基于快速分解正交变换状态估计的电网含坏数据检测与辨识

Detection and Identification of Bad Data in Power Grid Considering Fast Based of Orthogonal Transformation State Estimation

为解决原有电网含坏数据检测与辨识方法对电网状态估计能力较差导致电网不良数据检测与辨识的精准度较低、适用性较差等问题,引用快速分解正交变换算法,设计考虑快速分解正交变换状态估计的电网含坏数据检测与辨识方法。使用快速分解正交变换算法估计电网状态,采用量测量突变检测法检测电网中的含坏数据。设定相应的检测与辨识平台,实现高精度电网含坏数据的检测与辨识,从而完成基于快速分解正交变换状态估计的电网含坏数据检测与辨识方法的设计。此外,构建算例测试环节,通过与传统方法对比可知,此方法的检测精度更高,可推广应用。

In view of the poor power grid state estimation ability of the original power grid containing bad data detection and identification methods,the detection and identification of bad grid data has low accuracy and poor applicability.The fast decomposition orthogonal transformation algorithm is used to design a method for detecting and identifying bad data in the power grid considering the fast decomposition orthogonal transformation state estimation.The fast decomposition orthogonal transformation algorithm is used to complete the power grid state estimation,and the quantitative measurement mutation detection method is used to detect bad data in the power grid.Set up the corresponding detection and identification platform to achieve high-precision detection and identification of bad data in the power grid.So far,the design of the detection and identification method of power grid containing bad data considering fast decomposition of orthogonal transformation state estimation is completed.Construct the test link of the calculation example.By comparing with the traditional method,it can be seen that the detection accuracy of this method is higher,and this method should be popularized and applied.