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Dynamic Temporal Graph Sequence Data for Resilience-Oriented Distribution Network Reconfiguration

  • Liu, Boming | Oak Ridge National Laboratory
  • Eiffert, Brett | Oak Ridge National Laboratory
  • Zhang, Chen | Oak Ridge National Laboratory
  • Dong, Jin | Oak Ridge National Laboratory
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Overview

Description

This dataset comprises temporal dynamic graph sequences generated from power grid simulations focused on grid reconfiguration to enhance resilience. The simulations model failure propagation under varying conditions, with nodes assigned distinct failure probabilities. For each time step, the dataset captures the evolution of node states (functional or failed) and features critical to grid operations, such as pv_output, load_profile, load_dispatch, dg_output, loss, and voltage. Node types include sources, normal loads, and nodes with specific equipment like PVs, micro turbines, or shunt capacitors. The dataset is structured to support the training of dynamic graph neural networks, facilitating research on node feature prediction and edge dynamics under failure scenarios. Three distinct configurations are included, providing a robust foundation for modeling power grid resilience.

Funding resources

DOE contract number

DE-AC05-00OR22725

Originating research organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring organization

USDOE; ORNL Laboratory Directed Research and Development (LDRD)

Details

DOI

10.13139/OLCF/2437680

Release date

September 26, 2024

Dataset

Dataset type

ND Numeric Data

Software

HDF5 and Parquet readers needed for reading the data. DGL and PyTorch are recommended for training.

Acknowledgements

Papers using this dataset are requested to include the following text in their acknowledgements:

*Support for 10.13139/OLCF/2437680 is provided by the U.S. Department of Energy, project CADES under Contract DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.

Category

  • 29 ENERGY PLANNING, POLICY, AND ECONOMY

Keywords

  • dynamic graph,
  • network reconfiguration,
  • power systems,
  • resilience