Grid Data Models (GDM)#
GDM is a python package containing data models for power system assets and datasets. This package is actively being developed at National Renewable Energy Laboratory (NREL).
Installation#
You can install latest version of grid-data-models from PyPi.
pip install grid-data-models
Why Grid Data Models ?#
In an effort to reduce code duplication and provide client packages a standard interface to interact with power system data, a group of research engineers at NREL is working on developing standard data models. Features:
Built-in validation layer: Use of pydantic allows us to validate model fields.
Connectivity Validation: Ensures logical consistency in grid design, e.g.:
Three-phase equipment cannot connect to single-phase buses.
Transformer low-voltage sides cannot connect to high-voltage buses.
Time series data management: GDM uses infrasys package which enables efficient time series data management by sharing arrays across components and offloading system memory. For example, we can attach time series power consumption data to a load profile.
Built-in unit conversion: GDM leverages pint for unit conversion for power system quantities. For e.g power, voltage, time etc.
JSON serialization/deserialization: GDM uses infrasys to serialize and deserialize distribution system components to/from JSON.
Temporal Modeling: Supports temporal changes within a distribution model, enabling enhanced scenaio management capabilities.
Graph-Based Analysis: Exposes a connectivity graph using NetworkX, allowing advanced graph-based algorithms and visualizations.
Interoperability: Easily integrates with existing tools.
How to get started ?#
To get started, you can clone and pip install this library from here.
Contributors#
Kapil Duwadi
Tarek Elgindy
Aadil Latif
Pedro Andres Sanchez Perez
Daniel Thom
Jeremy Keen