sector) but also the substantial term of small

hydropower, conventionally defined in recent years as units ≤50 MW—the definition

long used by China, the world’s leading adopter. We therefore next add back small hydro

according to the best available database (BNEF), which measures capacity bottom-up and

project-by-project. We apply the European Association for Small Hydro’s typical 0.4

small-hydro capacity factor for 2010 in each year (subject to unknown year-to-year

smoothing errors, since few countries except China report annual output from small

hydro). We also add back the “geothermal, biomass, and other” renewables from Fig.

SM-4, using Cao et al.’s BP data shown in their graph S1 but omitted from their graph

S2. Fig. SM-6 shows how these two corrections, restoring the conventional elements of

“modern renewables,” make their growth outpace nuclear power’s growth over 3- and

10-year, though not quite 1-year, timescales:

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SM-6. Adding BNEF’s small-hydro capacity (rising from 104 GW in 2000 to 178 GW in

2016) at nominal 0.4 capacity factor, and BP’s “geothermal, biomass, and other”

renewables, restores the conventionally defined “modern renewables” total, which

outpaces fastest nuclear growth on the 3- and 10-year timescales.

However, all the foregoing comparisons use BP’s convention of inflating nuclear output

by an average of 5.5% to imputed “gross generation” including electricity used in the

plant but not sent out to the grid. In contrast, ~99.9–100.0% of the electricity generated

by modern renewables reported by BP, as well as of small hydro, is net generation sent

out to the grid, as we confirmed from major national data sources. Correcting for this

factor divides all Cao et al.’s nuclear outputs by 1.055, resulting in modern renewables’

growing faster than nuclear power on all three timescales when all technologies’ outputs

are fairly compared net-to-net (Fig. SM-7):

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SM-7. Apples-to-apples comparison of net output growth from nuclear and modern

renewables.

Next, while keeping BP’s nuclear output data through 2004, we adopt the authoritative

global data source (IAEA-PRIS) starting in 2005 when, according to IAEA, it became

reliably reported by Member States. Since the fastest nuclear growth was well before

2005, the graph remains identical to Fig. SM-7, but Fig. SM-8 shows it for completeness

in describing our “best available” data sources shown in Fig. SM-1.

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SM-8. Using BP nuclear data through 2004 but IAEA-PRIS nuclear data in and after

2005 does not change the results in Fig. SM-7.

Next, in Fig. SM-9 below, we address data-quality issues by replacing BP renewable data

with our best available industry and official data (ref. 3). Renewable-energy data sources

are a complex and evolving topic to which our organization has long paid close attention.

Unlike fuels, renewable energy can be produced anywhere, is often not subject to manda-

tory reporting (especially at smaller scale), and is seldom traded, removing major fuels’

opportunity to crosscheck global balances. Most serious analysts prefer a range of other

data sources for renewables, which were and are not BP’s primary focus of expertise and

attention. The BP database is venerable (1951– ) (44), extensive (~300k data points),

respected, conscientious, objective, public, free, online, and usefully consistent over time

and probably within countries, where BP/government relationships are often of long

standing. However, it is has no source or methodological transparency, is compiled by

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staff no longer willing to respond to scholarly inquiries, is only sketchily described, and

is historically fuel-centric. It is also well-known to understate output from some renew-

ables, particularly “geothermal, biomass, and other.” Compared to our best available data

sources, tab 3 of our spreadsheet shows an average BP underreporting of 26% for modern

renewables’ output before we add back BNEF’s small hydro, or ~9.5% after. Except in

1987, BP’s underreporting exceeded 10% until 1996, and was 2–3× during 1973–86.

Underreporting compared with what?

Our compilation in ref. 3 draws on a wide range of cited industry (including BP), govern-

ment, and international-agency sources to compile a more fully rounded picture of

renewable output from 1990 for wind and PV and from 2000 for other renewables. Of

necessity, our estimates for nonhydro renewables before 1990 are simply the residual

term of all renewables minus large hydro, both from IEA World Energy Balances,

although some small hydro may be included in the large-hydro term, as definitions were

not yet standardized. Fortunately, that doesn’t affect this analysis because those early

renewable outputs were so small.

