THE 2035 JAPANREPORT
PLUMMETING COSTS OF SOLAR, WIND,
AND BATTERIES CAN ACCELERATE JAPAN’S CLEAN
AND INDEPENDENT ELECTRICITY FUTURE
AUTHORS
Kenji Shiraishi1,2, Won Young Park1, Nikit Abhyankar 1,2,
Umed Paliwal1,2, Nina Khanna1, Toru Morotomi3, Jiang Lin1,2*,
and Amol Phadke1,2*Lawrence Berkeley National Laboratory
University of California, Berkeley
3
Kyoto University*corresponding author
1

2

LBNL-2001526

ABSTRACTJapan faces a significant energy security
risk as it imports nearly all of the fuel usedin its power sector, with clean electricity
accounting for only 24% of the total. This
study shows that, due to the decreasing
costs of solar, wind (especially offshore),and battery technology, Japan can achieve
a 90% clean electricity share by 2035.
This would also result in a 6% reduction
in electricity costs, nearly eliminate
dependence on imported LNG and coal, as
well as dramatically reduce power sector
emissions. Additionally, the study finds thatJapan’s power grid will remain dependable
without the need for new gas capacity orcoal generation. To take advantage of thesesignificant economic, environmental, andenergy security benefits, strong policies suchas a 90% clean electricity target by 2035 andcorresponding renewable deployment goals
are required.

DISCLAIMERTECHNICAL REVIEW COMMITTEE

While this document is believed to contain correct
information, neither the United States Government nor
any agency thereof, nor The Regents of the Universityof California, nor any of their employees, makes any
warranty, express or implied, or assumes any legal
responsibility for the accuracy, completeness, orusefulness of any information, apparatus, product, or
process disclosed, or represents that its use would not
infringe privately owned rights. Reference herein to any
specific commercial product, process, or service by its
trade name, trademark, manufacturer, or otherwise, does
not necessarily constitute or imply its endorsement,
recommendation, or favoring by the United States
Government or any agency thereof, or The Regents of the
University of California. The views and opinions of authors
expressed herein do not necessarily state or reflect thoseof the United States Government or any agency thereof,or The Regents of the University of California.

Below are the members of the technical review
committee. The committee provided input and guidance
related to study design and evaluation, but the contents
and conclusions of the report, including any errors andomissions, are the sole responsibility of the authors.
Committee member affiliations in no way imply that thoseorganizations support or endorse this work in any way.

Ernest Orlando Lawrence Berkeley National Laboratory is
an equal opportunity employer.

Funding for this report was provided by Climate
Imperative Foundation.

COPYRIGHT NOTICE

The following people provided invaluable technicalsupport, input, review, and assistance in making thisreport possible:

This manuscript has been authored by authors at
Lawrence Berkeley National Laboratory under Contract
No. DE-AC02-05CH11231 with the U.S. Department ofEnergy. The U.S. Government retains, and the publisher,by accepting the article for publication, acknowledges,that the U.S. Government retains a non-exclusive, paid-up,
irrevocable, worldwide license to publish or reproduce thepublished form of this manuscript, or allow others to doso, for U.S. Government purposes.

Takamura, Yukari | University of Tokyo
Komiyama, Ryoichi | University of Tokyo
Nagata, Tetsuro | Kyoto University
Sakurai, Keiichiro | National Institute of Advanced
Industrial Science and Technology
Kurosaki, Miho | Kamakura Sustainability Institute
Independent Analyst

ACKNOWLEDGEMENTS

Kimiko Hirata and Chisaki Watanabe of Climate Integrate
James Hyungkwan Kim of Lawrence Berkeley National
Laboratory
Yoh Yasuda of Kyoto University
Anya Breitenbach of Forge & Foundry Strategic
Jin Kato of Japan Wind Power Association
Takeaki Masukawa and Kanzo Sugimoto of Japan
Photovoltaic Energy Association
Annie Dore of Beespring Designs

TABLE OF
CONTENTSEXECUTIVE SUMMARY
1

INTRODUCTION

2 METHODS AND DATA SUMMARY

1
10
13

2.1 Policy Scenario

13

2.2 Modeling Tools and Approach

15

2.3 Key Modeling Input

17

2.4 Sensitivity Analysis

22

3 KEY FINDINGS

24

3.1	Japan’s 90% Clean ENERGY
Grid Can Dependably MeetElectricity Demand with Large
Additions of RE and Energy
Storage		24

3.2	Clean Energy Deployment
Can Reduce Wholesale
Electricity Costs By 6%

32

3.3	90% Clean Energy Deloyment
Can Reduce Fossil Fuel Import
Costs By 85%, Bolstering
Japan’s Energy Security

36

3.4	Scaling-Up Renewables toAchieve a 90% Clean Energy
Grid Is Feasible

37

3.5	Clean Energy Can Cut CO2
Emissions By 92%, Providing
Significant Environmental
Benefits		

40

4 CAVEATS AND FUTURE WORK42

5	CONCLUSIONS AND POLICYINSIGHTS		

43

5.1 Key Conclusions

43

5.2 Possible Future Actions

44

References			

50

APPENDIX A | Modeling Approach

54

APPENDIX B | Modeling Inputs

56

APPENDIX C | Solar and Wind Profiles 60
APPENDIX D | Carbon Price Sensitivity 67
APPENDIX E | Regional Results ofBase Scenario		

69

APPENDIX F | Sensitivity Analysis

71

EXECUTIVE
SUMMARY

The global energy crisis poses critical challenges for the Japanese people andtheir economy. The country depends on foreign fossil fuel imports for about 90%
of its primary energy consumption. At the same time, technological advancements
and dramatic reductions in solar, wind, and battery storage costs present newopportunities to make clean electricity generation more affordable, while reducing
emissions and better positioning the country to meet its 2050 goal of carbon
neutrality.
The most important strategy for decarbonization is establishing clean energy
sources to feed the grid and substantially increase its supply Japan’s electricity
without using fossil fuels. These clean energy options include primarily solar- andwind-based renewable energy (RE), as well as smaller amounts of power generated
by nuclear and natural gas plants. Generation from any resource that does notproduce direct carbon dioxide (CO2) emissions is considered clean energy in thisanalysis, including generation from solar, wind, hydropower, biomass, geothermal,hydrogen, and nuclear sources.
Japan’s near-term goal is to transition 59% of electricity generation to clean energy
sources by Fiscal Year (FY) 2030, compared to the 24% of electricity supplied bythese sources in FY 2019. This study examines the factors involved in hitting cost,dependability, and emissions targets, while making even greater cuts in fossil fuelused for electricity generation by 2035.

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The study addresses three vital questions:
What effect will recent declines in wind, solar, and battery storage costs haveon the pace and scale of renewable resource development?
What clean energy goals are technically and economically feasible, given theinherent uncertainties such as electricity demand growth, fossil fuel prices,and RE and energy storage costs?
How can a faster transition to clean energy deliver not only environmental
and economic benefits, but also reduce security risks related to dependence
on imported fossil fuels?

Using detailed state-of-the-art capacity expansion
and hourly dispatch models to explore one
core Clean Energy policy scenario (referred tothroughout this report as the “Clean Energy”
scenario), researchers examined its potential impact
on Japan in the 2020 through 2035 time frame. This
core Clean Energy Scenario evaluates transition
from Japan’s non-fossil electricity generation goalfor 2030 to a 90% clean generation electric systemby 2035. The study also applied multiple sensitivity
analyses to this Clean Energy Scenario, including
high and low renewable energy and storage costs;
high fossil fuel prices (2022 levels); high levels ofelectrification; and the extended lifetime of nuclear
generators.
The Clean Energy Scenario limits annual
deployment of clean energy generation to thatneeded to exceed Japanese government goal of
non-fossil energy commanding a 59% share ofelectricity generation by 2030, and a 90% shareby 2035. Research findings show that this shareof clean energy deployment can be achievable,
dependable, and cost effective. Rapid increases
in renewable energy generation, in tandem withgrowth in electrification of technologies, showpromise to accelerate progress toward Japan’s
carbon neutrality goals and combat climate change.

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KEY FINDINGS
Table ES-1 shows the report’s findings at a glance, and the following discussion
expands on these findings.

TABLE ES1. Japan’s Power System Characteristics by Case Modeled in the Report
CURRENT GRID (2023)

90% CLEAN (2035)

Highly Decarbonized Grid
Dependable Grid
Electricity Cost Reductions
Feasible Scale-Up
Environmental Savings
Energy Independence

STRONG POLICIES ARE REQUIRED TO CREATE A 90% CLEAN GRID BY 2035
The 90% Clean Grid (Clean Energy Scenario) assumes strong policies drive 90%
clean electricity by 2035. Institutional, market, and regulatory changes needed tofacilitate the rapid transformation to a 90% clean power sector in Japan.

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JAPAN’S 90% CLEAN GRID IS DEPENDABLE WITHOUT COAL GENERATION OR
NEW NATURAL GAS PLANTS
There has been longstanding debate about whether Japan could dependably
operate electricity systems with high shares of variable RE (VRE). The study
finds that a 90% clean energy grid that features accelerated solar and windcapacity additions, new battery storage, and new interregional transmission
infrastructure can be combined with a small percentage of the existing fossil
fuel-based generation capacity to dependably meet Japan’s electricity demand,
while maintaining planning reserve margin and operating reserves. An additionof 116 gigawatt hours (GWh; 29 gigawatts for 4 hours) of battery storage and 11.8
gigawatts (GW) of new interregional transmission lines, coupled with existingflexible methods of generation (dispatchable hydropower, pumped hydropower,
and natural gas), can cost-effectively balance operation of a 90% clean energy grid,even during periods of low RE generation and/or high demand.
In the Clean Energy Scenario, RE generated mainly from solar photovoltaic (PV)and wind sources totals 70% of annual electricity generation by 2035. Nuclear
power and natural gas-fired power account for 20% and 10% of electricity
generated, respectively. All existing coal plants, which generated 32% of the total
electricity supply in FY 2019, are phased out by 2035, and no new fossil fuelpowered plants are built.

GENERATION ENERGY MIXTOTAL INSTALLED CAPACITY

1,000

500

Battery Storage
Pumped Hydro

750

8%
10%
8%
4%

500

23%
1%
6%
1%

250

400

TOTAL C APACIT Y (GW )G E N E R ATIO N ( T Wh/ Y E AR)

10%

29

Hydro

27

Wind

23

Offshore Wind
Fixed

23
24

O
 ffshore Wind
Float

19

300

25

R
 esidential PV

132

200

25

2
8
3

Utility/
Commercial PV
Geothermal
Biomass
HydrogenNuclear

100
20%

76

10%

36

LNG
Coal

0
2020

2025

2030

2035

0
2020

2025

2030

Oil

2035

FIGURE ES1. Generation Energy Mix and Total Installed Capacity between 2020
and 2035, Clean Energy Scenario

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ELECTRICITY COSTS FROM THE 90% CLEAN GRID ARE LOWER THANTODAY’S COSTS
In the Clean Energy Scenario, RE coupled with enhanced energy storage andinterregional transmission lines make it possible to displace a significant amountof generation from existing coal and natural gas plants, while maintaining grid
dependability and decreasing wholesale electricity costs. The incremental costof developing new solar and wind plants, battery storage, and transmission
infrastructure in the Clean Energy Scenario is smaller than the fossil fuel, operationand maintenance (O&M), and fixed costs found in running today’s typical fossil fuelfired plants (Figure ES2).
This suggests that more rapid deployment of renewable generation, increasing
by an average of 10 GW per year between 2020 and 2035, would actually reduceaverage wholesale electricity costs by 6% from the 2020 level. Wholesale electricity
costs include the cost of generation and storage, plus incremental transmission
investments. If social costs of carbon (SCC) is included, wholesale electricity costs
are about 36% lower in 2035 under the Clean Energy Scenario than they are in
2020, assuming 12,980 JPY/ton of CO2 ($118/t-CO2) at 2.5% discount rate from thelatest study (Rennert et al., 2022). All scenarios in this study include the current
level of Global Warming Countermeasure Tax, 289 JPY/t-CO2 ($2.6/t-CO2), not the
SCC presented here.
Retaining natural gas-fired power plants helps balancing seasonal and cross-day
load variation against solar and wind generation, reducing the necessity of longduration energy storage and further renewable plant buildout.

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AVE R AG E COST O F G E N E R ATIO N (J PY/K Wh)

W/O SCC

W SCC

15

10

5

0

2020

2025

2030

2035

2020

2025

2030

2035

FIGURE ES2. Wholesale Electricity Costs with and without Social Costs of Carbon(SCC) for the Clean Energy Scenario, between 2020 and 2035 (2020 JPY)

85% REDUCED FOSSIL FUEL IMPORTS AND A 90% CLEAN ENERGY GRID CANSIGNIFICANTLY BOLSTER JAPAN’S ENERGY SECURITY
Under the Clean Energy scenario, imported coal and natural gas costs would
decrease by 85%, from 3.9 trillion JPY in 2020 to 0.59 trillion JPY in 2035. The
decline in imported coal and natural gas costs would be even greater over time
under the high fuel cost sensitivity scenario (set at the 2022 cost levels), comparedto the base fuel costs used in the Clean Energy Scenario. Not only would the 90%
clean energy grid translate into lower electric bills. By maximizing Japan’s use ofdomestic renewable resources, it would significantly decrease the nation’s heavy
dependence on imported fossil fuels. In turn, this would bolster Japan’s energy
security, insulating consumers and the economy from skyrocketing international
fossil fuel prices.

SCALING-UP RENEWABLES TO ACHIEVE THE 90% CLEAN ENERGY GRID ISFEASIBLE
Under the 90% Clean Energy Scenario, the combined capacity of all RE sources
rise from 90 GW in 2020 to 188 GW in 2030 and 254 GW in 2035 (Figure ES1). In
particular, accelerated wind and solar capacity growth makes the 90% clean energy
grid feasible.

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On average, an additional 10 GW of RE need to be brought on-line each year (from2020 to 2035). This annual increase, comparable to Japan’s single-year renewablebuildout record of 9.7 GW (FY 2015), is challenging but feasible (Figure ES3).

AVE R AG E AN N UAL C APACIT Y AD DITIO N(GW/ Y E AR)

Solar power additions are dominant in 2020s, while offshore wind’s continued
technology cost declines and high capacity factors make it the dominant growtharea in the 2030s. This shift to clean energy will require attention to rapidly break
down institutional, market, and regulatory barriers, along with swift advancements
in battery storage and interregional transmission lines to balance VRE generation
against loads.

