Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/14452
Title: Power harmonics analysis for electrical device signature identification using the artificial neural network and support vector machine
Authors: NG WIN SIAU
Keywords: Power harmonics, artificial neural network, support vector machine, genetic algorithm, signature identification, multi class
Issue Date: 23-Jan-2005
Source: NG WIN SIAU (2005-01-23). Power harmonics analysis for electrical device signature identification using the artificial neural network and support vector machine. ScholarBank@NUS Repository.
Abstract: A novel idea of nonintrusively identifying the electrical devices present in a power system by analyzing the current waveform harmonics using the artificial neural network (ANN) or support vector machine (SVM) was developed. The research has shown that different devices produced distinctly different current harmonic signatures. Various ANN architectures and SVM-based classifiers with different kernels were compared. The ANN and SVM-based classifiers were trained to map phase angles and magnitudes (represented in the complex form) of the current waveform harmonics to the combinations of devices present in the system. The trained ANN and SVM-based models performed with high classification accuracy. Classification of harmonic signatures from multiples of electrically identical devices was also studied. The multilayer perceptron ANN, which was the best classifier due to its high accuracy yet low computational resource requirement, was further optimized by evolving its weights using genetic algorithm.
URI: http://scholarbank.nus.edu.sg/handle/10635/14452
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Ng Win Siau - HT027257M.pdf750.07 kBAdobe PDF

OPEN

NoneView/Download

Page view(s)

334
checked on Dec 11, 2017

Download(s)

1,217
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.