LAND OF THE
RISING SUN
AND OFFSHORE
WIND
The financial risks and economic viability ofcoal power in Japan

ReportOctober 2019

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A b out Ca r b on Tr a c k e r
The Carbon Tracker Initiative is a team of financial specialists making climate risk real in today’s
capital markets. Our research to date on unburnable carbon and stranded assets has started a newdebate on how to align the financial system in the transition to a low carbon economy.
www.carbontracker.org | hello@carbontracker.org

A b out t h i s n ot e
The principal authors of the report:▪
▪
▪

Matt Gray, Head of Power & Utilities, Carbon Tracker
Yukari Takamura, Professor, Institute for Future Initiatives, The University of Tokyo
Michiyo Morisawa, Director, CDP Worldwide-Japan

The principal authors were supported by Durand D’souza, Magali Joseph and Nicolás GonzálezJiménez from Carbon Tracker. The project economics model was developed by Matt Gray andDurand D’souza. The Levelised Cost of Electricity (LCOE) model was developed by Andrei Ilas who
consulted to Carbon Tracker.
The data and analytics from this note are drawn from Carbon Tracker’s Global Coal Power
Economics Model, a techno-economic simulation model which covers ~95% of global operating
capacity and ~90% of capacity under-construction. This model was developed by the Power andUtilities team from 2016 to 2019 and provides current and forward-looking estimates of the shortand long run marginal cost, operating cashflow, competitiveness relative to the LCOE ofrenewables, phase-out year and stranded asset risk in a below 2°C scenario. More information on
this data and analytics is available at Carbon Tracker’s coal economics portal.
The authors would like to thank the following individuals and organisations for peer-reviewing thereport:
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪

Miyako Enokibori, CDP Worldwide-Japan
Kae Takase, CDP Worldwide-Japan
Kentaro Tamura, Institute for Global Environmental Strategies (IGES)
Akihisa Kuriyama, Institute for Global Environmental Strategies (IGES)
Kenichi Oshima, Ryukoku University
Kimiko Hirata, Kiko Network
Dylan Tanner, Influence Map
Sriya Sundaresan, Carbon Tracker
Kate Woolerton, Carbon Tracker
Andrew Grant, Carbon Tracker
Mark Fulton, Carbon Tracker
Robert Schuwerk, Carbon Tracker

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P ow e r & Ut i l i t i e s Te a mMatt Gray – Head of Power & Utilities
mgray@carbontracker.org
Sriya Sundaresan – Senior Analyst
ssundaresan@carbontracker.org
Durand D’souza – Data Scientist
ddsouza@carbontracker.org
Magali Joseph – Analyst
mjoseph@carbontracker.org
Stefan Lavelle – Junior Data Scientist
slavelle@carbontracker.org
Isabella Soldner-Rembold – Junior Data Scientist
isoldner-rembold@carbontracker.org
Aurore Le Galiot – Associate
alegaliot@carbontracker.org
Richard Folland – Government Affairs Adviser
richard@carbontracker.org

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Table of Contents
1

Executive Summary ..................................................................................................... 42

Background .............................................................................................................. 113

Data sources, key assumptions and modelling methodologies ..................................... 16

4

Findings ................................................................................................................... 24

5

Policy recommendation ............................................................................................. 33

6

Modelling risks and revisions ..................................................................................... 34

7

Conclusions .............................................................................................................. 36

8

References ................................................................................................................ 37

9

Appendix – LCOE modelling ...................................................................................... 40

10 Disclaimer ................................................................................................................ 43

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1 Executive Summary
In this report, we analyse the financial and economic viability of new and existing coal power
investments in Japan. In doing so, it aims to shine a spotlight on the risks associated with investingand operating coal power in Japan.

1.1 Carbon conundrum: Paris alignment or coal power?
Japan’s policymaking is gradually becoming more ambitious with regards to climate change.
Examples include:▪

▪

The recent Strategic Energy Plan (SEP) stated for the first time in the history of Japan's energy
policy that renewables should become the main source of power and efforts should be madeto decarbonize the energy sector by 2050.1
The Long-term Strategy for Decarbonization (LTSD), which was approved by the cabinet andsubmitted to the UNFCCC in June 2019, states: "The Government will work to reduce CO2
emissions from thermal power generation to realize a decarbonized society and consistent
with the long-term goals set out in the Paris Agreement.”2

Despite these policy signals, Japan is still investing heavily in coal power. The nation currently has
over 11 GW of under-construction, permitted or pre-permitted coal capacity as of September 20,
2019. This capacity could have an overnight capital cost of US$29bn and would need to beclosed prematurely to remain consistent with the temperature goal in the Paris Agreement.3
Regardless of the Paris Agreement, there is a growing expectation that coal will face fierce
competition from renewable energy in the future, calling into question not only new investment
decisions but the long-term viability of the operating fleet.

1.2 The financial viability of new coal projects is highly sensitive to changing
market conditions
Carbon Tracker has developed a project finance model for every planned and under-construction
coal unit in Japan. The purpose of these models is to illustrate how, under different scenarios, acoal project could become unviable over its lifetime. In the absence of publicly available
information, we developed a breakeven scenario analysis to understand how key variables could
compromise project viability. As detailed in Table 1, assuming all else is equal4, these projects
could have a negative Internal Rate of Return (IRR) if the:▪
▪
▪

Capacity factor goes below 48%;
Total fuel price exceeds US$104/t;
Tariff falls under US$72/MWh; or

METI (2018). Cabinet Decision on the New Strategic Energy Plan. Available:
https://www.meti.go.jp/english/press/2018/0703_002.html
2
The Government of Japan (2019). The Long-term Strategy under the Paris Agreement. Cabinet decision, June 11,
2019. Available: https://unfccc.int/sites/default/files/resource/The%20Longterm%20Strategy%20under%20the%20Paris%20Agreement.pdf
3
According to the International Energy Agency (IEA), emissions reduction scenarios consistent with a well-below-2°C
temperature goal only allow for net-zero or negative emissions from the energy sector. High efficiency and CCSequipped coal are not net-zero or negative emissions technologies. IEA (2016). Energy Insights 2016. Available:
https://www.iea.org/publications/freepublications/publication/ECCE2016.pdf
4
The breakeven analysis assumes the other variables are fixed based on historical data. See Table 2 and 4 of thereport.
1

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Carbon price increases above US$25/tCO2.

For context, based on publicly available data and Carbon Tracker calculations, in 2018, the:▪
▪
▪
▪

Capacity factor averaged 73%;5Total fuel price averaged US$105/t;6Tariff prices (based on the Japan Electric Power Exchange) averaged US$87/MWh;7 andCarbon price was US$2.68/tCO2.8

OCCTO Supply Plan 2019. Available:
https://www.occto.or.jp/kyoukei/torimatome/files/190329_kyokei_torimatome.pdf
6Based on Carbon Tracker analysis. Includes the expenses incurred in buying, transporting, and preparing the coal.
See the report for all assumptions.
7
Japanese Electric Power exchange. Available: http://www.jepx.org/english/market/index.html
8Environment and Economy Division Ministry of the Environment January (2017). Greening of Whole Tax System
and Carbon Tax in Japan. Available: https://www.env.go.jp/en/policy/tax/20170130_greening.pdf
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T ABLE 1. R ESULTS OF THE PROJECT ECONOMICS MODEL FOR PLANNED AND UNDER -CONSTRUCTION COAL
UNITSForecasted Net
Present Value(NPV) (million
US$)

Lowest capacity
factor to achieve an
IRR greater than
WACC = 2.5% (%)

Highest fuelprice to achieve
an IRR greaterthan WACC =2.5% (US$/t)

Lowest tariff toachieve an IRR
greater than
WACC = 2.5%
(US$/MWh)

Highest carbon
price in 2040 toachieve an IRR
greater than
WACC = 2.5%
(US$/tCO2)

Project

Parent owner

Akita Unit 1

KEPCO,Marubeni$1,110

49%

$109

$70

$28

Akita Unit 2

KEPCO,Marubeni$1,110

49%

$109

$70

$28

Hirono IGCC

Mitsubishi (90%),
TEPCO (10%)

$539

62%

$95

$75

$21

$766

50%

$100

$73

$24

$65

59%

$85

$78

$10

Hitachinaka
Kyodo Unit 1
Kaita

JERA
Chugoku ElectricPower (50%),
Hiroshima Gas(50%)
Kobelco Power

Kobe Unit 3

Kobe 2$1,050

45%

$111

$69

$32

Kobe Unit 4

Kobelco Power
Kobe 2$1,028

44%

$111

$69

$31

$201

40%

$106

$68

$23

$1,970

42%

$121

$66

$38

$575

62%

$95

$75

$21

KushiroMisumi Unit 2

Nakoso IGCC

IDI
Infrastructures FPowerCoal Mine,
Taiheiyo
Chugoku Electric
Kouhatsu
Inc.
Power
Mitsubishi (90%),
TEPCO (5%),
Joban Joint
Power (5%)

Saijo Unit 1

Shikoku ElectricPower$1,239

42%

$125

$64

$40

Kashima Unit 2

Nippon Steel, Jpower$1,011

47%

$111

$70

$33

$1,029

44%

$112

$68

$34

$1,954

43%

$118

$67

$36

$176

57%

$87

$77

$11

Takehara New
Unit 1
Taketoyo Unit 5
Tokuyama East
Power No. 3

J-POWER

JERA
Tokuyama,
Marubeni, Tokyo
Century

Ube Unit 1

J-POWER, Ube
Industries$1,122

43%

$117

$67

$34

Ube Unit 2

J-POWER, Ube
Industries$1,113

42%

$119

$67

$34

$74

54%

$87

$77

$11

$5

48%

$76

$82

$4

$5

47%

$76

$82

$4

n/a

48%

$104

$72

$25

Yokkaichi

Yokosuka Unit 1

Yokosuka Unit 2

Average

Mitsubishi

JERA

JERA

n/a

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Source: Carbon Tracker analysis
Notes: Our project economics model is based on a number of high-level assumptions, due a lack of publicly
available data. See Table 2 and 4 as well as Section 6 of the report for the modelling assumptions and risks
associated with this analysis.

