PowerDynamics.jl

Provides all the tools you need to create a dynamic power grid model and analyze it.
https://github.com/JuliaEnergy/PowerDynamics.jl

Category: Energy Systems
Sub Category: Grid Analysis and Planning

Keywords from Contributors

power-systems dynamic-simulation inverters microgrids julialang numerical programming-language sciml differential-equations energy-system

Last synced: about 22 hours ago
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Package for dynamical modeling of power grids

README.md

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PowerDynamics.jl: An Open-Source Framework Written in Julia for Dynamic Power Grid Modeling and Analysis.
The main idea of this package is to turn dynamic power grid models into a right-hand-side function of a DAE system, which can then be solved using OrdinaryDiffEq.jl.

The main features of PowerDynamics are:

  • ModelingToolkit.jl based Frontend: Component models such as machines, controllers, power lines, ... are all defined as symbolic, equation-based MTK models.
  • NetworkDynamics.jl based Backend: PD.jl generates Julia code for each of the MTK models as NetworkDynamics.jl compatible vertex- and edge models. NetworkDynamics is used to interconnect those bus and edge models.
  • Component-Based Initialisation: Annotate your dynamic models with simplified powerflow models. Solve the powerflow and initialize free dynamic states and parameters of the node and edge models to fit the powerflow result.
  • Symbolic Indexing and Observables: Use your typical SciML syntax like plot(sol, idxs=VIndex(2,:busbar₊u_mag)) to access arbitrary states, parameters, observables of your MTK models (in this case, the variable named busbar₊u_mag of vertex model 2).

... and there is much more! Please check out the Documentation.

Citation

If you use PowerDynamics.jl in your research publications, please cite our paper.

@article{PowerDynamics2022,
  title={PowerDynamics.jl--An experimentally validated open-source package for the dynamical analysis of power grids},
  author={Plietzsch, Anton and Kogler, Raphael and Auer, Sabine and Merino, Julia and Gil-de-Muro, Asier and Li{\ss}e, Jan and Vogel, Christina and Hellmann, Frank},
  journal = {SoftwareX},
  volume = {17},
  pages = {100861},
  year = {2022},
  publisher={Elsevier}
}

Funding

Development of this project was in part funded by the German Federal Ministry for Economic Affairs and Climate Action as part of the OpPoDyn-Project (Project ID 01258425/1, 2024-2027).

Citation (CITATION.bib)

@article{PowerDynamics2022,
  title={PowerDynamics.jl--An experimentally validated open-source package for the dynamical analysis of power grids},
  author={Plietzsch, Anton and Kogler, Raphael and Auer, Sabine and Merino, Julia and Gil-de-Muro, Asier and Li{\ss}e, Jan and Vogel, Christina and Hellmann, Frank},
  journal = {SoftwareX},
  volume = {17},
  pages = {100861},
  year = {2022},
  publisher={Elsevier}
}

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Name Email Commits
Hans Würfel g****t@w****o 370
Jan Lisse j****e@p****e 188
timkittel 1****l 140
SabineAuer s****r@e****m 104
Mandy Wältermann m****n@t****e 74
antonplietzsch 4****h 50
github-actions[bot] 4****] 34
Paul Schultz 2****k 32
Jan Lisse j****e@g****m 20
Tim Kittel t****l@e****m 18
Micha m****r@p****e 18
Frank Hellmann h****n@p****e 8
WouterVer 4****r 8
Anbue63 3****3 6
CompatHelper Julia c****y@j****g 6
dependabot[bot] 4****] 4
Anna Büttner 3****r 2
Fredrik Ekre e****k@g****m 2
Jan Weidner j****6@g****m 2
Logan Kilpatrick 2****3@g****m 2
Morten Piibeleht m****t@g****m 2
Oscar Dowson o****w 2
byronbest 4****t 2

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Last synced: 9 days ago

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Past year issues: 2
Past year pull requests: 30
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Package metadata

juliahub.com: PowerDynamics

Package for dynamical modeling of power grids

  • Homepage: https://juliaenergy.github.io/PowerDynamics.jl/latest/
  • Documentation: https://docs.juliahub.com/General/PowerDynamics/stable/
  • Licenses: MIT
  • Latest release: 4.3.1 (published 3 months ago)
  • Last Synced: 2025-12-20T22:06:47.055Z (5 days ago)
  • Versions: 36
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 8 Total
  • Rankings:
    • Forks count: 5.775%
    • Stargazers count: 8.373%
    • Dependent repos count: 9.94%
    • Average: 15.751%
    • Dependent packages count: 38.915%

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