Correlating Power Outage Spread with Infrastructure Interdependencies During Hurricanes
Avishek Bose, Sangkeun Lee, Narayan Bhusal, Supriya Chinthavali
TL;DR
The study tackles how hurricanes propagate power outages through interdependent critical infrastructure networks. It integrates wind-swath forecasts from HurricaneMapping2023, the NAERM-IA interdependency graph, and ORNL's EAGLE-I outage data to map affected components within k-hop neighborhoods and relate them to peak county outages. A positive relationship is found between the extent of infrastructure reachable within a k-hop radius from initial impact and observed outages, with stronger correlations at higher wind speeds and indications that indirect connections contribute meaningfully to outage spread. The work demonstrates the value of interdependency-aware modeling for identifying indirectly affected regions and informing resilience and response planning.
Abstract
Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events.