A Spatio-Temporal Threat and Dynamic Vulnerability-Based Risk Assessment for Electric Grids Facing Natural Disasters
Conference
Rahman, N, Chowdhury, MA, Kamalasadan, S et al. (2026). A Spatio-Temporal Threat and Dynamic Vulnerability-Based Risk Assessment for Electric Grids Facing Natural Disasters
. 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 10.1109/PESGM58988.2026.11693568
Rahman, N, Chowdhury, MA, Kamalasadan, S et al. (2026). A Spatio-Temporal Threat and Dynamic Vulnerability-Based Risk Assessment for Electric Grids Facing Natural Disasters
. 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 10.1109/PESGM58988.2026.11693568
Increasing extreme-weather threats - particularly hurricanes - require real-time, high-fidelity risk assessment to support resilient grid operations. This paper presents a structure-aware, data-driven online risk assessment framework that integrates dynamic system vulnerability with geographically varying threat likelihood via statistical inference. The framework combines Monte Carlo-based hurricane threat impact modeling with bus-level dynamic vulnerability indices derived from voltage, frequency, and generator rotor-angle responses to disturbance scenarios. The combination is based on a statistical inference correlation. The vulnerability and threat indices are then embedded using a probability-based weight selection to represent the overall risk in a normalized form that captures both the electric lines' threat attenuation and node-level similarity based on dynamic behavior. The framework is validated on the IEEE 39-bus system with inverter-based resources (IBRs) and subsequently scaled to a real-world 500-bus transmission grid. Results show that the proposed approach correlates strongly with traditional risk metrics while additionally capturing structural propagation effects. The proposed method offers actionable situational awareness for grid operators and is scalable for integration into online security assessment tools for future IBR-rich power systems.
