A Review on DSTATCOM Neural Network Control Algorithm for Power Quality Improvement

This paper reviews neural network control algorithm for power quality improvement. Further, this paper focuses on the neural network control algorithm for DSTATCOM and surveys its area of improvements. Various architectures of Neural Network such as Adaline/Widrow-Hoff, perceptron, Back-propagation...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 785; no. Recent Trends in Power Engineering; pp. 363 - 367
Main Authors Saad, Puteh, Tunku Mansur, Tunku Muhammad Nizar, Ali, Rosnazri, Baharudin, N.H., Syed Hassan, Syed Idris
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.08.2015
Subjects
Architecture (computers)
Back propagation
Control theory
Industrial applications
Networks
Neural networks
Radial basis function
Three phase
Harmonics
Shunt Active Power Filter
Power Quality
DSTATCOM
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Summary:This paper reviews neural network control algorithm for power quality improvement. Further, this paper focuses on the neural network control algorithm for DSTATCOM and surveys its area of improvements. Various architectures of Neural Network such as Adaline/Widrow-Hoff, perceptron, Back-propagation (BP), Hopfield, and Radial Basis Function (RBF) that has been reviewed in this paper. It is found that many researches on theoretical works and single phase system are widely performed, whereas its application on distribution network for three phase system is hardly found. Even so much improvement that have been done by researchers theoretically to improve the drawbacks of Neural Network controller; there are still wide gaps for verification through experimental implementation and industrial applications.
Bibliography:Selected, peer reviewed papers from the 2015 9th International Power Engineering and Optimization Conference (PEOCO 2015), March 18-19, 2015, Melaka, Malaysia
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ISBN:9783038355120
3038355127
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.785.363