Open AccessApplication of improved wavelet denoising method in low-frequency oscillation analysis of power system
Author(s) -
Mosi Liu,
Zhen Sun,
Mingpo Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1633/1/012115
Subject(s) - wavelet , noise reduction , oscillation (cell signaling) , signal (programming language) , matlab , noise (video) , low frequency oscillation , computer science , algorithm , interference (communication) , power (physics) , pattern recognition (psychology) , mathematics , electric power system , artificial intelligence , telecommunications , physics , channel (broadcasting) , genetics , quantum mechanics , image (mathematics) , biology , programming language , operating system
The Prony algorithm has been widely used in low-frequency oscillation analysis of power system due to its good mathematical characteristics. However, the Prony algorithm is very sensitive to noise and requires a high level of input signal. This paper overcomes the shortcomings of traditional soft and hard threshold denoising methods by improving the threshold and threshold function of wavelet denoising. Using the improved wavelet threshold denoising method to preprocess the sampled signal can effectively improve the anti-interference ability of the Prony algorithm. The simulation experiment is performed with MATLAB and the experimental results show the effectiveness of the improved method.