py-dss-tools

py-dss-tools is a Python package that builds on the capabilities of the py-dss-interface package to provide advanced functionalities for creating Python-OpenDSS solutions more efficiently. By combining the robust connection to OpenDSS provided by py-dss-interface with the feature-rich tools of py-dss-tools, users can streamline their workflows and gain powerful new capabilities for analyzing and manipulating OpenDSS models.

For more information about py-dss-interface, visit its GitHub repository.

Key Features

py-dss-tools can be used in two main ways:

1. Directly with the `dss_tools` Object: - Import the object: from py_dss_tools import dss_tools - Connect it to the dss object from py-dss-interface:

   ```python

   import py_dss_interface

   from py_dss_tools import dss_tools

   dss = py_dss_interface.DSS()

   dss_tools.update_dss(dss)

   ```

   • Examples are available in the folder examples/dss_tools or in the link Examples of dss_tools.

2. Using the `CreateStudy` Class: - Select a study type such as static, temporal, or faultstudy. - Import and create a study:

   ```python

   from py_dss_tools import CreateStudy

   study = CreateStudy.static("My Study", dss_file=dss_file)

   ```

   • Examples are available in the folder examples/studies or in the link Examples of studies.

Available Features

1. Model Access and Modification:
   • Access detailed model information through organized pandas DataFrames.
   • Modify models using powerful built-in functions.
   • Use via:
     • dss_tools.model
     • study.model
2. Simulation Results:
   • Retrieve SnapShot Power Flow results, including voltages, currents, and powers.
   • Access QSTS simulation data (e.g., energymeter and monitors).
   • Analyze FaultStudy results such as short-circuit impedances.
   • Results are tailored to the type of study created and are presented in pandas DataFrames.
   • Use via:
     • dss_tools.results
     • study.results
3. Visualization:
   • View results and circuit topology using three approaches:
     • dss_view: Leverages the DSSView.exe program (similar to OpenDSS).
     • interactive_view: Powered by Plotly for dynamic, interactive plots.
     • static_view: Static plots using Matplotlib.
   • Examples include:
     • Voltage profiles.
     • Time-series results.
     • Circuit topology plots.

Usage Examples

Explore examples on how to use py-dss-tools in the following GitHub folders:

• Examples of dss_tools
• Examples of studies

Development and Contributions

py-dss-tools is under continuous development. Contributions and suggestions are welcome to enhance its functionality and usability. If you have feature requests or feedback, feel free to reach out or submit issues on GitHub.

Installation

Install py-dss-tools via pip:

pip install py-dss-tools

Dependencies

py-dss-tools requires py-dss-interface. Ensure that it is installed in your Python environment before using py-dss-tools.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

Special thanks to the contributors of py-dss-interface, as its robust connection to OpenDSS serves as the foundation for py-dss-tools.