The Open Source energy Model Base for the European Union (OSeMBE)

Europe REEEM OSeMOSYS long-term 2050 EMP-E
Name The Open Source energy Model Base for the European Union
Acronym OSeMBE
Methodical Focus open source , Country resolution model of the EU el. sector , long-term
Institution(s) KTH Royal Institute of Technology
Author(s) (institution, working field, active time period) Hauke Henke; KTH Royal Institute of Technology
Current contact person Hauke Henke
Contact (e-mail)
Primary Purpose OSeMBE is designed as an engagement tool. From the choice of modelling system to the representation of the modeled energy system. The aim is to provide a platform for a set of different audiences who want to get engaged with energy modelling, but have no to little previous modelling experience. This could be university students, researchers in and outside the energy field, but also stakeholders like policy makers who intend to get a better understanding of the energy nexus and or modelling. The model provides the base to build a sound and diverse community of modellers and model users that can contribute and develop the model according to their needs in a transparent way.
Primary Outputs Key outputs of OSeMBE are the power generation capacities and generation mixes for all EU28, Switzerland and Norway, as well as the overall system cost.
Support / Community / Forum
Framework OSeMOSYS
Link to User Documentation
Link to Developer/Code Documentation
Documentation quality expandable
Source of funding REEEM, H2020 project, European Comission
Number of devolopers less than 10
Number of users less than 10
Open Source
License Open Data Commons Attribution License 1.0
Source code available
Link to source code
Data provided all
Cooperative programming
GitHub Organisation
GitHub Contributions Graph
Modelling software OSeMOSYS
Internal data processing software MoManIv1.10, Excel
External optimizer
Additional software
Citation reference Henke, H.T.J., et al., The Base for a European Engagement Model - An Open Source Electricity Model of seven countries around the Baltic Sea, CYSENI 2018, Kaunas, Lithuania
Citation DOI
Please list references to reports and studies which were produced using the model
Example research questions Impacts of EU decarbonisation pathways
Larger scale usage REEEM H2020 project,
Model validation checked with measurements (measured data)
Example research questions Impacts of EU decarbonisation pathways
further properties
Model specific properties Stakeholder engagement model
Modeled energy sectors (final energy) electricity
Modeled demand sectors -
Modelled energy carriers (primary energy carrier)
Gas Natural gas
Liquids Petrol
Solid Hard coal, Uranium, Biomass, Sun, Wind, Hydro, Geothermal heat
Renewables Sun, Wind, Hydro, Geothermal heat
Modeled technologies: components for generation or conversion
Renewables PV, Wind, Hydro, Biomass
Conventional gas, coal, oil, liquid fuels, nuclear
Modeled technologies: components for transfer, infrastructure or grid
Electricity transmission
Gas -
Heat -
Properties electrical grid -
Modeled technologies: components for storage -
User behaviour and demand side management
Changes in efficiency The change in efficiency can be considered in a deterministic way, i.e. the efficiency can be entered on an annual base.
Market models -
Geographical coverage
Geographic (spatial) resolution continents, national states
Time resolution user defined
Comment on geographic (spatial) resolution The electricity system of all 30 countries included are modeled and connected by the existing and planned trans-border transmission lines.
Observation period >1 year
Additional dimensions (sector) economic
Model class (optimisation) LP
Model class (simulation) Bottom up
Short description of mathematical model class
Mathematical objective costs
Approach to uncertainty Deterministic
Suited for many scenarios / monte-carlo
typical computation time less than a day
Typical computation hardware RAM: 256 GB, CPU: 3.5 GHz
Technical data anchored in the model
Interfaces MoManI
Model file format .exe
Input data file format text
Output data file format text
Integration with other models
Integration of other models

If you find bugs or if you have ideas to improve the Open Energy Platform, you are welcome to add your comments to the existing issues on GitHub.
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Please note that the platform is still under construction and therefore the design of this page is still highly volatile!

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  • Compare a selection of models for different purposes - e.g. to develop a strategy to link them
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Use case example model Fact Sheet: For a European pathway simulation (EPS) we want to choose the models that best meet our requirements. All partners include their models in the Model Fact Sheets and tag them with “EPS”. To compare the models we filter all “EPS” models and choose different characteristics that we want to compare. OEP will give us tables (views) that facilitate the comparison.