Maximum Power Point Tracking of PV Grids Using Deep Learning

In this paper, we develop a deep learning model using back propagation neural network (BPNN) that helps to obtain maximum power point. This aims maximise the output from solar grids when panels are connected with boost converter under different variable load conditions. BPNN-DL enables prediction of reference voltage at weather conditions for severing various ensures stable voltage. The proposed is tested estimate robustness modules internal/external interferences. results simulation show method achieves each panel compared existing methods in terms regression analysis on training, testing, and validation.