Power Quality Disturbances Classification using Wavelet and Support Vector Machines

Authors:
Peisheng Gao;Weilin Wu
Affiliations:
Zhejiang University, China;Zhejiang University, China
Venue:
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 01
Year:
2006

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Classification of power system disturbances using support vector machines

Expert Systems with Applications: An International Journal

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Abstract

Based on wavelet multiresolution analysis (MRA) and support vector machines (SVMs), a classification method for power quality disturbances in electrical power system is presented. After multiresolution signal decomposition of power quality disturbances, characteristic vectors can be obtained. Short time power transform (STPT) is also used to supplement the characteristic vectors from MRA. Support vector machines are used to classify these characteristic vectors of power quality disturbances, and the performance of SVMs is compared with that of artificial neural network (ANN).