I N T R O D U CT I O N

ELECTRIC POWER GRIDI N T E R CO N N E C T I O N S I N
N O RT H E A S T A S I AA QUA NTITATIVE A NA LY S IS OFECONOMIC AND ENVIRO NMENTA L BENEFITSASIA PACIFIC ENERGY RESEARCH CENTRENOVEMBER 2015
This report is published at http://aperc.ieej.or.jp/

Published by:
Asia Pacific Energy Research Centre
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Website: http://aperc.ieej.or.jp/© 2015 Asia Pacific Energy Research Centre
November 2015

FOREWORD

FOREWORD
Following the Asia-Pacific Economic Cooperation’s mission of promoting economic
prosperity in a sustainable way, this research document performs a quantitative
analysis of opportunities and challenges of electric power grid interconnections inNortheast Asia (NEA) with a focus on renewable energy utilisation.
The new energy situations created by a number of recent natural and economic
events, including serious air pollution issues in China, nuclear disasters in Japan andpower shortage and rolling blackout in Korea, require a review of the previous
priorities of the energy policies. This background made power grid interconnection
more attractive in NEA as a means to build an economically efficient power systemand to effectively utilize renewable energy in the region. Quantitative examinations
and discussions of these potential benefits are the backbone of this researchdocument.
Besides the analysis, this document also summarises recent power market situation
as well as grid interconnection proposals over the last two decades, in order todeliver comprehensive information to policy makers.
I would like to thank the experts who have provided their knowledge to thisdocument, the feedback gained through workshops, academic and professional
events and peer-review processes has greatly enriched the outcomes presented. As
an independent research project, however, the contents herein reflect only APERC’sview and might change in the meantime depending on drastic external events orchanges in the energy and policy agendas of particular economies.
This report is the work of the Asia Pacific Energy Research Centre. It is anindependent study, does not necessarily reflect the view of or policies of the APEC
Energy Working Group or individual member economies. Hopefully, this researchdocument will become a cornerstone of the establishment of information exchange
and international collaborative activities for leveraging APEC’s economic andcooperative strengths.

Takato OJIMI
President
Asia Pacific Energy Research Centre
November 2015

PAGE iA CK N O W L E D GE M E N T S

ACKNOWLEDGEMENTS
The present report, Electric Power Grid Interconnections in Northeast Asia: A
Quantitative Analysis of Economic and Environmental Benefits, was made possible
through the initiative and efforts of the following people.
PROJECT LEADER AND AUTHOR

Takashi Otsuki
CONTRIBUTORS

Ralph D. Samuelson
Aishah B. Mohd Isa
Dmitry A. Sokolov
Brantley T. Liddle
EDITORS

Enago (Crimson Interactive K.K.), Takashi Otsuki and Naomi S. Wynn

The project’s structure was largely based on a kick-off expert workshop held on
March 2014 in Tokyo Japan. The Asia Pacific Energy Research Centre (APERC) would
like to thank the following experts for their participation in the workshop and theirinsightful contributions.
Prof Gao Shixian
Director, Energy Research Institute,
National Development and Reform Commission, China
Mr Syaiful Ibrahim
Secretary in Charge, The Heads of ASEAN Power Utilities/Authorities, Indonesia
Mr Kensuke Kanekiyo,
Advisor, The Institute of Energy Economics, JapanMr Ichiro Kutani
Senior Economist, The Institute of Energy Economics, JapanDr Ji Chul Ryu
Energy Economist.
Formerly Executive Director, Korea Energy Economics Institute, Korea
Prof Boris Saneev
Deputy Director, Melentiev Energy Systems Institute,
Siberian Branch of The Russian Academy of Science, Russia
PAGE iiA CK N O W L E D GE M E N T S

Dr Nawal Kamel
Visiting Professor, Chulalongkorn University, Thailand

APERC appreciates the helpful comments, observations and suggestions from thefollowing reviewers to improve the quality of this research project.
Mr Ichiro Kutani
Senior Economist, The Institute of Energy Economics, JapanMr Yuhji Matsuo
Senior Economist, The Institute of Energy Economics, Japan
Prof Ryoichi Komiyama
Associate Professor, Resilience Engineering Research Center,
School of Engineering, The University of Tokyo, Japan
Prof Nikolai I. Voropai
Professor, Corresponding Member of Russian Academy of Science,
Director of Melentiev Energy Systems Institute,
Siberian Branch of The Russian Academy of Science, Russia
Dr Sergei Podkovalnikov
Chief of laboratory, Melentiev Energy Systems Institute,
Siberian Branch of The Russian Academy of Science, Russia
Ms Ksenia Kushkina
Project leader, Asian energy supergrid project, Center for Energy Systems,
Skolkovo Institute of Science and Technology, Russia

Large parts of Section 4-5 and Appendix A.1-A.2 are revisions of the author’s
journal article: ‘Electric power grid interconnections in Northeast Asia: A quantitative
analysis of opportunities and challenges’, Takashi Otsuki, Aishah Binti Mohd Isa andRalph D. Samuelson, Energy Policy Volume 89 pp.311-329 (2016). This article will be
published as an open access article (license type: CC BY 4.0). APERC would like tosincerely thank Energy Policy (Elsevier journal) and four anonymous journal referees
for their helpful suggestions for improvements.

PAGE iii

CONTENTS

CONTENTSFORE WORD .................................................................................. IACKNOWLEDGEMEN TS ................................................................ II
CONTENTS ................................................................................. IV
LIST OF FIGURES ......................................................................... V
LIST OF TABLES ......................................................................... VII
LIST OF ABBREVIATION S .......................................................... VIIIE XECUTIVE SUMMA RY ................................................................. 1
1. INTRODUCTION ....................................................................... 3
2. OVERVIE W OF POWER GR IDS IN APEC NORTHEAST ASIA ......... 6
2.1. China ........................................................................................................................................... 6
2.2. Japan ........................................................................................................................................ 122.3. Korea........................................................................................................................................ 18
2.4. Russia....................................................................................................................................... 222.5. Comparison of the major indicators across NEA region...................................... 27
3. MA JOR CONCEPTS OF POWER GRID INTERCONNECTIONS ....... 30
3.1. NEA-wide grid interconnection concepts.................................................................. 30
3.2. Bilateral interconnection concepts ............................................................................... 42
4. MODELLING AND A NALYS IS OF GRID INTERCONN ECTIONS ..... 52
4.1. Methodology: a multi-region power system model.............................................. 52
4.2. Scenario settings ................................................................................................................. 54
4.3. Input data assumptions .................................................................................................... 56
4.4. Simulation results ............................................................................................................... 65
5. CONCLUSIONS AND POLICY IMPLICATI ONS ............................. 77
APPENDIX .................................................................................. 80
A.1 Mathematical formulation ............................................................................................... 80
A.2 Model validation ................................................................................................................. 87
A.3 Discussion on capaity reserve constraint ................................................................... 89
REFERENCES ............................................................................... 90

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L IS T O F F I G U R E S

LIST OF FIGURES
Figure 1 Power grid interconnection concept (examples) ................................................... 4
Figure 2 Power grids, China............................................................................................................. 6
Figure 3 500kV and 300kV transmission line networks, China........................................... 7
Figure 4 Electricity supply system, China.................................................................................... 8
Figure 5 Historical power-generation capacity, peak load and generation, China .... 9
Figure 6 Peak load by power grid, China, 2012 ....................................................................... 9
Figure 7 Historical average electricity prices, China and major provinces/cities innortheast area ................................................................................................................. 10
Figure 8 Electricity service areas, Japan ................................................................................... 12
Figure 9 Transmission line network (above 154kV), Japan ............................................... 13
Figure 10 Electricity supply system, Japan, after April 2005 .............................................. 13
Figure 11 Historical power-generation capacity, peak load and generation, Japan15
Figure 12 Installed power-generation capacity and peak load level by power
utilities, Japan, FY2012............................................................................................... 15
Figure 13 Historical electricity prices, Japan .......................................................................... 16
Figure 14 Electricity market, Korea ............................................................................................ 18
Figure 15 Electric power grids, Korea ....................................................................................... 19
Figure 16 Historical power-generation capacity, peak load and generation, Korea20
Figure 17 Historical electricity prices, Korea .......................................................................... 21
Figure 18 Future capacity projections, 7th Basic Plan for Long-term Electricity
Supply and Demand ................................................................................................... 22
Figure 19 Power grids, Russia ...................................................................................................... 23
Figure 20 Transmission network areas, Russia ...................................................................... 23
Figure 21 Historical power-generation capacity, peak load and generation, Russia ..
..................................................................................................................................... 24
Figure 22 Installed capacity and peak load by power grid, Russia, 2012.................... 25
Figure 23 Historical average electricity prices, Russia’s Far East region (Far Eastern
Energy Company area and Sakhalinenergo area) ........................................... 26
Figure 24 Russia’s Far East power sector development, up to 2030............................. 27
Figure 25 Comparison of major indicators, Northeast Asia region, 2012................... 28
Figure 26 Northeast Asian Electrical System Ties concept ............................................... 33
Figure 27 Reliability assessment of NEAREST concept (example) ................................. 34
Figure 28 Pan-Asian Energy Infrastructure concept............................................................ 35
Figure 29 Asia Super Grid concept ............................................................................................ 36
Figure 30 Asia Pacific Power Grid concept ............................................................................. 37
Figure 31 Gobitec and Asia Super Grid concept .................................................................. 39
Figure 32 Northeast Asia Super Grid concept ....................................................................... 40
Figure 33 Northeast Asia Super Grid concepts ..................................................................... 41
Figure 34 China–Korea interconnection concept ................................................................. 46
Figure 35 Prospects for energy bridge development, Russia .......................................... 47
Figure 36 Possible future China–Russia interconnection options, as of 2012 ........... 47
Figure 37 Japan–Korea interconnections route .................................................................... 49
Figure 38 Japan–Russia interconnection concepts .............................................................. 50
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L IS T O F F I G U R E S

Figure 39 Korea–Russia interconnection plans in Korea’s Energy Master Plan ........ 51
Figure 40 Multi-region power system model, schematic diagram ................................ 53
Figure 41 Regional division and assumed transmission distances ................................ 54
Figure 42 Estimated daily load curve (ratio to peak load), city nodes ......................... 56
Figure 43 Initial capacity assumptions ..................................................................................... 57
Figure 44 Flow chart for the calculation of wind power output in the Gobi Desert
area (GD) ......................................................................................................................... 61
Figure 45 Assumed wind output profile, the Gobi Desert area (GD) ............................ 61
Figure 46 Assumed Photovoltaics output profile, the Gobi desert area (GD) ........... 62
Figure 47 Geographical distributions of hydro energy resources, Russia .................. 64
Figure 48 Power generation in Northeast Asia and changes from Base scenario ... 65
Figure 49 Power-generation mix and net imports by node............................................. 67
Figure 50 Direct CO2 emissions, Northeast Asia ................................................................... 68
Figure 51 Annual electricity flows, each scenario, Northeast Asia................................. 70
Figure 52 Yearly total system costs and changes from Base scenario, Northeast Asia..................................................................................................................................... 71
Figure 53 Additional investments from Base scenario, Northeast Asia ....................... 72
Figure 54 Power-generation profile and marginal generation costs, winter season,
Japan Hokkaido node (JP-H) ................................................................................... 73
Figure 55 Average marginal generation costs ...................................................................... 73
Figure 56 Power-generation profile and marginal generation costs, winter peakseason, China North node (CH-N) ........................................................................ 74
Figure 57 Power-generation profile and marginal generation costs, summer peakseason, Japan West node (JP-W)........................................................................... 75
Figure 58 Economic benefits of the Gobi+RuHyd scenario in each case .................... 76

Figure A1 Comparison of modelled generated electricity and historical data inNortheast Asia .............................................................................................................. 87
Figure A2 Modelled net imports and historical data .......................................................... 88
Figure A3 Comparison of the average retail electricity prices with the modelled
average marginal costs of power generation ................................................... 88
Figure A4 Comparison of the results with Constraint (A.25) and with (A.29) ............ 89

PAGE viL IS T O F T A BL E S

LIST OF TABLES
Table 1 Major existing cross-border interconnections, Northeast Asia ......................... 3
Table 2 Power development targets, 12th Five-Year Plan, China .................................. 11
Table 3 Major region-wide grid interconnection proposals, Northeast Asia ............ 31
Table 4 Independent system vs. interconnection system, economic evaluation ..... 34
Table 5 Total construction investment and operation & maintenance costs ............. 39
Table 6 Total supply unit cost estimation and comparison with weighted average
electricity charge of importing countries ................................................................ 39
Table 7 Major concepts and progress, interconnection routes ...................................... 43
Table 8 Scenarios, definitions ...................................................................................................... 55
Table 9 Assumptions for generation and storage facilities .............................................. 59
Table 10 Cost assumptions for North China (CN-N), China Northeast (SN-NE) and
the Gobi Desert area (GD) .......................................................................................... 59
Table 11 Cost assumptions for Japan nodes (JP-H, JP-E and JP-W) ............................. 59
Table 12 Cost assumptions for Korea (KR) ............................................................................. 60
Table 13 Cost assumptions for Russia nodes (RU-FE, RU-SI and RU-SK) ................... 60
Table 14 Fuel prices assumption ................................................................................................ 60
Table 15 Initial cost assumptions for each interconnection route [USD/kW] ........... 63
Table 16 Assumptions for additional hydro power plants................................................ 64
Table 17 Case settings of sensitivity analysis (150 cases total) ....................................... 76
Table 18 Summary of the simulation results of each scenario ....................................... 77

Table A1 Endogenous variables in the multi region power system model ................. 80
Table A2 Assumed length of each season ............................................................................... 82

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L IS T O F A B BR E V I A T IO N S

LIST OF ABBREVIATIONSAC

Alternating Current

AAGR

Average Annual Growth Rate

APEC

Asia-Pacific Economic Cooperation

APERC

Asia Pacific Energy Research Centre

ASEAN

Association of Southeast Asian Nations

ASG

Asian super gridbbl

BarrelDC

Direct Current

DH

District Heating

DPRK

Democratic People’s Republic of Korea

EBRD

European Bank for Reconstruction and Development

EDMC

The Energy Data and Modelling Center, The Institute of Energy
Economics, JapanEENSExpected Energy Not Supplied

EHV

Extra High Voltage

EIA

Energy Information Administration, US Department of Energy

ESCJ

Electric Power System Council of JapanESI SB RAS

Melentiev Energy Systems Institute, Siberian Branch of The Russian
Academy of Science, Russia

FEEC

Far Eastern Energy Company

FEPC

Federation of Electric Power Companies of Japan

FGC UES

Federal Grid Company of Unified Energy System (Russia)

F/S

Feasibility StudyGAMS

General Algebraic Modeling System

Gt-CO2

Gigaton-CO2

GW

Gigawatt

GWh

Gigawatt-hour

HAPUA

The Heads of ASEAN Power Utilities / Authorities

HV

High Voltage

HVAC

High-Voltage Alternating Current

HVDC

High-Voltage Direct Current

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L IS T O F A B BR E V I A T IO N S

IEAInternational Energy Agency

IPS

Integrated Power System

JAIFJapan Atomic Industrial ForumJEPICJapan Electric Power Information Center

JREF

Japan Renewable Energy Foundation

KEEI

Korea Energy Economics Institute

KEPCO

Korea Electric Power Corporation

KERI

Korea Electrotechnology Research Institute

KESIS

Korea Energy Statistics Information System

kW

Kilowatt

kWh

Kilowatt-hour

LHV

Lower Heating Value

LOLE

Loss of Load Expectation

MEPI

Ministry of Electric Power Industry (China)

METI

Ministry of Economy, Trade and Industry (Japan)

MKE

Ministry of Knowledge Economy (Korea)

MMBtu

Million British Thermal Unit

MOTIE

Ministry of Trade, Industry and Energy (Korea)

MOU

Memorandum of Understanding

Mt-CO2

Megaton-CO2

MUFJ

Bank of Tokyo-Mitsubishi UFJ

MW

Megawatt

MWh

Megawatt-hour

NEA

Northeast Asia

NEAREST

Northeast Asian Electrical System Ties

NREL

National Renewable Energy Laboratory (US)O&M

Operation and Maintenance

OCCTO

Organization for Cross-regional Coordination of Transmission Operators(Japan)PPSPower Producer and SupplierPV

Photovoltaics

R&D

Research and Development

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L IS T O F A B BR E V I A T IO N S

RITEResearch Institute of Innovative Technology for the Earth (Japan)

SGCC

State Grid Corporation of China

Skoltech

Skolkovo Institute of Science and Technology (Russia)

SO UPS

System Operator of the United Power System of Russia

TSUC

Total Supply Unit CostTW

Terawatt

TWh

Terawatt-hour

UHVUltra High Voltage

USD

US Dollar

WAEC

Weighted Average Electricity Charge

WGC

Wholesale Generation Company (Russia)

PAGE xE X E CU T IV E S U M M A R Y

EXECUTIVE SUMMARY
Several recent regional events, including the nuclear disaster in Japan, the power
shortage and rolling blackouts in Korea, and increased concern regarding air
pollution in China, have made power grid interconnections potentially more attractive.
Several organisations have proposed power grid interconnection concepts, i.e., Asia
Super Grid and Gobitec, with a focus on developing the abundant renewable
resources in the Gobi Desert and Eastern Russia and on building a more resilient andeconomically efficient power system. These concepts are still at the discussion stage;
therefore, in order to deliver comprehensive information for policy making and toadvance the negotiations, this report focuses on the following points:


Overview of power grids in Northeast Asia (NEA) economies (Section 2);Major concepts of power grid interconnection in NEA (Section 3); andModelling and analysis of economic and environmental benefits of gridinterconnections (Section 4).

Quantitative examinations and discussions of potential benefits are the backbone ofthis research document. Through our research, following findings are obtained fromour simulation analysis.

A coordinating organisation is necessary to draw up a
blueprint for NEA-wide interconnections.
Various interconnection concepts have been proposed by private companies andresearch institutes; however, there is limited coordination by economy’s authorities orinternational/regional organisations in NEA (such as the Heads of ASEAN Power
Utilities / Authorities (HAPUA) in the ASEAN region). In order to draw up a detailed
blueprint for NEA-wide interconnections as well as to research, discuss andimplement the concepts in an effective manner, a coordinating entity should beestablished.

Modest economic benefits are likely to be a major challenge for
implementation.
Our simulation analysis shows that interconnections contribute significantly to fuelcost savings by shifting to cheaper fossil fuel or to renewables. However, the large
initial investments, needed for developing the renewables and transmission lines,
partly offset the fuel cost savings, resulting in modest total cost reductions. The
limited total cost savings are likely to pose an implementation challenge for NEA gridinterconnections. This result also suggests that grid interconnections become more
economically attractive in higher fuel price (=larger fuel cost savings) or lower initialcost (=less investments) situations, and vice versa. The relevant planning
organisations should carefully consider the future fuel price and initial cost trends
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E X E CU T IV E S U M M A R Y

when considering how to interconnect power grids in an economical manner. This
study also shows that the economic benefits expand with higher carbon prices.
Regional carbon market and emission reduction regulations are important for
implementing power grid interconnections and expanding renewable energy forexport.

Grid interconnection in NEA should be in tandem withrenewable energy developments.
Access to wind and solar resources in the Gobi Desert and additional hydro resourcesin Eastern Russia promotes an environmentally-friendly generation mix with. On theother hand, cost-optimal grid interconnections without renewable energy
development would promote low-cost coal-fired generation in China and Russia,
resulting in an emissions increase in NEA and potentially worsening air pollution in
China. Thus, interconnection projects should be undertaken with renewable energy
expansion in order to reap both economic and environmental benefits.

Unexploited hydropower in Eastern Russia would be the driverof opportunities for Russia and neighbouring regions.
Our study implies that additional hydropower developments stimulate the scale ofinterconnection between Eastern Russia and neighbouring regions. Historically,
electric utilities and transmission companies in Russia, in cooperation withorganizations in neighbouring economies, have been exploring the possibilities ofcross-border connection. As the costs for hydro generation largely depend on sitespecific characteristics, the relevant planning organisations should assess theunexploited hydropower potential, which can be economically developed for export.

The planning organisations should carefully discuss the
economic viability before implementation.
The findings above imply the modest economic benefits and barriers due touncertainties in future fuel prices, initial costs and carbon prices. Given the oil andAsian LNG deflation after mid-2014 as well as no regional emissions regulations in
NEA, grid interconnection would face economic challenges. Our modelling approachalso includes several simplifications that should be addressed in future work (Section
5). The planning organisations need to carefully discuss the economic viability in amore detailed manner considering site specific conditions, before stepping forward
and implementing the project.

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I N T R O D U CT I O N

1. INTRODUCTION
Over the past two decades, electric power grid interconnections have gained
attention in Northeast Asia (NEA), an area that we define as four Asia-Pacific
Economic Cooperation (APEC) economies--China, Japan, the Republic of Korea(Korea), and Russia-- and two non-APEC economies--Mongolia and the Democratic
People’s Republic of Korea (DPRK). Various interconnection schemes have been
proposed for NEA (Streets, 2003; Yun & Zhang, 2005; Hata, 2005; Hippel, et al., 2011).
Yet, while technically feasible (KEPCO, 2014a), these cooperative proposals have beenhampered by factors such as existing national policies of energy self-sufficiency andthe sometimes-volatile diplomatic and political situation in the region. Thus, the only
existing cross-border power cooperation projects are small in scale, linking Russia to
Mongolia, Russia to China, and China to the DPRK (Table 1).
Table 1 Major existing cross-border interconnections, Northeast Asia
Transmission Line Component

Voltage [kV]

Gusinoozerskaya GRES (Russia) – Darkhan (Mongolia)

220

Kharanorskay GRES (Russia) – Choibalsan (Mongolia)

110

Chadan (Russia) – Khandagaity – Ulanngom (Mongolia)

110

Blagoveshensk (Russia) – Heihe (China)

220/110Sivaki (Russia) – Sirius /Aigun (China)

110

Blagoveshensk (Russia) – Sirius /Aigun (China)

2*220

Amurskay (Russia) – Heihe (China)

500

Source: Podkovalnikov (2002)

However, several recent regional events have made regional power interconnections
potentially more attractive. The Great Earthquake and nuclear disaster in Japan(March, 2011) pushed the economy to focus more on resilient power system andrenewable energy. The power shortages and rolling blackouts in Korea (September,2011) highlighted the vulnerabilities of its power system. Air pollution issues in China,
largely attributed to coal-dependent power sector, has become an increasingly
important concern. Meeting these economies’ electricity demand with a cleaner andmore reliable power system has become a major challenge; thus, several
organisations have proposed multilateral power grid interconnection concepts, i.e.,
Gobitec and Asian Super Grid—interconnecting power grids and effectively utilising
the abundant renewable energy resources in the Gobi Desert and Eastern Russia—asillustrated in Figure 1 (Energy Charter, et al., 2014; KEPCO, 2014a). The wind and PV
potential in Mongolia has been estimated at 1100GW and 1500GW, respectively(Elliott, et al., 2001; Energy Charter, et al., 2014), and economically feasiblehydropower potential in Eastern Russia is estimated at 690TWh/year (estimated by
European Bank for Reconstruction and Development, see IEA (2003)).

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I N T R O D U CT I O N

Figure 1 Power grid interconnection concept (examples)a) Energy Charter, et al. (2014)b) KEPCO (2014a)

Source: Energy Charter, et al. (2014) and KEPCO (2014a)
Note: Each figure is reproduced as Figure 31a) and Figure 32, respectively.

