Improved Maximum Power Point Tracking of Standalone Solar PV system for Faster and Accurate Convergence

Solar photovoltaic (PV) arrays exhibit a nonlinear relationship between power (P) and voltage (V) when exposed to consistent solar irradiation, typically resulting in a single maximum power point (MPP) on the Power - Voltage curve within the operational voltage range. However, varying weather conditions can lead to the appearance of multiple MPPs, complicating the task of pinpointing the optimal operating voltage for achieving absolute maximum power. To address this challenge, this research proposes an enhanced maximum power point tracking (MPPT) method that incorporates fuzzy logic. The aim is to achieve expedited and more precise convergence to the MPP, irrespective of stable or varying weather conditions. The results show that the improved tracking algorithm decreases the time to reach the MPP by 47% compared to traditional hill climbing algorithms. The study uses MATLAB/Simulink to mathematically model a photovoltaic array. The proposed method is simulated and compared with various commercially available MPPT techniques, including traditional hill-climbing methods. It uses simulated and empirical results to validate the enhanced efficacy of the method. Additionally, the paper discusses the development of an economical solar charge controller incorporating the advanced MPPT algorithm, emphasizing practical applications and improvements in real-world efficiency.