The Application of the LEAP The Application of the LEAP Software Tool to Energy Sector Software Tool to Energy Sector Analysis in the Republic of KoreaAnalysis in the Republic of Korea

East Asia Energy Futures / Asia Energy Security Project

5 November, 2003Vancouver, Canada.

Hoseok Kim

Directions of the StudyDirections of the Study

Applying LEAP software tool to the ROKEstablishing a comprehensive and effective LEAP data set for the ROKAssessing the properness of the application and datasetProjecting future energy outlook based on business-as-usual caseDeveloping reasonable and meaningful alternative scenariosAnalyzing the results and implication of the alternative scenarios

This presentation will showHow to apply the LEAP software tool to the ROK’s 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

Organization of the PresentationOrganization of the Presentation

1. ROK’s Energy Policy 2. LEAP Modeling in ROK3. LEAP ROK2003 4. Demand Sector5. Transformation Sector6. BAU Energy Paths7. Obstacles and Tasks8. Alternative Scenarios

1. 1. ROKROK’’ss Energy PolicyEnergy Policy

Energy Policy and Modeling

Various types of energy policy give a exogenous shock to (inter)national energy system.

Energy demand & supplyEnergy mixEnergy efficiencyThe innovation of energy –related technology

Energy models help to foresee the impacts and to analyze the implications of energy policy.

ROK’s Energy Policy: Problems and Challenges

Maintaining a stable energy supply for enduring economic growthEncouraging competition in energy marketReducing the dependence on oil Diversification of energy sourcesEstablishing environment- and climate-friendly energy system for Sustainable Development. Strengthening the long-run potential for pollution controlRestructuring an energy system with low GHG emissions

Directions of ROK’s Energy Policy

Sustainable Energy System

To stimulate energy efficiencyTo stabilize energy supply capacity

Energy Technology Innovation

To develop energy technologies

Competitive Energy Markets

To privatize energy industriesTo improve efficiency in energy market

Regional Cooperation To diversify energy sourcesTo stabilize energy supply and prices

2. LEAP Modeling in ROK2. LEAP Modeling in ROK

Previous Work

Beijing workshop, June 2000Nautilus provided support in the use of the LEAP software The first national dataset for LEAP was developed.

Berkeley workshop, February 2001The first rigorous application was made.(ROK2000)The conceptual and analytical understanding was elaborated in the training session.

Berkeley workshop, January 2002After the 3rd training workshop ROK2000 was completed. And the dataset was applied to the LFG generation issue.

Why LEAP?

There is a huge range of models that can be used to address energy-related issues, and they are grouped into three categories:macroeconometric models, CGE models, energy-economy modelsEnergy-economy models, so called ‘bottom-up’models, are technology based models found on engineering relationships..

Strengths and Weakness of Bottom-Up ArpproachStrengths of Bottom-up Approach

The capacity to address at a more detailed sectoral and sub-sectoral level the implications of energy policies on energy system

Weaknesses of Bottom-up ApproachThe models may fail to adequately capture opportunity or welfare costs of technological substitution. The choice of modeling platform depends on the purpose of analysis.

LEAP Modeling Platform

LEAP modeling platform With its flexible structures, LEAP allows the user 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 a comprehensive system for maintaining energy information.

Best Conditions for Applying LEAP Modeling PlatformLEAP model is most useful where:

There is insufficient historical macro-economic data for trend analysisThere are significant technological changes in energy sector. There are short-run development problemsThere is a need to disaggregate energy uses. There is a strong policy scheme that is shaping the national energy system.

Energy Modeling in the ROK

Macroeconometric ModelsCGE Models

KEED (Korea Energy Environmental Dynamic GE Model, KEEI)

Energy-Economy ModelsKEEI Model, EFOM-Env (Korea Energy Economics Institute)MARKAL (Korea Institute of Energy Research) META-Net, LEAP (Yonsei University)

3. LEAP ROK2003: An Overview3. LEAP ROK2003: An Overview

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 with reasonable and rigorous BAU paths

Determinants of Model Structure

The purpose of analysisThe modes of shockMethodological approach of the analysisTime horizonGeographical coverageSectoral coverageData restriction or availability

ROK Models

The purpose is to assess the recent ROK’s energy policy scheme and its regional implicationShock: Policies on energy demand, supply, and technological changeMethodology: LEAP software (scenario analysis)Time horizon: 2000-2015 (medium-term)Geographical coverage: National modelSectoral coverage: Energy sectorData availability: Quite good!

The Structure of ROK2003

ROK 2003

DEMAND SECTORS

TRANSFORMATIONSECTOR RESOUCE

Residential

Industrial

Commercial & Public

Transportation

Electricity Generation

District Heating

Town Gas Production

LNG Gasification

SECONDARYElectricity , Town Gas

Natural Gas, Heat

PRIMARYCoal, Gasoline

Diesel, KeroseneFuel oil, LPG

Naphtha, LNGNuclear, Hydro

ROK2002 Model Diagram

Current Status of ROK2003

Well equipped with key data, parameters, and BAU pathHighly disaggregated in residential demand, transportation and transformation sectors Well structured to be applied in electricity generation and transportation analysisTwo alternative scenarios are under developing in the climate policy context

Key Data Gaps

Small Electricity AppliancesRenewable Energy UsesMass transit & freight: BAU path Air TransportationHeat Production of CHPElectricity Production of HOBOil Refining ProcessDomestic Coal Mining

