Design and Implementation of Solar based Maximum Power Point Tracking using Machine Learning

The photovoltaic-based applications are discussed in this study. For a photovoltaic (PV) system to produce the most power, an automated MPPT algorithm calibration and effective MPPT implementation are essential. In our proposed maximum power point tracker method system PV array’s global maximum power point is automatically determined using an Artificial Neural Network (ANN)-based strategy. A solar tracking system with batteries is subjected to this technique. Photovoltaic systems are appropriate for AI-based MPPT approaches. The function approximation of the MPPT problem in PV, the best approach and network architecture should be chosen for the performance of several training algorithms and network architectures is taken into consideration. Due to the nonlinear, dynamic nature of PV panels, soft computing technologies based on artificial neural networks (ANN) will be used for function approximation. PV panel modelling and a MATLAB- simulated ANN-based MPPT technique created the data set needed to train neural networks.