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Research on Quick Detection of Abnormal Events in Power Grid Based on the Large Dimensional Random Matrix Theory

机译:基于大尺寸随机矩阵理论的电网异常事件快速检测研究

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Detecting abnormal operating states in the power grid is a fundamental method used in processing abnormal events in the power grid, while the massive applications of WAMS (wide area measurement system) provide conditions for detecting weak anomalies in the power grid. According to the random matrix theory, acquisition signals of a variety of PMUs (phase measurement units) were constructed into a large-dimensional random matrix. Based on the characteristics of spectral distribution of the large dimensional random matrix, the principle and criterion for detecting abnormal states in the power grid were proposed on the basis of the spectral distribution of the large-dimensional random matrix. What's more, the detection method proposed was proven to be effective by analyzing PMU frequency monitoring data in the case. The method proposed in this paper can be used for sensitively detecting abnormal events in the power grid and making a quick judgment, which offers a new way of analyzing and processing abnormal events in the power grid.
机译:检测电网中的异常操作状态是用于在电网中处理异常事件的基本方法,而WAMS(宽面积测量系统)的大规模应用提供了检测电网中的弱异常的条件。根据随机矩阵理论,构造各种PMU(相位测量单元)的采集信号被构造成大维随机矩阵。基于大维随机矩阵的光谱分布特征,基于大维随机矩阵的光谱分布,提出了用于检测电网中的异常状态的原理和标准。更重要的是,通过在案例中分析PMU频率监测数据,证明提出的检测方法是有效的。本文提出的方法可用于敏感地检测电网中的异常事件并进行快速判断,这提供了一种新的分析和处理电网中异常事件的新方法。

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