Risk-Based Probabilistic Quantification of Power Distribution System Operational Resilience

被引:64
作者
Poudel, Shiva [1 ]
Dubey, Anamika [1 ]
Bose, Anjan [1 ]
机构
[1] Washington State Univ, Sch Elect Engn & Comp Sci, Pullman, WA 99164 USA
来源
IEEE SYSTEMS JOURNAL | 2020年 / 14卷 / 03期
关键词
Conditional value at risk (CVaR); distribution system resilience; resilience metric; value at risk (VaR); RESTORATION; INFRASTRUCTURE; RESOURCES; ENERGY;
D O I
10.1109/JSYST.2019.2940939
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is of growing concern to ensure the resilience in electricity infrastructure systems to extreme weather events with the help of appropriate hardening measures and new operational procedures. An effective mitigation strategy requires a quantitative metric for resilience that can not only model the impacts of the unseen catastrophic events for complex electric power distribution networks, but also evaluate the potential improvements offered by different planning measures. In this article, we propose probabilistic metrics to quantify the operational resilience of the electric power distribution systems to high-impact low-probability (HILP) events. Specifically, we define two risk-based measures: value-at-risk (VaR alpha) and conditional value-at-risk (CVaR(alpha)) that measure resilience as the maximum loss of energy and conditional expectation of a loss of energy, respectively, for the events beyond a prespecified risk threshold, a. Next, we present a simulation-based framework to evaluate the proposed resilience metrics for different weather scenarios with the help of modified IEEE 37-bus and IEEE 123-bus system. The simulation approach is also extended to evaluate the impacts of different planning measures on the proposed resilience metrics.
引用
收藏
页码:3506 / 3517
页数:12
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