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Open source software and crowdsourcing for energy analysis

Author

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  • Bazilian, Morgan
  • Rice, Andrew
  • Rotich, Juliana
  • Howells, Mark
  • DeCarolis, Joseph
  • Macmillan, Stuart
  • Brooks, Cameron
  • Bauer, Florian
  • Liebreich, Michael

Abstract

Informed energy decision making requires effective software, high-quality input data, and a suitably trained user community. Developing these resources can be expensive and time consuming. Even when data and tools are intended for public re-use they often come with technical, legal, economic and social barriers that make them difficult to adopt, adapt and combine for use in new contexts. We focus on the promise of open, publically accessible software and data as well as crowdsourcing techniques to develop robust energy analysis tools that can deliver crucial, policy-relevant insight, particularly in developing countries, where planning resources are highly constrained—and the need to adapt these resources and methods to the local context is high. We survey existing research, which argues that these techniques can produce high-quality results, and also explore the potential role that linked, open data can play in both supporting the modelling process and in enhancing public engagement with energy issues.

Suggested Citation

  • Bazilian, Morgan & Rice, Andrew & Rotich, Juliana & Howells, Mark & DeCarolis, Joseph & Macmillan, Stuart & Brooks, Cameron & Bauer, Florian & Liebreich, Michael, 2012. "Open source software and crowdsourcing for energy analysis," Energy Policy, Elsevier, vol. 49(C), pages 149-153.
    • Handle: RePEc:eee:enepol:v:49:y:2012:i:c:p:149-153
    DOI: 10.1016/j.enpol.2012.06.032
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    References listed on IDEAS

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    9. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    10. Groissböck, Markus, 2019. "Are open source energy system optimization tools mature enough for serious use?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 234-248.
    11. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    12. Jonathan Klimt & Niklas Eiling & Felix Wege & Jonas Baude & Antonello Monti, 2023. "The Role of Open-Source Software in the Energy Sector," Energies, MDPI, vol. 16(16), pages 1-17, August.
    13. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    14. Rady, Yassin Yehia & Rocco, Matteo V. & Serag-Eldin, M.A. & Colombo, Emanuela, 2018. "Modelling for power generation sector in Developing Countries: Case of Egypt," Energy, Elsevier, vol. 165(PB), pages 198-209.
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