Data and Code for VELE-Based Structural Stress Analysis of IEEE Benchmark Power Grid Networks

Description

This dataset contains the reproducibility materials for the manuscript entitled “Vertex Eccentricity Labeled Energy as a Structural Stress Indicator for Power Grid Resilience: A Study on IEEE Benchmark Networks.” The files include Python scripts, a Google Colab notebook, processed graph representations of IEEE30, IEEE57, IEEE118, and IEEE300 benchmark networks, node-attack trajectories, line-addition outputs, random-trial validation results, summary tables, figures, and run logs. The dataset supports the structural graph-based analysis reported in the manuscript, including the computation of Vertex Eccentricity Labeled Energy, bounded VELE resilience scores, comparison with standard graph measures, and evaluation under random, adaptive degree, and adaptive betweenness node attacks. The benchmark systems are treated as simple undirected graphs for structural screening only; no impedance, voltage, load, capacity, dispatch, or power-flow data are used in the reported experiments.

Steps to reproduce

The benchmark systems IEEE30, IEEE57, IEEE118, and IEEE300 were converted into simple undirected graph edge lists. Parallel branches and electrical attributes were not used, because the study focuses only on structural graph screening. To reproduce the results, unzip the dataset package and install the required Python packages listed in requirements.txt. Then run src/reproduce_results.py, or alternatively open the Colab notebook in the notebooks folder and run all cells in order. The workflow loads the processed benchmark graph files from input_graphs, computes Vertex Eccentricity Labeled Energy, applies the line-addition strategies, performs random, adaptive degree, and adaptive betweenness node attacks, and exports the attack trajectories, AUC tables, statistical validation files, synthetic-network checks, figures, and run logs. The script also includes source-data support for regenerating processed graph files from public MATPOWER benchmark case files. All output tables and figures reported in the associated manuscript can be checked against the files included in the tables, raw_results, figures, and logs folders.

Institutions

• Marwadi University

  Gujarat, Rajkot

Categories

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