FIGURE ES3. Average
Annual Renewable
Capacity Additions by
Periods, Clean Energy
Scenario

15

JAPAN'S SINGLE YEAR RE DEPLOYMENT RECORD
10(9.7 GW IN FY2015)

Wind
Offshore Wind Fixed

5

Offshore Wind Float
Residential PV
Utility/Commercial PV
Other RE0

FY 2014-FY 2019
(HISTORICAL)

Y2020-Y2025

Y2026-Y2030

Y2031-Y2035

CLEAN ENERGY CAN CUT ELECTRICITY SECTOR CO2 EMISSIONS BY 92%
Generating 90% of electricity from clean energy by 2035 would significantly cut
carbon dioxide (CO2) emissions, resulting in important environmental benefits. By
2035, the Clean Energy Scenario was shown to potentially reduce total electricity
sector CO2 emissions by 92% compared to 2020 levels. The reductions of 345
million tons of CO2 emissions in 2035 is equal to nearly 30% of Japan’s total CO2
emissions in FY 2019. As a result, the emission intensity of electricity generation
drops by 91% from 404 kilograms (kg)-CO2/kilowatt hour (kWh) in 2020 to 36
kg-CO2/kWh in 2035. The extremely low emission intensity supports deeper
decarbonization of other sectors, such as electrified transportation, heating, andmore.

THE 2035 JAPAN REPORT|7

It also reduces exposure to fine particulate matter (PM2.5), sulfur dioxide (SO2),
nitrogen oxide (NOx), and heavy metals (e.g., mercury, cadmium, arsenic, chromium,and beryllium) emitted by fossil fuel-burning power plants . This could deliversignificant health benefits, potentially extending lifespan and reducing the societal
costs of medical care.

REACHING COST-EFFECTIVE LEVELS OF CLEAN ENERGY GENERATION WILLREQUIRE OVERCOMING POLICY, MARKET, AND LAND-USE BARRIERS
A rapid and cost-effective transition to the 90% clean energy grid will require
integrated, sustained policy support to overcome institutional, market, andregulatory barriers. The share of electricity generated from RE sources in the Clean
Energy Scenario begins to accelerate in the 2020-2035 time period, suggestingthat policy and regulatory changes to speed up deployment should begin sooner
rather than later.
The recommendations outlined below are intended to inform debate on public andcorporate policies to address the pressing energy and climate crisis with stablebusiness models, low integration costs, dependable systems, and minimal land-use
impacts.
Establishing Medium-Term Policy Targets (Beyond 2030)• Set medium-term targets for renewable generation and coal phaseout in
2035 and beyond to reduce policy and market uncertainties• Create coherent policy packages to enable the medium-term policy targets
including research, development, and demonstration (RD&D) and carbon
pricing
Accelerating RE Deployment and Coal-Fired Power Phaseout By Mitigating
Environmental Externalities• Consolidate feed-in tariffs, including feed-in premiums, and auctions, toaccelerate renewable deployment• Increase the price of carbon to accelerate coal-fired power phaseout• Invest part of the carbon revenues in RD&D related to innovations needed tocreate a zero-carbon grid
Lowering Institutional and Societal Barriers to Rapid RE Deployment• Establish qualified renewable energy zones (REZs) with suitable topography
and land-use designations to avoid delays in permitting and deployment

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8• Integrate the zoning process in transmission planning• Involve stakeholders at early stages of planning to cultivate public input andacceptancePursuing a Just Energy Transition through Targeted Assistance Policies• Mitigate the societal and economic impacts of coal phaseout with transition
assistance programs for communities and businesses• Use carbon revenues to reimburse households and businesses for part oftheir utility expenditures, reducing the tax burden
Ensuring System Dependability, Enhancing Operational Flexibility, and Boosting
Energy Efficiency• Create markets and profitable business models for flexible resources
including energy storage, demand-side management and measures, andflexible generation• Drive investments in cost-effective energy efficiency improvement throughstandard setting or adoption of fiscal incentives
Through the support of these policies, swift decarbonization of Japan’s electricity
system would make it possible to more quickly cut emissions related to fasterand more widespread electrification of other sectors, reducing CO2 emissions andsmoothing the country’s path to a carbon-neutral economy by 2050.

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1
INTRODUCTION

Japan, the world’s third-largest economy, is facing a pressing series of related
energy-related dilemmas in the wake of the Russian invasion of Ukraine:
simultaneously ensuring energy affordability and energy security, while making
the deep cuts in greenhouse gas (GHG) emissions needed to meet the nation’s
climate change goals. These targets include shifting electricity generation to 59%
clean energy sources by 2035 and achieving carbon neutrality by 2050 in supportof Japan’s commitment to the global goal of limiting the average temperature
increase to 1.5°C.
As of 2020, only 11.2% of Japan’s primary energy was supplied by domestic
resources (GoJ, 2021b), exposing the nation’s people and economy to the highvolatility of international fuel prices (Figure 1). Liquified natural gas (LNG) andcoal power plants (typically fueled with coal N.E.S., a common type of coal used inJapan) still account for roughly 80% of the nation’s electricity generation. Spikes ininternational energy prices led to Japan’s 2022 wholesale electricity price of 22.6
Yen (JPY)/kWh being double that of the average in the preceding 10 years (11.5
JPY/kWh from 2012-2021).

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Japan recently established a national target of net-zero GHG emissions by 2050
(GoJ, 2021a). This builds on the government’s earlier nationally determinedcommitment (NDC) to reduce GHG emission levels from 26% to 46% between 2013
and 2030, which was made as part of the Paris Agreement (GoJ, 2021d; GoJ,
2021e). Meeting these ambitious 2030 and 2050 national and international climatechange commitments will require accelerated deployment of renewable energy(RE) and early phaseout of coal-powered electricity generation plants.

4,000

12.5

10.0

I M P O RT ( TR I LLIO N J PY )CI F PR ICE (J PY/G J)

3,000

2,000

1,000

7.5

5.0

2.5

C
 oal N.E.S.
LNG
C oal N.E.S.

0

LNG

0.0

1990

2000

2010

2020

1990

2000

2010

2020

FIGURE 1. CIF (Cost, Insurance, and Freight) Price and Annual Import of Coal N.E.S.
and LNG in Japan (nominal)
Note: N.E.S. is a common type of coal for electricity generation

Skyrocketing fossil fuel prices, global constraints on fossil fuel supplies, andambitious climate change targets create strong motivation for shifting to clean
energy. As seen in U.S., Indian, and Chinese analyses, recent advancements anddramatic cost reductions in solar, wind, and battery storage technologies create
new opportunities to improve energy security, maximizing the use of domesticenergy resources while reducing emissions and costs related to electricity
generation (Bistline et al., 2022; Abhyankar et al., 2021, 2022; Phadke et al., 2020).
The economic case to tackle energy challenges with accelerated deployment ofclean energy is particularly strong in fuel-resource-poor countries such as Japan.
Given that global carbon emissions must be halved by 2030 to limit warming to
1.5°C and avoid catastrophic climate impacts (IPCC, 2018), it is imperative thatJapan accelerates its transition to a clean energy grid.

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This report examines the technical feasibility, costs, and implications of Japan
increasing the share of electricity generated from clean (non-fossil) energy to 90%
by 2035. The report aims to answer three key questions:
What effect will recent declines in wind, solar, and battery storage costs haveon the pace and scale of renewable resource development?
What clean energy goals are technically and economically feasible, given
the inherent uncertainties including in electricity demand growth, fossil fuelprices, and RE and energy storage costs?
How can a faster transition to clean energy deliver not only environmental
and economic benefits, but also reduce security risks related to dependence
on imported fossil fuels?
The electricity sector will play a pivotal role in meeting Japan’s environmental
goals. Generation of a larger share of electricity from non-fossil sources, combinedwith electrification of the transportation, industrial, and building sectors, can resultin significant emissions reductions.
This report draws from and expands upon a growing body of literature and analysis
that explore high-renewable and low-carbon power systems around the world.
Several recent studies assessed the operational and economic impacts of a highshare of VRE on Japan’s power grid in the near term (e.g. Komiyama and Fujii, 2014,
Komiyama and Fujii, 2017, Komiyama and Fujii, 2019, Komiyama and Fujii, 2021) andin 2050 (e.g. Matsuo et al., 2018; Matsuo et al., 2020). However, most of the recent
studies did not consider the recent dramatic decline in renewable energy andbattery storage costs, allowed interregional transmission expansions, or exploredthe detailed pathways for deep decarbonization of power systems to a targeted
year, which is often 2050. Our study attempts to build on the existing literature andaddress some of these gaps by (a) developing a spatially and temporally resolved
capacity expansion and economic dispatch model using an industry standard
platform, PLEXOS, that assesses the least cost resource mix at the national level,with interregional transmission requirement, and power plant level hourly economic
dispatch, (b) using the latest renewable energy and storage cost estimates andtrends, informed by prices observed in the market and expert consultations, and(c) explore the opportunities for large CO2 reductions to happen more rapidly whilebolstering Japan’s energy security.
The report is organized into the following sections:• Section 2 provides an overview of methods used in the electricity andemissions analyses.
• Section 3 describes results.
• Section 4 summarizes key conclusions, provides policy recommendations,and outlines priority areas for future research.

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2
METHODS ANDDATA SUMMARY

This study is based on intensive scenario building, cost data development, andpower system modeling using detailed, best-available data inputs, and state-of-theart modeling tools. The analysis combines detailed load, wind, and solar profiles
with projections for RE, and energy storage costs. Generation from any resourcethat does not produce direct CO2 emissions is considered to be clean energy in thisanalysis, including generation from solar, wind, hydropower, biomass, hydrogen, andnuclear sources.
Models are based on a detailed representation of Japan’s electricity system,
including hourly transmission constraints, region-specific wind and solar profiles,
and recent RE and energy storage cost projections.
Analyses found in this report use capacity expansion and hourly dispatch models
developed in PLEXOS (an industry standard capacity expansion and production
cost modeling platform) to analyze the least-cost (optimal) combination ofgeneration, storage, and interregional transmission strategies on an annual basis.
Electricity demand projections are based on government projections and scenarios
described in the 6th Strategic Energy Plan of Japan (GoJ, 2021e)
This section provides a brief overview of the study’s core policy scenario, key inputs
and assumptions, modeling tools and approaches, and sensitivity analyses. The
study appendices include detailed descriptions of methods and inputs used formodeling and the development of hourly load, wind, and solar profiles.

2.1 POLICY SCENARIO
The analysis used in this study examines one core scenario. The Clean Energy
Scenario is consistent with current Japanese policy goals for 2030 and G7’s

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commitment to fully or predominantly decarbonizing electricity by 2035, andexplores whether further expansion of clean energy deployment through 2035 isachievable, dependable, and cost-effective. This scenario is based on clean (nonfossil) energy resources being used to generate a 90% share of Japan’s electricity
by 2035. Sensitivity analyses explore variations on the Clean Energy Scenario.
Table 1 benchmarks the Clean Energy Scenario assumptions against national 2030
and 2035 goals. This study’s assumptions related to coal generation, RE generationand capacity, and the share of electricity generated from non-fossil energy(including RE) sources include:• Coal generation is forced to phase out by 2035.
• The amount of new RE generation that can be added in any given year must
exceed the amount needed to meet current policy targets for 2030.
• After 2030, annual targets for generation of electricity from clean energy
sources must be met.
• The total amount of electricity generated is calculated through leastcost optimization, subject to limits such as 2030 and 2035 clean energy
generation targets, and nuclear power regulatory policy targets.

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TABLE 1. Policy Scenario Assumptions Benchmarked Against National Goals
NATIONAL GOALS

CLEAN ENERGY SCENARIO
ASSUMPTIONS

Reference
policies or plans• New 2030 U.N. NDC Target• 6th Strategic Energy Plan
• Japan 2050 Carbon Neutrality Goal
• G7 pledge to achieve “fully or predominantly decarbonized”
electricity by 2035

Coal generation• G7 pledge to phase out
unabated coal by 2035

• 19% by 2030
(6th Strategic Energy Plan)• All plants phased out by
2035

RE generation
capacity
additions• 36%-38% by 2030
- PV: 103.5 GW - 117.6 GW- Wind: 23.6 GW		 • Onshore 17.9 GW		 • Offshore 5.7 GW• At least 36% by 2030

Clean
(non-fossil)
energygeneration share• 59% by 2030
- RE 36-38%- Nuclear 20%-22%- Hydrogen/Ammonia 1%• 59% in 2030
• 90% in 2035
• Linear increase between
2030 and 2035

Nuclear restart• All operatable plants restart• 20-year extension of
lifetime• 25 GW restart (restartyear depends on individual
plants)• No addition of new nuclear
plantsHydrogen orammonia

1% in 2030

1% in 2030

GW = gigawatts; PV = photovoltaic

2.2 MODELING TOOLS AND APPROACH
The electricity system analysis was conducted using PLEXOS, a modeling platformwidely used for industry-standard power systems analysis. Researchers used a twostage modeling approach.
First, a capacity expansion model was used to develop least-cost generation,
storage, and interregional transmission portfolios each year from 2020 to 2035 forcore and sensitivity scenario. Then, a production cost model was used to examine
2035 operating costs, emissions, and dependability for 8,760 hours based on

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DC power flows; it does not consider the more complex dynamics of AC powersystems. Generation, transmission, and storage investments and operations are
optimized to achieve the 2030 generation mix based on the 6th Strategic Energy
Plan of Japan and 90% clean energy generation with the phaseout of coal-fired
plants by 2035.
Models included generation resources, generation constraints, unit commitments,
and transmission constraints (available transfer capacity) for 10 nodes connectedby 23 gigawatts (GW) of interregional transmission corridors in 2020 (Figure 2).
The model excludes generators that are not dispatched by the transmission &distribution companies (i.e.,off-grid generators are excluded). Analysis assumed
that the electricity system was balanced in every hour, and the 10% planning reserve
margin in the capacity expansion model and three types of operational reserves in
the production cost model were managed at a regional grid scale (for details, see
Appendix B), enabling efficient resource sharing among regions.

