Optimal Decomposition of Utility Outage Sequence for Cascading Failure Interaction Estimation
Optimal Decomposition of Utility Outage Sequence for Cascading Failure Interaction Estimation
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DOI：
10.1109/pmaps53380.2022.9810630
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发表时间：
2022-06
期刊：
影响因子：
--
通讯作者：
Lei Wang;Junjian Qi
中科院分区：
文献类型：
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作者：
Lei Wang;Junjian Qi
从电力中断数据中估计的组件故障相互作用可以捕获一般故障传播模式，并帮助识别电力系统的关键组件。通常，根据任意选择的阈值，根据中断时间将公用事业中断分组为级联和代。本文提出了一种电力中断数据的最优分解方法。通过泊松过程近似停电序列的时间模式，计算出自适应的发电持续时间阈值，对每个级联的发电进行分组。与传统方法相比，该方法可以揭示更多的失效相互作用，并降低了非均质性。基于实际电力中断数据的结果证明了所提出的最优分解方法的有效性。
Estimated component failure interactions from utility outage data can capture the general failure propagation patterns and help identify key components of a power system. Conventionally, utility outages are grouped into cascades and generations according to inter-outage time based on arbitrarily chosen thresholds. In this paper, we propose an optimal decomposition approach for utility outage data. By approximating the temporal pattern of the outage sequence by a Poisson process, an adaptive generation duration threshold is calculated to group the generations for each cascade. Compared to the conventional method, the proposed method can reveal more failure interactions and mitigate heterogeneity. The results based on real utility outage data demonstrate the effectiveness of the proposed optimal decomposition approach.