A New Optimization Method for Improving the Performance of Photovoltaic System

As the leading renewable energy source, solar energy is ideally suited for combating global warming. Solar systems in the form of photovoltaic (PV) generation strongly depend on their operating conditions in terms of techno-economic effectiveness. The partial shading (PS) environment, which results in significant power losses, exacerbates the difficulty of nonlinear control. High tracking and settling time, oscillations at global maxima (GM), and local maxima (LM) trapping under PS conditions are all apparent shortcomings of metaheuristics-based maximum power point tracking (MPPT) control systems. This research introduces a novel meta-heuristic technique based on MPPT control of PV systems called the Arithmetic Optimization Algorithm (AOA) technique. The proposed method enhances the performance of photovoltaic (PV) systems by permitting faster, more precise tracking and extremely low oscillations. The simulation results demonstrate that the proposed AOA control method is notable for its ease of implementation, robustness, and steady-state power tracking efficiency of up to 99.643.