Title :
A hybrid PSO and GSA-based maximum power point tracking algorithm for PV systems
Author :
Dhas, B. Goldvin Sugirtha ; Deepa, S.N.
Author_Institution :
Dept. of Electr. & Electron. Eng., Anna Univ., Coimbatore, India
Abstract :
This paper proposes a hybridization of particle swarm optimization (PSO) and gravitational search algorithm (GSA) for maximum power point tracking (MPPT) in photovoltaic (PV) system. The main concept is to integrate the exploitation ability of PSO with the exploration ability of GSA to synthesize algorithms´ strength. In this method, the oscillation is reduced once the maximum power point (MPP) is located. To evaluate the effectiveness of the proposed methodology, MATLAB-SIMULINK simulations are carried out under step changes in irradiance of the PV array. The simulation results show the hybrid algorithm possesses a better capability to escape from local maxima with faster convergence than conventional PSO and GSA.
Keywords :
maximum power point trackers; particle swarm optimisation; photovoltaic power systems; search problems; GSA exploration ability; MATLAB-SIMULINK simulation; PSO exploitation ability; gravitational search algorithm; hybrid PSO-GSA algorithm; maximum power point tracking algorithm; oscillation reduction; particle swarm optimization; photovoltaic power systems; Arrays; Fluctuations; Mathematical model; Maximum power point trackers; Oscillators; Photovoltaic systems; Maximum power point tracking (MPPT); boost converter; gravitational search algorithm (GSA); particle swarm optimization (PSO); photovoltaic (PV) system;
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on
Conference_Location :
Enathi
Print_ISBN :
978-1-4799-1594-1
DOI :
10.1109/ICCIC.2013.6724181