gridmeta

A repository for extracting dehydrated metadata for distribution power grid model.

https://github.com/grid-atlas/grid-meta

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
    2 of 2 committers (100.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.6%) to scientific vocabulary

Keywords

jsonschema mkdocs-material opendss python
Last synced: 6 months ago · JSON representation ·

Repository

A repository for extracting dehydrated metadata for distribution power grid model.

Basic Info
Statistics
  • Stars: 6
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 2
Topics
jsonschema mkdocs-material opendss python
Created 9 months ago · Last pushed 6 months ago
Metadata Files
Readme Changelog License Citation

README.md

Getting Started with grid-meta

Build Python License Coverage

View Full Documentation..

Welcome! Follow the steps below to get grid-meta up and running locally.
We recommend using a Python virtual environment for a clean install 🔒🐍.

🧪 Step 1: Set Up a Python Environment

To avoid dependency conflicts, create and activate a virtual environment.

You can use any tool of your choice — here are a few popular options:

🟢 Option A: Using venv (Standard Library) ```bash python3 -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate ```
🔵 Option B: Using conda ```bash conda create -n grid-reducer-env python=3.10 conda activate grid-reducer-env ```

🚀 Step 2: Install the Project Locally

Install the project.

bash pip install gridmeta

✅ This will also install all required dependencies.

🛠 Example CLI Usage

You can currently use this package as CLI tool. To see the available commands please use following command.

bash gridmeta --help

```bash Usage: gridmeta [OPTIONS] COMMAND [ARGS]...

Options: --help Show this message and exit.

Commands: extract-opendss-dehydrated-dataset ```

To extract opendss model dehydrated metadata you can use following command.

bash gridmeta extract-opendss-dehydrated-dataset -f tests\data\opendss\ieee13\master.dss -o test.json

You can specify privacy flag with -pm option.

bash gridmeta extract-opendss-dehydrated-dataset -f tests\data\opendss\ieee13\master.dss -pm "low" -o test.json

Make sure to pass appropriate file paths. You can also update model year, state, region type and description from command line. Defaults will be used if these are not provided.

Example

Here is an example of extracted metadata for IEEE 13 opendss model.