FIGURE 2. Generation
Resources and Transmission
Network Includedin the Modeling in 2020

<1.0 GW
1.0—2.0 GW

HOKKAIDO

2.0—4.0 GW
4.0—6.0 GW

KYUSHU
HOKURIKUCHUGOKU

KYUSHUKANSAITOHOKU

TOKYO

CHUBU
SHIKOKU
OKINAWATHE 2035 JAPAN REPORT|

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2.3 KEY MODELING INPUTElectricity Demand
Growth in Japan’s electricity demand between now and 2035 is highly uncertain.
It will depend on the structure and pace of growth or decline in the economy,
the population, and the level of electrification in the transportation, industry, andbuildings sectors.
Electricity demand is projected to decline by 0.8% every year through 2030 inline with the sixth Strategic Energy Plan based on anticipated energy efficiency
improvements and population decline (GoJ, 2021d). Japan’s expected population
drop is significant, from 125.3 million people in 2020 to 112.2 million in 2035 (GoJ,
2022b). Based on these projections, researchers assume electricity demand will
decrease between 2020 and 2030, and then remain stable from 2030 through2035 (see Figure 3). This study excludes generators that are not dispatched by thetransmission & distribution companies (i.e., off-grid generators are excluded). This
study also considers increased electrification of the transportation, industry, andbuildings sectors as part of the sensitivity analysis, where electricity demand isassumed to stay constant rather than decline after 2020.

FIGURE 3. National Electricity
Demand Projection Used in Clean
Energy Scenario

1,000

800

T Wh/ Y E AR

TWh = terawatt hours.
Transmission and distribution loss: 4%
600

400

200

0

2020

2025

2030

2035

THE 2035 JAPAN REPORT|

17

Technology and Fuel Costs
Extensive resource cost inputs included those for wind, solar, and battery storage
technology, as well as coal and natural gas. The United States National Renewable
Energy Laboratory (NREL) Annual Technology Base (ATB) provides projectionsof installed and fixed operation and maintenance (O&M) costs for onshore wind,offshore wind, solar photovoltaic (PV), and battery storage in the United States(NREL, 2022). Plummeting costs for wind and solar energy have dramatically
improved the prospects for rapid, cost-effective decarbonization, leading tolevelized cost of electricity (LCOE) projections for the ATB scenarios being revised
downwards in almost every year between 2015 and 2019 (Phadke et al., 2020).
Projections of installed costs and fixed operations and maintenance (O&M) costs
for generation, energy storage, and interregional transmission lines in Japan are
primarily based on Japan’s cost data. For solar, wind, and battery cost projection,
we combined Japan’s cost data, the 2022 ATB forecasts and industry consultations
with necessary adjustment to reflect Japan’s country-specific factors.
Given simultaneous technological advancements and future cost uncertainties,
offshore wind and battery storage technology costs (low, base, and high priceinputs for the core and sensitivity scenarios) in this study are based on 2020
Japanese costs (Advisory Committee, 2021) and are assumed to converge with
the U.S. costs projected in NREL’s advanced (“Low” in this report), moderate(“Base”), and conservative (“High”) ATB scenarios. Utility and commercial-scalesolar uses ATB’s commercial-scale solar projection due to the relatively small scaleof non-residential solar PV projects in Japan. Onshore wind costs are based on theassumption that the capital costs converge to those of ATB estimates, while noncapital costs are held constant across the study period. Figure 4 summarizes thecapital cost projections of solar, wind, and battery technologies. Grid connection
costs of offshore wind are adjusted according to the proximity between theoffshore wind clusters and high voltage transmission lines. The technology costs ofother technologies are summarized in Appendix B.

THE 2035 JAPAN REPORT|18

SOLAR

WIND
H
 igh

300

200

Base
Low

150
200

TH O U SAN D J PY/K W (2020 J PY )

100
100
50

0

0

OFFSHORE WIND

OFFSHORE WIND—FLOAT
800

600
500

600
400
400

300
200

200
100
0

0

2020

2025

2030

2035

2020

2025

2030

2035

BATTERY

FIGURE 4. Technology Cost Inputs
for Solar PV, Onshore Wind, Offshore
Wind, and 4-Hour Battery Storage

TH O U SAN D J PY/K Wh(2020 J PY )

50
40
30

1 USD = 110 JPY(an average of 2012-2021 exchange rates)

20
10
0

2020

2025

2030

2035

Longer-term fuel price trends in Japan are highly uncertain. Coal and gas pricesrose to record levels in 2011 and 2022 (GoJ, 2022b). The study’s high fuel pricesensitivity scenario bases Japanese fuel prices on the average from January to
September 2022 (GoJ, 2022b). The base fuel price used for the core and additional
sensitivity scenarios is based on the average between July 2012 and December 2021
(Figure 5). This study does not consider a low fuel price scenario, because future
prices will not likely be lower than historical trends given global supply constraints.
Because the study did not model intraregional transmission, the model,
distribution-connected, and transmission-connected resources look the same froman operational perspective. Data on land, incremental distribution, and transmission

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19

costs was not detailed enough to more meaningfully assess the tradeoffs between
utility-scale and distributed resources.

BASE

HIGH

2,000

J PY/G J

1,500

1,000

500

0

LNG

COAL

NUCLEAR

BIOMASSLNG

COAL

NUCLEAR

BIOMASSFIGURE 5. Fuel Price Inputs for Coal and Gas
1 USD = 110 JPY (an average of 2012-2021 exchange rates). GJ = gigajoules.

Solar and Wind Profiles
For this study, we estimated wind and solar resource potential and developed
detailed solar and wind profiles for each region in Japan. The methodology canbe divided into two parts. First part involves estimating the resource potential,i.e., the maximum solar and wind capacity that can be installed in a region. We use
average annual capacity factors from Global Wind and Solar Atlas and multiple
exclusion criteria to estimate the potential. Exclusion criteria include elevation,slope, landcover, natural parks, defense areas, fishery zones and ocean depth.
The second part involves developing detailed hourly generation profiles. We use
meteorological data from reanalysis datasets and simulate site level wind and solar
generation using NREL’s System Advisor Model (SAM) Typical wind and solar farms
are designed in SAM and hourly generation is estimated by passing meteorological
data through it. We then use an aggregation algorithm to combine hourly
generation from multiple sites in a region and create a representative regional wind

THE 2035 JAPAN REPORT|

20

and solar resource profile. For offshore wind we develop multiple clusters for fixedand floating wind using the spatially constrained multivariate clustering algorithm.
We then develop profiles for each of those clusters. Complete methodology anddata sources are discussed in detail in Appendix C.

Nuclear Generation
Because factors other than economics often motivate operation and expansion of
nuclear power facilities, this study bases nuclear generation capacity projections
on policy targets, rather than on cost. As of 2022, 10 nuclear power plants alreadyrestarted, while 7 and 10 nuclear power plants are approved for and under review
for restart, respectively. It was assumed that all of the existing nuclear power plantsthat already applied for approval would resume operation by 2023 (for alreadyapproved plants) and 2025 (for plants under review) under the current aggressive
nuclear restart policy. The base case also assumes every nuclear plant is granted
20-year operating permit extension. As a sensitivity, this study also included ascenario that conservatively assumes no 20-year extension is granted for any
nuclear power plants, except for those already granted extension.

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Other Assumptions
Table 2 summarizes other assumptions used in this study.

TABLE 2. Other Assumptions
PARAMETERASSUMPTIONS

Coal retirements

The retirement of existing coal-fired plants at the end of each of
their 50-year lifetimes, decreasing the amount of coal generationeach year, until coal generation is completely phased out in 2035.

Gas retirements

The retirement of existing gas-fired plants at the end of each of their
50-year lifetimes.

Nuclear extensions

The retirement of existing nuclear plants at the end of each of their
60-year lifetimes including 20-year extension in the base cases.

Transmission
expansions

A maximum 100% increase in existing individual transmission line
capacity.

Solar PVretirements andcapacities

The retirement of solar PV plants at the end of each of their 30-year
lifetimes and an average capacity factor (CF) of 17%.

Wind turbine
retirements andcapacities

The retirement of wind turbines at the end of each of their 30-year
lifetimes and average CFs of 31% (onshore) and 44% (offshore).

Maximum annual
capacity expansion

Solar PV and onshore wind capacity limited to the historicalmaximum for solar PV installations and twice as much as thehistorical maximum for onshore wind turbine installations (based on
2012-2020 data).

2.4 SENSITIVITY ANALYSISThe analysis considered five sensitivities: “High RE and Storage Cost scenario”,“Low RE and Storage Cost scenario”), “High Fuel Cost scenario”, “Low Nuclear
scenario”, and “High Electrification scenario”. These sensitivity cases differ only
from the core Clean Energy Scenario by changing the assumptions for one key
input parameter. Low RE and Storage Cost scenario and High RE and Storage Cost
scenario use our cost projections based on the NREL ATB 2022 advanced andconservative cases, respectively. The High Fuel Cost scenario applies the 2022 level
fuel costs across the entire study period. The Low Nuclear scenario assumes no 20year lifetime extension is granted, except for those that have already been granted
the extension as of 2022. The High Electrification scenario assumes electricity
demand stays constant during the study period.

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22

For dependability, we conducted two types of sensitivity analyses. First, to test
the system dependability during very high system stress, we simulated the hourly
dispatch in the net peak load weeks with an unanticipated demand shock (10%increase in demand in the highest 2035 summer and winter net load periods).
Second, to examine the system dependability impact of the inter-annual variability
in wind, solar, and hydropower generation, we also simulated the hourly operationof the Japan’s power system over 35,040 hours (each hour in 4 weather years).

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23

3
KEY FINDINGSThis section highlights the key findings from this analysis. Results for the sensitivity
analyses are integrated with these key findings. Additional details are provided in
the appendices.

3.1 JAPAN’S 90% CLEAN ENERGY GRID CAN DEPENDABLY MEETELECTRICITY DEMAND WITH LARGE ADDITIONS OF RE AND ENERGYSTORAGE
There has been longstanding debate about whether Japan could dependably
operate electricity systems with high shares of VRE. The study finds that a 90%
clean energy grid that features accelerated solar and wind capacity additions, newbattery storage, and augmented interregional transmission infrastructure can be
combined with a small percentage of the existing fossil fuel-based generation andpumped hydro storage capacity to dependably meet Japan’s electricity demand
without coal generation, while maintaining necessary planning reserve margin andoperating reserves.
In the Clean Energy with base fuel price scenario, clean energy generation increases
from 24% of total generation in 2020 to 59% in 2030. This mix will make it possible
to meet 2030 NDC goals and eventually attain a clean energy generation share of
90% in 2035.
The significant increase in clean energy is mainly supplied by expanding the sharesof energy generated by offshore and onshore wind (26%) and solar PV (27%)(Figure 6). Battery storage capacity grows to 1.5 GW in 2030 and 29 GW in 2035,
to integrate more solar and wind generation. The steep increase in the battery
storage deployment rate in 2030 is dependent on two factors:• Abundant existing pumped hydro storage provide sufficient energy storage
in the 2020s• Solar and wind generation accounting for a relatively small percentage of
total generation in the 2020s (20% in 2025 and 30% in 2029)

THE 2035 JAPAN REPORT|24

Natural gas-fired power, generating the largest share of electricity (37%) in FY 2019,accounts for 10% of total generation in 2035. Retirement of each coal-fired plant as
it reaches 50 years in service reduces the total capacity of these plants by about 45
GW from 2020 to 36 GW in 2035. All existing coal plants, generating 32% of total
electricity supply in FY 2019, are forced to phased out by 2035, and no new fossil
fuel-powered plants are built.
Although not in regular operation, prior to their 50-year retirement, the remaining
coal-fired power plants provide planning reserve margin and operating reserves.
Reservoir hydropower, natural gas, and energy storage also compensate forcapacity shortfalls in extreme climate events such as historic heat wave.
GENERATION ENERGY MIXTOTAL INSTALLED CAPACITY

1,000

500

Battery Storage
Pumped Hydro

750

8%
10%
8%
4%

500

23%
1%
6%
1%

250

400

TOTAL C APACIT Y (GW )G E N E R ATIO N ( T Wh/ Y E AR)

10%

29

Hydro

27

Wind

23

Offshore Wind
Fixed

23
24

Offshore Wind
Float

19

300

25

R
 esidential PV

132

200

25

2
8
3

Utility/
Commercial PV
GeothermalB iomass
HydrogenN uclear

100
20%

76

10%

36

LNG
Coal

0
2020

2025

2030

2035

0
2020

2025

2030

Oil

2035

FIGURE 6. Generation Energy Mix and Total Installed Capacity between
2020 and 2035, Clean Energy Scenario

Researchers also conducted sensitivity analyses with different inputs andassumptions. The difference in generation mix and installed capacity of all scenarios
from the Clean Energy Scenario is summarized in Figure 7.
First, under the High Fuel Cost Scenario, solar and wind technologies deliverelectricity at a price far cheaper than that produced with coal and LNG. This
results in an additional 35 GW of solar and wind capacity, 19 GW of battery storage

THE 2035 JAPAN REPORT|

25

capacity, and 7 GW of interregional transmission lines by 2035 (compared to the
Clean Energy Scenario), leading to 94% clean energy in 2035.
Second, the High RE and Storage Cost sensitivity scenario, with more transmission
facilities and offshore wind plants and fewer solar and energy storage resources,
deploys proportions of resources opposite those of the Low RE and Storage Cost
sensitivity scenario. This trend is due to the relationship between battery storage
and transmission prices. When transmission is cheaper than battery storage,transmission is built to utilize wind resources in distant areas in northern part ofJapan. On the other hand, when battery storage is cheaper than transmission
construction, battery storage enables the deployment of solar PV near load centerssuch as Tokyo, Nagoya, and Osaka.
Third, the High Electrification scenario requires additional solar, wind, battery
storage, and transmission capacity, as well as more frequent natural gas plant
operation.
Fourth, the Low Nuclear scenario suggests that the addition of 9 GW of solar,
14 GW of offshore wind, 17 GW of battery storage, and 11 GW of interregionaltransmission lines can complement retirement of 8 GW of nuclear capacity whenplants reach 40 years of service by 2035.

