电力系统保护与控制2012，Vol.40Issue(13)：18-23,6.
基于经验模态分解自适应滤波的次同步振荡ESPRIT分析
ESPRIT analysis of subsynchronous oscillation based on the empirical mode decomposition self-adaptive filter
摘要
Abstract
Estimation of signal parameters via rotational invariance techniques (ESPRIT) can be used to identify subsynchronous oscillation. However, this method can't identify mode parameter efficiently in the noise. This paper uses the empirical mode decomposition (EMD) method to filter the noise before the parameters are identified. And then, the improved ESPRIT is compared with the non-filtered ESPRIT and the PRONY algorithm in order to prove its availability. Simulation results show that using empirical mode decomposition, self-adaptive filter can be realized and the veracity is improved. In consideration of the self-adaptibility of EMD and the speediness and accuracy of ESPRIT identification, the proposed method can be applied to on-line detection of subsynchronous oscillation (SSO), laying a foundation for the monitor and research of SSO of large system.关键词
高压直流/次同步振荡/经验模态分解/旋转矢量不变技术参数估计/振荡模态Key words
high voltage direct current/ subsynchronous oscillation/ empirical mode decomposition/ ESPRIT/ oscillation mode分类
信息技术与安全科学引用本文复制引用
李宽,李兴源,胡楠,赵睿,穆子龙..基于经验模态分解自适应滤波的次同步振荡ESPRIT分析[J].电力系统保护与控制,2012,40(13):18-23,6.基金项目
国家自然科学基金重点项目(51037003) （51037003）
四川省科技厅基础应用计划(2010jy0018) （2010jy0018）
四川省电力公司科技项目(11H0889) （11H0889）
