A Risk-Driven Probabilistic Approach to Quantify Resilience in Power Distribution Systems

TL;DR

This paper introduces a probabilistic resilience metric for power distribution systems that combines system attributes and extreme weather scenarios to aid planning and operational decisions.

Contribution

It proposes a novel resilience metric using conditional value-at-risk and Choquet Integral, providing a new quantitative tool for resilience assessment.

Findings

The metric effectively evaluates resilience under extreme weather scenarios.

Simulation results demonstrate its utility in prioritizing resilience investments.

Framework offers system operators enhanced decision-making flexibility.

Abstract

It is of growing concern to ensure resilience in power distribution systems to extreme weather events. However, there are no clear methodologies or metrics available for resilience assessment that allows system planners to assess the impact of appropriate planning measures and new operational procedures for resilience enhancement. In this paper, we propose a resilience metric using parameters that define system attributes and performance. To represent extreme events (tail probability), the conditional value-at-risk of each of the parameters are combined using Choquet Integral to evaluate the overall resilience. The effectiveness of the proposed resilience metric is studied within the simulation-based framework under extreme weather scenarios with the help of a modified IEEE 123-bus system. With the proposed framework, system operators will have additional flexibility to prioritize one investment over the others to enhance the resilience of the grid.