互相关优化改进矩阵束算法及其在次同步振荡模态参数辨识的应用

摘要

Aiming at the problems of traditional matrix pencil algorithm such as unstable calculation results and the accuracy of poles extraction not high enough as the signal-to-noise ratio being low, this paper proposes an improved matrix pencil ( IMP) algorithm based on the cross-correlation ( CC) , and applies it to subsynchronous oscillation modal identification of power systems.The new al-gorithm is compared with the traditional matrix pencil algorithm and the improved prony algorithm in case studies, and the results show that the proposed algorithm has characteristics of high fitting degree and strong anti-noise ability, and is able to rapidly and accu-rately identify the modes of subsynchronous oscillation, and thus in benefit of analyzing subsynchronous oscillation modal of large power systems with high noise, and designing damping controllers.%针对传统的矩阵束算法在低信噪比时存在计算数值不稳定、极点提取精确度不高的缺点,提出了一种基于互相关( cross-correlation, CC)优化的改进矩阵束( improved matrix pencil algorithm, IMP)算法,应用于电力系统次同步振荡模态辨识,并结合算例与传统的矩阵束算法和改进Prony算法辨识结果进行了比较。结果表明：该方法能快速准确地辨识系统的次同步振荡模态,具有拟合度高、抗噪声能力强的特点,有助于大系统及强噪声背景下次同步振荡模态分析及阻尼控制器的设计研究。