pandapower

Convenient Power System Modelling and Analysis based on PYPOWER and pandas

https://github.com/e2niee/pandapower

Science Score: 54.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
○
DOI references
○
Academic publication links
✓
Committers with academic emails
53 of 144 committers (36.8%) from academic institutions
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary

Keywords

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

Keywords from Contributors

powersystem energy-system electrical nrel interface plotly energy-system-model power-systems matpower matpower-github

Last synced: 4 months ago · JSON representation ·

Repository

Convenient Power System Modelling and Analysis based on PYPOWER and pandas

Basic Info

Host: GitHub
Owner: e2nIEE
License: other
Language: Python
Default Branch: develop
Homepage: https://www.pandapower.org
Size: 664 MB

Statistics

Stars: 1,016
Watchers: 51
Forks: 523
Open Issues: 203
Releases: 45

Topics

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

Created almost 9 years ago · Last pushed 4 months ago

Metadata Files

Readme Changelog Contributing License Citation Authors

README.rst

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

|

.. 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 `_).

|

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

|

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

|

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

Owner

Name: e2nIEE
Login: e2nIEE
Kind: organization
Email: info@pandapower.org
Location: Kassel, Germany

Repositories: 7
Profile: https://github.com/e2nIEE

Joint account of the pandapower development team at the University of Kassel, Department e2n and the Fraunhofer IEE

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}}

GitHub Events

Total

Fork event: 42
Create event: 26
Commit comment event: 1
Release event: 1
Issues event: 172
Watch event: 153
Delete event: 19
Member event: 2
Issue comment event: 547
Push event: 292
Pull request review comment event: 116
Pull request review event: 260
Pull request event: 256

Last Year

Fork event: 42
Create event: 26
Commit comment event: 1
Release event: 1
Issues event: 172
Watch event: 153
Delete event: 19
Member event: 2
Issue comment event: 547
Push event: 292
Pull request review comment event: 116
Pull request review event: 260
Pull request event: 256

Committers

Last synced: 4 months ago

All Time

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

Past Year

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

Top Committers

Name	Email	Commits
Roman Bolgaryn	r**n@i**e	1,055
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...

Committer Domains (Top 20 + Academic)

iee.fraunhofer.de: 20 uni-kassel.de: 18 iwes.fraunhofer.de: 5 iee-extern.fraunhofer.de: 3 alliander.com: 2 student.uni-kassel.de: 2 gmx.de: 2 jhmenke.de: 1 mail.ru: 1 elektro.dtu.dk: 1 gmx.at: 1 9code.ch: 1 joschkathurner.de: 1 ei.uni-hannover.de: 1 163.com: 1 bergkv.ist: 1 ifht.rwth-aachen.de: 1 powerco.co.nz: 1 kit.edu: 1 outlook.de: 1 uni-bonn.de: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 338
Total pull requests: 623
Average time to close issues: about 1 year
Average time to close pull requests: about 1 month
Total issue authors: 185
Total pull request authors: 71
Average comments per issue: 2.35
Average comments per pull request: 1.31
Merged pull requests: 446
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 102
Pull requests: 296
Average time to close issues: 27 days
Average time to close pull requests: 15 days
Issue authors: 64
Pull request authors: 35
Average comments per issue: 1.15
Average comments per pull request: 1.31
Merged pull requests: 200
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

SteffenMeinecke (17)
rbolgaryn (16)
KS-HTK (14)
AnkurArohi (13)
dlohmeier (7)
vogt31337 (7)
SimonRubenDrauz (6)
BDonnot (5)
HafizRiaz (5)
marhofmann (5)
jkisse (5)
jwiemer112 (5)
quant12345 (4)
PB-vines (4)
bp50hz (4)

Pull Request Authors

rbolgaryn (68)
KS-HTK (67)
SteffenMeinecke (66)
vogt31337 (39)
mrifraunhofer (34)
mfranz13 (29)
pawellytaev (29)
hilbrich (21)
SimonRubenDrauz (19)
quant12345 (19)
dlohmeier (16)
mfisch42 (15)
heckstrahler (15)
Ghanshyam-grid (13)
Irene270 (12)

Top Labels

Issue Labels

bug (127) enhancement (26) OPF (21) powerflow (20) maintenance (18) converter (16) plotting (15) feature (15) fileIO (14) question (13) help wanted! (13) 3ph powerflow (12) dependencies (8) compatibility (8) shortcircuit (8) docs/tutorials (8) stale (7) PowerModels (6) controller (5) timeseries (4) networks (3) pd2ppc (2) protection (2) CI (2) state estimation (2) PandaModels (2) topology (2) dc (2) power-grid-model (1) coverage (1)

Pull Request Labels

converter (31) bug (25) plotting (16) enhancement (15) powerflow (15) maintenance (12) feature (12) controller (8) fileIO (6) docs/tutorials (5) compatibility (5) dependencies (5) stale (4) timeseries (3) shortcircuit (3) topology (3) networks (3) question (3) protection (1) grid_equivalents (1) contingency (1)

Packages

Total packages: 3
Total downloads:
- pypi 89,765 last-month
Total docker downloads: 289

Total dependent packages: 28
(may contain duplicates)
Total dependent repositories: 75
(may contain duplicates)
Total versions: 150
Total maintainers: 2

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
License: BSD License
Latest release: 3.1.2
published 6 months ago

Versions: 50
Dependent Packages: 28
Dependent Repositories: 75
Downloads: 89,765 Last month
Docker Downloads: 289

Rankings

Dependent packages count: 0.7%

Average: 1.7%

Dependent repos count: 1.7%

Downloads: 2.1%

Docker downloads count: 2.2%

Maintainers (2)

pandapower vogt31337

Last synced: 4 months ago

proxy.golang.org: github.com/e2nIEE/pandapower

Documentation: https://pkg.go.dev/github.com/e2nIEE/pandapower#section-documentation
License: other
Latest release: v3.1.2+incompatible
published 6 months ago

Versions: 50
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.4%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 4 months ago

proxy.golang.org: github.com/e2niee/pandapower

Documentation: https://pkg.go.dev/github.com/e2niee/pandapower#section-documentation
License: other
Latest release: v3.1.2+incompatible
published 6 months ago

Versions: 50
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.4%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 4 months ago

Dependencies

.github/workflows/github_test_action.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
codecov/codecov-action v1 composite
e2nIEE/sphinx-action master composite

doc/requirements.txt pypi

numpydoc >=1.5.0
sphinx >=5.3.0
sphinx_rtd_theme >=1.1.1

setup.py pypi

deepdiff *
networkx >=2.5
numpy *
packaging *
pandas >=1.0
scipy *
tqdm *

.github/workflows/test_release.yml actions

actions/checkout v4 composite
actions/setup-python v5 composite

.github/workflows/upload_release.yml actions

actions/checkout v4 composite
actions/setup-python v5 composite
juliangruber/sleep-action v1 composite

pyproject.toml pypi

deepdiff *
networkx >=2.5
numpy *
packaging *
pandas >=1.0
scipy *
tqdm *