There have been some previous economic analyses on connecting power grids invarious parts of the world: Southern Africa is the focus of Bowen, et al. (1999), Europeof Lilliestam & Ellenbeck (2011) and Schaber, et al. (2012) and Southeast Asia of
Chang & Li (2013) and Matsuo, et al. (2015). Among those studies, Schaber, et al.
(2012) conducted a detailed analysis on the impacts of grid interconnections onregional renewable energy utilization. They employed a Europe-wide power systemmodel with a detailed temporal resolution (hourly time slice for six representative
weeks), which appropriately reproduce the actual power generation, electricity prices
and cross-border power transportation.
Economics of power grid interconnection in the NEA region has been investigated.
Cost-benefits analyses of grid interconnection scenarios in NEA were performed byHippel (2001), Podkovalnikov (2002), Lee, et al. (2005), Chung & Kim (2007), Energy
Charter, et al. (2014) and Chudinova, et al. (2015). Analyses on power system
reliability were conducted by Choi, et al. (2006) and Yoon (2007). Yet, to ourknowledge, few studies have focused on the whole of NEA and analysed the impactsof grid interconnections with a focus on renewables both in the Gobi Desert andEastern Russia considering power systems particulars (e.g. load curves, generation
dispatch). Except for Energy Charter, et al. (2014) and Chudinova, et al. (2015), thestudies listed above covered only a part of NEA (three to four out of the six
economies) and did not consider renewable energy in the Gobi Desert. Chudinova, etal. (2015) does not take into account renewables in the Gobi Desert, either. As forEnergy Charter, et al, (2014), they proposed to install 50GW of wind and 50GW ofsolar photovoltaics (PV) in the Gobi Desert, and estimated the supply costs to other
NEA economies. However, their cost assessment did not consider regional powersystem particulars, such as the load curve of the importing economies and theseasonal and diurnal output variation of the solar and wind power from the Gobi
Desert.
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Thus, we developed a multi-region power system model, which covers the whole of
NEA, in order to quantitatively evaluate the potential benefits of, and barriers to,power grid interconnection and expansion of renewable energy for export. The
model seeks to minimize overall system cost, considering seasonal and daily
characteristics of electric load of each region and output patterns of renewables in
the Gobi Desert. We analyse following points with the model:the potential economic benefits (total costs, marginal generating costs and soon) for the entire NEA region and for each economy;the potential CO2 reductions by sharing renewable resources in the NEA; andthe optimal generation mix and cross-border power flow considering
representative hourly/daily load curves for each season.

We believe that our analysis contributes to understanding of the costs and benefits ofthe grid interconnection and large-scale renewable energy utilization in NEA from asystems viewpoint. However, it is important to note that this work mainly focuses on
economic analyses. Other important factors, such as technical challenges, geopoliticalobstacles or law harmonisation, are beyond our research scope. These topics should
thus be explored in the future research.
This report consists of five sections. First, the objective and scope of this study arebriefly explained in this section. Section 2 details the characteristics of power grids inthe major NEA economies and introduces the stakeholders in each region. Next,
Section 3 summarises the major proposals and recent activities/progresses of gridinterconnections. Section 4, which provides the modelling and analysis of power gridinterconnection, is the main part of this report. This section discusses our model
structure, assumptions and simulation results. Finally, the major findings and policy
implications derived from this study are listed in Section 5.

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O V E R V IE W O F P O W E R G R ID S IN NEA

2. O V E R V I E W O F P O W E R G R I D S
IN APEC NORTHE AST ASIA
Electricity market varies from economy to economy in APEC NEA. This section
summarises the recent situation of each economy’s electricity sector, includingtransmission line networks, generation mix, electricity tariffs, future development
plans and so on. Section 2.5 briefly compares the major indicators across NEA.

2.1.

CHINA

2.1.1. ELECTRICITY MARKET AND POWER GRID
China has seven power grids (Figure 2). The State Grid Corporation of China (SGCC)
owns the Northeast, North China, Central China, East China, Northwest and the Tibet
power grids, whereas the China Southern Power Grid Company covers the South
China power grid. The grids’ frequency is 50Hz. Figure 3 describes China’stransmission line network (500kV and 300kV). China has been accelerating highvoltage (HV) grid interconnections among its domestic power grids to resolve
regional demand–supply imbalances and transmit electricity from resource-abundantregions (central/west area) to ‘energy hungry’ regions (east coastal area).
Figure 2 Power grids, China

Source: Xu & Alleyne (2012).
Note: The original figure included Chinese Taipei; we have edited the map to exclude this area.
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O V E R V IE W O F P O W E R G R ID S IN NEA

Figure 3 500kV and 300kV transmission line networks, China

Source: Cartier (2013).
Note: China has recently been constructing ultra-high-voltage transmission lines. According to JEPIC(2014a), 1000kV and 800kV transmission line extent amounted to approximately 6105km in 2012.

China’s electricity industry has been centrally run by the state since the creation of
the People’s Republic of China in 1949. Power-generation assets were assigned toand operated by various state-owned enterprises, which are placed under theadministrative supervision of the Ministry of Electric Power Industry (MEPI) (Gee, et al.,2007). In 1986, China began reforming its power sector in three phases. In the firstphase (1986–97), in order to solve power shortage issues and meet surging demand,the central government allowed provincial and local governments as well as privatecompanies to build and operate power-generation facilities. In the second phase,
MEPI’s assets were transferred to the newly established State Electric Power
Corporation in 1997; moreover, MEPI was abolished and its administrative functions
were transferred to the Electric Power Department of the State Economic and Trade
Commission (SETC) in 1998. Then, in the final phase in 2002, the State Council of the
China unbundled power generation and transmission/distribution. The State ElectricPower Corporation was divided into two state grid corporations (SGCC and China
Southern Power Grid Company), five power-generation companies, and four power
service companies (Gee, et al., 2007).
In China, generated electricity is supplied through SGCC/China Southern Power Grid
Company and through Provincial-level, City-level and Township-level grid companies(Figure 4). China has interconnections with several neighbouring foreigncountries/economies, including DPRK, Kyrgyzstan, Mongolia, Southeast Asian
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O V E R V IE W O F P O W E R G R ID S IN NEA

counties and Russia. In the NEA region, China imported 2.6TWh of electricity from
Russia in 2012, and in 2013, this expanded to 3.5TWh, accounting for approximately
half of total imports.
Figure 4 Electricity supply system, China
Generation

Power-generating companies (Public, Private)

State Grid Corporation of China,
China Southern Power Grid Company, and so on
Provincial-level State Grid Company , and so on
City-level State Grid Company , and so on
Township-level State Grid Company, and so on

Direct dealing(Test operation stage)

Transmission
andDistribution

Consumer

Source: JEPIC (2014b).

2 . 1 . 2 . E L E C T R I C I T Y D E M A N D A N D S U P P LY
In 2012, China’s power-generation capacity reached 1 150GW (Figure 5), which wasseven times and three times larger than that in 1990 and 2000, respectively. Over thelast decade, thermal power-generation facilities recorded the largest growth in termsof capacity, increasing by approximately 560GW from 2000 to 2012, whereas nuclear
power-generation facilities increased by approximately 8GW and hydro powergeneration facilities by approximately 170GW. Coal-fired power-generation holds thelargest share (66%) in total capacity in China, with an expected average annual
growth rate (AAGR) of 7.8% from 2010 to 2015 (Section 2.1.3). Concerning the powergeneration mix, thermal power plants account for 78% and hydro power plants for
17% of the mix. In 2012, nuclear power plants accounted for approximately 1% and
2% shares in capacity and generation mix, respectively.
Among all the renewable power-generation facilities, wind power capacity showedremarkable growth at an AAGR of more than 40% from 2005 to 2012. According to
JEPIC (2014a), its capacity increased to more than 60GW by 2012; however, its sharein total generation was not more than 2.1% mainly because of lower capacity factor
than dispatchable generation as well as of grid access limitation issues.
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O V E R V IE W O F P O W E R G R ID S IN NEA

The scale of China’s power grid varies from grid to grid (Figure 6). As explained in
Section 4, the definition of NEA in this study includes both the Northeast and North
China grids. The Northeast grid has the smallest peak load (52GW) among the power
grids denoted in the figure: it is approximately one-third of the East China grid’s peakload (175GW). The North China grid, which covers the Beijing area, has the second
largest peak load (163GW).
Figure 5 Historical power-generation capacity, peak load and generation, Chinaa) Installed capacity and peak loadb) Generation

GW

TWh

1 400

6 000
Nuclear

NuclearThermal
5 000

Thermal

1 200

1 000

Peak load

Hydro

Hydro
4 000

800

Wind

Wind
3 000
Other
2 000
Peak
load
1 000

600
400
200
0

Other

0

2000

2005

2010

2011

2012

2000

2005

2010

2011

2012

Sources: JEPIC (2004; 2007; 2012; 2013).
Note: Historical peak load data for 2000 was not available in the source document.

Figure 6 Peak load by power grid, China, 2012
GW
200

150

100

50

0

Northeast

North
China

East
China

CentralChina

Northwest

China
Southern

Source: JEPIC (2014a).

According to RITE (2014), the average efficiency of China’s thermal power plants
between 2009 and 2011 was 36.8% (at the generation end, on a lower-heating-value(LHV) basis), which is lower than the global average by 2.0 points. The average
efficiency of coal-fired plants for these three years was 35.6%. RITE (2014) reported
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O V E R V IE W O F P O W E R G R ID S IN NEA

that the efficiency of coal-fired plants in China showed a gradual improving trend,
especially after 2005, and became higher than the global average efficiency of suchplants in 2012 (35.2%).
Figure 7 shows historical average electricity prices in China and in major
provinces/cities in the northeast area. The price in each Chinese province is regulatedby the government. The government applies lower prices to the economicallyunderdeveloped provinces (for example, Inner Mongolia). These regulated prices do
not reflect market mechanisms, and the low prices have continuously caused powercompanies to experience deficits.
Electricity prices show increasing trends over the last decade. They have risen by 4%
from 2000 to 2011, and the average price in 2011 was 0.583 CNY/kWh. Among theprovinces/cities in Figure 7, the 2011 prices ranged from 0.393 CNY/kWh (westernpart of Inner Mongolia Autonomous Region) to 0.711 CNY/kWh (Beijing). Beijing’s
price is approximately 1.8 times higher than that in the western part of Inner
Mongolia.
Figure 7 Historical average electricity prices, China and major provinces/cities
in northeast area
CNY/kWh
0.8

Heilongjiang
Jilin
Liaoning

0.6

Beijing
Tianjin
Shanxi

0.4

Shandong
Innner Mongolia (East part)

0.2

Innner Mongolia (West part)

Average (China total)

0
2000

2005

2010

2011

2012

Sources: JEPIC (2004; 2007; 2012; 2014a) and SERC (2010).
Note: The ‘China total’ price in 2000 is the average of the State Electric Power Corporation area. The
Average prices in 2012 are estimated by the average price in State Grid Corporation area, the average
price in China Southern Power Grid Company area and the generated electricity in each area in 2012.
Due to data availability constraints, only 2010–2012 prices for Inner Mongolia (west part) and 2010–2011
for Inner Mongolia (east part) are included.

2.1.3. ECONOMY’S ENERGY PLAN
The 12th Five-Year Plan for National Economic and Social Development (the 12thFive-Year Plan) is China’s latest five-year plan (The State Council of the PR China,2011). As of Sep-2015, the 13th plan is under discussion. The 12th plan was endorsedby the National People’s Congress on 14 March 2011. This five-year plan clarifies thenational strategic intent, the government’s focus and the people’s common program
PAGE 10

O V E R V IE W O F P O W E R G R ID S IN NEAof action during the five-year period starting in 2011 (APERC, 2013a). With regards toenergy development, the plan’s focus includes nuclear power, renewable and power
grid development as follows:

Nuclear power: China will accelerate nuclear power development in the coastal
provinces, continuously develop nuclear power plants in inland areas and start
construction of 40GW nuclear power plants1.

Hydro power: China will construct large-scale hydro power plants in theprioritised areas, including Chin-sha River and Dadu River, and start hydro plant
construction with a total capacity of 120GW.

Wind power: China will construct large-scale wind farms (six onshore and two
offshore). Newly added capacity will be more than 70GW.

Solar power: China will deploy 5GW solar power plants, prioritising Tibet
Autonomous Region, Inner Mongolia Autonomous Region, Gansu Province,
Ningxia Hui Autonomous Region, Qinghai Province, Xinjiang Uyghur
Autonomous Region, Yunnan Province and so on.

Power grid: China will construct more than 200,000km of transmission lines(>330kV).

The plan also mentions a five-year power development plan as summarised in Table
2. Total capacity will increase by approximately 520GW from 2010 to 2015 (at a 9%
AAGR). The plan indicates China’s intention to promote clean power sources,
including wind (26.4% AAGR), solar (89.5%) and nuclear (29.9%). However, coal-fired
plants are expected to grow most quickly in terms of absolute capacity:
approximately an additional 300GW is expected during the period.
Table 2 Power development targets, 12th Five-Year Plan, China
2010

2015

AAGR

Total Capacity [hundred million kW]

9.7

14.9

9.0%

Coal-fired [hundred million kW]

6.6

9.6

7.8%

Hydro [million kW]

2.2

2.9

2.7%

Nuclear [million kW]

10.82

40

29.9%

Gas-fired [million kW]

26.42

56

16.2%

Wind [million kW]

31

100

26.4%

Solar [million kW]

0.86

2.1

89.5%

Source: The State Council of the PR China (2011).

1 Note that the 12th Five-Year Plan was approved merely three days after the Fukushima Daiichi nuclear

power plant accident, and some delays or readjustments to the plan might occur in the future.

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O V E R V IE W O F P O W E R G R ID S IN NEA

2.2.

JA PA N2.2.1. ELECTRICITY MARKET AND POWER GRID
Japan has ten electricity service areas, each traditionally dominated by a verticallyintegrated private utility. Each utility is responsible for ensuring a stable power supply
in each service area and has developed and managed a self-sufficient power supply
system. As depicted in Figure 8 and Figure 9, the frequency in east Japan (Hokkaido,
Tohoku and Tokyo area) is 50Hz, whereas it is 60Hz in west Japan. Three frequency
converter (FC) stations (Sakuma, Shin-shinano and Higashi-shimizu) with a total
capacity of 1200MW have been installed to connect east and west Japan.
Japan’s electricity market has been partially liberalised to ensure fair competition andtransparency. The Electricity Business Act amended in 1995 allows independent
power producers (IPPs) to participate in the electricity wholesale market;
subsequently, the 1999 amendment (enforced from March 2000) liberalised themarket for extra-high voltage (EHV) consumers (more than 2MW) and allowed power
producers and suppliers (PPSs)2 to sell electricity to the partially liberalised market.
Figure 8 Electricity service areas, Japan

Source: FEPC (2012).

2 IPSs are allowed to participate in the electricity wholesale market. In contrast, PPSs are allowed to sellelectricity to consumers in the liberalized market (≥50kW) using general electric utilities’ transmission
lines.

PAGE 12O V E R V IE W O F P O W E R G R ID S IN NEA

Figure 9 Transmission line network (above 154kV), Japan

500kV transmission line
154kV~275kV transmission line
HVDC transmission line
Frequency converter facility (F.C.)

Shin-shinano F.C.

Sakuma F.C.

Higashi-shimizu F.C.

Source: Imaizumi (2012).

Figure 10 Electricity supply system, Japan, after April 2005

Source: FEPC (2014a).

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O V E R V IE W O F P O W E R G R ID S IN NEA

The amendment in 2003 expanded the scope of liberalisation: the market for
consumers requiring more than 50kW was liberalised in April 2004 (FEPC, 2014a). As
of April 2015, the liberalised market accounts for approximately 60% of Japan’s total
electricity demand3. Japan Electric Power Exchange (JEPX) was established in 2003
and commenced power exchange from April 2005. Furthermore, to support fair andtransparent transmission and distribution operations, the Electric Power System
Council of Japan (ESCJ) was established in 2004 and started operations in April 2005.
ESCJ’s duties include rule-making, dispute resolution, coordination of loaddispatching operations and so on. (ESCJ, 2013). Figure 10 shows the electricity supply
systems from April 2005.
After the Great East Japan Earthquake in March 2011 and the subsequent Fukushima
Daiichi nuclear power plant accident, the Japanese power industry faces mountingpressure to fully deregulate the electricity market to realise competitive and moretransparent electricity supply. The Electricity Business Act was amended in 2013, 2014
and 2015 to reform electricity system. This reform focuses mainly on three stages asfollows (METI, 2015a): 1) Establishment of the Organization for Cross-regional
Coordination of Transmission Operators (OCCTO) in April 20154; 2) full power retailliberalisation from April 2016; and 3) legal unbundling of the transmission anddistribution sector from 2020 and transition to full liberalisation of retail electricity
price after the unbundling. In order to avoid a monopoly situation after retailliberalisation in 2016, retail tariffs of designated utilities will be regulated as atransitional measure, and then gradually deregulated after legal unbundling.
Amendments to the Electricity Business Act for the three stages were enacted in
November 2013, June 2014 and June 2015.

2 . 2 . 2 . E L E C T R I C I T Y D E M A N D A N D S U P P LY
Especially after the two oil crises, Japan has been trying to balance the ‘3E’ (economy,energy and environment) factors and diversify the fuel mix of its power generation asshown in Figure 11. In FY2012, on a capacity basis, coal-fired plants accounted for
16%, gas-fired plants accounted for 27%, oil-fired plants accounted for 19% andhydro (including pumped hydro storage) plants account for 19% of power-generation
capacity. Although there are uncertainties regarding future nuclear power utilisation,
its share of total capacity has held steady at approximately 10%. The powergeneration mix before FY2010, shown in Figure 11b), illustrates Japan’s ‘3E’ energy
strategy. After the nuclear accident, nuclear power generation significantly decreased
from 288TWh (29% of total generation) in FY2010 to 102TWh (11% of total
generation) in FY2011 and further to 16TWh (2% of total generation) in FY2012. Fossil
fuel-fired power plants, mainly gas-fired and oil-fired plants, replaced the losses ofnuclear generation capacity; that is, in FY2011, gas-fired and coal-fired power
generation increased by 83TWh and 62TWh, respectively, from the previous year.

3 The scope of liberalization differs in Okinawa (FEPC, 2014a).
4 The role of ESCJ was transferred to OCCTO, and ESCJ was dissolved on 31st March 2015.

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O V E R V IE W O F P O W E R G R ID S IN NEA

New and renewable (except hydro) energy sources gradually increased; however, its
share in the total power-generation mix was 1.6% in 2012. Peak load usually occurredin the summer season in Japan, and it showed a slight growth for 2000–2010 at a
0.5% AAGR. After the nuclear accident, strong energy saving efforts in the economy
contributed to a peak load reduction of 22GW in FY2012 from FY2010.
Figure 11 Historical power-generation capacity, peak load and generation,Japana) Installed capacity and peak loadb) Generation

GW

TWh

300

1 000

Peak load

Nuclear250

Coal-fired

800

Gas-fired200
600

Oil-fired

150

Hydro

400

100

Pumped Hydro

200

50

New &
renewables

00FY2000 FY2005 FY2010 FY2011 FY2012

FY2000 FY2005 FY2010 FY2011 FY2012

Sources: METI (2014b) and EDMC (2015).
Note: Figure 11 shows capacity and generation data of 10 general electric power utilities.

Figure 12 Installed power-generation capacity and peak load level by power
utilities, Japan, FY2012
GW
80

Others
Hydro

60

Thermal40

NuclearPeak load

2050Hz area

Okinawa

KyusyuShikoku

ChugokuKansai

Hokuriku

Chubu

Tokyo

TohokuHokkaido

060Hz area

Source: EDMC (2014).

The largest power grid is the Tokyo electric power company area (Figure 12). Installedcapacity owned by Tokyo Electric Power Company accounts for 30% of total ten
electric power utilities (as of FY2012). The 50Hz area comprises three electric power
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O V E R V IE W O F P O W E R G R ID S IN NEA

companies. Hokkaido is connected to the Tohoku area (Honshu island) via the
Kitahon high voltage direct current (HVDC) link (250kV, 600MW), and another
300MW link is planned to be installed by 2019. The 60Hz area comprises sevenelectric service areas. Kyusyu island and Shikoku island are connected to Honshu
island via Kanmon Interconnecting Line (500kV, 5570MW) and Honshi
Interconnecting Line (500kV, 2400MW), respectively. In addition to three existing
frequency conversion stations (total 1200MW) between 50Hz and 60Hz areas, Tokyo
Electric Power Company and Chubu Electric Power Company plan to install a DC linkwith a capacity of 900MW in about FY2020 (OCCTO, 2015).
According to RITE (2014), the average efficiency of a Japanese thermal power plant
between 2009 and 2011 was 44.7% (at the generation end, on an LHV basis), higher
than the global average by 7.4 points. During the same period, the average efficiency
of coal-fired plants was 41.4%, and of gas-fired plants was 47.9%. Coal-fired power
plants in Japan maintained the highest efficiency in the world as of 2011.
Figure 13 describes historical electricity prices in Japan. As of 2015, Japan’s electricity
market is partially liberalised5, and the electricity price for non-liberalised markets(low voltage, less than 50kW) is regulated by the Ministry of Economy, Trade andIndustry (METI). Electric power utilities have to obtain permission from a METI
minister to increase the regulated electricity prices. Japan’s electricity prices havebeen one of the highest among developed economies.
Figure 13 Historical electricity prices, Japan
JPY/kWh
25

Lighting
Power service

20

Average151050FY2000FY2005FY2010FY2011FY2012

Source: METI (2014b).

Average prices were 22.3 JPY/kWh for lighting and 15.7 JPY/kWh for power services.
The prices show decreasing trends from 2000 to 2010, partly because of the efficient

5 Electricity market is planned to be fully liberalised from April 2015.

See Section 2.2.3.

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O V E R V IE W O F P O W E R G R ID S IN NEA

operation efforts (Kyuden, 2015). However, after the accident, many utilities applied
to increase regulated electricity prices due to the increasing fuel costs for thermal
power plants. According to NHK (2014), electric power utilities have increased
electricity prices by 13%–37% from March 2011 to July 2014.

2.2.3. ECONOMY’S ENERGY PLAN
In April 2014, the Cabinet decided to approve the revised Strategic Energy Plan. This
fourth plan gives a direction to Japan’s energy policies for the medium/long-term(approximately the next 20 years). The revised plan states that the period from now
to 2018-2020 is devoted to building more liberalised and competitive energy markets(METI, 2014c). In addition to electricity market reform mentioned in Section 2.2.1,
amendments to the Gas Business Act were enacted in June 2015 to fully liberalise thegas retail market by about 2017 and to legally unbundle gas pipes owned by three
town gas utilities, Tokyo Gas, Osaka Gas and Toho Gas, by April 2022 (METI, 2015a).
Under the Strategic Energy Plan, Japan will decrease nuclear dependence whilestrengthening energy efficiency and expanding renewable energy use. Accordingly, in
July 2015, the expert committee in METI concluded Japan’s Long-term Energy Supply
and Demand Outlook. The committee projected energy demand to 2030 using
macroeconomic indicators, and calculated total energy savings with a bottom-up
estimation about sectorial savings potential. The Outlook indicates an electricity mix,
primary energy demand and supply, and energy-related CO2 emissions (Koyama,2015), and aims to ensure the ‘S+3E’ policy where ‘Safety’ is the foremost condition. It
has three steps: 1) increase energy self-sufficiency (including nuclear as quasidomestic energy) to 24.3% from 6% in 2012; 2) lower electricity costs by 2% to 5%
from FY 2013 levels; and 3) reduce energy-related CO2 emissions by 21.9% from FY
2013 levels, to bring total GHG reductions to 26% (METI, 2015b).
The long-term outlook aims for a well-balanced generation mix where nuclear
accounts for 20-22% of total generated electricity, renewables for 22-24%, liquefied
natural gas for 27%, coal for 26% and oil for 3%. The share of nuclear is smaller than
before the earthquake (when it was about 30%), thus lowering nuclear dependence.
Within renewables, the two largest sources are hydro, accounting for 8.8-9.2%, andsolar (7.0%). However, the outlook assumes radical energy savings: energy intensity in
TFEC needs to be improves by 35% from 2012, equivalent to the drastic
improvements after the oil crises. Therefore, economy-wide efforts --especially incommercial and residential sectors-- would be necessary to realise the outlook. It isalso important to note that Projected demand assumes a 1.7% economic growth rate
based on the ‘revitalized economy’ policy (CAO, 2015), which assumes higher growththan recent actual growth.

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O V E R V IE W O F P O W E R G R ID S IN NEA

2.3.

