Latin America Modeling and Scenarios Workshop MODELING ENERGY AND CLIMATE CHANGE SCENARIOS IN COLOMB

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Latin America Modeling and Scenarios Workshop
MODELING ENERGY AND CLIMATE CHANGE SCENARIOS IN
COLOMBIA

• José Eddy Torres Energy consultant
• Angela Inés Cadena University of los Andes
• Rio de Janeiro, Brazil, September 13-14, 2006

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Agenda

• Colombian Economy, Energy and Population
• Emissions, Land Use and Climate Change
• Modelling Options Implemented in Colombia
• ENPEP
• LEAP
• MARKAL
• Energy Reference Scenarios and GHG Emissions
  Projections
• Issues and Options in Constructing the Second
  Communication
• Conclusions

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The Economy

• Intermediate sized GDP, Population, Area
• Support stable institutions, modern social
  physical infrastructure development,
  environmental concern and action.

4
Energy Economy Export Revenues
5
The energy sector Petroleum and Coal
6
The energy sector Electricity
7
The energy sector Natural gas
8
Final energy consumption by sector
9
Final energy consumption by fuel
10
Fuel Sales by Service Stations 96-2005
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Fuel Sales by Service Stations 96-2005
BPD National Aggregate

23 721 BPDC con 96 GrCons
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Internal energy supply
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Population

• All running models have used 1985-2015 population
  projections for drivers
• Projection for 2005 46.03 million
• 2005 census released May-now
• 41,242,948! 4.8 mn/10.4 less

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Population 75 Urban modernizing
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Emission Levels
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GHG Emissions 1990 - 1994
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CO2 emissions from energy sector
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Land Use 103.9 mn ha

• 49.6 mn ha of forest and woodlands (48)
• 39.4 pasture 1.7 cropland 3 arable
• 11 urban and other uses
• WITH KNOWN FORESTRY AND AGRO-FORESTRY SCHEMES

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CDM Strategy (Min-Environment)

• Forest sector potential and competitiveness
• 10 demonstration projects Costs of CO2 capture
  reforestation and conservation activities

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Current CDM Portfolio

• Source MAVDT

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Modelling energy and climate change scenarios

• ENPEP UPME, 1994 today (energy policy)
• LEAP GAS UPME, 1997
• LEAP IDEAM Uniandes, 2001 today (academic
  exercises)
• MARKAL Uniandes, Facultad de Minas, 1992
  today (academic studies and recently metropolitan
  land use and infrastructure development)

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The ENPEP Model (Energy and Planing Evaluation
Program)(Argonne National Lab. UPME Colombia)
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Final energy demand forecast

• Exogenous variables
• GDP (national and sectoral )
• Population and households
• Prices
• Supply reserves, international trade
• Policies coverage, environmental constraints
• Technical parameters

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Final demand forecast
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The LEAP Model Energy Flows
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LEAP-Colombia

• Exogenous variables GDP, population, households
• Time horizon 2000 - 2020
• Base year UPME Energy Balance
• Energy and Environmental policies and or special
  constraints UPME
• Reference scenario UPME 2000 2020 (PEN 2003
  2020). Results
• Higher growth rate natural gas, diesel oil and
  fuel oil
• Lower growth rate gasoline and (non-commercial)
  wood

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LEAP Colombia ResultsReference case
(Industrial sector - steam)

• Higher fuel oil and natural gas use

Natural Gas Crude oil Fuel Oil Diesel
Oil Carbón Bagasse
l
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LEAP Colombia Results Reference case
(Transport sector - Passangers, urban)

• Increase of ACPM, Natural gas, and decrease of
  gasoline

Natural gas Gasoline ACPM
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LEAP COLOMBIA ResultsReference case

• Final energy demand by fuel - Forecast (Teracal)

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LEAP Colombia ResultsBase line

• Energy demand by sector (Teracal)

• CO2 emissions

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Mitigation Scenarios

• Transmilenio Ethanol
• URE CONOCE (UPME)
• Liberalization in derivatives marker no taxes,
  no subsidies
• Proposed
• Bio-diesel
• Massive transportation systems and different
  mobility strategies
• Cogeneration
• Renewables

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Mitigations ScenariosPassangers transportation

• Transmilenio Ethanol

Natural gas Gasoline ACPM Ethanol Transmilenio
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Mitigation ScenariosResidential sector

• Efficient lighting

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Mitigation scenarios CO2 reductions

• Transmilenio Ethanol

• CONOCE

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MARKAL-Family of models

• Linear programming technology rich model for
  representing, optimizing and analyzing the
  production, conversion, end-use and use of
  various forms of energy
• Supply-demand partial equilibrium on energy
  markets
• Perfect foresight information 2000-2100
• Maximization of social surplus, while satisfying
  final demands and exogenous constraints (eg. CO2
  limits)
• Multi-regional

