摘要
针对目前电力系统低频振荡模式识别和参数提取中的噪声干扰等问题,提出一种基于希尔伯特变换(Hilbert transformation,HT)和能量函数经验模态分解(energy function of empirical mode decomposition,EFEMD)相结合的低频振荡模态辨识方法。首先运用经验模态分解(empirical mode decomposition,EMD)对含有噪声的电力系统低频振荡广域测量信号进行经验模态分解得到各个固有模态函数(intrinsic modal function,IMF),随后应用EFEMD-HT能量法对IMF进行能量计算并权重,筛选出系统的主导振荡模式,最后通过Hilbert变换对主导振荡模式进行参数的提取。通过对理想信号、EPRI-36机系统仿真信号以及电网实测PMU信号的仿真验证了所提EFEMD-HT能量法的可行性与有效性,能够对系统的主导振荡模式进行准确地辨识。
To solve the problems of noise interference in low-frequency oscillation pattern recognition and parameter extraction of power system,a low-frequency oscillation modal identification method based on the combination of Hilbert Transformation(HT)and energy function of empirical mode decomposition(EFEMD)is proposed.Firstly,EMD is used to decompose the low-frequency oscillation-area measurement signal in power system with noise to obtain each intrinsic mode function(IMF).Then EFEMD-HT energy method is used to calculate the energy of each intrinsic mode function and weight it,and the dominant oscillation mode of the system is screened out.Finally,Hilbert transform is used to extract the parameters of the dominant oscillation mode.The feasibility and effectiveness of the proposed EFEMD-HT energy method are verified by the simulation of ideal signal,EPRI-36 system simulation signal and the measured PMU signal of the power grid,and the dominant oscillation mode of the system can be accurately identified.
作者
张程
邱炳林
刘佳静
ZHANG Cheng;QIU Binglin;LIU Jiajing(School of Electronic,Electrical Engineering and Physics,Fujian University of Technology,Fuzhou 350118,China;Fujian Provincial University Engineering Research Center for Simulation Analysis and Integrated Control of Smart Grid,Fuzhou 350118,China)
出处
《南方电网技术》
CSCD
北大核心
2022年第3期48-57,共10页
Southern Power System Technology
基金
国家自然科学基金(51977039)
福建省高校工程研究中心开放基金项目“智能电网仿真分析与综合控制”(KF-D2010)。
作者简介
张程(1982),男,副教授,硕士生导师,博士,研究方向为电力系统稳定性分析、广域监测等,zhangcheng@fjut.edu.cn;邱炳林(1998),男,硕士研究生,研究方向为电力系统分析、稳定和控制,1577204130@qq.com;刘佳静(1996),女,硕士研究生,研究方向为电力系统分析、稳定和控制,1104761596@qq.com。
