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Sökning: WFRF:(Pfenninger Stefan)

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1.
  • Dekker, Mark M., et al. (författare)
  • Identifying energy model fingerprints in mitigation scenarios
  • 2023
  • Ingår i: Nature Energy. - : Springer Nature. - 2058-7546. ; 8:12, s. 1395-1404
  • Tidskriftsartikel (refereegranskat)abstract
    • Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.
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2.
  • Pfenninger, Stefan, et al. (författare)
  • Opening the black box of energy modelling : Strategies and lessons learned
  • 2018
  • Ingår i: Energy Strategy Reviews. - : ELSEVIER SCIENCE BV. - 2211-467X .- 2211-4688. ; 19, s. 63-71
  • Tidskriftsartikel (refereegranskat)abstract
    • The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research.
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