48030-001: Strategy for Northeast Asia Power System Interconnection · 2020-02-14 · on regional energy markets. The second objective is to determine the impact of these potential

Technical Assistance Consultant’s R eport Project Number: 48030-001 February 2020

Mongolia: S trategy for Northeast Asia Power S ystem Interconnection (Cofinanced by the C limate Change Fund, the People’s R epublic of China R egional Cooperation and Poverty R eduction Fund, and the R epublic of Korea e-Asia and Knowledge Partnership Fund)

Prepared by

E lectricite de France

Paris, France

For the Ministry of E nergy, Mongolia

This consultant’s report does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents.

TA 9001-MON: S trategy for Northeast Asia Power S ystem Interconnections

E DF R eferences: C IS T – DCO – PhL – 18 - 207

This consultant’s report does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents.

Module 2 report on Market and Power Trade Assessment

1

EDF ELECTRICITE DE FRANCE with a capital of 1 006 625 696.50 euros – TA-9001 MON: Strategy for Northeast Asia Power System Interconnection

552 081 371 R.C.S. Paris EDF References: CIST – DCO – PhL – 18 - 207

www.edf.fr

FOREWORD

The project Team would like to thank:

- The Ministry of Energy of Mongolia for easing direct discussions with the National Dispatching Center, TRANSCO and Public Entities in Mongolia

- The ADB’s Country Coordinators of Mongolia, People’s Republic of China, Republic of Korea, Japan for their support:

Mongolia: Mr. Byambasaikhan

PRC: Ms. Geng Dan (Danna)

ROK: Mr. Jung-Hwan Kim

Japan: Mr. Omatsu Ryo and Mr. Shota Ichimura

Here is a reminder of the place of the Module 2 in the Project organization:


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TABLE OF CONTENTS

EXECUTIVE SUMMARY ......................................................................................................................... 7

1 METHODOLOGY ............................................................................................................................ 8

1.1 Objectives of the study ............................................................................................................. 8

1.2 Methodology of the study ......................................................................................................... 8

1.3 Model used ................................................................................................................................. 9

1.4 List of inputs and outputs of the model ................................................................................ 11

1.5 Review of the benefits and costs of power system evolutions .......................................... 12

2 INPUT DATA USED IN THE STUDY ............................................................................................ 13

3 STUDY RESULTS ......................................................................................................................... 18

3.1 SCENARIOS 2036 .................................................................................................................... 18

3.1.1 Impact of interconnection and RES in Mongolia on the NAPSI region generation mix......... 19

3.1.2 Results on profitability ........................................................................................................... 20

3.1.3 Impact of interconnection and RES in Mongolia on the NAPSI region CO2 emissions ........ 22

3.1.4 Use of the interconnection lines ............................................................................................ 23

3.1.5 Variants with RES in Korea/Japan instead of Mongolia ........................................................ 24

4 SCENARIOS 2020 AND 2026 ...................................................................................................... 26

5 CONCLUSIONS ............................................................................................................................ 27


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LIST OF TABLES

Table 1. Demand and generation dataset (outside coal, gas and fuel oil, which are optimized

by the model) ...................................................................................................................... 14

Table 2. Global economic hypotheses on commodities ....................................................... 15

Table 3. Variable generation costs dataset (input of power plants) ...................................... 15

Table 4. Annualized fixed generation costs dataset (include CAPEX and OPEX) ................ 16

Table 5. Cost assessments for interconnection overhead lines/submarine cables (annualized

costs, including CAPEX, OPEX and losses) ........................................................................ 17

Table 6. Comparison of CAPEX and load factors in 2036 for the renewables in Mongolia, Korea

and Japan ........................................................................................................................... 25

LIST OF FIGURES

Figure 1 The five steps of a Cost-Benefit Analysis ................................................................. 9

Figure 2 Main features of the optimization model used ........................................................ 10

