A hybrid least squares-clonal selection based algorithm for harmonics estimation - Moravej, Zahra; Enayati, Javad (International transactions on electrical energy systems, 2014)
SUMMARY This paper presents a new algorithm for harmonics estimation in power systems. Because of the nonlinearity of phases of sinusoids, the estimation of harmonic parameters is a nonlinear problem. However, nonlinear solving for amplitude estimation decreases speed of convergence. Thereby, hybrid methods decompose the harmonics estimation problem into two problems, linear for amplitude and nonlinear for phase. The objective of this paper is to introduce an accurate approach for harmonic parameters estimation. This approach is based on a stochastic search method, that is, clonal selection, to estimate the phases and a linear estimator, that is, least squares (LS), to estimate the amplitudes. This paper also indicates high accuracy of proposed algorithm in comparison with discrete Fourier transform and LS–Adaline (hybrid of LS and Adaline neural network) methods, especially in multiple frequency and highly noisy situations. Performance of the algorithm in noise rejecting even in interharmonics presence is shown by extracted simulation results of MATLAB (MathWorks Inc., Natick, MA, USA). Copyright © 2012 John Wiley & Sons, Ltd.