KORE A

2.3.1. ELECTRICITY MARKET AND POWER GRID
Korea’s electricity industry is dominated by Korea Electric Power Corporation (KEPCO).
Its generation section was separated into six power-generation companies in April
2001. These are Korea Hydro & Nuclear Power, which owns the economy’s nuclearenergy power plants and hydro power plants, and five generation companies, which
took over ownership of thermal power plants and pumped hydro storage facilities.
KEPCO retained the economy-wide transmission and distribution grids as shown in
Figure 14. KEPCO purchases electricity from power markets (KPX: Korea Power
Exchange) and delivers it to general consumers. Large-scale consumers (consuming
more than 30,000kW) can directly purchase from KPX, and CES (Community Energy
Suppliers) can directly supply energy to their licensed area. Figure 15 shows Korea’s
electric power grid (KEPCO, 2013). Its frequency is 60Hz, and the backbonetransmission network has voltages of 345kV and 765kV.
To rectify an energy demand–supply structure that is overly dependent on oil, theconstruction of oil-fired power plants was strictly controlled, whereas thedevelopment of nuclear, coal and natural gas electricity-generation units waspromoted. During the period of the Seventh Basic Plan (2015-2029), 13 nuclearenergy power plants (total 18.2GW), 20 coal-fired power plants (18.1GW) and 14 gasfired power plants (10.1GW) were planned for construction (see also Section 2.3.3).
Figure 14 Electricity market, Korea

Source: KEPCO (2009).
Note: IPP = independent power producer; PPA = power purchase agreement; GENCO = generationcompany

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O V E R V IE W O F P O W E R G R ID S IN NEA

Figure 15 Electric power grids, Korea

Source: KEPCO (2013).
Note: DC = Direct Current.

2 . 3 . 2 . E L E C T R I C I T Y D E M A N D A N D S U P P LY
The power-generation capacity mix in Korea is dominated by thermal power
generation (61%), mostly those based on coal and combined-cycle technologies.
Nuclear power also has a significant share, accounting for approximately a quarter of
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O V E R V IE W O F P O W E R G R ID S IN NEA

the installed capacity in 2012. The rest of the total power capacity consists of Hydro(8%), district energy (3%) and renewables (3%). The trend from 2000 to 2012 showsthat thermal power generation has continued to grow from approximately 32GW in
2000 to 50GW in 2012. The capacity for district and renewable energy has also
gradually increased since 2005. Peak load shows constant growth at a 5% AAGR. Peakload occurred in summer season before 2008. However, after 2009, the peak season
has shifted to winter. Due to low-price electricity, most consumers in Korea use air
conditioners for heating, resulting in larger electricity demand in winter (FEPC, 2013)
Korea’s electricity generation increased from 118TWh in 1990 by over four times toreach 494TWh in 2012. The AAGR was highest during the first 10 years (1990–2000)
at 9.4%, while in the latter 12 years, the rate is lower at an annual average of 3.8%.
Most generation came from thermal power (66%), followed by nuclear power (30%).
Thermal power generation was fuelled by coal (40% of total generation), gas (23%)
and oil (3%) as described in Figure 16b).
Figure 16 Historical power-generation capacity, peak load and generation,
Koreaa) Installed capacity and peak loadb) Generation

GW

TWh

100

600
Nuclear

Nuclear500
Coal-fired

Coal-fired

Gas-fired400

Gas-firedOil-fired300

Oil-fired

Hydro
200
District
Energy100
Alternative
Energy0

HydroPeak load
80
60
40
20
0
2000

2005

2010

2011

2012

2000

District Energy

Alternative
Energy
2005

2010

2011

2012

Source: MOTIE (2013).

According to RITE (2014), average efficiency of Korea’s thermal power plants between
2009 and 2011 was 40.6% (at the generation end, on an LHV basis), higher than the
global average by 3.3 points. The average efficiency of coal-fired plants for the three
years was 36.1% and that for gas-fired plants was 51.0%. High-efficiency gas
combined cycle is a dominant gas-fired plant type in Korea, and this technology
contributes to improved efficiency.
Electricity tariffs in Korea are regulated by the government. Average revenue perkilowatt-hour sold in 2012 was 99.1 KRW. Prices, except for agricultural use, show anincreasing trend from 2010 to 2012, as can be seen in Figure 17, due to increasingfuel prices and investment costs. However, regulated electricity prices are still lower
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O V E R V IE W O F P O W E R G R ID S IN NEA

than the overall power-generation costs, and KEPCO has remained in a chronic stateof deficit since 2008.
Figure 17 Historical electricity prices, Korea
KRW/kWh120

Residential
Public/Service

100

Educational
80

Industrial

60

Agricultural
Street lighting

40

Average

20

0
2000

2005

2010

2011

2012

Source: KESIS (2015).

2.3.3. ECONOMY’S ENERGY PLAN
The 7th Basic Plan for Long-Term Electricity Supply and Demand was decided by
MOTIE (Ministry of Trade, Industry and Energy) in July 2015. This is the Korean
government’s official electricity-sector plan. The 7th plan provides a forecast and planfor future electricity demand and supply up to 2029. General directions andhighlights of the new plan are: 1) prioritisation of secure and stable electricity supply,2) acceleration of low-carbon generation to reduce GHG emissions after 2020, 3) the
first nuclear retirement in Korea (Kori-I in June 2017) and additions of two reactors, 4)
cancellation of four new coal-fired plants, and 5) promotion of distributed renewables(MOTIE, 2015; JAIF, 2015).
The 7th plan foresees that Korea’s electricity market steadily grows in terms of
consumption, from approximately 498TWh in 2015 to 766TWh in 2029. Compared to
the 6th plan, the growth slightly declines mainly due to the downward revision of GDP
forecast. Annual peak load continues to occur in winter season (usually aroundDecember ~ January); however, summer peak (usually around August) remains thesimilar level to winter peak. Therefore, tight demand-supply situation is expected tooccur both in summer and winter periods.
The 7th plan illustrates that approximately 14% of total demand (110TWh) is reduced
by demand management measures, including the use of smart-metre, electricity
pricing mechanisms, promotion of higher-efficient products, and so on (Figure 18).
Coal-fired generation decreases its share; however, it still remains as the main fuelsource due to growing demand. Despite the cancellation of four plants, coal-fired
capacity is projected to increase from 27GW in 2015 to 44GW by 2029, respectively
accounting for 28% and 27% in capacity mix. NRE (new and renewable) technologies
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O V E R V IE W O F P O W E R G R ID S IN NEA

show the largest expansion among the fuel type, in terms of capacity, from about
6GW in 2014 to 33GW by 2029.
Figure 18 Future capacity projections, 7th Basic Plan for Long-term Electricity
Supply and Demand
GW
200

New & renewable energy
District CHP

150

Hydro
Oil-fired100

Gas-fired
Coal-fired
Nuclear

50

Peak load

0
2015

2020

2025

2029

Peak load (after demand
management)

Source: MOTIE (2015).

2.4.

RUSSIA

2.4.1. ELECTRICITY MARKET AND POWER GRID
Russia classifies its territory into seven integrated power systems (IPSs): IPSNorthwest, IPS-Center, IPS-Middle Volga, IPS-Urals, IPS-South, IPS-Siberia and IPSEast (Figure 19), and these IPSs comprise 69 regional power systems with a frequencyof 50Hz (EBRD, 2010). Figure 20 describes Russia’s transmission network area (Popel,2012). Major existing cross-border interconnections from IPS-Siberia and IPS-East toneighbouring NEA economies (China and Mongolia) are given in Table 1.
Russia began restructuring its power industry in 2000. All thermal-generation andregional power-distribution companies were privatised before July 2008. From July
2008, the generation and transmission assets in Russia have been separated underbinding regulations. Generation assets are consolidated into two types ofinterregional companies: 7 wholesale generation companies (WGCs) and 14 territorial
generation companies. Six WCGs were established, with one state-owned holding
company (RusHydro) which controls over 53 hydro power plants. Each WGC has
power plants sited in different regions to prevent the emergence of a possible
electricity market monopoly.
Ultra-high-voltage (UHV) and high-voltage (HV) transmission lines are mainly
assigned to the Federal Grid Company of Unified Energy System (FGC UES), whereas
middle- and lower-voltage lines and distribution grids are owned and operated byinter-regional distribution grid companies. FGC UES is the operator and manager of
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O V E R V IE W O F P O W E R G R ID S IN NEA

Russia’s unified electricity transmission grid system, including HV transmission lines,
and holds the status of a natural monopoly (FGC UES, 2014). The Federal
Antimonopoly Service is in charge of monitoring the long-distance powertransmission market.
Figure 19 Power grids, Russia

1: IPS-North West, 2: IPS-Center
3: IPS-Middle Volga, 4: IPS-Urals
5: IPS-South, 6: IPS-Siberia, 7: IPS-East

Source: EBRD (2010).
Note: IPS=integrated power system.

Figure 20 Transmission network areas, Russia

Federal grid area
Isolated grid area
Non-electrified area

Source: Popel (2012).

The free electricity trading market (one-day forward) was launched in November
2003 within the framework of the Federal Wholesale Electricity Market (FOREM). In
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O V E R V IE W O F P O W E R G R ID S IN NEA

September 2006, the regulated sector of the wholesale market was replaced by asystem of contracts to be concluded between buyers and sellers.
As mentioned below, Russia is interconnected to various regions, including China,
Kazakhstan, Georgia, Mongolia, South Ossetia, Ukraine and Azerbaijan. Inter RAO, apublic6 Russian company, manages cross-border electricity trading.

2 . 4 . 2 . E L E C T R I C I T Y D E M A N D A N D S U P P LY
Russia’s power-generation capacity reached approximately 233GW in 2012 (Figure21) at an AAGR of 1.1% from 2000. Thermal power plant capacity holds the biggest
share, at approximately 69% over the last decade. The peak load season is winter.
Russia has developed the largest and oldest district heating (DH) systems in theworld, and has almost 500 combined heat and power stations, 200,000km of DH
pipeline network, and more than 65,000 boiler houses (IEA, 2009).
Figure 21 Historical power-generation capacity, peak load and generation,
Russiaa) Installed capacity and peak loadb) Generation

GW

TWh

250

1 200
Nuclear

Nuclear

1 000
ThermalThermalPeak load

200
150
100

800

Hydro

Hydro
600

Other
renewables

Other
400
renewable
s
200

50
0

0
2000

2005

2010

2011

2012

2000

2005

2010

2011

2012

Sources: EIA (2015), JEPIC (2014a).

Concerning the power-generation mix in 2012, thermal power plants account for 67%,hydro power plants for 16% and nuclear for 17%. Nuclear generation increased by
1.35 times between 2000 and 2012, whereas hydro power plants remained at thesame level (1.01 times). Renewables (except hydro) increased by 35% from 2000;
however, its share has remained at approximately 0.3% over the last decade.
In 2012, the volume of exports amounted to 18.4TWh, which is 4.3TWh less than in2011 (–19.1 %). The decline in exports is due to lower purchase volumes by the

6 State-owned entities are the major shareholders of Inter RAO.

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O V E R V IE W O F P O W E R G R ID S IN NEA

Republic of Finland (–60.6% compared to 2011). The main directions of exports in2012 were Lithuania (26.0 % of total exports), Finland (20.7 % of total exports) andBelarus (20.1% of total exports). Electricity was also supplied to China (14.3% of totalexports), Kazakhstan (12.4% of total exports), Georgia, Mongolia, South Ossetia,
Ukraine and Azerbaijan. In 2012, electricity imports totalled 2.6TWh, which is 0.8TWhless than in 2011 (–23.8 %). The decline was recorded in all electricity imports. The
main origins of electricity imports in 2012, as well as in 2011, were Kazakhstan (75.7 %of total imports) and Georgia (14.1% of total imports). Russia also imports from
Azerbaijan, Mongolia and Belarus.
The scale of Russia’s power grids varies from region to region (Figure 22). As
mentioned in Section 4, our study’s definition includes a part of IPS-Siberia and IPSEast as city nodes. IPS-East has the smallest grid scale in terms of installed capacity,
mainly comprising 5.7GW thermal power plants and 3.3GW hydro power plants. The
total installed capacity in IPS-Siberia is the second largest among the seven powersystems, mostly comprising hydro power plants (23GW in 2012).
Figure 22 Installed capacity and peak load by power grid, Russia, 2012
GW
60

Hydro

50

ThermalNuclear40

Peak load
30

20
10

East

Siberia

South

Urals

MiddleVolga

Center

North
west

0

Source: JAIF (2013).

According to RITE (2014), the average efficiency of Russian thermal power plants
between 2009 and 2011 was 31.8% (at the generation end, on an LHV basis), which islower than the global average by 5.5 points. The average efficiency of coal-fired andgas-fired plants for the three years was 30.6% and 32.3%, respectively. RITE (2014)
reported that over the last ten years, both coal-fired and gas-fired plant efficiency inRussia has remained constant.

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O V E R V IE W O F P O W E R G R ID S IN NEA

Figure 23 indicates historical average electricity prices in Russia in the areas for boththe joint stock companies ‘Far Eastern Energy Company (FEEC)’ and ‘Sakhalinenergo’7.
Electricity in isolated power grids in the Far East region is sold through regulated
retail markets at regulated prices. For the Amur Region, Khabarovsk and Primorye
territories as well as the Jewish Autonomous region, the electricity tariff for end
consumers in the retail market is determined based on the principles of wholesale
prices translation provided in the ‘Fundamental Principles and the Rules for Applying
Prices/Tariffs’ approved by the Order of the Russian Federal Tariff Service dated 30
November 2010, No. 364-e/4.
The electricity prices in the Far East area show increasing trends over the last decade.
The average value in the FEEC area rose by 4.3 times from 2000 to 2012 (from0.62 RUB/kWh to 2.65 RUB/kWh) at an AAGR of 13%. Electricity prices in the Sakhalinarea are higher than those in the FEEC area by approximately 30%.
Figure 23 Historical average electricity prices, Russia’s Far East region (Far
Eastern Energy Company area and Sakhalinenergo area)
RUB/kWh
4

Amur region(FEEC area)
Primorye territory(FEEC area)
Khabarovsk territory(FEEC area)
Jewish autonomous oblast(FEEC area)
Far Eastern Energy Company(average of FEEC area)
Sakhalinenergo (JSC)

3

2

1

0
2000

2005

2010

2011

2012

Source: RAO Energy System of East (2013).
Note: FEEC = Far Eastern Energy Company. The value of ‘FEEC average’ in 2005 and 2000 is derived fromthe average tariff for the whole Far East electricity system.

2.4.3. REGIONAL ENERGY PLAN
Figure 24 shows the power development plan till 2030 in Russia’s Far East region. The
installation of a 500kV transmission line is planned for the Far East’s power system tostrengthen its backbone transmission networks. In addition, the plan mentions a
200kV-scale new power line in Sakhalin. The region has nuclear development plans
with a total capacity of 1120MW until 2030, hydro power development plants (total

7 These areas belong to IPS-East in Figure 19.

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O V E R V IE W O F P O W E R G R ID S IN NEA

capacity: 1680MW), new and renewable energy (total capacity: 400MW) and thermal
power plants (total capacity: 9400MW).
Figure 24 Russia’s Far East power sector development, up to 2030.

Source: Saneev & Sokolov (2015).

2.5.

C O M PA R I S O N O F T H E M A J O R
I N D I C ATO R S A C R O S S N E A R E G I O NSection 2 summarised the electricity market, electricity demand and supply situation,and regional energy plans in NEA. This section compares the major indicators in the
NEA’s different sub-regions. Figure 25 shows the frequency, peak load, power
generation mix, and electricity prices.
Figure 25a) describes the frequency in this region, including in Mongolia and DPRK.
The NEA region comprises a 50Hz area (China, the east part of Japan, Mongolia andRussia) and a 60Hz area (the DPRK, the western parts of Japan, and Korea). As Section
3.2 subsequently mentions, the Russia (50Hz) and Korea (60Hz) are interested inconnecting their regions, and the Korean utility has displayed an interest in China(50Hz)–Korea (60Hz) interconnections. These cases propose HVDC interconnections,which are feasible from a technical viewpoint.
Figure 25b) indicates the peak load in each sub-region. Japan is disaggregated into
three categories in the figure: the Hokkaido island area (50Hz), Tohoku+Tokyo area
(50Hz) and the rest of Japan (‘west Japan’, 60Hz), which correspond to the modelled
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O V E R V IE W O F P O W E R G R ID S IN NEA

nodes in Section 4. The North China power grid, which includes the Beijing area, isthe largest among the sub-regions. Its scale (163GW) is approximately two–threetimes larger than the China Northeast, Tohoku+Tokyo, west Japan or Korea grids. In
contrast, the Hokkaido (Japan) and Far East (Russia) areas are relatively small(approximately 5GW).
Figure 25 Comparison of major indicators, Northeast Asia region, 2012a) Frequencyb) Peak load
GW
200
150
100
163
50
52

6

64

89

77

5

China

c) Generation capacity shareJapan

Far East(FEEC area)

West Japan(estimated)Tohoku+TokyoHokkaido

50Hz
60Hz

North China
grid area

Northeast
grid area

0

Korea Russiad) Average electricity price level

GW%

2012USD/kWh

100%

0.25

Other
Wind
Hydro
ThermalNuclear

80%
60%
40%
20%

0.22

0.2
0.15

0.08-0.12

0.1

0.09

0.08-0.09

0.09

0.05

North China
grid area

Far East(FEEC area)

China

Average

Korea Russia

Northeast
grid area

Far East(FEEC area)

West Japan(estimated)Tohoku+TokyoJapan

0

Average

China

Hokkaido

Northeast+North China

0%

Japan

Korea

RussiaNote: FEEC = Far Eastern Energy Company. Figure 25a) shows frequency in Mongolia and DPRK forreference. The peak load in west Japan in Figure 25b) is estimated from the monthly peak load data ineach power service area. Figure 25d) shows average prices in 2012 for Japan, Korea and the Russia FEEC
area. Average exchange rates in 2012 are assumed for this comparison. For the North China andNortheast China grids, the graph shows the ranges of electricity prices in each region.

Each region relies on thermal power plants (Figure 25c)). The nuclear capacity sharesin Japan and Korea are more than 20%. Hydro capacity accounts for approximately
37% in Russia’s Far East region and approximately 14%–20% in Japan’s regions. In
contrast, the hydro capacity share is relatively small in Korea (8%) and in
Northeast+North China (4%). Overall, China has abundant hydro resources (economic
potential: 402GW and 1750TWh/y). However, these resources are distributed mainly
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O V E R V IE W O F P O W E R G R ID S IN NEA

in the western and southern parts of China, and the economic potential in the
Northeast+North China area is only 5.4% (approximately 22GW) (Huang & Yan, 2009).
Instead, wind resources are plentiful in northern parts of China, and this source’s
capacity in the Northeast+North China grid reached 41GW (12% in capacity mix) in2012 (JEPIC, 2014a).
The average price in Japan (0.22 USD/kWh) is approximately double that of otherregions (Figure 25d)). The prices in other regions (northeast part of China, Korea andFar East Russia) are at a similar level (approximately 0.09–0.12 USD/kWh). China andRussia have faced difficulties in agreeing on power imports/exports prices and theirpower trade was disrupted twice (Sakai, 2014). In general, a larger domestic price gap
provides more appropriate conditions for power trades to ensure profit margins(between trading price and domestic price). Conversely, unless these average prices
hide significant differences by period (season/time of day), it remains hard to secure
certain margins from the power trade among the economies with similar electricity
prices (for example, China, Korea and Russia in 2012).

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3. M A J O R C O N C E P T S O F P O W E R
GRID INTERCONNECTIONSThis section summarises the major grid interconnection concepts in NEA. First, thissection outlines NEA region-wide grid interconnection concepts (Section 3.1). Then,
Section 3.2 focuses on the proposals of each individual (bilateral) interconnection.

3.1.

NEA-WIDE GRID
INTERCONNECTION CONCEPTS

Since the 1990s, grid interconnection concepts—for example, ‘Northeast AsianElectrical System Ties’ (NEARST)—have been discussed mainly by Melentiev Energy
System Institute, Siberian Branch of the Russian Academy of Science (ESI SB RAS) witha focus on investment savings and power-system reliability improvements (KERI,
2003; EN+, 2012; Belyaev, et al., 2014). However, cross-border power gridconnections have not been explored fully in NEA thus far, and discussions stagnatedin the latter half of the 2000s. Around or after 2010, several regional events
mentioned (Section 1) made interconnections more attractive as a means ofpromoting renewable energy, building a resilient power system and achieving an
economical electricity supply (by levelling demand or effective use of fossil fuelresources). According to our survey, six out of seven major concepts has been
proposed after 2010 (Table 3).
The mainly focused energy sources in ‘Asia Super Grid’ (JREF, 2011), ‘Asia PacificPower Grid’ (Japan Policy Council, 2011) and ‘Gobitec and Asian Super Grid’ (Energy
Charter, et al., 2014) are renewable energy; in particular, these concepts emphasisethat larger grid scale due to interconnections contributes to integrating variable
renewables. Other concepts include effective utilization of fossil fuel-fired plants aswell. ‘GRENATEC’ (GRENATEC, 2010) proposes a shift from carbon-intensive coal tocleaner fuel, including renewables and natural gas, by enhancing power grid and gas
pipeline connectivity. ‘Northeast Asia Super Grid’ (Skoltech, 2014a) focuses onthermal plants and conventional renewables. Massive deployments of variable
renewables are not considered in this concept. Geographical coverage varies concept
by concept. Three of the concepts (GRENATEC, Asia Super Grid and Asia Pacific Power
Grid) propose connecting power grid to outside NEA regions, such as ASEAN andAustralia grid.
Various interconnection concepts have been proposed by various private companies
or research institutes; however, there is limited coordination by economy’s authorities
or international/regional organisations (like HAPUA in the ASEAN region) so far. In
order to draw up a detailed blueprint as well as to research, discuss and implement
the concepts in an effective manner, a coordinating entity should be established.
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Table 3 Major region-wide grid interconnection proposals, Northeast Asia
Proposal title

Main related organisations

Quick descriptions(Source)
NEAREST(Northeast AsianElectrical System
Ties)(Belyaev, et al.,
1998; KERI, 2003;
EN+, 2012)

GRENATEC Melentiev Energy System
Institute, Siberian Branch of
the Russian Academy of
Science Korea Electrotechnology
Research Institute GRENATEC(GRENATEC, 2010)

 Geographical scope: China, Japan, Korea,
Mongolia and Russia.
 Purpose: peak-load sharing, investment oroperation costs reduction and reliability
enhancement
 Several quantitative analyses on the certain
connection routes have already been
conducted.

 Geographical scope: ASEAN nations,
Australia, China, Japan, Korea and Chinese
Taipei.
 Purpose: shift from coal-fired to gas-fired
and renewable energy
 Proposed connections include power lines
as well as gas pipelines and fibre optic
cables to realise ‘cloud energy’.

Asia Super Grid
(JREF, 2011)

 Japan Renewable Energy
Foundation

 Geographical scope: Bangladesh, Bhutan,
China, India, Japan, Korea, Malaysia,
Philippines, Singapore, Chinese Taipei,
Thailand and Russia
 Purpose: demand levelling, resilienceenhancements, renewable energy
promotion and fair electricity price

Asia Pacific Power
Grid (Japan Policy
Council, 2011)

 Japan Policy Council

 Geographical scope: ASEAN power gridregion, Australia, Japan, Korea and Chinese
Taipei.
 Purpose: renewable energy promotion
 Propose establishing ‘Green Energy Grid
Organization’ (tentative name) to realise an
Asia Pacific Power Grid.

NEA Super Grid(KEPCO, 2014a)

 Korea Electric Power
Corporation

 Geographical scope: China, Japan, Korea,
Mongolia and Russia
 Purpose: energy resource sharing, demandlevelling and power system reliability
improvements

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M A J O R C O N C E P T S O F P O W E R G R ID I N T E R CO N N E CT IO N S

Proposal title

Main related organisations

Quick descriptions(Source)
Gobitec and AsianSuper Grid
(Energy Charter, etal., 2014)

 Energy Charter Secretariat
 Korea Energy Economics
Institute Geographical scope: China, Japan, Korea,
Mongolia and Russia.
 Purpose: renewable energy promotion.

