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Coupling bottom-up and top-down energy models: challenges and results

with TIAM and GEMINI-E3

Maryse Labriet1, Marc Vielle2, Laurent Drouet3, Alain Haurie4, Amit Kanudia5, Richard Loulou6

1 Kanlo Consultants, France and Spain2 Ecole Polytechnique de Lausanne and ORDECSYS, Switzerland

3 Ecole Polytechnique de Lausanne, Switzerland4 University of Geneva and ORDECSYS, Switzerland

5 Kanors Consulting, India6 Kanlo Consultants, France

International Energy WorkshopVenice (Italy), June 17th, 2009

TOCSIN

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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

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GEMINI-E3

• 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://www.gemini-e3.net/

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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 2005-2100 (2005-2050 is used here)• Website: www.etsap.org/documentation (Energy Technology

System Analysis Programme)

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Connecting the models: regions, sectors and commodities

• Choose a common regional aggregation level

TIAM GEMINI-E3

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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.

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Coupling Framework

GEMINI-E3 TIAM

Demand functionsdemand=driverelast

Energy mixEnergy prices

Technical progressInvestments 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

COUPLING

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Coupling Algorithm

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

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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?

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Convergence

Achieved at iteration 4

Convergence criteria

0.0%

2.5%

5.0%

7.5%

10.0%

0 2 4 6 8 10Iteration

Conv

erge

nce

crite

ria

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0

5

10

15

20

25

2005 2015 2025 2035 2045

GtC

REF

Coupled models (3.5 W/m2)

TIAM-Elast (3.5 W/m2)

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 price ($/tCO2)

281

324

0

100

200

300

400

2005 2015 2025 2035 2045

$/tC

O2

Coupled modelsTIAM-elastNo elast

Global crude oil price

0

2

4

6

8

10

12

14

2005 2015 2025 2035 2045

$/G

J

REFCoupled (3.5 W/m2)TIAM-Elast (3.5 W/m2)

CO2 emissions (GtC/yr)

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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

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Variations (TIAM-Elast vs Reference) of industrial service demands at the World level

-10%

-8%

-6%

-4%

-2%

0%

Che

mic

al

Iron

and

Ste

el

Pul

p an

dpa

per

Non

-fe

rrou

s

Non

-m

etal

Oth

erin

dust

ry

2010

2020

2030

2040

2050

Industrial sectorVariations (Coupled models vs Reference) of industrial service

demands at the World level

-20%

-15%

-10%

-5%

0%

5%

Che

mic

al

Iron

and

Ste

el

Pul

p an

dpa

per

Non

-fe

rrou

s

Non

-m

etal

Oth

erin

dust

ry

2010

2020

2030

2040

2050

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Example: the Iron&Steel sector

Variations (Coupled models vs Reference) of Iron and Steel Production in 2050 (%)

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

AF

R

AU

S

CA

N

CH

I

CS

A

EE

U

FS

U

IND

JPN

ME

A

ME

X

OD

A

SK

O

US

A

WE

U

Relative values of production w.r.t. Ref

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

EUR XEU FSU USA CAN AUZ JAP MEX CHI IND ASI LAT MID AFR

Export variation

Import variation

Domestic demand variation

Domestic production =

Domestic demand+ Exports- Imports

Decision factors

Relative values of domestic consumption and trade w.r.t. Ref

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Some macro-economic effects (from GEMINI-E3)

-13%

-11%

-9%

-7%

-5%

-3%

-1%

1%

EUR XEU FSU USA CAN AUZ JAP MEX LAT MID CHI IND ASI AFR

GDP

Consumption

Surplus

• 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

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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?

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Some of the technology decisionsGHG emissions (GtC-equiv)

0

10

20

30

2000 2010 2020 2030 2040 2050

GtC

-equ

iv p

er y

ear

ReferenceS1S2S2B

CO2 price

0

200

400

600

2000 2010 2020 2030 2040 2050

$/tC

O2

-eq

ui

S1

S2

S2B

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)

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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

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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

-14%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2%EUR XEU FSU USA CAN AUZ JAP MEX LAT MID CHI IND ASI AFR World

Scenario 1

Scenario 2

Scenario 2b

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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