Open Energy Modelling Framework - Python toolbox for energy system modelling and optimisation.

The omeof project aims to be a loose organisational frame for tools in the wide field of (energy) system modelling.


The solph library is designed to create and solve linear or mixed-integer linear optimization problems. It is based on optimization modelling language pyomo.

To use solph at least one linear solver has to be installed on your system. See the pyomo installation guide to learn which solvers are supported. Solph is tested with the open source solver cbc and the gurobi solver (free for academic use). The open glpk solver recently showed some odd behaviour.

The formulation of the energy system is based on the oemof-network library but contains additional components such as storages. Furthermore the network class are enhanced with additional parameters such as efficiencies, bounds, cost and more. See the API documentation for more details. Try the examples to learn how to build a linear energy system.


Coming soon…


Cycle Detection in Time Series (CyDeTS). An algorithm to detect cycles in times series along with their respective depth-of-cycle (DoC) and duration.


The demandlib library can be used to create load profiles for elctricity and heat knowing the annual demand. See the documentation of the demandlib for examples and a full description of the library.


The feedinlib library serves as an interface between Open Data weather data and libraries to calculate feedin timeseries for fluctuating renewable energy sources.

It is currently under revision (see here for further information). To begin with it will provide an interface to the pvlib and windpowerlib and functions to download MERRA2 weather data and open_FRED weather data. See documentation of the feedinlib for a full description of the library.


Coming soon…