Large-scale data analysis of power grid resilience across multiple US service regions

Severe weather events frequently result in large-scale power failures, affecting millions of people for extended durations. However, the lack of comprehensive, detailed failure and recovery data has impeded large-scale resilience studies. Here, we analyse data from four major service regions representing Upstate New York during Super Storm Sandy and daily operations. Using non-stationary spatiotemporal random processes that relate infrastructural failures to recoveries and cost, our data analysis shows that local power failures have a disproportionally large non-local impact on people (that is, the top 20% of failures interrupted 84% of services to customers). A large number (89%) of small failures, represented by the bottom 34% of customers and commonplace devices, resulted in 56% of the total cost of 28 million customer interruption hours. Our study shows that extreme weather does not cause, but rather exacerbates, existing vulnerabilities, which are obscured in daily operations.