Resiliency metrics quantifying emergency response in a distribution system

TL;DR

The paper addresses quantifying emergency response resilience in electric distribution systems during storm events, extending beyond critical-load restoration to all customers. It proposes an operational resilience framework built on outage and restore processes, with $O(t)$, $R(t)$, and $P(t)=O(t)-R(t)$, and defines metrics such as $A^{\rm cust}$, $n$, $n^{\rm cust}$, and resource measures like $C^{\rm crew}$. It introduces the normalized resilience metrics $RE$, $AIR$, and $REPAIR$, and demonstrates their calculation from post-storm data and a historical rerunning approach to simulate gains from additional crews. The results from multiple storms illustrate how these metrics differentiate performance, guide resource allocation, and enable business-case assessments for resilience investments.

Abstract

The electric distribution system is a cornerstone of modern life, playing a critical role in the daily activities and well-being of individuals. As the world transitions toward a decarbonized future, where even mobility relies on electricity, ensuring the resilience of the grid becomes paramount. This paper introduces novel resilience metrics designed to equip utilities and stakeholders with actionable tools to assess performance during storm events. The metrics focus on emergency storm response and the resources required to improve customer service. The practical calculation of the metrics from historical utility data is demonstrated for multiple storm events. Additionally, the metrics' improvement with added crews is estimated by "rerunning history" with faster restoration. By applying this resilience framework, utilities can enhance their restoration strategies and unlock potential cost savings, benefiting both providers and customers in an era of heightened energy dependency.

Figures (3)

• Figure 1: Crew Dispatching Hierarchy
• Figure 2: Operational resilience processes
• Figure 3: Reduction in REPAIR with 10% more crews