1.3 New renewables cheaper than new coal by 2022 and existing coal by 2025
There are three economic inflections points which will make coal economically obsolete relative torenewable energy:i. When new renewable energy outcompetes new or under-construction coal;ii. When new renewable energy outcompetes existing coal; andiii. When new firm (or dispatchable) renewable energy outcompetes existing coal.
Independent of an additional carbon price or more stringent air pollution regulations, the LCOE ofrenewable energy in Japan could be lower than the LCOE of coal by 2022. Specifically, the LCOE
of offshore wind, utility-scale solar PV and onshore wind could be cheaper than the LCOE of coalby 2022, 2023 and 2025 respectively.
F IGURE 1. T HE LCOE OF RENEWABLES VERSUS THE LCOE OF COAL IN J APAN

Source: Carbon Tracker analysis
Notes: the key assumptions for onshore wind include: CAPEX of US$2231/KW, O&M of 1.7% of CAPEX, capacity
factor of 26%, capacity projection of 30 GW by 2040, real WACC of 3.5%, debt equity split of 80:20, a learning
rate of 25%. The key assumptions for solar PV include: CAPEX of US$1932/KW, O&M of 1.3% of CAPEX, capacity
factor of 14%, capacity projection of 282 GW in 2040, real WACC of 3.5%, debt equity split 80/20 and learning
rate 60%. The key assumptions for offshore wind include: CAPEX of 4135 US$/kW, annual O&M costs 2.5% of

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CAPEX, capacity factor of 49%, real WACC of 4.2%, debt equity split of 75:25, capacity projection of 20 GW in
2040 and learning rate of 12%. See Table 2 and the appendix for more information.

Crucially, the LCOE of offshore wind and utility-scale solar PV could be cheaper than the long-run
marginal cost (LRMC) of existing coal plants by 2025 and 2027 for onshore wind.
F IGURE 2. T HE LCOE OF RENEWABLES VERSUS THE LRMC OF EXISTING COAL IN J APAN

Source: Carbon Tracker analysis
Notes: Upper and lower bounds for the cost of operating coal units are calculated using several scenarios. Notes:
Operating coal cost is capacity-weighted and based on long-run marginal cost, which includes fuel, variable O&M
and fixed O&M (SRMC plus fixed operating and maintenance costs). Imported coal is assumed from Australia,
Russia and Indonesia. The upper and lower bounds represent the 25% and 75% confidence intervals in the long-run
marginal cost given the variance in historical coal prices from the last 10 years. The historical mean coal price is$75/ton. See Figure 1 notes and Table 2 of the main report for other assumptions.

1.4 Without policy reform, the Japanese consumer could pay for US$71bn of
stranded coal assets through higher power prices
Our analysis shows that building coal power today equals high-cost power and fiscal liabilities
tomorrow. Japan’s planned and operating coal capacity is partially protected by regulations thatgive coal generators an unfair advantage in the marketplace. These regulations include, but are
not limited to:•

A baseload power market that includes the fixed cost of mothballed nuclear power andcould help shelter coal generators from any future carbon price exposure; and•An inefficient dispatch that prioritises nuclear before wind and solar and could lead tocurtailment of wind and solar in the future.
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These regulations are sheltering high-cost coal from significant cost declines in renewable energy.
Without policy reform, the Japanese consumer may not be receiving the lowest-cost power
possible. In our below 2°C scenario, where planned, under-construction and operating coalcapacity is forced to shut down in a manner consistent with the temperature goal in the Paris
Agreement, stranded asset risk from capital investments and reduced operating cashflows could
amount to US$71bn.9 Of this US$71bn, US$29bn could be avoided if the Japanese government
immediately reconsiders the development of planned and under construction capacity. As detailedin Figure 3, due to Japan’s current regulatory environment, this liability could result in higher
energy costs for the consumer.
F IGURE 3. H OW STRANDED COAL ASSETS COULD MATERIALISE IN THE JAPANESE ECONOMY

Source: Carbon Tracker analysis
Notes: See the main report for more information.

This scenario is consistent with government’s ambition to reduce CO2 emissions from thermal power generationconsistent with the Paris Agreement. See footnote 2.
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1.5 Policy recommendations
We offer two policy recommendations. Please note that these policy recommendations are highlevel by design.

1.5.1 Immediately reconsider planned and under construction capacityand develop a retirement schedule for the existing fleet that is consistent
with the decarbonisation goal in the Paris Agreement
If Japan intends to meet the temperature goal in the Paris Agreement, it needs to phase-out
unabated coal power by 2030.10 This reality has immediate implications for new coal investments.
Both planned and under-construction capacity will unlikely be a least-cost solution over the capital
recovery period, which is typically 15-20 years. Our analysis highlights how coal power is losing its
economic footing, independent of additional climate change and air pollution policies. As such,
Japan should immediately reconsider building new coal. Policy makers also need to provide aclear direction of travel for the existing coal fleet that is consistent with the long term
decarbonization goal of the Paris Agreement11. Japanese policymakers should develop aretirement schedule based on the LRMC of individual coal units with view to inducing smoothtransition from coal. This analysis will allow asset owners to close the higher cost units first andlower cost units last, which should help ensure the end consumer receives the lowest cost power
possible.

1.5.2 Accelerate renewable energy through non -discriminatory
regulations
Without further reform the Japanese government risks missing the economic opportunity
associated with renewable energy and locking-in high cost power. In doing so, the government
will likely further compromise energy security, public debt and economic competitiveness.
Renewable energy and other supporting technologies – such as battery storage, demand response
and high-voltage transmission – are part of a mega trend with no precedent in the 21st century.
The benefits from this mega trend will go to those governments who develop a strategy to capture
value from the rapid growth of these technologies. Japan has a long track record of technologicaland engineering prowess that means the nation is well placed to capture value from thesetechnologies as markets mature and product quality commands a price premium. Incentivising
renewables begins with seeing these technologies as an opportunity to reinvigorate the nation’s
industry and economy as well promote energy security. To execute this vision, wholesale changes
need to be made to ensure renewable capacity gets built at scale and in manner that maximises its
value to the grid. At the heart of these changes is a step change in transparency to avoid
discriminatory regulations and potential market abuse.

IEA (2017). Energy Technology Perspectives. Available: https://www.iea.org/etp/
According to the IEA: i) high efficiency coal technologies are inconsistent with the carbon intensity for power
generation under the a 2°C scenario; and ii) 85% to 95% capture rate for CCS is used for IEA modelling, leaving
residual emissions that are likely inconsistent with the long-term goal in the Paris Agreement. See: IEA (2016).
Energy, Climate Change and Environnent. 2016 Insights. Available:
https://www.iea.org/publications/freepublications/publication/ECCE2016.pdf
10
11

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2 Background
2.1 Context of the report
This report follows previous analysis by Carbon Tracker on the financial risks and economic
competitiveness of coal power globally which drew the following conclusions:▪ 42% of the global operating fleet was likely unprofitable in 2018 and 72% could be so by
2040 – independent of additional climate or air pollution policy;▪ 35% of coal capacity cost more to run than building new renewables in 2018, increasing to
96% by 2030; and▪ Coal owners could avoid US$267bn in stranded asset risk by phasing-out coal capacity.12
In this report Carbon Tracker use a series of reasonable assumptions to analyse the financial risks
and economic competitiveness associated with new and existing coal power.

2.2 Power market overview
Japan is the fourth largest consumer of power in the world behind China, the US and India.
Security of supply has historically been of upmost importance to Japan, as the nation imports foralmost all of its fossil fuel supply. Japan’s recent energy policy has been dominated by efforts toovercome the impact from the 2011 Fukushima Daiichi nuclear disaster. According to theInternational Energy Agency (IEA), the Fukushima disaster and the subsequent shutdown ofJapan’s nuclear units increased its import dependence from 80% to nearly 95% in 2010 and
resulted in power generation emissions rising by around one-quarter as it used more foreign coal,oil and gas.13
Japanese energy policy is mainly defined and implemented based on the SEP, which the Basic Act
on Energy Policy (2002) obliges the government to formulate. SEP is revised at least every three
years and is usually to be accompanied by supply and demand forecasts. The SEP was approvedby the cabinet in August 2018 and decided to maintain the previous power mix decided in 2015,
calling for nuclear energy to account for 20%-22% of power generation by 2030, with 22%-24%
coming from renewable energy sources, while coal's share will decline to 26%, gas to 27% andoil's to just 3%. This electricity mix is a basis of Japan's 2030 greenhouse gas emissions target,
which aims to reduce greenhouse gas emissions by 26% by 2030, compared with 2013 levels.14
Japan’s grid network is divided into ten areas, with each area historically having one verticallyintegrated utility that operates as a monopoly franchise, controlling generation, distribution andretail.15 Hokkaido, Tohoku and TEPCO are the eastern grids, while the western grids are
Chugoku, Kansai, Hokuriku, Chubu, Kyushu, Shikoku and Okinawa. The eastern grids have a
50Hz frequency while the western grids have a 60Hz frequency. Apart from Okinawa, nine areas
are interconnected. The inter-area connection capacity is limited. As part of electricity market

Carbon Tracker (2018). Powering Down Coal. Available: https://www.carbontracker.org/reports/coal-portal/
IEA (2016). Energy Policies of IEA Countries: 2016 Review. Available:
https://www.iea.org/publications/freepublications/publication/EnergyPoliciesofIEACountriesJapan2016.pdf
14
METI (2018). Cabinet Decision on the New Strategic Energy Plan. Available:
https://www.meti.go.jp/english/press/2018/0703_002.html
15
The country was initially divided into nine regions for integrated utilities. In 1972, when Okinawa was returned toJapan, the number of vertically integrated utilities was increased to ten. The ten vertically integrated utilities include:
Hokkaido Electric Power, Tohoku Electric Power, Tokyo Electric Power, Chubu Electric Power, Hokuriku ElectricPower, Kansai Electric Power, Chugoku Electric Power, Shikoku Electric Power, Kyushu Electric Power, and Okinawa
Electric Power. Available: https://www.emsc.meti.go.jp/english/info/public/pdf/180122.pdf
12
13

