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District heating system unit design and dispatch optimization dashboard using Mixed Integer Linear Programming (MILP).

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OWP Optimization Dashboard

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.

Key Features

  • 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

Funding

Installation

For now, only direct download from the GitHub Repository is supported, so just clone it locally or download a ZIP file of the code. To use the heat pump model classes or visualization dashboard, the necessary dependencies have to be installed from the requirements.txt file. In a clean environment from the root directory the installation from this file could look like this:

conda create -n my_new_env python=3.11
conda activate my_new_env
python -m pip install -r requirements.txt

Run the dashboard

Running the heat pump 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

License

See the LICENSE file for further information.

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District heating system unit design and dispatch optimization dashboard using Mixed Integer Linear Programming (MILP).

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