弹性(材料科学)
公制(单位)
决策支持系统
计算机科学
运筹学
可靠性工程
工程类
风险分析(工程)
业务
运营管理
物理
人工智能
热力学
作者
Gowtham Kandaperumal,Shikhar Pandey,Anurag K. Srivastava
标识
DOI:10.1109/tsg.2021.3119508
摘要
With the increasing number of catastrophic weather events and resulting disruption in the energy supply to essential loads, the distribution grid operators' focus has shifted from reliability to resiliency against high impact, low-frequency events. Given the enhanced automation to enable the smarter grid, there are several assets/resources at the disposal of electric utilities to enhances resiliency. However, with a lack of comprehensive resilience tools for informed operational decisions and planning, utilities face a challenge in investing and prioritizing operational control actions for resiliency. The distribution system resilience is also highly dependent on system attributes, including network, control, generating resources, location of loads and resources, as well as the progression of an extreme event. In this work, we present a novel multi-stage resilience measure called the Anticipate-Withstand-Recover (AWR) metrics. The AWR metrics are based on integrating relevant 'system characteristics based factors', before, during, and after the extreme event. The developed methodology utilizes a pragmatic and flexible approach by adopting concepts from the national emergency preparedness paradigm, proactive and reactive controls of grid assets, graph theory with system and component constraints, and multi-criteria decision-making process. The proposed metrics are applied to provide decision support for a) the operational resilience and b) planning investments, and validated for a real system in Alaska during the entirety of the event progression.
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