Harmonic analysis and detection of power system based on double moment wavelet transform

Author(s):  
Liang Kangyou ◽  
Yuan Ling ◽  
Tan Yuhang
2013 ◽  
Vol 415 ◽  
pp. 241-244
Author(s):  
Rong Hui Liu ◽  
Ai Qang Pan ◽  
Xiu Yang

In this paper, the principles of wavelet transform and wavelet packet transform were presented. The wavelet packet transform had good characteristics of uniform frequency decomposition, and thus transient harmonic analysis method was proposed based on wavelet packet transform. Finally, transient interharmonic, time varying harmonic and transient oscillation signals in power systems were simulated with Matlab emulator. The perfect results of simulation show that the presented method can accurately detect the transient harmonics, which provides support for harmonic analysis in power systems.


2021 ◽  
Vol 11 (15) ◽  
pp. 7007
Author(s):  
Janusz P. Paplinski ◽  
Aleksandr Cariow

This article presents an efficient algorithm for computing a 10-point DFT. The proposed algorithm reduces the number of multiplications at the cost of a slight increase in the number of additions in comparison with the known algorithms. Using a 10-point DFT for harmonic power system analysis can improve accuracy and reduce errors caused by spectral leakage. This paper compares the computational complexity for an L×10M-point DFT with a 2M-point DFT.


2013 ◽  
Vol 483 ◽  
pp. 630-634
Author(s):  
Shu Chuan Gan ◽  
Ling Tang ◽  
Li Cao ◽  
Ying Gao Yue

An algorithm of artificial colony algorithm to optimize the BP neural network algorithm was presented and used to analyze the harmonics of power system. The artificial bee colony algorithm global searching ability, convergence speed for the BP neural network algorithm for harmonic analysis is easy to fall into local optimal solution of the disadvantages, and the initial weights of the artificial bee colony algorithm also greatly enhance whole algorithm model generalization capability. This algorithm using MATLAB for Artificial bee colony algorithm and BP neural network algorithm simulation training toolbox found using artificial bee colony algorithm to optimize BP neural network algorithm converges faster results with greater accuracy, with better harmonic analysis results.


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