A Study on Probabilistic Assessment of Cascading Failure Risks Based on Extreme Temperature Distribution Modeling

This study develops a simulation framework for quantitative assessment of power system stability and cascading failure risks under extreme temperature events. Extreme temperature scenarios are generated using Generalized Pareto Distribution (GPD) from meteorological observations, incorporating temperature-dependent load increases, power factor deterioration, and dynamic line rating reductions. The framework integrates equipment outage models based on overload rates and reactive power exceedance with undervoltage load shedding and generator redispatch to identify vulnerable components and quantify regional outage probabilities. Monte Carlo-based probabilistic assessment identifies critical transmission components and vulnerable equipment, providing quantitative risk evaluation for climate-resilient power system planning. This methodology enables practical analytical tools for developing climate adaptation strategies in power systems facing escalating extreme weather events.