Figure 3 Objective function of the optimization model .......................................................... 10

Figure 4 Constraints to be respected by the optimization model .......................................... 11

Figure 5 Notation used in the description of the optimization model .................................... 11

Figure 6 The four main scenarios used in the study ............................................................ 13

Figure 7 Generation mix (in energy) compared to current and other projected pie charts .... 18

Figure 8 Generation mix and deviations (in energy) in the NAPSI region for the 2036 scenarios

............................................................................................................................................ 19

Figure 9 Results of the Cost-Benefits Analyses: annual gains in the 2036 scenarios .......... 20

Figure 10 Impact of interconnection and RES in Mongolia on the CO2 emissions of the power

sector in the NAPSI region .................................................................................................. 22

Figure 11 Diagrams of the load flow distribution on the various interconnection lines, showing

the direction and the magnitude of the flows ........................................................................ 23

Figure 12 Cost-Benefit Analyses of different variants of location for installing renewables

Mongolia, Korea, and Japan ................................................................................................ 24

Figure 13 Cost-Benefit Analyses of the 2020 and 2026 scenarios compared to the 2036

moderate interconnection scenario ...................................................................................... 26


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PHYSICAL UNITS AND CONVERSION FACTORS

bbl barrel (1t = 7.3 bbl)

cal calorie (1 cal = 4.1868 J)

Gcal Giga calorie

GWh Gigawatt-hour

h hour

km kilometer

km² square kilometer

kW kilo Watt

kWp kilo Watt peak (solar PV)

kWh kilo Watt hour (1 kWh = 3.6 MJ)

MBtu Million British Thermal Units (= 1 055 MJ = 252 kCal)

one cubic foot of natural gas produces approximately 1,000 BTU

MJ Million Joule (= 0,948.10–3 MBtu = 238.8 kcal)

MW Mega Watt

m meter

m3/d cubic meter per day

mm millimeter

mm3 million cubic meter

Nm3 Normal cubic meter, i.e. measured under normal conditions, i.e. 0°C and 1013 mbar

(1 Nm3 = 1.057 m3 measured under standard conditions, i.e. 15°C and 1013 mbar)

pu per unit

sqm Square meter

t ton

toe tons of oil equivalent

tcf ton cubic feet

°C Degrees Celsius


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ABBREVIATIONS AND ACRONYMS

ADB Asian Development Bank

BNEF Bloomberg New Energy Finance

BTB Back To Back

CAPEX Capital Expenditure

CBA Cost-Benefit Analysis

CCGT Combined Cycle Gas Turbine

CEPRI China Electric Power Research Institute

CHP Combined Heat Power

EENS Expected of Energy Not Supplied

ERC Energy Regulatory Commission

ESRI Environmental Systems Research Institute

GDP Gross Domestic Product

GHI Global horizontal irradiation

GIS Geographical Information System

GTI Global Tilted Irradiation/Irradiance

HPP Hydro Power Plant

HV High Voltage

HVAC High Voltage Alternative Current

HVDC High Voltage Direct Current

IEA International Energy Agency

IEC International Electrotechnical Commission

IHS Markit Provider of business and finance information for major industries

IRENA International Renewable Energy Agency

LCoE Levelized Cost of Electricity

MCDA Multi-criteria decision Analysis

MoE Ministry of Energy (Mongolia)

MNT Mongolian currency

NDC National Dispatching Center (Mongolia)

NEA North East Asia

NREC National Renewable Energy Corporation (Mongolia)

NREL National Renewable Energy Laboratory of the USA

NTPG National Power Transmission Grid (Mongolia)

NWP Numerical Weather Prediction

O&M Operation and Maintenance

OCGT Open Cycle Gas Turbine

OPEX Operational expenditure

PRC People’s Republic of China

PV Photovoltaic

RES Renewable Energy Source

TL Transmission Line

TPP Thermal Power Plant

UA Unit of Account


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UNESCAP United Nations Economic and Social Commission for Asia and the Pacific

USD United States Dollar

VSC Voltage Source Converter

WACC Weighted Average Cost of Capital

WLC Weighted linear combination

In this report, "$" refers to US dollars.


