Quantitative Resilience-Based Assessment Framework Using EAGLE-I Power Outage Data

Catastrophic impacts to power systems caused by extreme weather events have significantly increased during the last decade. These events highlight the need to develop approaches to assess the resilience of power systems against extreme events; however, the availability of data that capture power system performance during and after disruptive events is scarce. This paper proposes an assessment framework to evaluate the performance aspects of the power grid during extreme outage events using the Environment for Analysis of Geo-Located Energy Information (EAGLE-I) data. EAGLE-I data include information related to the number of impacted customers, the duration, and the location of power outages in the United States. Statistical analyses were conducted to extract resilience-based outage data and derive probability distribution functions of their impact and recovery characteristics. A list of extreme events is identified based on population-based threshold values. Metrics from other power outage assessments were used to measure the characteristics of each event, including the impact rate and duration, the recovery rate and duration, and the impact level. A probability distribution function is obtained for each metric. The proposed framework is conducted for each state across the United States. The obtained results provide a probabilistic representation of state-level outage behaviors, which can be applied as a framework to evaluate various resilience enhancement techniques.

Automated summary

Catastrophic impacts caused by extreme weather events on power systems have increased significantly in the past decade. However, data capturing the performance of power systems during and after disruptive events is scarce. This paper proposes an assessment framework using EAGLE-I data to evaluate the performance aspects of the power grid during extreme outage events, providing a probabilistic representation of state-level outage behaviors for evaluating resilience enhancement techniques.