Opening the black box of energy modelling: Strategies and lessons learned

Energy Strategy Reviews

Lion Hirth¹  Eva Schmid²  Frauke Wiese³  Matthew Gidden⁴  Clemens Wingenbach⁵  Guido Pleßmann⁶  Tim Tröndle⁷  Heidi Heinrichs⁸  Stefan Pfenninger⁹  Jörn C. Richstein^1,10  Clara Heuberger^1,11  Chris Davis^1,12  Uwe Krien^1,13  Arjuna Nebel^1,14  Carsten Matke^1,15  Ingmar Schlecht^1,16  Abhishek Shivakumar^1,17  Berit Müller^1,17  Iain Staffell^1,17  Tom Brown^1,18  Robbie Morrison^1,19  Simon Hilpert^2,20  Matthias Reeg^2,21 

[1]Corresponding author.

[2]Hertie School of Governance, Berlin, Germany

[3]Mercator Research Institute on Global Commons and Climate Change (MCC), Berlin, Germany

[4]PIK, Potsdam, Germany

[5]DIW, Berlin, Germany

[6]DLR Institute of Networked Energy Systems, Oldenburg, Germany

[7]DLR, Germany

[8]Danish Technical University, Denmark

[9]ETH Zürich, Switzerland

[10]Energy Consultant, Berlin, Germany

[11]FIAS, University of Frankfurt, Germany

[12]GERMANWATCH, Berlin, Germany

[13]IIASA, Laxenburg, Austria

[14]Imperial College London, UK

[15]Institute of Energy and Climate Research, FZ Jülich, Germany

[16]Neon Neue Energieökonomik GmbH, Berlin, Germany

[17]Reiner Lemoine Institute, Germany

[18]University of Basel, Switzerland

[19]University of Flensburg, Germany

[20]University of Groningen, The Netherlands

[21]Wuppertal Institute, Germany

DOI  :  

来源: DOAJ

【 摘 要 】

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. Keywords: Open source, Open data, Energy modelling

【 授权许可】

Unknown