Hybrid bat-grasshopper and bat-modified multiverse optimization for solar photovoltaics maximum power generation

Abstract

A hybrid BAT with Grasshopper (GH) algorithm and BAT-MMVO (Modified Multiverse Optimization) are exhibited for harvesting maximum power from photovoltaics (PV) using the Xilinx System Generator (XSG) implanted controller. Using a hybrid BAT-GH and BAT-MMVO algorithm, the proposed implanted controller finds the best switching pulse for the boost converter. The implanted controller, switching schemes, and the Photovoltaic (PV) supported boost converter were built using the XSG domain. The hardware implementation of the best two cases were done using a microcontroller in a smaller scale. This aims to gather the maximum amount of power by a PV array for solar irradiation and cell temperature under varied environmental situations. The PV structure in the XSG domain is used to construct the system model for prediction. The major emphasis of this work is to keep the difference of actual power and reference power as minimum. Finally, the implanted controller's performance is compared to that of other existing hybrid controllers. The performance of the proposed algorithm is found to yield good results in terms of power extraction. The theoretical and experimental results are presented. The computational efforts for the implementation of the algorithm are found to be less complex when compared to other existing methods.