基于社交网络影响力的连锁故障关键线路辨识

Critical branch identification of cascading failure based on social network influence analysis

为有效管控大停电风险,准确辨识诱发电力系统连锁故障的关键线路是非常有必要的。为此,本文基于社交网络影响力分析提出一种电力系统连锁故障的关键线路辨识方法。首先,采用连锁故障的样本数据,构建描述故障传播特性的社交网络;然后,建立连锁故障传播过程中的线路影响力量化方法,计及不同线路影响力的重叠性,通过最大化关键线路集合的故障传播影响,识别传播连锁故障的重要线路元件;最后,基于省级电网验证了所提方法的有效性。

To effectively manage the blackout risk,it is necessary to identify critical branches that induce the cascading failures of the power system.In this context,a method to identify critical branches based on the influence analysis of social network is proposed.First,the social network is constructed with the samples of cascadings failure to capture its propagation patterns.Then,the influence of branch outages on the propagation of cascading failures is quantified.The total influence of critical branch set is maximized with the consideration of the overlap between the influence of branches,which can effectively identify the representative branch in the cascading failure propagation.Finally,the validity of the proposed method is verified on a provincial power grid.