摘要
Prony是电力系统振荡分析中常用的一种方法,但其对噪声数据异常敏感,针对这一问题,提出基于集合经验模态分解(EEMD)与Prony的联合分析方法用于分析电力系统次同步振荡问题。利用EEMD对含噪声信号进行分解,去除其中的高频噪声分量,同时有效解决经验模态分解(EMD)去噪时的模态混频问题,得到平稳信号后利用Prony可准确识别次同步振荡的特征参数,将该联合分析方法用于某300 MW汽轮发电机组的次同步振荡分析中,验证了其抗噪性强和准确度高的优点。
Prony method is used commonly in power system oscillation analysis,but it abnormally sensitive to noise data.A method based on ensemble empirical mode decomposition(EEMD)and Prony is proposed to solve this problem and is used to analyze subsynchronous oscillation of power system.Use EEMD to decompose the noisy signal,remove the high-frequency noise component,and effectively solve the modal mixing problem in empirical mode decomposition(EMD)denoising;after obtaining the stable signal,Prony can accurately identify the characteristic parameters of the subsynchronous oscillation.The joint analysis method is used in the subsynchronous oscillation analysis of a 300 MW steam turbine generator unit,which verifies the advantages of strong noise resistance and high accuracy.
作者
马晓腾
顾煜炯
杨晓峰
MA Xiao-teng;GU Yu-jiong;YANG Xiao-feng(School of Energy Power and Mechanical Engineering,North China Electric Power University,Beijing 102206,China;China Huaneng Group Clean Energy Research Institute,Beijing 102209,China)
出处
《电工电气》
2021年第3期20-24,51,共6页
Electrotechnics Electric
关键词
次同步振荡
PRONY方法
噪声
集合经验模态分解
汽轮发电机组
subsynchronous oscillation
Prony method
noise
ensemble empirical mode decomposition
steam turbine generator
