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ieeh-power-system-data-model

A hierarchical data model for the description of electrical power systems.

https://github.com/ieeh-tu-dresden/power-system-data-model

Science Score: 75.0%

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
    Found 5 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ✓
    Institutional organization owner
    Organization ieeh-tu-dresden has institutional domain (tu-dresden.de)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.4%) to scientific vocabulary

Keywords

datamodel powersystem python
Last synced: 6 months ago · JSON representation ·

Repository

A hierarchical data model for the description of electrical power systems.

Basic Info
  • Host: GitHub
  • Owner: ieeh-tu-dresden
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 14.3 MB
Statistics
  • Stars: 7
  • Watchers: 0
  • Forks: 0
  • Open Issues: 12
  • Releases: 19
Topics
datamodel powersystem python
Created almost 3 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing License Citation Authors Zenodo

README.md

License

A data model for the description of electrical power systems.

Field of Application

This data model is intended to describe electrical power systems. It provides a hierarchical structure/schema to describe unique entity relations as well as parameter sets.

The data model is structured as the following schema:

Grid Topology

This is the base topology containing all elements of the exported grid: - Branches (symmetrical: overhead lines, cables, fuses from type "branch") - Nodes - Transformers (symmetrical: 2- or 3-winding) - External grids - Loads (consumer, producer, grid assets) topology relationship diagram

In addition to the explicitly defined element attributes, it is possible to save user-specific additional information as optional AttributeData (Export example of powerfactory-tools).

Topology Case

This holds information about disabled elements to represent a specific operational case based on the base topology. topology case relationship diagram

Steadystate Case

This holds information for a specific operational case such as: - power draw/infeed of load - tap posistion of transformer - operating point of external grid steadystate case relationship diagram

General Remarks

Please find below some important general remarks and assumptions to consider for consistent usage across different applications: - The passive sign convention should be used for all types of loads (consumer as well as producer). - Numeric values should be set using the SI unit convention. - Topology - Only symmetrical grid assets, e.g. transformer or line, are supported. - The Rated Power should always be defined positive (absolute value). - The interaction between load models and controllers are depicted in the following schematic: active/reactive power schematics

Installation

Just install via pip:

bash pip install ieeh-power-system-data-model

Development

Install the Python package and project manager uv

Clone power-system-data-model

bash git@github.com:ieeh-tu-dresden/power-system-data-model.git

bash cd power-system-data-model

Install power-system-data-model as a production tool

bash uv sync --no-dev

Install power-system-data-model in development mode

bash uv sync

For development in Visual Studio Code, all configurations are already provided:

Attribution

Please provide a link to this repository:

https://github.com/ieeh-tu-dresden/power-system-data-model

Please cite as:

Institute of Electrical Power Systems and High Voltage Engineering - TU Dresden, Power System Data Model - A data model for the description of electrical power systems, Zenodo, 2023. https://doi.org/10.5281/zenodo.8087079.

DOI

Owner

  • Name: Institute of Electrical Power Systems and High Voltage Engineering - TU Dresden
  • Login: ieeh-tu-dresden
  • Kind: organization
  • Location: Germany

Official github account of the IEEH (@ TU Dresden) - one of the leading German higher education research institutes in the field of power systems

Citation (CITATION.cff) 

cff-version: 2.3.3
message: "If you use this software, please cite it as below."
authors:
  - family-names: "Institute of Electrical Power Systems and High Voltage Engineering - TU Dresden"
    given-names:
title: "Power System Data Model - A data model for the description of electrical power systems"
doi: 10.5281/zenodo.7781375
date-released: 2023
repository-code: "https://github.com/ieeh-tu-dresden/power-system-data-model"
keywords:
  - "Power System Modeling"
  - "JSON"
  - "Python"
  - "Data Model"
license: BSD 3-Clause

GitHub Events

Total
  • Create event: 32
  • Release event: 2
  • Issues event: 26
  • Watch event: 2
  • Delete event: 20
  • Issue comment event: 12
  • Push event: 67
  • Pull request review comment event: 9
  • Pull request review event: 32
  • Pull request event: 57
Last Year
  • Create event: 32
  • Release event: 2
  • Issues event: 26
  • Watch event: 2
  • Delete event: 20
  • Issue comment event: 12
  • Push event: 67
  • Pull request review comment event: 9
  • Pull request review event: 32
  • Pull request event: 57

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 88
  • Total pull requests: 128
  • Average time to close issues: 20 days
  • Average time to close pull requests: 7 days
  • Total issue authors: 5
  • Total pull request authors: 4
  • Average comments per issue: 0.16
  • Average comments per pull request: 0.27
  • Merged pull requests: 89
  • Bot issues: 0
  • Bot pull requests: 41
Past Year
  • Issues: 12
  • Pull requests: 59
  • Average time to close issues: 9 days
  • Average time to close pull requests: 10 days
  • Issue authors: 2
  • Pull request authors: 4
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.39
  • Merged pull requests: 23
  • Bot issues: 0
  • Bot pull requests: 37
View more stats
Top Authors
Issue Authors
  • SebastianDD (45)
  • sasanjac (32)
  • FiedLa (3)
  • cklb (2)
  • jayqi (1)
Pull Request Authors
  • SebastianDD (54)
  • sasanjac (52)
  • dependabot[bot] (48)
  • github-actions[bot] (4)
Top Labels
Issue Labels
bug (28) enhancement (25) ci (15) documentation (8) code enhancement (6) wontfix (2)
Pull Request Labels
dependencies (47) github_actions (46) enhancement (1) documentation (1) ci (1) python (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 179 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 0
  • Total versions: 21
  • Total maintainers: 1
pypi.org: ieeh-power-system-data-model

A data model for describing power systems

  • Documentation: https://ieeh-power-system-data-model.readthedocs.io/
  • License: BSD 3-Clause License Copyright (c) 2022-2025, Institute of Electrical Power Systems and High Voltage Engineering - TU Dresden All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  • Latest release: 2.3.3
    published 10 months ago
  • Versions: 21
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 179 Last month
Rankings
Dependent packages count: 6.6%
Average: 18.6%
Dependent repos count: 30.6%
Maintainers (1)
tud-ieeh
Last synced: 6 months ago

Dependencies

.github/workflows/checks.yml actions
  • actions/checkout v3 composite
  • pdm-project/setup-pdm v3 composite
.github/workflows/release.yml actions
  • FantasticFiasco/action-update-license-year v2 composite
  • actions/checkout v3 composite
  • benjefferies/branch-protection-bot master composite
  • commitizen-tools/commitizen-action master composite
  • pdm-project/setup-pdm v3 composite
  • softprops/action-gh-release v1 composite
.github/workflows/tests.yml actions
  • actions/checkout v3 composite
  • pdm-project/setup-pdm v3 composite
pyproject.toml pypi
  • loguru *
  • pydantic *