Extracting resilience events from utility outage data based on overlapping times and locations

TL;DR

This paper presents a method to automatically identify resilience events from utility outage data by analyzing overlapping times and locations, aiding in the study of infrastructure resilience during extreme weather.

Contribution

It introduces an automated approach to group utility outages into resilience events using spatial and temporal overlaps, applicable to various data granularities.

Findings

Effective grouping of outages into events demonstrated

Applicable to detailed and aggregated outage data

Facilitates resilience analysis during extreme weather

Abstract

To study resilience with real data, it is necessary to group the individual outages recorded by utilities into events in which the outages bunch up and overlap due to extreme weather. We show how to automatically group utility outage data into resilience events based on their time and location. The methods work with both detailed utility outage data and EAGLE-I data.