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EXECUTIVE SUMMARY

The first objective of this module is to assess the economic feasibility of a massive Renewable

Energy Resources (RES) development in the Mongolian Power System to be largely exported

on regional energy markets.

The second objective is to determine the impact of these potential evolutions on the level of

CO2 emissions of the electric sector in the NAPSI region.

The main findings and key messages are the following:

- Interconnection between North East Asia countries is beneficial, already in the pre-

sent situation and with the existing generation fleets

- Interconnection lines are all used in both directions, allowing countries to export or import according to hours and situations

- Development of renewable generation in Mongolia will bring additional benefits in the mid-term (2036), due to drastic cost reduction of renewables in Mongolia in the forth-coming decades

- Generating RES in Mongolia brings higher profit than producing the same amount of renewable energy in Korea or Japan

- Beyond financial profits, these future evolutions will bring other valuable benefits (re-duction of CO2 emissions, contribution to the achievement of the clean energy objec-tives for the different countries, job creations, opportunities for adaptation of national networks).

The report starts with the description of methodology followed, then the input data of the study

are presented, and finally the results are shown and explained.


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1 METHODOLOGY

1.1 OBJECTIVES OF THE STUDY

The first objective of this module is to assess the economic feasibility of a massive Renewable

Energy Resources (RES) development in the Mongolian Power System to be largely exported

on regional energy markets. The second objective is to determine the impact of these potential

evolutions on the level of CO2 emissions of the electric sector in the NAPSI region.

1.2 METHODOLOGY OF THE STUDY

The methodology adopted is based on the principles of Cost-Benefit Analysis (CBA).

This approach allows to assess the societal value of a project, for large geographical and

functional perimeters. Therefore, it is well suited to help institutional actors to carry out strategic

arbitrages on power system development (generation + network).

The main features of a CBA are the following:

- CBA assesses societal value (instead of private values)

- CBA is based on a comparison of factual and counterfactual scenarios and allows to explicitly identify alternative scenario’s impacts on power system processes, in order to avoid risks of double counting of benefits or CO2 emissions

- Sensitivity analyses allow to cope with long term scenarios uncertainties.


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Figure 1 The five steps of a Cost-Benefit Analysis

1.3 MODEL USED

The model used has a twofold purpose:

- It is a generation expansion planning tool that optimizes the share of each available asset type. The optimization is done with respect to the system fundamentals, e.g. cost structure of generation technologies and level of power demand. The time horizon can be multiannual so that long-run trade-off can be made.

- The model also provides hourly optimization of the dispatch of thermal generation in order to satisfy the residual demand (i.e. demand - RES intermittent generation) all over the years represented in the study.


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Figure 2 Main features of the optimization model used

The main modelling characteristics are the following:

- The model can take into account several balancing areas linked by transmission lines dimensioned by their commercial exchange capacity.

- The temporal resolution is hourly, either on all days along the year, or only on repre-sentative days. The model embeds a clustering module that can select the representa-tive days among a large amount of data according to their statistical representation.

- In each balancing area, power supply is made of dispatchable generation units with an aggregated view by technology, and must-run generation units (wind and solar power, run-of-river hydro, CHP) that can be modelled either by a generation time series or by capacity factor time series associated with generating capacity.

The next figures present successively the objective function of the model (i.e. the criteria used

to optimize the system), the constraints to be respected, and the notations.

