Probabilistic Resilience Analysis of the Icelandic Power System under Extreme Weather

Abstract

This paper presents a probabilistic methodology for assessing power system resilience, motivated by the extreme weather storm experienced in Iceland in December 2019. The methodology is built on the basis of models and data available to the Icelandic transmission system operator in anticipation of the said storm. We study resilience in terms of the ability of the system to contain further service disruption, while potentially operating with reduced component availability due to the storm impact. To do so, we develop a Monte Carlo assessment framework combining weather-dependent component failure probabilities, enumerated through historical failure rate data and forecasted wind-speed data, with a bi-level attacker-defender optimization model for vulnerability identification. Our findings suggest that the ability of the Icelandic power system to contain service disruption moderately reduces with the storm-induced potential reduction of its available components. In other words, and as also validated in practice, the system is indeed resilient.

Keywords

• attacker-defender
• probabilistic
• resilience
• extreme weather
• failure rates
• contingencies