Optimal Estimation of Harmonic Components Using ISFLA

In this paper a novel method based on evolutionary algorithms is presented to estimate the harmonic components. In general, the optimization of the harmonic estimation process is a multi-component problem, in which evaluation of the phase and harmonic frequency is the nonlinear part of the problem and is solved based on the mathematical and evolutionary methods; while estimation of amplitude of the harmonic component is a linear issue that is performed by combining the least squares method with the aforementioned approaches. In this paper, firstly, the optimal estimation of integer harmonic components has been introduced based on the improved shuffled frog leaping algorithm (ISFLA) in the presence of two types of noise. The obtained results present the lower error of the proposed method than to IGHS, FBF PSO, GA and FFT methods. Thereafter, the effectiveness of the presented algorithm in optimal estimation of frequency, phase, and amplitude of the integer and non-integer harmonics are investigated. The optimization of the estimation of various harmonic components under different conditions using ISFLA leads to an improvement in the assessment of power quality in power systems especially in the distribution networks, considering a lot of the nonlinear loads and harmonic resources connected to the network.