Harmonics Phasor Estimation by Using Sparse Based Sigmoid Least Mean Mixed Norm (SLMMN) Approach

This paper centres around the precise fundamental frequency and phasor estimation of power signals within the sight of harmonics and inter-harmonics unsettling influences based on an adaptive filter with Least Mean Mixed Norm (LMMN) framework and a sigmoid cost function. Moreover, the underlying sparse behaviour of the adaptive filter has been exploited through penalty terms like zero attracting and reweighted zero attracting to significantly improve the preciseness and the convergence of the estimation. The outcomes of some test cases are presented which focusses on the performance of the algorithm to settle the broad and selective issues of smart grid and micro grids