Energy system optimization dashboard using mixed integer linear programming. Developed as part of the project "Offene Wärmespeicherplanung (OWP)" as part of Inno!Nord of the T!Raum initiative funded by the German Federal Ministry of Education and Research.
- Combined invest and dispatch optimization based on oemof.solph
- Parametrization and result visualizaiton with a Streamlit dashboard
- Wide range of typical heating plants
- Comprehensive data base of heat load data, energy prices and emission factors
For now, only direct download from the GitHub Repository is supported, so just clone it locally or download a ZIP file of the code. If you are using Miniforge or another environment management tool using conda, you can create and activate a clean environment like this:
conda create -n my_new_env python=3.11
conda activate my_new_env
To use the optimization dashboard, the necessary dependencies have to be installed. In a clean environment from the root directory the installation from this file could look like this:
python -m pip install "c:\path\to\the\package"
If you have already navigated your terminal (e.g. cmd) to the package directory, the path string in the command above simplifies to a single period character ("."), which means the current working directory.
Running the optimization dashboard is as easy as running the following command from the root directory in your virtual environment with dependencies installed:
streamlit run src\Home.py
See the LICENSE file for further information.