Coupling%20bottom-up%20and%20top-down%20energy%20models:%20challenges%20and%20results%20with%20TIAM%20and%20GEMINI-E3%20Maryse%20Labriet1,%20Marc%20Vielle2,%20Laurent%20Drouet3,%20Alain%20Haurie4,%20Amit%20Kanudia5,%20Richard%20Loulou6%201%20Kanlo%20Consultants,%20France%20and%20Spain%202%20Ecole%20Polytechnique%20de - PowerPoint PPT Presentation

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1 Kanlo Consultants, France and Spain. 2 Ecole Polytechnique de Lausanne and ORDECSYS, Switzerland ... Polytechnique de Lausanne, Switzerland. 4 University ... – PowerPoint PPT presentation

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Title: Coupling%20bottom-up%20and%20top-down%20energy%20models:%20challenges%20and%20results%20with%20TIAM%20and%20GEMINI-E3%20Maryse%20Labriet1,%20Marc%20Vielle2,%20Laurent%20Drouet3,%20Alain%20Haurie4,%20Amit%20Kanudia5,%20Richard%20Loulou6%201%20Kanlo%20Consultants,%20France%20and%20Spain%202%20Ecole%20Polytechnique%20de

Coupling bottom-up and top-down energy models
challenges and results with TIAM and
GEMINI-E3Maryse Labriet1, Marc Vielle2, Laurent
Drouet3, Alain Haurie4, Amit Kanudia5, Richard
Loulou61 Kanlo Consultants, France and Spain2
Ecole Polytechnique de Lausanne and ORDECSYS,
Switzerland 3 Ecole Polytechnique de Lausanne,
Switzerland4 University of Geneva and ORDECSYS,
Switzerland5 Kanors Consulting, India6 Kanlo
Consultants, FranceInternational Energy
WorkshopVenice (Italy), June 17th, 2009
Aims of coupling
  • Enhance the description of world energy system
    by combining the strengths of the two models
  • Detailed technological representation of the
    energy system of ETSAP-TIAM allowing the
    endogenous computation of (amongst others) energy
    flows and prices
  • General equilibrium effects of GEMINI-E3 allowing
    the explicit representation of the main economic
    factors (labor, consumption, capital, etc.) and
    their interactions with the energy service demands

  • General Equilibrium Model
  • 28 countries/regions 18 sectors
  • CO2 and other GHG
  • Reference year 2001 based on GTAP database
  • Time period 2001- 2050
  • Website http//

  • Technology rich, dynamic inter-temporal partial
    equilibrium representing the entire energy
  • Based on maximum total surplus (via LP) with own
    price elastic service demands
  • Driven by demands for energy services. eg. tons
    aluminium, km car travel, etc.
  • 15 regions linked by trades of 9 energy
    commodities emissions
  • CO2 and other GHGs
  • Reference year 2005 IEA Energy Statistics
  • Time horizon 2005-2100 (2005-2050 is used here)
  • Website (Energy
    Technology System Analysis Programme)

Connecting the models regions, sectors and
  • Choose a common regional aggregation level

Connecting the models regions, sectors and
  • Create connections between the two activity
    classifications (the two models are based on two
    different data sets)
  • Additions of activity sectors in GEMINI-E3
    hydrogen, biomass, adjusted share of other
    non-fossil fuels.

Coupling Framework
  • Harmonisation of the two models (POP, GDP, energy
    prices, some energy constraints)
  • Coupling of the two models

Energy mix Energy prices Technical
progress Investments Cost CO2 price
DriversGDP Industrial outputs
Service demands
Coupling Algorithm
Starting point harmonized models (GDP, POP,
energy prices)
Case study World Climate Agreement
  • Radiative forcing limited to 3.5 W/m2 (2005-2050,
    no overshooting)
  • Full World cooperation
  • All sectors
  • All countries
  • Only one carbon price for each time period,
    equivalent to a tax applied to all sectors and
    all countries
  • What do we learn from the coupling?

