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电力系统低频振荡在线辨识的改进Prony算法
引用本文:肖晋宇,谢小荣,胡志祥,韩英铎.电力系统低频振荡在线辨识的改进Prony算法[J].清华大学学报(自然科学版),2004,44(7):883-887.
作者姓名:肖晋宇  谢小荣  胡志祥  韩英铎
作者单位:清华大学,电机工程与应用电子技术系,北京,100084
基金项目:国家自然科学基金资助项目(59877011)
摘    要:研究在线的振荡特征辨识算法是实现电力系统低频振荡在线监视以及广域阻尼控制的重要理论基础。广域测量系统的发展和应用使得低频振荡的在线辨识成为可能。该文提出了一种用于在线分析电力系统低频振荡的改进Prony算法,该算法针对输入信号的实际阶数和线性预测参数的估计进行了综合改进。经过算法时间复杂度的分析,证明改进算法提高了计算速度。计算机仿真和动模实验结果表明,改进算法能够得到更符合系统实际阶数的降阶模型,分析计算占空比小于4%,满足在线低频振荡辨识和系统振荡特性分析的需要。

关 键 词:广域测量系统  Prony算法  低频振荡  在线辨识
文章编号:1000-0054(2004)07-0883-05
修稿时间:2003年6月23日

Improved Prony method for online identification of low-frequency oscillations in power systems
XIAO Jinyu,XIE Xiaorong,HU Zhixiang,HAN Yingduo.Improved Prony method for online identification of low-frequency oscillations in power systems[J].Journal of Tsinghua University(Science and Technology),2004,44(7):883-887.
Authors:XIAO Jinyu  XIE Xiaorong  HU Zhixiang  HAN Yingduo
Abstract:On-line oscillation characteristic analysis algorithms are used to monitor on-line low-frequency oscillations for control of wide-area damping. The development of wide area measurement systems allow detection of low-frequency oscillations on line. This paper discribes an improved Prony method for the detection of low-frequency oscillations. That significantly improves the identification of the practical order of the input signal and estimates of the linear prediction parameters. The time complexity of the algorithm is analyzed in the paper. Numerical simulations and physical test results demonstrate that the reduced-order model is more accurate with less computations; therefore, it is useful for online applications.
Keywords:wide  area measurement system  Prony method  low-frequency oscillations  online identification
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