Power Grid Model Data Science (DS)
The Power Grid Model DS project extends the capabilities of the power-grid-model calculation core with a modelling and simulation interface. This is aimed at building data science software applications related to or using the power-grid-model project. It defines a Grid dataclass which manages the consistency of the complete network.
Some highlighted features:
- Using a model definition that corresponds to the power-grid-model, through which it is easy to do efficient grid calculations.
- The extended numpy model provides features which make development more pleasant and easy.
- Using the graph representation of the network, graph algorithms in rustworkx can be used to analyze the network.
- An interface to model network mutations which is useful in simulation use-cases.
- Visualization for easy exploration and debugging.
See the power-grid-model-ds documentation for more information.
Installation
Pip
pip install power-grid-model-ds
uv
uv add power-grid-model-ds
License
This project is licensed under the Mozilla Public License, version 2.0 - see LICENSE for details.
Licenses third-party libraries
This project includes third-party libraries, which are licensed under their own respective Open-Source licenses. SPDX-License-Identifier headers are used to show which license is applicable. The concerning license files can be found in the LICENSES directory.
Contributing
Please read CODE_OF_CONDUCT and CONTRIBUTING for details on the process for submitting pull requests to us.
Citations
If you are using Power Grid Model DS in your research work, please consider citing our library using the following references.
@software{Schouten_PowerGridModel_power-grid-model-ds,
author = {Schouten, Jaap and Baaijen, Thijs and Koppen, Vincent and van der Voort, Sven and {Contributors to the LF Energy project Power Grid Model}},
doi = {10.5281/zenodo.14825565},
license = {MPL-2.0},
title = {{PowerGridModel/power-grid-model-ds}},
url = {https://github.com/PowerGridModel/power-grid-model-ds}
}
@software{Xiang_PowerGridModel_power-grid-model,
author = {Xiang, Yu and Salemink, Peter and van Westering, Werner and Bharambe, Nitish and Govers, Martinus G.H. and van den Bogaard, Jonas and Stoeller, Bram and Wang, Zhen and Guo, Jerry Jinfeng and Figueroa Manrique, Santiago and Jagutis, Laurynas and Wang, Chenguang and van Raalte, Marc and {Contributors to the LF Energy project Power Grid Model}},
doi = {10.5281/zenodo.8054429},
license = {MPL-2.0},
title = {{PowerGridModel/power-grid-model}},
url = {https://github.com/PowerGridModel/power-grid-model}
}
@inproceedings{Xiang2023,
author = {Xiang, Yu and Salemink, Peter and Stoeller, Bram and Bharambe, Nitish and van Westering, Werner},
booktitle={27th International Conference on Electricity Distribution (CIRED 2023)},
title={Power grid model: a high-performance distribution grid calculation library},
year={2023},
volume={2023},
number={},
pages={1089-1093},
keywords={},
doi={10.1049/icp.2023.0633}
}
Contact
Please read SUPPORT for how to connect and get into contact with the Power Grid Model project.
Metadata
Release files for power-grid-model-ds 1.10.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| power_grid_model_ds-1.10.4.tar.gz | 76.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| power_grid_model_ds-1.10.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 186.3 kB
Release files / power_grid_model_ds-1.10.4.tar.gz
| Download URL | power_grid_model_ds-1.10.4.tar.gz |
|---|---|
| Size | 76.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2d2a831bfb932234936ba2d4be27a692447ef1778a6a69d48b5672c4cc9032f3
|
|
BLAKE2b-256 checksum How to use checksums |
aa654dfc0599eb5f8705ceacf0cc53cd3e6fb71f978258081c8464ea7cc375ae
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 10, 2026.
Transparency logRelease files / power_grid_model_ds-1.10.4-py3-none-any.whl
| Download URL | power_grid_model_ds-1.10.4-py3-none-any.whl |
|---|---|
| Size | 109.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
67ab738088fd8e80164598c302776aa7530b5bf007dc83c3162dbcf41f9ff29b
|
|
BLAKE2b-256 checksum How to use checksums |
44f0aa2bee91352e46de5cee771de92d73448fd62eccaf5eab547b9eeff51cb9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 10, 2026.
Transparency log