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26

GENERATION ENERGY MIXTOTAL INSTALLED CAPACITY
75

C APACIT Y D I FFE R E N CE WITH R E S PEC T
TO BA S E C A S E (GW )G E N E R ATIO N DI FFE R E N CE WITH R E S PEC T TO
BA S E C A S E ( T Wh/ Y E AR)

80

40

0

-40

-80
HIGH FUEL
HIGH
HIGH
LOW
LOW
COST
RE AND
RE AND ELECTRIFI- NUCLEAR
STORAGE STORAGE CATION
COST
COST

50

25

0

-25

-50
HIGH FUEL HIGH
LOW
HIGH
LOW
COST
RE AND
RE AND ELECTRIFI- NUCLEAR
STORAGE STORAGE CATION
COST
COST

SCE NAR IO
Battery

Offshore Wind FixedTransmission

LNG

Offshore Wind Float

SCE NAR IO
Wind

Utility/Commercial PV

Nuclear

OthersFIGURE 7. Difference in Generation Mix and Total Installed Capacity in 2035 for
All Sensitivity Scenarios When Compared to Clean Energy Scenario

The study’s dispatch results show that the optimal capacity mix can meet demand
every hour of the year without loss of load in 10 regions, while abiding by technicalconstraints including operating reserves, ramp rates, and minimum generationlevels. Figure 8 shows the average hourly system dispatch for all 12 months of 2035
in the Clean Energy Scenario. Throughout the year, energy storage (including newbattery storage and existing pumped hydro) charges during the day and discharges
at the times in the evening and morning, when solar PV does not generate
electricity to balance the load and variable generation. Despite the addition ofbattery storage, about 9% of available renewable energy must be curtailed annually,as shown in Figure 8.

THE 2035 JAPAN REPORT

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27

1

2

3

4

5

6

7

8

9

10

11

12

200
150
100
50

GW

0
-50

150
100
50
0
-50

0 5 10 15 20 25 0 5 10 15 20 25 0 5 10 15 20 25 0 5 10 15 20 25 0 5 10 15 20 25 0 5 10 15 20 25
Curtailment

Battery Discharging

Offshore Wind Fixed
Biomass

Hydrogen

Pumped Hydro

Offshore Wind Float
Nuclear

Coal

LNG

Residential PV
Battery Charging

Hydro

Wind

Utility/Commercial PV
Hydro Pumping

Geothermal
Average Hourly Load

FIGURE 8. National System Average Hourly Dispatch in 2035 for 12 Months

On the other hand, natural gas plants that operate mostly in high net load (loadminus the output from variable solar and wind RE sources, also known as “residualload”) winter and summer seasons are critical for balancing the grid. Figures 9
and 10 show net loads in the peak weeks of summer and winter, respectively. The
summer net load peaks on August 7 at 8 p.m., when solar generation quickly drops
to zero after sunset, and the system load is still high. The winter net load peaks on
January 30 at 8 a.m., when wind generation decreases, and solar generation does
not yet start.
In both cases, natural gas plants, hydro, and energy storage help balance the peaks.
Even during the highest net load weeks in 2035, the RE share of overall generationis ~59% in the summer and ~72% in the winter, while the annual average share is90%.

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Curtailment

200

Battery Discharging
Pumped Hydro
LNG

150

Hydro
Wind
Offshore Wind Fixed

100

GW

Offshore Wind Float
Residential PV
Utility/Commercial PV

50

Geothermal
Biomass
Hydrogen0

Nuclear
Coal
Battery Charging-50

AUG 05

AUG 07

AUG 09AUG 11

Hydro Pumping
Hourly Load

FIGURE 9. National System Dispatch in the Highest Net Load Week of Summer 2035

Curtailment

200

Battery Discharging
Pumped Hydro
LNG

150

Hydro
Wind

100

Offshore Wind Fixed

GW

Offshore Wind Float
Residential PV

50

Utility/Commercial PV
Geothermal0Biomass
Hydrogen-50

Nuclear
Coal
Battery Charging-100

JAN 28

JAN 30

FEB 01

FEB 03

Hydro Pumping
Hourly Load

FIGURE 10. National System Dispatch in the Highest Net Load Week of Winter 2035

THE 2035 JAPAN REPORT|29

In addition, to further validate the optimal generation capacity needed to meetsystem demand every hour, even during periods of low RE generation and/or
high demand, researchers conducted two sensitivity analyses that simulate hourly
operation of Japan’s power system:• With extreme demand bumps in summer and winter• For four weather years (35,040 hours, using the time-synchronized load dataand solar and wind generation data from 2017–2020)
The first sensitivity analysis showed that with a 10% demand shock (extreme
increase due to a historic heat wave or deep freeze), in which peak demand
increases to from 153 GW to nearly 168 GW, the system still has adequate resources
to meet electricity needs during the highest summer and winter net load weeks(Figures 11 and Figure 12). Coal power plants that have been reserved for such
events briefly operate to support the unusual demand peak during this period.

Curtailment

200

Battery Discharging
Pumped Hydro
LNG

150

Hydro
Wind
Offshore Wind Fixed

100

GW

Offshore Wind Float
Residential PV
Utility/Commercial PV

50

Geothermal
Biomass
Hydrogen0

Nuclear
Coal
Battery Charging-50

AUG 05

AUG 07

AUG 09AUG 11

Hydro Pumping
Hourly Load

FIGURE 11. National System Dispatch in the Highest Net Load Week in Summer
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30

Curtailment

300

Battery Discharging
Pumped Hydro
LNG
Hydro

200

Wind
Offshore Wind Fixed

GW

Offshore Wind Float
Residential PV

100

Utility/Commercial PV
Geothermal
Biomass0

Hydrogen
Nuclear
Coal
Battery Charging-100

JAN 28

JAN 30

FEB 01

FEB 03

Hydro Pumping
Hourly Load

FIGURE 12. National System Dispatch in the Highest Net Load Week in Winter 2035,
with a 10% Demand ShockThe second sensitivity analysis with dispatch simulation showed that the optimal
capacity mix could meet the electricity load of 10 regions for each hour across aspan of four weather years (35,040 hours in all), while still abiding by technicalconstraints (see Appendix B for details). During the four weather years, thestudy finds significant seasonal (intrayear) variation in load and solar and wind
generation, as shown in Figure 13.
Daily loads peak twice in summer (August) and winter (January) months at 2,979–
3,195 GWh/day. (This and future metrics are based on a seven-day moving average.)
Solar generation peaks in late May–July at 768–818 GWh/day. Onshore and offshore
wind generation peaks in the winter at 678–766 GWh/day in January.
The load hits the bottom in late April or early May at 1,751–1,918 GWh/day (59%–63%of its peak). Solar and wind generation decline the most in fall and winter (Octoberthrough January) at 213–316 GWh/day (26%–41% of its peak). The next-lowest
generation period for RE is in the summer (June through September), with solar at
41–55 GWh/day (11%–15% of its peak) and wind at 110–177 GWh/day (14%–26% of its
peak.
Natural gas plants play a critical role in balancing loads with the seasonal variabilityof RE at multiple timescales. Battery storage, pumped hydro, and natural gas plants
play critical roles in daily and hourly balancing.

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31

While the annual capacity factor of natural gas plants is 21%–26%, the monthly
summer capacity factor is as high as 51%. In the 2050-time horizon, long-durationenergy storage such as hydrogen plus RE can replace the seasonal balancing
function of natural gas plants (Mahmud et al., 2023) but existing natural gas plants
can play a pivotal role in the short- and mid-term period, maintaining power systemdependability at a relatively low cost.

LOAD
4,000
3,000
2,000
1,000
0

LNG

GWh/DAY

1,250
1,000
750
500
250
0

OFFSHORE WIND
1,000
750
500
250
0

ONSHORE WIND
500
400
300
200
100
0

SOLAR
1,000
750
500
250
0

JAN 2035 JUL 2035 JAN 2036 JUL 2036 JAN 2037 JUL 2037 JAN 2038 JUL 2038 JAN 2039
Seven-day moving averages

FIGURE 13. Daily Load and Power System Dispatch of Natural Gas and Variable
Renewable Generation Over 4 Weather Years in the 90% Clean Case

3.2 CLEAN ENERGY DEPLOYMENT CAN REDUCE WHOLESALE ELECTRICITYCOSTS BY 6%
The Clean Energy Scenario’s average wholesale electricity costs suggest that the2035 policy goals for additions to renewable generation capacity can be costeffective. Average wholesale electricity costs are lower in 2035 under the 90%
Clean Energy Scenario than they are in 2020 (Figure 14). In the Clean Energy
Scenario, the average 2035 wholesale electricity cost (9.03 JPY/kWh) is 6% lower

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32

than the average 2020 average wholesale cost (9.67 JPY/kWh) (Figure 15) underconservative fuel price assumptions based on 2012–2021 averages. If social costs ofcarbon (SCC) is included, wholesale electricity costs are about 36% lower in 2035
under the Clean Energy Scenario than they are in 2020, assuming 12,980 JPY/t-CO2($118/t-CO2) at 2.5% discount rate from the latest study (Rennert et al., 2022). All
scenarios in this study include the current level of Global Warming CountermeasureTax, 289 JPY/t-CO2 ($2.6/t-CO2), not the SCC presented here.
Average wholesale electricity costs are total wholesale electricity costs divided
by total generation. Here, wholesale electricity costs include costs for installedcapacity, fixed O&M, fuel for generation, energy storage, and incremental
interregional transmission investments. Distribution costs and existing transmission
costs are not included.

10.0

Transmission
Battery Discharging
Hydro
Wind

TR I LLIO N J PY/ Y E AR

7.5

Offshore Wind Fixed
Offshore Wind Float
Residential PV
Utility/Commercial PV

5.0

Geothermal
Biomass
Hydrogen

2.5

Nuclear
LNG
Coal
Oil

0.0

2020

2025

2030

2035

FISC AL Y E AR

FIGURE 14. Annual Wholesale Electricity Costs in 2020 JPY, Clean Energy Scenario
The cost of electricity generated by RE sources depends less on volatile fossil fuelprices and more on the capital costs (Figure 14). Given the lead time required forconstruction of power plants and transmission lines, proactive planning is essential
to expedite the process.

THE 2035 JAPAN REPORT|33

W/O SCCW SCC

AVE R AG E WH O LE SALE COSTS (J PY/K Wh)

15

10

5

0

2020

2025

2030

2035

2020

2025

2030

2035

FIGURE 15. Average Wholesale Electricity Costs with and without Social Costs ofCarbon (SCC) for the Clean Energy Scenario

In the Clean Energy Scenario, RE coupled with enhanced energy storage andinterregional transmission lines make it possible to displace a significant amountof generation from existing coal and natural gas plants, while maintaining grid
dependability and decreasing wholesale electricity costs. The incremental costof developing new solar and wind plants, battery storage, and transmission
infrastructure in the Clean Energy Scenario is smaller than the fossil fuel, operationand maintenance (O&M), and fixed costs found in running today’s typical fossil fuelfired plants (Figure 16).

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34

4
Transmission
Battery Storage

TR I LLIO N J PY/ Y E AR

2

Hydro
Wind
Offshore Wind Fixed

0

Offshore Wind Float
Residential PV
Utility/Commercial PV
Geothermal-2

Biomass
Hydrogen
Nuclear

-4

Oil
Coal
LNG

-6

INCREMENTAL
COST

INCREMENTAL
SAVINGSNETSAVINGS

FIGURE 16. Incremental Costs, Incremental Cost Savings, and Incremental Net Costs
in the Clean Energy Scenario, between 2020 and 2035 (in 2020 JPY)

The sensitivity analysis shows that the
90% clean energy grid is affordable
based on a number of assumptions
as shown in Figure 17. With 2022-level
fuel costs (High Fuel Costs Scenario)
and replacement of most of current
natural gas and all of coal plants withnew renewables, the average wholesalecosts can be significantly reduced by
31% between 2020 and 2035. In all
the other scenarios with the base fuelcosts, the average wholesale costsof the 90% clean energy grid arestable within a range of -10% (Low RE
and Storage Costs) and +0.6% (Low
Nuclear). The sensitivity analyses showthat average 2035 generation costs
could increase by as much as 0.4%
with high RE and storage costs, ordecrease by as much as 10% as a resultof low RE and storage costs.

THE 2035 JAPAN REPORT|35

AVE R AG E WH O LE SALE COSTS (J PY/K Wh)

15

FIGURE 17.
Average Wholesale
Electricity Costs
in 2020 JPY of
All Scenarios

10

Base
High Fuel Cost scenario

5 igh RE and Storage Cost
H
scenario ow RE and Storage Cost
L
scenario
High Electrification
scenarioLow Nuclear scenario

0

2020

2025

2030

2035

3.3 90% CLEAN ENERGY DELOYMENT CAN REDUCE FOSSIL FUEL IMPORTCOSTS BY 85%, BOLSTERING JAPAN’S ENERGY SECURITY
Under the 90% Clean Energy Scenario with base fuel prices, imported coal andnatural gas costs would decrease by 85%, from 3.9 trillion JPY in 2020 to 0.59
trillion JPY in 2035 (Figure 18). The scenario’s base fuel prices offer even greatersavings when compared with 2022 levels.
The study estimates final average 2022 imported coal and natural gas costs, basedon the current high fuel prices, at 7.3 trillion JPY. In 2022, in a single year, the LNG
prices doubled and coal prices more than tripled in comparison the averages acrossthe previous 10 years (2012–2021).
Not only would the 90% clean energy grid translate into lower electric bills.
Maximizing Japan’s use of domestic renewable resources would significantly
decrease the nation’s heavy dependence on imported fossil fuels. In turn, this would
bolster Japan’s energy security, and insulating the economy from skyrocketinginternational fossil fuel prices.

THE 2035 JAPAN REPORT|36

FU E L COSTS ( TR I LLIO N J PY/ Y E AR)

4

FIGURE 18. Imported Fuel Costs forPower Generation Under the Clean
Energy Scenario in 2020 JPY

3

2

1

Coal
LNG

0

2020

2025

2030

2035

FISC AL Y E AR

3.4 SCALING-UP RENEWABLES TO ACHIEVE A 90% CLEAN ENERGY GRID ISFEASIBLE
Under the 90% Clean Energy Scenario, the combined capacity of all RE sources
rises from 90 GW in 2020 to 188 GW in 2030 and 254 GW in 2035 (Figure 19). In
particular, accelerated wind and solar capacity growth makes the 90% clean energy
grid feasible.
On average, an additional 10 GW of renewable energy need to be brought online
each year (from 2020 to 2035). This annual increase, comparable to Japan’s singleyear renewable buildout record of 9.7 GW (FY 2015), is challenging but feasible.
Solar power additions are dominant in 2020s, while offshore wind’s continued
technology cost declines and high capacity factors make it the dominant growtharea in the 2030s. This shift to clean energy will require attention to rapidly break
down institutional, market, and regulatory barriers.