The 2000–16 renewable underreporting by BP is in its aggregated “geothermal, biomass,

and other” category, where we take as authoritative the Bloomberg New Energy Finance

subscriber database because it reflects bottom-up, project-by-project global reporting by

~200 worldwide staff intimately engaged in each country’s and region’s market activities.

To ensure the reasonableness of our capacity and output data, we also cross-check against

some Navigant data and other proprietary databases as well as the open international

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sources (IEA, IRENA, UNEP, REN21). To avoid confusion by IEA’s odd convention

(mentioned above) of converting nuclear but not renewable electricity to its primary

equivalent, we track electrical output solely in TWh, and validate our gross-net

conventions against each database’s described methodology, including BP, BNEF, and

IAEA. Our “best available” dataset adopts BP’s output data for the two largest renewable

terms, wind and solar (where BP data respectively start in 1985 and 1989) because they

agree almost exactly with our other data sources, presumably originating from the same

national data. We also cross-check those data against official national data from major

producing countries and regional and world solar, wind, and other trade-association data.

The differences between BP and best available data are modest (Fig. SM-9 vs. SM-8) but

not zero.

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SM-9. Using the best available data sources modestly increases modern renewables’

speed advantage over nuclear power at the 3-y and 10-y timescales and slightly decreases

it over the fastest single growth year.

These successive corrections clearly reverse Cao et al.’s conclusions, as can be seen by

comparing Figs. SM-5 and SM-9.

That reversal strengthens considerably if we include subsequent 2016 data (Fig. SM-10),

enhanced by a year of secular growth undistorted by the sharp drop in 2015 US wind

capacity additions caused by Congressional meddling with tax rules:

SM-10. Through 2016, net output grew robustly faster from modern renewables than

from nuclear power on all three timescales analyzed.

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Either through 2015 or using subsequent 2016 data, and using their own BP data or the

best available data, Cao et al.’s findings about the relative output growth rates of modern

renewable and nuclear energy are unsupportable, though one must peel many layers of

the analytic onion to discover why.

For another useful perspective, Fig. SM-11 compares these technologies’ annual net

output additions:

SM-11. Peak annual addition of net output for nuclear power (1985) nearly matched

modern renewables’ (229) in 2015, but fell 12% behind in 2016

Recent net output additions from modern renewables (gray) are larger, more consistent,

and more broadly based across the world than the rapid net output growth (black) that

nuclear power achieved in 1984–85 but did not subsequently sustain. Instead, Fig. SM-11

portrays a waning, obsolete, and uneconomic nuclear technology already powerfully

overtaken by a flourishing, modern, and profitable suite of renewable technologies.

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Finally, since many of Cao et al.’s statements are generically about “renewables,” not just

modern renewables, Fig. SM-12 includes big hydro to show the “all renewables” picture:

SM-12. Peak annual addition of net output from nuclear power (1985) was considerably

smaller than recent additions by all renewables, which were 62% higher in 2016

Including big hydro further emphasizes that the cluster of gray bars at the right-hand side

dwarfs the burst of black bars in the mid-1980s, without counting the latter additions’

later reversals shown as negative black bars of increasing size and frequency. Those

nuclear retirements should, starting by 2020, overtake any conceivable nuclear additions

(45) and mark nuclear output’s irreversible decline.

This necessarily tedious step-by-step graphical analysis completes our demonstration that

Cao et al.’s evidence contradicts their conclusions, while even better and later evidence

does so even more strongly. Despite some volatility introduced by 2017–18 US political

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interference with renewable power markets, we concur with BNEF’s, IEA’s, and other

authorities’ expectation that renewable growth, driven chiefly by economic fundamentals,

will remain rapid and robust.

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