 Energy Systems Institute,
Russian Academy of Science(ESI RAS) Massive integration of wind (50GW) andsolar (50GW) power generation in the Gobi
desert area

 Ministry of Energy, Mongolia HVDC connection from Gobi desert area toother related regions

 Japan Renewable Energy
Foundation

 Electricity supply costs [USD/kilowatt-hour]
estimated from the Gobi area

Northeast Asia
Super grid

 Skolkovo Institute of Scienceand Technology (Skoltech) Geographical scope: China, Japan, Korea,
Mongolia and Russia.

(Skoltech, 2014a)

 Melentiev Energy Systems
Institute, Siberian Branch of
the Russian Academy of
Science Purpose: energy resource sharing, demandlevelling En+ Group Korea Electric Power
Corporation

 Three interconnection options from Russia
to Korea Modelling and analysis work finished in
April 2015.

 Korea Energy Economics
Institute
Note: ASEAN = Association of Southeast Asian Nations; HVDC = high-voltage direct current.

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M A J O R C O N C E P T S O F P O W E R G R ID I N T E R CO N N E CT IO N S

3.1.1. NORTHEAST ASIAN ELECTRICAL SYSTEMTIES (NEAREST)
The NEAREST concept has been discussed since the 1990s, led mainly by Melentiev
Energy Systems Institute, Siberian Branch of the Russian Academy of Science (ESI SB
RAS). NEAREST’s proposed geographical scope covers China, Japan, Korea, Mongolia
and Russia (Figure 26). Belyaev et al. (2014) summarised the potential benefits of
NEAREST as follows: a) decreasing demand for installed generation capacities due todiversity in daily and yearly peak loads, b) increasing reliability of electric powersystems to be interconnected, c) involvement of large renewable energy (primarilyhydropower) sources in the energy balances of different countries, d) acquisition ofincomes from electricity trade and e) reduction of electricity prices.
Figure 26 Northeast Asian Electrical System Ties concept

Source: Belyaev, et al. (1998).
Note: NEA = Northeast Asia; AC = alternating current; DC = direct current.

Chung and Kim (2007) analysed the economic feasibility of the NEAREST concept
with a focus on DPRK, Korea and Russia. They employed a mathematical optimisation(linear programming) model, called ORIRES, originally developed by ESI SB RAS. They
conducted simulations under the assumption that imported electricity contributes toachieving the reserve margin criteria of the importing region (see Equation (2) in
Chung and Kim (2007)), and concluded that power grid interconnection produces
immense economic benefits due to avoiding the construction of new power plants(Table 4). Interconnections reduce the total annual system costs by 7%–11.1% eachyear.

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M A J O R C O N C E P T S O F P O W E R G R ID I N T E R CO N N E CT IO N S

Table 4 Independent system vs. interconnection system, economic evaluation

Year 2010

Year 2015

Year 2020

Interconnected line

Generating facility

investment costinvestment cost

Fuel cost

Total

Independent

-

3 595

9 660

13 254

Interconnected

168

2 052

10 10312 323

Total cost changes

-

-

-

-7.0%

Independent

-

7 268

9 785

17 053

Interconnected

234

5 156

9 898

15 288

Total cost changes

-

-

-

-10.4%

Independent-

10 89520 918Interconnected

298

7 462

18 591

Total cost changes

-

-

-

-11.1%

Source: Chung & Kim (2007). APERC reproduces the table based on the information in the source.

Choi et al. (2006) and Yoon (2007) analysed the benefits to power-system reliability
from grid interconnections between Korea, DPRK and Russia’s Far East region. These
researches developed a reliability evaluation model, called NEAREL (NREARESTReliability), to assess reliability indices including loss of load expectation (LOLE) and
expected energy not supplied (EENS) in the related economies. Choi et al. (2006)
examined the reasonable interconnection capacity using sensitivity analysis, and Yoon
(2007) analysed the reliability of four interconnection scenarios between Korea andRussia’s Far East region. Figure 27a) shows the interconnection scenario examined in
Choi et al. (2006), and Figure 27b) shows the simulation results in Korea (LOLE and
EENS). Figure 27b) indicates that reliability indices show a saturation trend fromapproximately 3GW tie-line capacity.
Figure 27 Reliability assessment of NEAREST concept (example)a) Schematic diagram of the studyb) Results of Korean power system reliability
assessment

Source: Choi, et al. (2006).
Note: LOLE = loss of load expectation; EENS = expected energy not supplied.
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3 . 1 . 2 . G R E N AT E C
GRENATEC is a private research organisation studying the viability of a ‘Pan-Asian
Energy Infrastructure’ (GRENATEC, 2010). The proposed concept would connect
Australia to Northeast Asia via the South and East China Seas through a combinationof HVDC transmission lines, gas pipelines and fibre optic infrastructures (Figure 28).
The aim is to create flexible cross-border energy and information networks to replacecarbon-intensive coal energy with gas and renewable energy in the region. The
network is called ‘cloud energy’ in GRENATEC, and pipeline gas and renewableelectricity are intended to be traded like network packets in the telecommunications
field. They advocate realisation of this concept by 2050.
Figure 28 Pan-Asian Energy Infrastructure concept

Source: GRENATEC (2010).

3.1.3. ASIA SUPER GRIDThe Japan Renewable Energy Foundation (JREF) proposed the Asia Super Grid
concept (Figure 29) in September 2011 (JREF, 2011). This concept entails connecting
countries in the NEA region (such as Japan and Russia) and South Asia countries(such as India) through Southeast Asia via HVDC transmission line technology. The
objectives of establishing these interconnections are demand levelling, stableelectricity supply and fair electricity prices. Electricity prices in Japan areapproximately 0.2 USD/kWh, which is twice to ten times as expensive as in other
Asian counties. According to their concept, HVDC transmission losses areapproximately 5% for 3,000km transmission length, and it could be cost effective forthe region. They also insist that this super grid is an effective means for large-scale
integration of renewable energy as time-zone and climate differences contribute tosmoothing output variations. This concept does not include quantitative analyses of
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costs and benefits. However, as mentioned in Section 3.1.5, JREF is actively pursuingthis topic.
Figure 29 Asia Super Grid concept

Source: JREF (2011).

3 . 1 . 4 . A S I A PA C I F I C P O W E R G R I DJapan’s Policy Council (Chair: Mr. Hiroya Masuda, Former Minister of Internal Affairs
and Communications from August 2007 to September 2008) proposed the Asia
Pacific Power Grid concept, which would connect Japan and Korea to Australia
through Southeast Asian countries as depicted in Figure 30. This proposal was theCouncil’s first recommendation, advocating that ‘Japan should propose and lead therealisation of an Asia Pacific Power Grid as part of its diplomatic strategy to establish
a society based on renewable energy’ (Japan Policy Council, 2011). They proposed
five points as follows: An international power grid should be established to promote renewable energy
and overcome its instability. Through an Asia–Pacific partnership in energy
coordination, a mutually complementary framework should be created.
 Japanese renewable energy technologies should be transferred to Asia tostrengthen the power supply in the region and secure a back-up power supply forJapan while contributing to the reduction of carbon dioxide emissions.
 An international platform, Green Energy Grid Organization (tentative name),should be created to promote renewable energy and establish the international
power grid.

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 To prepare for connections with the international power grid, a domestic power
grid unifying the entire nation should be established, with separation between thegeneration and distribution of electricity.
 Research and development efforts that will lead to discontinuous innovations,such as lithium-air batteries, should be intensified.
Their proposal mainly concerns the concept’s overall scope and does not include any
quantitative analyses or assumptions about the economics involved.
Figure 30 Asia Pacific Power Grid concept

Source: Japan Policy Council (2011).

3.1.5. GOBITEC AND ASIAN SUPER GRIDThe Gobitec and ASG initiatives conducted international research projects andpublished a report titled ‘Gobitec and Asian Super Grid for Renewable Energies inNortheast Asia’ in January 2014 (Energy Charter, 2014c). The initiative involves fiveproject partners from related regions: Energy Charter Secretariat, Korea Energy
Economics Institute (KEEI), ESI SB RAS, Ministry of Energy of Mongolia and JREF.
Fraunhofer Institute for Systems and Innovation Research ISI and Fraunhofer Institutefor Solar Energy Systems ISE joined as project consultants. JREF is actively researching
this topic and organised an international symposium titled ‘Roadmap to Asia Super
Grid’ in January 2014 (JREF, 2014).
The Gobitec concept represents the idea of producing clean energy from renewableenergy sources in the Gobi desert and subsequently delivering the produced energy
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M A J O R C O N C E P T S O F P O W E R G R ID I N T E R CO N N E CT IO N S

to regions with high demand. The proposal calls for transmission of clean electricity
via a large-scale cross-border transmission network—the ASG—which would connect
Russia, Mongolia, China, Korea and Japan as shown in Figure 31. The overall potentialof solar and wind energy in the Gobi desert is approximately 1.5TW and 1.1TW,
respectively (Energy Charter et al. (2014), p.26). They propose the installation of
50GW solar power and 50GW wind power capacity. The total investment inconstruction and annual O&M costs are estimated to be approximately
294.6 billion USD and 7.4 billion USD/y, respectively (Table 5).
This initiative proposed the concept as well as conducted a first analysis of its
technological, legal, economic and environmental opportunities/challenges. The key
outcomes of their analysis are as follows: Technological: Due to the extensive electricity transmission distance, the study
strongly recommended the use of point-to-point HVDC transmission lines. To
maintain low transmission loss, the Gobitec network should be operated at a
voltage of more than 1000kV.
 Legal: The study concluded that a legal framework, the Energy Charter Treaty, isnecessary for the enactment of the concept to ensure a positive investment
climate, reliable transit regime and protection of property rights.
 Economic: The report estimated total supply unit cost (TSUC) [USD/kilowatt-hour]
and weighted average electricity charge (WAEC) considering the distribution shareof exported electricity (Table 6). By comparing TSUC and WAEC, the study
concluded that the concept can be beneficial if the average capacity factor of theinstalled renewables is greater than at least 30%.
 Environmental: The study also estimated CO2 reduction effects using emission
factor data for 2011. Total CO2 reduction of approximately 187Mt-CO2 can beachieved: 149Mt-CO2 in China, 21Mt-CO2 in Korea, 13Mt-CO2 in Japan and 4MtCO2 in Mongolia. (Energy Charter et al. (2014) mentioned 187Gt-CO2 reductions,but we suspect a unit calculation error.)

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Figure 31 Gobitec and Asia Super Grid concepta) Possible interconnections of the ASGb) Generation mix of 2030 and Gobitec
capacity

Source: Energy Charter, et al. (2014).

Table 5 Total construction investment and operation & maintenance costs
Construction cost

Annual O&M cost

[Million USD][Million USD/year]

Gobitec

237 900

5 948

Asian Super Grid (ASG)-Total

56 710

1 418

ASG+Gobitec collecting system

34 562864

Mongolia side collecting system

235

6

Russia side collecting system

666

17

China side collecting system

16 750419

Korea side collecting system

1 476

37

Japan side collecting system

3 021

76

294 610

7 366

Sum

Source: Energy Charter, et al. (2014). APERC reproduces the table based on the information in the source.

Table 6 Total supply unit cost estimation and comparison with weighted
average electricity charge of importing countries
Capacity factor of renewables (solar+wind farms)
a. Annual sales energy amount

20%

30%

40%

50%

60%

162

243

234

438

525

32 40232 40232 40232 40232 402

0.200

0.133

0.100

0.080

0.067

0.136

0.125

0.120

0.117

0.115

[TWh/year]
b. Total annual cost
[Millions USD/year]
Total supply unit cost (=a/b/1000)[USD/kWh]
Weighted Average Electricity Charge[USD/kWh]
Source: Energy Charter, et al. (2014). APERC reproduces the table based on the information in the source.
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3.1.6. NEA SUPER GRID (KEPCO)KEPCO features a super grid team in its power grid planning department, which isactively working on the super grid concept as well as attending international
symposiums (JREF, 2014; Energy Charter, 2014a) and participating in international
research activities (see also Section 3.1.7). KEPCO maintains an overall picture of thesuper grid as shown in Figure 32, which is intended to integrate diverse energy
sources, share peak load among related regions and realise a reliable power system.
Figure 32 Northeast Asia Super Grid concept

Source: KEPCO (2014a).

3 . 1 . 7 . N O RT H E A S T A S I A S U P E R G R I D ( S KO LT E C H )The Center for Energy Systems at the Skolkovo Institute of Science and Technology(Skoltech)—a private graduate university in Skolkovo, a suburban area of Moscow—
started research on modelling and analysis of the so-called ‘super grid’ or ‘Asian
Energy Ring’ in the framework of a memorandum signed between Skoltech, the En+
Group and KEPCO (Korea) during Russian President Vladimir Putin’s visit to Korea in
November 2013 (Skoltech, 2014b).
Since then, researchers from Skoltech and Melentiev Energy Systems Institute,
Siberian Branch of the Russian Academy of Science (ESI SB RAS) have studied thepotential benefits of the super grid concept as illustrated in Figure 33. This researchseeks to develop options for electricity exports from Russia to countries in NEA. As
depicted in Figure 33, three alternative routes from Russia to Korea are considered: asubmarine cable connection from Dalian (China) and two transmission lines through
DPRK. The project’s profitability might substantially increase with Japan’s
participation with supplies undertaken by the northern (undersea cable fromPAGE 40

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Sakhalin) and southern (undersea cable from Korea through Kyushu to Honshu
islands) routes. (Skoltech, 2014a; Skoltech & ESI SB RAS, 2015).
On April 2015, Skoltech hosted an international workshop on the Asian energy supergrid project, during which they presented results of the research conducted bySkoltech in conjunction with the ESI SB RAS and supports of KEPCO and En+ group.
Skoltech presented simulation results showing the benefits of power gridinterconnection in the region. Calculated annual benefit is 24.4 billion USD/year in
the “Limited integration scenario” (Skoltech & ESI SB RAS, 2015). This scenario takes
into account energy security concerns of individual economies.
Figure 33 Northeast Asia Super Grid concepts

Source: Skoltech & ESI RAS (2015).

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3.2.

B I L AT E R A L I N T E R C O N N E C T I O N
CONCEPTS

Several organisations in the relevant regions are working on bilateralinterconnections in order to realise the NEA-wide grid interconnection concept (seeSection 3.1). We also conducted a survey regarding these bilateral interconnection
activities over the last few years, which are summarised in Table 7.
According to our survey, Korean and Russian organisations, including KEPCO, Inter
RAO and FGC UES, are working actively to expand cross-border power trades. KEPCO
has signed the aforementioned MOU with Skoltech and the En+ Group in November
2013, and Korea’s master plan mentioned that Korea-Russia connection should beconsidered as a future potential project if it is profitable and DPRK situation improves(MOTIE, 2014). The SGCC (China) and Russia’s grid company signed a strategiccooperation agreement in May 2014 with the Chinese Premier Xi Jinping and Russian
President Vladimir Putin in attendance. By contrast, involvements of Japan side islimited; several telecommunication companies and trading companies have shown
their interests, yet electric power utilities --which owns transmission network until thelegal unbundling (April 2020)-- have not been involved in the discussions.
The relevant organisations have commenced a feasibility study (F/S) on Korea–Russia(through DPRK), Japan–Korea and Japan–Russia (Far East) interconnections. The
group of Korean and Russian organisations above (KEPCO, Skoltech and En+) as well
as Melentiev Energy System Institute (ESI SB RAS) has quantitatively discussed KoreaRussia route as a part of NEA-wide super grid (Skoltech & ESI SB RAS, 2015). KEPCO(2014a) presented that ‘Pre-Feasibility Study’ is ongoing for the Japan–Korea route
discussions, and Nikkei (2013) reported that a group of Japanese and Russiancompanies plans to conduct a F/S to evaluate the project’s profitability. Concerning
the China–Korea interconnections, KEPCO mentioned that they are interested in joint
research with the Chinese side (KEPCO, 2014b). As of mid-2015, most of the concepts
do not specify a power plant type for generating the energy to be exported/imported,with several concepts proposed as follows:

China–Russia: Thermal power (Smirnov, 2012), coal-fired (Asiam Research Institute,2014) and hydro power (RusHydro, 2014); Russia exports to China in theseconcepts.

 Japan–Russia: Hydro power (Nikkei, 2013) from Russia’s Far East region orcoal/gas-fired from the Sakhalin region to Japan.

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Table 7 Major concepts and progress, interconnection routes
RouteChina–Korea

Related organisations
Korea Electric Power Corporation(Korea)

China–Russia

Source/Quick descriptions

Progress

Presentation at international symposiums (KEPCO, 2014a;
KEPCO, 2014b)
Concept: Connect western Gyeonggi-do area to eastern
China (3GW HVDC line).

Proposal

Involvement by China

Proposal

Pricing agreement
Transmission
infrastructure in Russia
IPS-East

Federal Grid Company of United
Energy System (Russia)

Presentation at an international conference (Kazachenkov,
2012)

Inter RAO (Russia)

Presentation at an international conference (Smirnov,
2012)
Concept: Export power generated by Russia’s thermal
plants to China.

Study phase

ROSSETI’s company news (ROSSETI, 2014)
The two companies signed a strategic cooperationagreement.

Cooperationagreement
signed

Reports by Asiam Research Institute(Asiam Research Institute, 2014)
Concept: Inter RAO builds the largest coal-fired plants(8GW) in the Far East region to export power to China.

Study phase

RusHydro company news (RusHydro, 2014)
The parties signed a preliminary agreement to establish a
joint venture to construct up to 2GW hydro plants in
Russia and evaluate the power export potential to China.

Cooperationagreement
signedFederal Grid Company of United
Energy System (Russia)
State Grid Corporation (China)
Inter RAO (Russia)



RusHydro (Russia)
Three Gorges Corporation (China)Barriers

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RouteJapan–Korea

Related organisations
Korea Electric Power Corporation(Korea)Japan–Russia

Inter RAO (Russia)
Mitsui Corporation (Japan)
Softbank (Japan)Source/Quick descriptions

Progress

Barriers

Presentation at international symposiums (KEPCO, 2014a;
KEPCO, 2014b) and report by Korea JoongAng Daily on
KEPCO’s interests (JoongAng, 2014)
Concept: Connect Gyeongnam area to Fukuoka (2GW
HVDC line).

Pre-F/Sphase

Involvement by Japan(power utilities/publicbodies)Nikkei reported the group started F/S (Nikkei, 2013)
Concept: Russia’s Far East region exports hydro power toJapan.
Overall investment costs to be calculated within 2014.

Study phase(no updates
available
since 2013)Long transmission
distance (if the Far East
region and Hokkaido areconnected via Sakhalin)
Large investment needed
for transmission system in
the Far East region.

Inter RAO (Russia)

RAO Energy System of East (Russia)Presentation at an international symposium (Inter RAO,
2014)
Concept: Sakhalin region exports coal-fired/gas-fired
power to the Hokkaido and Honshu areas.
Total capacity: Up to 3GW.

ProposalPresentation at an bilateral symposium (RAO Energy
System of East, 2014)
Concept: Build an energy bridge between Russia’s Far Eastarea, Sakhalin and Japan. 2–4GW electricity export toJapan.
Three stages project: (1) Connect Hokkaido and Sakhalin,(2) Construct power plant in Sakhalin, and (3) connect
Sakhalin and ‘mainland’ Russia.

Proposal(Pre-F/S
expected in
November
2014)

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Route
Korea–Russia(through DPRK)

Related organisations
Ministry of Trade, Industry &Energy (Korea)

Source/Quick descriptions

ProgressMentioned in Korea’s Energy Master Plan (MOTIE, 2014)
Concept: Korea imports low-cost electricity from Russia.
Two plans proposed, 2–5GW HVDC tie lines.
Conduct joint study by Korean and Russian private sectors.

Study phase(conductedby private
sector)

Korea Electric Power Corporation(Korea)

MOU signed

En+ (Russia)



Skoltech (Russia)

Presentation at international symposiums (KEPCO, 2014a;
KEPCO, 2014b)
Concept: Connect Vladivostok to North Gyeonggido with
HVDC 500kV–800kV tie line.
MOU signed. F/S is on-going.

Federal Grid Company of United
Energy System (Russia)

Presentation at an international conference (Kazachenkov,
2012)

Proposal

Barriers

Security issues related toDPRKLong transmission
distance

Pre-F/S
phase

HVDC = high-voltage direct current; F/S = feasibility study.

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3.2.1. CHINA–KOREA ROUTE
As described in Figure 34, KEPCO presented their grid interconnection concepts,
including a China–Korea route, at several international symposia (KEPCO, 2014a;
KEPCO, 2014b). They propose to connect Western Gyeonggi-do area and the easternpart of China via HVDC 500kV lines with 3GW capacity. KEPCO mentioned theirinterest in a joint study on this route with the Chinese side.
Figure 34 China–Korea interconnection concept

Source: KEPCO (2014b).
Note: This figure shows the China–Korea route as well as Japan–Korea and Korea–Russia routes.

3.2.2. CHINA–RUSSIA ROUTE
China and Russia have already been interconnected, and historically, Russia hasexported electricity to China. Annual cross-border electricity exports areapproximately 2.63TWh and 3.50TWh in 2012 and 2013, respectively. Russiancompanies, including Inter RAO, FGC UES and RusHydro, work actively to expand
their power trade opportunities. As mentioned in Table 7, several proposals andactivities have been observed in the last few years. Historically, Russian stakeholders
mainly presented their power trade concepts; however, recently, stakeholders in bothcountries have started actively working and signed some corporation agreements(such as those between SGCC and FGC UES and between RusHydro and China Three
Gorges Corporation).
In 2012, FGC UES presented the ‘energy bridge’ concept (Figure 35). This concept
includes interconnections between west and east Russia as well as between Russia
and neighbouring regions, including NEA.

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Moreover, Inter RAO also presented three future options in 2012 to expand theelectricity trade between China and Russia. The first option involved exporting
thermal power (3.6GW scale) from Amur Oblast to Shenyang, with an estimatedannual export amount of 18TWh. The second option entailed exporting 7–7.5GWscale thermal power from Amur Oblast to Beijing, with approximately 38TWh in
annual exports (Figure 36a)). The last option involved the second option as well as
power flows from the Buryatia and Zabaykalsk regions, with total annual exports of
76TWh (Figure 36b)).
Figure 35 Prospects for energy bridge development, Russia

Source: Kazachenkov (2012).

Figure 36 Possible future China–Russia interconnection options, as of 2012a) ‘Option 2’ in Smirnov (2012)b) ‘Option 3’ in Smirnov (2012)

Beijing

Beijing

Source: Smirnov (2012).
MWt =megawatt; kWth =kilowatt hour; bln. = billion.

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In May 2014, Russian grids and the SGCC signed a strategic cooperation agreementwith the Chinese Premier Xi Jinping and Russian President Vladimir Putin in
attendance (ROSSETI, 2014). This agreement opened the way to exploring thepossibility of a European–Asian energy bridge and supplying electricity to China.
Further, these companies agreed to discuss the possibility of constructing UHV (Ultra
High Voltage) transmission lines—both AC (alternating current) and DC (direct
current)—and EHV (Extra High Voltage) sub-stations in Russia.
Furthermore, also in May 2014, the Asiam Research Institute reported that Inter RAO
conducted a F/S to build the world’s largest coal-fired power plant and export its
electricity to China (Asiam Research Institute, 2014). According to this article, InterRAO studied the costs and lead times of a plant with 8GW capacity, and analysts
estimated that the project would cost approximately 12 billion USD. This planrequires that the plant’s coal resources be sourced from Erkovetskaya.
In November 2014, Russia’s largest hydropower producer, RusHydro, announced thesigning of a preliminary agreement with the China Three Gorges Corporation(RusHydro, 2014). The agreement mainly focused on the establishment of a joint
venture, with RusHydro having 51% ownership, to build and operate up to 2GW
hydro power plants in Amur Oblast and Khabarovsk Kray in Russia (total cost of the
projects estimated as 230 billion RUB). RusHydro will conduct detailed F/Ss for eachproject and examine the electricity export potential to China.
However, according to Sakai (2014), power transmission from Russia to China has
been disrupted twice because of delays in reaching a power-trade price agreement.
Price issues would be an important agenda for expanding interconnections between
these economies.

