物理学报Issue(6)：068401-1-068401-9,9.DOI:10.7498/aps.63.068401
基于CCF-TLS-ESPRIT算法的低频振荡在线辨识
On-line identification for low frequency oscillation based on CCF-TLS-ESPRIT algorithm
摘要
Abstract
On-line identification for low frequency oscillation needs to measure signals which couple with white Gaussian noise from wide area monitoring systems (WAMSs). Processed by low pass filter, white Gaussian noise can turn into colored Gaussian noise, so the accuracy of oscillatory indentification would be reduced. To solve the problem of colored Gaussian noise, in this paper we propose a cross-correlation-function (CCF) method that could reduce the influence of colored Gaussian noise. Combined with TLS-ESPRIT algorithm, CCF-TLS-ESPRIT could identify oscillatory modes in the environment of colored Gaussian noise rapidly. The simulation results show the effectiveness of the proposed method.关键词
广域测量技术/互相关函数/总体最小二乘-旋转不变技术参数估计/高斯色噪声Key words
wide area monitoring systems/cross-correlation-function/TLS-ESPRIT/colored Gaussian noise引用本文复制引用
胡楠,李兴源,李宽,覃波..基于CCF-TLS-ESPRIT算法的低频振荡在线辨识[J].物理学报,2014,(6):068401-1-068401-9,9.基金项目
国家自然科学基金重点项目(批准号:51037003)和国家电网公司大电网重大专项(批准号：SGCC-MPLG027-2012)资助的课题.@@@@Project supported by the Key Program of the National Natural Science Foundation of China (Grant No.51037003), and the State Grid Corporation of China, Major Projects on Planning and Operation Control of Large Scale Grid (Grant No. SGCC-MPLG027-2012) （批准号:51037003）
