电力系统保护与控制2025，Vol.53Issue(14)：100-110,11.DOI:10.19783/j.cnki.pspc.241215
基于改进SOBI-SGMD算法的次同步振荡模态辨识研究
Research on subsynchronous oscillation mode identification based on improved SOBI-SGMD algorithm
摘要
Abstract
Aiming at the problem of accurate identification of subsynchronous oscillation(SSO)signals,a multi-channel SSO identification and early warning method is proposed by combining symplectic geometry mode decomposition(SGMD)improved with dynamic time warping(DTW)and second-order blind identification(SOBI).First,SGMD is applied to the SSO signal,which is then subjected to diagonal averaging and adaptive reconstruction to obtain the initial symplectic geometric mode components(ISGMCs).The optimal distance between ISGMCs is calculated by DTW algorithm to measure the similarity of sequences,and the symplectic geometry components(SGCs)with independent modes are adaptively selected.Next,the dominant SGCs are used as observation signals and input into the SOBI algorithm.By performing joint approximate diagonalization on the observation matrix,the complete SSO source estimation signals are obtained.The least square method is introduced to improve the SOBI algorithm,enabling direct identification of the SSO oscillation frequency and attenuation factor.Finally,through comparative analysis of ideal and simulation examples,it is verified that the proposed algorithm can accurately and efficiently identify multi-channel subsynchronous oscillation signals.关键词
辛几何模态分解/二阶盲辨识/次同步振荡/多通道辨识/动态时间规整算法Key words
symplectic geometry mode decomposition/second order blind identification/subsynchronous oscillation/multi-channel identification/dynamic time warping algorithm引用本文复制引用
郭成,杨宣铭,杨灵睿,奚鑫泽..基于改进SOBI-SGMD算法的次同步振荡模态辨识研究[J].电力系统保护与控制,2025,53(14):100-110,11.基金项目
This work is supported by the National Natural Science Foundation of China(No.52367002). 国家自然科学基金项目资助(52367002) （No.52367002）
云南省科技厅联合基金重点项目资助(202201BE070001-15) （202201BE070001-15）
