A Novel MPPT Algorithm based on Aquila Optimizer under PSC and Implementation using Raspberry

Abstract

In this paper, we propose an Aquila Optimizer (AO) algorithm specific to photovoltaic (PV) energy storage conversion system for the global maximum power point tracking (GMPPT) of a battery in partial shade conditions (PSC). Several simulation experiments were run in the Simulink 2021a environment to evaluate the performance of the suggested MPPT control. The simulation results show the highest accuracy, speed and stability of the suggested AO algorithm under PSC. After being integrated on a Raspberry Pi 4 Model B embedded board, the embedded software produced underwent a validation and verification procedure.