Figure 3 Objective function of the optimization model


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Figure 4 Constraints to be respected by the optimization model

Figure 5 Notation used in the description of the optimization model

1.4 LIST OF INPUTS AND OUTPUTS OF THE MODEL

The input dataset mainly consists of the following items:

- Hourly power demand time series within each area represented


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- Hourly generation or capacity factor time series for must-run assets

- Description of generation units (variable, fixed O&M and investment costs, initial ca-pacity, CO2 intensity, availability factor)

- Capacities of transmission lines

- Value of loss load

- CO2 value (if any, this feature being not used in the simulations presented here, all results corresponding to cases where the CO2 price was taken equal to zero).

The outputs include the following results:

- Optimal portfolio: within each area

- Hourly generation by technology and use of transmission lines

- Global system costs, marginal costs, revenues of generation units CO2 emissions.

1.5 REVIEW OF THE BENEFITS AND COSTS OF POWER SYSTEM EVOLU-TIONS

The development of renewable generation capacities in Mongolia combined with the creation

of new interconnection links in the region give birth to new energy exchanges between the

countries/areas concerned.

On the one hand, these energy exchanges bring potential benefits that can be decomposed

as follows:

- Benefits linked to the better use of the conventional generation fleets (pooling effects on investment and operational costs)

- Benefits linked to the substitutions between conventional generation units located in the various countries (switching effects on investment and operational costs, e.g. be-tween coal and gas units)

- Benefits linked to the substitution between conventional generation and renewable generation (which may have a significant impact in terms of CO2 emission reduction).

On the other hand, the associated costs to be considered are the development costs of the

renewable energy sources in Mongolia, and the development costs of the interconnection in-

frastructures.


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2 INPUT DATA USED IN THE STUDY

The main study criteria and the fundamental data of the systems have been specified in the

Module 3 report.

The analyses object of the Module 2 are carried out on four main scenarios combining various

time horizon (2020, 2026, 2036), various levels of renewable capacity in Mongolia (0.3GW,

5GW, 10GW, 100GW), and various configurations of interconnection between NAPSI coun-

tries/areas. These scenarios are the same as those used in Module 4 (generation resources).

Figure 6 The four main scenarios used in the study

Considering the current LCOEs of Mongolian wind and PV, and their perspectives of reduction

along the coming two decades, we have chosen to share the amount of renewable capacity

considered in Mongolia haft on wind and half on PV for all the scenarios considered.

Hence for 10GW capacity in Mongolia, and taken into account the respective power factors of

wind and PV in 2036 for Mongolia (Cf. Module 4), that gives 5GW of wind (generating 21TWh

annually), and 5GW of PV (generating 9TWh annually). Of course for 100GW total capacity

developed in Mongolia, the wind/solar capacities and generations are ten times greater.

A coherent data set on demand levels and structure of the generation fleet has been consti-

tuted. For the purpose of the study, the generation fleet is divided in two parts; one part is

fixed and considered as input of the model (nuclear, hydro, wind and solar), the rest

(conventional generation) is optimized by the model, and constitutes outputs of the

simulations.


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Table 1. Demand and generation dataset

(outside coal, gas and fuel oil, which are optimized by the model)


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A coherent dataset on economic parameters has been constituted, based on International En-

ergy Agency data and projections (World Energy Outlook 2017, New Policies Scenario), com-

pleted by direct information from ADB Country Coordinators and expertise of the consulting

team.

Table 2. Global economic hypotheses on commodities

The costs of fuels for conventional generation at the input of the power plants have been cal-

culated from the global economic hypotheses on commodities, and the transportation costs

between mines/gas fields/exporting-importing ports, making use of the “netback method” that

allows to build coherent values between countries/areas importing or exporting energy either

under the form of raw materials, or electricity. These costs are consistent with assessments

elaborated by IHS Markit (for cost of fuels in the Chinese provinces), Russian official agencies

(for cost of fuels in the Russian federal districts), and Mongolian government (for cost of coal

in Mongolia).

Table 3. Variable generation costs dataset (input of power plants)


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The fixed costs of generation units have been taken according to IEA data projections (Power

generation assumptions in the New Policies and 450 Scenarios in the World Energy Outlook

2016), completed by direct information from ADB Country Coordinators and expertise of the

consulting team.

