高电压技术2025，Vol.51Issue(1)：146-157,中插13-中插17,17.DOI:10.13336/j.1003-6520.hve.20240044
改进自适应VMD和TLS-ESPRIT的风电系统次/超同步振荡参数辨识
Improved Adaptive VMD and TLS-ESPRIT Sub/sup-synchronous Oscillation Parameter Identification for Wind Power Systems
摘要
Abstract
In order to solve the problem of poor noise adaptability and mode aliasing in the extraction process of coupled sub/sup-synchronous oscillation parameters by common identification methods,an adaptive variational mode decomposi-tion(VMD)is proposed in this paper.The total residual loss entropy,Chebyshev distance between components and edge entropy are defined to determine the number and bandwidth of decomposition mode,and the parameters of the decom-posed oscillating components are identified by using the least squares and rotation invariant technique(TLS-ESPRIT),without additional noise reduction algorithms.The effectiveness of the proposed method is verified by composite signal tests and PSCAD/EMTDC simulation.Finally,the proposed method is compared with the improved Prony algorithm and MCEEMD under different noise levels and frequencies of sub/sup-synchronous oscillation.The results show that the proposed method can be adopted to effectively suppress the noise interference of the original signal,and is more accurate in the decomposition of the coupled sub/sup-synchronous oscillation signal,and the parameter identification results are more reliable.Hence,the conclusion has a certain reference significance for oscillation tracing and improvement system damping of a wind power system.关键词
SSSO/改进VMD/损失总熵/TLS-ESPRIT/模态混叠Key words
SSSO/improved VMD/total residual loss entropy/TLS-ESPRIT/mode aliasing引用本文复制引用
李文博,钱伟荣,李淑蓉,沙鹏程,邓军波,张冠军..改进自适应VMD和TLS-ESPRIT的风电系统次/超同步振荡参数辨识[J].高电压技术,2025,51(1):146-157,中插13-中插17,17.基金项目
国家电网有限公司科技项目(5500-202414138A-1-1-ZN). Project supported by Science and Technology Project of SGCC(5500-202414138A-1-1-ZN). （5500-202414138A-1-1-ZN）