3 . 2 . 3 . J A PA N – KO R E A R O U T E
KEPCO has a concept to connect Gyeongnam area and Fukuoka via 500kV HVDC withapproximately 2GW capacity (Figure 34). The route would be approximately 200km
long, and KEPCO emphasises its technical feasibility based on their experience (theyhave successfully installed two power cables between Jindo and Jeju (105km)).
The newspaper JoongAng (2014) also reported this concept in August 2014 as
illustrated in Figure 37. The reported route passes Tsushima Island (Japan). In thatcase, the 200km submarine route is roughly divided into a 50km segment (Busan–
Tsushima) and 150km segment (Tsushima–Fukuoka). The article also noted that
Softbank’s chairman Masayoshi Son has shown an interest in the project as the firststep towards realising the Asia super grid concept (see Sections 3.1.3 and 3.1.5).

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Figure 37 Japan–Korea interconnections route

Source: Korea JoongAng Daily (2014).
Note: ‘last month’ in this figure is July 2014. This figure does not necessarily reflect KEPCO’s plan.

3 . 2 . 4 . J A PA N – R U S S I A R O U T E
In February 2013, Nikkei (2013) reported that a group of Japanese and Russiancompanies (Inter RAO, Mitsui Corporation and Softbank) commenced a F/S on
interconnections between Japan and Russia’s Far East region (Figure 38a)). Their
proposal is based on Japan importing hydro electricity from Russia’s Far East region.
The group intended to calculate overall investment costs during 2014 andaccordingly decide whether to continue negotiations. Nikkei pointed out somechallenges, including laws/regulations revision, concerns for stable supply and hugeinvestment needs.
In January 2014, Inter RAO (2014) ‘re-’proposed a different concept to connect
Hokkaido and Sakhalin. Coal-fired and gas-fired power plants in the Sakhalin region
are planned to be primary power supply sources to Japan (Figure 38b)). Total capacity
will reach up to 3GW, comprising three power plants: two 1050MW-scale coal-fired
plants and one 800MW-scale gas-fired plant. The proposed connection points are
Cape Crillon, Korsakov and Uglegorsk on the Sakhalin side and Cape Soya/Wakkanai
city on the Hokkaido side. They further proposed to connect Hokkaido to Niigata(located on Japan’s main island) via a submarine cable.
According to Inter RAO (2013), the idea of building an ‘energy bridge’ between
Hokkaido and Sakhalin islands was originally proposed by RAO UES in 1998. The
Russian side jointly conducted a pre-F/S with Marubeni Corporation (Japan) in 1999
and signed a protocol of cooperation with Sumitomo Corporation (Japan) in 2003.
However, no further progress has since been achieved.

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In September 2014, at the second Japan–Russia Forum held in Moscow, RAO Energy
System of East8 presented four prospective energy cooperation fields (RAO Energy
System of East, 2014). They proposed the Japan–Russia energy bridge concept,
comprising three phases as shown in Figure 38c): (1) construct transmission lines
between Hokkaido and Sakhalin islands, (2) install a 1GW-scale power plant andadditional transmission lines (500kV) in Sakhalin, and (3) construct a connection
between Sakhalin and ‘mainland’ Russia (500kV DC submarine cables). Total powertransmission scale would be 2–4GW.
Figure 38 Japan–Russia interconnection conceptsa) Nikkei (2013)b) Inter RAO (2014)
Power-generation units construction plan:- Total capacity: Up to 3 GW
- Realization in three stages- First stage: coal-fired power plant, 1050MW- Second stage: coal-fired power plant, 1050MW- Third stage: gas-fired power plant, 800MW

RussiaTransmission along Sea of Japan side

Sakhalin

China

Submarine cable connection

Far EastJapanc) RAO energy system of East (2014)
Phase 1- Submarine cable construction (La Pérouse Strait).
- Construction of power receivers and transmission
lines at Hokkaido isl.

Phase 2- Power plant construction for power exports orthe extension of existing power stations under
1GW.
- Additional transmission line construction (500kV)
in south Sakhalin.

Phase 3Phase 2Phase 3- Operation of two submarine 500kV DC cables
between Sakhalin and 'mainland' Russia toexport electricity from IPS-East.

Phase 12-4GW power export is expected. A pre-feasibility
study is expected in November 2014.

Sources: Nikkei (2013), Inter RAO (2014) and RAO Energy System of East (2014).

8 RAO Energy Systems of East was founded in July 2008 to manage the energy companies operating in

the United Energy System of East (Primorsky Krai, Khabarovsk Krai, Amur Oblast, Jewish Autonomous
Oblast, and South Yakutia) as well as in six isolated energy systems (RAO Energy System of East, 2015).

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3.2.5. KOREA–RUSSIA ROUTE
Several research institutes have studied the Korea–Russia route for more than ten
years (see Section 3.1.1). In January 2014, Korea’s Energy Master Plan mentioned two
possible approaches to grid interconnection with Russia (Figure 39). The mainconcept involves importing electricity at a low cost due to Russia’s abundantresources. The plan mentioned that the Korean and Russian private sectors should
conduct a joint study, whereas the master plan mentioned that ‘the concept should
be considered as a prospective mid- to long- term governmental project if the joint
study concluded that it is profitable and if the overall conditions, including interKorean relations, improve’ (MOTIE, 2014). Plan 1 is a Korea–DPRK–Russia HVDC link,supplying power in the DPRK. The proposed HVDC capacity is 2–5GW, andtransmission length will be approximately 1,200km. Plan 2 is a direct connection
between Korea and Russia via HVDC with a capacity of 3–5GW. Transmission length
will be approximately 1,000km.
Figure 39 Korea–Russia interconnection plans in Korea’s Energy Master Plan

Source: MOTIE (2014).

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4. M O D E L L I N G A N D A N A LY S I S
OF GRID INTERCONNECTIONS
Referring to the literature summarised in the previous sections, we developed amulti-region power system model (Linear Programming model) and macroscopicallyexamined the potential benefits of power grid interconnections in NEA. 9 This section
explains the methodology and assumptions as well as the results.

4.1.

M E T H O D O LO G Y : A M U LT I - R E G I O N
POWER SYSTEM MODEL

We developed a multi-region power system model using linear programming
techniques. Figure 40 presents a schematic diagram of this model. This model aims tominimise a single-year overall system cost, consisting of the annualised initial cost,
operation and maintenance (O&M) cost, fuel cost and carbon cost of the whole NEA,
under various technical and political constraints. Hence, the NEA economies are
assumed to fully cooperate to achieve the regional optimisation. The model considers
several power-generation technologies such as nuclear, coal-fired, gas-fired, oil-fired,hydro, solar photovoltaics (PV) and wind; pumped hydro storage as a storage facility;and High-voltage (HV) line/cable technology as transmission line technology. A
detailed mathematical description of the model is provided in Appendix A.1.
Validation of the model is discussed in Appendix A.2.
A capital recovery factor is used to annualise initial investments in generation,
storage and cross-border transmission facilities. The assumed discount rate is 3% andlifetime assumptions are discussed in Section 4.3.2 and 4.3.3. O&M cost includes both
fixed and variable O&M cost. Fixed O&M cost, which is incurred even if the plant was
not operated (i.e., landowner cost), is assumed to be in proportion to capacity, whilevariable O&M cost (i.e., consumables) varies with generated electricity. Carbon cost in
this study considers direct emissions from fuel combustions.
The cost of generation includes initial cost, fixed and variable O&M cost, fuel costand carbon cost. The cost of cross-border transmission lines includes initial cost and
9 Large parts of Section 4-5 and Appendix A.1-A.2 are revisions of the author’s journal article: ‘Electric

power grid interconnections in Northeast Asia: A quantitative analysis of opportunities and challenges’,
Takashi Otsuki, Aishah Binti Mohd Isa and Ralph D. Samuelson, Energy Policy Volume 89 pp.311-329(2016). This article will be published as an open access article (license: CC BY 4.0). APERC would like tosincerely thank Energy Policy (Elsevier journal) and four anonymous journal referees for their helpful
suggestions for improvements. Note that the results in this report are slightly different from the journal
article due to different model setups. For example, this report considers the Russia-Siberia node as a citynode (Figure 41), while the journal article considers it as a supply node.

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fixed O&M cost. Power trade is selected by its benefit (usually the savings in
generation cost) is larger than the cost of cross-border transmission lines.
Figure 40 Multi-region power system model, schematic diagram• Wind• Photovoltaics (PV)• Nuclear• Coal-fired• Gas-fired• Oil-fired• Hydro• Additional hydro 1• Additional hydro 2
Electricity imports
From other nodes

Electricity

Suppression control

Electricity

Electricity

Power gridElectricity load
(exogenous variable)

Electricity

Pumped hydroElectricity exports
To other nodes

Source: APERC analysis.

This model is formulated in a consistent way in the General Algebraic Modelling
System (GAMS) software. There are 75 thousand equations or constraints and 38
thousand endogenous variables. For our modelling work, we referred to the detailed
modelling approach in Schaber, et al. (2012), Komiyama & Fujii (2014) and Komiyama,
et al. (2015), but due to data availability we selected the temporal and geographicalresolution as explained below.
Regarding the temporal resolution, the model considers the hourly load curves oftypical days for five seasons (Summer-peak, Summer-average, Winter-peak, Winteraverage and intermediate) in order to model the diversity of seasonal and daily load
variation among the regions. Thus, in each node, one calendar year is decomposed
into 120 time segments (= 24 hours per day × 1 representative day per season × 5
seasons per year).
As for the geographical resolution, we divide NEA into ten nodes (Figure 41),
represented by eight city nodes (round markers) and two supply nodes (triangle
markers). City nodes have electricity demand and power supply facilities, while supply
nodes can have only power supply facilities to export electricity. Initial capacity ofsupply nodes are set to zero in this analysis, and endogenous capacity additions areallowed in both types of nodes. Six of the city nodes correspond to power grid or
power service areas: North China grid (CH-N); China Northeast grid (CH-NE); Japan
Hokkaido area (JP-H); Korea (KR); Russia Far East power system (RU-FE), and Russia
Siberia power system (RU-SI). The Tohoku and Tokyo areas in Japan are aggregatedas JP-E, and the western parts of Japan as JP-W. Supply nodes consist of the Gobi
Desert area in Mongolia (GD) and the Russia Sakhalin area (RU-SK), which haverelatively abundant energy potential (wind and solar in GD, and coal and gas in RUPAGE 53

M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

SK) compared to its electricity demand. Electricity demand in the supply nodes is
simplified in this analysis; however, we believe our model is detailed enough to reflect
the key drivers of costs and benefits of grid interconnections as market size of
Sakhalin and Mongolia are much smaller that Hokkaido area –the smallest modelledcity node– by a factor of nine to seventeen (Saneev & Sokolov, 2015; RAO Energy
System of East, 2015; HEPCO, 2015).
Figure 41 Regional division and assumed transmission distances
1070kmRussia-Siberia(RU-SI)
Russia-Far East
(RU-FE)3050kmRussia-Sakhalin(RU-SK)
870km

1130km
1400kmJapan-Hokkaido(JP-H)

China-Northeast(CH-NE)

Gobi Desert area
(GD)

1700km1340km1030km900km

China-North(CH-N)

750km

1200km

480km

Korea
(KR)

Japan-East(JP-E)

1200kmCity Node

Japan-West(JP-W)

Supply Node

Source: APERC analysis.

We modelled electricity transmission as a transport problem. Kirchhoff’s first law(conservation of current) is considered in each node of the network, but the secondlaw (voltage law) is not incorporated. This simplified approach allows us to keep the
optimisation problem linear and to optimise grid extensions, generation expansion
and operations simultaneously (Schaber, et al., 2012). Distances between nodes in
Figure 41 were based on airline distances between representative cities in eachregion plus 20% to allow for expected circuity (Google, 2015). Regarding thetransmission between KR and RU-FE, there are significant diplomatic challenges
involved in arranging transit across the DPRK. However, we take this route into
account as the Korea Energy Master Plan explicitly mentions that the connection“should be a prospective mid- to long-term governmental project” if it is profitableand overall conditions, including inter-Korean relations, improve (MOTIE, 2014).

4.2.

SCENARIO SETTINGS

We examine the five scenarios in Table 8. The simulated year in this study is 2030. The
Base scenario assumes no grid expansion from the existing transmission line capacity.
In the NoNewRE scenario, new interconnections are allowed based on total systemcost optimisation, but renewable capacity is fixed to the Base scenario assumptions at
all nodes. The RuHyd scenario endogenously allows additional hydro power
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development in the Russian nodes. As hydro power developments for Russian
domestic supply are already considered in the initial capacity settings in Figure 43, we
assume that the additional hydro plants are used only for exports to the foreign
nodes in this study. The Gobitec scenario attempts to quantify the costs and benefitsof the “Gobitec/ASG” concept proposed by Energy Charter et al. (2014) 10 . Theytargeted 50GW of wind and 50GW of solar PV in GD (the Gobi Desert) by 2030. The
last scenario (Gobitec+RuHyd) considers both the Gobitec and the RuHyd
assumptions. The assumed carbon price is 30 USD/t-CO2 for all scenarios. Further
explanations of the assumptions, including the limits for fossil fuel capacity additions
and additional hydro potential in Russia, are given in Section 4.3.
Table 8 Scenarios, definitions
Scenario

Base

NoNewRE

RuHyd

Gobitec

Gobite+RuHyd

Fossil fuel-

Cost optimised for all scenarios. For coal-fired plants, we impose upper bounds based

fired capacity

on the projected capacity in APERC (2013b), reflecting environmental concerns.

Wind/PV

Projected capacity for 2030 (APERC, 2013b)

capacity

Gobi Desert (GD): 50GW solar,
50GW wind (Energy Charter, etal., 2014). Other nodes: same as
Base scenario

Hydro

Projected capacity for

Endogenous additions

same as Basesame as RuHyd

capacity2030 (APERC, 2013b)

allowed in Russia nodes

scenario

scenariofor export (see Section
4.3.4). Other nodes:
same as Base scenario
Inter-

Current

connection

capacity

Cost optimised for the last four scenarios

Carbon price

30 USD/t-CO2 for all scenarios

Source: APERC analysis.
Note: PV=photovoltaic.

Kunstýř & Mano (2013) investigated the security risks for Japan of importing
electricity from Russia. They concluded that the power trade would not pose
substantial security risks for Japan with the appropriate measures, such as ensuring acapacity buffer at the current level. In general, each service area needs to be preparedfor cross-boundary transmission interruptions. Therefore we limit the share of net
transmission inflows at each city node to be less than the reserve margin level as
described in Equation (A.23) in Appendix A.1.

10 To our knowledge, they do not mention the reason for their choice of this level of capacity, but there

seems to be a consideration of energy security risk (Mano, 2014). The land area of 50GW solar PV
capacity would account for approximately 0.1% of the Gobi Desert area, assuming that total Gobi Desert
area is 1,300,000km2 and the land area required for solar PV cells is 20km2/GW (Eurus Energy, 2012).

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4.3.

I N P U T D ATA A S S U M P T I O N S

4.3.1. ELECTRICITY DEMAND AND LOAD CURVES
Our analysis considers the seasonal and diurnal characteristics of electric load in eachnode. We estimated electricity demand in 2030 from each node’s historical data
(JEPIC, 2013; The Government of Japan, 2014) and the projected growth rate from
APERC (2013b). We also constructed daily load curves for the five seasons fromavailable historical load curve information and load factor data (JEPIC, 2006; SO UPS,
2014; Nagayama, 2014; The Government of Japan, 2014). Figure 42 depicts theestimated daily load curves in the Summer-peak and Winter-peak seasons11. Notethat all the curves are plotted in Japan Standard Time. Time differences among themodelled city nodes are a maximum two hours12. Japan and Korea are located in thesame time zone. Compared to these two regions, China and Russia Siberia area
(Irkutsk time) is one hour behind, while Russia Far East area (Vladivostok time) is one
hour ahead. The peak load season varies by node; for example, the peak load season
is summer in JP-E and JP-W and winter in Russia nodes. The daily load curve in Japanis characterised as ‘mountain-shaped’ mainly due to daytime consumptions incommercial sector; by contrast, the daily load curve in Russia is relatively levelised but
it shows large seasonal variations due to due to heating demand in inter period.
Figure 42 Estimated daily load curve (ratio to peak load), city nodesa) Summer-peak
1b) Winter-peakRatio to peak load in each node1

0.8

Ratio to peak load in each node

0.8

0.6

0.6
CH-N, CH-NE
JP-H
JP-E
JP-W
KR
RU-FE
RU-SI

0.4
0.2

0

CH-N, CH-NE
JP-H
JP-E
JP-W
KR
RU-FE
RU-SI

0.4
0.2

0
0

2

4

6

8

10 12 14 16 18 20 22
Time of day (Japan Standard Time)

0

2

4

6

8

10 12 14 16 18 20 22
Time of day (Japan Standard Time)

Sources: JEPIC (2006), The Government of Japan (2014), SO UPS (2014).

11 Due to data availability, the same load curve is assumed for CH-N and CH-NE.
12 None of the modelled city nodes in China, Japan, Korea and Russia use daylight saving time (DST) as

of September 2015. Mongolia does use DST, but the wind and solar output curves in Figure 45~Figure
46, as well as all of our other calculations for the Gobi Desert (GD), are in Mongolia Standard Time, whichis the same as the time at the China nodes.

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4 . 3 . 2 . G E N E R AT I O N A N D S TO R A G E FA C I L I T I E S
C A PA C I T Y
The model is allowed to endogenously add fossil fuel-fired generation capacity in the
all scenarios. Capacities for nuclear, solar PV and wind are given exogenously in eachscenario. Hydro plant capacities are exogenous variables, except for RU-SI and RU-FE
in the Ruhyd and Gobitec+RuHyd scenarios. Assumptions for additional hydropotential for these nodes are discussed in Section 4.3.4. Figure 43 depicts initial
capacity settings for generation and storage facilities.
The initial capacity of fossil fuel-fired plants and pumped hydro are based on existing
capacities in 2011 (JEPIC, 2014a; Hippel, et al., 2011). For coal-fired plants, we impose
upper bounds based on the projected capacity in APERC (2013b), reflecting
environmental concerns. The initial capacity for renewables, except for GD (the Gobi
desert area), is estimated based on the projected capacity for 2030 in APERC (2013b)
as well as renewable energy potential (McElroy, et al., 2009; Energy and Environment
Council, 2011). For renewables in GD in the Gobitec and Gobitec+RuHyd scenarios, we
assumed 50GW of PV and 50GW of wind turbines (Energy Charter, et al., 2014). For
nuclear generation, we estimated the capacity in 2030 based on available information(JAIF, 2013; MOTIE, 2014).
Figure 43 Initial capacity assumptions
GW
300

Pumped Hydro
Hydro
PV
Wind
Oil
Gas
Coal
Nuclear

200

100

0
CN-NE

CH-N

JP-H

JP-E

JP-W

KR

RU-FE

RU-SI

Sources: METI (2013b), JAIF (2013), FEPC (2014b), Hippel, et al. (2011), JEPIC (2013).
Note: PV = photovoltaic.

CO S T S , E F F I C I EN C Y A N D AVA IL A B I L I T Y
Table 9 ~ Table 13 show the assumptions for generation and storage facilities. We set
the assumptions in a consistent way, comparing multiple sources from internationalorganisations, governments, industries as well as research institutes in order toensure the validity. Specifically, the initial costs data for 2030 are estimated from IEA
and individual economy analyses and projections (IEA, 2010; IEA, 2014a; METI, 2015c;
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Skoltech & ESI SB RAS, 2015). The future Initial cost of fossil fuel-fired plants andwind power remain similar to the current level, while solar PV shows drastic cost
reductions13. Annual fixed O&M cost [USD/kW/year] are estimated based on EIA(2013), IEA (2014a) and METI (2015c). For variable O&M cost (except fuel costs), in
Japan we assumed 2 USD/MWh for nuclear, 5 USD/MWh for coal-fired, 6 USD/MWh
for gas-fired and 4 USD/MWh for oil-fired plants (EIA, 2013; METI, 2015c). In otherregions, we adjusted the variable O&M cost using the ratio of initial cost between
Japan and each region. The carbon content of each fuel type is derived from EDMC
(2014). Assumptions for own-use of electricity at generating plants, ramp-up/downrate, minimum output level and conversion efficiency are taken from IEA (2014b;
2014c) and METI (2015c).
In considering the maximum availability for nuclear, fossil fuel-fired and hydrogeneration, we estimated the values using historical capacity and generation data
(JEPIC, 2013; EDMC, 2014; KESIS, 2015). We confirmed that the model reproduces
results similar to the actual power system (see Appendix A.2). As for wind and PV,
hourly output profiles are given exogenously. We estimated those output profiles for
GD (the Gobi Desert) as explained later in this section. Because of the limited
meteorological information available for some economies, the daily output profiles
for other areas rely on the following simple assumptions: the daily output profile forwind is kept flat at all time in all seasons assuming 20% capacity factor, and, for PV,
hourly output profiles in each season are assumed from the observed or estimatedprofiles in Zhao et al. (2009) and Shiraki et al. (2011). Also, please note that theoutput of hydro power is kept flat among the seasons (see equation (A.12)) assuming
40% capacity factor, and seasonal variation is not considered in this study.
Fossil fuel price assumptions in 2030 in Table 14 have been determined from the best
available projections (IEA, 2010; Shinoda, 2013; MUFJ, 2013; Morita, 2013; Ling, 2013;
KESIS, 2015). We based these estimates on historical CIF prices for energy importing
economies, historical FOB prices for exporting economies, and future import pricetrends from IEA WEO (2013). We conduct the simulations in Sections 4.4.1~4.4.5
under the fossil fuel price assumptions. However, the assumptions for future fuelprices include significant uncertainties given their past volatile nature over the last
decade. Therefore, we conducted a sensitivity analysis of future energy prices in
Section 4.4.6.

13 IEA (2014a) shows the projected initial cost in 2020 and 2035, and, for example, the initial cost of large

scale solar PV in China is projected to decrease by approximately 40% by 2035 compared to the 2012
level.

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Table 9 Assumptions for generation and storage facilities
Nuclear

Coal

Gas

Oil

Hydro

Wind

PV

PumpedLife time [year]

40

40

40

40

60

20

20

60

Carbon content

0

3.8

2.1

2.9

0

0

0

0

[t-CO2/toe]Own-use rate [%]

4

6

3

5

-

-

-

-

Maximum ramp-up

0

30

50

100

-

-

-

-

Capacity credit [%]

90

90

90

90

40

25

15

85

Minimum output

100

30

20

15

-

-

-

-

-

-

-

-

-

-

-

75

-

-

-

-

-

-

-

0.01

/ down rate [%/h]level [%]
Cycle efficiency(storage) [%]Self-discharge rate(storage) [%/hour]
Sources: EDMC (2014), IEA (2014b; 2014c), METI (2015c).

Table 10 Cost assumptions for North China (CN-N), China Northeast (SN-NE)
and the Gobi Desert area (GD)
Nuclear

Coal

Gas

Oil

Hydro

Wind

PV

PumpedInitial cost [USD/kW]

2 600

750

700

800

1 760

1 300

1 100

1 760

Fixed O&M cost

65

15

14

16

30

33

17

40

0.001

0.002

0.004

0.002

0

0

0

0

0.8

0.7

0.9

0.9

0.4

Estimated

0.8

-

0.40

0.50

0.37

-

[USD/kW/year]
Variable O&M cost
[USD/kWh]
Maximum
availability
Efficiency

output profile---(fossil fuel plants)
Sources: IEA (2010; 2014a; 2014b; 2014c), EIA (2013), JEPIC (2013).

