Additional tools for cgmes2pgm_converter to integrate PowerGridModel with the Common Grid Model Exchange Standard (CGMES)
Project description
CGMES2PGM-Suite
cgmes2pgm_suite provides additional tools for cgmes2pgm_converter to integrate PowerGridModel with the Common Grid Model Exchange Standard (CGMES).
It focuses on performing the state estimation on CGMES datasets.
Features
- Start an Apache Jena Fuseki as docker container
- Upload Datasets to a SPARQL endpoint
- Human readable exports of PGM Datasets in TXT and Excel
- Create SV-Profile from PGM Results
- Debug state estimation by manipulating datasets (e.g., subnet splitting)
- Configure conversion and state estimation via a configuration file
- Simulate measurements:
- when real measurements are not provided via an Operation Profile, but a State Variable (SV) Profile is available
- generates an Operation Profile with distorted measurements based on the SV Profile
Installation
The package can be installed via pip:
pip install cgmes2pgm_suite
To start an Apache Jena Fuseki server via this package, Docker is required. See Docker installation guide.
Usage
This package can be run as a standalone application, performing the conversion and running PGM's state estimation. To do so, you need to install the package and then run the following command:
python -m cgmes2pgm_suite --config <path_to_config_file>
The provided configuration file contains the dataset configuration and the parameters for the conversion and state estimation. An example configuration file can be found in /example.
Quick Start
For a quick start, we recommend cloning this project and using the provided test cases.
If the project is cloned, setup the environment and install the package:
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install -e ".[dev]"
pre-commit install
To run the Conformity Datasets, you need to download Test Configurations v3.0.3 from ENTSO-E CIM Conformity and Interoperability respecting their License.
Place the rdf/xml files of each dataset in the respective subdirectory of tests/datasets.
Afterwards, you can run all datasets using:
pytest -m "integration"
Note: Running the tests creates a Fuseki Docker container on port 3030. The container is automatically removed after the tests are finished.
The results of the tests can be found in the tests/out directory.
If you want to add your own datasets, the following steps are required:
- Place the rdf/xml files in the
tests/data/directory - Create a configuration file in the
tests/configs/directory, by copying an existing one - Update the name, output directory and location of the rdf/xml files in the new configuration file
Datasets
The conversion, measurement simulation and state estimation has been tested with the CGMES conformity datasets.
The following datasets have been tested:
| Dataset | Size (Nodes) | Estimation Result | Comment |
|---|---|---|---|
| PowerFlow | 2 | 🟢 | |
| PST | 2 | 🟢 | All three Scenarios |
| MiniGrid | 13 | 🟢 | |
| MicroGrid | 13 | 🟢 | PST with AsymmetricalPhaseTapChanger (BE-TR2_2) has been split |
| SmallGrid | 167 | 🟢 | |
| Svedala | 191 | 🟢 | |
| RealGrid | 6051 | 🟡 | Requires smaller sigmas in measurement simulation to converge |
| FullGrid | 26 | ? | SV-Profile does not contain power flows for all branches, resulting in an insufficient amount of simulated measurements |
Dataset Version: CGMES Conformity Assessment Scheme Test Configurations v3.0.2
The used configuration files can be found in the /tests/configs directory.
License
This project is licensed under the Apache License 2.0.
Dependencies
This project includes third-party dependencies, which are licensed under their own respective licenses.
- cgmes2pgm_converter (Apache License 2.0)
- bidict (Mozilla Public License 2.0)
- numpy (BSD License)
- pandas (BSD License)
- power-grid-model (Mozilla Public License 2.0)
- power-grid-model-io (Mozilla Public License 2.0)
- SPARQLWrapper (W3C License)
- XlsxWriter (BSD License)
- PyYAML (MIT License)
- StrEnum (MIT License)
- docker (Apache License 2.0)
This project includes code from jena-fuseki-docker
in the src/cgmes2pgm_suite/resources/docker directory, which is redistributed under the original Apache License 2.0.
See the root‑level NOTICE file for full attribution.
Commercial Support and Services
For organizations requiring commercial support, professional maintenance, integration services, or custom extensions for this project, these services are available from SOPTIM AG.
Please feel free to contact us via powergridmodel@soptim.de.
Contributing
We welcome contributions to improve this project. Please see our Contributing Guide for details on how to submit pull requests, report issues, and suggest improvements.
Code of Conduct
This project adheres to a code of conduct adapted from the Apache Foundation's Code of Conduct. We expect all contributors and users to follow these guidelines to ensure a welcoming and inclusive community.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file cgmes2pgm_suite-0.3.0.tar.gz.
File metadata
- Download URL: cgmes2pgm_suite-0.3.0.tar.gz
- Upload date:
- Size: 70.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
369e16b48c944826f3758c3be2bacb4a444c5add30541cff801ff5f0139ac8a7
|
|
| MD5 |
d0dd0f6030ce30a3422f27cdd566190e
|
|
| BLAKE2b-256 |
3ce10d9634cd0a33e9db277d9bce3102778cadc4385094f734ea57a3470226b3
|
File details
Details for the file cgmes2pgm_suite-0.3.0-py3-none-any.whl.
File metadata
- Download URL: cgmes2pgm_suite-0.3.0-py3-none-any.whl
- Upload date:
- Size: 104.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9d2f52d7cf50bd2e5f6ba3d41a68e213dbbc9b433521cf37d6fe6132adc3e033
|
|
| MD5 |
c5fd3cb6f03e9a584ff40035897129fc
|
|
| BLAKE2b-256 |
40e69f061c5ff3c46d7249cf88a1fdf10460db0babc4ef588e3852d995a29986
|