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基于实测信号的电力系统低频振荡模态辨识
引用本文:蔡国伟,杨德友,张俊丰,刘铖.基于实测信号的电力系统低频振荡模态辨识[J].电网技术,2011(1):59-65.
作者姓名:蔡国伟  杨德友  张俊丰  刘铖
作者单位:东北电力大学电气工程学院;华北电力大学电气与电子工程学院;
基金项目:国家自然科学基金项目(50777007)~~
摘    要:广域相量测量系统的应用为基于量测的电力系统稳定性分析提供了有力支持。基于动态量测信息准确地辨识电力系统低频振荡模态参数及振型,对提高电力系统低频振荡的实时监测与控制至关重要。结合经验模态分解与随机子空间辨识算法,基于发电机有功功率的动态量测信息,开展了电力系统低频振荡辨识与分析的研究。该方法能够在较短的时间从含噪信号内提取原系统真实准确的振荡信息,同时能够得到各振荡模式相应的振型,有效地克服Prony算法和自回归滑动平均算法受噪声、系统实际阶数的影响大,以及单一随机子空间辨识算法难以处理非线性、非平稳振荡信号的缺点。测试系统及仿真结果验证了该方法在电力系统低频振荡分析中的可行性。

关 键 词:低频振荡  动态特性  经验模态分解  随机子空间辨识

Mode Identification of Power System Low-Frequency Oscillation Based on Measured Signal
CAI Guowei,YANG Deyou,ZHANG Junfeng,LIU Cheng.Mode Identification of Power System Low-Frequency Oscillation Based on Measured Signal[J].Power System Technology,2011(1):59-65.
Authors:CAI Guowei  YANG Deyou  ZHANG Junfeng  LIU Cheng
Affiliation:CAI Guowei1,YANG Deyou2,ZHANG Junfeng1,LIU Cheng1(1.School of Electrical Engineering,Northeast Dianli University,Jilin 132012,Jilin Province,China,2.School of Electrical and Electronic Engineering,North China Electric Power University,Changping District,Beijing 102206,China)
Abstract:Application of wide area measurement system(WAMS) provides strong support to measurement-based power system stability analysis,so it is of great importance for the improvement of real-time monitoring and control of power system low-frequency oscillation to well and truly identify oscillation modals and oscillation parameters based on the information from dynamic measurement.Combining empirical mode decomposition(EMD) with stochastic subspace identification(SSI) algorithm and according to the dynamically mea...
Keywords:low frequency oscillations  dynamic characteristics  empirical mode decomposition(EMD)  stochastic subspace identification(SSI)  
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