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REMIND-D: A Hybrid Energy-Economy Model of Germany

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Author Info

  • Eva Schmid

    (Potsdam Institute for Climate Impact Research)

  • Brigitte Knopf

    (Potsdam Institute for Climate Impact Research)

  • Nico Bauer

    (Potsdam Institute for Climate Impact Research)

Abstract

This paper presents a detailed documentation of the hybrid energy-economy model REMIND-D. REMIND-D is a Ramsey-type growth model for Germany that integrates a detailed bottom-up energy system module, coupled by a hard link. The model provides a quantitative framework for analyzing long-term domestic CO2 emission reduction scenarios. Due to its hybrid nature, REMIND-D facilitates an integrated analysis of the interplay between technological mitigation options in the different sectors of the energy system as well as overall macroeconomic dynamics. REMIND-D is an intertemporal optimization model, featuring optimal annual mitigation effort and technology deployment as a model output. In order to provide transparency on model assumptions, this paper gives an overview of the model structure, the input data used to calibrate REMIND-D to the Federal Republic of Germany, as well as the techno-economic parameters of the technologies considered in the energy system module.

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Bibliographic Info

Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2012.09.

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Date of creation: Feb 2012
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Handle: RePEc:fem:femwpa:2012.09

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Keywords: Hybrid Model; Germany; Energy System; Domestic Mitigation;

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References

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  1. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
  2. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
  3. Nico Bauer & Ottmar Edenhofer & Socrates Kypreos, 2008. "Linking energy system and macroeconomic growth models," Computational Management Science, Springer, vol. 5(1), pages 95-117, February.
  4. Fichtner, W. & Goebelt, M. & Rentz, O., 2001. "The efficiency of international cooperation in mitigating climate change: analysis of joint implementation, the clean development mechanism and emission trading for the Federal Republic of Germany, th," Energy Policy, Elsevier, vol. 29(10), pages 817-830, August.
  5. Blesl, Markus & Das, Anjana & Fahl, Ulrich & Remme, Uwe, 2007. "Role of energy efficiency standards in reducing CO2 emissions in Germany: An assessment with TIMES," Energy Policy, Elsevier, vol. 35(2), pages 772-785, February.
  6. Landry, Maurice & Malouin, Jean-Louis & Oral, Muhittin, 1983. "Model validation in operations research," European Journal of Operational Research, Elsevier, vol. 14(3), pages 207-220, November.
  7. Valentina Bosetti, Carlo Carraro, Marzio Galeotti, Emanuele Massetti, Massimo Tavoni, 2006. "A World induced Technical Change Hybrid Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 13-38.
  8. Hourcade, Jean-Charles & Robinson, John, 1996. "Mitigating factors : Assessing the costs of reducing GHG emissions," Energy Policy, Elsevier, vol. 24(10-11), pages 863-873.
  9. Meyer, Bernd & Distelkamp, Martin & Wolter, Marc Ingo, 2007. "Material efficiency and economic-environmental sustainability. Results of simulations for Germany with the model PANTA RHEI," Ecological Economics, Elsevier, vol. 63(1), pages 192-200, June.
  10. McDowall, William & Eames, Malcolm, 2006. "Forecasts, scenarios, visions, backcasts and roadmaps to the hydrogen economy: A review of the hydrogen futures literature," Energy Policy, Elsevier, vol. 34(11), pages 1236-1250, July.
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Cited by:
  1. Schmid, Eva & Pahle, Michael & Knopf, Brigitte, 2013. "Renewable electricity generation in Germany: A meta-analysis of mitigation scenarios," Energy Policy, Elsevier, vol. 61(C), pages 1151-1163.

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