面向量化级联停电风险

I. Dobson, K. R. Wierzbicki, Janghoon Kim, Hui Ren
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引用次数: 26

摘要

由于最初的故障在各种复杂的罕见事件中传播,停电变得普遍。我们用一个初始故障按分支过程随机传播的整体概率模型来描述这个复杂的级联。分支过程参数可以从观测数据或模拟中统计估计,然后用于有效地预测停电规模的概率分布。我们回顾了这些方法在模拟和观测数据上的当前测试,并讨论了实现量化电力系统级联故障的验证和实用方法的下一步步骤。从观测数据和模拟中有效量化级联停电风险的能力可以为监测输电系统可靠性和量化所提出的改进的可靠性效益提供新的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards quantifying cascading blackout risk
Blackouts become widespread by initial failures propagating in a diverse and intricate cascade of rare events. We describe this complicated cascade using a bulk probabilistic model in which the initial failures propagate randomly according to a branching process. The branching process parameters can be statistically estimated from observed data or simulations and then used to efficiently predict the probability distribution of blackout size. We review the current testing of these methods on simulations and observed data and discuss the next steps towards achieving verified and practical methods for quantifying cascading failure of electric power systems. The ability to efficiently quantify cascading blackout risk from observed data and simulations could offer new ways to monitor power transmission system reliability and quantify the reliability benefit of proposed improvements.
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