Implementation of Fuzzy and Neural Networks-Based MPPT Techniques on Solar PV System

Increasing the efficiency of energy harvesting in photovoltaic (PV) systems is a key topic of research for the long-term usage of solar energy. To achieve this, several techniques, including the Maximum Power Point Tracking (MPPT) algorithms, have been created. These include MPPT approaches based on Artificial Neural Networks (ANN) and Fuzzy Logic (FL), which have attracted much interest due to their ability to adapt to changing environmental circumstances and enhance the overall performance of PV systems. This presentation discusses the Implementation of FL and ANN-based MPPT techniques in solar PV systems. Both methods make an effort to adjust the operating voltage and current to track the PV array's maximum power point (MPP). However, underlying ideologies and implementation methods, however, vary.