摘要
Since the scale and uncertainty of the power sys-tem have been rapidly increasing,the computation efficiency of constructing the security region boundary(SRB)has become a prominent problem.Based on the topological features of histori-cal operation data,a sample generation method for SRB identi-fication is proposed to generate evenly distributed samples,which cover dominant security modes.The boundary sample pair(BSP)composed of a secure sample and an unsecure sam-ple is defined to describe the feature of SRB.The resolution,sampling,and span indices are designed to evaluate the cover-age degree of existing BSPs on the SRB and generate samples closer to the SRB.Based on the feature of flat distribution of BSPs over the SRB,the principal component analysis(PCA)is adopted to calculate the tangent vectors and normal vectors of SRB.Then,the sample distribution can be expanded along the tangent vector and corrected along the normal vector to cover different security modes.Finally,a sample set is randomly gen-erated based on the IEEE standard example and another new sample set is generated by the proposed method.The results in-dicate that the new sample set is closer to the SRB and covers different security modes with a small calculation time cost.
