Open Energy Modelling Initiative (Ofer Abarbanel online library)

The Open Energy Modelling Initiative (openmod) is a grassroots community of energy system modellers from universities and research institutes across Europe and elsewhere. The initiative promotes the use of open-source software and open data in energy system modelling for research and policy advice. The Open Energy Modelling Initiative documents a variety of open-source energy models and addresses practical and conceptual issues regarding their development and application. The initiative runs an email list, an internet forum, and a wiki and hosts occasional academic workshops. A statement of aims is available.[1]


The application of open-source development to energy modelling dates back to around 2010. This section provides some background for the growing interest in open methods.

Growth in open energy modelling

Just two active open energy modelling projects were cited in a 2011 paper: OSeMOSYS and TEMOA.[2]:5861 Balmorel was also open at that time, having been made public in 2001.[b] As of November 2016, the openmod wiki lists 24 such undertakings.[3]

Academic literature

This 2012 paper presents the case for using “open, publicly accessible software and data as well as crowdsourcing techniques to develop robust energy analysis tools”.[4]:149 The paper claims that these techniques can produce high-quality results and are particularly relevant for developing countries.

There is an increasing call for the energy models and datasets used for energy policy analysis and advice to be made public in the interests of transparency and quality.[5] A 2010 paper concerning energy efficiency modeling argues that “an open peer review process can greatly support model verification and validation, which are essential for model development”.[6]:17[7] One 2012 study argues that the source code and datasets used in such models should be placed under publicly accessible version control to enable third-parties to run and check specific models.[8] Another 2014 study argues that the public trust needed to underpin a rapid transition in energy systems can only be built through the use of transparent open-source energy models.[9] The UK TIMES project (UKTM) is open source, according to a 2014 presentation, because “energy modelling must be replicable and verifiable to be considered part of the scientific process” and because this fits with the “drive towards clarity and quality assurance in the provision of policy insights”.[10]:8 In 2016, the Deep Decarbonization Pathways Project (DDPP) is seeking to improve its modelling methodologies, a key motivation being “the intertwined goals of transparency, communicability and policy credibility.”[11]:S27 A 2016 paper argues that model-based energy scenario studies, wishing to influence decision-makers in government and industry, must become more comprehensible and more transparent. To these ends, the paper provides a checklist of transparency criteria that should be completed by modelers. The authors note however that they “consider open source approaches to be an extreme case of transparency that does not automatically facilitate the comprehensibility of studies for policy advice.”[12]:4 An editorial from 2016 opines that closed energy models providing public policy support “are inconsistent with the open access movement [and] publically [sic] funded research”.[13]:2 A 2017 paper lists the benefits of open data and models and the reasons that many projects nonetheless remain closed. The paper makes a number of recommendations for projects wishing to transition to a more open approach. The authors also conclude that, in terms of openness, energy research has lagged behind other fields, most notably physics, biotechnology, and medicine.[14] Moreover:

Given the importance of rapid global coordinated action on climate mitigation and the clear benefits of shared research efforts and transparently reproducible policy analysis, openness in energy research should not be for the sake of having some code or data available on a website, but as an initial step towards fundamentally better ways to both conduct our research and engage decision-makers with [our] models and the assumptions embedded within them.[14]:214

A one-page opinion piece in Nature News from 2017 advances the case for using open energy data and modeling to build public trust in policy analysis. The article also argues that scientific journals have a responsibility to require that data and code be submitted alongside text for scrutiny, currently only Energy Economics makes this practice mandatory within the energy domain.[15]

Copyright and open energy data

Issues surrounding copyright remain at the forefront with regard to open energy data. Most energy datasets are collated and published by official or semi-official sources, for example, national statistics offices, transmission system operators, and electricity market operators. The doctrine of open data requires that these datasets be available under free licenses (such as CC BY 4.0) or be in the public domain. But most published energy datasets carry proprietary licenses, limiting their reuse in numerical and statistical models, open or otherwise. Measures to enforce market transparency have not helped because the associated information is normally licensed to preclude downstream usage. Recent transparency measures include the 2013 European energy market transparency regulation 543/2013 [16] and a 2016 amendment to the German Energy Industry Act [17] to establish a nation energy information platform, slated to launch on 1 July 2017. Energy databases are protected under general database law, irrespective of the copyright status of the information they hold.[18]

In December 2017, participants from the Open Energy Modelling Initiative and allied research communities made a written submission to the European Commission on the re-use of public sector information.[19] The document provides a comprehensive account of the data issues faced by researchers engaged in open energy system modeling and energy market analysis and quoted extensively from a German legal opinion.[20]

Public policy support

In May 2016 the European Union announced that “all scientific articles in Europe must be freely accessible as of 2020”.[21] This is a step in the right direction, but the new policy makes no mention of open software and its importance to the scientific process.[22] In August 2016, the United States government announced a new federal source code policy which mandates that at least 20% of custom source code developed by or for any agency of the federal government be released as open-source software (OSS).[23] The US Department of Energy (DOE) is participating in the program. The project is hosted on a dedicated website and subject to a three-year pilot.[23][24] Open-source campaigners are using the initiative to advocate that European governments adopt similar practices.[25] In 2017 the Free Software Foundation Europe (FSFE) issued a position paper calling for free software and open standards to be central to European science funding, including the flagship EU program Horizon 2020. The position paper focuses on open data and open data processing and the question of open modeling is not traversed per se.[26]


The Open Energy Modelling Initiative participants take turns to host regular academic workshops.

