"Renewable Integrated Line Failure Dataset for IEEE39 Bus System"

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Authors: Bhuvaneshwari Shaktawat, YashVardhan Singh Shaktawat, Pankaj Dilip Achlerkar
Cited by: 0

Abstract

"Grid stability faces dual threats from climate-intensified disasters and low-inertia renewables. This study unveils a comprehensive dataset from a custom IEEE 39-bus testbench powered by Synchronous Generators (SGs) and Inverter-based Resources (IBRs), capturing realistic dynamics under faults at every line and diverse locations. Starting with an all-SG configuration, we progressively replace SGs with current-controlled IBRs to mirror modern inertia challenges. Data generation systematically varies key SG\/IBR parameters - voltage phasor, current phasor, rotor angle (\u03b4), speed (\u03c9) - across wide operating ranges, producing high-fidelity time-series for dynamic studies, inertia and damping estimation, and critical clearing time (CCT) prediction. This reveals how gains (Ki and Kd) tuning bolsters fault resilience. Leveraging the dataset, we develop Feature Training for precise CCT forecasting and physics-informed neural networks (PINNs) to derive energy functions for transient stability analysis. This granular resource enables ML-driven assessments, high-renewable-grid planning, and real-time controls. Models and data are publicly available to advance reproducible research."

Fields of Study & Subjects

Power System Optimization and Stability Microgrid Control and Optimization Power Systems Fault Detection

Publication details

Journal / source
IEEE DataPort
Publication date
27 February 2026
Language
EN
Document type
Dataset