Title: Artificial neural network-based harmonics extraction algorithm for shunt active power filter control

Authors: Awan U. Krismanto; Abraham Lomi; Rusdy Hartungi

Addresses: Department of Electrical Engineering, Institute of Technology Nasional Malang, Jl. Raya Karanglo Km. 2, Malang 65143, Indonesia. ' Department of Electrical Engineering, Institute of Technology Nasional Malang, J1. Raya Karanglo Km. 2, Malang 65143, Indonesia. ' Department of Electrical Engineering, University of Central Lancashire, Preston, Lancashire, PR12HE, UK

Abstract: This paper presents a harmonics extraction algorithm using artificial neural network methods. The neural network algorithm was used due to the simpler calculation process compared with conventional method such as fast Fourier transform (FFT). Two types of neural network, i.e., multi-layer perceptron (MLP) and radial basis function (RBF) were employed to extract harmonics current component from its distorted wave current. Further, the extracted harmonics current was used as reference current for shunt active power filter (APF) control. This paper compared the performance of MLP and RBF for harmonics extraction. The advantages of RBF are simpler shape of the network and faster learning speed. Unfortunately, the RBF need to be trained recursively for various harmonics component. MLP can be used to extract various harmonics component in specific data range but need large number of data training hence slower training process.

Keywords: artificial neural networks; ANNs; radial basis function; RBF; multi-layer perceptron; MLP; harmonics extraction; shunt active power filter; SAPF.

DOI: 10.1504/IJPELEC.2012.046606

International Journal of Power Electronics, 2012 Vol.4 No.3, pp.273 - 289

Received: 06 Dec 2010
Accepted: 12 Aug 2011
Published online: 23 Aug 2014 *

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