The Most Frequent N-k Line Outages Occur in Motifs That Can Improve Contingency Selection
The Most Frequent N-k Line Outages Occur in Motifs That Can Improve Contingency Selection
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DOI：
10.1109/tpwrs.2023.3249825
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发表时间：
2022-09
影响因子：
6.6
通讯作者：
Kai Zhou;I. Dobson;Zhaoyu Wang
中科院分区：
文献类型：
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作者：
Kai Zhou;I. Dobson;Zhaoyu Wang
同时发生的多路停电在输电网中表现出多种空间格局。其中一些空间模式形成了网络偶然性主题，我们将其定义为多次中断的模式，这些模式比从网络中随机选择的多次中断发生得更频繁。我们表明，从这些常见的偶然性动机中选择N-k偶然性可以解释多次启动线路中断的大部分概率。使用两个传输系统的历史停电数据证明了这一结果。它支持N-k应急列表，与详尽列表或随机选择相比，它在考虑可能的多次初始中断方面效率更高。基于基序构建的N-k个应急列表可以提高级联停电模拟中的风险估计，并有助于确定公用事业应急选择。
Multiple line outages that occur together show a variety of spatial patterns in the power transmission network. Some of these spatial patterns form network contingency motifs, which we define as the patterns of multiple outages that occur much more frequently than multiple outages chosen randomly from the network. We show that choosing N-k contingencies from these commonly occurring contingency motifs accounts for most of the probability of multiple initiating line outages. This result is demonstrated using historical outage data for two transmission systems. It enables N-k contingency lists that are much more efficient in accounting for the likely multiple initiating outages than exhaustive listing or random selection. The N-k contingency lists constructed from motifs can improve risk estimation in cascading outage simulations and help to confirm utility contingency selection.