Skip to main content

Python/C++ library for distribution power system analysis

Project description

PyPI version Anaconda-Server Badge License: MPL2.0 Build and Test C++ and Python Check Code Quality Clang Tidy REUSE Compliance Check docs Downloads Downloads

Quality Gate Status Coverage Maintainability Rating Reliability Rating Security Rating Vulnerabilities

DOI

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:

  • Power Flow
  • State Estimation
  • Short Circuit

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.

Want to be updated on the latest news and releases? Subscribe to the Power Grid Model mailing list by sending an (empty) email to: powergridmodel+subscribe@lists.lfenergy.org

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.

DOI

@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 Wang, Zhen and Guo, Jerry 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 = {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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

power_grid_model-1.7.70.tar.gz (805.4 kB view details)

Uploaded Source

Built Distributions

power_grid_model-1.7.70-py3-none-win_amd64.whl (536.8 kB view details)

Uploaded Python 3 Windows x86-64

power_grid_model-1.7.70-py3-none-musllinux_1_2_x86_64.whl (1.8 MB view details)

Uploaded Python 3 musllinux: musl 1.2+ x86-64

power_grid_model-1.7.70-py3-none-manylinux_2_24_x86_64.whl (829.2 kB view details)

Uploaded Python 3 manylinux: glibc 2.24+ x86-64

power_grid_model-1.7.70-py3-none-manylinux_2_24_aarch64.whl (759.8 kB view details)

Uploaded Python 3 manylinux: glibc 2.24+ ARM64

power_grid_model-1.7.70-py3-none-macosx_11_0_arm64.whl (589.9 kB view details)

Uploaded Python 3 macOS 11.0+ ARM64

power_grid_model-1.7.70-py3-none-macosx_10_9_x86_64.whl (642.6 kB view details)

Uploaded Python 3 macOS 10.9+ x86-64

File details

Details for the file power_grid_model-1.7.70.tar.gz.

File metadata

  • Download URL: power_grid_model-1.7.70.tar.gz
  • Upload date:
  • Size: 805.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.14

File hashes

Hashes for power_grid_model-1.7.70.tar.gz
Algorithm Hash digest
SHA256 affc314e8a0e00af62f0c686e51144525db94fa7bb488cb717b61630a2dbeb97
MD5 8844a3dbc187d62bf7dcdce425dd6d19
BLAKE2b-256 39aee23a872786960d0495f050bb47254fd6aec7d495109a14849298c703b463

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.70-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.70-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 70e2b50b761f9340f6730d2938ca2314bb896c072a41002ac2f4b736b99ae919
MD5 e7f48880296748e5d6dc0431495a97d6
BLAKE2b-256 d78c589686ae40b9c11ed607c8c012c6928481c1ed63102cd68ce4c3ab95b880

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.70-py3-none-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.70-py3-none-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 3c74a1c2a7a0e18d8dbfd94e95929eb39ef8a316af72a709c1b5479722bf9350
MD5 6037fd45ed573335354ce68461c993d6
BLAKE2b-256 b3361bb0fde9d22149d32a0adc07f40440098b2fe611868f33cb035c9c7c890f

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.70-py3-none-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.70-py3-none-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 fda657af544d6d7ee308c5e101c99645384f11e56849b8d89ff06a5729226ff8
MD5 db6acc2d00f8b80df8a9fb2112831432
BLAKE2b-256 7eac6f4ded7cc69d22bec947e4cb5ee9920e147ab512e9e26894f9daeef65ea4

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.70-py3-none-manylinux_2_24_aarch64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.70-py3-none-manylinux_2_24_aarch64.whl
Algorithm Hash digest
SHA256 1916880e7a62082f1c0eb76a41ecaa9a2d68b9a07c4088b3ff869b96e310c115
MD5 d6253acf20a167956e1b0ecd7a63753c
BLAKE2b-256 c4534a2afb66cb61dc70be0a119c9df3c1772d393bac73bf0b831e043e36c847

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.70-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.70-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9947f6078ba91813f24666a9f73158c09b3b10ef301ec611d62229b06d588b72
MD5 fe382104f6196d10383ce9cb2e156a1a
BLAKE2b-256 ad8ecafd306089b285451a9dd5bb7a381c3e539f1bf0d552f4eb030fe967e20a

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.70-py3-none-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.70-py3-none-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4aa9a5974161ffdc396075dab9fb1048d4d3102e1ea5e99c69bdb7b2136880cf
MD5 b2fedc2dc4d80e5d50ab91d7941b8b64
BLAKE2b-256 3d484b0ac584d78bb0d360acebeff0bc3efe599bd6a923e625b0830e89f4b359

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page