DocumentCode :
2912440
Title :
An application of neural network in distribution system harmonic detection
Author :
Chen, Sung-Ling ; Tsay, Ming-Tong ; Lin, Chia-Hung
Author_Institution :
Dept. of Electr. Eng., Cheng Shiu Univ., Kaohsiung, Taiwan
Volume :
C
fYear :
2004
fDate :
21-24 Nov. 2004
Firstpage :
228
Abstract :
In this paper, an effective tool is proposed to detect harmonic components by using probabilistic neural network (PNN). PNN is used to detect the harmonics from the distorted waveforms. PNN can be fast learning and recalling process, no iteration for weight regulations in the learning process, no pre-decision for the number of hidden layers and the number of hidden nodes in each layer, and adaptability for architecture changes. Many tests are conducted and the results show that PNN has advantages over other previously developed algorithm. It provides a simplifying model and shorten processing time to detect harmonics.
Keywords :
learning (artificial intelligence); neural nets; power distribution; power engineering computing; power system harmonics; probability; detect harmonic component; distribution system harmonic detection; fast learning; probabilistic neural network; recalling process; Artificial neural networks; Harmonic distortion; Intelligent networks; Joining processes; Neural networks; Power quality; Power system analysis computing; Power system harmonics; Power system measurements; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2004. 2004 IEEE Region 10 Conference
Print_ISBN :
0-7803-8560-8
Type :
conf
DOI :
10.1109/TENCON.2004.1414749
Filename :
1414749
Link To Document :
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