A Scandinavian Transition Towards a Carbon-Neutral Energy System

Part of the Lecture Notes in Energy book series (LNEN, volume 64)


This study demonstrates a cost-optimal transition towards a carbon neutral energy system in Scandinavia (Denmark, Norway and Sweden) in 2050 with no import of biofuels and no use of CO2 storage. The Scandinavian electricity sector is already highly renewable and carbon neutrality requires extensive changes in other parts of the energy system, including the building, transport and industry sectors. The analysis is done with a stochastic TIMES model that considers the short-term uncertainty of renewable electricity generation and heat demand. In this study, a simplified deterministic approach gives significantly lower investments in wind power, PV and low-efficient electricity based heating in buildings compared to the stochastic analysis. This implies that an appropriate representation of short-term uncertainty is an important premise to provide reasonable policy recommendations from energy system models. Moreover, carbon neutrality requires significant decarbonization of the end-use sectors, especially the transport sector. Hydrogen is the dominant fuel used in the transport sector, and it is cost-optimal to invest in both inflexible hydrogen production and more capital intensive flexible hydrogen production. The results emphasise the importance of considering the entire energy system when designing policy to reach carbon neutrality. This is because the required investments in electricity capacity depend on the degree of electrification, and the future electricity consumption depends on the availability and competiveness of biofuels.


  1. Danish Energy Agency (2017a) Basisfremskrivning 2017. Available at https://ens.dk/sites/ens.dk/files/Forsyning/bf2017_hovedpublikation_13_mar_final.pdf
  2. Danish Energy Agency. (2017b) Dansk klimapolitik (Danish Climate Policy). Available at https://ens.dk/ansvarsomraader/energi-klimapolitik/fakta-om-dansk-energi-klimapolitik/dansk-klimapolitik
  3. Eurostat (2017) Environment and energy. Available at http://ec.europa.eu/eurostat/data/database
  4. Higle LJ (2005) Stochastic programming: optimization when uncertainty matters. Tutorials in Operational Research, New Orleans, INFORMSGoogle Scholar
  5. IEA (2012) Energy technology perspectives 2012: pathways to a clean energy system. France, ParisCrossRefGoogle Scholar
  6. IEA (2013) Nordic energy technology perspectives: pathways to a carbon neutral energy future. Paris, France, IEA and Nordic Energy Research. Available at http://www.iea.org/media/etp/nordic/NETP.pdf
  7. IEA (2016) Nordic energy technology perspectives 2016—cities, flexibility and pathways to carbon-neutrality. IEA and Nordic Energy Research, Paris, FranceGoogle Scholar
  8. Kall, P, Wallace SW (1994) Stochastic programming. John Wiley & Sons, ChichesterGoogle Scholar
  9. Lind A, Rosenberg E (2013) TIMES-Norway model documentation. Kjeller, Norway, Institute for Energy TechnologyGoogle Scholar
  10. Loulou R (2008) ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation. CMS 5(1–2):41–66MathSciNetCrossRefMATHGoogle Scholar
  11. Loulou R, Labriet M (2008) ETSAP-TIAM: the TIMES integrated assessment model Part I: model structure. CMS 5(1–2):7–40CrossRefMATHGoogle Scholar
  12. Loulou R, Lehtila A, Kanudia A, Remme U, Goldstein G (2005a) Documentation for the TIMES model—part III. Energy technology systems analysis programme. Available at http://iea-etsap.org/docs/TIMESDoc-GAMS.pdf
  13. Loulou R, Remme U, Kanudia A, Lehtila A, Goldstein G (2005b) Documentation for the TIMES model—Part I. Energy technology systems analysis programme. Available at http://iea-etsap.org/docs/TIMESDoc-Details.pdf
  14. Loulou R, Remme U, Kanudia A, Lehtila A, Goldstein G (2005c) Documentation for the TIMES Model—Part II. Energy technology systems analysis programme. Available at http://iea-etsap.org/docs/TIMESDoc-Details.pdf
  15. NVE (2015) Kostnader i energisektoren. Kraft, varme og effektivisering. The norwegian water resources and energy directorate. Oslo, Norway. Available at http://publikasjoner.nve.no/rapport/2015/rapport2015_02a.pdf
  16. Rosenberg E, K. A. Espegren (2014) CenSES energiframskrivinger mot 2050. Available at https://www.ife.no/no/publications/2014/ensys/censes-energiframskrivinger-mot-2050
  17. Seljom P, Lindberg KB, Tomasgard A, Doorman G, Sartori I (2017) The impact of zero energy buildings on the scandinavian energy system. Energy 118(Supplement C): 284–296Google Scholar
  18. Seljom P, Tomasgard A (2015) Short-term uncertainty in long-term energy system models—A case study of wind power in Denmark. Energy Econ 49(Supplement C): 157–167Google Scholar
  19. Seljom P, Tomasgard A (2017) The impact of policy actions and future energy prices on the cost-optimal development of the energy system in Norway and Sweden. Energy Policy 106(Supplement C): 85–102Google Scholar
  20. Swedish Energy Agency (2013) LÃ¥ngtidsprognos 2012. Available at http://www.energimyndigheten.se/Global/Statistik/Prognoser/L%C3%A5ngsiktsprognos%202012.pdf
  21. The Government of Sweden (2017) The climate policy framework. Available at http://www.government.se/articles/2017/06/the-climate-policy-framework/
  22. The Norwegian Ministry of Climate and Environment (2017) Climate Act (Klimaloven), Prop. 77 L (2016–2017). Available at https://www.regjeringen.no/no/dokumenter/prop.-77-l-20162017/id2546463/

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute for Energy Technology (IFE)KjellerNorway

Personalised recommendations