弹性(材料科学)
脆弱性
电力系统
概率逻辑
极端天气
可靠性工程
计算机科学
适应(眼睛)
风险分析(工程)
气候变化
工程类
功率(物理)
人工智能
热力学
物理化学
医学
量子力学
生态学
生物
光学
物理
化学
作者
Mathaios Panteli,Cassandra Pickering,Sean Wilkinson,Richard Dawson,Pierluigi Mancarella
标识
DOI:10.1109/tpwrs.2016.2641463
摘要
Historical electrical disturbances highlight the impact of extreme weather on power system resilience. Even though the occurrence of such events is rare, the severity of their potential impact calls for (i) developing suitable resilience assessment techniques to capture their impacts and (ii) assessing relevant strategies to mitigate them. This paper aims to provide fundamentals insights on the modelling and quantification of power systems resilience. Specifically, a fragility model of individual components and then of the whole transmission system is built for mapping the real-time impact of severe weather, with focus on wind events, on their failure probabilities. A probabilistic multi-temporal and multi-regional resilience assessment methodology, based on optimal power flow and sequential Monte Carlo simulation, is then introduced, allowing the assessment of the spatiotemporal impact of a windstorm moving across a transmission network. Different risk-based resilience enhancement (or “adaptation”) measures are evaluated, which are driven by the resilience achievement worth (RAW) index of the individual transmission components. The methodology is demonstrated using a test version of the Great Britain’s system. As key outputs, the results demonstrate how, by using a mix of infrastructure and operational indices, it is possible to effectively quantify system resilience to extreme weather, identify and prioritize critical network sections, whose criticality depends on the weather intensity, and assess the technical benefits of different adaptation measures to enhance resilience.
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