Comparative Analysis of Different Maximum Power Point Tracking Algorithms for Photovoltaic System
This paper presents a comprehensive comparative analysis of Golden Section Search (GSS), Artificial Neural Network (ANN), and Adaptive Neuro Fuzzy Inference System (ANFIS), alongside well-known Perturb and Observe and Incremental Conductance (INC) Maximum Power Point Tracking (MPPT) algorithms for Photovoltaic (PV) system. The methodology involves theoretical development, simulation, and real-time experimentation using Matlab/Simulink and the Humusoft MF 634 data-acquisition card. Real-time experiments validate algorithm effectiveness under real-world conditions, facilitated by precise control mechanisms using Taraz's power electronics converter modules. The results contribute to ongoing efforts in optimizing MPPT technology and advancing the efficiency of PV systems for renewable energy generation.