Pyromof is an oemof.solph-based optimization modelling framework for individual pyrolysis plants with flexibility options. It is being developed within the project PyFlex.
The framework's purpose is to assess the profitability of different pyrolysis plants with different sets of flexibity-enhancing components under different policies. The following components are available:
| sinks | sources | converter | storage |
|---|---|---|---|
| markets for biochar, CO2 removal certificats, heat, electricity, hydrogen, bio-oil | biomass, heat | biomass dryer, pyrolysis, combined heat and power, combustor, organic rankine cycle, power to heat, hydrogen extraction from syngas, heat exchanger, condensor | storage for syngas, heat, electricity and hydrogen |
Available policy options up to know are a fixed feed-in premium for electricity, a sliding premium for electricity and investment subsidies for pyrolysis. More will be implemented soon.
Pyromof has been tested with Python3.12. In order to install pyromof, proceed with the following steps:
- Create a virtual environment (e.g. with venv)
- Clone the github repository (
git clone https://github.com/IOEW-FF2/pyromof.git) - Enter the folder and
- Install the package with
pip install -e .. The-e-flag installs the project in editable mode - if you only want to run the model, you can install it without it.
In order to run the model you need a solver. By default, the code expects the solver cbc which you can find in https://github.com/coin-or/Cbc/releases. If you want to use a different one, you have to adjust the code in pyromof/optimize.py om.solve(solver="your_solver"). If you use Windows, the file "cbc.exe" (located in the bin folder) should be placed in the same folder as this readme-file.
The input data are not yet provided within this repository. A description on how to design the input data and how to run the model is provided in docs/usage.md.
We welcome your feedback and the creation of issues if you notice bugs or have ideas for improvements.