pandapower

An easy to use open source tool for power system modeling, analysis and optimization with a high degree of automation.
https://github.com/e2niee/pandapower

Category: Energy Systems
Sub Category: Energy System Modeling Frameworks

Keywords

analysis loadflow optimization power powerflow python short-circuit state-estimation system

Keywords from Contributors

distribution-networks district-heating gas-network-simulation hydrogen multi-energy-systems pipe-network water-network-distribution energy-system power-systems powersystems

Last synced: about 8 hours ago
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Repository metadata

Convenient Power System Modelling and Analysis based on PYPOWER and pandas

README.rst

          
.. image:: https://www.pandapower.org/images/pp.svg
   :target: https://www.pandapower.org
   :alt: logo

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.. image:: https://badge.fury.io/py/pandapower.svg
   :target: https://pypi.python.org/pypi/pandapower
   :alt: PyPI

.. image:: https://img.shields.io/pypi/pyversions/pandapower.svg
   :target: https://pypi.python.org/pypi/pandapower
   :alt: versions

.. image:: https://readthedocs.org/projects/pandapower/badge/
   :target: http://pandapower.readthedocs.io/
   :alt: docs

.. image:: https://codecov.io/github/e2nIEE/pandapower/coverage.svg?branch=master
   :target: https://app.codecov.io/github/e2nIEE/pandapower?branch=master
   :alt: codecov

.. image:: https://api.codacy.com/project/badge/Grade/e2ce960935fd4f96b4be4dff9a0c76e3
   :target: https://app.codacy.com/gh/e2nIEE/pandapower?branch=master
   :alt: codacy

.. image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg
   :target: https://github.com/e2nIEE/pandapower/blob/master/LICENSE
   :alt: BSD

.. image:: https://pepy.tech/badge/pandapower
   :target: https://pepy.tech/project/pandapower
   :alt: pepy

.. image:: https://mybinder.org/badge_logo.svg
   :target: https://mybinder.org/v2/gh/e2nIEE/pandapower/master?filepath=tutorials
   :alt: binder





pandapower is an easy to use network calculation program aimed to automate the analysis and optimization of power
systems. It uses the data analysis library `pandas `_ and is compatible with the commonly
used MATPOWER / PYPOWER case format. pandapower allows using different solvers including an improved Newton-Raphson
power flow implementation, all `PYPOWER `_ solvers, the C++ library solvers for fast steady-state distribution power system analysis of `PowerGridModel `_, the Newton-Raphson power flow solvers in the C++ library `lightsim2grid `_, and the
`PowerModels.jl `_ library.

More information about pandapower can be found on `www.pandapower.org `_:

About pandapower:

- `Power System Modeling `_
- `Power System Analysis `_
- `Citing pandapower `_

Getting Started:

- `Installation Notes `_
- `Minimal Example `_
- `Interactive Tutorials `_
- `Documentation `_

If you are interested in the latest pandapower developments, subscribe to our `mailing list `_!

.. image:: https://simbench.de/wp-content/uploads/2019/01/logo.png
   :target: https://www.simbench.net
   :alt: SimBench_logo

To get realistic load profile data and grid models across all voltage levels that are ready to
be used in pandapower, have a look at the *SimBench* `project website `_ or
`on GitHub `_.

.. image:: https://www.pandapipes.org/images/pp.svg
   :target: https://www.pandapipes.org
   :width: 270pt
   :alt: pandapipes_logo

If you want to model pipe networks (heat, gas or water) as well, we recommend
pandapower's sibling project *pandapipes* (`website `_, `GitHub repository `_).

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pandapower is a joint development of the research group of the Department for Sustainable Electrical Energy Systems (e2n), University of Kassel and the Department for Distribution System
Operation at the Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), Kassel.

.. image:: http://www.pandapower.org/images/contact/Logo_e2n.png
    :target: https://www.uni-kassel.de/eecs/en/sections/energiemanagement-und-betrieb-elektrischer-netze/home
    :width: 500

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.. image:: https://www.pandapower.org/images/contact/Logo_Fraunhofer_IEE.png
    :target: https://www.iee.fraunhofer.de/en.html
    :width: 500

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We welcome contributions to pandapower of any kind - if you want to contribute, please check out the `pandapower contribution guidelines `_.

        

Citation (CITATION.bib)

@ARTICLE{pandapower.2018,
    author={L. Thurner and A. Scheidler and F. Sch{\"a}fer and J. Menke and J. Dollichon and F. Meier and S. Meinecke and M. Braun},
    journal={IEEE Transactions on Power Systems},
    title={pandapower — An Open-Source Python Tool for Convenient Modeling, Analysis, and Optimization of Electric Power Systems},
    year={2018},
    month={Nov},
    volume={33},
    number={6},
    pages={6510-6521},
    doi={10.1109/TPWRS.2018.2829021},
    ISSN={0885-8950}}

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Last synced: 28 days ago

Total Commits: 6,165
Total Committers: 144
Avg Commits per committer: 42.813
Development Distribution Score (DDS): 0.829

Commits in past year: 708
Committers in past year: 34
Avg Commits per committer in past year: 20.824
Development Distribution Score (DDS) in past year: 0.862