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reform, the Organisation for Cross-Regional Coordination of Transmission Operators (OCCTO)
was established in 2015 to coordinate the transmission of power between regional grids.
Japan has high reserve margins across its ten grids and thus variable renewable energy does notpose serious threats to its ten grids. Nonetheless, the spatial distribution of renewable energy
varies significantly in Japan. The overall power system in Japan only accommodates around 6% ofwind and solar, but Kyushu, a large island located in the southwest, has a higher share of variable
renewable energy and has already faced curtailment problems. On Kyushu, the instantaneous
solar PV penetration in certain periods is about 80% of electricity demand.16 This has resulted in
the development operational approaches to optimise the existing resources, including: thermal
plants, reservoir hydro and pumped storage hydropower plants.
F IGURE 4. O VERVIEW OF J APAN ’S POWER GRIDS AND THEIR INTERCONNECTORS

Source: Carbon Tracker analysis adapted from OCCTO (2019)

Nikkei Asian Review (2018). https://asia.nikkei.com/Spotlight/Environment/Japan-to-slash-fixed-prices-forsolar-power-feed-ins
16

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Prior to 2000, Japan’s retail market has been held by vertically integrated utilities who offered
regulated tariffs on a cost-plus basis, which stifled innovation in energy efficiency and demand
response. Since 2000, Japan policymakers have been deregulating its retail market to allow newentrants. These reforms were fully implemented in April 2016. According to the Agency for Natural
Resources, as of 9 of September 2019, there are 611 registered retailers.17 Retailers can secure
power by purchasing in the wholesale market, owning generation assets, signing PPAs and buying
continuous backup.18
From 2020 onwards, policymakers are requiring legal unbundling: vertically integrated utilities are
required to breakup their business in two parts – via a holding or affiliate company structure – into
generation & retailing and transmission & distribution. The separate businesses will unlikely prove
to be independent like liberalised markets in Europe, as they will remain part of the same holding
company that is listed on capital markets. To facilitate the power system reform, the government
has decided to create new markets between now and 2020. These new markets include baseload,
capacity, non-fossil fuel certificates, balancing services, interconnector capacity and gross bidding.
Figure 5 illustrates Japan’s power value chain before and after 2020.

Agency of Natural Resources (2019). Available:
https://www.enecho.meti.go.jp/category/electricity_and_gas/electric/summary/retailers_list/
18
Tariffs for users below 50kW remain regulated until 2020 unless consumers opt out. See footnote 4 for more
information. METI (2018). Available: https://www.emsc.meti.go.jp/english/info/public/pdf/180122.pdf
1713

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F IGURE 5. JAPAN ’S POWER MARKET BEFORE AND AFTER 2020

Source: Adapted from Bloomberg NEF (2017)

2.3 The role of coal and climate action beyond central government
According to Climate Analytics, between 1990 and 2016, around 90% of the rise in energyrelated emissions is explained by the increase in emissions from coal power.19 Therefore, in termsof climate policy measures, addressing emissions from coal should be a primary focus for Japan.
Despite ongoing efforts towards a cleaner power mix, coal is the dominant source of electricity in

Based on data from MOEJ and METI. Climate Analytics (2017). Science-based coal phase-out timeline for Japan.
Implications for policymakers. Available: https://climateanalytics.org/media/coalphaseout-2018-en-report_1.pdf
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Japan, producing 29%20 of total gross generation in 2017. As detailed above, according to the
SEP, by 2030 coal is still expected to generate around a quarter of power in Japan. Japan has 11
GW of coal planned and under construction. The country’s SEP, which aims to stimulate theeconomy with lowest cost energy and improve energy independence, risks being derailed by acontinued focus on coal power.
Japanese investors, corporations and local government are becoming increasingly supportive of
more ambitious climate policy. After the adoption of the Paris Agreement in 2015, financial
institutions are actively requesting company disclosure of climate-related risk. The Task force on
Climate related Financial Disclosure (TCFD) established under G20 published recommendations
for disclosure in 2017. The Government now strongly supports this initiative. As of 20 September
2019, 44 of Japanese financial institutions and 128 companies from non-financial sector
expressed its support for the recommendations of the TCFD.21
In May 2019, Tokyo Keizai reported22 that 90% of companies listed on the Tokyo Stock Exchange:▪
▪

Have implemented or are considering a science-based target consistent with thetemperature goal in the Paris Agreement.
Are requesting energy providers to supply low-carbon emission power and more than half
are requesting the Government to change the policy direction toward decarbonization
including drastic reduction or phase-out of coal.

In June 2019, 20 companies, including Apple and Sony, have requested the government increase
Japan's renewable energy target from 22-24% in 2030 to 30%.23 19 large local governments havealso made similar declarations.24

Ministry of Environment (2017). Available: http://www.env.go.jp/earth/ondanka/ghgmrv/emissions/results/JNGI2019_2-7.pdf
21
METI, (2017). TCFD. Available:
https://www.meti.go.jp/policy/energy_environment/global_warming/disclosure.html
22
Toyo Keizai Weekly No. 18 May 2019. Available: https://toyokeizai.net/sp/visual/tkp/decarbonization-survey/
23
The Climate Group (2019). Available: https://www.theclimategroup.org/news/major-companies-call-ambitious2030-renewable-electricity-targets-japan
24
City Renewable Energy Council (2019) Available: https://enekyo-city.jp/wp-content/uploads/20190730.pdf
20

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3 Data sources,
methodologies

key

assumptions

07/10/2019

andmodelling

3.1 Data sources and key assumptions
The asset-level model outputs in this analysis are based on a number of assumptions aboutcommodity prices (fuel, power and carbon), variable and fixed operations and maintenance costs(O&M) and policy outcomes (out-of-market revenues and control technologies costs, for example).
These data sources and assumptions are detailed in Table 2. For the technical definitions used inthis report see Box 1.
T ABLE 2. D ATASETS AND KEY ASSUMPTIONS USED IN THIS ANALYSISPARAMETERDETAIL

SOURCE

Inventory data on unitlevel characteristics

Unit name, plant name, plant location, unit installed capacity; unit status, yearof unit operation, parent organization, sponsor organization, combustion
technology type, coal type, heat rate, and emissions factor.

Kiko Network (2019), Global
Energy Monitor (2019)

In the absence of publicly available information we assume for the following
boiler technologies: US$/kW 2,100 for subcritical, US$/kW 2,400 for
supercritical, US$/kW 2,600 for ultra-super and US$/kW 2,900 for IGCC.

IEA (2014)

Cooling type andpollution control
technologies by plant

Installed environmental control technologies for nitrogen dioxide, sulphur
dioxide and particulate matter, as well as the type of cooling technology.

Platts (2019)

Fixed O&M

Fixed O&M assumptions depend on the combustion technology of the boiler
US$9/kW for subcritical technologies; US$12/kW for supercritical technologies;
US$13/kW for ultra-supercritical technologies; and US$21/kW for integrated
gasification combined cycle technologies (IGCC).

Carbon Tracker estimatebased on IEA (2014)

Variable O&M

Variable O&M assumptions depend on the combustion technology of the boiler:
US$5.98/MWh for subcritical technologies; US$4.79/MWh for supercriticaltechnologies; US$4.49/MWh for ultra-supercritical technologies; andUS$7.73/MWh for integrated gasification combined cycle technologies. We
also index the cost depending on the unit’s size: 133% for units 0 to 100 MW;
107% for units 100 to 300 MW and 100% for units 300 MW or more.

North America Electric
Reliability Corporation (2010)

Capacity factor

Realised annual capacity factors at the asset level for existing capacity.

Kiko Network based on METI(2019)

Fuel type, cost andtransport

Fuel costs include the expenses incurred in buying, transporting, and preparing
the coal. For the cost of coal for producers we use benchmarks from Bloomberg
LP. Estimates for 2019 are based on daily price averages, while from 2019
onwards we take an annual average from 2015 to 2019. Fuel costs also
include a model which calculates the transport of coal. This is a cost-optimised
supply route algorithm, which computes the distance between a unit’s locationand the nearest suitable coal mine, considering coal type, mode of transportand related costs and other charges, and available port, mine and import
capacities. We assume bituminous coal is imported from Australia, Indonesia
and Russia via seaborne and then land routes to plant Japan.

Bloomberg (2019), Ports.com(2018), UN Comtrade (2018),
Carbon Tracker analysis

Carbon price

US$2.68 t/CO2 based on 289 yen/tCO2 from implemented government
policy.

Environment and Economy
Division Ministry of theEnvironment January (2017)

Combustion efficiency

Gross, low heating value (LHV) adjusted for unit age.

IEA (2015) and Carbon
Tracker analysis

Efficiency adjustmentsfrom cooling andpollution controls

Adjustments made to the overall combustion efficiency of the plant dependingon the technology installed.

EPA (2018)

Environmental control
technology capital andoperational costs

These costs include fixed operations and maintenance ($/kW per year) andvariable operations and maintenance ($/MWh). Adjusted for pollutant andnameplate capacity of plant.

US EPA (2018)

Unabated coal-fired
power generation
pathway for below 2°C
scenario

We assume OECD decline rates in the IEA’s Beyond 2°C scenario (B2DS) forJapan generation.

IEA (2017), Carbon Tracker
analysis

Capital cost

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Pollution limit regulations
and associated capitaland operational costs

No changes to existing air pollution regulations assumed over the modelling
period.

Carbon Tracker analysis

Plant revenues

Japan is in the process of liberalizing its power market. The real sales price per
kWh is decided by over-the-counter trading and not disclosed to the third
parties. As a proxy for revenues we use a five-year of average day-ahead spot
prices from Japan Electric Power Exchange.

Bloomberg LP (2019)

LCOE estimates ofonshore wind, offshore
wind and solar PV

Top-down cost analysis based on high, medium and low scenarios. See the
Appendix for more information.

Carbon Tracker estimate

Discount rate for the netpresent value (NPV)

5% for the below 2°C stranded asset model.

Carbon Tracker estimate

Working cost of capital(WACC)

2.8%, 3.5% and 4.2% for the high, medium and low scenarios of the LCOE
estimates, respectively. 2.5% for project economics model.

Carbon Tracker estimate

Sources: see above and references.

