Harmonics estimation using KF-Adaline algorithm and elimination with hybrid active power filter in distorted power system signals
by P.K. Ray; Gayadhar Panda
International Journal of Modelling, Identification and Control (IJMIC), Vol. 16, No. 2, 2012

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.

Online publication date: Wed, 17-Dec-2014

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