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AVE R AG E AN N UAL C APACIT Y AD DITIO N(GW/ Y E AR)

15

FIGURE 19.
Average Annual Renewable
Capacity Additions by
Periods, Clean Energy
Scenario

JAPAN'S SINGLE YEAR RE DEPLOYMENT RECORD
10(9.7 GW IN FY2015)

Wind
Offshore Wind Fixed

5

Offshore Wind Float
Residential PV
Utility/Commercial PV
Other RE0

FY 2014-FY 2019
(HISTORICAL)

Y2020-Y2025

Y2026-Y2030

Y2031-Y2035

It will also call for swift advancements in battery storage and interregionaltransmission lines to balance VRE generation against loads. Battery storage
capacity grows to 1.5 GW in 2030 and 29 GW in 2035, at the rate of 6 GW/year
in 2030s. While 5.5 GW in transmission capacity additions have already been
approved between now and 2028, an additional 6.3 GW of expansion is needed tosupport 90% clean energy deployment (Figure 20). These outcomes rely on thefollowing aspects of the Clean Energy Scenario:• Deep reductions in installed costs for solar PV and wind power make itpossible to cost-effectively build these systems.
• Low-cost grid-scale battery storage allows for development closer to load
centers, reducing requirements for expensive long-distance transmission
lines and investments in grid balancing.
• Electricity demand is not expected to grow between 2020 and 2035,
minimizing incremental increases transmission investment.

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ADDITIONALEXPANSION
6.3 GW

TR AN S M ISS IO N C APACIT Y [GW ]40

ALREADY
PLANNEDEXPANSION
5.5 GW30

Chubu Hokuriku
Chubu Kansai
Chugoku Kyushu
Chugoku Shikoku
Hokkaido Tohoku

EXISTING
LINE 23
GW

Hokkaido Tokyo
Hokuriku Kansai
Kansai Chugoku

20

Kansai Shikoku
Tohoku Tokyo
Tokyo Chubu

10

0

2020

2025

2030

2035

<1.0 GW
1.0—3.0 GW
3.0—5.0 GW>5.0 GW

FIGURE 20.
Transmission
Capacity Expansion
by 2035 in Clean
Energy Scenario

Under the Clean Energy Scenario, the 90% clean energy grid requires 38 trillion JPY(real 2020 JPY) of cumulative investment from 2020 to 2035 (Fig 21). This capital
investment in predominantly RE generation, battery storage, and interregionaltransmission is essentially financed with fossil fuel cost savings. This represents 27%of the Japanese government’s goal of public and private “green transformation(GX)” investments totaling 150 trillion JPY over the next decade (GoJ, 2022a).
Japanese Government defines GX as “structural transition from fossil-fuel centeredindustry and society to clean energy centered industry and society (ibid).

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FIGURE 21. Cumulative New
Capital Investment for Generation
and Transmission, 2020–2035,
Clean Energy Scenario

CU M U L ATIVE I NVE STM E NT ( TR I LLIO N J PY )40

30

Transmission
Battery Storage

20

Wind
Offshore Wind Fixed
Offshore Wind Float
Residential PV

10

Utility/Commercial PV
Geothermal
Biomass
Hydrogen

0

2020

2025

2030

2035

3.5 CLEAN ENERGY CAN CUT CO2 EMISSIONS BY 92%, PROVIDINGSIGNIFICANT ENVIRONMENTAL BENEFITS
Generating 90% of electricity from clean energy by 2035 would significantly cut
CO2 emissions, resulting in important environmental benefits. As shown in Figure
22, By 2035, the Clean Energy Scenario was shown to potentially reduce electricity
sector CO2 emissions by 92% (345 million tons of CO2, approximately equivalent to
30% of Japan’s total CO2 emissions in FY 2019) compared to 2020 levels. According
to simulation results, this is possible as the emission intensity of electric generation
drops by 91% from 404 kilograms (kg)–CO2/kilowatt hour (kWh) in 2020 to 36
kg–CO2/kWh in 2035. The extremely low emission intensity supports deeper
decarbonization of other sectors, such as electrified transportation, heating, andmore.
It also reduces exposure to fine particulate matter (PM2.5), sulfur dioxide (SO2),
nitrogen oxide (NOx), and heavy metals (e.g., mercury, cadmium, arsenic, chromium,and beryllium) emitted by fossil fuel-burning power plants (J. Lelieveld et al., 2015;
Ito, 2010). This could deliver significant health benefits, potentially extending
lifespan.

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40

400

C AR BO N I NTE N S IT Y (KG - CO2 /K Wh)

CO2 E M ISS IO N (M I LLIO N TO N N E )

400

300

200

100

300

200

100

0

0

2020

2025

2030

2035

2020

2025

2030

2035

FIGURE 22. CO2 Emissions and Carbon Intensity, Clean Energy Scenario

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4
CAVEATS AND
FUTURE WORK

Although we assessed an operationally feasible least-cost pathway of Japan’s
power system using weather-synchronized load and generation data, further work
is needed to advance our understanding of other facets of a 90% clean powersystem. First, this report primarily focuses on renewable-specific technology
pathways rather than explore the full portfolio of clean energy technologies.
The technologies and approaches examined in this report could contribute todeep decarbonization of the future electricity supply, lowering system costs
while accelerating emission reductions. Additionally, issues such as loss of load
probability, system inertia, alternating-current (AC) transmission flow of both
intra- and inter- regional transmission lines, and issues in AC power system such asreactive power compensation need further assessment. Options to address theseissues have been identified elsewhere (for example, Denholm, 2020).
Second, our assessment does not explicitly address the operational impacts of
day-ahead / intra-day forecast errors in RE and load, while we included operating(spinning) reserves in our production cost model to ensure the least-cost system
has a certain capability to address such forecast errors. However, several studies
have shown that with state-of-the-art forecasting techniques and the shorter gate
closure time, the impact of such forecast errors appears to be small (for example,
Hodge, 2015; Martinz-Anido, 2016; IEA Wind TCP Task 25, 2021).
Although this analysis does not attempt a full power-system dependability
assessment, we perform scenario and sensitivity analysis to ensure that demandis met in all periods, including during extreme weather events and periods of low
renewable energy generation. This modeling approach provides confidence that a
90% clean electricity grid is operationally feasible.

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5
CONCLUSIONSAND POLICYINSIGHTS

Sustained declines in costs for wind, solar, and energy storage technologies create
new opportunities to lower Japan’s wholesale electricity costs and reduce related
emissions. The results of this study suggest that expanding Japan’s share ofelectricity generated from clean energy sources to around 59% by 2030, and thento 90% by 2035, would deliver the needed reductions in electricity costs, while
making it possible to meet carbon neutrality and air quality improvement goals.
Transitioning to a system with 90% of electricity generated from clean energy
sources would require overcoming barriers to the development and integrationof wind generation, solar generation, and energy storage technologies. This final
section summarizes the study’s key conclusions, provides recommendations
for changes in policy and regulation based on the results, and outlines possible
priorities for future research to meet those challenges.

5.1 KEY CONCLUSIONS
Declining wind, solar, and energy storage costs are changing the economicsof Japan’s electricity sector. This analysis illustrates emerging changes in theeconomics of Japan’s electricity sector. In the selected scenarios, the lowest-costresources for meeting electricity demand growth combine wind, solar, and energy
storage.
Japan’s electricity system can be dependably operated with high levels of
clean energy generation. The base fuel price case analysis shows that a highly
dependable system is possible with 90% of Japan’s electricity provided by clean
energy sources, without any coal generation. This 2035 generation model is shown

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to operate dependably with a mix of 59% (in summer) to 72% (in winter) wind andsolar energy—even during unanticipated load increases.
Increasing clean energy generation would deliver additional emission reduction
and health benefits. Increasing the share of clean energy generation to 90% ormore by 2035 would significantly cut CO2 emissions. Additional reductions in air
pollutant emissions can be delivered by widespread electrification of the greater
economy, offering environmental and health benefits beyond the scope of thisstudy.
For instance, an accelerated shift to electric vehicles and batteries charged withpower from clean energy plants will reduce both vehicle tailpipe and power plantemissions. The combination of electrification and clean energy generation would be
a powerful force in hastening progress toward Japan’s environmental goals.
Reaching cost-effective levels of clean energy generation will require overcoming
barriers to wind, solar, and energy storage development and integration. The
Clean Energy Scenario involves an unprecedented scale of wind, solar, and energy
storage development. From 2030 to 2035 in the Clean Energy Scenario, RE
generation grows from nearly 188 GW to 254 GW in 2035. Battery storage grows
to 29 GW by 2035. Successfully adding clean energy systems to the grid at thisscale and in this time frame requires significant changes in regulations, markets,
operations, and land use.
Meeting 2035 goals will rely on a shift to a low-cost RE pathway that begins now.
For the share of electricity generated from RE sources to begin its acceleration in
the 2020–2035 time period (as in the Clean Energy Scenario), policy and regulatorychanges to support this deployment need to be immediately implemented. While
there already may be momentum behind the accelerated growth of wind and solar
energy development, lowering remaining barriers to rapid expansion of battery
storage has yet to be made a near-term priority.

5.2 POSSIBLE FUTURE ACTIONSThe enabling conditions needed to deliver benefits in five key areas are:Establishing Medium-Term Policy Targets (Beyond 2030)
This study has shown that the clean energy transition will require massive
investments in generation, storage, and transmission, and significant technologicalinnovation. Possible technological and policy options to support the transition are

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diverse. To avoid technology lock-in and investment in future stranded assets thatlead to high costs in the power system, Japan needs medium-term policy targets
to guide technology development and capital investment (Hidalgo-Gonzalez et al.,2021).
While a 2030 short-term target for the generation mix and a long-term 2050
carbon neutrality goal have been set (GoJ, 2021d), Japan has not establishedintermediate RE and emissions targets to bridge between those 2030 and 2050
objectives. Specific policy schemes to support these targets, such as carbon
pricing, have yet to be presented. Given that energy projects typically require morethan a decade of planning and capital investment, the need to set medium-term
policy targets beyond 2030 is urgent.
The Japanese government plans to invest trillions of dollars in decarbonization
technologies through the Green Innovation Fund (GoJ, 2021c) and Green
Transformation (GX) Bonds (GoJ, 2022a) to achieve carbon neutrality by 2050. In
allocating these massive amounts of public funds, it is essential to align plans withmedium- and long-term policy targets to maximize cost-effectiveness.

Accelerating RE Deployment and Coal-Fired Power Phaseout
Carbon emissions are the representative environmental externalities. In principle,
internalizing the societal cost of carbon (SCC) with carbon pricing is vital toefficiently reduce carbon emissions (Rode et al., 2021).
Estimates of the SCC vary widely. For example, the U.S. Environmental Protection
Agency proposed increasing their estimate of the SCC from the current standardof 51 USD /t-CO2 to 190 USD /t-CO2 (Interagency Working Group, 2021). Currently,
Japan’s carbon price is 289 JPY /t-CO2 (2.6 USD /t-CO2). The Japanese governmentis currently planning to introduce a new emissions trading scheme, which will
include the electric power sector starting in 2026 (GoJ, 2022a).
Increasing the carbon price closer to the level of the estimated SCC should
accelerate the clean energy transition. Carbon taxes and emissions trading havebeen introduced in many countries worldwide and across industries including theelectric power sector (e.g., RGGI in the U.S., California, EU-ETS, Canada, and China).
However, an immediate, significant increase in carbon price to match the SCC isoften politically or economically infeasible. In those instances, a combination ofother policy measures is called for to achieve a clean energy transition.

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Japan has supported various types of RE through feed-in tariffs (FIT), including
the newly introduced Feed-in Premium (FIP). Unlike the typical renewable portfolio
standard (RPS), which encourages competition among RE technologies, a FIT
controls the deployment rate of different RE technologies through tailored financial
incentives (Lesser & Su, 2008). This makes mass deployment practical and could
result in cost reductions for offshore wind power in Japan.
Carbon pricing and FIT are both needed for an economically feasible phaseout ofcoal-fired power generation, the largest source of CO2 emissions in Japan’s electric
power system. Based on this study’s analysis, 99% of coal can be phased out by
2035 by linearly increasing the carbon price from 289 JPY /t-CO2 (2.6 USD /t-CO2)
in 2020 to 6,000 JPY /t-CO2 (55 USD /t-CO2) in 2035, assuming the base fuelprices used in this paper (see Appendix D).
This price is low compared to existing or planned carbon prices in other developed
countries (approximate JPY equivalents):• European Union: About 90 Euros (EUR) /t-CO2 in 2022 (12,600 JPY/t-CO2, 1
EUR = 140 JPY)
• Canada: 65 Canadian Dollars (CAD) /t-CO2 in 2023 and 170 CAD /t-CO2 in
2035 (6,500 JPY/t-CO2 in 2023 and 17,000 JPY/t-CO2 in 2035, 1 CAD = 100
JPY)• Singapore: 25 Singapore Dollars (SGD) /t-CO2 in 2024, 45 SGD /t-CO2 in
2026, and 50–80 SGD/t-CO2 in 2030 (2,500 JPY/t-CO2 in 2024, 4,500 JPY/tCO2 in 2026, 5,000-8,000 JPY/t-CO2 in 2030, 1 SGD = 100 JPY)
Furthermore, the revenue from carbon pricing can be used as a financial resourcefor public and private investment in decarbonizing technologies. In addition, as
shown in below, the tax burden of carbon pricing can be mitigated by partial
reimbursement.

Reducing Institutional and Societal Barriers to Rapid RE Deployment
In addition to economic barriers, there are institutional and societal barriers to
the large-scale, rapid deployment of RE, including potential community andenvironmental impacts of RE projects, delays in the administrative process suchas permits and approvals, and investment risks. Some RE projects have reportedly
led to societal and environmental debates that span entire countries (Segreto etal., 2020), including in Japan. For the large-scale, rapid deployment of RE, it isnecessary to eliminate not only economic barriers presented by carbon pricing and
FIT, but also these institutional and societal barriers.

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To properly weigh societal and environmental considerations and to expedite thepermitting process for construction and connection to the grid, multi-stakeholder
processes have proven effective in the selection and zoning of suitable sites (USAID
and NREL, 2017). Lack of social acceptance can be a significant obstacle to RE
development in countries worldwide, including Japan.
Renewable energy zones (REZs) are geographic areas with high-quality RE
resources that have been pre-qualified as socially and environmentally suitablefor development. Early involvement of relevant stakeholders in selecting REZs caneffectively avert development issues, helping expedite the permitting and approval
process. Texas and California have selected REZs for wind energy, solar power,
and transmission line projects since the late 2000s to streamline development andpermitting, reduce economic costs, and minimize environmental impacts.
In addition, inexpensive RE and cost-effective RE deployment need to be madenational priorities. Because the benefits of enhanced energy security and reduced
emissions are enjoyed by the nation as a whole, power transmission investments
should be allocated nationwide, (Andrade & Baldick, 2017). A transmission line
master plan s is currently being developed by the Organization for Cross-regional
Coordination of Transmission Operators, Japan (OCCTO) to integrate high share of
renewable electricity.

