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The Application of the LEAPThe Application of the LEAPSoftware Tool to Energy SectorSoftware Tool to Energy Sector
Analysis in the Republic of KoreaAnalysis in the Republic of Korea
East Asia Energy Futures / AsiaEnergy Security Project
5 November, 2003Vancouver, Canada.
Hoseok Kim
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Directions of the StudyDirections of the Study
Applying LEAP software tool to the ROK
Establishing a comprehensive and effective LEAP dataset for the ROK
Assessing the properness of the application and dataset
Projecting future energy outlook based on business-as-usual case
Developing reasonable and meaningful alternative
scenarios
Analyzing the results and implication of the alternative
scenarios
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This presentation will show
How to apply the LEAP software tool to theROKs energy sector.
The structure of ROK2003: An Overview
The obstacles and problems in the application
Possible energy issues being analyzed based
on LEAP ROK data set and ROK2003. Know-how might be shared with other
regional working group
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Organization of the PresentationOrganization of the Presentation
1. ROKs Energy Policy
2. LEAP Modeling in ROK
3. LEAP ROK2003
4. Demand Sector5. Transformation Sector
6. BAU Energy Paths7. Obstacles and Tasks
8. Alternative Scenarios
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1.1. ROKROKss Energy PolicyEnergy Policy
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Energy Policy and Modeling
Various types of energy policy give a
exogenous shock to (inter)national energysystem.
Energy demand & supply
Energy mix
Energy efficiency
The innovation of energy related technologyEnergy models help to foresee the impacts and
to analyze the implications of energy policy.
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ROKs Energy Policy: Problems and
Challenges Maintaining a stable energy supply for enduring
economic growth
Encouraging competition in energy market
Reducing the dependence on oil
Diversification of energy sources
Establishing environment- and climate-friendly energysystem forSustainable Development.
Strengthening the long-run potential for pollution
control Restructuring an energy system with low GHG
emissions
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Directions of ROKs Energy Policy
Sustainable Energy
System To stimulate energy
efficiency
To stabilize energy
supply capacity
Energy Technology
Innovation
To develop energy
technologies
Competitive Energy
Markets To privatize energy
industries
To improve efficiency in
energy market
Regional Cooperation
To diversify energy
sources
To stabilize energy
supply and prices
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2. LEAP Modeling in ROK2. LEAP Modeling in ROK
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Previous Work
Beijing workshop, June 2000
Nautilus provided support in the use of the LEAP software The first national dataset for LEAP was developed.
Berkeley workshop, February 2001
The first rigorous application was made.(ROK2000) The conceptual and analytical understanding was elaborated
in the training session.
Berkeley workshop, January 2002 After the 3rd training workshop ROK2000 was completed.
And the dataset was applied to the LFG generation issue.
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Why LEAP?
There is a huge range of models that can be
used to address energy-related issues, and theyare grouped into three categories:
macroeconometric models, CGE models,
energy-economy models
Energy-economy models, so called bottom-up
models, are technology based models found onengineering relationships..
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Strengths and Weakness of Bottom-Up
ArpproachStrengths of Bottom-up Approach
The capacity to address at a more detailed sectoral andsub-sectoral level the implications of energy policies
on energy system
Weaknesses of Bottom-up Approach The models may fail to adequately capture opportunity
or welfare costs of technological substitution.
The choice of modeling platform depends on the
purpose of analysis.
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LEAP Modeling Platform
LEAP modeling platform
With its flexible structures, LEAP allows theuser to simulate and assess the impacts of
alternative energy policies on energy system-
especially technological fields, and to project
the energy supply and demand situation
As a database, LEAP provides acomprehensive system for maintaining energy
information.
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Best Conditions for Applying LEAP
Modeling PlatformLEAP model is most useful where:
There is insufficient historical macro-economicdata for trend analysis
There are significant technological changes in
energy sector. There are short-run development problems
There is a need to disaggregate energy uses. There is a strong policy scheme that is shaping
the national energy system.