Achieved at iteration 4
Some verifications
CO2 emissions (GtC/yr)
  • No difference between Coupled models and
  • Of course, energy service reductions help for
    mitigation (lower CO2 price than w/o elasticities)

Focus on final energy services
  • Expected added value of the coupling of TIAM and
    GEMINI-E3 better representation of the factors
    influencing the demands for energy services,
    globally and more importantly, regionally
  • What is observed in the results of the Coupled
  • Agriculture, commercial, residential and road
    transport behave similarly in both approaches,
    with slightly higher reductions in the Coupled
    models in residential and non-road sectors, and
    slightly smaller reduction in commercial and
  • Demands for non-road transport (aviation,
    navigation) are more drastically reduced in
  • More complex dynamics in the industry sector,
    while in TIAM-Elast, all industrial energy
    services decrease

Industrial sector
Example the IronSteel sector
Relative values of production w.r.t. Ref
Domestic production Domestic demand Exports-
Decision factors
Relative values of domestic consumption and trade
w.r.t. Ref
Some macro-economic effects (from GEMINI-E3)
  • Energy exporting countries loss of terms of
  • Other affected countries where the energy
    intensive industry is strong
  • Importing countries / high energy efficiency
    smaller costs

Other applications Partial Climate Agreements
  • (S2) Climate Agreement Limited to the Energy
    Intensive Industries in Non-OECD in order to
    avoid penalizing too much the households
    (residential and transport) but also to limit the
    loss of competitiveness of developed countries.
    Same target 3.5 W/m2.
  • (S2B) Climate Agreement Limited to the
    Electricity generation of Non-OECD countries.
    Target 3.5 W/m2 infeasible. Target 4.0 W/m2.
  • What are the impacts on the energy system?
  • Are there emissions / investment leakages?
  • Are the costs supported by Non-OECD countries

Some of the technology decisions
  • S1 Full Cooperation 3.5 W/m2
  • S2 Only Energy Intensive Sectors of Non-OECD
    3.5 W/m2
  • S2B Only Electricity Sectors of Non-OECD 4.0
  • More electricity consumed in S2 wrt S1 by
    industry in all countries, and by residential in
    OECD only. No increase of electricity consumed in
    Non-OECD in S2B
  • Electricity generation by plants with CCS and
    renewable in all scenarios
  • Increase of emissions of the residential sector
    of Non-OECD countries in both scenarios biomass
    consumed in residential is transferred to
    industry and power plants, and replaced by coal
  • No rebound of oil consumption in Non-OECD
  • Displacement of gas extraction in S2B when Supply
    is excluded form the Climate agreement (AFR, FSU)

Other effects leakages?
  • Industrial productions and trade variations of S2
    (where industry of Non-OECD is covered by the
    Climate agreement) follow the same trends as in
    S1 (full cooperation)
  • There is displacement of some energy intensive
    industries in S2B when industry is excluded from
    the Climate agreement (AFR, MEA), but remains
  • No increase of emissions thanks to the decrease
    of World oil consumption ? less extraction ? less
  • Macro-economic costs reduced for non-OECD

Macro-economic impacts(surplus in of
households final consumption)
  • S2 more costly for developed countries than the
    full coop (S1), since the CO2 price is higher
  • Developing countries are better households are
    exempted from carbon taxation and benefit from
    the decrease of fossil fuel prices vs Reference
  • Energy exporting countries are especially better
    since the World energy consumption does not
    decrease so much
  • S2B smaller costs (more acceptable?), but less
    strict environmental target

  • Fine technology and energy analysis (mix, prices,
    technical progress) provided by ETSAP-TIAM
  • Fine macro-economic analysis (GDP, sectoral
    outputs) provided by GEMINI-E3. Finer
    representation of the variations of the demands
    for energy services, especially at the regional
    level (possible displacement of the production).
  • Crucial (and not easy) Connections between the
    two models
  • Complexity in the understanding of the results,
    especially the macro-economic ones, since
    GEMINI-E3 is the most altered model in the
    coupled approach