Key Data Sources

Ministry of Commerce, Industry, and EnergyKorea Energy Economics InstituteKorea National Statistical OfficeKorea Development InstituteThe Bank of KoreaKorea Electric Power CorporationKorea District Heating CorporationKorea Coal Corporation Korea Gas Corporation

4. Demand Sector4. Demand Sector

The Structure of Demand Sector

DEMAND SECTOR

RESIDENTIAL TRANSPORTATION INDUSTRIAL COMMERCIAL & PUBLIC

CookingSpace Heating

LightingAppliances

Household VehiclesMass Transit & Freight

Agriculture & FisheryMining

ManufacturingConstruction

Commercial SectorPublic Sector

Energy Balance: TFE

2,626 1,160 22 229 -1,141 -PUBLIC

32,414 7,891 1,097 9,024 49 13,487 718 RESIDENT

30,999 175 -30,824 -TRANSP

83,135 11,374 3,308 207 47,209 19,129 INDUSTRIAL

149,173 20,600 1,119 12,561 256 92,660 19,847 FINAL

TotalElectHeatTown GasLNGPetcoalUNIT: 000 TOE

Final Energy Demand in 2000

150100%

2.11.4%

1.10.7%

20.613.7%

12.68.4%

93.662.4%

19.813.2%

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

TotalRenewableHeatElectri

cityTown Gas

PetroleumCoal(M TOE)

Evolution from 1984 to 2002 of TFE by Sector

010,00020,00030,00040,00050,00060,00070,00080,00090,000

100,000

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

K T

OE

Industrial Res & ComTransportationPublic

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

K T

OE

Coal Petroleum Town GasElectricityOthers

End-Uses of Residential Sector

Refrigerator, Rice cooker, Air conditioner, TV, PC, Electric stove, Kimchi Refrigerator, Washing machine, Vacuum cleaner

ELECTRICITYAPPLIANCES

Town Gas StoveLPG Stove

LPGTown Gas

COOKING

Incandescent bulbsFluorescent bulbsOther bulbs

ELECTRICITYLIGHTING

BoilersDistrict Heating

COAL, GAS, HEAT, OIL,

ELECTRICITYHEATING

DEVICEFUEL TYPEEND USES

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

Industrial Sector

Commercial & Public Sector

29.58 29.53 28.82 28.66 K TOE/M m^2

Energy Intensity

1,075 928 725 473 M m^2 Floor Space

31,804 27,399 20,900 13,558 K TOE Energy Use

2030202020102000

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

5. Transformation Sector5. Transformation Sector

Transformation Sector

Transformation

ElectricGeneration

Town GasProduction

District Heating

Coal, Fuel OilDiesel, Natural Gas

HydroNuclear

LPGNatural Gas

Natural GasTown GasFuel Oil

LPGGasification

LNG

Energy Balance: Transformation

179 -12,520 12,387 312 -

Town Gas

532 -355 120 436 331 -Heat

39,541 27,241 1,402 -22,910

-809 108 5,403 6,042 23,064

Electricity

192,888 27,241 1,402 18,924 100,280 42,911 PRIMARY

TotalNuclearHydroElectHeatTown

GasLNGPetcoalUNIT: 000 TOE

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(%)

Electric Generation by Fuel

0

50000

100000

150000

200000

250000

300000

GWh

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

Trend of Electric Generation

InternalCombinedLNG OilCoalNuclearHydro

6. BAU Energy Path6. BAU Energy Path

Assumptions of BAU Path

GDP: 4.9% annual growth rate for the years 2000-15Population: 0.6% annual growth rateHouseholds: 1.5% annual growth rateResidential

Expansion of town gas use and district heatingDisappearance of LPG and coal uses

Industrial Decrease of the share of industrial GDPDecrease of manufacturing and increase of construction

Commercial & PublicIncrease of floorspace in commercial and public sector

Electricity Generation CapacityStable maintenance of nuclearExpansion of CHPReduction of coal and oil generation

Increase of LNG gasification facilitiesExpansion of district heating areaEnlargement of town gas-using households

Major Demographic Data Outlook

POPULATION

-5,000

10,00015,00020,00025,000

30,00035,00040,000

45,00050,000

1970 1975 1980 1985 1990 1995 2000

Thousand PERSON

HOUSEHOLDS

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

1970 1975 1980 1985 1990 1995 2000

Thousand Households

Person per Household

-

1.00

2.00

3.00

4.00

5.00

6.00

1970 1975 1980 1985 1990 1995 2000

Persons

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 1995 W

o

Final Energy Demand: BAU

Energy Supply of Transformation Sector

Imports of Primary Energy: BAU

Electricity Generation: BAU

Global Warming Potential: Demand : BAU

Global Warming Potential: Transformation : BAU

Examining the Results: TFE & TPES

Projected TFE in 2015: 226.9 MtoeMOCIE’s outlook: 231.7 MtoeAccounts for 97%

Projected TPES in 2015: 254.7 Mtoe MOCIE’s outlook: 288.4 MtoeAccounts for 88.3%

BAU paths describe ROK’s energy system quite well.

Introduction and expansion of Natural Gas Vehicle (NGV) Introduction and expansion of LFG generationExpansion of compact household vehiclesIntroduction of ‘fuel cell’Changes in energy/environmental technologyStructural change in electricity sectorVarious regional cooperations

Future Work

Developing future energy scenariosCollecting and supplementing missing data Trying plausible structural modificationsUpdating the dataset (2000 2001)Disaggregating major (sub)sectors