  Date Host City Country
1 18–19 September 2014 DIW Berlin Berlin Germany
2 13–14 April 2015 MCC Berlin [27] Berlin Germany
3 10–11 September 2015 Imperial College London (ICL) [28] London United Kingdom
4 28–29 April 2016 KTH Royal Institute of Technology [29] Stockholm Sweden
5 27–28 October 2016 Department of Energy, Politecnico di Milano Milan Italy
6 20–21 April 2017 Frankfurt Institute for Advanced Studies (FIAS) [30] Frankfurt Germany
7 12–13 October 2017 Technical University of Munich (TUM) Munich Germany
8 6–8 June 2018 Climate Policy Group, ETH Zurich Zürich Switzerland
9 22–24 May 2019 Department of Engineering, Aarhus University Aarhus Denmark
10 18–19 September 2019 National Renewable Energy Laboratory (NREL) Golden, Colorado United States
11 15–17 January 2020 Hertie School Berlin Germany


  1. ^“openmod — Open Energy Modelling Initiative”. Open Energy Modelling Initiative. Retrieved 10 October 2016.
  2. ^Howells, Mark; Rogner, Holger; Strachan, Neil; Heaps, Charles; Huntington, Hillard; Kypreos, Socrates; Hughes, Alison; Silveira, Semida; DeCarolis, Joe; Bazilian, Morgan; Roehrl, Alexander (2011). “OSeMOSYS: the open source energy modeling system : an introduction to its ethos, structure and development”. Energy Policy. 39 (10): 5850–5870. doi:10.1016/j.enpol.2011.06.033. The misspelling of Morgan Bazillian has been corrected in the citation. ResearchGate version.
  3. ^“Open Models”. Open Energy Modelling Initiative. Retrieved 3 November 2016.
  4. ^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” (PDF). Energy Policy. 49: 149–153. doi:10.1016/j.enpol.2012.06.032. Retrieved 17 June 2016.
  5. ^acatech; Lepoldina; Akademienunion, eds. (2016). Consulting with energy scenarios: requirements for scientific policy advice (PDF). Berlin, Germany: acatech — National Academy of Science and Engineering. ISBN 978-3-8047-3550-7. Retrieved 19 December2016.
  6. ^Mundaca, Luis; Neij, Lena; Worrell, Ernst; McNeil, Michael A (1 August 2010). “Evaluating energy efficiency policies with energy-economy models — Report number LBNL-3862E”. Annual Review of Environment and Resources. 35: 305–344. doi:10.1146/annurev-environ-052810-164840. OSTI 1001644. Retrieved 19 December 2016.
  7. ^Mundaca, Luis; Neij, Lena; Worrell, Ernst; McNeil, Michael A (22 October 2010). “Evaluating energy efficiency policies with energy-economy models”. Annual Review of Environment and Resources. 35 (1): 305–344. doi:10.1146/annurev-environ-052810-164840. ISSN 1543-5938.
  8. ^DeCarolis, Joseph F; Hunter, Kevin; Sreepathi, Sarat (2012). “The case for repeatable analysis with energy economy optimization models” (PDF). Energy Economics. 34 (6): 1845–1853. doi:10.1016/j.eneco.2012.07.004. ISSN 0140-9883. Retrieved 8 July 2016.
  9. ^Wiese, Frauke; Bökenkamp, Gesine; Wingenbach, Clemens; Hohmeyer, Olav (2014). “An open source energy system simulation model as an instrument for public participation in the development of strategies for a sustainable future”. Wiley Interdisciplinary Reviews: Energy and Environment. 3 (5): 490–504. doi:10.1002/wene.109. ISSN 2041-840X.
  10. ^Strachan, Neil; Fais, Birgit; Daly, Hannah (18 November 2014). Redefining the energy modelling-policy interface: developing a fully open source UK TIMES model — Presentation (PDF). Energy Technology Systems Analysis Programme (ETSAP) Workshop, Technical University of Denmark (DTU). Copenhagen, Denmark. Retrieved 8 November 2016.
  11. ^Pye, Steve; Bataille, Chris (2016). “Improving deep decarbonization modelling capacity for developed and developing country contexts”. Climate Policy. 16 (S1): S27–S46. doi:10.1080/14693062.2016.1173004.
  12. ^Cao, Karl-Kiên; Cebulla, Felix; Gómez Vilchez, Jonatan J; Mousavi, Babak; Prehofer, Sigrid (28 September 2016). “Raising awareness in model-based energy scenario studies — a transparency checklist”. Energy, Sustainability and Society. 6 (1): 28–47. doi:10.1186/s13705-016-0090-z. ISSN 2192-0567.
  13. ^Strachan, Neil; Fais, Birgit; Daly, Hannah (29 February 2016). “Reinventing the energy modelling–policy interface”. Nature Energy. 1 (3): 16012. Bibcode:2016NatEn…116012S. doi:10.1038/nenergy.2016.12. ISSN 2058-7546.