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BOX 1 METRIC DEFINITIONS

Short-run marginal cost. The short-run marginal cost (SRMC) of a coal unit includes fuel, carbon(where applicable) and variable O&M (VOM) cost. Fuel costs include the cost of buying,transporting, and preparing the coal. There are different types of coal which vary in costdepending on the energy content. The transportation costs depend on whether the coal isimported from the seaborne market or purchased domestically from a nearby mine. VOM costs
vary with the use of the unit. These costs include, but are not limited to, purchasing water,
power and chemicals, lubricants, and other supplies, as well as disposing of waste. The shortrun operating cost tends to impact dispatch decisions in liberalised markets where units enter
competitive markets for the right to sell power to consumers. Liberalised markets operate in thefollowing way:
1. The grid operator forecasts power demand ahead of time.
2. The grid operator asks for bids to supply quantity of power required to meet the forecast.
Power generators typically bid at SRMC of producing the next unit of power.
3. The grid operator starts purchasing the power offered by the lowest bid operators until
they add up to the required power in the forecast. This is called the uniform clearing
price.
4. The grid operator pays all suppliers the same uniform clearing price regardless of what
they bid. In regulated markets the way coal plants are dispatched varies depending onmarket structures.
LRMC. LRMC includes SRMC plus fixed O&M (FOM) and any capital additions from meeting
environmental regulations. FOM include the expenses incurred at a power plant that do notvary significantly with generation and include staffing, equipment, administrative expenses,
maintenance and operating fees, as well as installing and operating control technologies tomeet regulations. While the SRMC governs dispatch decisions, the LRMC impacts the bottomline.
Relative competitiveness. The year when the LCOE of either onshore wind or solar PV is lower
than the LRMC of coal capacity.
Gross profitability. Revenues from in-market (i.e. wholesale power markets) and out-of-market(i.e. ancillary and balancing services and capacity markets) sources minus the LRMC.
Below 2°C scenario retirement year. The year when the unit should be retired to be consistent
with the temperature goal in the Paris Agreement. The retirement schedule is determined basedon the long run marginal cost or gross profitability. See Section 3.2.3 Below 2°C scenario
model for more information.
Below 2°C scenario stranded asset risk. The potential revenues lost from shutting the unit
prematurely in accordance with the retirement year mentioned above. See Section 3.2.3 Below
2°C scenario model for more information.
Stranded asset. A fossil fuel energy and generation resources which, at some time prior to theend of their economic life (as assumed at the investment decision point), are no longer able toearn an economic return (i.e. meet the company’s internal rate of return), as a result ofchanges in the market and regulatory environment associated with the transition to a lowcarbon economy.

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3.2 Modelling methodology overview
3.2.1 Project economics model
Carbon Tracker’s project economic model analyses the financial viability of planned coal capacity
and coal capacity under-construction. The purpose of this analysis to illustrate how, under different
scenarios, a coal project could become unviable over its lifetime. The main assumptions
underpinning model outputs are detailed in Table 2 and 4.
Project finance modelling assesses the risk-reward of lending to, or investing in, a coal power
project and includes a forecast of revenues, construction, operating and maintenance costs, tax,
the IRR and NPV. The NPV is the difference between the present value of cash inflows and thepresent value of cash outflows. The IRR is the discount rate that makes the NPV of all cash flows
from a particular project equal to zero.
As detailed in Figure 6, there is a coal capacity underutilisation trend occurring across the globe,
whereby coal capacity additions are outpacing coal generation.
F IGURE 6. GLOBAL COAL CAPACITY VERSUS AVERAGE GLOBAL CAPACITY FACTOR FROM 2006 TO 2018
Capacity factor (RHA)

2,500,000

Capacity (MW)

2,000,000
1,500,000

75%
70%

65%
60%

1,000,000
500,000
055%

Capacity factor (%)

Capacity (LHA)

50%
45%

Source: Global Energy Monitor, BP and Carbon Tracker analysis
Notes: Based on gross generation from BP.

A declining capacity factor is one example of how a project could become unviable over its
lifetime. The process of pouring capital into increasingly underutilised assets cannot continue
indefinitely; at some point the IRR becomes so low that debt obligations cannot be met.25 At thatstage one of two events occur: capital from projects will become stranded because debt
obligations will not be met, or the projects will start to deliver little to no IRR. Diminishing returns is
a very serious concern and should prompt governments and investors to act with conviction to stop
economically irrational coal power investments.

Unless there is a policy to compensate generators from declining capacity factors, which does occur in several
jurisdictions.
25

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To illustrate how coal power investments will lose their viability with lower levels of utilisation,
Figure 7 compares the IRR of a hypothetical coal project with different capacity factors. Since a
proportion of a coal plant’s running cost is fixed, a lower capacity factor means that fixed O&M
costs are spread over a smaller number of operating hours. This, in turn, progressively reduces the
IRR of the project. In theory, once the IRR is less than the cost of capital it becomes an unviable
project.
F IGURE 7. ILLUSTRATIVE EXAMPLE OF HOW A DECLINING CAPACITY FACTOR IMPACTS THE PROJECT IRR
IRR (%)

WACC (%)

16%
14%

IRR (%)

12%
10%
8%
6%
4%

2%
0%
85%

80%

75%

70%

65%

60%

55%

50%

45%

40%

35%

Capacity factor (%)
Source: Carbon Tracker analysis
Notes: for illustrative purposes only.

3.2.2 Relative economics model
Carbon Tracker’s transition risk model compares both the LCOE of new coal investments and the
LRMC of existing coal assets with the LCOE of onshore wind, offshore wind and utility-scale solar
PV.26 The assumptions for the LRMC and LCOE estimates are detailed in Table 2 and the
Appendix.
There are three economic inflection points that policymakers and investors need to track to provide
the least-cost power and avoid stranded assets: when new renewables and gas outcompete newcoal; when new renewables and gas outcompete operating existing coal; and when new firm (ordispatchable) renewables and gas outcompete operating existing coal. These inflection points areillustrated in Figure 8.

We acknowledge that LCOE analysis is a limited metric as it does not consider revenues from generation and thesystem value of wind and solar. According to the IEA, the best way to integrate variable renewable energy (VRE) isto transform the overall power system through system-friendly deployment, improved operating strategies andinvestment in additional flexible resources. Flexible resources include better located generation, grid infrastructure,storage and demand side integration. See: IEA (2016), Next-generation wind and solar power: From cost to value.
Available:
https://www.iea.org/publications/freepublications/publication/NextGenerationWindandSolarPower.pdf
26

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F IGURE 8. T HE INTERSECTION BETWEEN THE ECONOMIC INFLECTION POINTS AND THE POLICYMAKINGPROCESS FOR A LEAST - COST POWER SYSTEM

Source: Carbon Tracker analysis (2018)

LCOE is a standard analytical tool used to compare power generation technologies and is widelyused in power market analysis and modelling.27 While the limitations of using generic LCOE
analysis for understanding the economics of power generation have been well documented, it
does provide a simple proxy for when new investments in coal power no longer make economic
sense and when investors and policymakers should plan and implement a coal power phaseout.28 The LCOE is simply the sum of all costs divided by the amount of generation. The costs
include capital costs, the capital recovery factor, fixed O&M, variable O&M, fuel and carbon taxes.

3.2.3 Below 2°C stranded asset model
The stranded asset risk in Carbon Tracker’s 2°C scenario is defined as the difference between the
NPV of revenues in a BAU scenario and a scenario consistent with the temperature goal in the
Paris Agreement. The retirement schedules are developed based on the LRMC. Underlying thisanalysis is the logic that in the context of efforts to reduce carbon emissions and demand for coal
power, the least economically efficient will be retired first. The modelling approach involves threesteps.
Firstly, we identify the amount of capacity that is required to fill the generation requirement in the
IEA’s beyond 2°C scenario (B2DS). Under the B2DS, coal generation without carbon capture andstorage (CCS) is phased-out globally by 2040. This analysis assumes CCS will not be available to

While we recognise that other renewable options for power generation may be appropriate in some regions,onshore wind, offshore wind and utility-scale solar-PV have been chosen for comparability and simplicity.
28
LCOE analysis is a limited metric as it does not consider revenues from generation and the system value of windand solar. For more information, see: IEA (2016). Next-generation wind and solar power: From cost to value.
Available:
https://www.iea.org/publications/freepublications/publication/NextGenerationWindandSolarPower.pdf
27

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extend the lifetimes of coal capacity, as the costs will likely be prohibitively expensive.29 Regions
have different phase-out dates. For Japan, we assume a phase-out date of 2030 which is broadly
consistent with other OECD countries.30
Secondly, we rank the coal-fired generation units to develop a retirement schedule, based on theauthority, region or grid responsible for maintaining security of supply. The units are ranked basedon the LRMC. The coal units with the highest LRMC are phased-out until the aggregated asset level
generation reaches the limits set out in the B2DS.
Thirdly, we calculate the cash flow of every operating and under-construction unit in both theB2DS and BAU outcomes to understand stranded asset risk. Stranded asset risk under the B2DS isdefined as the difference between the NPV of cash flows in the B2DS (which phases-out all coal
power by 2030) and the NPV of cash flows in the BAU scenario (which includes announced
retirements in company reports or otherwise assumes a minimum lifetime of 40 years). Figure 9
provides a schematic illustration of the below 2°C stranded asset modelling methodology.

