Title: Harmonics estimation using KF-Adaline algorithm and elimination with hybrid active power filter in distorted power system signals

Authors: P.K. Ray; Gayadhar Panda

Addresses: Department of Electrical Engineering, Indira Gandhi Institute of Technology, Sarang, Odisha 759146, India. ' Department of Electrical Engineering, Indira Gandhi Institute of Technology, Sarang, Odisha 759146, India

Abstract: Harmonics estimation and its elimination for a signal distorted with additive noise is an interdisciplinary area of interest for many researchers. This paper presents Kalman filter – adaptive linear neural network (KF-Adaline) approach for harmonics estimation and hybrid active power filter (HAPF) with modified PWM control technique for its elimination in distorted power system signals. In the estimation process, the weight of the Adaline is updated using Kalman filter algorithm. Harmonics components are estimated from the updated weights of the Adaline. In order to mitigate these harmonics, HAPF with modified PWM control is proposed. The modified PWM control technique is based on comparing simultaneously a triangular high frequency carrier signal with a slow varying regulation signal and it is opposite. A laboratory prototype for HAPF with modified PWM technique is built for harmonics elimination in distorted power system signals. Simulation and experimental results are presented to verify the good behaviour of the modified PWM control technique. In addition, the performance of the HAPF is found to be much better than that of the APF as far as the source current distortion is concerned.

Keywords: harmonics estimation; harmonics elimination; KF-Adaline; hybrid active power filters; HAPF; modified PWM control; distorted signals; power systems; Kalman filter; neural networks; pulse width modulation; current distortion.

DOI: 10.1504/IJMIC.2012.047122

International Journal of Modelling, Identification and Control, 2012 Vol.16 No.2, pp.149 - 158

Published online: 31 May 2012 *

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