Power System Resilience to Extreme Weather: Fragility Modeling, Probabilistic Impact Assessment, and Adaptation Measures

TLDR

Extreme weather has historically caused electrical disturbances that threaten power system resilience. The study seeks to develop resilience assessment techniques and provide foundational insights into modeling and quantifying power system resilience to extreme weather. A fragility‑based model of components and the entire transmission system, coupled with a probabilistic multitemporal, multiregional assessment using optimal power flow and Monte Carlo simulation, evaluates risk‑based resilience enhancement measures and is demonstrated on a Great Britain test system. The results show that combining infrastructure and operational indices enables effective quantification of resilience, identification and prioritization of critical network sections based on weather intensity, and assessment of the technical benefits of adaptation measures.

Abstract

Historical electrical disturbances highlight the impact of extreme weather on power system resilience. Even though the occurrence of such events is rare, the severity of their potential impact calls for developing suitable resilience assessment techniques to capture their impacts and assessing relevant strategies to mitigate them. This paper aims to provide fundamentals insights on the modeling and quantification of power systems resilience. Specifically, a fragility model of individual components and then of the whole transmission system is built for mapping the real-time impact of severe weather, with focus on wind events, on their failure probabilities. A probabilistic multitemporal and multiregional resilience assessment methodology, based on optimal power flow and sequential Monte Carlo simulation, is then introduced, allowing the assessment of the spatiotemporal impact of a windstorm moving across a transmission network. Different risk-based resilience enhancement (or adaptation) measures are evaluated, which are driven by the resilience achievement worth index of the individual transmission components. The methodology is demonstrated using a test version of the Great Britain's system. As key outputs, the results demonstrate how, by using a mix of infrastructure and operational indices, it is possible to effectively quantify system resilience to extreme weather, identify and prioritize critical network sections, whose criticality depends on the weather intensity, and assess the technical benefits of different adaptation measures to enhance resilience.