```json { "metadata": { "state": "WA", "createdat": "2025-02-26T16:07:47.810263", "modelyear": 2025, "info": "", "regiontype": "Suburban" }, "assets": { "transformers": [ { "kva": 500, "count": 1, "isregulator": false, "issubstationtransformer": false, "numphase": 3, "highkv": 4.16, "lowkv": 0.48, "avgcustomersserved": 3.0, "mincustomersserved": 3.0, "maxcustomersserved": 3.0, "stdcustomersserved": "NaN", "minpctpeakloading": 107.2857856604396, "avgpctpeakloading": 107.2857856604396, "maxpctpeakloading": 107.2857856604396, "stdpctpeakloading": "NaN" }, { "kva": 1666, "count": 3, "isregulator": true, "issubstationtransformer": false, "numphase": 1, "highkv": 2.4, "lowkv": 2.4, "avgcustomersserved": 5.0, "mincustomersserved": 0.0, "maxcustomersserved": 15.0, "stdcustomersserved": 8.660254037844387, "minpctpeakloading": 56.934951911321086, "avgpctpeakloading": 72.20336662873115, "maxpctpeakloading": 81.85450680902247, "stdpctpeakloading": 13.375776014643415 }, { "kva": 5000, "count": 1, "isregulator": false, "issubstationtransformer": true, "numphase": 3, "highkv": 115.0, "lowkv": 4.16, "avgcustomersserved": 15.0, "mincustomersserved": 15.0, "maxcustomersserved": 15.0, "stdcustomersserved": "NaN", "minpctpeakloading": 80.6972565800457, "avgpctpeakloading": 80.6972565800457, "maxpctpeakloading": 80.6972565800457, "stdpctpeakloading": "NaN" } ], "feedersections": [ { "kv": 2.40178, "numphase": 1.0, "count": 2.0, "avgfeedermiles": 0.16763999999999998, "minfeedermiles": 0.09144, "maxfeedermiles": 0.24383999999999997, "stdfeedermiles": 0.10776307345282983, "minampacity": 400.0, "avgampacity": 400.0, "maxampacity": 400.0, "stdampacity": 0.0, "avgperunitresistanceohmpermile": 8.259058763487898e-5, "minperunitresistanceohmpermile": 4.504941143720672e-5, "maxperunitresistanceohmpermile": 0.00012013176383255125, "stdperunitresistanceohmpermile": 5.309124052618614e-5, "avgperunitreactanceohmpermile": 0.00017173146325459316, "minperunitreactanceohmpermile": 9.36717072297781e-5, "maxperunitreactanceohmpermile": 0.00024979121927940824, "stdperunitreactanceohmpermile": 0.00011039316564582839, "mincustomersserved": 1.0, "avgcustomersserved": 1.0, "maxcustomersserved": 1.0, "stdcustomersserved": 0.0, "minpctpeakloading": 15.674269355370459, "avgpctpeakloading": 16.73120979790217, "maxpctpeakloading": 17.788150240433882, "stdpctpeakloading": 1.4947395084489676 }, { "kv": 2.40178, "numphase": 2.0, "count": 3.0, "avgfeedermiles": 0.11175999999999998, "minfeedermiles": 0.09144, "maxfeedermiles": 0.15239999999999998, "stdfeedermiles": 0.035195272409799576, "minampacity": 400.0, "avgampacity": 400.0, "maxampacity": 400.0, "stdampacity": 0.0, "avgperunitresistanceohmpermile": 0.0003202409042304056, "minperunitresistanceohmpermile": 0.0002217052413902808, "maxperunitresistanceohmpermile": 0.000369508735650468, "stdperunitresistanceohmpermile": 8.533438719828638e-5, "avgperunitreactanceohmpermile": 0.0007264657732177418, "minperunitreactanceohmpermile": 0.0005029378429968982, "maxperunitreactanceohmpermile": 0.0008382297383281636, "stdperunitreactanceohmpermile": 0.00019358086602660592, "mincustomersserved": 1.0, "avgcustomersserved": 1.6666666666666667, "maxcustomersserved": 2.0, "stdcustomersserved": 0.5773502691896257, "minpctpeakloading": 16.094312794909246, "avgpctpeakloading": 23.23659848839567, "maxpctpeakloading": 35.82733535181359, "stdpctpeakloading": 10.936738998493551 }, { "kv": 2.40178, "numphase": 3.0, "count": 6.0, "avgfeedermiles": 0.30479999999999996, "minfeedermiles": 0.15239999999999998, "maxfeedermiles": 0.6095999999999999, "stdfeedermiles": 0.1788621873986338, "minampacity": 400.0, "avgampacity": 400.0, "maxampacity": 400.0, "stdampacity": 0.0, "avgperunitresistanceohmpermile": 0.0001431742504224452, "minperunitresistanceohmpermile": 