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Information Technology Journal
  Year: 2012 | Volume: 11 | Issue: 11 | Page No.: 1632-1637
DOI: 10.3923/itj.2012.1632.1637
 
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Denoising of Power Quality Disturbance Based on Self-adapting Neural Fuzzy Control

Li Jiasheng, Xiao Weichu, Zhang Xuejun, Li Wenguo and Hu Saichun

Abstract:
In order to increase the accuracy of power quality disturbance detection in noising environment, this study puts forward a denoising algorithm of power quality disturbance based on self-adapting to neutral fuzzy control. It establishes a structure with double-input and single-output neural network fuzzy system. Meanwhile, it presents the principle of denoising and makes a simulation analysis on disturbance circumstances with colored noise such as harmonic wave, voltage sag, voltage swell, voltage interruption etc. The results indicate that the proposed algorithm can well remove the signal-disturbing noise in grid. The waveform is visual clarity; the process of analyzing and calculating is simple and fast; the data got from calculation is few, which make the disturbance denoising of power quality more practical.
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How to cite this article:

Li Jiasheng, Xiao Weichu, Zhang Xuejun, Li Wenguo and Hu Saichun, 2012. Denoising of Power Quality Disturbance Based on Self-adapting Neural Fuzzy Control. Information Technology Journal, 11: 1632-1637.

DOI: 10.3923/itj.2012.1632.1637

URL: https://scialert.net/abstract/?doi=itj.2012.1632.1637

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