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Energy Modeling in the ROK
Macroeconometric Models
CGE Models KEED (Korea Energy Environmental Dynamic
GE Model, KEEI)
Energy-Economy Models
KEEI Model, EFOM-Env (Korea Energy
Economics Institute) MARKAL (Korea Institute of Energy Research)
META-Net, LEAP (Yonsei University)
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3. LEAP ROK2003: An Overview3. LEAP ROK2003: An Overview
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LEAP ROK Models
ROK1998 (LEAP v.95)
Highly aggregated but simple and intuitive ROK2000 (LEAP v.2000)
Highly disaggregated but complex and with
uncertainties in BAU paths
ROK2003 (LEAP v.2003))
Less disaggregated than ROK2000 but withreasonable and rigorous BAU paths
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Determinants of Model Structure
The purpose of analysis
The modes of shock Methodological approach of the analysis
Time horizon Geographical coverage
Sectoral coverage
Data restriction or availability
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ROK Models
The purpose is to assess the recent ROKs energy
policy scheme and its regional implication
Shock: Policies on energy demand, supply, and
technological change
Methodology: LEAP software (scenario analysis) Time horizon: 2000-2015 (medium-term)
Geographical coverage: National model
Sectoral coverage: Energy sector
Data availability: Quite good!
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The Structure of ROK2003
ROK 2003
DEMAND
SECTORS
TRANSFORMATION
SECTORRESOUCE
Residential
Industrial
Commercial & Public
Transportation
Electricity Generation
District Heating
Town Gas Production
LNG Gasification
SECONDARYElectricity , Town Gas
Natural Gas, Heat
PRIMARY
Coal, Gasoline
Diesel, KeroseneFuel oil, LPG
Naphtha, LNG
Nuclear, Hydro
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ROK2002 Model Diagram
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Current Status of ROK2003
Well equipped with key data, parameters, and
BAU path Highly disaggregated in residential demand,
transportation and transformation sectors
Well structured to be applied in electricity
generation and transportation analysis
Two alternative scenarios are under developingin the climate policy context
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Key Data Gaps
Small Electricity Appliances
Renewable Energy Uses Mass transit & freight: BAU path
Air Transportation Heat Production of CHP
Electricity Production of HOB
Oil Refining Process
Domestic Coal Mining
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Key Data Sources
Ministry of Commerce, Industry, and Energy
Korea Energy Economics Institute Korea National Statistical Office
Korea Development Institute
The Bank of Korea
Korea Electric Power Corporation
Korea District Heating Corporation Korea Coal Corporation
Korea Gas Corporation
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4. Demand Sector4. Demand Sector
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The Structure of Demand Sector
DEMAND SECTOR
RESIDENTIAL TRANSPORTATION INDUSTRIAL COMMERCIAL & PUBLIC
Cooking
Space HeatingLighting
Appliances
Household Vehicles
Mass Transit & Freight
Agriculture & Fishery
Mining
Manufacturing
Construction
Commercial Sector
Public Sector
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Energy Balance: TFE
2,6261,16022229-1,141-PUBLIC
32,4147,8911,0979,0244913,487718RESIDENT
30,999175-30,824-TRANSP
83,13511,3743,30820747,20919,129INDUSTRIAL
149,17320,6001,11912,56125692,66019,847FINAL
TotalElectHeatTown GasLNGPetcoalUNIT: 000
TOE
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Final Energy Demand in 2000
150
100%
2.1
1.4%
1.1
0.7%
20.6
13.7%
12.6
8.4%
93.6
62.4%
19.8
13.2%Total
20.6%31.0000.2030.80Transportation
1.7%2.6001.20.21.10Public &
Others
21.6%32.40.21.17.99.013.50.7Residential &
Commercial
56.0%83.91.9011.43.348.219.1Industrial
TotalRenew
ableHeat
Electri
city
Town
Gas
Petrol
eumCoal(M TOE)
E l ti f 1984 t 2002 f TFE b
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Evolution from 1984 to 2002 of TFE by
Sector
010,000
20,000
30,000
40,00050,000
60,000
70,000
80,00090,000
100,000
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
KT
OE
Industrial
Res & Com
Transportation
Public
E l ti f 1984 t 2002 f TFE b
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Evolution from 1984 to 2002 of TFE by
Fuel
0
20,000
40,000
60,000
80,000
100,000
120,000
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
KT
OE
Coal
PetroleumTown Gas
Electricity
Others
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End-Uses of Residential Sector
Refrigerator, Rice cooker, Air conditioner, TV,
PC, Electric stove, Kimchi Refrigerator,
Washing machine, Vacuum cleanerELECTRICITYAPPLIANCES
Town Gas Stove
LPG Stove
LPG
Town GasCOOKING
Incandescent bulbs
Fluorescent bulbs
Other bulbs
ELECTRICITYLIGHTING
Boilers
District Heating
COAL, GAS,HEAT, OIL,
ELECTRICITY
HEATING
DEVICEFUEL TYPEEND USES
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Residential Sector
0.2Coal
0.4Electricity
0.9Oil
