摘要
基于特征系统实现算法(eigensystem realization algorithm,ERA)求解简便、运算量小的优点,提出了一种改进的次同步振荡参数辨识方法。改进的算法先通过拼接同步相量的实部矩阵和虚部矩阵构造实数域汉克尔矩阵,并对其进行矩阵分解得到系统矩阵,再求系统矩阵的特征值从而实现次同步振荡角频率的提取,仅利用200 ms的同步相量序列即可实现次同步振荡参数的高效辨识。改进的ERA有效解决了现有ERA在辨识过程中未考虑基波分量和振荡分量的角频率两两共轭约束的局限。再分别利用合成和实际测量的同步相量测量终端数据对改进的ERA进行验证研究,结果表明所提算法可以准确提取基波和次同步/超同步振荡参数,并有效实现次同步振荡的动态实时监测。
Based on the simplicity and low computational cost of eigensystem realization algorithm(ERA),an improved parameter identification method for subsynchronous oscillation is proposed.The improved algorithm constructs the real domain Hankel matrix by splicing the real part matrix and the imaginary part matrix of synchrophasor and decomposes it to get the system matrix,and then it calculates the eigenvalues of system matrix so as to extract the angular frequency of subsynchronous oscillations.The efficient identification of subsynchronous oscillations parameters can be realized only by using the synchrophasor sequence of 200 ms.The improved ERA effectively solves the limitations that the pairwise conjugate constraints of angular frequency of fundamental and oscillatory components are not considered in the identification process of existing ERA.Finally,the improved ERA is verified by using the synthetic and actual synchrophasor measurement terminal data,and the results show that the proposed algorithm can accurately extract the fundamental and subsynchronous/supersynchronous oscillation parameters,and effectively realize the dynamic real-time monitoring of the subsynchronous oscillations.
作者
曾雪洋
陈刚
刘一霖
张放
史华勃
王曦
ZENG Xueyang;CHEN Gang;LIU Yilin;ZHANG Fang;SHI Huabo;WANG Xi(State Grid Sichuan Electric Power Research Institute,Chengdu 610041,Sichuan,China;Power Internet of Things Key Laboratory of Sichuan Province,Chengdu 610041,Sichuan,China;School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China)
出处
《四川电力技术》
2025年第1期1-9,17,共10页
Sichuan Electric Power Technology
基金
国家电网有限公司科技项目(521997230001)。
关键词
同步相量
次同步振荡
参数辨识
特征系统实现算法
synchrophasor
subsynchronous oscillation
parameter identification
eigensystem realization algorithm