Pursuing a Just Energy Transition through Targeted Assistance Policies
Economic pain inflicted on the few will never result in a just energy transition(Wang & Lo, 2021). This can be addressed in part by refunding a portion of therevenue from carbon pricing to individual households with programs such as
California’s climate credits and Canada’s climate action incentives. Allocating therevenues from carbon pricing to benefit disadvantaged/low-income communities
is another effective strategy to ensure a just transition. For example, at least
35% of California’s cap-and-trade auction revenue is allocated for the use of
disadvantaged/low-income communities in dealing with environmental justiceissues.
The socioeconomic impacts of coal-fired power phaseout on local communities
and businesses also require mitigation. Carbon price revenues can soften theeconomic and workforce impacts of plant closures by funding training for local
workers in new skills, financial compensation, and accelerated depreciation to local
communities and company employees. For example, under the American Rescue
Plan Act of 2021 and the Inflation Reduction Act of 2022, the U.S. governmentis facilitating the transition from coal to renewable energy. These efforts include
establishing financial and technical assistance through the Just Transition Fund andthe National Economic Transition Platform.

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Ensuring Power System Dependability, Enhancing Operational Flexibility, andBoosting Energy Efficiency
As presented in this study, it is especially vital to ensure flexibility and dependability
in a grid dominated by solar and wind power, with their inherent variability anduncertainty. When transitioning from a fossil fuel-based power system to a REbased power system, there is a risk of jeopardizing the dependability of energy
systems without adequate coordination (Grubert & Hastings-Simon, 2022).
Flexibility can be supported by flexible gas-fired and hydropower plants, energy
storage systems, and demand side management and measures (e.g., demand
response and vehicle-to-grid) (Degefa et al., 2021). Appropriate design of capacity
and ancillary service markets and profitable business models are necessary to
encourage sufficient investments in these and other flexibility resources.
Battery storage significantly contributes to the dependability of the electric powersystem, as this analysis has shown. Policy targets can encourage commercializationof battery storage and help secure revenue in the various capacity and ancillary
service markets.
In addition, subsidies or a mandate to deploy a certain level of battery storage
can be effective at the early stages of battery storage deployment, when thetechnology and markets are still relatively immature. The U.S. federal government
provides an investment tax credit (ITC) for battery storage installed with solar
power under the Inflation Reduction Act of 2022 (Inflation Reduction Act of 2022,2022). In addition, nine U.S. state governments mandate electric utilities to procure
or install battery storage.
Demand response measures also have great potential to ensure the dependabilityof the electricity system, especially in response to the record heat and cold waves
expected to become more frequent as climate change progresses. Similarly, thecapacity and ancillary markets enable natural gas-fired, flexible thermal power
generation to play a role in ensuring the system’s dependability on summer andwinter peak load days.
This proposed investment in the transmission and distribution network will also
improve the system’s dependability by sharing planning reserve margin andoperating reserves among regions and smoothing the fluctuation of loads andvariable renewable energy generation. Constructing a transmission and distribution
network requires a long lead time of about 5 to 10 years, which makes earlyplanning all the more crucial.
Energy efficiency measures are effective in improving dependability and lowering
power system costs (Relf et al., 2018). Record heat and cold waves associatedTHE 2035 JAPAN REPORT|48

with climate change are expected to cause future increase in peak loads. Building
insulation will lower these peak loads and strengthen the dependability of thepower system. Since the economic payback time of insulation is typically short,mandatory measures such as strengthening insulation requirements in building
codes are often most effective for new buildings. On the other hand, financial
incentives can be more effective for retrofitting existing building stock.
Through these possible actions, the swift decarbonization of Japan’s electricity
system would make it possible to more quickly electrify other demand sectors,
reducing CO2 emissions and smoothing the country’s path to a carbon-neutral
economy by 2050.

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REFERENCES

Abhyankar, N., Deorah, S., & Phadke, A. (2021). Least-Cost Pathway for India’s Power
System Investments through 2030. https://eta-publications.lbl.gov/sites/default/
files/fri_india_report_v28_wcover.pdf
Abhyankar, N., Lin, J., Kahrl, F., Yin, S., Paliwal, U., Liu, X., Khanna, N., Phadke, A.,& Luo, Q. (2022). Achieving An 80 Percent Carbon Free Electricity System
In China By 2035 - Energy Innovation: Policy and Technology. https://energyinnovation.org/publication/achieving-an-80-percent-carbon-freeelectricity-system-in-china-by-2035/
Advisory Committee for Natural Resources and Energy of Japan. (2021). Generation
costs report for long-term energy projection subcommittee (Japanese).
Andrade, J., & Baldick, R. (2017). Estimation of Transmission Costs for New
Generation. https://energy.utexas.edu/sites/default/files/utaustin_fce_transmissioncosts_2017.pdf
Bistline, J., Abhyankar, N., Blanford, G., Clarke, L., Fakhry, R., McJeon, H., Reilly,J., Roney, C., Wilson, T., Yuan, M., & Zhao, A. (2022). Actions for reducing US
emissions at least 50% by 2030. Science, 376(6596), 923–924. https://doi.
org/10.1126/science.abn0661/suppl_file/science.abn0661_sm.pdf
Burrough, P. A., and McDonell, R. A., (1998). Principles of Geographical Information
Systems, Oxford University Press, New York, 190 pp.
Committee on the Procurement Prices of Renewable Electricity. (2022). Reportson the Procurement Prices of Renewable Electricity. https://www.meti.go.jp/
shingikai/santeii/
Degefa, M. Z., Sperstad, I. B., & Sæle, H. (2021). Comprehensive classifications andcharacterizations of power system flexibility resources. Electric Power Systems
Research, 194, 107022. https://doi.org/10.1016/j.epsr.2021.107022
European Centre for Medium-Range Weather Forecasts (ECMWF). (2020).
European Center for Medium-Range Weather Forecast’s Reanalysis 5thGeneration (ERA-5). https://www.ecmwf.int/en/forecasts/datasets/reanalysisdatasets/era5

THE 2035 JAPAN REPORT|

50

Global Modeling and Assimilation Office (GMAO). (2015). Modern-Era Retrospective
analysis for Research and Applications, Version 2. doi: 10.5067/vjafpli1csiv
Government of Japan (GoJ). (2021a). Amendment of the Act on Promotionof Global Warming Countermeasures (testimony). https://www.env.go.jp/
press/109218.html
GoJ. (2021b). Annual Whitepaper on Energy 2020. https://www.enecho.meti.go.jp/
about/whitepaper/
GoJ. (2021c). Green Innovation Fund. https://www.meti.go.jp/policy/energy_
environment/global_warming/gifund/index.html
GoJ. (2021d). Japan’s Nationally Determined Contribution (NDC). https://unfccc.
int/sites/default/files/ndc/2022-06/japan_first%20ndc%20%28updated%20
submission%29.pdf
GoJ. (2021e). Japan’s Sixth Strategic Energy Plan. https://www.enecho.meti.go.jp/
category/others/basic_plan/
GoJ (2021f). Cost information of power plants in Japan. https://www.enecho.meti.
go.jp/committee/council/basic_policy_subcommittee/mitoshi/cost_wg/pdf/
cost_wg_20210908_02.pdf
GoJ. (2022a). Green Transformation (GX) Executive Meeting (4th). https://www.cas.
go.jp/jp/seisaku/gx_jikkou_kaigi/dai4/index.html
GoJ. (2022b). Trade Statistics of Japan. https://www.customs.go.jp/toukei/info/
index_e.htm
Grubert, E., & Hastings-Simon, S. (2022). Designing the mid-transition: A review of
medium-term challenges for coordinated decarbonization in the United States.
In Wiley Interdisciplinary Reviews: Climate Change (Vol. 13, Issue 3). John Wileyand Sons Inc. https://doi.org/10.1002/wcc.768
Hidalgo-Gonzalez, P. L., Johnston, J., & Kammen, D. M. (2021). Cost and impact of
weak medium term policies in the electricity system in Western North America.
The Electricity Journal, 34(3), 106925. https://doi.org/10.1016/j.tej.2021.106925
Interagency Working Group on Social Cost of Greenhouse Gases. (2021). TechnicalSupport Document: Social Cost of Carbon, Methane, and Nitrous Oxide Interim
Estimates under Executive Order 13990.
Intergovernmental Panel on Climate Change (IPCC). (2018). Special Report: Global
Warming of 1.5°C. https://www.ipcc.ch/sr15/
IEA Wind TCP Task 25 (2021), Design and operation of energy systems with large

THE 2035 JAPAN REPORT|

51

amounts of variable generation, Final summary report. https://publications.vtt.
fi/pdf/technology/2021/T396.pdf
IRENA (2017), Planning for the Renewable Future: Long-term modelling and tools
to expand variable renewable power in emerging economies, International
Renewable Energy Agency, Abu Dhabi. /-/media/Files/IRENA/Agency/
Publication/2017/IRENA_Planning_for_the_Renewable_Future_2017.
pdf?rev=8bf1e29230e74ce39e19b6f3bfd5914d
Ito, S. (2010). Trace Substance Emissions from Coal Combustion and Recent Topics.
Proceedings of the Society of Chemical Engineers, Japan, 2010f (0), 346-347
Japan Electric Power Exchange (JEPX). (2022). HJKS: Hatsudensho Joho Kokai
System https://hjks.jepx.or.jp/hjks/
Komiyama, R., Fujii, Y. (2014). Assessment of massive integration of photovoltaic
system considering rechargeable battery in Japan with high time-resolution
optimal power generation mix model, Energy Policy, 66, 73-89, https://doi.
org/10.1016/j.enpol.2013.11.022.
Komiyama, R., Fujii, Y. (2017). Assessment of post-Fukushima renewable energy
policy in Japan’s nation-wide power grid. Energy Policy, 101 (C), 594-611
Komiyama, Ryoichi & Fujii, Yasumasa, (2019). Optimal integration assessment ofsolar PV in Japan’s electric power grid, Renewable Energy, 139(C), 1012-1028.
Lelieveld, J., Evans, J., Fnais, M. et al. (2015) The contribution of outdoor air
pollution sources to premature mortality on a global scale. Nature 525, 367–371.
https://doi.org/10.1038/nature15371
Lesser, J. A., & Su, X. (2008). Design of an economically efficient feed-in tariffstructure for renewable energy development. Energy Policy, 36(3), 981–990.
https://doi.org/10.1016/j.enpol.2007.11.007
Matsuo, Y., Endo, S., Nagatomi, Y., Shibata, Y., Komiyama, R., Fujii, Y., (2020)
Investigating the economics of the power sector under high penetrationof variable renewable energies, Applied Energy, 267, 113956, https://doi.
org/10.1016/j.apenergy.2019.113956.
Muhmud, Z., Shiraishi, K., Abido, M. Y., Sánchez-Pérez, P. A., Kurtz, S. (2023).
Hierarchical approach to evaluating storage requirements for renewableenergy-driven grids. iScience, 26(1), https://doi.org/10.1016/j.isci.2022.105900
Ministry of Economy, Trade, and Industry (METI). (2021). Electric Utility Business
Handbook.
METI. (2022). Feed-in Tariff Statistics. https://www.fit-portal.go.jp/
PublicInfoSummary
National Renewable Energy Laboratory (NREL). (2017). System Advisor Model(SAM) Version 2017. 9. 5. https://sam.nrel.gov/
THE 2035 JAPAN REPORT|52

NREL. (2022). Annual Technology Baseline 2022 (ATB 2022). https://atb.nrel.gov/
electricity/2022/technologies
Organization for Cross-regional Coordination of Transmission Operators, Japan.
(2021). Firm capacity coefficients for solar, wind, and hydro power generators
in each area for Fiscal Year 2022 supply plan. https://www.occto.or.jp/kyoukei/
teishutsu/files/202111_choseikeisu_l5_ichiran.pdf
Phadke, A., Paliwal, U., Abhyankar, N., McNair, T., Paulos, B., Wooley, D., & O’Connell,
R. (2020). 2035 the Report - Plummeting Solar, Wind, and Battery Costs
Can Accelerate Our Clean Electricity Future. https://www.2035report.com/
electricity/
Relf, G., York, D., & Kushler, M. (2018). Keeping the Lights On: Energy Efficiency andElectric System Reliability | ACEEE. https://www.aceee.org/research-report/u1809
Rennert, K., Errickson, F., Prest, B.C. et al. Comprehensive evidence implies a higher
social cost of CO2. Nature 610, 687–692 (2022). https://doi.org/10.1038/s41586022-05224-9
Rode, A., Carleton, T., Delgado, M., Greenstone, M., Houser, T., Hsiang, S., Hultgren,
A., Jina, A., Kopp, R. E., McCusker, K. E., Nath, I., Rising, J., & Yuan, J. (2021).
Estimating a social cost of carbon for global energy consumption. Nature 2021
598:7880, 598(7880), 308–314. https://doi.org/10.1038/s41586-021-03883-8
Segreto, M., Principe, L., Desormeaux, A., Torre, M., Tomassetti, L., Tratzi, P., Paolini,V., & Petracchini, F. (2020). Trends in Social Acceptance of Renewable Energy
Across Europe—A Literature Review. International Journal of Environmental
Research and Public Health 2020, Vol. 17, Page 9161, 17(24), 9161. https://doi.
org/10.3390/IJERPH17249161
U.S. Agency for International Development (USAID) and NREL. (2017). Renewable
Energy Zone (REZ) Transmission Planning Process — Greening the Grid.
https://greeningthegrid.org/news/new-resource-renewable-energy-zone-reztransmission-planning-process
U.S. Government. (2022). Inflation Reduction Act of 2022 (testimony).
Wang, X., & Lo, K. (2021). Just transition: A conceptual review. Energy Research &Social Science, 82, 102291. https://doi.org/10.1016/j.erss.2021.102291

THE 2035 JAPAN REPORT|53

APPENDIX A | MODELING APPROACH
The state-of-the-art methodology for studies that assess the impacts of highrenewable energy (RE) share on electric power systems is to use capacity
expansion and production cost models. For this study, we use a combination of acapacity expansion model and a production cost model using PLEXOS, an industrystandard model that is used by grid operators and utilities worldwide (Abhyankar
et al.; 2022, IRENA, 2017). First, we use a capacity expansion model to identify
the least-cost (“optimal”) generation, storage, and interregional transmission
investments from 2020 to 2035 that meet regional electric power demandrequirements, grid dependability (reserve) requirements, technology resource
constraints, and policy constraints. Second, we use the production cost model toassess the operational feasibility of the least-cost portfolio by simulating hourly
dispatch of generators, storage, and transmission ties in the year 2035. For eachyear, we simulate hourly economic dispatch using the production cost model toensure that the grid can run dependably for all 8,760 hours in the year, including
the hours when the system is most constrained.
PLEXOS uses deterministic, mixed-integer optimization to minimize the cost of
meeting load given physical (e.g., generator capacities, ramp rates, transmission
limits) and economic (e.g., fuel prices, start-up costs, import/export limits) gridparameters. Moreover, PLEXOS simulates unit commitment and actual energy
dispatch for each hour (at 1-minute intervals) of a given period. As a transparent
model, PLEXOS makes available to the user the entire mathematical problem
formulation. The model minimizes total generation cost (fixed plus variable
costs) for the entire system, including existing and new generation capacity andtransmission networks (Abhyankar et al., 2022). We assess the optimal resourcemix under a range of scenarios examining deployment rates, coal plant retirements,
demand growth, electricity market design, demand response, and supply chain
challenges.
We represent the Japanese electricity grid using 9 interconnected nodes connectedby 23 GW of interregional transmission corridors and 1 isolated node (Okinawa) in
2020 (Figure 2).

