The letter proposes an algorithm for big data generation based on realistic selection of a set of contingencies for power systems described by undirected graphs. Every contingency is created by eliminating a certain number of elements in the system represented by graph edges. The number of elements as well as the distance between elements of the contingency is randomly selected according to a geometric probability distributions based on historical data. The duration of a fault that starts the contingency as well as the time intervals between elements of the contingency are chosen by sampling from a gamma distribution. In addition, the absence of islands in the system is assessed by analyzing the connectedness of the graph with deleted edges, which is quantified by computing the number of zero eigenvalues of the Laplacian matrix of the resulting graphs. The algorithm is validated on the Nordic 44-bus power system.

中文翻译：

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大数据生成现实突发事件的自动化设计

这封信提出了一种基于对无向图描述的电力系统的一组意外事件的现实选择的大数据生成算法。每个偶然性都是通过消除系统中由图边表示的一定数量的元素来创建的。根据历史数据的几何概率分布随机选择元素的数量以及元素之间的距离。通过从伽马分布中采样来选择启动意外事件的故障持续时间以及意外事件元素之间的时间间隔。此外，通过分析删除边的图的连通性来评估系统中是否存在孤岛，这是通过计算结果图的拉普拉斯矩阵的零特征值的数量来量化的。该算法已在 Nordic 44 总线电源系统上得到验证。