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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications Economic and technology uncertainty and implications for

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Economic and technology uncertainty and implications for policy advise

Fr´ ed´ eric Babonneau and Alain Haurie

ORDECSYS, 4 place de l’Etrier, 1224, Chˆ ene-Bougeries, Switzerland

Bruxelles, 8 June 2010

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Outline

1

Methods and models

2

Uncertainty and role of CCS in abatement strategies

3

Uncertainty on other drivers

4

New methods to tackle uncertainty analysis for energy/climate policy

5

Publications

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Outline

1

Methods and models

2

Uncertainty and role of CCS in abatement strategies

3

Uncertainty on other drivers

4

New methods to tackle uncertainty analysis for energy/climate policy

5

Publications

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

A Gamut of Models and Methods

We used 6 Economy-Energy-Environmental models ...

3 bottom-up models : TIAM, TIAMEC and TIMES PanEU. 3 top-down models : WITCH, DEMETER and GEMINI-E3.

... and implemented the most advanced stochastic methods ...

Stochastic and Dynamic programming Robust Optimization Monte-Carlo and Parametric programming

... to address the questions :

How important can be CCS in abatement strategies ? What could be the CCS impacts in a long-term horizon ? What are the main sources of uncertainty impacting the success of climate policies ? How to robustify energy policies under uncertainty ?

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Outline

1

Methods and models

2

Uncertainty and role of CCS in abatement strategies

3

Uncertainty on other drivers

4

New methods to tackle uncertainty analysis for energy/climate policy

5

Publications

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Uncertainties concerning CCS

Uncertainties into consideration Mid-term CCS uncertainty : cost, date of availability, storage capacities. Long-term CCS uncertainty : leakage. Uncertainty of policy scenarios : level of carbon tax in the future. Used models in the analysis 3 bottom-up models : TIAM, TIAMEC and TIMES PanEU 2 mid-term top-down models : WITCH and GEMINI-E3 1 long-term top-down model : DEMETER

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Main insights for CCS deployment

Analysis with WITCH stochastic

1

Uncertainty on long term carbon tax (resolved in 2030)⇒

2

The implementation of CCS technologies appears to be a good bridging option before the next generation of carbon free technologies become competitive (solar, especially). ⇒

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Main insights on CCS leakage

Analysis with DEMETER

1

When assuming a 1%/yr leakage rate the effectiveness and attractiveness of CCS is : ⇒

not reduced with a high value for the discount rate (about 3%) and moderate long-term climate change damages reduced very substantially with a prescriptive low value for the discount rate (about 1%)

2

The uncertainties regarding the leakage rate and the extent of climate-induced damages to the global economy should not prevent us from using CCS on a large scale. ⇒

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Main insights from TIAM stochastic

The method of stochastic programming is implemented on TIAM ⇒ The possible concentration profiles ⇒ The possible emission profiles ⇒ The contribution of CCS and forestry for sequestration ⇒

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Conclusion of the study with TIMES PanEU

Using parametric analysis

The results show a high influence of climate policy on the market share of CCS power plants. Under an ambitious climate policy regime (-83% in 2050 compared to Kyoto base) the electricity demand increases up to 6500 TWh in 2050 in the EU-27 plus Norway, Switzerland and Iceland (EU-27+3), driven by the change of the end use sectors towards electric applications. This increase is accompanied by a strong emission reduction in the public heat and electricity sector, which contributes importantly to the achievement of the

  • verall GHG reduction target. Thereby CCS technologies play an important role,

achieving a maximum market share in the EU-27+3 in 2050 of almost 40% (2500 TWh) of total electricity generation under a -83% climate target. However under less tight climate targets (here -74% in 2050 compared to Kyoto base) the market share amounts to a maximum of 30% (1700 TWh) in 2050.

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Outline

1

Methods and models

2

Uncertainty and role of CCS in abatement strategies

3

Uncertainty on other drivers

4

New methods to tackle uncertainty analysis for energy/climate policy

5

Publications

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

SP/MC analysis with TIAM and GEMINI-E3

Uncertainties into consideration Climate sensitivity Price of oil Economic growth Methods and models We used SP with the bottom-up model TIAM and MCA with the global top-down model GEMINI-E3.