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54

Figure A1 depicts our overall method and the various data components.

Future load
projections

Capacity underconstruction +announced targets
System operations,reserves &market rules

Thermal operational
constraints

Hourly load profiles

PLEXOSRE (solar and wind)profiles + hydroconstraints

Capital, O&M andtransmission costs

Capacity expansion and economic dispatch
model with hourly resolution at plant level
Fuel prices andavailability constraints

Hourly dispatch &transmission flows

Total electricity
supply cost

FIGURE A1. Overall modeling approachTHE 2035 JAPAN REPORT|55

APPENDIX B | MODELING INPUTS
Projections of installed costs and fixed operations and maintenance (O&M) costs foronshore wind, offshore wind, solar PV, and battery storage in Japan are based onJapan’s cost data; the 2022 United States National Renewable Energy Laboratory(NREL) Annual Technology Base (ATB) forecasts; and industry consultations(Committee on Procurement Prices, 2022; GoJ 2021f; NREL 2022). Table B1 shows
the assumptions on capital costs of wind, solar, and battery storage. Roundtrip
efficiency of battery storage and pumped hydro storage are assumed to be 90%
and 80%, respectively.

TABLE B1. Solar, wind, and battery storage capital cost assumptions
LOW

BASE

HIGH

LOW

BASE

HIGH

SOLAR PVBATTERY STORAGE (4-HR)

YEAR

COST/KW: THOUSAND JPY/KW (USD/KW)

COST/KW: THOUSAND JPY/KW (USD/KW)

2020

198
(1,800)198(1,800)198(1,800)

48
(433)

48
(433)

48
(433)

2030

81
(736)

102
(927)

166
(1,510)

16
(141)

25
(225)

30
(273)

2035

76
(691)

96
(873)

150
(1,360)

14
(127)

23
(229)

27
(246)

Onshore wind
Cost/kW: thousand JPY/kW (USD/kW)

Offshore wind (fixed-bottom)
Cost/kW: thousand JPY/kW (USD/kW)

2020

280
(2,550)280(2,550)280(2,550)515(4,681)

515(4,681)

515(4,681)2030

204(1,850)222(2,020)226(2,050)321(2,915)348(3,614)406(3,691)2035

188(1,710)207(1,880)212(1,930)253(2,301)286(2,602)361(3,278)

Offshore wind (floating)

Cost/kW: thousand JPY/kW (USD/kW)

2020

572
(5,200)600(5,455)650(5,908)2030

399(3,629)445(4,042)539(4,901)2035

374(3,406)421(3,832)521(4,738)

1 USD = 110 JPY (Average exchange rate from 09/2013 to 08/2022)

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Other clean energy costs and operational parameters have been taken fromJapanese Government estimates (GoJ 2021f, Committee on the Procurement Prices
of Renewable Electricity, 2022)and industry consultations. Table B2 summarizes theassumptions.

TABLE B2. Other Clean Technology Costs and Operational Parameters

HEAT RATE(GJ/MWh)FORCEDOUTAGERATE (%)

MAINTENANCEOUTAGE RATE(%)

RAMPING(% OF INSTALLEDCAPACITY PERMINUTE)AUXILIARYCONSUMPTION(%)

CAPITAL
COST*

FIXED
O&M
COST*

Biomass

398(3,620)

27
(245)

8.3

5

10

N/A

6

Geothermal

790(7,180)

33
(300)

N/A

5

10

N/A

11

Hydropower

620(5,640)

16
(145)

N/A

5

5

100%

1

Hydrogen;Ammonia161(1,460)

6.4
(58)

6.6

5

5

2%

2.3

* C apital and fixed O&M costs are in 1,000 JPY/kW (2020 JPY/2020 USD) / 1 USD = 110 JPY(Average exchange rate from 09/2013 to 08/2022)

CAPITAL
COST*

FIXED
O&M COST*HEAT RATE(GJ/MWh)FORCED OUTAGERATE (%)

MAINTENANCEOUTAGE RATE (%)

COLD -STARTTIME (HOURS)MINIMUM UP-TIME(HOURS)MINIMUM DOWN-TIME(HOURS)TECHNICAL MINIMUMLEVEL (%)

RAMPING (% OF
INSTALLED CAPACITYPER MINUTE)

AUXILIARYCONSUMPTION (%)

TABLE B3. Conventional Technology Costs and Operational Parameters

Coal

244
(2,220)

11.9
(108)

8.3

5

10

24

12

6

40

1

5.5

Gas CCGT

161(1,460)

6.4
(58)

6.6

5

5

12

6

3

30

2

2.3

Gas GT

101
(922)

2.3
(21)

9.7

5

5

1

1

1

20

10

2.3

Nuclear516(4,690)

17.3
(157)

10.3

5

20

96

96

96

90

N/A

4.0

* C apital and fixed O&M costs are in thousand JPY/kW (2020 thousand JPY [2020 USD]); 1 USD = 110
JPY (Average exchange rate from 09/2013 to 08/2022)

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Conventional technology (coal, nuclear, natural gas) capital and fixed O&M costs
have been taken from previous Japan and U.S. estimates (GoJ, 2021f; NREL, 2022).
Operational parameters such as ramp rates, technical minimum levels, auxiliary
consumption, minimum up and down times, etc., have been taken from the data
used in previous Japan and U.S. studies, regulatory norms, and expert/industry
consultations. They are summarized in Table B3. Capacity and commission year ofexisting power plants are taken from multiple sources including Japan Electricity
Power Exchange database (JEPX, 2022), Feed-in Tariff Statistics (METI, 2022),
generation companies’ websites, and Electric Utility Businesses Handbook (METI,2021).

TABLE B4. Summary of Key Assumptions and Variables
PARAMETERASSUMPTIONSOURCE

Geographic Scope

10 regions (nodes)

Solar, Wind, andBattery Storage
Technology Costs

NREL ATB 2022 projections withadjustments

Other RE andConventional
Technology Costs

Geothermal, biomass, hydro,
GoJ 2021f, Expert
hydrogen, natural gas, coal,consultations
and nuclear costs are based onJapanese Government estimations.

Operations &Maintenance (O&M)

Fixed and variable O&M costs of all
non-retired plants are included

Weighted Average Costof Capital (WACC)

2.5 % (real)

OCCTO 2021, Expert
consultations

Electricity Demand

Annual and monthly amounts,
along with daily and hourly load
profiles, all by region.

GoJ 2021e, 10 Regional
T&D companies’ website,
Expert consultations

Extreme Events Analysis

Use weather data and energy
load for four weather-years (2017–2020).

NREL ATB 2022,
GoJ 2021f, Advisory
Committee 2021, Expert
consultations

Weather affects both demand andwind and solar supply.
Nuclear Retirements

Nuclear plants that are not granted Expert consultations
20-year extension as of 2022
assumed to retire in 40 years in the
nuclear retirement sensitivity.

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58

PARAMETER

ASSUMPTIONSOURCE

Technical LifespanWind: 30 years

GoJ 2021f, JEPX 2022,
NREL 2022, Expert
consultations

Solar PV: 30 years
Hydropower: 100 years
Battery: 15 years
Nuclear: 60 years
Gas: 50 years
Coal: 50 years
Economic LifespanStandard amortization is 30 years,
batteries are 15 years.

Residential Solar,
Geothermal, Hydrogen,and Biomass

Their 2030 targets are met at least, GoJ 2021e
while more deployment is allowed
when economical.

Carbon Price

The CO2 price is 289 JPY/t-CO2 for
all cases from 2020 to 2035. In the
carbon price analysis (appendix
D), the CO2 price linearly ramps up
from 2026, reaching the final CO2
price by 2035.

Planning Reserve Margin

10% in each region

Operating Reserves

Regulation reserves, spinningLew et al. (2013),
reserves (contingency reserves),
ReEDs (2021), Expert
and flexibility reserves (ramping
consultation
reserves) are included as afunction of load and solar and windshare. The reserve requirementlevels are calculated based on Lew
et al. (2013)

Firm capacity of
renewable energy

In estimating planning reserve
OCCTO (2021), Expert
margin, we used firm capacity
consultation
estimates of renewable energy(i.e.,solar, wind, and hydro) in eachregion from Japanese authority(OCCTO 2021).

Expert consultations

Expert Consultation

THE 2035 JAPAN REPORT|59

APPENDIX C | SOLAR AND WIND PROFILES
We estimated the solar and wind (offshore and onshore) resource potential andprofiles from the ground up. This section explains the methodology used, which
can be divided into two parts. The first part involves estimating the total resource
potential of solar and wind available in each region. This forms an upper limit on theamount of new capacity that can be built in PLEXOS for each region. To estimate
resource potential, we use the capacity factor data along with multiple exclusion
datasets, including land cover, elevation, slope of terrain, natural parks, fisheryzones and defense areas. The second part involves estimating the representativehourly solar and wind profiles for each region. Profiles are estimated at site level
using meteorological data from re-analysis datasets, and then an aggregation
algorithm is used to create a provincial/cluster level representative profile. The
potential and profiles are estimated at the regional level for onshore wind and solar
and at a cluster level for floating and fix bottom offshore wind.

RESOURCE POTENTIAL
Solar
To estimate the solar resource potential in each region, we start with thecomplete area of that region and remove the areas which are not suitable forsolar development. We use four exclusion criteria for estimating the solar resource
potential: land cover, slope, elevation and natural parks.
The land cover dataset comes from the European Space Agency’s Copernicus
programme. We use the Moderate Dynamic Land Cover Dataset, which has a spatial
resolution of 100m and divides land cover into 23 classes. We exclude dense forest(i.e., forests with canopy > 70%), wetlands, moss and lichens, urban and builtup
areas, areas with snow and ice, permanent water bodies, and open seas.
In addition to land cover, we use elevation and slope to remove areas not suitable
for solar development. The elevation data also comes from the European Space
Agency’s Copernicus programme, the Copernicus GLO-30 Digital Elevation Model.
The dataset has a spatial resolution of 30 m and provides elevation of the surfaceof earth, including man made buildings and infrastructure. We estimate slope fromthe elevation dataset using the planar method. The method estimates the steepest
descent based on the maximum change in elevations between the cell and the 8neighboring cells (Burrough, et al., 1995).

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We exclude areas which have an elevation of more than 4,000 m and slope above 5
degrees. We then remove areas which fall under the territory of natural parks. Afterexclusions based upon land cover, elevation, slope, and natural parks, the areas thatare left in a region are considered suitable for solar development.
To estimate the quality of solar resource potential in each region, we use theresource data from Global Solar Atlas. Solar Atlas provides annual average solar
capacity factors at 30 arcsec (~1 km) spatial resolution. This dataset and its windcounterpart, Global Wind Atlas, were developed by the World Bank. The Solar
Atlas models solar generation using 10 years of meteorological data and creates anaveraged solar capacity factor data. We combine the capacity factor data with the
RE suitability data derived, after exclusions, to create a solar resource map of Japan(Figure C1). This map shows the capacity factor at all developable sites in Japan.

FIGURE C1.
Developable Sites
for Solar PV

CAPACITY FACTOR
Band 1: band=1<= 0.12
0.12—0.14
0.14—0.16
0.16—0.18> 0.18CF

CAPACITY(GW)> 0.1800.16­­-0.18

159

0.14-0.16796

0.12-0.14

470

ONSHORE WIND
The methodology for estimating onshore wind resource potential is very similar
to the method used for solar. We take the complete area of a region and remove
the areas not suitable for wind development to estimate the resource potential.
We use the same land cover, elevation, slope, and natural parks datasets as used
for solar. However, we use different limits on elevation and slope as solar and wind
have different slope and elevation considerations. We exclude areas with elevation
greater than 3000m and slope greater than 11.31 degrees for onshore wind.

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For land cover, we use the same criteria as solar and remove dense forests (i.e.,
forest with canopy > 70%), wetlands, moss and lichens, urban and builtup areas,
areas with snow and ice, permanent water bodies, and open seas. The Global Wind
Atlas provides the annual average wind capacity factors at 1 km spatial resolution. It
was created using 10 years of hourly meteorological data, and then averaged to getan annual average capacity factor for a site. We combine the Wind Atlas capacity
factor data with our developable sites data to get a wind resource map of Japan(Figure C2). This map shows the onshore wind capacity factors at all developablesites in Japan.

