电工技术学报2017，Vol.32Issue(6)：1-13,13.
基于广义形态滤波与改进矩阵束的电力系统低频振荡模态辨识
Power System Low Frequency Oscillation Identification Based on the Generalized Morphological Method and Improved Matrix Pencil Algorithm
摘要
Abstract
Since more and more serious low-frequency oscillation phenomena have happened in interconnected power grids, a high-accuracy low-frequency oscillation identification method is proposed to overcome the shortages of the existing methods. The method is based on the opening and closing operations of generalized morphology to design an improved generalized morphological filter, which can effectively eliminate the noise and retain the original features of signals. An advanced matrix pencil algorithm was proposed to identify parameters from low frequency oscillation signals. A standardized singular entropy technique was utilized to solve the key problem of order determination. By this way the estimating value of the order can be very close to the real value in the power system, which enhances identification accuracy. Simulations verified the proposed low-frequency oscillation identification method.关键词
低频振荡/广义形态学/矩阵束/奇异熵/模态辨识Key words
Low frequency oscillation/generalized morphology/matrix pencil/singular entropy/mode identification分类
信息技术与安全科学引用本文复制引用
金涛,刘对..基于广义形态滤波与改进矩阵束的电力系统低频振荡模态辨识[J].电工技术学报,2017,32(6):1-13,13.基金项目
欧盟FP7国际科技合作基金(909880),国家自然科学基金(61304260)和福建省杰出青年科学基金(2012J06012)资助项目. （909880）