Table 4. Annualized fixed generation costs dataset (include CAPEX and OPEX)

As far as interconnection infrastructures are concerned, assessments have been done in the

framework of Module 5 (networks) and used in this study. The following table sums up the

values retained for the 2036 scenario (moderate interconnection). The costs presented are

annualized costs and include CAPEX, OPEX and losses. They are given in the form of a range

of values to take into account the high uncertainties unavoidably associated with such an ex-

ercise of costing projection for this type of infrastructures.


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Table 5. Cost assessments for interconnection overhead lines/submarine cables

(annualized costs, including CAPEX, OPEX and losses)

The costs relative to the infrastructures to be deployed for the other scenarios (2026, 2036

with large interconnection) can be deduced from these figures, using down-scaling or up-scal-

ing factors based on the transmission capacities considered.

Annualized Estimated Cost

Node 1 Node 2 Length and type

Transmission

Capacity

(GW)

Range (M$/year)

Mongolia (UB) Mongolia (Gobi) 430 km (OHL) 2 49 - 86

Mongolia (UB) Russia-Siberia 520 km (OHL) 2 52 - 91

Mongolia (Gobi) China-East 520 km (OHL) 6 165 - 297

China-East Rep. of Korea20 km (OHL) +

500 km (cable)3 138 - 258

China-East Russia-Far East 750 km (OHL) 2 58 - 106

Rep. of Korea Japan20 km (OHL) +

230 km (cable)2 62 - 112

Rep. of Korea Russia-Far East50 km (OHL) +

1400 km (cable)2 84 - 156

Russia-Siberia Russia-Far East 3500 km (OHL) 2 142 - 272

Russia-Far East Japan2200 km (OHL) +

200 km (cable)2 125 - 238

2036 scenario (moderate interconnection)


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3 STUDY RESULTS

We choose to present results beginning by the scenario 2036, because the logic we adopt is

to deal first with the long-term fundamentals that will guide decisions makers in defining their

targets of energy policy and their priority in terms of long-term investments. The results of the

interim scenarios 2020 and 2026, presented afterwards, will be helpful to determine the best

ways and rhythms to reach the target and manage the transition periods.

3.1 SCENARIOS 2036

First of all, we present below the generation mix that results from the optimization model, com-

pared to current and other projected pie charts.

Figure 7 Generation mix (in energy) compared to current and other projected pie charts

We recall that the model is set to optimize only the fossil fuel fleet (coal, gas, fuel oil), the other

technologies (renewable and nuclear) being considered as fixed by the model.

In the mix simulated for 2036 (left hand side), coal occupies a large place (around 40%), gas

a small place (4%), and fuel oil a very limited place (less than 1%).

For comparison purpose, the current mix (in energy) of NAPSI region in 2016 (in the middle of

the figure) is composed of 5% nuclear, 58% coal, 10% gas, 3% fuel oil, 18% hydro, 3% wind

and 2% solar.

We can also compare the simulated pie chart for 2036 with the one (right hand side) reconsti-

tuted from IEA projected data for 2040 (World Energy Outlook 2017, New Policies scenario),

in which nuclear would stand for 11%, coal 38%, gas 11%, fuel oil nearly 0%, hydro 16%, wind

12%, PV 10%, and other renewables 3%. The main differences between these two pie charts

(the 2036 simulated one and the 2040 IEA one) are likely to have two causes. The first is

related to the hypotheses on renewable energies (supposedly more developed in our dataset).

Total

10800 TWh

Total

7800 TWh

Total

10900 TWh


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The second is the carbon pricing policy (not applied in our simulations), applied for the IEA in

China with a price of 35$/tCO2 and in Korea with a price of 48$/t. This last fact must certainly

explain the discrepancies observed on the development of gas and coal.

