 | |
| Abbreviation | openmod |
|---|---|
| Formation | September 2014 (11 years ago) (2014-09) [a] |
| Type | Internet-based with periodic workshops |
| Purpose | Promote open-source energy models and open energy sector data |
Official language | English |
| Website | openmod-initiative |
|---|---|
| Wiki | wiki |
| Forum | forum |
| Email list | groups |
| YouTube channel | www |
TheOpen Energy Modelling Initiative (openmod) is agrassroots community ofenergy system modellers from universities and research institutes across Europe and elsewhere. The initiative promotes the use ofopen-source software andopen data inenergy systemmodelling 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 anemail list, aninternet forum, and awiki and hosts occasional academic workshops. A statement of aims is available.[1]
The application ofopen-source development to energy modelling dates back to around 2003. This section provides some background for the growing interest in open methods.
Just two active open energy modelling projects were cited in a 2011 paper: OSeMOSYS and TEMOA.[2]: 5861 Balmorel was also public at that time, having been made available on a website in 2001.[b]As of November 2016,[update] the openmod wiki lists 24 such undertakings.[3]As of October 2021,[update] the Open Energy Platform lists 17 open energy frameworks and about 50 open energy models.
This 2012 paper presents the case for using "open, publicly accessible software and data as well ascrowdsourcing 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 anddatasets used forenergy 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 thesource code and datasets used in such models should be placed under publicly accessibleversion 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, theDeep 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 inNature News from 2017 advances the case for using open energy data and modeling to build public trust in policy analysis. The article also argues thatscientific journals have a responsibility to require that data and code be submitted alongside text for scrutiny, currently onlyEnergy Economics makes this practice mandatory within the energy domain.[15]
Issues surroundingcopyright 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, andelectricity market operators. The doctrine of open data requires that these datasets be available underfree licenses (such asCC BY 4.0) or be in thepublic domain. But most published energy datasets carry proprietary licenses, limiting their reuse in numerical and statistical models, open or otherwise. Measures to enforcemarket 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 may also be protected under generaldatabase 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 theEuropean Commission on there-use ofpublic 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]
In May 2020, participants from the Open Energy Modelling Initiative made a further submission on the European strategy for data.[21][22] In mid‑2021, participants made two written submissions on a proposedData Act — legislative work-in-progress intended primarily to improvepublic interest business-to-government (B2G) information transfers within theEuropean Economic Area (EEA).[23][24] More specifically, the two Data Act submissions drew attention to restrictive but nonetheless compliant public disclosure reporting practices deployed by theEuropean Energy Exchange (EEX).
In May 2016, theEuropean Union announced that "all scientific articles in Europe must be freely accessible as of 2020".[25] 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.[26] In August 2016, theUnited States government announced a new federalsource code policy which mandates that at least 20% of custom source code developed by or for any agency of the federal government be released asopen-source software (OSS).[27] TheUS Department of Energy (DOE) is participating in the program. The project is hosted on a dedicated website and subject to a three-year pilot.[27][28] Open-source campaigners are using the initiative to advocate that European governments adopt similar practices.[29] In 2017 theFree Software Foundation Europe (FSFE) issued aposition paper calling for free software and open standards to be central to European science funding, including the flagshipEU programHorizon 2020. The position paper focuses on open data and open data processing and the question of open modeling is not traversed per se.[30]
A trend evident by 2023 is the adoption of regulators within the European Union and North America. Fairley (2023), writing in theIEEE Spectrum publication, provides an overview.[31] And as one example, theCanada Energy Regulator is using thePyPSA framework for systems analysis.[32]
The Open Energy Modelling Initiative participants take turns to host regular academic workshops.
| Date | Host | City | Country | Comment | |
|---|---|---|---|---|---|
| 1 | 18–19 September 2014 | DIW Berlin [33] | Berlin | Germany | establishment meeting with 28 participants [33] |
| 2 | 13–14 April 2015 | MCC Berlin [34] | Berlin | Germany | |
| 3 | 10–11 September 2015 | Imperial College London (ICL) [35] | London | United Kingdom | in association withGrantham Research Institute on Climate Change and the Environment |
| 4 | 28–29 April 2016 | KTH Royal Institute of Technology [36] | Stockholm | Sweden | |
| 5 | 27–28 October 2016 | Department of Energy,Politecnico di Milano | Milan | Italy | Archived 12 July 2016 at theWayback Machine |
| 6 | 20–21 April 2017 | Frankfurt Institute for Advanced Studies (FIAS) [37] | 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 | 63 attendees |
| 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 | circa 190 attendees |
| 12 | March thru May 2020 | 2020 mini‑workshop series | online | — | duringCOVID-19 pandemic, 3 events for 2020 |
| 14 | 5 May 2021 | 2021 mini‑workshop | online | — | duringCOVID-19 pandemic |
| 15 | 17 February 2022 | 2022 mini‑workshop | online | — | duringCOVID-19 pandemic |
| 16 | 22–24 March 2023 | International Institute for Applied Systems Analysis (IIASA) | Laxenburg,Vienna | Austria | limited to 65 attendees |
| 17 | 13–14 November 2023 | Stanford University Campus | San Francisco Bay Area | United States | limited to 80 attendees |
| 18 | 26–28 March 2024 | CRESYM and OTE | Grenoble | France | limited to 100 attendees |
| 19 | 25–26 March 2025 | KTH Royal Institute of Technology | Stockholm | Sweden | 60 attendees |
The Open Energy Modelling Initiative also holds occasional specialist meetings.
| Date | Subject | City | Country | Comment | |
|---|---|---|---|---|---|
| 13 | 4 December 2020 | Climate forecasting for energy workshop | online | — | joint organization withS2S4E project |
Related to openmod
Open energy data
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