Frequent changes in power grid topology bring risks to the stable operation of power systems. It is essential to identify changes in the power grid topology quickly and accurately. This paper presents a novel method named network reduction-based topology change identification (NR-TCI) algorithm to identify topology changes in multi-machine power systems. The proposed algorithm can quickly identify power grid topology changes using only phasor measurement unit (PMU) data sampled during the system’s transient process. The NR-TCI algorithm uses the network order reduction method to reduce the order of a bus admittance matrix and then uses PMU measurement data to estimate the reduced admittance matrix by least square method. Finally, the reduced admittance matrix is adopted to find topological information, and the Sherman–Morrison formula is utilized to identify the topology changes. The effectiveness of the proposed NR-TCI algorithm is verified with a case study of a 3 machine 9 bus system in Matlab. In addition, the influence of PMU sampling frequency on the effectiveness of the proposed algorithm is also studied.

中文翻译：

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通过简化导纳矩阵识别电网中的拓扑变化

电网拓扑结构的频繁变化给电力系统的稳定运行带来风险。快速准确地识别电网拓扑结构的变化至关重要。本文提出了一种基于网络缩减的拓扑变化识别（NR-TCI）算法来识别多机电力系统中的拓扑变化。所提出的算法可以仅使用在系统瞬态过程中采样的相量测量单元（PMU）数据快速识别电网拓扑变化。NR-TCI算法采用网络降阶方法对总线导纳矩阵进行降阶，然后使用PMU测量数据通过最小二乘法估计降阶导纳矩阵。最后采用约化导纳矩阵求拓扑信息，Sherman-Morrison 公式用于识别拓扑变化。所提出的 NR-TCI 算法的有效性通过 Matlab 中的一个 3 机 9 总线系统的案例研究得到验证。此外，还研究了 PMU 采样频率对所提算法有效性的影响。