低频振荡模式辨识中信号非线性去趋的平滑先验方法  

Smoothness prior approach to removing nonlinear trends from signals in identification of low frequency oscillation mode

作　　者：周念成[1] 王予疆[1] 陈刚 徐玉韬[1] 刘贵富[1] 何潜[3] 李军[3] 

机构地区：[1]输配电装备及系统安全与新技术国家重点实验室(重庆大学),重庆400044 [2]南方电网科学研究院,广东广州510080 [3]重庆市电力公司,重庆400014

出　　处：《电力系统保护与控制》2012年第11期1-5,29,共6页Power System Protection and Control

基　　金：国家重点基础研究发展计划(973计划)资助项目(2009CB724505-1);重庆电力公司科技项目(20100658)~~

摘　　要：基于PMU实测信号的低频振荡模式在线辨识是阻尼控制的基础,有效去除PMU实测信号中的非线性趋势才能保证模式辨识的精度。提出了基于平滑先验法的PMU实测信号非线性去趋方法。在分析平滑先验法基本原理基础上,为适应低频振荡模式辨识中信号非线性去趋要求,对其频率响应特性进行研究,确定平滑先验法的正则化参数。采用IEEE-39节点系统时域仿真信号和某电网的PMU实测信号对所提方法进行测试,并与经验模态分解法和数字滤波法进行了比较,表明该方法能够更有效地去除信号中的非线性趋势,较大幅度地提高计算速度,同时也能提高低频振荡模式辨识精度,具有较高的实际应用价值。The online identification of low frequency oscillation mode based on measured signal from PMU is the base of damping control.Removing nonlinear trend from the signal effectively can ensure the precision of mode identification.A method named smoothness prior approach is proposed to remove the nonlinear trend from measured signal.In order to meet the demand of removing nonlinear trend for identification of low frequency oscillation,based on analyzing the basic principle of smoothness prior approach,it determines regularization parameter of smoothness prior approach according to its characteristic of frequency response.It is used to analyze the simulation signals from IEEE-39 bus power system and the measured signals in some power grid,and compared with empirical mode decomposition and digital filter method.The results demonstrate that this proposed method can successfully remove nonlinear trend from the signal and improve the speed of computation,as well as the precision of mode identification,which has a relatively high practical value.

关 键 词：平滑先验法 非线性趋势 实测信号 在线辨识 低频振荡模式 

分 类 号：TM712[电气工程—电力系统及自动化]