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Main conclusion

1

The price of oil and behind it the behaviour of OPEC affects the possibility of reaching a target climate. The climate negotiation must therefore incorporate the specificities of these countries.

2

The impact of uncertainty of the climate sensitivity parameter Cs is major, requiring the implementation of early actions (before 2040) in order to reach the temperature target. The “wait and see” approach is not recommended.⇒

3

Economic growth: For GEMINI-E3, the economic development of Asia is a decisive factor in the cost and the success of a climate policy. China and India have to be integrated as soon as possible in the climate agreement. For TIAM, the uncertainty of the GDP growth rates has very little impact

  • n pre-2040 decisions compared to the climate sensitivity uncertainty.

Need for a basket of carbon technologies : There is not a single silver-bullet technology to combat carbon emissions and CCS alone cannot provide the solution to climate change. ⇒

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Outline

1

Methods and models

2

Uncertainty and role of CCS in abatement strategies

3

Uncertainty on other drivers

4

New methods to tackle uncertainty analysis for energy/climate policy

5

Publications

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Robust Optimization to Analyse Security of EU energy supply

Uncertainties of energy supply routes to EU Technical problems on pipelines and tankers. Commercial and political stakes between suppliers and EU. etc ... Used model We used the global bottom-up model TIAM. Main conclusions derived from robust analysis

1

The results advise a higher diversification and a significant reduction of the concentration of supply sources, a feature that is desirable in itself.⇒

2

The supply of energy is guaranteed with a known and high probability.

3

Such reliability is achieved at what may be considered moderate an extra cost, not exceeding 0.7% of the total EU energy cost.

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Outline

1

Methods and models

2

Uncertainty and role of CCS in abatement strategies

3

Uncertainty on other drivers

4

New methods to tackle uncertainty analysis for energy/climate policy

5

Publications

Alain Haurie Stochastic analysis

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Methods and models Uncertainty and role of CCS in abatement strategies Uncertainty on other drivers New methods to tackle uncertainty analysis for energy/climate policy Publications

Published papers

  • O. Bahn, A. Haurie, and R. Malham. A stochastic control model for optimal timing of

climate policies. automatica, 44:1545-1558, 2008.

  • F. Babonneau, J.-P. Vial, and R. Apparigliato. Robust optimization for environmental and

energy planning. In J.A. Filar and A. Haurie, editors, Handbook on ”Uncertainty and Environmental Decision Making”, International Series in Operations Research and Management Science, pages 79-126, 2010 Submitted papers in a special issue of Environmental Modelling and Assessment

  • F. Babonneau, A. Haurie, R. Loulou and M. Vielle. Uncertainty and Economic Analysis of

Energy and Climate Policies using TIAM and GEMINI-E3 models.

  • R. Gerlagh and B.C.C. van der Zwaan. Evaluating Carbon Capture et Sequestration in

Perspective of the Very Long Term.

  • T. Kober and M. Blesl. Perspectives of CCS in Europe considering technical and economic

power plant uncertainties.

  • F. Babonneau, A. Kanudia, M. Labriet, R. Loulou and J.-P. Vial. Energy Security: a Robust

Programming Approach and Application to European Energy Supply via TIAM. I.J. Keppo and B.C.C. van der Zwaan. The role of CCS in long-term climate mitigation: the impact of uncertain CO2 storage availability.

  • E. De Cian and M. Tavoni. Hedging against climate policy and technology uncertainty:

implications for technology mix and policy instrument choice.

