A hybrid PSO and GSA-based maximum power point tracking algorithm for PV systems
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 al...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | 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. |
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DOI: | 10.1109/ICCIC.2013.6724181 |