5.54263103475702e-5, "maxperunitresistanceohmpermile": 0.0002217052413902808, "stdperunitresistanceohmpermile": 7.100745688573208e-5, "avgperunitreactanceohmpermile": 0.00032479046606481823, "minperunitreactanceohmpermile": 0.00012573446074922454, "maxperunitreactanceohmpermile": 0.0005029378429968982, "stdperunitreactanceohmpermile": 0.00016108025673573865, "mincustomersserved": 0.0, "avgcustomersserved": 6.333333333333333, "maxcustomersserved": 15.0, "stdcustomersserved": 5.501514942874069, "minpctpeakloading": 0.00014937875249263795, "avgpctpeakloading": 76.50571677687857, "maxpctpeakloading": 147.9353947021755, "stdpctpeakloading": 60.66546205074211 } ], "capacitors": [ { "kvar": 100.0, "numphase": 1.0, "kv": 2.4, "count": 1.0 }, { "kvar": 600.0, "numphase": 3.0, "kv": 4.16, "count": 1.0 } ], "switches": [ { "numphase": 3.0, "kv": 2.40178, "isnormallyopen": false, "count": 1.0, "avgampacity": 400.0, "minampacity": 400.0, "maxampacity": 400.0, "stdampacity": "NaN" } ], "loads": [ { "kv": 0.277, "count": 3.0, "numphase": 1.0, "totalcustomer": 3.0, "avgcustomersperload": 1.0, "mincustomersperload": 1.0, "maxcustomersperload": 1.0, "stdcustomersperload": 0.0, "avgpeakkw": 133.33333333333334, "avgpeakkvar": 96.66666666666667, "minpeakkw": 120.0, "minpeakkvar": 90.0, "maxpeakkw": 160.0, "maxpeakkvar": 110.0, "stdpeakkw": 23.094010767585033, "stdpeakkvar": 11.547005383792516 }, { "kv": 2.4, "count": 9.0, "numphase": 1.0, "totalcustomer": 9.0, "avgcustomersperload": 1.0, "mincustomersperload": 1.0, "maxcustomersperload": 1.0, "stdcustomersperload": 0.0, "avgpeakkw": 167.88888888888889, "avgpeakkvar": 96.55555555555556, "minpeakkw": 17.0, "minpeakkvar": 10.0, "maxpeakkw": 485.0, "maxpeakkvar": 212.0, "stdpeakkw": 142.64768175862903, "stdpeakkvar": 67.38529348290899 }, { "kv": 4.16, "count": 2.0, "numphase": 1.0, "totalcustomer": 2.0, "avgcustomersperload": 1.0, "mincustomersperload": 1.0, "maxcustomersperload": 1.0, "stdcustomersperload": 0.0, "avgpeakkw": 200.0, "avgpeakkvar": 141.5, "minpeakkw": 170.0, "minpeakkvar": 132.0, "maxpeakkw": 230.0, "maxpeakkvar": 151.0, "stdpeakkw": 42.42640687119285, "stdpeakkvar": 13.435028842544403 }, { "kv": 4.16, "count": 1.0, "numphase": 3.0, "totalcustomer": 1.0, "avgcustomersperload": 1.0, "mincustomersperload": 1.0, "maxcustomersperload": 1.0, "stdcustomersperload": "NaN", "avgpeakkw": 1155.0, "avgpeakkvar": 660.0, "minpeakkw": 1155.0, "minpeakkvar": 660.0, "maxpeakkw": 1155.0, "maxpeakkvar": 660.0, "stdpeakkw": "NaN", "stdpeakkvar": "NaN" } ] }, "voltagemetrics": [ { "snapshotcategory": "NetPeakLoad", "kv": 0.27713, "numphase": 3.0, "avgvoltagepu": 0.9926781594690027, "minvoltagepu": 0.9824563162208678, "maxvoltagepu": 1.0084186207663994, "stdvoltagepu": 0.013832992200133702 }, { "snapshotcategory": "NetPeakLoad", "kv": 2.40178, "numphase": 1.0, "avgvoltagepu": 0.968088461668005, "minvoltagepu": 0.9608430966208247, "maxvoltagepu": 0.9753338267151852, "stdvoltagepu": 0.01024649351406627 }, { "snapshotcategory": "NetPeakLoad", "kv": 2.40178, "numphase": 2.0, "avgvoltagepu": 0.9973335665813833, "minvoltagepu": 0.9628590008697668, "maxvoltagepu": 1.0197285920694914, "stdvoltagepu": 0.022007077364035624 }, { "snapshotcategory": "NetPeakLoad", "kv": 2.40178, "numphase": 3.0, "avgvoltagepu": 1.0077043602060967, "minvoltagepu": 0.9629552840078276, "maxvoltagepu": 1.0560497133305953, "stdvoltagepu": 0.029312299320140376 }, { "snapshotcategory": "NetPeakLoad", "kv": 66.39528, "numphase": 3.0, "avgvoltagepu": 0.9999724980882166, "minvoltagepu": 0.9999501168596413, "maxvoltagepu": 0.9999938117414283, "stdvoltage_pu": 2.1866994797273813e-5 } ] }

```

Attribution and Disclaimer