Name Email Commits
Roman Bolgaryn r****n@i****e 1055
Leon Thurner l****r@u****e 889
Steffen Meinecke s****e@u****e 661
Florian Schaefer f****r@u****e 387
Zhenqi Wang z****g@u****e 242
sdrauz S****z@i****e 192
hkoertge h****e@i****e 176
fmeier f****r@u****e 139
Shankho Ghosh g****o@g****m 132
Jan-Hendrik Menke j****e@u****e 126
Maryam Majidi m****i@u****e 121
mvogt m****t@i****e 114
Zheng Liu z****u@u****e 114
dlohmeier d****r@i****e 108
smeinecke s****e 103
Panos Xenos x****s@g****m 98
pawellytaev p****v@u****e 96
Jan Wiemer j****r@i****e 94
Jolando Kisse j****e@u****e 79
Alexander Scheidler a****r@i****e 76
Dominik Hilbrich d****h@i****e 70
jko j****c@g****m 67
Schaefer S****r 53
chefPony a****z@g****m 50
613j 3****L 49
Jannis Kupka j****a@u****e 42
Jan-Hendrik Menke m****l@j****e 39
mrichter m****r@i****e 37
Laurynas Zavistanavicius l****s@i****e 33
Moritz Franz m****z@i****e 33
and 114 more...

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Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 383
Total pull requests: 404
Average time to close issues: about 1 year
Average time to close pull requests: about 1 month
Total issue authors: 179
Total pull request authors: 67
Average comments per issue: 2.87
Average comments per pull request: 1.51
Merged pull request: 298
Bot issues: 0
Bot pull requests: 0

Past year issues: 134
Past year pull requests: 230
Past year average time to close issues: about 2 months
Past year average time to close pull requests: 19 days
Past year issue authors: 65
Past year pull request authors: 39
Past year average comments per issue: 2.51
Past year average comments per pull request: 1.51
Past year merged pull request: 163
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/e2niee/pandapower

Top Issue Authors

  • rbolgaryn (22)
  • KS-HTK (19)
  • SteffenMeinecke (18)
  • AnkurArohi (14)
  • SimonRubenDrauz (8)
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  • dlohmeier (8)
  • vogt31337 (8)
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Top Pull Request Authors

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  • SteffenMeinecke (42)
  • KS-HTK (38)
  • vogt31337 (25)
  • mfranz13 (22)
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  • pawellytaev (17)
  • dlohmeier (14)
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  • SimonRubenDrauz (13)
  • quant12345 (13)
  • heckstrahler (10)
  • mfisch42 (9)
  • jkisse (7)
  • Ghanshyam-grid (6)

Top Issue Labels

  • bug (146)
  • enhancement (40)
  • OPF (28)
  • powerflow (26)
  • maintenance (26)
  • feature (23)
  • question (22)
  • converter (18)
  • help wanted! (18)
  • fileIO (18)
  • plotting (17)
  • 3ph powerflow (14)
  • shortcircuit (12)
  • docs/tutorials (10)
  • compatibility (10)
  • dependencies (10)
  • state estimation (9)
  • stale (9)
  • controller (8)
  • PowerModels (7)
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  • topology (4)
  • dc (4)
  • networks (3)
  • protection (3)
  • CI (2)
  • pd2ppc (2)
  • PandaModels (2)
  • coverage (1)
  • power-grid-model (1)

Top Pull Request Labels

  • bug (23)
  • converter (20)
  • powerflow (14)
  • plotting (12)
  • enhancement (10)
  • maintenance (9)
  • feature (9)
  • compatibility (6)
  • docs/tutorials (5)
  • controller (5)
  • fileIO (4)
  • dependencies (4)
  • stale (4)
  • networks (3)
  • timeseries (2)
  • shortcircuit (2)
  • topology (2)
  • question (2)
  • protection (1)
  • grid_equivalents (1)
  • contingency (1)

Package metadata

pypi.org: pandapower

An easy to use open source tool for power system modeling, analysis and optimization with a high degree of automation.

  • Homepage: https://www.pandapower.org
  • Documentation: https://pandapower.readthedocs.io
  • Licenses: BSD License
  • Latest release: 3.1.1 (published 12 days ago)
  • Last Synced: 2025-06-06T10:41:46.688Z (1 day ago)
  • Versions: 49
  • Dependent Packages: 28
  • Dependent Repositories: 75
  • Downloads: 50,151 Last month
  • Docker Downloads: 289
  • Rankings:
    • Dependent packages count: 0.701%
    • Average: 1.697%
    • Dependent repos count: 1.715%
    • Downloads: 2.134%
    • Docker downloads count: 2.238%
  • Maintainers (2)
proxy.golang.org: github.com/e2niee/pandapower

  • Homepage:
  • Documentation: https://pkg.go.dev/github.com/e2niee/pandapower#section-documentation
  • Licenses: other
  • Latest release: v3.1.1+incompatible (published 12 days ago)
  • Last Synced: 2025-06-06T10:41:46.429Z (1 day ago)
  • Versions: 49
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent packages count: 5.401%
    • Average: 5.583%
    • Dependent repos count: 5.764%
proxy.golang.org: github.com/e2nIEE/pandapower

  • Homepage:
  • Documentation: https://pkg.go.dev/github.com/e2nIEE/pandapower#section-documentation
  • Licenses: other
  • Latest release: v3.1.1+incompatible (published 12 days ago)
  • Last Synced: 2025-06-06T10:41:46.664Z (1 day ago)
  • Versions: 49
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent packages count: 5.401%
    • Average: 5.583%
    • Dependent repos count: 5.764%

Dependencies

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doc/requirements.txt pypi
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setup.py pypi
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  • pandas >=1.0
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.github/workflows/test_release.yml actions
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  • actions/setup-python v5 composite
.github/workflows/upload_release.yml actions
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  • juliangruber/sleep-action v1 composite
pyproject.toml pypi
  • deepdiff *
  • networkx >=2.5
  • numpy *
  • packaging *
  • pandas >=1.0
  • scipy *
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Score: 22.87543537304854