基于随机矩阵理论的电网事件监测研究

电力系统在线事件监测对电网态势感知具有重要意义.针对现代大规模电网的事件监测问题,文中提出一种基于随机矩阵谱分布特性的电网事件监测方法.首先利用大数据处理方法构建电网电气信息的随机矩阵模型.然后将电网事件监测问题转化为分析随机矩阵谱分布问题,并建立基于协方差矩阵最大最小特征值之差的评价指标,最后根据评价指标确定事件发生.为了验证文中所提方法的有效性,通过IEEE 39节点标准系统进行了仿真分析,同时通过与传统的MSR方法进行对比,证明在强噪声环境下具有更强的适应性.

Research on Grid Event Monitoring Based on Random Matrix Theory

On-line event monitoring of power systems is of great significance for situational awareness of power grids.Aiming at the problem of event monitoring in modern large-scale power grids,a method of power grid event monitoring based on the random matrix spectral distribution characteristics is proposed.First,a big data processing method is used to build a random matrix model of the electrical information of the power grid.Then the grid event monitoring problem is transformed into an analysis of the random matrix spectrum distribution problem,and an evaluation index based on the difference between the maximum and minimum eigenvalues of the covariance matrix is established.Finally,the event is determined based on the evaluation index.In order to verify the effectiveness of the method proposed in this paper,simulation analysis was performed through the IEEE 39-node standard system.At the same time,it was compared with the traditional MSR method to prove that it has stronger adaptability in strong noise environments.