This release is a pre-release and may not be stable for production use.
Power Grid Model
power-grid-model is a library for steady-state distribution power system analysis distributed for Python and C.
The core of the library is written in C++.
Currently, it supports the following calculations:
- Symmetric and asymmetric power flow calculation with Newton-Raphson method, iterative current method and linear method
- Symmetric and asymmetric state estimation with iterative linear method
See the power-grid-model documentation for more information. For various conversions to the power-grid-model, refer to the power-grid-model-io repository.
Installation
Install from PyPI
You can directly install the package from PyPI.
pip install power-grid-model
Install from Conda
If you are using conda, you can directly install the package from conda-forge channel.
conda install -c conda-forge power-grid-model
Build and install from Source
To install the library from source, refer to the Build Guide.
Examples
Please refer to Examples for more detailed examples for power flow and state estimation. Notebooks for validating the input data and exporting input/output data are also included.
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, CONTRIBUTING, PROJECT GOVERNANCE and RELEASE for details on the process for submitting pull requests to us.
Visit Contribute for a list of good first issues in this repo.
Citations
If you are using Power Grid Model in your research work, please consider citing our library using the following references.
@software{Xiang_PowerGridModel_power-grid-model,
author = {Xiang, Yu and Salemink, Peter and Bharambe, Nitish and Govers, Martinus and van den Bogaard, Jonas and Stoeller, Bram and Jagutis, Laurynas and Wang, Chenguang and {Contributors from 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 = {CIRED 2023 - The 27th International Conference and Exhibition on Electricity Distribution},
title = {Power grid model: A high-performance distribution grid calculation library},
year = {2023},
volume={2023},
number = {},
pages={1-5}
}
Contact
Please read SUPPORT for how to connect and get into contact with the Power Gird Model project.
Release files for power-grid-model 1.5.0rc9216009937633
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-1.5.0rc9216009937633.tar.gz | 319.2 kB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| power_grid_model-1.5.0rc9216009937633-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details |
| power_grid_model-1.5.0rc9216009937633-py3-none-musllinux_1_2_x86_64.whl | Python 3 | none | Linux musl 1.2+ x86-64 | Details |
| power_grid_model-1.5.0rc9216009937633-py3-none-manylinux_2_24_x86_64.whl | Python 3 | none | Linux glibc 2.24+ x86-64 | Details |
| power_grid_model-1.5.0rc9216009937633-py3-none-manylinux_2_24_aarch64.whl | Python 3 | none | Linux glibc 2.24+ ARM64 | Details |
| power_grid_model-1.5.0rc9216009937633-py3-none-macosx_11_0_arm64.whl | Python 3 | none | macOS 11.0+ ARM64 | Details |
| power_grid_model-1.5.0rc9216009937633-py3-none-macosx_10_9_x86_64.whl | Python 3 | none | macOS 10.9+ x86-64 | Details |
Total release size: 3.9 MB
Release files / power-grid-model-1.5.0rc9216009937633.tar.gz
| Download URL | power-grid-model-1.5.0rc9216009937633.tar.gz |
|---|---|
| Size | 319.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
97791bdf470b59425ca001a60d6de3d872073494a322a037ea1cf82b68168260
|
|
BLAKE2b-256 checksum How to use checksums |
0c59e1dfd69a526f85d898ca05236444e9c190fac75d1eb38a499f7ff56dbf2e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / power_grid_model-1.5.0rc9216009937633-py3-none-win_amd64.whl
| Download URL | power_grid_model-1.5.0rc9216009937633-py3-none-win_amd64.whl |
|---|---|
| Size | 381.6 kB |
| Tags | Python 3 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
5b1c19e6abf7869105ca019c55e62632bb06f5ca2a61a1736dedc1cf934adc6c
|
|
BLAKE2b-256 checksum How to use checksums |
899bcdadc2b1200e46a3241818400cf72aaa50463e012c6af1fd143715a25b6f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / power_grid_model-1.5.0rc9216009937633-py3-none-musllinux_1_2_x86_64.whl
| Download URL | power_grid_model-1.5.0rc9216009937633-py3-none-musllinux_1_2_x86_64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | Linux musl 1.2+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
62d96750fe882c6b5f9fe226b4e7ce2560ec1cc17c066cf7e9fefe72e7b984d8
|
|
BLAKE2b-256 checksum How to use checksums |
8896d1c83b06a2f4bfcab792836b158bcc8a8279e191b07692fc489186ef07d7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / power_grid_model-1.5.0rc9216009937633-py3-none-manylinux_2_24_x86_64.whl
| Download URL | power_grid_model-1.5.0rc9216009937633-py3-none-manylinux_2_24_x86_64.whl |
|---|---|
| Size | 527.8 kB |
| Tags | Linux glibc 2.24+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
56eaa693c371dbbf5404b2c8b33400e32b73f7c4f6dda8800bcfb3c90ea01ff6
|
|
BLAKE2b-256 checksum How to use checksums |
94ce659e0456ae8f68c5cd86d603b4330776056a3a0c3e8bd9608f9c3c6788ed
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / power_grid_model-1.5.0rc9216009937633-py3-none-manylinux_2_24_aarch64.whl
| Download URL | power_grid_model-1.5.0rc9216009937633-py3-none-manylinux_2_24_aarch64.whl |
|---|---|
| Size | 494.0 kB |
| Tags | Linux glibc 2.24+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
d6fe24e53e7c55f239cfaaf1bbbe71d6785ccbfc646b510cf3c12c351a8e0a50
|
|
BLAKE2b-256 checksum How to use checksums |
97c9398c3f1fc2ac161bab216e978de8fb70b192da4c300b4a11ef55ed0866e7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / power_grid_model-1.5.0rc9216009937633-py3-none-macosx_11_0_arm64.whl
| Download URL | power_grid_model-1.5.0rc9216009937633-py3-none-macosx_11_0_arm64.whl |
|---|---|
| Size | 390.7 kB |
| Tags | Python 3 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
891e749e7b9019ac1cb2873725ed67a4e37f560524973d300a61745ca72846aa
|
|
BLAKE2b-256 checksum How to use checksums |
ccfd13d9d731d92a5ad7c059d98e289698c8a845c7c007a7a94b5761d6ca4c3a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / power_grid_model-1.5.0rc9216009937633-py3-none-macosx_10_9_x86_64.whl
| Download URL | power_grid_model-1.5.0rc9216009937633-py3-none-macosx_10_9_x86_64.whl |
|---|---|
| Size | 410.4 kB |
| Tags | Python 3 macOS 10.9+ x86-64 |
|
SHA-256 checksum How to use checksums |
87354bb9ccd56553661c93cd8b47c9b60b5eac960e6ddbaf38f6da8d82ea1f43
|
|
BLAKE2b-256 checksum How to use checksums |
8b3565503071927ed0f73aba70fd3aba84a282a8cd3d4cad6bd0d64f8503e648
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