  14. ^ Jump up to:ab Pfenninger, Stefan; DeCarolis, Joseph; Hirth, Lion; Quoilin, Sylvain; Staffell, Iain (February 2017). “The importance of open data and software: is energy research lagging behind?”. Energy Policy. 101: 211–215. doi:10.1016/j.enpol.2016.11.046. ISSN 0301-4215.
  15. ^Pfenninger, Stefan (23 February 2017). “Energy scientists must show their workings”(PDF). Nature News. 542 (7642): 393. Bibcode:2017Natur.542..393P. doi:10.1038/542393a. PMID 28230147. Retrieved 26 February 2017.
  16. ^“Commission Regulation (EU) No 543/2013 of 14 June 2013 on submission and publication of data in electricity markets and amending Annex I to Regulation (EC) No 714/2009 of the European Parliament and of the Council”. Official Journal of the European Union (L 163): 1–12. 15 June 2013. Retrieved 1 December 2016.
  17. ^ 111d Energiewirtschaftsgesetz(EnWG) [ Energy Industry Act] of 13 October 2016. p. 115–116. Einrichtung einer nationalen Informationsplattform [Establishment of a national information platform].
  18. ^Boecker, Lina (21 November 2016). Energy databases: protection and licensing (PDF). Berlin, Germany: JBB Rechtsanwaelte.
  19. ^Morrison, Robbie; Brown, Tom; De Felice, Matteo (10 December 2017). Submission on the re-use of public sector information: with an emphasis on energy system datasets — Release 09 (PDF). Berlin, Germany. Retrieved 13 December 2017.
  20. ^Jaeger, Till (24 July 2017). Legal aspects of European electricity data — Legal opinion(PDF). Berlin, Germany: JBB Rechtsanwälte. Retrieved 13 October 2017.
  21. ^Hendrikx, Michiel (27 May 2016). “All European scientific articles to be freely accessible by 2020” (PDF) (Press release). The Netherlands: Ministry of Education, Culture and Science. Retrieved 7 August 2016.
  22. ^Albers, Erik (2 June 2016). “There is no open science without the use of open standards and free software”. Retrieved 7 August 2016.
  23. ^ Jump up to:ab Scott, Tony; Rung, Anne E (8 August 2016). Federal Source Code Policy: Achieving Efficiency, Transparency, and Innovation through Reusable and Open Source Software — Memorandum for the Heads of Departments and Agencies — M-16-21 (PDF). Washington DC, USA: Office of Budget and Management, Executive Office of the President. Archived from the original (PDF) on 20 September 2016. Retrieved 14 September 2016.Also available as HTML at:
  24. ^“The People’s Code: Unlock the tremendous potential of the Federal Government’s software”. USA. Retrieved 24 November 2016.
  25. ^New, William (22 August 2016). “New US government source code policy could provide model for Europe”. Intellectual Property Watch. Geneva, Switzerland. Retrieved 14 September 2016.
  26. ^Gkotsopoulou, Olga; Albers, Erik; Di Cosmo, Roberto; Malaja, Polina; Sanjurjo, Fernando (5 January 2017). Position paper for the endorsement of free software and open standards in Horizon 2020 and all publicly-funded research (PDF). Berlin, Germany: Free Software Foundation Europe (FSFE). Retrieved 9 February 2017.
  27. ^“OSeMOSYS Newsletter”. Retrieved 25 April 2016.
  28. ^“Open Energy Modelling Workshop”. Retrieved 25 September 2015.
  29. ^“Open Energy Modelling Workshop — KTH, Stockholm 2016”. Retrieved 28 April 2016.
  30. ^“Open Energy Modelling Workshop — Frankfurt 2017”. Retrieved 1 December 2016.
  31. ^Morrison, Robbie (20 November 2019). “An open energy system modeling community”. Generation R Blog. Hannover, Germany: Leibniz Research Alliance Open Science. doi:10.25815/ff3b-d154. ISSN 2512-3815. Retrieved 22 November 2019. Creative Commons CC‑BY‑4.0 license.
  32. ^“Energiedaten für alle – Projekt “Open Power System Data” an der EUF gestartet”[Energy data for all — project “Open Power System Data” started at the EUF] (in German). Retrieved 25 September 2015.
  33. ^“Offene Plattform macht Energiedaten zugänglich” [Open platform makes energy data available] (in German). 14 September 2015. Retrieved 25 September 2015.

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Ofer Abarbanel online library

Ofer Abarbanel online library

Ofer Abarbanel online library