A harmonic parameter estimation method based on Particle Swarm Optimizer with Natural Selection

This paper presents a novel method to solve the estimation of the amplitudes and phases of different harmonic components contained in a power electrical signal, based on Particle Swarm Optimizer with Natural Selection (PSONS). PSONS is an Evolutionary Algorithm (EA) with the natural selection mechanism. The proposed method utilizes PSONS to estimate the phases of the harmonics and a standard least-square (LS) method to estimate the amplitudes alternately and recursively to minimize the value of the predefined fitness function which aims to search for the best phases and amplitudes. Simulation studies have been carried out to verify the feasibility of the proposed method. The results demonstrates that PSONS achieves high accuracy in harmonic estimation and outperforms the conventional PSO and GA in estimation accuracy and the conventional PSO in convergence speed.