3.1.1 IMPACT OF INTERCONNECTION AND RES IN MONGOLIA ON THE NAPSI REGION GENERA-

TION MIX

Figure 8 Generation mix and deviations (in energy) in the NAPSI region for the 2036 scenarios

On the right hand side of the diagram, the positive (respectively negative) deviations observed

correspond to an increase (respectively a decrease) of energy generated by the concerned

technology, compared to the situation where the countries are isolated. The main changes

concern wind, solar, coal and gas technologies.

The first bar (Interco + 10GW RES) shows that moderate interconnection associated with the

implementation of 10GW renewables in Mongolia (generating around 30 TWh), allows to de-

crease coal generation by 8 TWh, and gas generation by 22 TWh, compared to the reference

case (all countries isolated).

The second bar (Large Interco +100GW RES) shows that high capacity interconnection asso-

ciated with the implementation of 100GW renewables in Mongolia (generating around 300

TWh), allows to decrease to a high extent the use of coal (by around 170 TWh) and gas (by

around 130 TWh).

Hence we see that in these two cases, the combined effect of interconnection and RES in

Mongolia is a substitution of coal and gas by this renewable energy.


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3.1.2 RESULTS ON PROFITABILITY

Figure 9 Results of the Cost-Benefits Analyses: annual gains in the 2036 scenarios

The figure must be read as follows:

- For each situation simulated, the model calculates the global system costs (sum of all fixed and variable costs of the optimized part of the generation mix), and compares them to the global system costs obtained in “country isolated” situation. The cost dif-ference between this factual and counterfactual scenarios gives the gross gain brought by the modifications made in-between. Therefore, the gross gain corresponds to the collective benefits calculated by the optimization model, including the savings in terms of investment expenses and operation expenses, but excluding the investments linked to interconnection infrastructures and renewables in Mongolia.

- Then we subtract the investments linked to interconnection infrastructures and renew-ables in Mongolia, this gives the net gain. Therefore, the net gain corresponds to the final profits including all expenses and revenues. The net gain is given with a range, to take into account uncertainties, particularly on interconnection infrastructure costs.

- As we reason with annualized costs and variable costs on a yearly basis, all gross and net gains are annual values

- As the gain values are not the same order of magnitude between the two cases pre-sented on the figure, we have adopted two different scales, the left hand side one being five times enlarged than the right hand side one.


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The results presented on Figure 9 can be interpreted as follows

- Starting from the left hand side, the first set of dots and bar (Interco) shows the sole effect of the implementation of interconnection (moderate interconnection). The annual gross gain is around 4Bn$, and the annual net gain (integrating the cost of intercon-nection) is around 3Bn$. In other words, the implementation of the sole intercon-

nection is financially profitable (annual net collective benefits of around 3Bn$).

- The second set of dots and bar (Interco + 10GW RES) shows that interconnection associated with the implementation of 10GW renewables in Mongolia, generates a higher annual gross gain (around 5.1Bn$), and a higher annual net gain (3.2Bn$) than the interconnection alone. In other words, renewables in Mongolia bring additional

benefits to the implementation of the interconnection, increasing the annual col-

lective net benefits to a level of approx. 3.08Bn$.

- The third set of dots and bar (Large Interco +10GW RES) shows the outcome of in-creasing largely the interconnection capacity between NAPSI countries, conserving 10GW RES in Mongolia. This results in a large increase of both annual gross gain (18.2Bn$) and annual net gain (9.3Bn$). In other words, the perspective of increas-

ing largely the interconnection capacities brings extended net collective bene-

fits.

- The fourth set of dots and bar (Large Interco +100GW RES) shows that high capacity interconnection associated with the implementation of 100GW renewables in Mongolia, allows to reach high level of annual gross gain (27.6Bn$) and annual net gain (10.7Bn$). In other words combining high capacity interconnection implementa-

tion and development of large amounts of renewables in Mongolia is collectively

highly profitable.


