HHT和Prony算法在电力系统低频振荡模态识别中的应用

Application of HHT and Prony Algorithm in Recognition of Low-frequency Oscillation Modality in Power System

电力系统的大规模互联使低频振荡现象越来越突出,如何准确识别低频振荡模式成为需要解决的重点问题。将Hillbert-Huang变换(HHT)与Prony算法的优点相结合,先利用HHT将实测信号分解为若干个本征模态函数(IMF)分量,再利用Prony算法在含有低频振荡信息的IMF分量中提取模态参数。通过算例分析确认,HHT与Prony算法相结合,可以有效提取出系统的低频振荡参数,效果优于仅应用单一变换或算法。

Large-scale interconnection of power system would made low-frequency oscillation more and more highlighted, how to accurately identify low-frequency oscillation mode has become the focal point to be solved. Combining with the advantages of HHT and the Prony algorithm, the measured signal was decomposed by HHT into several IMF compents, and the Prony algorithm was used to extract modal parameter from the IMF eompents that containing low frequency oscillation information. By case study it is confirmed that by combining HHT with Prony algorithm, it can effectively extract the low frequency oscillation parameters of the system, and the effect is better than applying only a single transformation or algorithm.