Skip to main content

Python/C++ library for distribution power system analysis

Project description

PyPI version Anaconda-Server Badge License: MIT 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-1.7.26.tar.gz (749.2 kB view details)

Uploaded Source

Built Distributions

power_grid_model-1.7.26-py3-none-win_amd64.whl (511.1 kB view details)

Uploaded Python 3 Windows x86-64

power_grid_model-1.7.26-py3-none-musllinux_1_2_x86_64.whl (1.7 MB view details)

Uploaded Python 3 musllinux: musl 1.2+ x86-64

power_grid_model-1.7.26-py3-none-manylinux_2_24_x86_64.whl (827.6 kB view details)

Uploaded Python 3 manylinux: glibc 2.24+ x86-64

power_grid_model-1.7.26-py3-none-manylinux_2_24_aarch64.whl (766.1 kB view details)

Uploaded Python 3 manylinux: glibc 2.24+ ARM64

power_grid_model-1.7.26-py3-none-macosx_11_0_arm64.whl (580.6 kB view details)

Uploaded Python 3 macOS 11.0+ ARM64

power_grid_model-1.7.26-py3-none-macosx_10_9_x86_64.whl (640.6 kB view details)

Uploaded Python 3 macOS 10.9+ x86-64

File details

Details for the file power-grid-model-1.7.26.tar.gz.

File metadata

  • Download URL: power-grid-model-1.7.26.tar.gz
  • Upload date:
  • Size: 749.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.13

File hashes

Hashes for power-grid-model-1.7.26.tar.gz
Algorithm Hash digest
SHA256 34d6a0857b696353f7d8ab8929a7d99621db75bbd62e2a62e150ed4a1171b80f
MD5 0de50c0259c5c9e5907d20fce49ac9ed
BLAKE2b-256 48452666fde5c7d756c6b558c5534b4de61bd977cde71c2ce9aa34c15b4e5e95

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.26-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.26-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 b2a496162d15cf0455c0cb8b4047bbbe00f66afa8f249de0ff733415ce86bad9
MD5 05b23c8d2ffd27b2ddfa5ded608aa986
BLAKE2b-256 cedda93ba515e8441942887ddda0a27f0f716a05436d67e1b1913ef1502f811d

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.26-py3-none-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.26-py3-none-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 6475aa2cf6ea4c689a13e20b842b83db7218be44b1967615e2de90c00dc2b791
MD5 8271cf31c220cef309fbe6f2b6a0273a
BLAKE2b-256 3bedc5594901015e65bc6c422d1b979a900aad5eb7180ee58af0a72b3f35752b

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.26-py3-none-manylinux_2_24_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.26-py3-none-manylinux_2_24_x86_64.whl
Algorithm Hash digest
SHA256 99d51a7dab94a52317069131548de3ef94b02ea7635ab4ffa228913d0056eaab
MD5 3d2f6e5d91ccb1d72d3ad9153eeb535e
BLAKE2b-256 ed94fd5395cb8a126e2f517e4fdaa6789c6a8ce36cdd158d647a75f02ad16381

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.26-py3-none-manylinux_2_24_aarch64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.26-py3-none-manylinux_2_24_aarch64.whl
Algorithm Hash digest
SHA256 6b146befbae45543f70215f8fe6999126ec098adf1292946acd1f56b54759449
MD5 faee0306e13c2ca09272d7e15c5775b0
BLAKE2b-256 524e0ab67098b5d0c4c1defd367364c6a7d68b7f6394912e59dbbfce26c7149e

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.26-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.26-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d196fb9e36a54921d5390312822c27f16dddb7cd5704ec236de34915c631c576
MD5 b7b350678d768439c29d353140defb26
BLAKE2b-256 22130df4ddaa294213740f2ab8c8cfd0d6c512aa0442f93cd921fc5ded8c9373

See more details on using hashes here.

File details

Details for the file power_grid_model-1.7.26-py3-none-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for power_grid_model-1.7.26-py3-none-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 45749c527ccc3e5c708f50e1168c146c378b48722f1c0e5dd8304045f0f8891e
MD5 21c6430a411b96374a5ecbb377c5a552
BLAKE2b-256 931f84c3e3fa5e99688c49f525121119e0752e70b8d8ba63c587b654c8fa4dbe

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