There is currently two CCS-equipped coal-fired power plant operating in the world today (Boundary Dam in
Canada and Petra Nova in the US). Due to limited progress to date and the new build and retrofit costs comparedto other decarbonisation options, this report assumes that CCS will only be viable in niche applications over the
lifetimes of the fossil fuel plants analysed, and thus is not included in this study which focuses on global averages
without subsidies. For more information see: Carbon Tracker (2016). End of the load for coal and gas? Available:
https:// www.carbontracker.org/reports/the-end-of-the-load-for-coal-and-gas/
30
For more information see: IEA (2017). Energy Technology Perspectives (ETP) 2017. Available:
https://www.iea.org/etp/
29

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F IGURE 9. SCHEMATIC ILLUSTRATION OF THE MODELLING METHODOLOGY

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4 Findings
4.1.1 Project economics of planned and under-construction coal
Japan currently has over 11 GW of under-construction, permitted or pre-permitted coal capacity.
Without a policy intervention, this capacity is likely to be operational by the early to mid-2020sand has an estimated overnight capital cost of US$29 billion.
T ABLE 3. UNDER -CONSTRUCTION AND PLANNED COAL CAPACITY IN JAPAN
Project

StatusCapacity(MW)

Boilertechnology

Estimatedstart date

Estimated capital
cost (million US$)

Akita Unit 1

Permitted

650

Ultra-super

2024

1,690

Akita Unit 2

Permitted

650

Ultra-super

2024

1,690

Hirono IGCC

Construction

540

IGCC

2021

1,134

Hitachinaka Kyodo Unit 1

Construction

650

Ultra-super

2020

1,690

Kaita

Construction

112

Subcritical

2021

291

Kobe Unit 3

Construction

650

Ultra-super

2021

1,690

Kobe Unit 4

Construction

650

Ultra-super

2022

1,690

KushiroConstruction

112

Ultra-super

2020

235

Misumi Unit 2

Construction

1000

Ultra-super

2022

2,600

Nakoso IGCC

Construction

540

IGCC

2020

1,134

Saijo Unit 1

Construction

500

Ultra-super

2023

1,300

Kashima Unit 2

Construction

645

Ultra-super

2020

1,677

Takehara New Unit 1

Construction

600

Ultra-super

2020

1,560

Taketoyo Unit 5

Construction

1070

Ultra-super

2022

2,782

Tokuyama East Power No. 3

Construction

300

Subcritical

2022

780

Ube Unit 1

Pre-permit

600

Ultra-super

2026

1,560

Ube Unit 2

Pre-permit

600

Ultra-super

2026

1,560

Yokkaichi

Pre-permit

112

Subcritical

2019

235

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Yokosuka Unit 1

Construction

650

Ultra-super

2023

1,690

Yokosuka Unit 2

Construction

650

Ultra-super

2024

1,690

Total

n/a

11,281n/a

2021

28,679Source: Global Energy Monitor (2019), Kiko Network (2019), IEA (2014) and Carbon Tracker analysis

The main assumptions we use are presented in Table 4 below.
T ABLE 4. M AIN ASSUMPTIONS USED FOR THE PROJECT ECONOMICS MODEL
Parameter

DetailSourceCapital cost

In the absence of publicly available information we assume for thefollowing boiler technologies: US$/kW 2,100 for subcritical, US$/kW
2,400 for supercritical, US$/kW 2,600 for ultra-super and US$/kW 2,900
for IGCC.

IEA (2014)

Fuel price2014 to 2019 weighted average of Australian, Indonesia and Russiancoal. See Table 2 for transport algorithm.

Bloomberg (2019), Ports.com(2018), UN Comtrade (2018),
Carbon Tracker analysis

Average capacity factor based on realised annual capacity factors at theasset level for existing capacity.

Kiko Network based on METI(2019)

Revenues

As a proxy for revenues we use a one year of average day-ahead spot
prices from Japan Electric Power Exchange.

Bloomberg (2019)

WACC

2.5%

Carbon Tracker estimate

Discount rate

2.5%

Carbon Tracker estimate

Tax rate

27%

OECD (2019)

Debt to equity ratio

Due to a lack of publicly available information we use a 80:20 debt toequity ratio.

Carbon Tracker estimate

Capital allowances

Straight-line depreciation of equipment and building over 15 years and38 years, respectively. Assume that power equipment represents 50% of
capital costs and the building represents 11%.

Japan Ministry of Finance(2019), US Dept. of Energy(2008)

Capacity factor

Source: See table.
Notes: for other assumptions see Table 2.

The results of the project economics model are presented in Table 5. The results include a scenario
analysis of the three most important variables: capacity factor, fuel price, tariff price and carbon
price. If the capacity factor goes below 48%, the fuel price goes higher than US$104/t, the tariff islower than US$72/MWh, or the carbon price goes higher than US$26/tCO2, then these projects
could become unviable. If these projects become unviable it could leave consumers, taxpayers
and/or investors at risk.

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T ABLE 5. R ESULTS OF THE PROJECT ECONOMICS MODEL

Project

Parent owner

Akita Unit 1

KEPCO,Marubeni

Akita Unit 2

KEPCO,Marubeni

Hirono IGCC

Mitsubishi (90%),
TEPCO (10%)

Hitachinaka
Kyodo Unit 1
Kaita

JERA

KobeUnit 3
KobeUnit 4

Kobelco Power
Kobe 2

Kushiro

IDI Infrastructures
F-Power

Misumi Unit 2

Chugoku ElectricPower

Saijo Unit 1
Kashima Unit 2

Nippon Steel, Jpower

Taketoyo Unit 5

Ube Unit 1

J-POWER, Ube
Industries

Ube Unit 2

J-POWER, Ube
Industries

Yokosuka Unit 2
Average$1,110

49%

$109

$70

$28

$1,110

49%

$109

$70

$28

$539

62%

$95

$75

$21

$766

50%

$100

$73

$24

$65

59%

$85

$78

$10

$1,050

45%

$111

$69

$32

$1,028

44%

$111

$69

$31

$201

40%

$106

$68

$23

$1,970

42%

$121

$66

$38

$575

62%

$95

$75

$21

$1,239

42%

$125

$64

$40

$1,011

47%

$111

$70

$33

$1,029

44%

$112

$68

$34

$1,954

43%

$118

$67

$36

$176

57%

$87

$77

$11

$1,122

43%

$117

$67

$34

$1,113

42%

$119

$67

$34

$74
$5

54%
48%

$87
$76

$77
$82

$11
$4

$5
n/a

47%
48%

$76
$104

$82
$72

$4
$25

JERA

Tokuyama East
Power No. 3

Yokosuka Unit 1

Highest carbon
price in 2040 toachieve an IRR
greater than
WACC = 2.5%
(US$/tCO2)

J-POWER

Tokuyama,
Marubeni, Tokyo
Century

Yokkaichi

Lowest tariff toachieve an IRR
greater than
WACC = 2.5%
(US$/MWh)

Mitsubishi (90%),
TEPCO (5%),
Joban Joint
Power (5%)
Shikoku Electric
Power

Takehara New
Unit 1Highest fuelprice to achieve
an IRR greaterthan WACC =2.5% (US$/t)

Chugoku ElectricPower (50%),
Hiroshima Gas(50%)
Kobelco Power
Kobe 2

Nakoso IGCC

Forecasted NPV(million US$)

Lowest capacity
factor to achieve
an IRR greaterthan WACC =2.5% (%)

Mitsubishi
JERA
JERA
n/a

Source: Carbon Tracker analysis
Notes: Scenarios assume a five-year average for the other variables. For example, the capacity factor scenarios
assume a five-year average fuel and tariff prices.

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4.1.2 Relative economics: new renewables cheaper than new coal by2022
While Japan currently has some of highest renewable energy costs in the world, it should be notedthat the cost of solar PV has declined by 74% from 2010 to 2018. 31 As detailed in Figure 10, we
expect new offshore wind to be cheaper than new coal by 2022 and new solar PV by 2023. The
government has fixed mid-term cost targets of 7 yen/kWh (~US$65/MWh) in 2025 for utility-scalesolar PV and 8-9 yen/kWh (~US$74-84/MWh) by 2030 for onshore wind.32 These official targets
are largely consistent with predicted cost trends in Figure 10. These changing cost dynamics post asignificant stranded asset risk if investors and policymakers decide to move forward with the 11 GW ofcoal capacity under-construction, permitted or pre-permit. The capital recovery period for new
investments in coal capacity is typically 15-20 years and therefore we consider these investments highrisk, as burning coal to generate power will unlikely be a least-cost option from a systems value
perspective before debt is fully amortised.
F IGURE 10. LCOE OF COAL VERSUS ONSHORE WIND , OFFSHORE WIND AND SOLAR PV IN JAPANSource: Carbon Tracker analysis
Notes: Notes: the key assumptions for onshore wind include: CAPEX of US$2231/KW, O&M of 1.7% of CAPEX,
capacity factor of 26%, capacity projection of 30 GW by 2040, real WACC of 3.5%, debt equity split of 80:20, a
learning rate of 25%. The key assumptions for solar PV include: CAPEX of US$1932/KW, O&M of 1.3% of CAPEX,
capacity factor of 14%, capacity projection of 282 GW in 2040, real WACC of 3.5%, debt equity split 80/20 andlearning rate 60%. The key assumptions for offshore wind include: CAPEX of 4135 US$/kW, annual O&M costs
2.5% of CAPEX, capacity factor of 49%, real WACC of 4.2%, debt equity split of 75:25, capacity projection of 20
GW in 2040 and learning rate of 12%. See Table 2 and the appendix for more information.

IRENA (2019), Renewable Power Generation Costs in 2018, International Renewable Energy Agency (2019).
Opinion on the Tariffs of FY2019 Onward by the Tariff setting committee (in Japanese). Available:
https://www.meti.go.jp/shingikai/santeii/pdf/20190109001_01.pdf
31
32

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4.1.3 New renewables cheaper than existing coal by 2025
Due to the deflationary trend of renewable energy we expect that, in the not too distant future, newinvestments in renewable energy will likely cost less than running coal. As illustrated in Figure 11 andTable 6, the relative competitiveness of coal-fired power depends on prevailing fuel prices. In the lower
bound fuel prices, it could be cheaper to build new offshore wind and solar PV than operate existingcoal plants by 2026. In the mid-range fuel prices, it could be cheaper to build new offshore wind andsolar PV by 2025. Finally, in the upper-bound fuel prices it could be cheaper to build new offshore
wind by 2024 and new solar PV by 2025. These results are based on a median LCOE forecast for solar
PV and onshore wind. However, it is plausible that LCOE prices will drop further. See Table 6 for morescenarios summarising these possibilities. Moreover, making coal highly dispatchable to accommodate
increased amounts of low-cost variable renewable energy increases O&M costs, exacerbating its
economic disadvantage.33
F IGURE 11. LRMC OF J APAN ’S OPERATING COAL CAPACITY VS THE LCOE OF NEW ONSHORE WIND ,OFFSHORE WIND AND SOLAR PV

Source: Carbon Tracker analysis
Notes: Upper and lower bounds for the cost of operating coal units are calculated using several scenarios. Notes:
Operating coal cost is capacity-weighted and based on LRMC, which includes fuel, variable O&M and fixed O&M(SRMC plus fixed operating and maintenance costs). Imported coal is assumed from Australia, Russia andIndonesia. The upper and lower bounds represent the 25% and 75% confidence intervals in the LRMC given thevariance in historical coal prices from the last 10 years. The historical mean coal price is $75/ton.

