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1 Coupling bottom-up and top-down energy models: challenges and results with TIAM and GEMINI-E3 Maryse Labriet 1, Marc Vielle 2, Laurent Drouet 3, Alain.

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Presentation on theme: "1 Coupling bottom-up and top-down energy models: challenges and results with TIAM and GEMINI-E3 Maryse Labriet 1, Marc Vielle 2, Laurent Drouet 3, Alain."— Presentation transcript:

1 1 Coupling bottom-up and top-down energy models: challenges and results with TIAM and GEMINI-E3 Maryse Labriet 1, Marc Vielle 2, Laurent Drouet 3, Alain Haurie 4, Amit Kanudia 5, Richard Loulou 6 1 Kanlo Consultants, France and Spain 2 Ecole Polytechnique de Lausanne and ORDECSYS, Switzerland 3 Ecole Polytechnique de Lausanne, Switzerland 4 University of Geneva and ORDECSYS, Switzerland 5 Kanors Consulting, India 6 Kanlo Consultants, France International Energy Workshop Venice (Italy), June 17 th, 2009 TOCSIN

2 2 Aims of coupling Enhance the description of world energy system by combining the strengths of the two models : 1.Detailed technological representation of the energy system of ETSAP-TIAM allowing the endogenous computation of (amongst others) energy flows and prices 2.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

3 3 GEMINI-E3 General Equilibrium Model 28 countries/regions – 18 sectors CO 2 and other GHG Reference year 2001 – based on GTAP database Time period Website:

4 4 ETSAP-TIAM Technology rich, dynamic inter-temporal partial equilibrium representing the entire energy systems 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 ( is used here) Website: (Energy Technology System Analysis Programme)

5 5 Connecting the models: regions, sectors and commodities Choose a common regional aggregation level TIAM GEMINI-E3

6 6 Connecting the models: regions, sectors and commodities 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.

7 7 Coupling Framework GEMINI-E3 TIAM Demand functions demand=driver elast Energy mix Energy prices Technical progress Investments Cost CO2 price Drivers: GDP Industrial outputs Service demands Harmonisation of the two models (POP, GDP, energy prices, some energy constraints) Coupling of the two models COUPLINGCOUPLING

8 8 Coupling Algorithm Starting point: harmonized models (GDP, POP, energy prices)

9 9 Case study: World Climate Agreement Radiative forcing limited to 3.5 W/m 2 ( , 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?

10 10 Convergence Achieved at iteration 4 Convergence criteria

11 11 Some verifications  No difference between Coupled models and TIAM-Elast  Of course, energy service reductions help for mitigation (lower CO2 price than w/o elasticities) CO2 emissions (GtC/yr)

12 12 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 models? 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 agriculture. Demands for non-road transport (aviation, navigation) are more drastically reduced in TIAM-Elast More complex dynamics in the industry sector, while in TIAM- Elast, all industrial energy services decrease

13 13 Industrial sector

14 14 Example: the Iron&Steel sector Relative values of production w.r.t. Ref Domestic production = Domestic demand + Exports - Imports Decision factors Relative values of domestic consumption and trade w.r.t. Ref

15 15 Some macro-economic effects (from GEMINI-E3) Energy exporting countries: loss of terms of trade Other affected countries: where the energy intensive industry is strong Importing countries / high energy efficiency: smaller costs

16 16 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 reduced?

17 17 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 W/m2 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)

18 18 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 moderate No increase of emissions thanks to the decrease of World oil consumption  less extraction  less emissions Macro-economic costs reduced for non-OECD countries

19 19 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

20 20 Conclusion 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

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