Interference Source of Voltage Sag in Distribution System Automatic Identification and Classification Using Wavelet and Neural Network

Author

Wei, Chen ; Xiaohong, Hao ; Jie, Lin

Author_Institution

Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol.

Volume

2

fYear

0

fDate

0-0 0

Firstpage

7508

Lastpage

7512

Abstract

Voltage sags due to line fault, transformer energizing and induction motor starting were analyzed based on an PSB (power system blockset) simulation model in the paper at first. Then presents a method to identify and classify interference source of voltage sag in distribution system using a novel combination of wavelet transform and artificial neural network. The simulated waves were discomposed into 7 levers using wavelet transform, afterwards, the energy feature, which was extracted from the wavelet coefficients under different levers, was employed as the inputs of the neural networks to identify and classify the interference source of voltage sag. The results of simulation and case study show the proposed method is simple and validity

Keywords

neural nets; power distribution; power engineering computing; power supply quality; power system simulation; wavelet transforms; artificial neural network; distribution system automatic identification; induction motor; interference source; line fault; power quality; power system blockset simulation model; transformer; voltage sag; wavelet transform; Artificial neural networks; Induction motors; Interference; Neural networks; Power quality; Power system analysis computing; Power system modeling; Power system simulation; Voltage fluctuations; Wavelet transforms; neural network; power quality; power system; voltage sag; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713425

Filename

1713425