Probabilistic Quantification of Power Distribution System Operational Resilience

Abstract

High-impact, low-probability (HILP) events resulting from extreme weather conditions have a significant impact on the aging power distribution infrastructures. It is of growing concern to minimize the impacts of such catastrophic events on critical infrastructures by appropriately hardening the infrastructure and implementing new operational procedures. This calls for a quantitative assessment of distribution system resilience that can not only predict the impacts of the future events but also be used to evaluate different planning measures taken to minimize the impacts of extreme events. In this paper, we propose a probabilistic metric to quantify the operational resilience of the distribution grid. The metric is based on Conditional Value-at-Risk ( CVaR) measure where resilience is defined as the conditional expectation of loss of energy in MWh for events beyond a prespecified risk threshold. A simulation-based framework to evaluate the proposed metric for resilience under different weather scenarios is presented. The impacts of restorative actions, specifically using distributed generators and remote-controlled switches (RCS) and the impacts of infrastructure hardening on resilience metric is also investigated. Numerical simulations are performed on the IEEE 123-bus test system.