Table 11 Cost assumptions for Japan nodes (JP-H, JP-E and JP-W)
Nuclear

Coal

Gas

Oil

Hydro

Wind

PV

PumpedInitial cost [USD/kW]

4 000

2 400

1 150

1 900

6 000

1 700

2 500

6 000

Fixed O&M cost

104

48

23

39

70

33

31

70

0.002

0.005

0.006

0.004

0

0

0

0

0.7

0.75

0.7

0.9

0.4

Estimated

0.8

-

0.42

0.5

0.37

-

[USD/kW/year]
Variable O&M cost
[USD/kWh]
Maximum
availability
Efficiency

output profile---(fossil fuel plants)
Sources: EIA (2013), IEA (2014a; 2014c), EDMC (2014), METI (2015c).
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Table 12 Cost assumptions for Korea (KR)
Nuclear

Coal

Gas

Oil

Hydro

Wind

PV

PumpedInitial cost [USD/kW]

3 300

1 500

800

1 900

2 500

1 600

2 250

2 500

Fixed O&M cost

86

30

16

39

30

40

34

30

0.002

0.003

0.005

0.004

0

0

0

0

0.95

0.9

0.9

0.9

0.4

Estimated

0.8[USD/kW/year]
Variable O&M cost
[USD/kWh]
Maximum
availability
Efficiency

output profile
-

0.40

0.50

0.37

-

-

-

-

(fossil fuel plants)
Sources: IEA (2010; 2014a; 2014b; 2014c), EIA (2013), KESIS (2015).

Table 13 Cost assumptions for Russia nodes (RU-FE, RU-SI and RU-SK)
Nuclear

Coal

Gas

Oil

Hydro

Wind

PV

PumpedInitial cost [USD/kW]

2 800

2 200

1 000

1 200

2 500

1 500

2 000

2 500

Fixed O&M cost

73

44

20

24

30

38

30

30

0.001

0.005

0.005

0.003

0

0

0

0

0.8

0.7

0.9

0.9

0.4

Estimated

0.8[USD/kW/year]
Variable O&M cost
[USD/kWh]
Maximum
availability
Efficiency

output profile
-

0.4

0.5

0.37

-

-

-

-

(fossil fuel plants)
Sources: EIA (2013), JEPIC (2013), IEA (2014a; 2014c), Skoltech & ESI SB RAS (2015).

Table 14 Fuel prices assumption
Coal [USD/t]

Gas [USD/MMBtu]

China

110.5

Russia

99.8

Japan

140.1

14.4

Korea

137.3

13.5

Oil [USD/bbl]

9.3
121.5

Sources: IEA (2010; 2013), Shinoda (2013), Ling (2013), MUFJ (2013), Morita (2013), KESIS (2015).

INTERMITTENT RENEWABLE ENERGY OUTPUT
PROFILES IN GOBI DESERT AREA
The seasonal profile of the region-wide wind output in GD is estimated by using
long-term wind observation data (Elliott, et al., 2001). We used a similar estimation
approach to Komiyama, et al. (2015). Figure 44 shows a flow chart for this calculation.
Elliott, et al. (2001) reports average hourly wind speed data in a day in each month atvarious sites. We selected five observation sites (Sainshand, Mandalgovi, Center
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Tuvshin Sukh, Tumurbaatar, and Center Manlai Ummu station), and estimated theweighted average wind speed of the Gobi Desert area. Next, we estimated theequivalent wind speed at the hub height of the wind turbines using the power law,assuming that the measured wind speed is at 10m and that the n-value in the powerlaw is eight (For discussion of the power law, see Peterson & Hennessey, Jr (1979)).
Then, we calculated the hourly wind turbine output profile (Figure 45) based on the
average hourly wind speed at hub height and a typical power curve.
Wind speed data in January is assumed for the winter season, in July for the summer
season. Wind speed in the intermediate season is estimated by averaging the data for
April and October. The assumption for the hub height of the wind turbine is 80m,
while the cut-in wind speed, rated speed, and cut-out wind speed are 5m/s, 12.5m/s
and 25m/s, respectively. The estimated average wind capacity factor is 26%. The data
in Elliott, et al. (2001) show the high wind speeds observed in the intermediate season(around April and October) in the Gobi area, and that trend is reflected in Figure 45.
Figure 44 Flow chart for the calculation of wind power output in the Gobi
Desert area (GD)
Wind speed data from
Elliott, et al. (2001)

Weighted average windspeed in Gobi Desert

Height of observation
point

Equivalent average windspeed at hub height

Hub height of windturbineWind output of
unit capacity

Power lawparameter

Performance curve ofwind turbine

Sources: Komiyama, et al. (2015) and APERC Analysis.

Figure 45 Assumed wind output profile, the Gobi Desert area (GD)

Wind output profile(ratio to installed capacity)

1

WinterSummer

0.8

Intermediate

0.6

0.4
0.2
0
0

6

12
18
Time of day (Mongolia Standard Time)

Source: APERC Analysis.
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As for the average solar PV output profile (Figure 46), we estimated by referring toBattushig et al. (2003) and Adiyabat et al. (2005). Battushig et al. (2003) reported theaverage hourly maximum power of PV modules in October, November, December,March and April in the Gobi desert area. PV output profiles depend on various
climatic conditions at the sites, such as sunshine duration, air mass and ambient
temperature. Because of limited information about detailed solar irradiation in thearea, we estimated output profiles by assuming that the observed output shape in
April in Battushig et al. (2003) is the representative diurnal variation in theintermediate and the summer season in the Gobi Desert area and that the shape in
December represents winter season. We then calculated the PV output profile in eachseason based on the shapes and the observed daily average PV energy output[Wh/day] in each season in Sainshand city in Mongolia (Adiyabat, et al., 2005).
Figure 46 Assumed Photovoltaics output profile, the Gobi desert area (GD)

PV output profile(ratio to installed capacity)

1

WinterSummer

0.8

Intermediate

0.6

0.4
0.2
0

0

6

12
18
Time of day (Mongolia Standard Time)

Source: APERC Analysis.
Note: PV = photovoltaic.

4.3.3. TRANSMISSION LINES
Costs of HVAC overhead lines are assumed for overhead interconnections, except for
the KR~RU-FE connection, where HVDC technology is proposed in governmental
publications (MOTIE, 2014). For undersea connections, HVDC cable technology isassumed. Regarding HVAC substation/switching stations, one substation/switchingstation is assumed to be installed for every 150km of HVAC overhead transmission
line to ensure grid stability. For HVDC connections, we assume AC-DC conversion
stations are installed at the each end of the connection. For the connection between
JP-E (50Hz) and JP-W (60Hz), BTB (Back-to-Back) facilities for frequency conversion
are considered. Also, BTB facilities are assumed to be installed between ChinaMongolia (the Gobi Desert), China-Russia and Russia-Mongolia (the Gobi Desert).
Therefore, this study assumes that each economy connected via DC lines/cables or
BTB for stable grid operation.

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We estimated transmission costs by drawing from Bahrman & Johnson (2007),
Schaber et al. (2012) and Matsuo, et al. (2015). We assume substation/switchingstation costs of 240M USD/station and AC-DC conversion station costs of
480M USD/station, all for stations of 3GW of transmission capacity. We also assume
1.2M USD/km for overhead lines (rated power: 3GW) and 7.2M USD/km for HVDC
submarine cables (rated power: 3GW). Assumed transmission distances are shown in
Figure 41. The linear programming model requires that interconnection capacity
costs be expressed as cost per unit of capacity14. We thus calculated the initial costfor each transmission route [USD/kW], as shown in Table 15. Assumed lifetime,transmission losses and annual fixed O&M cost are 40 years, 5%/1000km and 0.3% ina ratio to initial cost, respectively (Bahrman & Johnson, 2007; Matsuo, et al., 2015).
No capacity additions are allowed in the Base scenario (see Section 4.2), and we do
not constrain capacity additions in the other scenarios. Instead, the constraint on the
net imports to each city node (equation (A.26) in Appendix A.1) indirectly regulates
the maximum transmission capacity level.
Table 15 Initial cost assumptions for each interconnection route [USD/kW]
CH-N

CH-NE

JP-H

JP-E

JP-W

KR

RU-FE

RU-SI

RU-SK

GD

CH-N

-

700

-

-

-

1 992

-

-

-

1 000

CH-NE

700

-

-

-

-

-

1 520

-

-

1 416

JP-H

-

-

-

1 392

-

-

-

-

1 288

-

JP-E

-

-

1 392

-

672

-

-

-

-

-

JP-W

-

-

-

672

-

1 840

-

-

-

-

KR

1 992

-

-

-

1 840

-

1 560

-

-

-

RU-FE

-

1 520

-

-

-

1 560

-

-

1 548

3 060

RU-SI

-

-

-

-

-

-

-

-

-

1 252

-

-

1 288

-

-

-

1 548

-

-

-

1 000

1 416

-

-

-

-

3 060

1 252

-

-

RU-SK
GD

Source: APERC analysis.
Note: ‘-’ indicates that new interconnections are not allowed in this study.

4.3.4. ADDITIONAL HYDRO POW ER POTENTIAL IN
RUSSIAThe assumptions for the additional hydro potential in Russia are based on estimatesby the European Bank for Reconstruction and Development (from IEA (2003)).
According to IEA (2003), ‘economically feasible hydropower capability’ in East Siberia
and in the Far East is 350TWh/year and 294TWh/year, respectively. These regions

14 Thus, the LP model does not explicitly consider the number of transmission units nor the size of each

unit. In order to explicitly take into account the scale of initial investments for each unit of transmission
technology, it should be considered as a future work to develop an integer programming model.

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account for 81% of the total potential in Russia. However, as shown in Figure 47,hydro resources are widely distributed in the Far East region, which consists of the Far
East (or federal) power grid area, the autonomous power grid area and the nonelectrified area (IEA, 2003). Similarly, hydro potential in East Siberia is widelydistributed from the south border region to the northern part of the region. Only
limited parts of the Far East and East Siberia regions have been connected to federal
grid (Popel, 2012). Therefore, we made a simple assumption that one third of theeconomical hydro potential of the Far East and Siberia is accessible in practice.
Figure 47 Geographical distributions of hydro energy resources, Russia

ScoresScore

Source: Practical Science (2014).

We estimated additional hydro potential on a gigawatt-basis using the assumed‘accessible potential’ (on a terawatt-hours basis), capacity factor (40%) andsubtracting-off existing capacity (already exploited resources). We equally divided thetotal additional potential into two categories (Add-Hydro1, Add-Hydro2) assummarised in Table 16. The initial costs of hydro power potential depend on its
geographical location, and in general, undeveloped resources are more expensive
than already exploited resources. Thus, this study assumes a higher initial cost for the
additional hydro resources compared to the already exploited resources. Add-Hyd1 isassumed to be more expensive than the average cost of already exploited resources(Table 10) by 25% and Add-Hyd2 is assumed to be more expensive by 50%.
Table 16 Assumptions for additional hydro power plants
Additional hydro potential [GW]

Initial cost

RU-FE

RU-SI

[USD/kW]

Additional hydro 1 (Add-hyd 1)

13

5

3125

Additional hydro 2 (Add-hyd 2)

13

5

3750

Source: APERC analysis.
Note: average cost in Russian hydro power plants is assumed as 2500 USD/kW.
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However, it is important to note again that initial investments for hydro power plants
differ greatly site by site and this uncertainty could affect the results presented in the
Section 4.4.1 ~ 4.4.5. This study, thus, performs an additional analysis considering
different sets of cost assumptions, including initial costs of hydro generation in Russia,
in Section 4.4.6.

4.3.5. RESERVE MARGIN
As our study focuses on hourly dispatch, we assumed operating reserve margins inequation (A.22) in Appendix A.1 as follows: 10% for China, Japan and Korea and 15%
for Russia referring to general criteria and/or historical data (FEPC (2014b) for Japan,
KPX (2015) for Korea and SO UPS (2014b) for Russia. As for the China nodes, we
assumed a level similar to Japan and Korea, due to limited data availability).

4.4.

S I M U L AT I O N R E S U LT S

4 . 4 . 1 . G E N E R AT I O NCoal-fired generation remains the dominant source in this region even under the
Gobitec+RuHyd scenario (Figure 48a)). In the Base scenario, coal-fired electricity
accounts for 61% of total generation, and it increases to 63% in the NoNewRE
scenario. This is because grid interconnection allows high electricity cost regions (likeJapan and Korea) to access cheaper coal electricity from China and Russia. The
NoNewRE scenario in Figure 48b) shows coal-fired generation in the China nodes andRussia Sakhalin (RU-SK) replace gas-fired generation in Japan (JP-H, JP-E and JP-W)
and Korea (KR). This result implies that cost optimal grid interconnections without
newly expanding renewable energy potentially increases coal-fired generation in
China and Russia. This situation might be undesirable especially for China, which issuffering from severe air pollution.
Figure 48 Power generation in Northeast Asia and changes from Base scenarioa) Power generationb) Changes from Base scenario

TWh

TWh

5 000

400

Add-Hyd 1 & 2
Hydro
PV
Wind
Oil
Gas
Coal
Nuclear

4 000
3 000
2 000
1 000

Coal (CH-N & CH-NE)
Coal (RU-SK)
Gas (JP-H & JP-E)
Gas (JP-W)
Gas (KR)
Add-Hyd1 & 2 (RU-FE)
Wind (GD)
PV (GD)
Other
Transmission Loss

200

0

-200

Gobitec+RuHydGobitec

RuHyd

NoNew
RE

Gobitec+RuHydGobitec

RuHyd

NoNew
RE

Base

Base

-400

0

Note: PV = photovoltaic; Add-Hyd1 & 2= additional hydro-1 and additional hydro-2.
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Deployments of renewables in Eastern Russia and the Gobi Desert contribute to an
environmentally-friendly generation mix in NEA (Figure 48a)). Renewables account for
12% of power generation both in the Base and the NoNewRE scenario, and increase
to 14%, 16% and 18% in the last three scenarios, respectively. In the RuHyd scenario,
additional hydro generation in Eastern Russia, instead of coal-fired generation in CHN, replaces gas-fired generation in JP-W and KR (Figure 48b)). Yet, China still exports
coal-fired generation as Japan and Korea have room for further imports. In the lasttwo scenarios, gas-fired generation in Japan and Korea as well as coal-fired
generation in CH-N are replaced by renewable electricity from GD (the Gobi Desert)
or Eastern Russia. The gap between the incremental generation and the generation
decreases elsewhere represent cross-boundary transmission losses. Relatively large
share of transmitted electricity is lost through long distance transmission; for example,
transmission losses reach 15% and 11% in the last two scenarios, respectively.
Electricity trade is very limited in the Base scenario, and, in the NoNewRE scenario, net
imports increases in Japan nodes and Korea node (Figure 49). The share of net
imports in JP-H (Japan Hokkaido area) and JP-E (the eastern parts of Japan) reaches
to 8.5% and 6.5% of annual demand, respectively. These regions import from the
newly installed fossil fuel fired coal plants in Sakhalin (RU-SK) with a capacity of 3GW.
JP-E also imports from China via KR and JP-W as well (see also Section 4.4.3). As
noted in Section 2.2, the model limits net transmission inflows to each city node to
the reserve margin at all times, reflecting a likely concern over secure electricity
supply (see Equation (A.26) in Appendix A.1). These reserve margins are assumed tobe 10% for China, Japan and Korea and 15% for Russia. In JP-W and KR, the net
imports almost reach this upper bound on average. The main exporter to these nodes
is China (see also Section 4.4.3).
In the RuHyd scenario, large scale hydro developments in RU-FE allow KR, JP-W and
JP-E to import the hydroelectricity from Russia instead of fossil fuel-fired electricity
from China or Russia. The net imports share in these importing nodes remains similarin level to the NoNewRE scenario; Japan and Korea nodes remains as the main
importers. The ‘Gobi electricity’ in the Gobitec scenario increases the imports share in
CH-NE to 1.9%, which contributes to reducing coal-fired generation in the China. In
the Gobitec+RuHyd scenario, the annual imports of the two China nodes amount
82TWh/y (net imports share: 4% in CH-N and 3% in CH-NE), resulting in further
reductions of coal generation in China (see also Figure 48b)). Our model calculates
electricity flow based on cost-optimisation; therefore, higher cost electricity isreplaced first by cheaper transmitted electricity. China starts large-scale imports inthe last scenario as the net imports share almost reaches the upper bound level inhigher cost nodes (not only JP-W and KR but also JP-E). This result implies that, fromthe economic standpoints, massive deployments of renewables both in NEA arenecessarily to largely reduce cheap but carbon-intensive coal generation in China.

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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

Figure 49 Power-generation mix and net imports by node

Net imports share[%]

GD

RU-SI

JP-E

RU-SK

-5

KR

- 400

RU-FE

0

SupplyNodeHydro(total)
Wind
Gas
Nuclear
Net imports share(right axis)

20
15
10

City
Node

GD

CH-N

Supply
Node

RU-SI

-5

RU-SK

- 400

KR

0

RU-FE

0

JP-E

5

JP-W

400

Net imports share[%]

800

GD

RU-SI

City
Node

RU-SK

-5

KR

- 400

RU-FE

0

JP-E

0

JP-W

5

1 200

JP-H

10

Net Imports
PV
Oil
Coal

1 600

CH-NE

15

400

JP-H

10

0

CH-N
20

Net imports share(right axis)

CH-NE

15

5

City
Node

Net imports share[%]Hydro(total)
Wind
Gas
Nuclear

800

CH-N

Generated electricity [TWh]20d) Gobitec scenario
Net Imports
PV
Oil
Coal

1 200

Net imports share(right axis)

SupplyNodec) RuHyd scenario
1 600

Hydro(total)
Wind
Gas
Nuclear

400

GD

RU-SI

City
Node

RU-SK

KR

-5

RU-FE

- 400

JP-E

0

JP-W

0

JP-H

5

CH-NE

400

800

JP-W

10

1 200

JP-H

Net imports share(right axis)

Net Imports
PV
Oil
Coal

1 600

CH-NE

800

15

Generated electricity [TWh]

1 200

20

Generated electricity [TWh]1 600

Hydro(total)
Wind
Gas
Nuclear

Net imports share[%]b) NoNewRE scenario
Net Imports
PV
Oil
Coal

CH-N

Generated electricity [TWh]a) Base scenario

Supply
Node

1 200
800

Hydro(total)
Wind
Gas
Nuclear
Net imports share(right axis)

20
15
10

City
Node

GD

RU-SK

RU-SI

RU-FE

-5

KR

- 400

JP-W

0

JP-E

0

JP-H

5

CH-NE

400

Net imports share[%]Net Imports
PV
Oil
Coal

1 600

CH-N

Generated electricity [TWh]e) Gobitec+RuHyd scenario

SupplyNode

Note: PV = photovoltaic. Note: ‘Net Imports’ in the figures indicates ‘Net Imported Electricity’ for apositive value and ‘Net Exported Electricity’ for a negative value. ‘Hydro (total)’ indicates a sum of‘Hydro’, ‘Additional hydro-1’ and ‘Additional hydro-2’.

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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

4.4.2. CO2 EMISSIONS
Figure 50 displays direct CO2 emissions in NEA from fossil fuel combustion. Larger
coal-fired generation in the NoNewRE scenario results in higher emissions by 64MtCO2 (+2.3%) compared to the Base scenario. This result implies that interconnection
without renewable resource expansion could increase CO2 emissions in NEA, which is
not desirable from the environmental perspectives. In the RuHyd scenario, additionalhydro developments in Eastern Russia slightly reduce the emissions by 0.4Mt-CO2(-0.01%). In the Gobitec and Gobitec+RuHyd scenarios, Gobi electricity or Gobi
electricity + hydro in Eastern Russia contribute to emissions reductions of about
84Mt-CO2 (-3.0%) and 149Mt-CO2 (-5.3%), respectively. These last two scenarios
result in larger reductions as the massive renewable deployments replace carbonintensive coal-fired electricity in China (see Figure 48b)). The modest benefit toemissions in the RuHyd scenario is because the emissions from exported coal-fired
generation in China (Figure 48b)) partly offset the reductions from hydro in Russia.
Figure 50 Direct CO2 emissions, Northeast Asia

2.80

2.71

2.65

(+2.3%)(-0.01%)(-3.0%)(-5.3%)

Gobitec

Gobitec+RuHyd

2.80

RuHyd

3

NoNew
RE

Gt-CO2
2.86

2

1

Base

0

Source: APERC analysis.

The CO2 reduction in the Gobitec scenario that we calculate (84Mt-CO2) is lower thanthat from Energy Charter, et al. (2014) (187Mt-CO2). (Please note that Energy Charter
et al. (2014) mentioned a 187Gt-CO2 reduction, but we suspect the units were
misstated.) The CO2 reduction differences are partly because of two factors. First, in
Energy Charter, et al. (2014), the assumptions for utilization factor for both PV andwind are 30%, which are much higher than our estimates (20% for PV and 26% forwind). Second, the two models use a substantially different dispatch logic for Gobi
electricity. Energy Charter, et al. (2014) assumed that 80% of Gobi electricity is sent tocoal-intensive (high CO2 emissions per kWh) China, and they use average emissions
factors in each importing region to estimate CO2 emission reductions. On the other
hand, our model determines the share of Gobi electricity at each importing node
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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

based on total system cost minimization. Thus, as shown in Figure 48b), the increase
in Gobi electricity results in reducing high cost gas-fired generation (with relatively
low CO2 emissions per kWh) in Japan and Korea.

4.4.3. ELECTRICIT Y FLOW
Figure 51a)-e) indicates cross-boundary electricity flows [terawatt-hours/year(TWh/y)] and transmission capacity [Gigawatt (GW)]. The Base scenario shows aninternational power trade only between Russia Far East (RU-FE) and Northeast China(CH-NE).
In the NoNewRE scenario, China and Russia export to Japan and Korea because of
low-cost electricity. Korea becomes a net importing economy as well as playing therole of a transit (“bridge”) economy between China/Russia and Japan. The economy
imports 139TWh/y from China, and exports to 73TWh/y to Japan. Transmission line
capacity of the China-Korea and Korea-Japan interconnections are 22GW and 12GW,
respectively, which are equivalent to 18% and 10% to the total installed capacity of
Korea. The figure also shows the newly added interconnections from Russia Sakhalin
to the eastern parts of Japan via Hokkaido (JP-H); however, the transmission capacityfrom the ‘mainland’ Russia Far East region (RU-FE) to Japan and Korea is relatively
small compared to the aforementioned connections. The limited transmission scale isprobably because of the higher transmission cost associated with the longer
transmission distances.
On the other hand, in the RuHyd scenario, RU-FE becomes a major exporter to Japanand Korea. The majority of the additional hydroelectricity in RU-FE is transmitted toKR (82TWh/y). The Gobitec scenario shows the large-scale cross-border electricity
flow from the Gobi Desert area to Korea and Japan. Transmission lines with a capacityof 100GW are installed from GD (the Gobi Desert) to match the capacity of thevariable renewables there. Yet the utilization rate of these connections, i.e., 22% in the
GD~CH-N connection, is relatively low because of the intermittency of thetransmitted power. In the Gobitec+RuHyd scenario, transmitted electricity from China
to Korea decreases compared to the Gobitec scenario because Korea imports powerfrom Russia rather than China. Instead, China consumes more of the Gobi Desert
electricity, resulting in lower fossil fuel-fired generation in the China nodes.
Electric utilities and transmission companies in Russia, in cooperation withorganizations in neighbouring economies, have been exploring the possibilities ofcross-border grid interconnection (Smirnov, 2012; Inter RAO, 2013). Our results
indicate that exporting fossil fuel-fired electricity from Sakhalin to Japan could be an
economic option. By contrast, the scale of connections from Eastern Russia isrelatively small in the NoNewRE and Gobitec scenarios, and it greatly expands under
the RuHyd and Gobitec+RuHyd scenarios in order to export additional hydro power.
The results imply that additional hydro power can stimulate opportunities forelectricity trade between the ‘mainland’ Russia and other regions.