The IEA Clean Coal Centre estimated these costs. Hot, warm and cold starting a 500 MW coal unit could cost
$94,000, $116,000 and $174,000, respectively. Load cycling a 500 MW coal unit down to 180 MW could cost
$13,000. IEA Clean Coal Centre (2016). Levelling the intermittency of renewables with coal. Available:
https://www.usea.org/sites/default/files/Leveling%20the%20intermittency%20of%20renewables%20with%20
coal%20-%20ccc268-1.pdf
33

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T ABLE 6: T HE YEAR WHEN NEW RENEWABLES WILL BE CHEAPER TO BUILD THAN OPERATING EXISTING COAL ,ACCORDING TO A RANGE OF SCENARIOS

Solar PV LCOE

Coal LRMC

Low

Mid

High

Onshore wind LCOE

Offshore wind LCOE

Low

Low

Mid

High

Mid

High

Low

2025

2026

2027

2027

2028

2029

2024

2026

2033

Mid

2024

2025

2026

2026

2027

2028

2023

2025

2028

High

2024

2025

2026

2025

2027

2028

2023

2024

2026

Source: Carbon Tracker analysis
Notes: See notes from Figure 11 for more information.

4.1.4 Dispatchable renewables and systems balancing
The point when new dispatchable (or firm) renewables outcompetes operating coal is outside thescope of this analysis. The challenge for policymakers today is no longer whether or not renewableenergy will be the least-cost option, but rather how to integrate wind and solar to maximise system
value or lower the cost to the overall system. The IEA notes that it is possible to get to 15% solar
and wind by simply upgrading some operational practices, such as grid codes, forecasting,scheduling and so on, which are not capital intensive.34
For example, in 2003, when wind made up 2% of annual generation in Ireland, the head of the
National Grid stated that:“This amount of wind generation does, however, pose an increased risk to the security and stabilityof the power system which the transmission system operator feels exceeds the level normally likely
to be accepted by a prudent system operator.”
Wind now makes up over 20% of annual generation in Ireland and during this time security ofsupply has increased.
A report by Agora and the Renewable Energy Institute found that the Japanese power system could
accommodate a larger proportion of wind and solar energy than is currently planned by 2030.
The report modelled two scenarios: (i) the currently planned amount of variable renewable energyof 22-24% or 64 GW solar and 10 GW wind; and (ii) a more ambitious scenario of 100 GW solarand 36 GW wind. The report concluded:▪
▪
▪

Several technical measures already exist to improve grid stability in situations where a highproportion of variable renewables could place a strain on grid operations.
Integrated grid and resource planning can help mitigate the impact of wind and solar PV
deployment on intraregional and interregional load flows.
Non-discriminatory market regulations, enhanced transparency and state-of-the-art
operational and planning practices to facilitate the integration of a higher proportion ofvariable renewables.

IEA (2017). Insights Series 2017 - Getting Wind and Solar onto the Grid. Available:
https://webstore.iea.org/insights-series-2017-getting-wind-and-solar-onto-the-grid
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4.1.5 Stranded coal assets and higher energy costs
Japan’s planned and operating coal capacity are currently safeguarded indirectly by thegovernment due to a combination of legacy PPAs35 and regulations that give coal generation an
advantage in the marketplace. These regulations include, but are not limited to, the baseload
power market and inefficient dispatch.
4.1.5.1 Baseload power market
In July 2019, Japan introduced its baseload market. The purpose of the baseload market is to givenew entrant retailers access to baseload power. Baseload power includes generation from coal,hydro, nuclear and geothermal assets which are predominantly owned by incumbent utilities.36
The price includes the FOM and VOM of these assets. The power is traded via the Japan ElectricPower Exchange, but price is decided via auctions. The baseload market emulates France’s market(termed ARENH), which was introduced in 2010. Importantly, mothballed nuclear capacity is
included in the baseload power market. This inflates the clearing cost of the baseload market as
the fixed cost of these non-operating facilities is blended into the price.37 This acts as a subsidy formothballed nuclear facilities and effectively forces new entrant retailers – and their customers – topay for these unused facilities. The latest results of bids for its first baseload market show the
impact of this policy decision. According to Genscape, prices in France’s ARENH were 23% lower
than the average wholesale power price in 2018 average.38 Moreover, assuming the baseload
market price clears below the price on the wholesale market, it could shelter coal generators fromany increase in generation costs from carbon pricing.
4.1.5.2 Cost-inefficient dispatch
As detailed in Table 7 Japan’s power market regulation currently mandates economicallyinefficient dispatch, prioritising nuclear, hydro and geothermal before wind and solar. In thecontext of Japan’s power market regulation, inefficient merit order results in generation
technologies with a higher SRMC being dispatched ahead of, and thus being curtailed before
those technologies with a lower SRMC. In practice, this dispatch order negatively impacts wind andsolar, which have a near-zero SRMC.

While PPA between retailers and developers, the government provides guidance for thermal bidding.
Of the 109 GW of capacity from coal, hydro, nuclear and geothermal assets around 85% is owned by incumbent
utilities. Bloomberg NEF (2017): Power Market Design Series: Japan. Unavailable without subscription.
37
Incumbent utilities are losing money due to offline nuclear capacity. Tokyo Electric, for example, paid US$5.7bn in2016. Genscape (2019). Available: https://www.genscape.com/blog/who-benefits-japan-baseload-market
38
Genscape (2019). Available: https://www.genscape.com/blog/who-benefits-japan-baseload-market
35
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T ABLE 7. J APAN’S INEFFICIENT POWER DISPATCH ORDER
Dispatch priority

Technology

1.

Nuclear2.

Solar and wind3.

Local biomass

4.

Large-scale biomass

5

Coal, gas, oil and co-firing biomass

Source: Bloomberg NEF adapted from OCCTO 39

Without policy reform the Japanese consumer could pay for US$71bn of
stranded coal assets through high power prices
These regulations may be sheltering high-cost coal from low-cost renewables and therefore meanthat the Japanese consumer may not be receiving the lowest-cost power possible. In Carbon
Tracker’s below 2°C scenario, where planned, under-construction and operating coal capacity isforced to shut down in a manner consistent with the temperature goal in the Paris Agreement,
stranded asset risk from capital investments and reduced operating cashflows could amount to$71bn. This scenario is not totally unrealistic in the context of Japan. For instance, Japan's LTSD
which was approved by the cabinet and submitted to the UNFCCC this June, states: “TheGovernment will work to reduce CO2 emissions from thermal power generation to realize adecarbonized society and consistent with the long-term goals set out in the Paris Agreement."40
Without policy reform, this liability will cascade through the economy as detailed in Figure 12.

Bloomberg NEF (2017): Power Market Design Series: Japan. Unavailable without subscription
The Government of Japan (2019). The Long-term Strategy under the Paris Agreement. Cabinet decision, June 11,
2019. Available: https://unfccc.int/sites/default/files/resource/The%20Longterm%20Strategy%20under%20the%20Paris%20Agreement.pdf
39
40

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F IGURE 12. HOW STRANDED ASSET RISK WILL MATERIALISE IN THE JAPANESE ECONOMY

Source: Carbon Tracker analysis

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5 Policy recommendation
We offer two recommendations. Please note that these policy recommendations are high level by
design. Detailed policy recommendations are outside the scope of this report and will form future
analysis with our local partners.

5.1 Immediately reconsider planned and under construction capacity anddevelop a retirement schedule for the existing fleet that is consistent with thedecarbonisation goal in the Paris Agreement
New investments in coal capacity will unlikely be a least-cost solution over the capital recovery
period. This period is typically 15-20 years for new coal capacity and 5-10 years for retrofits
relating to performance enhancements or control technology installations. This analysis highlights
how coal power is losing its economic footing, independent of additional climate change and air
pollution policies. As such, Japan should stop investing in and building new coal immediately.
Japanese policymakers should develop a retirement schedule based on the LRMC of individual
coal units. This analysis will allow policymakers to close the higher cost units first and lower cost
units last, which should help ensure that the end consumer receives the lowest cost electricity
possible, maximising economic growth. Once policymakers have developed a cost-optimised
retirement schedule at the asset level, they should then undertake systems planning analysis totake into consideration the system value of individual assets. Understanding system value isoutside the scope of this analysis. Carbon Tracker intends to conduct this analysis with local
partners and make this research publicly available.

5.2 Accelerate renewable energy through non-discriminatory regulations
Without further reform the Japanese government risks missing the economic opportunity
associated with renewable energy and locking-in high cost power. In doing so, the government
will likely further compromise energy security, public debt and economic competitiveness. Alongwith many other countries, Japan faces several technical and political challenges to decarbonise its
power system. Lowering renewable cost, making regulations and markets more renewablefriendly, capturing surging demand from business are the challenges that Japan should address
immediately.
Renewable energy and other supporting technologies – such as battery storage, demand response
and high-voltage transmission – are part of a mega trend with no precedent in the 21st century.
The benefits from this mega trend will go to those governments who develop a strategy to capture
value from the rapid growth of these technologies. Japan has a long track record of technologicaland engineering prowess that means the nation is well placed to capture value from thesetechnologies as markets mature and product quality commands a price premium.
Incentivising renewables begins with seeing these technologies as an opportunity to reinvigorate
the nation’s industry and economy as well promote energy security. To execute this vision,
wholesale changes need to be made to ensure renewable capacity gets built at scale and inmanner that maximises its value to the grid. At the heart of these changes is a step change intransparency to avoid discriminatory regulations and potential market abuse, as well as incentivise
investments in appropriately located renewables and the associated infrastructure required tomaximise its value to the power system.

