Abstract：Power system Low frequency oscillation has become a key factor that endanger the safe operation of the system, and the model and parameter influence on the system dynamic behavior can be completely reflected by the disturbed trajectory. The empirical mode decomposition (EMD) is briefly introduced in this paper, and a new method for eliminating non-stationary trend of Perturbed Trajectory based on empirical mode decomposition is proposed. The simulation result proves the validity and superiority.
林虹,陈琳. 基于经验模态分解的电力系统受扰轨迹去噪方法[J]. 电气技术, 2014, 15(08): 11-13.
Lin Hong, Chen Lin. Denoising Method of Power System Perturbed Trajectory Based on Empirical Mode Decomposition. Electrical Engineering, 2014, 15(08): 11-13.
[1] HUANG N E. The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. Proceedings of the Royal Society of London Series A, 1998,454(1971):903-995. [2] 经验模态分解方法及其实现[J].计算机工程与应用, 2006(32):44-47. [3] 陈伟,王尚旭,啜晓宇.基于经验模态分解的属性优化方法[J]. 石油地球物理勘探,2013(1):121-127. [4] 王焱,朱善安.基于经验模态分解的轴承故障诊断[J].机电工程,2007,24(10):77-78,90. [5] 穆钢,史坤鹏,安军.结合经验模态分解的信号能量法及其在低频振荡研究中的作用[J].中国电机工程学报,2008,28(19):36-41. [6] 徐千茹,文一宇,张旭航,等. 电力系统低频振荡综述[J].电力与能源,2014(01):38-42.
2014, Vol. 15 