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Colombian Reference Energy System
RESIDENTIAL - RURAL - URBAN
COOKING LIGHTING REFRIGERATION WATER HEATING AIR
CONDITIONING
OIL COAL DIESEL OIL FUEL OIL COKE ELECTRICITY
ELECTRICITY
EXPORTS
INDUSTRIAL
(CON)
- FBT - CEM - TXT - SGC - PAP - IAS -
CHE - OTH
STEAM MOTRIZ POWER DIRECT HEAT OTHER USES
ELECTRICITY GASOLINE KEROSENE DIESEL OIL NATURAL
GAS NON ENERGY
IMPORTS
TRANSPORT
PASSENGER FREIGHT
- ROAD - FLUVIAL - MARITIME - AERIAL
LPG GASOLINE JET FUEL KEROSENE DIESEL OIL FUEL
OIL NON ENERGY P. REFINERY GAS CNG COKE METHANOL H
YDROGEN OTHER PRODUCT
PROCESS OTHER USES
AGRICULTURAL
HYDRO ENERG. COAL URANIUM GEOTHERMAL PETROLEUM NAT
URAL GAS BIOMASS SOLAR ENERGY WIND
COMMERCIAL AND PUBLIC
LIGHTING ELECTROMECH. OTHER USES
MINING
(PRC)
(DMD)
GENERAL USES
BUILDING
(DM)
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Refinery Model - RES
H2S
GASES
C3/C3-C4/C4
GASES
LPG
LIGHT NAPHTA MEDIUM NAPHTA HEAVY NAPHTA JET
FUEL KEROSENE DIESEL OIL
H2S
H2S
ATMOSPHERIC DISTILLATION
GASES
2
5
CATALITIC REFORMER 80 RON
4
OIL CMA-CMB
GASES
2
HYDRO TREATER
C3
6
3
1
C3/C3
C4
ATMOSPHERIC GASOIL
C4/C4
REDUCED OIL
R80
GASOLINE
GASOLINE
VACUUM DISTILLATION
NAPHTA
CRACKING ORTHOFLOW
H2S
VACUUM GASOIL
CYCLE OIL
CLARIFIED OIL
JET FUEL
GASES
5
H2S
C3
CATALITIC REFORMER 90 RON
KEROSENE
C4
6
GASES
DIESEL OIL
R90
ASPHALT
7
NAPHTA
3
C4/C4
NAPHTA
CRACKING VOP
NAPHTA
DMOH
CYCLE OIL
DEMEX
UNIBON
C4/C4
FUEL OIL
DEMETAIL OIL
GASES
4
DEMEX BOTTOMS
NAPHTA
VBII VIISBR
CLARIFIED OIL
ASPHALT
7
VACUUM BOTTOMS
TAR
LUBES
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MARKAL-Colombia baseline (CO2 emissions)

• CO2 emissions path depends on expected economic
  growth
• (reference 4 and low 2.5)
• and increase of the thermal component for
  electricity generation

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Fuels for electricity generation

• Electricity demand 41,752 GWh (1995). Supplied
  with hydraulic generation (76) and thermal
  generation (24)
• To reduce the vulnerability, at least 45 of
  electricity demand must be supplied with thermal
  energy, in 2010

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Mg Cost of CO2 emission reduction (US95/tonne
90)
INDIA
COLOMBIA
SWEDEN
CANADA
SWITZERLAND
NETHERLANDS
GERMANY
ESTONIA

• SourceETSAP News No. 3, August 1997
• and A. CADENA

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Colombias competitiveness

• CO2 emission permits market
• Colombian permits supply (2010)
• Q(p) 0.872 0.192 p, for Q lt 26
  million tonnes of CO2

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CDM and IET International co-operation (PSI
collaboration)

• Methodological proposal based on the MARKAL
  family of models, for evaluating Kyoto
  flexibility mechanisms
• national MARKAL models for estimating CO2
  emission baselines
• develop a joint multinational MARKAL / MARKAL-ED
  linked by a global constraint for allocating
  reduction efforts
• identify optimal and potential technologies that
  could correspond to CDM projects
• Applications (Switzerland Colombia) show the
  attractiveness of CDM - IET schemes
• MARKAL family of models standard tools for
  identifying cost-efficient ways to curb CO2
  emission in the energy sector

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Joint MARKAL (O. Bakn, et al., 2000)

• MARKAL standard methodology for baselines
• Joint MARKAL equalise MRC

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CDM Results
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Switzerland Colombia CO2 emissions (million
tonnes) and undiscounted marginal reduction cost
(USD per tonne CO2)
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CDM Projects

• Industrial clean technology (boilers, furnaces
  and motors)
• efficiency improvements
• cleaner fuels
• Compressed natural gas for (urban) transportation
• Liquefied petroleum gas instead of
  (non-renewable) wood for cooking in the rural
  areas
• Efficient power plants for electricity
  generation
• industrial cogeneration plants
• gas turbine combined cycle
• small- and medium-scale hydropower plants

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CDM Projects (Swiss Kyoto)
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MARKAL-ED Trade (Bueler et al., 2000)

• Multiregional MARKAL model CO2 and fuels trade

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IET Results (CO2 millions tonnes)
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Sinks projects

• We modeled sinks in a MARKAL-type platform
• Not easy to identify /characterize forestry
  activities and land-use policies
• Performance of a forested area varies greatly
  among regions and tree species which makes its
  standardization difficult
• Understanding of the carbon sequestration and
  release cycle is not very deep
• Different kind of projects
• forestry plantations
• agroforestry systems
• biomass (energy) production
• Different trees by region
• Costa Atlántica Ecauliptus spp and Melina
• Valle del Cauca y Cauca Pinus spp and
  Eucaliptus spp
• Andina Alnus jorullensis and pinus spp
• Llanos Orientales Pinus caribaea

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Concluding remarks

• Linking source and sink reduction analysis
• Weak modeling tradition/skills in the
  environmental authorities, groups
• Focused on implementing CDM than elaborating a
  national policy
• Lack of information
• Sequestration activities requires specific data
• Data problems
• Wrongly stressed with liberalisation process
• Can not forbid us to build and use models
• Huge types/number of models . request a commom
  data bases ?
• Modeling issues
• GHGs analysis time horizon and key (scenarios)
  variables forecast
• Elasticities, AEEI
• Climate change concerns and discount rates