Power System Resilience to Extreme Weather: Fragility Modeling, Probabilistic Impact Assessment, and Adaptation Measures
Power System Resilience to Extreme Weather: Fragility Modeling, Probabilistic Impact Assessment, and Adaptation Measures
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DOI：
10.1109/tpwrs.2016.2641463
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发表时间：
2017-09
影响因子：
6.6
通讯作者：
M. Panteli;C. Pickering;S. Wilkinson;R. Dawson;P. Mancarella
中科院分区：
文献类型：
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作者：
M. Panteli;C. Pickering;S. Wilkinson;R. Dawson;P. Mancarella
历史上的电力扰动突出了极端天气对电力系统弹性的影响。尽管此类事件很少发生，但其潜在影响的严重性要求：1）开发适当的复原力评估技术以捕捉其影响; 2）评估相关战略以缓解这些影响。本文旨在为电力系统弹性的建模和量化提供基本的见解。具体而言，脆弱性模型的单个组件，然后整个传输系统的建立映射的实时影响恶劣天气，重点是风事件，其故障概率。然后介绍了一种基于最优潮流和序贯蒙特卡罗模拟的概率性多时相和多区域弹性评估方法，可以评估风暴在输电网络中移动的时空影响。不同的基于风险的弹性增强（或适应）措施进行了评估，这是由各个传输组件的弹性成就价值指数驱动。该方法是证明使用测试版的大不列颠的系统。作为关键产出，结果表明，通过使用基础设施和运行指数的组合，如何能够有效地量化系统对极端天气的抗御能力，确定关键网络部分并确定其优先顺序，其关键程度取决于天气强度，并评估不同适应措施的技术效益，以提高抗御能力。
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 1) developing suitable resilience assessment techniques to capture their impacts and 2) assessing relevant strategies to mitigate them. This paper aims to provide fundamentals insights on the modeling 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 multitemporal and multiregional 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 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.