论文部分内容阅读
该文将结构学领域用于分析建筑或机械结构振动特性的多参考点复指数(poly-reference complex exponential,PRCE)法引入电力系统,实现低频振荡辨识.该方法基于多通道信号,构造脉冲序列的自回归模型(autoregressive model,AR model),运用LQ分解,求解其自回归系数,再求解由自回归系数构成的矩阵多项式的根,得到频率和阻尼比,进而求得系统的模态矩阵.该文介绍了PRCE法在电力系统低频振荡模式辨识中的原理,16机系统的仿真结果验证了PRCE方法的有效性和正确性;与总体最小二乘一旋转不变技术参数估计(total least squares-estimation of signal parameters via rotational invariance techniques,TLS-ESPRIT) 方法、随机子空间(stochastic subspace identification,SSI)方法的对比表明,该方法辨识结果在辨识精度、效率上表现得更好.最后,基于四川电网实测数据验证了PRCE方法的有效性.“,”This paper presented a novel method multi reference point complex index (PRCE) which was formerly applied to analyze the vibration characteristics of the architecture or mechanism structures to identify the frequencies and damping ratios of low frequency oscillations.The method is based on a multi-channel input signals,constructed the Autoregressive model (AR model) from the pulse sequence,using LQ decomposition to solve the self-regression coefficients,and then solved by the roots from polynomial regression coefficient matrix obtained constituting the frequency,damping ratio and the mode shape.The theoretical aspects of the PRCE analysis method were firstly revisited briefly in the paper.Then the 16-generator system simulation results demonstrate the validity and correctness of poly-reference complex exponential (PRCE) method.Comparing with the total least squares-estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT) and the stochastic subspace identification (SSI) method shows that PRCE method is better in the accuracy and efficiency.Finally,the effectiveness of the method is demonstrate based on the real data from Sichuan power grid.