The increasing frequency and severity of extreme events have exposed fundamental limitations in how the resilience of electric power distribution grid is assessed and operationalized. Existing resilience metrics primarily rely on assumptions of all necessary data, often overlooking the varying operational scenarios and access to grid assets, changing events impacting the grid, and socio-economic disparities that shape real-world outcomes. As a result, current approaches can misrepresent system performance, leading to inefficient restoration strategies and inequitable service recovery across communities. In this work, we introduce a resilience framework for power distribution systems, which adopts with system operating conditions, threat characteristics, and data availability to enable context-aware evaluation of power system performance under extreme events. The proposed approach remains robust under incomplete and uncertain data, supporting its application in real-world operational environments. We further show that incorporating socio-economic indicators, including energy burden and vulnerability, reveals systematic disparities in service restoration that are not captured by conventional metrics. Building on this framework, we develop a resilience-driven restoration strategy that prioritizes recovery based on both system priority and community impact. Case study results demonstrate that incorporating socio-economic considerations alters crew restoration sequence, thereby reducing restoration crew operational inefficiencies and improving service outcomes for vulnerable customers. The findings made in this work highlight the need to move beyond purely technical resilience assessments toward integrated approaches that reflect both electrical infrastructural performance and societal impact, providing a foundation for more effective and inclusive resilience planning for future power systems.
Boateng et al. (Wed,) studied this question.