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6 Modelling risks and revisions
This analysis cannot capture unforeseen changes to commodity prices, environmental policies,
market structures and technology costs as well as company risk management and company
reporting practices. Below are the main modelling risks associated with this analysis.41
▪

▪

▪

▪

Debt to equity ratios. Owing to a lack of publicly available data, Carbon Tracker’s project
finance model does not make assumptions around debt to equity ratios, and therefore (i)the WACC estimate may not reflect the ratio between a company's total debt financing andits total equity financing; and (ii) we cannot estimate the IRR for financers.
Market structures. Market structures are rarely homogenous and vary from region to region
depending on numerous technical, political and economic factors. These differences are
essential for interpreting the results of this analysis as the asset stranding risk from high-costand unprofitable coal capacity materialises differently depending on market structures.
Risk management practices. Utilities often hedge their revenue and cost exposure throughthe future and forward markets. The level and extent of hedging varies depending onwhether the utility operates in a liberalised or regulated market, as well as on the evolutionof power market price formation. For instance, European utilities who operate in liberalised
power markets have historically hedged their revenues up to four years in advance. When
European utilities sell their power on the future and forward markets, they also cover theirfuel and carbon costs. For example, European carbon prices are currently ~€30/t now but
numerous generators are not necessarily exposed to this cost as they hedged their carbon
exposure when prices were ~€10/t. Moreover, due to increasing levels of variable renewableenergy, revenue optimisation – and thus risk management activities – are concentrated at
the front of the curve.
Fixed operating costs. Estimated fixed operating and maintenance costs (FOM) is particularly
challenging. The amount an operator spends on FOM depends on a variety of factors. Unit
owners who are expecting to close within 3 to 5 years can take a “sellotape” strategy tooperations by only making minimal investments to keep the unit running. However, over the
long-term, unit owners need to invest in operations and maintenance to sustain unit
performance and availability, as well as in control technologies to meet air pollution
regulations. These are not immaterial and could influence operating cash flows significantly.

In addition, we have made a number of modelling revisions to several markets since publishing
Powering Down Coal in November 2018. These revisions are detailed in Table 8 below.
T ABLE 8. M ODELLING REVISIONS SINCE POWERING DOWN COAL 2018
Fuel cost(US$/MWh)

Variable O&M
cost (US$/MWh)

Fixed O&M cost
(US$/MWh)

Control Tech
Cost
(US$/MWh)

Carbon cost
(US$/MWh)2018

Latest2018

Latest2018

Latest2018

Latest2018

LatestAustralia

29.32

29.32

1.29

1.30

8.66

8.66

5.06

5.06

0.00

0.00

China

41.61

42.73

3.56

3.57

2.13

2.10

0.13

0.14

0.00

0.00

EU

31.53

31.10

2.15

2.09

6.42

6.34

3.46

3.57

16.80

16.41

India

29.79

30.66

5.59

5.72

3.96

4.10

2.33

2.81

0.00

0.00

Indonesia

27.00

28.13

5.64

5.94

2.53

2.41

2.71

2.32

0.00

0.00

For a full breakdown of our commodity, policy regulatory and technology assumptions, please refer to themethodology document.
41

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Japan

47.11

41.49

6.15

6.04

1.72

1.83

5.75

6.07

0.00

2.58

Philippines

39.79

41.00

5.32

5.48

2.09

2.02

2.67

2.63

0.00

0.00

Russia

31.51

31.52

3.96

3.96

2.63

2.63

1.75

1.75

0.00

0.00

South Africa

21.75

21.35

5.36

5.28

7.61

7.31

4.28

4.92

0.00

0.00

South Korea

40.75

41.46

4.84

4.89

3.10

3.13

4.70

4.47

0.35

0.35

Turkey

36.70

36.70

4.57

4.57

2.62

2.62

3.97

3.97

0.00

0.00

Ukraine

54.90

54.90

7.03

7.03

6.93

6.93

1.34

1.34

0.00

0.00

United States

26.93

26.94

4.86

4.87

3.74

3.70

2.41

2.39

0.06

0.06

Vietnam

37.67

31.53

5.25

5.39

2.87

3.30

5.35

5.64

0.00

0.00

Revenues (US$/MWh)

Stranded Asset Risk (million US$)2018

Latest2018

LatestAustralia

65.57

65.57

15,16015,160

China

46.61

46.56

-388,775-388,775

EU

42.64

42.48

-122,947-122,947

India

57.66

57.59

76,174

76,174

Indonesia

68.73

68.85

34,73534,735

Japan

60.75

82.85

20,37071,495

Philippines

64.96

65.05

13,111

13,111

Russia

17.80

17.79

-19,930-19,930

South Africa

72.73

72.73

51,276

51,276South Korea

77.85

78.12

106,212106,212Turkey

22.27

22.27

-153

-153

Ukraine

63.54

63.54

-6,593-6,593

United States

33.87

33.86

-16,996-16,996

Vietnam

54.78

56.47

11,683

6,462

Source: Carbon Tracker analysis
Notes: 2018 column represents when Powering Down Coal was published in November 2018. The main change isthat these capacity-weighted averages now take into consideration whether a unit was operating during the
averaging period or not. Previously, this was ignored. The model results for Japan now include the capital costs
associated with capacity under construction, permitted and per-permit. Previously, this was ignored.

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7 Conclusions
In this report, we presented the findings of Carbon Tracker’s coal power economics analysis forJapan to understand the potential for asset stranding and relative competitiveness of renewableenergy. Coal has long been considered the least-cost option for power in Japan. However, that isquickly changing as a confluence of factors are disrupting coal’s pre-eminence. Most notably, lowcost renewable energy, which will soon be cheaper to build than to run coal plants. Japanesepolicymakers need to stop new investments in coal power immediately and start a longer
conversation about the future of the fuel. Failure to do so will result in stranded assets which will
likely be realised through high energy prices.

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8 References
Agency of Natural Resources (2019). Available:
https://www.enecho.meti.go.jp/category/electricity_and_gas/electric/summary/retailers_list/
Bloomberg NEF (2017). Power Market Design Series: Japan. Unavailable without subscription.
Bloomberg LP (2019). Terminal. Unavailable without subscription
Bloomberg NEF, (2019). Levelised Cost of Electricity (LCOE) by Country. Unavailable without subscription.
BP (2019). Statistical Review of World Energy. Available: https://www.bp.com/en/global/corporate/energyeconomics/statistical-review-of-world-energy.html
Carbon Tracker (2016). The end of the load for coal and gas. Available: www.carbontracker.org/reports/the-endof-the-load-for-coal-and-gas/
Carbon Tracker (2018). Powering Down Coal. Available: https://www.carbontracker.org/reports/coal-portal/
Carbon Tracker (2018). Methodology document. Available: https://www.carbontracker.org/reports/coal-portal/
Country Economy (2019). GDP by country. Accessed: 20/05/19. Available: https://countryeconomy.com
Climate Analytics (2017). Science-based coal phase-out timeline for Japan. Implications for policymakers. Available:
https://climateanalytics.org/media/coalphaseout-2018-en-report_1.pdf
Environment and Economy Division Ministry of the Environment January (2017). Greening of Whole Tax System
and Carbon Tax in Japan. Available: https://www.env.go.jp/en/policy/tax/20170130_greening.pdf
EPA (2018). Documentation for EPA Platform v6 – Chapter 5. Available:
https://www.epa.gov/sites/production/files/2018- 05/documents/epa_platform_v6_documentation__chapter_5.pdf
Genscape (2019). Who benefits Japan baseload market? Available: https://www.genscape.com/blog/whobenefits-japan-baseload-market
IEA Clean Centre (2016). Levelling the intermittency of renewables with coal. Available:
https://www.usea.org/sites/default/files/Leveling%20the%20intermittency%20of%20renewables%20with%20coal%20-%20ccc268-1.pdf
IEA (2014). World Energy Investment Outlook. Available:
http://www.worldenergyoutlook.org/weomodel/Investmentcosts/
IEA (2016). Energy and Air Pollution. Available:
https://www.iea.org/publications/freepublications/publication/WorldEnergyOutlookSpecialReport2016EnergyandA
irPollution.pdf
IEA (2016). Energy, Climate Change and Environnent. 2016 Insights. Available:
https://www.iea.org/publications/freepublications/publication/ECCE2016.pdf
IEA (2016), Next-generation wind and solar power: From cost to value. Available:
https://www.iea.org/publications/freepublications/publication/NextGenerationWindandSolarPower.pdf
IEA (2017). Insights Series 2017 - Getting Wind and Solar onto the Grid. Available:
https://webstore.iea.org/insights-series-2017-getting-wind-and-solar-onto-the-grid
IEA (2017). Energy Technology Perspectives (ETP) 2017. Available: https://www.iea.org/etp/
IEA (2018). Wind TCP Task 26- Offshore Wind Energy International Comparative Analysis
IMF (2019). Available: https://www.imf.org/external/datamapper/PCPIPCH@WEO/OEMDC/JPN

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IRENA (2018). Renewable Power Generation Costs in 2018. Available: https://www.irena.org//media/Files/IRENA/Agency/Publication/2018/Jan/IRENA_2017_Power_Costs_2018.pdf
IRENA statistics (2019). Available: https://www.irena.org/Statistics/View-Data-by-Topic/Capacity-andGeneration/Statistics-Time-Series
IRENA (2019). Global energy transformation: A roadmap to 2050. Available:
https://www.irena.org/publications/2019/Apr/Global-energy-transformation-A-roadmap-to-2050-2019Edition
Japan Ministry of Finance (2019). Ministerial ordinance on the useful life of depreciable assets. Available:
https://elaws.e-gov.go.jp/search/elawsSearch/elaws_search/lsg0500/detail?lawId=340M50000040015
Japan Climate Initiative (2019). Available: https://japanclimate.org/english/
Kiko Network (2019). Status of coal fired planned after 2012. Available: https://sekitan.jp/wpcontent/uploads/2019/08/outlook-of-coal-fire-plant_20190816_EN.pdf
METI, (2017). TCFD. Available:
https://www.meti.go.jp/policy/energy_environment/global_warming/disclosure.html
METI (2018). Electricity System and Market in Japan. Available:
https://www.emsc.meti.go.jp/english/info/public/pdf/180122.pdf
Ministry of Environment (2017). Available: http://www.env.go.jp/earth/ondanka/ghgmrv/emissions/results/JNGI2019_2-7.pdf
Ministry of Economy, Trade and Industry (2019). Electricity Generation statistics. Available:
https://www.meti.go.jp/statistics/tyo/seidou/chosahinmoku_hensen.html
METI (2018). Japan’s Energy 2018. Available:
https://www.enecho.meti.go.jp/en/category/brochures/pdf/japan_energy_2018.pdf
METI (2018). Cabinet Decision on the New Strategic Energy Plan. Available:
https://www.meti.go.jp/english/press/2018/0703_002.html
New Energy Update (2019). US solar maintenance costs plummet as tech gains multiply. Available:
https://analysis.newenergyupdate.com/pv-insider/us-solar-maintenance-costs-plummet-tech-gains-multiply
Nikkei Asian Review (2018). https://asia.nikkei.com/Spotlight/Environment/Japan-to-slash-fixed-prices-for-solarpower-feed-ins
North America Electric Reliability Corporation (2010). 2010 Special Reliability Scenario Assessment: Resource
Adequacy Impacts of Potential U.S. Environmental Regulations. Available:
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NREL (2016). Costs of Wind Energy Review. Available: https://www.nrel.gov/docs/fy18osti/70363.pdf
NYU Stern, A. Damodaran (2019). Available:
http://people.stern.nyu.edu/adamodar/New_Home_Page/datacurrent.html
OCCTO (2017). Available : https://www.occto.or.jp/en/information_disclosure/outlook_of_electricity_supplydemand/181210_outlook_of_electricity.html
OCCTO (2019). Available: https://www.occto.or.jp/pressrelease/2018/files/190329_kyokei_torimatome.pdf
Platts (2019). UDI World Electric Power Plants Database. Unavailable without a subscription.
Ports.com (2018). Available: http://ports.com/
Renewable Energy Institute, Agora Energiewende (2018). Integrating renewables into the Japanese
power grid by 2030. Available: https://www.renewable-ei.org/en/activities/reports/20181217.php

