IDEAS home Printed from https://ideas.repec.org/p/ags/feemcl/121911.html
   My bibliography  Save this paper

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

Author

Listed:
  • Schmid, Eva
  • Knopf, Brigitte
  • Bauer, Nico

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.

Suggested Citation

  • Schmid, Eva & Knopf, Brigitte & Bauer, Nico, 2012. "REMIND-D: A Hybrid Energy-Economy Model of Germany," Climate Change and Sustainable Development 121911, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemcl:121911
    DOI: 10.22004/ag.econ.121911
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/121911/files/NDL2012-009.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.121911?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. Yamashita, Kei & Barreto, Leonardo, 2005. "Energyplexes for the 21st century: Coal gasification for co-producing hydrogen, electricity and liquid fuels," Energy, Elsevier, vol. 30(13), pages 2453-2473.
    5. 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.
    6. 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.
    7. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    8. 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.
    9. Schmid, Eva & Knopf, Brigitte, 2012. "Ambitious mitigation scenarios for Germany: A participatory approach," Energy Policy, Elsevier, vol. 51(C), pages 662-672.
    10. David Cass, 1965. "Optimum Growth in an Aggregative Model of Capital Accumulation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 32(3), pages 233-240.
    11. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
    12. 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.
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
    2. Hanna, Richard & Gross, Robert, 2021. "How do energy systems model and scenario studies explicitly represent socio-economic, political and technological disruption and discontinuity? Implications for policy and practitioners," Energy Policy, Elsevier, vol. 149(C).
    3. Schmid, Eva & Knopf, Brigitte, 2012. "Ambitious mitigation scenarios for Germany: A participatory approach," Energy Policy, Elsevier, vol. 51(C), pages 662-672.
    4. Ueckerdt, Falko & Brecha, Robert & Luderer, Gunnar & Sullivan, Patrick & Schmid, Eva & Bauer, Nico & Böttger, Diana & Pietzcker, Robert, 2015. "Representing power sector variability and the integration of variable renewables in long-term energy-economy models using residual load duration curves," Energy, Elsevier, vol. 90(P2), pages 1799-1814.
    5. 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.
    6. Zhang, Shuwei & Bauer, Nico & Yin, Guangzhi & Xie, Xi, 2020. "Technology learning and diffusion at the global and local scales: A modeling exercise in the REMIND model," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    7. Knopf, Brigitte & Nahmmacher, Paul & Schmid, Eva, 2015. "The European renewable energy target for 2030 – An impact assessment of the electricity sector," Energy Policy, Elsevier, vol. 85(C), pages 50-60.
    8. Martínez-Gordón, R. & Morales-España, G. & Sijm, J. & Faaij, A.P.C., 2021. "A review of the role of spatial resolution in energy systems modelling: Lessons learned and applicability to the North Sea region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    9. Morales-España, Germán & Martínez-Gordón, Rafael & Sijm, Jos, 2022. "Classifying and modelling demand response in power systems," Energy, Elsevier, vol. 242(C).
    10. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    11. Ludig, Sylvie & Schmid, Eva & Haller, Markus & Bauer, Nico, 2015. "Assessment of transformation strategies for the German power sector under the uncertainty of demand development and technology availability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 143-156.
    12. Shafiei, Ehsan & Davidsdottir, Brynhildur & Leaver, Jonathan & Stefansson, Hlynur & Asgeirsson, Eyjolfur Ingi, 2014. "Potential impact of transition to a low-carbon transport system in Iceland," Energy Policy, Elsevier, vol. 69(C), pages 127-142.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hübler, Michael & Baumstark, Lavinia & Leimbach, Marian & Edenhofer, Ottmar & Bauer, Nico, 2012. "An integrated assessment model with endogenous growth," Ecological Economics, Elsevier, vol. 83(C), pages 118-131.
    2. Bosetti, Valentina & Longden, Thomas, 2013. "Light duty vehicle transportation and global climate policy: The importance of electric drive vehicles," Energy Policy, Elsevier, vol. 58(C), pages 209-219.
    3. Enrica Cian & Samuel Carrara & Massimo Tavoni, 2014. "Innovation benefits from nuclear phase-out: can they compensate the costs?," Climatic Change, Springer, vol. 123(3), pages 637-650, April.
    4. Jouvet, Pierre-André & Schumacher, Ingmar, 2012. "Learning-by-doing and the costs of a backstop for energy transition and sustainability," Ecological Economics, Elsevier, vol. 73(C), pages 122-132.
    5. Haller, Markus & Ludig, Sylvie & Bauer, Nico, 2012. "Bridging the scales: A conceptual model for coordinated expansion of renewable power generation, transmission and storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2687-2695.
    6. Loschel, Andreas, 2002. "Technological change in economic models of environmental policy: a survey," Ecological Economics, Elsevier, vol. 43(2-3), pages 105-126, December.
    7. Naqvi, Asjad & Stockhammer, Engelbert, 2018. "Directed Technological Change in a Post-Keynesian Ecological Macromodel," Ecological Economics, Elsevier, vol. 154(C), pages 168-188.
    8. Duan, Hong-Bo & Zhu, Lei & Fan, Ying, 2014. "Optimal carbon taxes in carbon-constrained China: A logistic-induced energy economic hybrid model," Energy, Elsevier, vol. 69(C), pages 345-356.
    9. Carraro, Carlo & De Cian, Enrica & Nicita, Lea & Massetti, Emanuele & Verdolini, Elena, 2010. "Environmental Policy and Technical Change: A Survey," International Review of Environmental and Resource Economics, now publishers, vol. 4(2), pages 163-219, October.
    10. Alexeeva-Talebi, Victoria & Böhringer, Christoph & Löschel, Andreas & Voigt, Sebastian, 2012. "The value-added of sectoral disaggregation: Implications on competitive consequences of climate change policies," Energy Economics, Elsevier, vol. 34(S2), pages 127-142.
    11. Diana Dimitrova, 2018. "The 2018 Nobel Prize in Economics," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 98-152.
    12. Enrica De Cian & Valentina Bosetti & Alessandra Sgobbi & Massimo Tavoni, 2009. "The 2008 WITCH Model: New Model Features and Baseline," Working Papers 2009.85, Fondazione Eni Enrico Mattei.
    13. Sergey Paltsev, 2016. "Energy Scenarios: The Value and Limits of Scenario Analysis," EcoMod2016 9371, EcoMod.
    14. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    15. De Cian, Enrica, 2006. "International Technology Spillovers in Climate-Economy Models: Two Possible Approaches," Climate Change Modelling and Policy Working Papers 12040, Fondazione Eni Enrico Mattei (FEEM).
    16. Popp, David & Santen, Nidhi & Fisher-Vanden, Karen & Webster, Mort, 2013. "Technology variation vs. R&D uncertainty: What matters most for energy patent success?," Resource and Energy Economics, Elsevier, vol. 35(4), pages 505-533.
    17. Kosugi, Takanobu, 2023. "Learning rate matters: Reexamining optimal power expansion planning with endogenized technological experience curves," Energy, Elsevier, vol. 283(C).
    18. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    19. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    20. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.

    More about this item

    Keywords

    Resource /Energy Economics and Policy;

    JEL classification:

    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:feemcl:121911. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/feemmit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.