利用S变换局部奇异值的同调机组识别方法

Coherency identification method using S-transform and local singular value decomposition

文中提出一种利用S变换局部奇异值的同调机组识别方法。将广域测量系统(Wide Area Measurement System,WAMS)采集到的系统发电机功角信息进行S变换,得到每台发电机的时频信息模值矩阵,将矩阵分割成块,计算各个子块的最大奇异值,利用时频信息模值矩阵中各个子块最大奇异值构造机组特征矩阵,采用分布聚类法对特征矩阵进行聚类分群。IEEE-39节点系统算例表明,该方法能够有效提取功角信息特征,具有很强的抗噪性,能够在不同故障类型下准确识别同调机组。

A new method of coherency identification using S-transform and local singular value decomposition（ SVD）is proposed in this paper. Time-frequency information matrix of each generator is obtained by S-transform of power angle information,which is obtained by WAMS. The maximum singular value of each sub-block is calculated,which is divided by the time-frequency information matrix. The coherency recognition feature matrix is constructed by the maximum singular value of each sub-block,and the coherency grouping is carried out by distributed clustering method. The example of IEEE-39 node system shows that this method can accurately identify coherent generators under different fault types with the characteristic of extracting the valid information of power-angle rocking curve effectively because of its strong anti-noise robustness.