摘要
为了精确检测同步电机参数,提出了一种小波变换和矩阵束相结合的新算法。该方法运用小波变换对短路电流进行消噪处理,提高其信噪比。运用矩阵束算法提取预处理后的短路电流各分量的频率和阻尼,然后对短路电流各分量的幅值和相位使用最小二乘法进行估计,进而实现同电机参数的辨识。针对在不同信噪比下的短路电流采样数据,分别运用TLS-ESPRIT算法和该方法进行同步电机参数辨识,仿真结果表明,与TLS-ESPRIT算法相比,该方法采用的数据样本数较少。在信噪比大于30dB时,该方法具有更高的计算精度;在信噪比低于30dB时(15～25dB),仍能精确地辨识同步电机的参数。该算法的计算精度高,抗噪性强,简单有效。
In order to accurately detect synchronous machine parameters, this paper presents a new algorithm based on the wavelet transform and the matrix pencil. This method pretreats the short-circuit current by noise with the wavelet transform to improve its SNR. Then matrix pencil algorithm is used to extract the frequency and damping of each component of short-circuit current. The magnitude and phase of each component of short-circuit current are estimated by least squares method, thus obtaining the synchronous parameters. Under different signal to noise ratio, it respectively uses TLS-ESPRIT algorithm and the method for parameter identification of synchronous machine. Simulation results show that comparing with the TLS-ESPRIT algorithm, it uses less samples. When SNR is larger than 30 dB, this method has higher recognition accuracy; and when SNR is between 15dB and 25dB, it still accurately identifies the parameters. The method developed in this paper is valid.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2012年第9期87-92,共6页
Power System Protection and Control
关键词
同步电机
参数辨识
小波预处理
矩阵束算法
最小二乘
synchronous machine
parameter identification
wavelet preprocessing
matrix pencil algorithm
least squares
