Abstract When an out-of-step (OOS) condition occurs in a power system, it splits into multiple islands. This uncontrolled separation happens due to distance relay operation on the lines where electrical centers appear. Real-time phasors obtained from Phasor Measurement Units (PMUs) can be used to track the evolution of electrical centers and identify the natural boundary of separation (cutset). Interestingly, electrical centers do not appear simultaneously on the cutset lines; instead, they evolve at different rates. Hence, the cutset is identified only when the signature of the last electrical center appears. We aim to accelerate the cutset prediction so that the complete cutset is identified when the first electrical center is predicted. For this, we propose a computationally efficient algorithm based on the application of graph theory and clustering technique. Thus, the proposed scheme addresses the significant delay in cutset prediction and thereby increases the time available for controlled islanding. Test results on standard IEEE systems and the All India test system validate the scheme.

中文翻译：

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在失步条件下加速自然割集预测的图论方法

摘要 当电力系统出现失步（OOS）情况时，它会分裂成多个孤岛。这种不受控制的分离是由于电气中心出现的线路上的距离继电器操作而发生的。从相量测量单元 (PMU) 获得的实时相量可用于跟踪电中心的演变并识别分离的自然边界（割集）。有趣的是，电中心不会同时出现在割集线上；相反，它们以不同的速度发展。因此，只有当最后一个电中心的签名出现时才识别割集。我们的目标是加速割集预测，以便在预测第一个电中心时识别完整的割集。为了这，我们基于图论和聚类技术的应用提出了一种计算效率高的算法。因此，所提出的方案解决了割集预测中的显着延迟，从而增加了可用于受控孤岛的时间。标准 IEEE 系统和全印度测试系统的测试结果验证了该方案。