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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

Figure 51 Annual electricity flows, each scenario, Northeast Asiaa) Base scenariob) NoNewRE scenario

Net electricity flow [TWh/y]Net electricity flow [TWh/y]Transmission capacity [GW]

Transmission capacity [GW]

0.4
(1.2)
1.6
(2.6)

0 – 10

6(4)

20 – 30

20 – 30

0.8(3.1)

40 – 50

30 – 40
50 – 100

100 ~

100 ~

c) RuHyd scenario

Net electricity flow [TWh/y]

3
(0.6)

Transmission capacity [GW]

8
(1.4)

4
(0.9)

82
(13)

TWh/year0 – 10

4
(4)

18
(13)

TWh/year0 – 10

170
(87)

1.4
(3.8)

20 – 30

89
(15)

4.1
(0.8)

0.5
(1.2)

10 – 20

75
(13)

2.1
(0.5)

Transmission capacity [GW]

0.8
(1.2)

40 – 5014(3)d) Gobitec scenario

Net electricity flow [TWh/y]30 – 40

73
(12)

139
(22)

40 – 50

50 – 100

20 – 30

0.2(4)

10 – 20

30 – 40

16
(2.6)

0.9
(0.4)

TWh/year0 – 10
10 – 20

21
(3)

0.4
(1.2)

TWh/year

10 – 20

2.4
(0.5)

29
(5)

30 – 40171(29)

40 – 50

50 – 100

50 – 100

100 ~

100 ~

1.1
(0.9)

102
(18)

42
(7)

e) Gobitec+RuHyd scenario
Net electricity flow [TWh/y]

5
(0.8)

Transmission capacity [GW]

4
(0.8)

0.9
(1.2)

TWh/year0 – 10
10 – 20

20 – 30
30 – 40
40 – 50

25
(14)

154
(86)

4
(4)
92
(17)

1.1
(0.9)

81
(13)

103
(18)

43
(7)

50 – 100
100 ~Source: APERC analysis.

4 . 4 . 4 . TOTA L C O S T S A N D I N V E S T M E N T S
Figure 52 depicts yearly total system cost and its changes from the Base scenario. The
costs shown include a carbon cost of 30 USD/t-CO2 (see Table 8). The total systemcost declines by 2.3B USD/y, 5.1B USD/y, 0.7B USD/y, and 2.7B USD/y from the Basein the NoNewRE, RuHyd, Gobitec, and Gobitec+RuHyd scenarios, respectively. These
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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

values are equivalent to 0.2%~1.2% reductions; therefore, the impacts ofinterconnection on total system cost appear to be modest in this analysis. The
annualized share of initial cost of cross-boundary transmission to total system cost is
relatively small, e.g., 2.2% in the Gobitec+RuHyd scenario.
However, grid interconnection affects some components of the total system costmore significantly. As shown in the last three scenarios in Figure 52b), while
deployment of renewables in Gobi and Eastern Russia and transmission lines havesignificant initial costs, renewable resource expansion contributes to fuel cost
reductions in the NEA region of about 6% (-11B USD/y), 8% (-16B USD/y) and 10% (20B USD/y) in the last three scenarios, respectively. These results imply two points asfollows: first, the benefits of renewable electricity trade mainly depend on fuel cost
reductions; second, the main costs which make the power trade and renewable
expansion less attractive are the initial costs of renewables and transmission lines.
Figure 52 Yearly total system costs and changes from Base scenario, NortheastAsiaa) Yearly system costsb) Changes from Base scenario

Billion USD/year

Billion USD/year
30

400

Carbon
Costs

300

Initial Costs(transmission line)

100

Initial Costs(power plant, storage)

Initial Costs(power plant, storage)
Fuel Costs-10

Total Cost Changes-20

Carbon Costs
Gobitec+RuHydGobitec

RuHyd

NoNew
RE

Gobitec+RuHyd-30
Gobitec

RuHyd

NoNew
RE

0

O&M Costs

10

0

O&M
Costs

Base

20

Base

200

Fuel
Costs

Initial Costs(transmission line)

Source: APERC analysis.
Note: O&M = Operation and Maintenance.

Large fuel cost savings are estimated in the importing regions, especially in the last
scenario: 3B USD/y, 11B USD/y and 6B USD/y in the China nodes, Japan and Korea,
respectively, which are equivalent to 4%, 15% and 23% reductions. Nevertheless,these results rely on the future cost assumptions in Section 4.3.2. In order toinvestigate the impact of future cost uncertainties on the economics of gridinterconnection, we perform a sensitivity analysis on the assumptions for fuel cost
and the initial cost of transmission lines and renewable energy in Section 4.4.6.

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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

Huge investments are necessary for grid interconnection and massive deployments ofrenewables (Figure 53). Compared to the Base scenario, additional investments
amount 60B USD, 150B USD, 300B USD and 390B USD in the NoNewRE ~Gobitec+RuHyd scenario, respectively. Estimated yearly total costs of Japan plus
Korea (Base scenario) is approximately 190B USD/year; therefore, the total
investments in the Gobitec+RuHyd scenario are more than doubled yearly costs ofthe two economies. As mentioned above, economic benefits in the form of cost
reductions appear to be modest. Given the large scale investments are required forthe concept, the NEA-wide interconnections may face an implementation challenges
due to financing issues (i.e., who can and how to finance). Our analysis of course
includes simplifications especially in terms of temporal and geographical resolution.
The relevant organisations should examine the return on investments in a moredetailed manner (i.e., assessment of specific interconnection routes considering local
power grid characteristics) before implementation.
Figure 53 Additional investments from Base scenario, Northeast Asia
Billion USD

500

PV and wind
(GD)

400

Add-Hyd 1 & 2(RU-FE, RU-SI)

300

Transmission lines
200
Other

100
0
Gobitec+RuHydGobitec

RuHyd

NoNew
RE

Base

-100

Source: APERC analysis.

4 . 4 . 5 . M A R G I N A L G E N E R AT I O N C O S T S
The dual solution to equation (A.7) in Appendix A.1 indicates the marginal costs ofelectricity generation, which are determined by the variable cost of generation,
storage, and transmission. The marginal costs are important indicators of theelectricity price level (IES, 2004; Schaber, et al., 2012). Figure 54 shows the power
generation profile and marginal generation costs in the winter peak season in JP-H in
the Base and NoNewRE scenarios as an example. A comparison of the two figuresindicates that power imports reduce gas-fired generation and contribute to alowering of marginal costs, especially during daytime (around 9:00~11:00 and 13:00~20:00). For example, at around 14:00, the marginal costs drop from 0.18 USD/kWhin the Base scenario to 0.12 USD/kWh in the NoNewRE scenario.

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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

Figure 54 Power-generation profile and marginal generation costs, winterseason, Japan Hokkaido node (JP-H)a) Baseb) NoNewRE

GW
8
7

Marginal costs (right axis)
Electricity demandGas-fired

6

0.2

8

3

Coal-fired

2

Hydro
Wind

1

0

2

4

5

4

0.1

Net imports

0.1

10 12 14 16 18 20 22

0

3
2
1

Nuclear0

0.2

6
Net imports
Pumped (discharge)

4

USD/kWh
Marginal costs (right axis)

7
PV

5

-1

GW

USD/kWh

Pumped (charge)

6

8

0

10 12 14 16 18 20 22

0Time of day (Japan time)

-1

0

2

4

6

8

Time of day (Japan time)

Source: APERC analysis.

Figure 55 Average marginal generation costs
USD/kWh
0.14
Weighted average of JP-E & JP-W
0.12

JP-H

Korea
0.1
Weighted average of RU-FE & RU-SI
0.08
Weighted average of CH-N & CH-NE

Gobitec+RuHydGobitec

RuHyd

NoNew
RE

Base

0.06

Source: APERC analysis.

Figure 55 presents the average marginal generation costs in the city nodes for the five
scenarios. For the China nodes and the Japan nodes (except JP-H), the figure shows
weighted average values. The average marginal costs varies from economy to economy
in NEA; it ranges from 0.075 USD/kWh in the China nodes to 0.107 USD/kWh in Korea
and 0.137 USD/kWh in Japan (except JP-H) in the Base scenario. Our model dispatches
generation with the lowest variable cost first; therefore, marginal generation cost

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M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

increases with larger electricity demand. As grid integration decreases net-demand15 ofimporting regions, the average marginal costs lowers in in electricity importing regions(and vice versa. See CH-N in the NoNewRE scenario in Figure 55 and marginal costs
from 11:00~21:00 in Figure 56). The Japan Hokkaido area (JP-H) and Korea (KR) show
relatively large reductions as the power imports significantly decrease or almost replacehigh-marginal cost generation, such as oil-fired and gas-fired generation, as shown in
Figure 49 and Figure 54. In the NoNewRE, the average marginal costs drops by 0.014
USD/kWh in JP-H and by 0.003 USD/kWh in Korea, which are equivalent to 11% and
3% reductions, respectively. As for the last three scenarios, the average marginal costs
in both regions remain at a similar level to the NoNewRE scenario.
Figure 56 Power-generation profile and marginal generation costs, winter peakseason, China North node (CH-N)a) Baseb) NoNewRE

GW

USD/kWh

GW

250

0.2

250

Electricity demand200

USD/kWh
0.2

Electricity demand200

Gas-fired
Marginal costs (right axis)

150

150

Coal-fired100

Coal-fired

0.1

50

0

Marginal costs (right axis)

100
50

Wind
Nuclear
0 2 4 60.1
Net imports

0
8 10 12 14 16 18 20 22-50Time of day (China time)

0
0

-50

2

4

6

8 10 12 14 16 18 20 22

Time of day (Chinal time)

Source: APERC analysis.

The Japan nodes, except JP-H, show small changes in average marginal generation
costs as the share of high marginal cost generation is relatively large compared to JPH, and the limited imports (which must be kept less than the reserve margin) are notenough to eliminate them (see Figure 57). After the nuclear power plant accident inJapan, electric utilities across the economy raised residential electricity prices by
13~37% (from March 2011 to July 2014) primarily because of additional fuel costs(NHK, 2014), and proposals for grid interconnection received increasing attention in
Japan as one of the potentially effective measures for lowering prices. Our results
indicate that parts of Japan would locally enjoy lowered prices from gridinterconnections. Yet, in Japan as a whole, even with the accelerated renewable
developments, the price reductions would be relatively small compared to theincreases after the nuclear accident, at least as long as imports are constrained due toenergy security concerns.
15 Domestic demand minus net imports.

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Figure 57 Power-generation profile and marginal generation costs, summer
peak season, Japan West node (JP-W)a) Baseb) Gobitec+RuHyd

GW

USD/kWh

GW

120

0.3

120

100

Marginal costs (right axis)
Electricity demand

Pumped (discharge)

PV
Oil-fired

80

0.2

0.3

Marginal costs (right axis)
Net imports

100

60

80

0.2

60

40

40

0.1

Coal-fired
Hydro
Nuclear
0

20-20

USD/kWh

0

2

4

Pumped (charge)
6

8 10 12 14 16 18 20 22

Time of day (Japan time)

0.1

20
0

0

-20

0

2

4

6

8 10 12 14 16 18 20 22

Time of day (Japan time)

Source: APERC analysis.

4 . 4 . 6 . S E N S I T I V I T Y A N A LY S I S
Figure 52b) suggested that the benefits achieved by interconnecting power grids andpromoting trade in renewable electricity depend mainly on fuel cost savings, and thathigher initial cost of renewables and transmission lines makes regional
interconnections less attractive. Also, uncertainties exist in future environmental
policies and regulations, including carbon prices. Therefore, in this section, we
conduct a sensitivity analysis on these three factors to investigate their impacts on
the economics of grid interconnection. We calculated one hundred-fifty cases total as
shown in Table 17: two installed capacity settings (generation, storage andtransmission capacity are fixed to the Base or Gobitec+RuHyd scenario result) × threecarbon prices (No carbon price, 30USD/t-CO2 (=”Ref.”), 100USD/t-CO2) × five fossil
fuel prices (-20%, -10%, 0% (=”Ref.”), +10%, +20% from Table 14) × five initial costsof renewable energy in the Gobi Desert and Russia and all transmission lines (-20%, 10%, 0% (=”Ref.”), +10%, +20%). Other assumptions are the same as shown in Table 9~ Table 13.
Figure 58 illustrates the economic benefits of the Gobi+RuHyd scenario in each case(total system cost reductions from the Base). The results show improved economic
viability of grid interconnections under lower initial cost, higher fossil fuel prices orhigher carbon prices. For example, the benefit increases to 12B USD/y in the +20%
fossil fuel price and -20% initial cost case under 30USD/t-CO2 carbon price (thisbenefit is approximately equivalent to a 3% total cost saving). Also, the benefit
expands to 24B USD/y with a carbon price of 100USD/t-CO2. On the other hand, theresults also suggest the benefit would shrink or become negative with 10~20% lower
fuel prices and higher initial costs under 30USD/t-CO2. In ‘no carbon price’ case,economic benefits become negative (-2B USD/y) even under the reference fuel prices
and initial costs.
PAGE 750M O D E L L IN G A N D A N A L YS IS O F G R ID I N T E R C O N N E C T IO N S

Table 17 Case settings of sensitivity analysis (150 cases total)
Case settings
Installed capacity settings of generation, storage andFixed to the Base or Gobitec+RuHyd scenariotransmission facilities

resultCarbon prices

No carbon price, 30USD/t-CO2, 100USD/t-CO2

Initial cost changes for renewables (the Gobi Desert-20%, -10%, 0% (=’Ref.’), +10%, +20%

and Russia) and transmission lines
Fossil fuel price changes from Table 14-20%, -10%, 0% (=’Ref.’), +10%, +20%

Source: APERC analysis.

Figure 58 Economic benefits of the Gobi+RuHyd scenario in each casea) No carbon priceb) 30USD/t-CO2 (‘Ref’)c) 100USD/t-CO2

Unit: Billion USD/year

Unit: Billion USD/year

Unit: Billion USD/year

5

2

0

-2

12

9

7

4

2

22

20

17

15

12

+20%

5

3

0

-2

-4

10

7

5

2

0

20

18

16

13

11

+10%

3

1

-2

-4

-6

8

5

3

0

-2

19

16

14

11

9

Ref.

1

-1

-4

-6

-8

6

3

1

-2

-4

17

15

12

10

7

-10%

-1

-3

-6

-8

-10

4

1

-1

-4

-6

15

13

11

8

6

-20%

-20%

-10%

Ref.

+10%

+20%

-20%

-10%

Ref.

+10%

+20%

-20%

-10%

Ref.

+10%

+20%

Initial costs(renewables in Gobi and Russia
and transmission lines)

Initial costs(renewables in Gobi and Russia
and transmission lines)

Fossil fuel prices

7

Initial costs(renewables in Gobi and Russia
and transmission lines)

Source: APERC analysis.

In Section 4.4.1 ~ 4.4.5, we assumed estimated initial costs of renewables andtransmission lines in 2030 based on IEA (2014a), Bahrman & Johnson (2007) and soon. However, these costs, especially for hydro generation and transmission lines,
depend on site-specific characteristics. Also, IEA (2014a) assumes learning rates which
reduce the future initial costs of renewables, yet uncertainties exist in these cost
reduction trends. Similarly, energy prices have shown their volatile nature in the past
decade, and the NEA region does not have a regional carbon market nor carbon
reduction regulations. The relevant planning organizations should carefully assess theactual initial costs and long-term fossil fuel price trends, bearing in mind theirsignificance, as indicated Figure 58. In addition, given the benefits expand underhigher carbon prices, Regional carbon market and emission reduction agreements
are important for implementing power grid interconnections and expanding
renewable energy for export.

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C O N CL U S IO N S A N D P O L IC Y I M P L I CA T I O N S

5. C O N C L U S I O N S A N D P O L I C Y
I M P L I C AT I O N SThis research report summarises overview of the power grids and gridinterconnection proposals in major NEA economies (Section 2 and 3), where wehighlighted the need for coordination by international/regional organisations for a
detailed blueprint and for effective implementations. Section 4 is the main content of
this study: a quantitative assessment of the economic viability of gridinterconnections in NEA and renewable energy developments in the Gobi Desert andEastern Russia.
In Section 4, we develop a single-year multi-region power system model. The model
is formulated as a linear program, which aims to minimize overall system cost. The
model considers nodal electric load characteristics, including representative hourly
load curves, as well as the output profile of variable renewables in the Gobi Desert.
We validated our model capability using historical data (see Appendix A.2).
We investigated five scenarios for the NEA power system of 2030: Base, NoNewRE,
RuHyd, Gobitec and Gobitec+RuHyd scenarios (see Table 8). Major results in eachscenario are summarized in Table 18. These simulation results lead us to several
interesting findings as follows.
Table 18 Summary of the simulation results of each scenario
Scenario

Base

NoNewRE

RuHyd

Gobitec

Gobitec+RuHydAnnual total cost

417B USD/y414B USD/y412B USD/y416B USD/y414B USD/yInitial costs

84B USD/y87B USD/y90B USD/y

100B USD/y103B USD/yFuel costs

197B USD/y190B USD/y185B USD/y181B USD/y177B USD/yAnnual CO2 emissions

2.80 Gt-CO2

2.86 Gt-CO22.80 Gt-CO2

2.71 Gt-CO22.65 Gt-CO2

61%

63%

62%

60%

59%

12%

12%

14%

16%

18%

Share of coal-fired
generation in NEA
Share of renewables
in NEA

Source: APERC analysis.
Note: Due to different model setups, the results in this report are slightly different from the author’s
journal article: ‘ Electric power grid interconnections in Northeast Asia: A quantitative analysis ofopportunities and challenges’, Takashi Otsuki, Aishah Binti Mohd Isa and Ralph D. Samuelson, Energy
Policy Volume 89 pp.311-329 (2016). For example, this report considers the Russia-Siberia node as a citynode (Figure 41), while the journal article considers it as a supply node.

First, from an environmental perspective, the Gobitec+RuHyd scenario shows thataccess to wind/solar resources in the Gobi Desert and additional hydro resources in
Eastern Russia promotes an environmentally-friendly generation mix. The total
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renewable share in NEA increases from 12% to 18% of which 2% is from Russia andthe remaining 4% is from the Gobi Desert. Deployment of these renewables
contributes to NEA emission reductions of 5.3%. By contrast, the NoNewRE scenario
shows that cost-optimal grid interconnections without renewable energy
development would promote low-cost coal generation in China and Russia, resulting
in an increase CO2 emissions in NEA (+2.3% from the Base) and potentially worse air
pollution in China. Thus, interconnection projects should be undertaken in tandemwith renewable energy expansion in order to reap both economic and environmental
benefits.
Second, all grid interconnection scenarios indicate that economic benefits in the formof total cost reductions depend mainly on the fuel cost saved by shifting to cheaper
fossil fuel or to renewables. Expanding renewable energy results in larger fuel costsavings, for example the 3% reductions (-7B USD/y) in the NoNewRE versus the 10%
reductions (-20B USD/y) in the Gobitec+RuHyd. However, the total system cost
reductions appear modest (less than 1.2% reduction from the Base) due to theincrease in initial costs and O&M costs. In addition, sensitivity analysis on fuel prices
and initial costs (Section 4.4.6) imply that the benefit potentially shrinks or becomes
negative with 10%~20% lower fuel prices and higher initial costs. These limited
economic benefits are likely to be a major challenge to implementing gridinterconnection in NEA. Given the large scale investments are required for NEA-wide
interconnections (Section 4.4.4), the relevant planning organizations should carefully
assess the actual initial costs and long-term fossil fuel price trends in order to assurethat implementation will be beneficial. Section 4.4.6 also shows that carbon prices areimportant for profitable implementation. The relevant organisations or economies
need to work on the establishment of regional carbon market and regional emission
reduction agreements.
Third, the RuHyd and Gobitec+RuHyd results imply that interconnection opportunities
between ‘mainland’ Russia (Siberia and Far East) and the rest of NEA expand withadditional hydro development in Eastern Russia. Hence, access to additionalhydropower will be the driver of opportunities for grid interconnections between
Russia and other regions.
Turning to priorities for future work, Section 4.4.6 mentioned the importance of sitespecific characteristics to the cost of renewables and transmission lines. Further
examination of site-specific costs, as well as site-specific performance of renewables,
should be undertaken. For example, if detailed meteorological data were available ineach node (i.e., hourly or more detailed data for a full year), future work could bettercharacterize the output of intermittent renewables.
Future work should perform sensitivity analysis on the upper bounds for net imports
in importing regions and the installed capacity of renewables in the Gobi Desert. Also,
additional modelling of other types of renewables, including biomass in China, would
be interesting to discuss their contribution to emissions reductions in NEA region.
Future work might discuss the mechanisms to appropriately share the cost-burden
and the credit for emission reductions among the NEA regions.
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Our modelling approach includes some simplifications that should be addressed infuture work. The single-year simulation could be replaced with a multi-year
simulation in order to examine the evolution of costs and benefits over time. Perhaps
most importantly, the current model is deterministic in nature. Incorporating
probabilistic representations could improve the robustness of the model in at least
two ways. First, incorporating probabilistic behaviour into the representation ofintermittent renewables would allow a more detailed examination of NEA-wide grid
integration issues, not only for the Gobi Desert renewables discussed in this paper,
but also for intermittent renewables in the other NEA economies. Second, aprobabilistic representation of the performance of additional system components(transmission lines and thermal generating facilities) would allow the model toaddress the impact of NEA grid interconnection on power system reliability and thecosts of maintaining reliability.

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APPENDIX
A.1

M AT H E M AT I C A L F O R M U L AT I O N

We describe the equations of the model in order to provide a detailed understandingof this study. Table A1 shows endogenous variables of the model.
Table A1 Endogenous variables in the multi region power system model
Endogenous variables
𝑇𝐶: Total annual cost [USD]
𝑥𝑝𝑛,𝑝,𝑠,𝑡 : Output of power plant p at local time t in season s in node n [kW]𝑑𝑒𝑛,𝑝,𝑠,𝑡 : Suppressed output of power plant p (p=wind or PV) at local time t in season s in node n [kW]𝑚𝑝𝑛,𝑝,𝑠 : Daily maximum output of power plant p in season s in node n [kW]𝑘𝑝𝑛,𝑝 : Capacity of power plant p in node n [kW]𝑥𝑙𝑛,𝑛2,𝑠,𝑡 : Power exports from node n to node n2 via line type l at time t (node n time) in season s [kW]𝑘𝑙𝑛,𝑛2,𝑙 : Total transmission capacity between node n and n2 via line type l [kW]𝑥𝑐ℎ𝑛,𝑠𝑡,𝑠,𝑡 : Electricity charge of storage st at local time t in season s in node n [kW]𝑥𝑑𝑐𝑛,𝑠𝑡,𝑠,𝑡 : Electricity discharge of storage st at local time t in season s in node n [kW]𝑠𝑡𝑒𝑛,𝑠𝑡,𝑠,𝑡 : Stored electricity of storage st at local time t in season s in node n [kWh]𝑘𝑠𝑡𝑛,𝑠𝑡 : kW-capacity of storage st in node n [kW]where 𝑛, 𝑛2 ∈ {1:CH-N, 2:CH-NE, 3:JP-H, 4:JP-E, 5:JP-W, 6:KR, 7:RU-FE, 8:RU-SI, 9:RU-SK, 10:GD},s ∈ {1:Summer-Peak, 2:Summer-Average, 3:Winter-Average, 4: Winter-Peak, 5: Intermediate }𝑡 ∈ {0 , 1, … , 23}
𝑝 ∈ {1:Nuclear, 2:Coal fired, 3:Gas fired, 4:Oil fired, 5:Hydro, 6: Wind, 7:PV, 8:Additional hydro 1 (AddHyd1), 9:Additional hydro 2 (Add-Hyd2)}
𝑠𝑡 ∈ {Pumped Hydro Storage}𝑙 ∈ {HV interconnection}
Source: APERC analysis.

OBJECTIVE FUNCTION
Equation (A.1) is the objective function. This model minimizes total system cost for asingle representative year. System cost is composed of annualized initial cost, O&M
cost, fuel cost and carbon cost for the whole of Northeast Asia (NEA). The cost of
power plant includes all four cost components above. The cost of a storage andtransmission line consists of initial cost and fixed O&M cost. Therefore, the model
choose cross-border power trade if its benefit (i.e., fuel cost savings) is larger than the
fixed cost of transmission line.
Equation (A.2)~(A.5) describe each component. In equation (A.2), annualized initialcost of power plant, storage and transmission line are calculated as the product of a
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capital recovery factor (PA, STA and LA, respectively), unit construction cost andinstalled capacity. For capital recovery factor calculation, the assumed discount rate is
3% and the lifetime assumptions are as discussed in Section 4.3.2 and 4.3.3. Equation(A.3) describes the O&M cost of power plant (fixed and variable O&M cost), storage(fixed O&M) and cross-border transmission line (fixed O&M). Equation (A.4) and (A.5)
respectively describe fuel cost and carbon cost for direct emissions. Time slot length(HW) is calculated in equation (A.6). Assumed seasonal length (SW) is in Table A2, andtime slice length (TW) is 1 hour.

