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Transmission utilities routinely collect detailed outage data, including resilience events in which outages bunch due to weather. The resilience events and associated metrics can readily be extracted from this historical outage data. Improvements such as asset hardening or investments in restoration lead to reduced outages or faster restoration. In this paper, we show how to rerun the historical events including the effects of the reduced outages or faster restorations to measure the resulting improvement in resilience metrics, thus quantifying the benefits of these investments. This is demonstrated with case studies for specific events (a derecho and a hurricane), and all large events or large thunderstorms in the Midwest USA. Instead of predicting future extreme events with models, which is very challenging, rerunning historical events readily quantifies the benefits of resilience investments if these investments had been made in the past. Rerunning historical events is particularly vivid in making the case for resilience investments as it quantifies the benefits for events actually experienced, rather than for uncertain future events. 

The impact of weather on the power grid has been a focus of multiple studies, and its importance has grown with the number and magnitude of extreme weather events. This paper uses transmission outage and inventory data collected in Transmission Availability Data System (TADS) to identify and analyze weather related transmission events and quantify their impact on the North American Bulk Electric System. The impact of a transmission event is measured by several factors: the number of outages, affected miles and MVA, event duration, and number of groups of simultaneous outages (known as generations of outages). We analyze the largest events from 2015 to 2019, and use an event propagation metric to estimate the probability of small, medium, and large events, and track how these probabilities change from year-to-year.