Performance of MPPT in photovoltaic systems using GA-ANN optimization scheme

Abstract

Researchers all over the world are currently moving toward using solar energy resulting from large energy demand and sources of energy as well as the environmental problems, such as dynamic weather conditions. The control of maximum power point tracking (MPPT) meteorological conditions is an essential portion of improving solar power systems. In this paper, we introduce an elastic controller depend on artificial neural network for regulating the MPPT. This controller is employed to the buck–boost DC-to-DC converter using the MATLAB/Simulink software program. This paper proposes a design that maximizes the performance of GA-ANN scheme, and compared with ANN scheme, efficiency of PV module is shown as well as the saving power for both schemes. The results show that GA-ANN has performance about 45% over ANN scheme.