Title :
Wavelet transform based fuzzy logic for power quality classification
Author :
Gu, Xinyi ; Lo, K.L.
Author_Institution :
Dept of Electron. & Electr. Eng., Univ. of Strathclyde, Glasgow, UK
fDate :
Aug. 31 2010-Sept. 3 2010
Abstract :
This paper proposes a wavelet-based fuzzy-expert system to power quality disturbance classification. The wavelet transform and Parseval´s theorem are introduced in this paper. To extract features in power-quality disturbance, the energy distribution of wavelet at each decomposition level is calculated. A fuzzy-expert system is proposed to classify the power quality disturbances. Based on the energy distribution patterns the membership functions of input and rule base are generated. Finally, the fuzzy set of the output variable is converted to a crisp number, in terms of which the disturbances are classified. The types of disturbances concerned include voltage sag/swell, interruption, harmonic, and flickers.
Keywords :
fuzzy logic; power distribution; wavelet transforms; Parseval´s theorem; energy distribution patterns; fuzzy expert system; fuzzy logic; power quality classification; wavelet transform; Distortion; Feature extraction; Power quality; Time frequency analysis; Voltage fluctuations; Wavelet transforms; Mallat algorithm; Parseval´s theorem; classification; energy distribution; fuzzy-expert system; power quality disturbance; wavelet transform;
Conference_Titel :
Universities Power Engineering Conference (UPEC), 2010 45th International
Conference_Location :
Cardiff, Wales
Print_ISBN :
978-1-4244-7667-1