FIGURE C2.
Developable Sites
for Onshore WindCAPACITY FACTOR
Band 1<= 0.20
0.20—0.25
0.25—0.35
0.35—0.45> 0.45CF

CAPACITY
(GW)

> 0.4

15

0.35­­-0.4

14

0.3-0.35

20

0.25-0.3

27

0.2-0.25

30

OFFSHORE WIND
To estimate the offshore wind resource potential, we use the map of the exclusive
economic zone (EEZ) of Japan, ocean depth data, GIS datasets of the locationsof defense areas and fishery zones. Surprisingly, we know very little about the
topography of Earth’s oceans, even less than we know about the topography ofMars.
The best global bathymetry dataset available is from the General Bathymetric Chartof the Oceans (GEBCO). GEBCO dataset has global coverage and has a spatial
resolution of 500 m. We start with a map of the EEZ of Japan and remove sites
with ocean depth greater than 1,000 m. We assume that sites with depth greater

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than 1,000 m are currently not economically developable for offshore wind. The
sites with ocean depth less than 60m are suitable for fixed bottom technology, andthe sites with ocean depth between 60 and 1,000m are assumed to be suitable forfloating wind technology.
These limits on technology suitability are derived from NREL which uses thesame limits for the United States. We then removed areas which fall in the
territory of defense areas and fishery zones. As we did for solar and wind, we
combined this dataset with the capacity factor data from the Global Wind Atlas
to create an offshore wind resource map for Japan, showing the capacity factor
at all developable offshore locations (Figure C3). We then developed cluster the
fixed bottom and floating wind sites using the Multivariate Spatially Constrained
Clustering algorithm. The clustering was done so as to keep the spatiallycontiguous sites which have similar capacity factors in the same clusters. We create
30 clusters for floating wind and 10 clustering for fixed bottom offshore wind. Mostof the Japanese offshore wind potential is at a ocean depth more than 60m so
more clusters were created for floating offshore wind. The maps of the clusters areshown in Figure C4.

FIGURE C3.
Developable Sites
for Offshore WindCFCAPACITY
(GW)

> 0.6

39

0.55­­-0.6

267

0.40—0.45

0.5-0.55

533

0.45—0.50

0.45-0.5385

0.50—0.55

0.4-0.45

137> 0.550.35-0.4

34

0.3-0.35

15

CAPACITY FACTOR
Band 1<= 0.40

THE 2035 JAPAN REPORT|63

FLOATING

FIXEDFIGURE C4. Clusters for floating wind and fixed bottom offshore wind

MODELING RESOURCE PROFILES
Here we describe the methodology used to create representative solar and windhourly generation profiles for each region. We use the resource map dataset
created in the previous section, i.e., the dataset with capacity factors at developablesites. In addition, we use meteorological data from reanalysis datasets. We extractwind speed, pressure, temperature, solar irradiance, etc., from reanalysis datasets
and pass them through a software tool that models wind farms and solar parks
to provide hourly solar and wind generation outputs. Several sites in a region are
aggregated to create a representative generation profile for each region. The
methodologies for solar, onshore wind, and offshore wind are discussed in detailbelow.

Solar
In the previous section, we created a gridded dataset of developable sites withannual average capacity factors. That gave us a technical resource potential, but
not all sites which technically can be developed would actually be developed. The
quality of resources drives the economics, and only the best resource sites actually
get developed. To get a representative resource profile for each region, we need tofind a sample of the best sites and aggregate their individual profiles.
For estimating the solar profile, we filter out the top 25 percentile of the sites withthe highest capacity factor. To ensure that we do not select very low-capacity

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factor sites, we only keep sites with capacity factors greater than 15%. From thispool of top sites in a region, we randomly select 2,000 sites. We then estimate
hourly generation at each of these 2,000 sites and average them to create a
representative solar profile for the region. Hourly meteorological data from ERA5 isused to estimate hourly generation at each of the 2,000 sites.
ERA5 is an hourly reanalysis dataset from European Centre for MediumRange Weather Forecasts (ECMWF, 2020ECMWF, 2020ECMWF, 2020ECMWF,
2020ECMWF, 2020ECMWF, 2020) and has a spatial resolution of 30 km x 30
km. ERA5 provides historical hourly data on wind speed, temperature, pressure,solar radiation, etc., at 137 pressure levels from surface up to a height of 80 km.
To estimate solar generation, we extract the surface solar radiation downwards(ssrd), temperature at 2 m and u and v component of wind speed at 10 m height. To
model solar generation at a site, we also need Direct Normal Irradiance (DNI) andDirect Horizontal Irradiance (DHI). The ssrd variable from ERA5 gives the Global
Horizontal Irradiance (GHI), and we use GHI to estimate DHI and DNI.
NREL’s DISC model provides empirical relationships between GHI and DHI, GHI
and DNI, based on Maxwell, 1987. NREL’s System Advisor Model (NREL, 2017) isused to model solar generation. The SAM software development kit takes GHI, DHI,
DNI, temperature, and u and v wind components as inputs, and then outputs solar
generation. We use a single axis system to simulate solar generation using SAM.
The hourly generation at 2,000 sites is averaged to create a representative profile
for the region.

Onshore Wind
The methodology for estimating onshore wind profiles is very similar to solar, anda similar method is used to select sample sites in each region. We filter the top 25
percentile of sites from the annual average capacity factor dataset developed while
estimating resource potential. To avoid very low-capacity factor sites, we remove
sites with capacity factors of less than 20%.
From this we randomly select 2,000 sites. We simulate hourly generation for a year
for each of these 2,000 sites using the SAM model. We model a wind farm with 32
turbines, arranged in an 8 x 4 rectangular shape. SAM takes wind speed at the hubheight of the turbine, wind direction, surface pressure, and temperature as inputs,
and then gives hourly farm generation as output.
Meteorological data is taken from MERRA2. It provides wind speed at 10 m and
50 m, which are then scaled to the hub height of the wind turbine used. Surfacepressure and temperature are also available from MERRA2. For simulating wind

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generation, we used meteorological data from U.S. National Aeronautics and Space
Administration (NASA)’s Modern-Era Retrospective analysis for Research andApplications (MERRA2) dataset which has a spatial resolution of 0.5 deg x 0.625
deg. MERRA2 data is shown to have better accuracy for wind speeds than ERA5,
for this reason, we select MERRA2 despite it having much lower spatial resolution
compared to ERA5. The spatial resolution of MERRA2 is 0.5 deg x 0.625 deg, quite
high for modeling wind speed, as winds can vary significantly by local topography.
To account for some of the effects of local topography, we use the average windspeed data from Wind Atlas, which has a much higher spatial resolution of 1 km x 1
k m. We create a scaling factor using the average wind speed data from Wind Atlas
and average wind speed data from MERRA2. We scale the hourly wind speeds in
MERRA2 by this factor to get a more accurate wind speed profile.
Corrected wind speeds are then passed through to SAM to get hourly generation.
The hourly generation from 2,000 sites is averaged to get a representative profile
for the region.

Offshore Wind
Because there are no predefined regional boundaries for offshore wind, we haveto create artificial clusters to get representative profiles. We clustered the offshore
wind sites into multiple clusters as discussed in earlier section. For each fixed andfloating wind cluster we estimate one representative profile in each of the clusters.
For the purpose of estimating profiles, we only keep sites with capacity factor
greater than 40% in each of the clusters. We assume that only sites with capacity
factor more than 40% are currently economically developable. We simulate hourly
generations at each site using SAM. Wind speed and direction at hub height,
temperature and pressure data is required for simulating wind generation in SAM.
The hourly generation from the all the sites in the cluster is aggregated to create a
representative profile for each cluster.

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APPENDIX D | CARBON PRICE SENSITIVITY
Carbon pricing is a policy instrument widely used to reduce CO2 emissions
around the world. Japan’s current carbon price (as of 2022) is 289 JPY/t-CO2. The
Japanese government is currently planning to introduce a new emissions trading
scheme, which includes electric power sector starting in 2026 (GoJ, 2022a).
In this sensitivity analysis, we relax constraints on the clean energy target (i.e., 90%of electricity generation comes from clean energy by 2035) and the coal phaseout(i.e., coal generation is phased out by 2035) in the capacity expansion modeling.
We raised carbon price on CO2 emissions at various rates to examine the effectof carbon price levels on generation mix and CO2 emissions. Under the original
scenarios, carbon price is constant at 289 JPY/t-CO2. In this sensitivity analysis, we
set the target carbon prices in 2035 at 2,000 JPY/t-CO2, 3,000 JPY/t-CO2, 4,000
JPY/t-CO2, 5,000 JPY/t-CO2, and 6,000 JPY/t-CO2. We assume that the carbon
prices linearly increase from 289 JPY in 2025 to the target carbon price in 2035, asshown in Figure D1.

C AR BO N PR ICE (J PY2020/t- CO2)6,000

FIGURE D1. Assumed Carbon Price
Paths in the Sensitivity Analysis
from 2020 to 2035

4,000

2,000

Carbon Price in 2035
JPY 6000
JPY 5000
JPY 4000
JPY 3000
JPY 2000

0

2020

2025

2030

2035

Figure D2 summarizes the generation mix and emissions in 2035 with different
carbon prices. Without 90% clean energy target or coal phaseout constraints, coal
is competitive with natural gas plants and operates in 2035, unless carbon price israised to 6,000 JPY/t-CO2. With the level of carbon price, clean power accounts for
91% of generation, and coal power accounts for less than 0.4% of generation.

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67

Due to high emission coefficient of coal power plants, emission reduction depends
on the capacity factor of coal plants. Even if clean energy sources (i.e., renewables
and nuclear) account for 80% of electricity supply with 2,000 JPY/t-CO2 carbon
price, its emissions reduction is only 69% from the 2020 level. Increasing carbon
price level reduces coal plant operation, resulting in significant decline in CO2emissions, up to 7% of the 2020 level. This implies that emissions reduction requires
substantially raising carbon prices from the current level; renewable energy
deployment is not sufficient in terms of climate change mitigation. This level ofcarbon price would also enable a 90% clean energy grid, if institutional and societal
barriers for clean energy deployment are lifted.

GENERATIONMIX IN 2035

CO 2 EMISSIONS IN 2035 AS A
PERCENTAGE OF THE 2020 LEVEL

100%

40

Hydro

OffshoreWind Fixed75%

OffshoreWind Float
Residential PV
Utility/
Commercial PV

50%

Geothermal
Biomass
Hydrogen25%

Nuclear
LNG

PE RCE NT O F 2020 E M ISS IO N S

Wind

30

20

10

Oil
Coal

0%

2000

3000

4000

5000

6000

C AR BO N PR ICE (J PY2020/t- CO2)

0

2000

3000

4000

5000

6000

C AR BO N PR ICE (J PY2020/t- CO2)

FIGURE D2. Generation Mix and CO2 emission in 2035 under different
carbon price targets

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APPENDIX E | REGIONAL RESULTS OF BASESCENARIO
Figures E1, E2, and E3summarize the regional distribution of the least-cost
capacity mix in 2035 under the 90% Clean Energy Scenario with base fuel costs
and the generation mix. The capacity mix and generation mix are significantly
different, depending on the existing generation, pumped hydropower storage, andtransmission capacity, plus various types of additional renewable energy potential.
While wind resources are geographically concentrated in particular areas, solar PV
is widely available across the regions. Abundant, high quality onshore and offshore
wind resources located in Tohoku and Hokkaido are utilized with 6 GW of the
new transmission lines to send the wind energy to Tokyo. As a result, 100% of theelectricity is supplied by clean energy in these northern regions, representing 45%
of wind capacity. In Shikoku and Okinawa, about 40% of the electricity is supplied
by offshore wind as well. Solar PV provides 38% and 37% of electricity supply inTokyo and Chugoku regions. The share of solar and wind (VREs) is more than 50%
in six regions (Hokkaido, Tohoku, Tokyo, Chubu, Shikoku, and Okinawa). Battery
storage, pumped-hydro storage, natural gas plants, hydro plants, and interregionaltransmission lines collectively provide operational flexibility to integrate such a high
VRE share.

<1.0 GW

FIGURE E1.
Regional Generation andInterregional Transmission
Capacity of the 90% Clean
Energy Scenario

1.0—3.0 GW
3.0—5.0 GW> 5.0 GW

HOKKAIDO(49 GW)TOHOKUKYUSHU(63 GW)

20

40

80

120

HOKURIKU(10 GW)

CHUGOKU(26 GW)

TOKYO(105 GW)

CHUBA

KYUSHU(40 GW)(69 GW)

KANSAISHIKOKU (50 GW)(19 GW)

OKINAWA(4 GW)

THE 2035 JAPAN REPORT|69

H O K K AI DO
TO H O K U
TO K YOCH U B U
HOKURIKUK AN SAICH U G O K U
S H I KO K U
KYUSHUO K I NAWA

0

30

60

90

120

C APACIT Y (GW )
Coal

LNG

NuclearOffshore Wind Float

HydrogenBiomass

Offshore Wind FixedWind

Geothermal
Hydro

Utility/Commercial PV
Pumped Hydro

Residential PV

Battery

FIGURE E2. 2035 Generation Capacity by Region under the 90% Clean Energy Scenario

H O K K AI DO
TO H O K U
TO K YOCH U B U
HOKURIKUK AN SAICH U G O K U
S H I KO K U
KYUSHUO K I NAWA

0%

Coal

LNG

Residential PV

25%

NuclearHydrogen

Offshore Wind Float

Biomass50%

75%

Geothermal

Utility/Commercial PV

Offshore Wind Fixed

Wind

100%

Hydro

FIGURE E3. 2035 Generation Mix by Region under the 90% Clean Energy Scenario

THE 2035 JAPAN REPORT|70

APPENDIX F | SENSITIVITY ANALYSIS
100

Hydro

% O F TOTAL G E N E R ATIO N T Wh

WindOffshore Wind
Fixed

75

Offshore Wind
Float
Residential PV
Utility/
Commercial PV

50

Geothermal
Biomass
Hydrogen
Nuclear

25

LNG

0

BASE

HIGH FUEL
COST

HIGH
RE AND
STORAGECOSTLOWRE AND
STORAGECOSTHIGHELECTRIFICATIONLOWNUCLEARSCE NAR IO

FIGURE F1. 2035 Generation Mix of All Scenarios

600

Transmission
Battery Storage
Hydro

C apacit y (GW )Wind
Offshore Wind
Fixed

400

Offshore Wind
Float
Residential PV
Utility/
Commercial PV
Geothermal

200

Biomass
Hydrogen
Nuclear
LNG
Coal

0

BASE

HIGH FUEL
COST

HIGH
RE AND
STORAGECOSTLOWRE AND
STORAGECOSTHIGHELECTRIFICATIONLOWNUCLEARSCE NAR IO

FIGURE F2. 2035 Capacity Mix of All Scenarios

THE 2035 JAPAN REPORT|71