Optimal Estimation of Harmonics in Power System using Intelligent Techniques

Fouad R. Zaro, Sami El Ferik, and Mohammad A. Abido


Harmonics Estimation, Least square method, Real coded genetic algorithm, Particle swarm optimization, Separable least square


This paper presents a new algorithm for harmonic estimation in power systems. It utilizes separable least squares (SLS) technique to estimate the magnitude and phase angle of the harmonics by analyzing the waveform. As well as hybrid techniques have been utilized in this paper to estimate harmonics, real coded genetic algorithm (RCGA) and particle swarm optimization (PSO) utilized to estimate the phase of the harmonics, alongside a least square (LS) method used to estimate harmonics amplitude. The three techniques are analyzed and the results are compared in terms of percentage of error and processing time for finding suitable efficient technique to estimate harmonics.

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