A novel combinatorial hybrid SFL–PS algorithm based neural network with perturb and observe for the MPPT controller of a hybrid PV-storage system

In recent years, various control methods have been proposed for maximum power point tracking (MPPT) of photovoltaic (PV) plants. Different MPPT PV systems in the literature evaluated terms energy efficiency, conversion, dynamic performance and reliability different environmental conditions. Among methods, Artificial Neural Network (ANN) is one best due to its ability noise rejection no need prior information physical parameters. For implementing ANN-based two input variables including temperature irradiance an output variable containing voltage MPP are taken into account. this paper, a hybrid shuffled frog leaping pattern search (HSFL–PS) algorithm used optimizing grid-tied system. The P&O approach cycle procedure starts precise scheme after training ANN specification neuron weights. MATLAB/Simulink utilized simulation tests confirm offered method. outcomes from validate improved recommended comparison with conventional fast response 011 sec.