Alain Haurie Stochastic analysis

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Fossil fuel emissions

Return 10 20 30 40 50 60 70 2010 2015 2020 2025 2030 2035 2040 2045 2050 GtCO2­eq Optimal det high tax det low tax determinist equivalent Alain Haurie Stochastic analysis

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Hedging against uncertain carbon tax

Return

50 100 150 200 250 2010 2015 2020 2025 2030 US$ Billion 200 400 600 800 1000 1200 2010 2015 2020 2025 2030 2035 GW

deterministic equivalent (1) stochastic optimal control (2)

NUCLEAR (1) NUCLEAR (2) CCS (1) CCS (2) W&S (1) W&S (2)

WITCH model simulation: The carbon tax level after 2030 can be high or low (equal probability) Investments ($ 109) and installed capacity (GW) for typical energy technologies (World level)

Alain Haurie Stochastic analysis

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Optimal CCS and CCS effectiveness

Return

10 20 30 40 50 60 70 2000 2020 2040 2060 2080 2100 [tCO2/yr] S1 S2 S3 S4 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2000 2020 2040 2060 2080 2100 [CCS effectiveness] S1 S2 S3 S4

S1: high discounting low damage low leakage; S2: High disc. high damage and low leakage; S3: low disc., high dam. low leak; S4: low disc. high dam. high leak. DEMETER simulation: CO2 capture (Gt/yr) Efficiency of CCS (%) (World level)

Alain Haurie Stochastic analysis

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Optimal CCS inflow

Return

10 20 30 40 50 60 70 2000 2020 2040 2060 2080 2100 [tCO2/yr] low dam, high leak low dam, low leak high dam, high leak high dam, low leak

Stochastic scenario; uncertainty resolves in 2050 DEMETER simulation: CCS inflow (in GtCO2/yr) (World level)

Alain Haurie Stochastic analysis

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Event tree for TIAM simulations

Return

GDP=High, Cs=1.5 ºC GDP=High, Cs=3.0 ºC GDP=High, Cs=5 ºC GDP=High, Cs=8 ºC GDP=Low, Cs=1.5 ºC GDP=Low, Cs=3 ºC GDP=Low, Cs=5 ºC GDP=Low, Cs=8 ºC

1998- 2002 2003- 2008 2009- 2020 2021- 2039 2040- 2060 2061- 2080 2081- 2100 TIMES periods 2000 2005 2015 2030 2050 2070 2090 Alain Haurie Stochastic analysis

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Concentration profiles in TIAM simulations

Return Base Case: 558 ppm 531 ppm 526 ppm 469 ppm 373 ppm 350 400 450 500 550 600 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 Atmospheric concentration (ppm CO2 equiv) PF Cs=1.5ºC (=Basecase) PF Cs=3ºC PF Cs=5ºC PF Cs=8ºC HEDGING Cs=1.5ºC HEDGING Cs=3ºC HEDGING Cs=5ºC HEDGING Cs=8ºC 423 ppm Alain Haurie Stochastic analysis

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Contribution of CCS and forestry in TIAM simulations

Return Alain Haurie Stochastic analysis

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Emission profiles in TIAM simulations

Return 14.1 9.7 4.4 2.7 12.0 11.5 4.5 2.0 2 4 6 8 10 12 14 16 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 GHG (GtC-equiv). BC = PF 1.5ºC PF 3ºC PF 5ºC PF 8ºC HEDGING 1.5ºC HEDGING 3ºC HEDGING 5ºC HEDGING 8ºC Alain Haurie Stochastic analysis

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Uncertainty in emissions projections.

Return 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 5 10 15 20 25 30 World GHG emissions in GT C−eq Unconstraint simulations 100% 50% Cs=4.4 Cs=2.9 Cs=1.7 Cs=1.1 Alain Haurie Stochastic analysis

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Energy consumption and Electricity generation in 2050

Return

1 2 3 4 5 6 7 8 9 10 11 Coal BAU Coal Scenario Oil BAU Oil scenario Gas BAU Gas scenario

  • Elec. BAU
  • Elec. scenario

Gtoe 10000 20000 30000 Coal BAU Coal scenario Oil BAU Oil scenario Gas BAU Gas scenario Nuclear BAU Nuclear sc.

  • Renew. BAU
  • Renew. sc.

Twh

GEMINI-E3 model MC simulation: Primary energy (Gtoe) and electricity generation (Twh) for BAU and Policy random scenarios (World level)

Alain Haurie Stochastic analysis