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3.1.3 IMPACT OF INTERCONNECTION AND RES IN MONGOLIA ON THE NAPSI REGION CO2 EMIS-

SIONS

Figure 10 Impact of interconnection and RES in Mongolia on the CO2 emissions

of the power sector in the NAPSI region

The CO2 emissions of the power sector is an output of the model, and results from the effective

operation of the fossil fuel fired plants in the various scenarios simulated.

The results presented on the figure can be interpreted as follows

- The implementation of the interconnection (moderate interconnection) cumulated to the development of 10GW RES in Mongolia (generating around 30TWh) leads to a global

CO2 emission saving of 17Mt (comparison of the light green bar in the middle with the black one at the left hand side). In other words, the substitution emission factor of this capacity of 10GW of Mongolian renewables is 0.57tCO2/MWh, sign that renewa-bles replace approximately coal for a quarter, and gas for the remaining three quarters. Note that this distribution between coal and gas substituted is coherent with the gener-ation variation between these two cases observed on Figure 8

- The dark green bar on the right shows that high capacity interconnection associated with the implementation of 100GW renewables in Mongolia, allows to reach a high level of CO2 emission savings. The 300TWh of renewables reduce CO2 emissions

by 210Mt, which gives a substitution emission factor (for this 100GW capacity of Mongolian renewables) of 0.70tCO2/MWh. This is the sign that renewables replace approximately coal for one half, and gas for the other half (this is also coherent with what is shown on Figure 8)

- We observe that the substitution emission factor depends on the amount of renewa-ble energy injected in the system. This is mainly due to the fact that, as presented in §1.5, changes introduced in the power system have several superimposed impacts, such as pooling effects and switching effects between technologies, which may result when cumulated in an apparent non-linear behavior.


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3.1.4 USE OF THE INTERCONNECTION LINES

Let us analyze now the load flows running through the various cross border lines, on the 2036

scenario with moderate interconnection and 10GW RES in Mongolia.

Figure 11 Diagrams of the load flow distribution on the various interconnection lines,

showing the direction and the magnitude of the flows

Figure 11 shows for each line the load flow distribution, in the form of its annual load flow

duration curve. These curves are deduced from chronological simulation results, by ranking

them from the highest to the lowest values. These curves allow to observe globally the sharing

of hours between the two load flow directions, and in terms of load flow magnitude.

We observe that most of the lines are used in both directions, depending on the situations

occurring along the year. That means that the interconnection lines are not purely used as


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export or import means, but have a shared function that contributes to bring a collective value

to the whole system.

Moreover, the fact that most of the lines are saturated at the maximum or minimum load a large part of the time is a good indicator that the capacities chosen in this scenario (2036 /

moderate interconnection) do not lead to overinvestments.

3.1.5 VARIANTS WITH RES IN KOREA/JAPAN INSTEAD OF MONGOLIA

These variants allow to assess the profitability of renewables developed in Korea or Japan,

and to compare it to the profitability of the same amount of renewable energy developed in

Mongolia.

In order to be consistent, we have compared situations where the additional renewable energy

is made equal, and not the additional renewable installed capacity. There is a certain differ-

ence, because of the power factors are not the same in the various countries, due to natural

resource quality discrepancies.

Hence, the various renewable additional capacities that are equivalent to the 10GW in Mon-

golia (5GW wind capacity producing annually 21TWh + 5GW PV capacity producing 9TWh

annually) are the following:

- For the Republic of Korea : an addition of 13.9GW of RES (7.3GW of wind producing

annually approx. 20TWh, and 6.6GW of PV producing annually approx. 10TWh)

- For Japan : an addition of 12.6GW of RES (7.3GW of wind producing annually approx.

20TWh, and 5.3GW of PV producing annually approx. 10TWh).

