A new MPPT design using arithmetic optimization algorithm for PV energy storage systems operating under partial shading conditions

Arithmetic optimization is a new metaheuristic algorithm that has shown great strength and good performance in handling and solving complex problems. In photovoltaic systems, and especially in the case of a partial shading condition, the power-voltage curve of the photovoltaic array exhibits multiple peaks of which only one is global, making the tracking of the global maximum power point more complex, and thus requiring a powerful metaheuristic maximum power point tracking algorithm. Therefore, to address this problem, this paper introduces a new design of an arithmetic optimization based maximum power point tracking controller for battery charging schemes through photovoltaic systems operating under partial shading conditions. The main objective of the arithmetic optimization based maximum power point tracking proposed here is to maximize the power extracted from the photovoltaic array under all types of climatic conditions in order to efficiently charge the battery through the maximization of its charging current. The feasibility and effectiveness of the proposed arithmetic optimization based maximum power point tracking method are verified through MATLAB simulations and processor-in-the-loop test using the low-cost STM32F429 embedded board. Moreover, a comparison of its performance with existing maximum power point tracking methods such as, hybrid of grey wolf optimization and particle swarm optimization, particle swarm optimization and perturb and observe is also carried out while considering real climatic conditions as well as uniform and partial shading scenarios. Simulation and processorin-the-loop results have demonstrated the good performance of the proposed method in terms of battery charging efficiency as well as the ability to track the global maximum power point with an efficiency of 99.99% and a tracking time of 0.85 s.