Abstract
In this paper, a new recursive adaptive filter based on a fast Gauss-Newton method has been proposed for the estimation of fundamental and harmonics for time-varying voltage and current signals in an electrical power network. The presented algorithm is based on the minimisation of a weighted forgetting factor-based error cost function by the use of recursive Gauss-Newton method. Further a Hessian matrix approximation is used to produce a fast recursive algorithm, which is immune to random noise, waveform distortion and increases the speed of convergence and accuracy. The algorithm models the typical time-varying signals and damped sinusoids and decaying dc components and the accompanied distortions due to harmonics and random noise in a manner that will be suitable for real-time harmonic estimation, which is a very important requirement in power quality analysis.
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