(A.1)

𝑚𝑖𝑛. 𝑇𝐶 = ∑(𝐶𝐼𝑛 + 𝐶𝑂𝑛 + 𝐶𝐹𝑛 + 𝐶𝐶𝑛 )𝑛

𝐶𝐼𝑛 = ∑ 𝑃𝐴𝑝 ∙ 𝑃𝐼𝑛,𝑝 ∙ 𝑘𝑝𝑛,𝑝 + ∑ 𝑆𝑇𝐴𝑠𝑡 ∙ 𝑆𝑇𝐼𝑛,𝑠𝑡 ∙ 𝑘𝑠𝑡𝑛,𝑠𝑡
𝑝

𝑠𝑡

(A.2)
+ ∑ ∑ 𝐿𝐼𝑙 ∙ 𝐿𝐼𝑛,𝑛2,𝑙 ∙ 𝑘𝑙𝑛,𝑛2,𝑙𝑛2<𝑛 𝑙𝐶𝑂𝑛 = ∑ (𝑃𝑂𝐹𝑛,𝑝 ∙ 𝑃𝐼𝑛,𝑝 ∙ 𝑘𝑝𝑛,𝑝 + ∑ ∑ 𝑃𝑂𝑉𝑛,𝑝 ∙ 𝑥𝑝𝑛,𝑝,𝑠,𝑡 ∙ 𝐻𝑊𝑠,𝑡 )
𝑝

𝑠

𝑡

(A.3)

+ ∑ 𝑆𝑇𝑂𝐹𝑛,𝑠𝑡 ∙ 𝑆𝑇𝐼𝑛,𝑠𝑡 ∙ 𝑘𝑠𝑡𝑛,𝑠𝑡 + ∑ ∑ 𝐿𝑂𝐹𝑙 ∙ 𝐿𝐼𝑛,𝑛2,𝑙 ∙ 𝑘𝑙𝑛,𝑛2,𝑙𝑠𝑡

𝐶𝐹𝑛 = ∑ ∑ ∑ 𝑃𝐹𝑛,𝑝 ∙ 𝑥𝑝𝑛,𝑝,𝑠,𝑡 ∙ 𝐻𝑊𝑠,𝑡
𝑝

𝑠

𝑠

(A.4)

𝑡

𝐶𝐶𝑛 = ∑ ∑ ∑ 𝐶𝑇𝐴𝑋 ∙ 𝐶𝑎𝑟𝑏𝑜𝑛𝑝 ∙ 𝑥𝑝𝑛,𝑝,𝑠,𝑡 ∙ 𝐻𝑊𝑠,𝑡𝑝𝑛2<𝑛 𝑙(A.5)

𝑡

𝐻𝑊𝑠,𝑡 = 8760 ∙ 𝑆𝑊𝑠 ∙ 𝑇𝑊𝑡 /12/24(A.6)

Where: CIn: annualized initial cost of power plant, storage and transmission line
in node n [USD/year], COn: annual O&M cost of power plant, storage andtransmission line in node n [USD/year], CFn: annual fuel cost in node n[USD/year], CCn: annual carbon cost for fuel combustion [USD/year], PAp: capital
recovery factor of power plant type p, PIn,p: initial cost of power plant type p innode n [USD/kW], STAst: capital recovery factor of storage type st, STIn,st: initialcost of storage type st in node n [USD/kW], LAl: capital recovery factor oftransmission line, LIn,n2,l: initial cost of transmission line between node n and n2[USD/kW], POFn,p: fixed O&M cost rate of power plant type p as a fraction of theinitial cost, POVn,p: variable O&M cost of power plant type p [USD/kWh], STOFn,st:
fixed O&M cost rate of storage type st as a fraction of the initial cost, LOFl: fixed
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O&M cost rate of a transmission line as a fraction of the initial cost, PFn,p: fuelcost of power plant type p [USD/kWh], Carbonp: carbon intensity of power plant
type p [t-CO2/kWh], CTAX: carbon price [USD/t-CO2], HWs,t: length of time slot
at local time t in season s [hours], SWs: length of season s [Months] (see Table
A2), TWt: length of time slice t [hour] (=1hour).
Table A2 Assumed length of each season
SeasonAssumed length [Months]

Summer-peak

0.2

Summer-average

2.8Winter-peak

0.2

Winter-average

2.8

Intermediate

6.0

Source: APERC analysis.

CONSTRAINTSElectricity demand–supply balance
Equation (A.7) ensures that electricity demand must be satisfied at all times in allseasons and in all nodes. The left part indicates the sum of power supply fromdomestic generators, net power imports and net power discharge of storage facilities.
Cross-boundary transmission losses are considered when transmitted power reaches
the importing node by multiplying exported power by transmission efficiency (xl*LE).
Time differences between power exporting and importing nodes are considered forimported power. ImT indicates the local time at the origin of electricity imports
defined as below. Note that we number hours of the day from 0 to 23 (Table A1).
The dual solution to this equation indicates the marginal costs of electricity
generation. The marginal costs are determined by the variable cost of generation,
storage, and transmission. Losses in transmission and storage indirectly increase
marginal costs and total system cost, as they lead to higher demand for power
generation (Schaber, et al., 2012) Equation (A.8) shows how we calculate cross-bordertransmission efficiency.
This model does not explicitly consider modes of operation of generation andstorage facilities. In the real world, storage facilities are either in charging mode
(pumping mode for pumped hydro storage), discharging mode (generation mode) or
standby mode at any given time. In our linear programming model, equation (A.7)
technically allows both charging and discharging simultaneously. However, becauseof the power losses this would involve, as represented in equation (A.23)~(A.24)
below, the model will avoid a solution with simultaneous charging and discharging.

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∑ 𝑥𝑝𝑛,𝑝,𝑠,𝑡 + ∑ ∑(𝑥𝑙𝑛2,𝑛,𝑙,𝑠,𝐼𝑚𝑇𝑛2,𝑛,𝑡 ∙ 𝐿𝐸𝑛,𝑛2,𝑙 − 𝑥𝑙𝑛,𝑛2,𝑙,𝑠,𝑡 )
𝑝

𝑛2

𝑙

(A.7)
+ ∑(𝑥𝑑𝑐𝑛,𝑠𝑡,𝑠,𝑡 − 𝑥𝑐ℎ𝑛,𝑠𝑡,𝑠,𝑡 ) = 𝐸𝐿𝐷𝑛,𝑠,𝑡𝑠𝑡
𝐷𝐼𝑆𝑛,𝑛2(A.8)

𝐿𝐸𝑛,𝑛2,𝑙 = (1 − 𝐿𝑂𝑆𝑙 ) 1000

Where: ELDn,s,t: electric load at local time t in season s in node n [MW], LEn,n2,l:cross-border transmission efficiency of transmission line type l between node n
and n2, LOSl: transmission losses of line type l [per thousand km], DISn,n2:transmission distance between node n and n2 [km], ImTn2,n,t: local time at theorigin of electricity imports, defined as:t+TimDn2,n+24
t+TimDn2,nt+TimDn2,n-24

for t+TimDn2,n < 0;
for 0 ≤ t+TimDn2,n < 24;
for t+TimDn2,n ≥ 24;

and TimDn2,n: time difference between nodes (e.g., TimDCH-N,KR=-1).

Installable capacity constraint
Installable capacity of each technology is constrained by its minimum and maximum
deployable limits. (see Section 4.3.2 and Section 4.3.3 for initial capacity and upper
limit assumptions).
𝑃𝑀𝐼𝑛,𝑝 ≤ 𝑘𝑝𝑛,𝑝 ≤ 𝑃𝑀𝐴𝑛,𝑝(A.9)

𝑆𝑀𝐼𝑛,𝑠𝑡 ≤ 𝑘𝑠𝑡𝑛,𝑠𝑡 ≤ 𝑆𝑀𝐴𝑛,𝑠𝑡(A.10)

𝐿𝑀𝐼𝑛,𝑛2,𝑙 ≤ 𝑘𝑙𝑛,𝑛2,𝑙 ≤ 𝐿𝑀𝐴𝑛,𝑛2,𝑙(A.11)

Where: PMIn,p: initial capacity of power plant type p in node n [kW], PMAn,p:capacity upper limit of power plant type p in node n [kW], SMIn,st: initial capacityof storage type st in node n [kW], SMAn,st: capacity upper limit of storage type st
in node n [kW], LMIn,n2,l: initial capacity of transmission line type l between noden and n2 [kW], LMAn,n2,l: capacity upper limit of transmission line type l between
node n and n2 [kW].

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Output constraint
Equations (A.12)~(A.16) constrain output of power plant, storage and transmission
lines. The output of power generation technologies, except wind power and PV, areconstrained to their available capacity [equation (A.12)]. For wind and PV, theseasonal hourly availability profiles (ROF) are exogenously given in equation (A.13).
These profiles for Gobi Desert (GD) are estimated in Section 4.3.2 based on
observation data (Elliott, et al., 2001). The left part of the equation (A.13) indicates
two destinations for output power from wind and PV: power supplied to grid (xp) or
suppressed (de). Equation (A.14) constrains the charge to or discharge from storage
facilities to their available power capacity (kW-capacity). Equation (A.15) constrains
stored electricity to the energy capacity (kWh-capacity), i.e., reservoir capacity ofpumped hydro.
𝑥𝑝𝑛,𝑝,𝑠,𝑡 ≤ 𝑃𝐴𝑉𝑝 ∙ 𝑘𝑝𝑛,𝑝 (𝑝 = 1, … , 5,8,9)(A.12)

𝑥𝑝𝑛,𝑝,𝑠,𝑡 + 𝑑𝑒𝑛,𝑝,𝑠,𝑡 = 𝑅𝑂𝐹𝑛,𝑝,𝑠,𝑡 ∙ 𝑘𝑝𝑛,𝑝 (𝑝 = 6,7)

(A.13)

𝑥𝑐ℎ𝑛,𝑠𝑡,𝑠,𝑡 + 𝑥𝑑𝑐𝑛,𝑠𝑡,𝑠,𝑡 ≤ 𝑆𝑇𝐴𝑉𝑠𝑡 ∙ 𝑘𝑠𝑡𝑛,𝑠𝑡(A.14)

𝑠𝑡𝑒𝑛,𝑠𝑡,𝑠,𝑡 ≤ 𝑆𝑇𝐴𝑉𝑠𝑡 ∙ 𝐶𝑅𝑇𝑠𝑡 ∙ 𝑘𝑠𝑡𝑛,𝑠𝑡(A.15)

𝑥𝑙𝑛2,𝑛,𝑙,𝑠,𝑡 + 𝑥𝑙𝑛,𝑛2,𝑙,𝑠,𝑡 ≤ 𝐿𝐴𝑉𝑙 ∙ 𝑘𝑙𝑛,𝑛2,𝑙(A.16)

Where: PAVn,p: availability factor of power plant type p (p=1,…,5,8,9), ROFn,p,s,t:
output profile of intermittent renewable(wind and PV) energy at local time t inseason s, STAVst: availability factor of storage type st, CRTst: maximum ratio of
kWh to kW of storage type st, LAVst: availability factor of transmission line type l.

Ramping constraint for thermal power plants (Nuclear and fossil fuel-fired)
The model considers technology-specific ramping constraints for nuclear and fossil
fuel-fired plants. For technical reasons, each technology has its own controllability,with output of these power plants changeable within their ramping capabilities.
Ramping up and ramping down limits are modelled as follows in this study.
𝑥𝑝𝑛,𝑝,𝑠,𝑡 ≤ 𝑥𝑝𝑛,𝑝,𝑠,𝑡−1 + 𝐿𝐹𝑅𝑝 ∙ 𝑘𝑝𝑛,𝑝 (𝑡 ≠ 0)

(A.17)

𝑥𝑝𝑛,𝑝,𝑠,0 ≤ 𝑥𝑝𝑛,𝑝,𝑠,23 + 𝐿𝐹𝑅𝑝 ∙ 𝑘𝑝𝑛,𝑝(A.18)

𝑥𝑝𝑛,𝑝,𝑠,𝑡 ≥ 𝑥𝑝𝑛,𝑝,𝑠,𝑡−1 − 𝐿𝐹𝑅𝑝 ∙ 𝑘𝑝𝑛,𝑝 (𝑡 ≠ 0)

(A.19)

𝑥𝑝𝑛,𝑝,𝑠,0 ≥ 𝑥𝑝𝑛,𝑝,𝑠,23 − 𝐿𝐹𝑅𝑝 ∙ 𝑘𝑝𝑛,𝑝(A.20)

Where: LFRp: maximum load following rate of power plant type p [/hour].
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Ramping constraint for thermal power plants (Nuclear and fossil fuel-fired)
Equation (A.21) requires that thermal plants generate electricity at no less than theirminimum output threshold. The model calculates the minimum output threshold bymultiplying minimum output rate (MOL) and daily maximum output (mp) as
described in equation (A.21). Daily maximum output for each plant type in eachseason is determined by equation (A.22).
𝑥𝑝𝑛,𝑝,𝑠,𝑡 ≥ 𝑚𝑝𝑛,𝑝,𝑠 ∙ 𝑀𝑂𝐿𝑝

(A.21)

𝑚𝑝𝑛,𝑝,𝑠 ≥ 𝑥𝑝𝑛,𝑝,𝑠,𝑡(A.22)

Where: MOLp: minimum output rate of operation of power plant type p.

Stored energy balance
Equation (A.23)~(A.24) relates power charge (xch), power discharge (xdc) and thelevel of stored electricity (ste). Self-discharge loss and charge/discharge efficiency are
considered in this equation.
𝑠𝑡𝑒𝑛,𝑠𝑡,𝑠,𝑡 = (1 − 𝑆𝐷𝑅𝑠𝑡 ) ∙ 𝑠𝑡𝑒𝑛,𝑠𝑡,𝑠,𝑡−1+(√𝐶𝐸𝐹𝑠𝑡 ∙ 𝑥𝑐ℎ𝑛,𝑠𝑡,𝑠,𝑡 − 𝑥𝑑𝑐𝑛,𝑠𝑡,𝑠,𝑡 /√𝐶𝐸𝐹𝑠𝑡 ) ∙ 𝑇𝑊𝑡 (𝑡 ≠ 0)
𝑠𝑡𝑒𝑛,𝑠𝑡,𝑠,0 = (1 − 𝑆𝐷𝑅𝑠𝑡 ) ∙ 𝑠𝑡𝑒𝑛,𝑠𝑡,𝑠,23+(√𝐶𝐸𝐹𝑠𝑡 ∙ 𝑥𝑐ℎ𝑛,𝑠𝑡,𝑠,0 − 𝑥𝑑𝑐𝑛,𝑠𝑡,𝑠,0 /√𝐶𝐸𝐹𝑠𝑡 ) ∙ 𝑇𝑊𝑡(A.23)(A.24)

Where: SDRst: self-discharge rate of storage type st, CEFst: cycle efficiency ofstorage type st, TWt: length of time slice t [hour] (=1hour).

Capacity reserve constraint for city nodes
Constraint (A.25) ensures a certain level of capacity reserve margin in city node for areliable power supply. There should be enough excess generation/storage capacityand domestic transmission at city node to cover demand plus the reserve margin.

∑ 𝑘𝑝𝑛,𝑝 ∙ 𝑃𝐶𝐶𝑝 + ∑ 𝑘𝑠𝑡𝑛,𝑠𝑡 ∙ 𝑆𝑇𝐶𝐶𝑠𝑡 + ∑ (𝑥𝑙𝑛2,𝑛,𝑙,𝑠,𝑡 ∙ 𝐿𝐸𝑛,𝑛2,𝑙 − 𝑥𝑙𝑛,𝑛2,𝑙,𝑠,𝑡 )𝑝𝑠𝑡𝑙,𝑛2∈𝑁𝑛(A.25)≥ (1 + 𝑅𝑉𝑀𝑛 ) ∙ 𝐸𝐿𝐷𝑛,𝑠,𝑡 (𝑛 = 1, … , 8)
Where: RVMn: reserve margin in node n, PCCp: capacity credit of power plant
type p, STCCst: capacity credit of storage type st, Nn = set of nodes located in thesame economy as node n.
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Upper constraints of net-imports for city nodes
In general, each power service area needs to be prepared for transmissioninterruptions. Thus, in the scenarios in this study, the net transmission inflows at eachcity node (left part of the equation) are limited to be less than the reserve marginlevel (NIS=RVM).

∑(𝑥𝑙𝑛2,𝑛,𝑙,𝑠,𝑡 ∙ 𝐿𝐸𝑛,𝑛2,𝑙 − 𝑥𝑙𝑛,𝑛2,𝑙,𝑠,𝑡 ) ≤ 𝑁𝐼𝑆𝑛 ∙ 𝐸𝐿𝐷𝑛,𝑠,𝑡(𝑛 = 1, … , 8)

(A.26)

𝑙,𝑛2

Where: NISn: maximum share of net imports in node n (we assume the reserve
margin for the scenarios in this study).

Additional hydro power export constraints
As explained in the RuHyd scenario in Section 4.2, this study considers additionalhydro developments in Russia Far East (RU-FE) and Russia Siberia (RU-SI) for
exporting to foreign nodes. This equation ensures that power exports from thesenodes should be larger than the output power of additional hydro.
9∑ 𝑥𝑙𝑛,𝑛2,𝑙,𝑠,𝑡 ≥ ∑ 𝑥𝑝𝑛,𝑝,𝑠,𝑡𝑙,𝑛2∉𝑁𝑛(A.27)

𝑝=8

Transmission line capacity constraints for supply nodes
Equation (A.28) requires each supply node (GD and RU-FE) to have enoughtransmission capacity to deliver the output of the installed generation capacity in thenode. This constraint may be active especially in the Gobitec and Gobitec+RuHyd
scenarios, where there are minimum constraints on generation capacity in the Gobi
Desert (GD) node. This constraint forces the total GD transmission capacity to at least
match the total GD generation capacity.

∑ 𝑘𝑙𝑛,𝑛2,𝑙 ≥ ∑ 𝑘𝑝𝑛,𝑝 (𝑛 = 9, 10)𝑙,𝑛2(A.28)𝑝

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A P P E N D IX

A.2

M O D E L VA L I D AT I O N

In order to validate the model’s ability to properly assess the real-world powersystem, we performed a simulation of the NEA power system of 2010, the mostrecent year before the Great East Japan Earthquake. The installed capacity of power
plants, storage and cross-border transmission line is calibrated to historical data
(JEPIC, 2012). Costs and fuel prices for 2010 are based on IEA (2010), IEA (2014a) and
Energy and Environment Council (2011). Historical average efficiency of fossil fuelfired plants is estimated using IEA (2014b). No carbon tax is assumed, and otherparameters are the same as shown in Section 4.3.
Figure A1 illustrates modelled generated electricity and statistical data (JEPIC, 2014a).
So-called base load and middle load plants (nuclear, coal, gas and hydro) shows
relatively a good fit. By contrast, the model tends to underestimate peak load plants(oil). As reported in Schaber, et al. (2012), this is because of the deterministic natureof the optimisation model. Probabilistic aspects, such as unforeseen forecast errors or
power plant outages, are not considered in the model, while peak load plants areoften operated to balance electricity demand and supply in those events.
Figure A1 Comparison of modelled generated electricity and historical data inNortheast Asia
Nuclear
Coal

Gas
Oil

Historical data 2010

Hydro

Model 2010

Other
Renewables
0

400

800

1 200

1 600

2 000

Electricity generation [TWh]Source: APERC analysis.

The model reproduces similar trends of cross-border electricity trade as shown in
Figure A2. The observed differences might be because the actual power trade is notalways scheduled based on cost-optimisation, as well as because the model simplifies
several aspects, especially in terms of simplified modelling of power transportation(see Section 4.1) or temporal resolution.
This study deduces electricity prices from average marginal generating costs, whichapproximately describe the regional retail price gap (Figure A3). We referred to JEPIC(2012) for the price in China, METI (2014b) for Japan, KESIS (2015) for Korea and RAO
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A P P E N D IX

Energy System of East (2013) for Russia Far East area. The computed marginal
generating costs tend to be lower than the actual prices (i.e. 4c/kWh in Japan and1c/kWh in Russia Far East). This is partly because of the costs, taxes or subsidies not
explicitly included in our model. The actual electricity price in Korea is lower than thecalculated average marginal costs. This is probably because Korea government
regulation holds electricity price at level lower than the actual generating costs. In
fact, from 2008 to 2012, Korea Electric Power Corporation was in a chronic state of
deficit (KEPCO, 2015).
The generated electricity and cross-border trades in the benchmark results areinsensitive to fuel price changes: a considerable price increase (90% for coal and 20%
for gas) does not have major impacts on the results.

Net imports [TWh]Figure A2 Modelled net imports and historical data
1.5
Model 2010

1

Historical data 2010

0.5
0
-0.5
-1
-1.5
CH-NE

JP-H

JP-E

JP-W

RU-FE

Source: APERC analysis.

Average price [USD/kWh]Figure A3 Comparison of the average retail electricity prices with the modelled
average marginal costs of power generation
0.20

Model 2010

0.15

Price ranges in North China and Northeast
grid provinces

Average price(histrical data)

0.10

0.05

0.00
Japan

China
(North China grid,Northeast grid)

Korea

Russia(Far East region)

Source: APERC analysis.
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A P P E N D IX

A.3

D I S C U S S I O N O N C A PA I T Y R E S E R V E
CONSTRAINT

Equation (A.25) does not take into account the demand levelling and capacity saving
benefits from non-domestic transmissions. This is because of our policy based on thesafer side from energy security perspectives. In this section, we additionally conduct
an analysis to discuss these benefits in NEA. We replace the Constraint (A.25) with thefollowing Constraint (A.29). The red part is changed from ‘𝑛2 ∈ 𝑁𝑛 ’ to ‘𝑛2’. Constraint(A.25) assumes that only domestic electricity trades contribute to demand levellingand capacity saving, while (A.29) considers non-domestic trades as well. We ran three
scenarios (the Base, NoNewRE and Gobitec+RuHyd) with Constraint (A.29).

∑ 𝑘𝑝𝑛,𝑝 ∙ 𝑃𝐶𝐶𝑝 + ∑ 𝑘𝑠𝑡𝑛,𝑠𝑡 ∙ 𝑆𝑇𝐶𝐶𝑠𝑡 + ∑(𝑥𝑙𝑛2,𝑛,𝑙,𝑠,𝑡 ∙ 𝐿𝐸𝑛,𝑛2,𝑙 − 𝑥𝑙𝑛,𝑛2,𝑙,𝑠,𝑡 )𝑝𝑠𝑡(A.29)𝑙,𝑛2≥ (1 + 𝑅𝑉𝑀𝑛 ) ∙ 𝐸𝐿𝐷𝑛,𝑠,𝑡 (𝑛 = 1, … , 8)
The results with Constraint (A.29) shows capacity saving effects (Figure A4a));however, its changes appears to be modest. Compared to (A.25) results, total
installed capacity in NEA is reduced by 6GW and 8GW with (A.29) in the NoNewRE
and Gobitec+RuHyd scenarios, respectively. Yet, these capacity savings are equivalent
only to 0.5~0.6% reductions, resulting in slight impacts on total cost (-0.03~-0.08%.
see Figure A4b)). Because of the small time difference (maximum two hours) in NEA,
peak-hours still occur more or less simultaneously in each region (Figure 42). This
would be the main cause of the modest demand levelling and capacity saving
benefits. The result implies that the benefits of interconnections are mainly due toother factors, such as low-cost electricity in the exporting regions. The result also
implies that the findings obtained through Section 4 are robust to these formulations.
Figure A4 Comparison of the results with Constraint (A.25) and with (A.29)b) Changes in yearly total cost from
Constraint (A.25) to (A.29)

GW

Billion USD/year

1 300

0.25

with
Constraint (A.29)

Other costs
0-0.5

Gobitec+RuHyd

1 000
NoNew
RE

-0.25

Base

1 100

Gobitec+RuHyd

1 200

Initial costs for
power plant

Base

with
Constraint (A.25)(Section 4 results)

NoNew
RE

a) Total installed capacity

Source: APERC analysis.
PAGE 89

R E FE R E N CE S

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