46.3LPG
51.3Town gas
Cooking
1.5Coal
1.6Electricity
3.4LPG
6.4District
37Town gas
48.6Oil
Heating
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Industrial Sector
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Commercial & Public Sector
29.5829.5328.8228.66K TOE/M
m^2
Energy
Intensity
1,075928725473M m^2Floor Space
31,80427,39920,90013,558K TOEEnergy Use
2030202020102000
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Transportation Sector
17,82411,731,000Sum
5,2682,254,000Truck
2,5421,284,000Bus
972522,000SUV
9,0427,671,000Cars
Fuel Use
(Ktoe)
Vehicle
PopulationHousehold
2,13869,170Bus
13,616546,328Sum
4927,297Rail
6,1911,827Marine
2,815235,791Truck
1,927232,243Taxi
Fuel Use
(Ktoe)
Vehicle
Population
MassTran &
Freight
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5. Transformation Sector5. Transformation Sector
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Transformation Sector
Transformation
Electric
Generation
Town Gas
Production
District
Heating
Coal, Fuel Oil
Diesel, Natural Gas
Hydro
Nuclear
LPG
Natural Gas
Natural Gas
Town Gas
Fuel Oil
LPG
Gasification
LNG
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Energy Balance: Transformation
179
-
12,52012,387312-
Town
Gas
532
-
355120436331-Heat
39,54127,2411,402
-
22,910
-
8091085,4036,04223,064
Electrici
ty
192,88827,2411,40218,924100,28042,911
PRIMA
RY
TotalNuclea
rHydroElectHeat
Town
GasLNGPetcoal
UNIT:
000
TOE
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Data on Generation Facilities
42.441,5441,346N.A.Nuclear
1.212,024617N.A.Hydro
9.516,53650544.15Combined
0.169,8401,15437.2Internal
0.6--35.68LNG
7.421,61280037.45Oil
38.732,62892039.25Coal
Output
Share (%)
O&M Cost
(KRW/kW)
Capital Cost
(K KRW/kW)
Efficiency
(%)
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Electric Generation by Fuel
0
50000
100000
150000
200000
250000
300000
G
W
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Trend of Electric Generation
Internal
Combined
LNG
Oil
Coal
Nuclear
Hydro
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6. BAU Energy Path6. BAU Energy Path
A ti f BAU P th
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Assumptions of BAU Path
GDP: 4.9% annual growth rate for the years 2000-15
Population: 0.6% annual growth rate
Households: 1.5% annual growth rate
Residential
Expansion of town gas use and district heating
Disappearance of LPG and coal uses
Industrial
Decrease of the share of industrial GDP
Decrease of manufacturing and increase of construction
Commercial & Public
Increase of floorspace in commercial and public sector
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Electricity Generation Capacity
Stable maintenance of nuclear Expansion of CHP
Reduction of coal and oil generation
Increase of LNG gasification facilities
Expansion of district heating area
Enlargement of town gas-using households
M j D hi D t O tl k
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Major Demographic Data Outlook
POPULATION
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
1970 1975 1980 1985 1990 1995 2000
Thousand
PER
SO
HOUSEHOLDS
-
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
1970 1975 1980 1985 1990 1995 2000
ThousandHousehold
Person per Household
-
1.00
2.00
3.00
4.00
5.00
6.00
1970 1975 1980 1985 1990 1995 2000
Persons
GDP O tl k
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GDP Outlook
GDP
-
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1980 1985 1990 1995 2000 2005 2010 2015 2020
Billion
199
5W
Fi l E D d BAU
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Final Energy Demand: BAU
Energy Supply of Transformation
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gy pp y
Sector
Imports of Primary Energy: BAU
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Imports of Primary Energy: BAU
Electricity Generation: BAU
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Electricity Generation: BAU
Global Warming Potential: Demand :
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BAU
Global Warming Potential:
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Transformation : BAU
Examining the Results: TFE & TPES
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Examining the Results: TFE & TPES
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Projected TFE in 2015: 226.9 Mtoe
MOCIEs outlook: 231.7 Mtoe
Accounts for 97%
Projected TPES in 2015: 254.7 Mtoe
MOCIEs outlook: 288.4 Mtoe
Accounts for 88.3%
BAU paths describe ROKs energy system quite well.
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Introduction and expansion of Natural Gas
Vehicle (NGV)
Introduction and expansion of LFG generation
Expansion of compact household vehicles
Introduction of fuel cell
Changes in energy/environmental technology
Structural change in electricity sector
Various regional cooperations
Future Work
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Future Work
Developing future energy scenarios
Collecting and supplementing missing data Trying plausible structural modifications
Updating the dataset (20002001)
Disaggregating major (sub)sectors