A python-based tool for the design and analysis of hybrid AC/DC grids
PyFlow ACDC is a program worked on by ADOreD Project
This project has received funding from the European Union’s Horizon Europe Research and Innovation programme under the Marie Skłodowska-Curie grant agreement No 101073554.
This project is experimental and under active development. Issue reports and contributions are very welcome.
To run examples, download the folder to your repository including the csv folders.
-
Install Git if you haven't already:
# For Ubuntu/Debian sudo apt-get install git # For Windows: Download from https://git-scm.com/download/win
-
Clone the repository:
git clone https://github.com/BernardoCV/pyflow_acdc.git
cd pyflow_acdc
- Install in development mode:
pip install -e .
This installs the package in "editable" mode, allowing you to modify the code without reinstalling.
- Create a new branch for your changes:
git checkout -b new-branch-name
git push origin new-branch-name
- To push your changes to the remote repository:
git add .
git commit -m "Description of your changes"
git pull origin new-branch-name
git push origin new-branch-name
- To pull the latest changes from the remote repository:
git pull origin main
To merge your changes into the main branch please contact the repository owner.
For Clustering you will need to install the following packages:
pip install numpy <2.0.0
pip install scikit-learn-extra
pip install scikit-learn
For mapping you will need to install the following packages:
pip install folium
For OPF you will need to install the following packages:
pip install numpy <2.0.0
pip install pyomo
pip install ipopt
For Dash you will need to install the following packages:
pip install dash
Online documentation can be found at:
https://pyflow-acdc.readthedocs.io/
To build the latest documentation of a branch, build it locally.
To build the documentation:
cd docs
pip install -r requirements.txt
make html
The documentation will be available in docs/_build/html/index.html