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Challenges in Soft-Linking: The Case of EMEC and TIMES-Sweden

Author

Listed:
  • Riekkola, Anna Krook

    (Luleå University of Technology)

  • Berg, Charlotte

    () (National Institute of Economic Research)

  • Ahlgren, Erik O.

    (Chalmers University of Technology)

  • Söderholm, Patrik

    (Luleå University of Technology)

Abstract

The aim of this study is to develop a method for how to soft-link a Computable General Equilibrium (CGE) model with a energy system model. The central research question is how the interaction between modellers and models can, both qualitatively and quantitatively, enable and facilitate a transparent energy and climate policy decision-making process at the national level. The paper describes this development in detail, and presents and discusses the results of the soft-linking methodology applied to a climate scenario. Important similarities and differences between two Swedish models, i.e. EMEC (a CGE model) and TIMES-Sweden (an energy system model), are identified. These findings are used to develop a robust and transparent method to translate simulation results between the two models, resulting in intermediate ‘translation models’ between EMEC and TIMES-Sweden. EMEC provides demand input to TIMES, while TIMES provides feedback on the energy efficiency parameters, the energy mix, and the prices of electricity and heat. These ‘translations’ can also be used stand-alone to feed into other energy system models. The presented soft-linking process demonstrates the importance of linking an energy system model with a macroeconomic model when studying energy and climate policy. With the same exogenous parameters, the soft-linking between the models results in a new picture of the economy and the energy system in 2035 compared with the corresponding model results in the absence of soft-linking. The study also leads to a better understanding of how the models can interact while preserving the respective models' strengths, to give an improved picture of both the flows in the economy and the impact of energy policy instruments.

Suggested Citation

  • Riekkola, Anna Krook & Berg, Charlotte & Ahlgren, Erik O. & Söderholm, Patrik, 2013. "Challenges in Soft-Linking: The Case of EMEC and TIMES-Sweden," Working Papers 133, National Institute of Economic Research.
  • Handle: RePEc:hhs:nierwp:0133
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    References listed on IDEAS

    as
    1. Xavier Labandeira, Pedro Linares and Miguel Rodriguez, 2009. "An Integrated Approach to Simulate the impacts of Carbon Emissions Trading Schemes," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    2. Jean Charles Hourcade & Mark Jaccard & Chris Bataille & Frédéric Ghersi, 2006. "Hybrid Modeling: New Answers to Old Challenges," Post-Print halshs-00471234, HAL.
    3. Patricia Fortes & Sofia Simões & Júlia Seixas & Denise Van Regemorter & Francisco Ferreira, 2013. "Top-down and bottom-up modelling to support low-carbon scenarios: climate policy implications," Climate Policy, Taylor & Francis Journals, vol. 13(3), pages 285-304, May.
    4. Krook Riekkola, Anna & Ahlgren, Erik O. & Söderholm, Patrik, 2011. "Ancillary benefits of climate policy in a small open economy: The case of Sweden," Energy Policy, Elsevier, vol. 39(9), pages 4985-4998, September.
    5. Böhringer, Christoph & Rutherford, Thomos F., 2009. "Integrated assessment of energy policies: Decomposing top-down and bottom-up," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1648-1661, September.
    6. Göran Östblom & Eva Samakovlis, 2007. "Linking health and productivity impacts to climate policy costs: a general equilibrium analysis," Climate Policy, Taylor & Francis Journals, vol. 7(5), pages 379-391, September.
    7. Messner, Sabine & Schrattenholzer, Leo, 2000. "MESSAGE–MACRO: linking an energy supply model with a macroeconomic module and solving it iteratively," Energy, Elsevier, vol. 25(3), pages 267-282.
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    Cited by:

    1. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    2. repec:eee:rensus:v:75:y:2017:i:c:p:21-34 is not listed on IDEAS
    3. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    4. repec:eee:appene:v:210:y:2018:i:c:p:499-517 is not listed on IDEAS

    More about this item

    Keywords

    Soft-linking; Computable General equilibrium; TIMES/MARKAL; Climate policy; Energy policy;

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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