Data-Driven Climate Outage Risk Characterization and Resilience Analysis in Joint Power-Communication Networks

2026-05-05

AI Summary

This study addresses the growing risk of climate-induced power outages by proposing a novel resilience assessment framework that integrates empirical analysis with cascading failure simulations in coupled power-communication networks. Leveraging large-scale empirical outage data from EAGLE-I and a multi-layer interdependent infrastructure model (MIIM), the work develops a data-driven approach on the IEEE 118-bus system to uncover climate-outage relationships and geographically heterogeneous cross-layer risk amplification. Results reveal that climate-related outages have increased by approximately 9,100 incidents annually on average, with coastal regions exhibiting significantly higher vulnerability. Under extreme weather conditions, system operational capacity drops sharply to 17.6%, demonstrating that interdependencies between infrastructure layers exacerbate regional resilience disparities and overcome the underestimation of coastal risks inherent in conventional aggregate statistical methods.

Abstract

Climate-driven power outages pose a growing threat to U.S. grid reliability, yet empirical outage studies and interdependency-based resilience analyses are rarely integrated. This paper presents a data-driven framework that integrates empirical outage characterization with cascade failure simulation in joint power-communication networks. Using the EAGLE-I national outage dataset (2015-2023, above 525,000 records), we characterize the climate-outage landscape through descriptive analysis and hypothesis testing, finding that climate-related outages increase by roughly 9,100 events per year and impose a significantly greater severity burden on coastal states. An interpretable logistic regression model then identifies the main predictors of severe outage risk, with Severe Weather emerging as the dominant factor. Guided by these findings, we construct four geographically representative failure scenarios and evaluate them using MIIM-based cascade simulation on the IEEE 118-bus system with a communication network overlay. Coastal scenarios produce substantially larger resilience gaps than the inland case, with the Extreme Coastal Severe Weather scenario reducing post-cascade operability to 17.6 percentage. The results show that aggregate outage statistics alone underestimate coastal risk, as cross-layer cascade propagation amplifies geographic damage in ways revealed only through interdependency-aware simulation.

Problem

• climate-driven outages
• power-communication interdependency
• resilience analysis
• cascade failure
• coastal risk

Innovation

• data-driven resilience
• power-communication interdependency
• climate-induced outages
• cascade simulation
• EAGLE-I dataset