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Renewable Energy Institute (2018). Wind Power Costs in Japan. Available: https://www.renewableei.org/en/activities/reports/img/pdf/20180125/JapanWindPowerCostReport_EN_20180124.pdf
Renewable Energy Institute (2019). https://www.renewable-ei.org/en/statistics/electricity/?cat=quarterly
The Climate Group (2019). Available: https://www.theclimategroup.org/news/major-companies-call-ambitious2030-renewable-electricity-targets-japan
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UN Comtrade (2018). UN Comtrade database. Available: https://comtrade.un.org/
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https://population.un.org/wpp/Download/Standard/Population/
World Bank (2019). Available: https://data.worldbank.org/indicator/FR.INR.LEND?locations=JP
World Bank (2019a). Global Wind Atlas. Available: https://globalwindatlas.info/
World Bank (2019b). Global Solar Atlas. Available: https://globalsolaratlas.info/

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9 Appendix – LCOE modelling
9.1.1 General considerations
The LCOE calculations are based on a discounted cash flow model in which costs (CAPEX andO&M) of developing and running renewable energy assets are discounted using a real weighted
average cost of capital (rWACC). These costs are then divided by the discounted (also using
rWACC) lifetime production (kWh) of the asset to obtain a unique value, the LCOE.
The variables of the model are the following ones:
▪
▪
▪
▪
▪

Investment Costs (CAPEX) - USD/kW
O&M Costs – annual % of CAPEXCapacity factor – percentage points of 8760 (number of hours in a year)
Lifetime of the asset – years
Real weighted average cost of capital (rWACC) – percentage points

The real weighted average cost of capital is calculated using a division between debt and equity tofinance a project, usually 80% debt and 20% equity for OECD countries. The weight of the debt
(e.g. 80%) is then multiplied by the cost of debt (interest charged for loans) minus the inflation
rate. The weight of the equity (e.g. 20%) is multiplied by the return on equity minus the inflation
rate. The sum of the two results is the rWACC. All assets are assumed to have a 25 years lifetime.

9.1.2 Assumptions for onshore wind
CAPEX for onshore wind in Japan in 2019 was estimated using data42 from 2016 from a research
paper produced by the Renewable Energy Institute. The cost breakdown structure came from thesame sources. CAPEX values were reduced by 8% annually going to 2019 to account for costdeclines during the period. A lower bound CAPEX was calculated using 15% assumption and ahigher bound using a 20% assumption.
O&M costs were collected from the same paper, declined by 5% per year going to 2019. A lower
bound O&M was calculated using 15% assumption and a higher bound using a 20% assumption.
Capacity factor data was collected from the same paper, mid value. The lower bound capacity
factor was declined by 3 percentage points while the higher bound capacity factor was added 3
percentage points.
Data on return on equity43 was taken from a dataset maintained here by Aswath Damodaran, afinance professor at NYU Stern. The mid value 14.67% return on equity was reduced by 15% toobtain the lower bound and increased by 15% to obtain the higher bound. Upper variation of RoE
is assumed to be less significant as the upper variation of other variables.
Data on cost of debt44 was sourced from World Bank. The rate, 0.99%, found was for loans on
short and medium term to which another 1 percentage point is added to account for the riskier
long term loan. Finally, inflation data45 was sourced from International Monetary Fund. The debt

Renewable Energy Institute (2018). Available: https://www.renewableei.org/en/activities/reports/img/pdf/20180125/JapanWindPowerCostReport_EN_20180124.pdf
43
NYU Stern, A. Damodaran (2019). Available:
http://people.stern.nyu.edu/adamodar/New_Home_Page/datacurrent.html
44World Bank (2019). Available: https://data.worldbank.org/indicator/FR.INR.LEND?locations=JP
45
IMF (2019). Available: https://www.imf.org/external/datamapper/PCPIPCH@WEO/OEMDC/JPN
42

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equity split was assumed to be 80% debt and 20% equity, a common assumption for OECDmember countries.
Data for capacity (MW) projections was sourced from the REMAP46 team at IRENA while data for2019 was projected using historical deployment data47 from IRENA. The underlying file is not beshared or quoted, as per the request of the REMAP team who created the projections using very
aggressive carbon prices.
A learning curve of 25%, upped from 21%, was used to project LCOE declines going forward
based on global results48 published in 2018.
Finally, the low, mid and high LCOE and the REMAP highest capacity projections were used tocompute the LCOE of onshore wind going to 2040.

9.1.3 Assumptions for solar PV
CAPEX for solar PV49 in Japan in 2019 was estimated using data from an IRENA publication,
specifically for Japan, for 2018 that was declined by 8% for 2019. The cost breakdown structure
came from the same sources. A lower bound CAPEX was calculated using 15% assumption and ahigher bound using a 20% assumption. The cost breakdown of solar PV is from the same paper.
O&M costs50 data was sourced from data on USA solar PV plants which was scaled upwards by thedifference between CAPEX in Japan versus CAPEX in USA to account for generally a more
expensive market in Japan. A lower bound O&M was calculated using 15% assumption and ahigher bound using a 20% assumption.
Capacity factor was calculated using fleet generation51 data for 2018 and adding an 8% premium
to account for the utility average production being dragged down by less productive rooftop
installations. The lower bound capacity factor was assumed to 15% lower while the higher boundcapacity factor was assumed to be 20% higher.
The same data for return on equity, debt and inflation and equity – debt split was used as in thecase of onshore wind. Capacity projections52 were collated using REMAP data and assumptions
from BNEF NEO 2018 as the REMAP data was less aggressive for 2040.
A learning rate of 60% was used for solar PV LCOE for two reasons: Japan has the highest CAPEX
and LCOE of utility solar PV which allows for significant declines going to 2040. Secondly, the
LCOE decline for Japan from 2010 to 2018 was 75%53 according to IRENA data.

IRENA. https://www.irena.org/remap/REmap-Publications
IRENA. https://www.irena.org/Statistics/View-Data-by-Topic/Capacity-and-Generation/Statistics-TimeSeries
48
IRENA (2018). Available: https://www.irena.org//media/Files/IRENA/Agency/Publication/2018/Jan/IRENA_2017_Power_Costs_2018.pdf
49
See footnote 33
50
New Energy Update (2019). https://analysis.newenergyupdate.com/pv-insider/us-solar-maintenance-costsplummet-tech-gains-multiply
51
Renewable Energy Institute (2019). https://www.renewable-ei.org/en/statistics/electricity/?cat=quarterly
52
IRENA (2019). Available: https://www.irena.org/publications/2019/Apr/Global-energy-transformation-Aroadmap-to-2050-2019Edition53
See footnote 33
46
47

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Learning rates were calculated using the most aggressive deployment scenario and the mid, low,
and high 2019 LCOE for solar PV.

9.1.4 Assumptions for offshore windHigh quality data for offshore wind is harder to come by for Japan given the thin deployment of
the technology in the country, 65 MW54 cumulative capacity at end of 2018 according to IRENA
stats. However, going further it seems that the government provides increasing support (here) tothe nascent industry.
CAPEX data for offshore wind was sourced from IRENA, from global weighted average CAPEX foroffshore wind and from the insight that projects outside of Europe tend to be less expensive thanthe ones in Europe, mostly due to cheaper wind turbine use. Thus, I assumed a 95% of the global
weighted average offshore wind CAPEX in 2019 in Japan. IEA is providing 2% lower value for2017 modelled project. A lower bound CAPEX was calculated using 15% assumption and a higher
bound using a 20% assumption. Cost break down of CAPEX was sourced from NREL55 and IEA56.
O&M costs were sourced from IRENA57 and IEA and were assumed to 2.5% of CAPEX for Japan in
2019, the mid-point between approximately 2% of CAPEX for IRENA and 3% from IEA. A lower
bound O&M was calculated using 15% assumption and a higher bound using a 20% assumption.
Capacity factor values were sourced as well from IRENA and IEA as the mid-point between the
global weighted average in IRENA publication and the value provided in the IEA offshore windreport. A lower bound capacity factor was calculated using a 15% decline rate and a higher
bound using a 20% increase rate.
The same data was used for debt, equity and inflation except that given the small offshore market
in Japan and the fact that offshore is riskier, more so in new market the equity debt split was
assumed to 70/30. IEA uses the same split in their report.
The low, mid and high LCOE calculated was used to compute the cost decline going further to
2040. REMAP most aggressive deployment scenario was used and a learning rate of 12%, 2%
lower than in IRENA58 2018 publication at global level, lower due to Japan having more
uncertainties over how much offshore will develop.

See footnote 32
NREL (2016). Available: https://www.nrel.gov/docs/fy18osti/70363.pdf
56
IEA (2018) - Wind TCP Task 26- Offshore Wind Energy International Comparative Analysis
57
See footnote 33
58
See footnote 33
54
55

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10 Disclaimer
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