Figure 12 Cost-Benefit Analyses of different variants of location for installing renewables

Mongolia, Korea, and Japan


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Of course, the left hand side of the diagram (corresponding to renewables installed in Mongo-

lia) is identical to what we have already seen (Cf. Figure 9).

In comparison we observe that producing the same amount of renewable energy in the Re-public of Korea or in Japan brings lower benefits. In other words, generating RES in Mongolia

brings higher profit than producing the same amount of renewable energy in Korea or

Japan.

The explanation comes from the consideration of the quality of wind and solar resources (char-

acterized by their power factors) and the perspectives of CAPEX levels in Mongolia in 2036,

compared to those of Korea and Japan. These last points are illustrated by Table 6.

Table 6. Comparison of CAPEX and load factors in 2036

for the renewables in Mongolia, Korea and Japan


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4 SCENARIOS 2020 AND 2026

Figure 13 sums up the results obtained when simulating the 2020 and 2026 scenarios, and

comparing them to the 2036 scenario (moderate interconnection), case we have already ana-

lyzed (Cf. Figure 9).

As the gain values are not the same order of magnitude between the various cases presented on the figure, we have adopted two different scales, the left hand side one being twenty times

enlarged than the right hand side one.

Figure 13 Cost-Benefit Analyses of the 2020 and 2026 scenarios

compared to the 2036 moderate interconnection scenario

The comparison leads to formulate the following statements:

- Trades through the existing cross border lines bring already benefits: the net gain

for the 2020 case with interconnection (in the left hand side of the diagram) is positive

(around 200M$/year)

- The development of interconnection is economically justified, and allows to in-

crease the social welfare in the NAPSI region: the net gain for the 2026 case with

interconnection (in the middle of the diagram) is largely positive (around 2.5Bn$/year)

and significantly larger than the 2020 net gain

- Renewables in Mongolia exported through the interconnection will be directly

profitable only in the mid-term: the net gains corresponding to Interco + RES are

above the net gains of the interconnection alone only for the 2036 scenario, and not in

the 2020 and 2026 scenarios.


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5 CONCLUSIONS

Interconnection between North East Asia countries is beneficial, already in the present situa-

tion and with the existing generation fleets.

Interconnection lines are all used in both directions, allowing countries to export or import ac-

cording to hours and situations.

Development of renewable generation in Mongolia will bring additional benefits in the mid-term

(2036), due to drastic cost reduction of renewables in Mongolia in the forthcoming decades.

Generating RES in Mongolia brings higher profit than producing the same amount of renewa-

ble energy in Korea or Japan.

Beyond financial profits, these future evolutions will bring other valuable benefits (reduction of

CO2 emissions, contribution to the achievement of the clean energy objectives for the different

countries, job creations, opportunities for adaptation of national networks).


28



www.edf.fr

MINISTRY OF ENERGY, GOVERNMENT OF MONGOLIA

Government Building 14, Khan-Uul District

Chinggis Avenue, 3-r Khoroo

Ulaanbaatar, 17060 Mongolia

Contact: Mr. Chimeddorj Demchigjav

General Director of Energy Policy Department

ASIAN DEVELOPMENT BANK

6 ADB Avenue

Mandaluyong City, 1550

Metro Manila, Philippines

Contact: Mr. Teruhisha Oi

Project Manager, Energy Division (EAEN), East Asia Department (EARD)

[email protected]

Consultant: EDF

EDF CIST, Immeuble Spallis, 2 rue Michel Faraday

93282 Saint-Denis Cedex

France

Contact: Mr. Philippe Lienhart

Strategy Innovation New Business Manager EDF CIST

Strategy for NAPSI Technical Assistance to Mongolia Team Leader

[email protected]

Deliverable: Module 2 Report on Market and Power Assessment

Date: 8 March 2018

Documents

48030-001: Strategy for Northeast Asia Power System Interconnection · 2020-02-14 · on regional energy markets. The second objective is to determine the impact of these potential