Prony和HHT算法在低频振荡在线辨识中的适用性比较  

Comparison of the applicability of Prony and HHT algorithms for on-line identification of low-frequency oscillation

作　　者：胡昊明[1,2] 郑伟[1] 徐伟[1] 鲍颜红[1] 刘韶峰[1] 段慧[1] 

机构地区：[1]国网电力科学研究院,江苏南京210003 [2]东南大学电气工程学院,江苏南京210008

出　　处：《电力系统保护与控制》2013年第14期33-40,共8页Power System Protection and Control

基　　金：国家电网公司资助项目"大电网规划与运行控制技术深化研究重大专项(SGCC-MPLG001-003-2012)"及"人工紧急调度与安全自动控制协同决策技术研究"

摘　　要：Prony算法和Hilbert-Huang变换(HHT)算法是目前实际应用于低频振荡信号辨识的两种算法。Prony算法对于无噪声干扰的平稳信号的分辨率和准确性较高。HHT算法具有时频分析和滤除高频分量的能力,抗噪声性能好,计算速度快,并可以分析主导模式随时间改变的非平稳信号。从准确性、稳定性、完备性、快速性四个方面比较了两种算法在低频振荡在线辨识中的适用性,指出增加前置滤波环节的Prony算法可以满足低频振荡在线监测的要求,而实现强迫振荡扰动源定位则必须采用可进行时频分析的HHT算法。通过实际算例验证了两种算法的适用性。Prony and Hilbert-Huang Transform （HHT） are two signal processing techniques utilized for on-line low-frequency oscillation detection. Prony algorithm is appropriate for processing stationary signals without noise. HHT algorithm has the ability of filtering high-frequency noise and processing non-stationary signals. The performance of Prony and HHT algorithms is compared from following aspects： accuracy, stability, completeness and speediness. Prony algorithm which includes the pre-filtering can meet the requirements of low-frequency oscillation monitoring, while HHT can be used for identification of disturbance source. The applicability of the two algorithms is validated with real power system data.

关 键 词：低频振荡 强迫振荡 在线辨识 PRONY HHT 

分 类 号：TM712[电气工程—电力系统及自动化]