This software was created under a project sponsored by the U.S. Department of Energy’s Office of Electricity, an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor Battelle, nor any of their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights.

Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

PACIFIC NORTHWEST NATIONAL LABORATORY

operated by BATTELLE

for the UNITED STATES DEPARTMENT OF ENERGY

under Contract DE-AC05-76RL01830

Owner

  • Name: Grid-Atlas
  • Login: Grid-Atlas
  • Kind: organization

Citation (CITATION.cff)

cff-version: 1.2.0
title: Grid Meta
message: 'If you use this software, please cite it as below.'
type: software
authors:
  - family-names: Duwadi
    given-names: Kapil
  - family-names: Bhattacharjee
    given-names: Kaustav
  - family-names: Anderson
    given-names: Alexander
  - family-names: Sadnam
    given-names: Rabayet
repository-code: 'https://github.com/Grid-Atlas/grid-meta'
url: 'https://grid-atlas.github.io/grid-meta'
abstract: >-
  A light weight Python Package for extracting metadata from OpenDSS model.

keywords:
  - python
  - altdss
  - pydantic
  - opendss
license: BSD-3-Clause
version: v1.0.0
funding:
  - name: U.S. Department of Energy's Office of Electricity
    url: 'https://www.energy.gov/oe/office-electricity'
    contract-number: 'DE-AC05-76RL01830'
date-released: 2025-07-01

GitHub Events

Total
  • Create event: 10
  • Release event: 1
  • Issues event: 6
  • Watch event: 3
  • Delete event: 7
  • Issue comment event: 1
  • Push event: 21
  • Public event: 1
  • Pull request event: 9
Last Year
  • Create event: 10
  • Release event: 1
  • Issues event: 6
  • Watch event: 3
  • Delete event: 7
  • Issue comment event: 1
  • Push event: 21
  • Public event: 1
  • Pull request event: 9

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 13
  • Total Committers: 2
  • Avg Commits per committer: 6.5
  • Development Distribution Score (DDS): 0.077
Past Year
  • Commits: 13
  • Committers: 2
  • Avg Commits per committer: 6.5
  • Development Distribution Score (DDS): 0.077
Top Committers
Name Email Commits
Kapil Duwadi k****i@p****v 12
Dr. Alex A. Anderson a****n@i****g 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 5
  • Total pull requests: 7
  • Average time to close issues: 1 day
  • Average time to close pull requests: 3 minutes
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.29
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 5
  • Pull requests: 7
  • Average time to close issues: 1 day
  • Average time to close pull requests: 3 minutes
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.29
  • Merged pull requests: 7
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • KapilDuwadi (6)
Pull Request Authors
  • KapilDuwadi (14)
Top Labels
Issue Labels
feature request (2) documentation (2) enhancement (1) bug (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 60 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
pypi.org: gridmeta

A repository for extracting dehydrated metadata for distribution power grid model.

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 60 Last month
Rankings
Dependent packages count: 8.9%
Average: 29.6%
Dependent repos count: 50.3%
Maintainers (1)
Last synced: 6 months ago

Dependencies

.github/workflows/check-major-updates.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
  • peter-evans/create-issue-from-file v4 composite
.github/workflows/ci.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
.github/workflows/doc.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
.github/workflows/publish.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
  • pypa/gh-action-pypi-publish release/v1 composite
pyproject.toml pypi
  • click ~=8.2.1
  • datamodel-code-generator ~=0.31.2
  • jsonschema ~=4.24.0
  • opendssdirect.py ~=0.9.4
  • pandas ~=2.2.3
  • pydantic ~=2.11.5
  • requests ~=2.32.3