A power-quality event data compression algorithm based on advanced Support Vector Machine

Author

Wei-yan, Zheng ; Wei-lin, Wu

Author_Institution

Coll. of Electr. Eng., Zhejiang Univ., Shanghai

fYear

2008

fDate

6-9 April 2008

Firstpage

2076

Lastpage

2080

Abstract

An algorithm using SVM (support vector machine) regression for power-quality (PQ) event data compression is presented, the advanced SVM regression can learn dependency from an array of wavelet coefficients which is 2-D representation of PQ event data decomposed by 2-D discrete-time wavelet transform (2-D DWT), using fewer Support Vectors (SV) to represent the original data, thus, the data could be compressed based on this feature. Experiment results show the good performance of proposed algorithm in PQ event data compression, comparing with traditional SVM compression data under the same conditions.

Keywords

discrete wavelet transforms; power engineering computing; power supply quality; support vector machines; SVM regression; advanced support vector machine; discrete-time wavelet transform; power-quality event data compression algorithm; wavelet coefficients; Data compression; Discrete wavelet transforms; Gray-scale; Image coding; Image segmentation; Matrix decomposition; Power quality; Power systems; Support vector machines; Wavelet coefficients; 2-D representation data; Advanced SVM; Discrete-time wavelet transform; PQ event;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on

Conference_Location

Nanjuing

Print_ISBN

978-7-900714-13-8

Electronic_ISBN

978-7-900714-13-8

Type

conf

DOI

10.1109/DRPT.2008.4523751

Filename

4523751