Name Oemof Application Brandenburg Berlin
Acronym oemof_abbb
Methodical Focus None
Institution(s) Reiner Lemoine Institut (RLI)
Author(s) (institution, working field, active time period) Elisa Gaudchau (RLI), Birgit Schachler (RLI), Ludwig Hülk (RLI)
Current contact person Elisa Gaudchau
Contact (e-mail)
Primary Purpose Simulation of the energy system in 2030 in the German region Berlin and Brandenburg
Primary Outputs CO2 emissions, Full Load Hours, export, ...
Support / Community / Forum
Framework oemof (
Link to User Documentation
Link to Developer/Code Documentation
Documentation quality expandable
Source of funding Private funding
Number of developers less than 10
Number of users less than 10
Open Source
License Not decided yet
Source code available
Access to source code
Data provided none
Collaborative programming
GitHub Organisation
GitHub Contributions Graph
Modelling software Python
Internal data processing software
External optimizer
Additional software
Citation reference -
Citation DOI -
Reference Studies/Models -
Example research questions -
Model usage -
Model validation -
Example research questions -
further properties
Model specific properties -
Modeled energy sectors (final energy) electricity, heat
Modeled demand sectors Households, Industry, Commercial sector
Modeled technologies: components for power generation or conversion
Renewables PV, Wind, Solar thermal
Conventional gas, oil
Modeled technologies: components for transfer, infrastructure or grid
Electricity transmission
Gas -
Heat -
Properties electrical grid -
Modeled technologies: components for storage heat
User behaviour and demand side management
Changes in efficiency
Market models -
Geographical coverage
Geographic (spatial) resolution regions
Time resolution hour
Comment on geographic (spatial) resolution Regionale Planugsgmeinschaften Brandenburg + Berlin
Observation period 1 year
Additional dimensions (sector) -
Model class (optimisation) LP
Model class (simulation) -
Short description of mathematical model class
Mathematical objective costs
Approach to uncertainty -
Suited for many scenarios / monte-carlo
typical computation time less than an hour
Typical computation hardware -
Technical data anchored in the model -
Model file format .py
Input data file format .csv
Output data file format .csv
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.
You can also fork the project and get involved.

Please note that the platform is still under construction and therefore the design of this page is still highly volatile!




oemof oemof_abbb