Maximum Power Point Tracking Method Based on Perturb and Observe Coupled with a Neural Network for Photovoltaic Systems Operating Under Fast Changing Environments
Yesid Briceno-Fajardo, Gustavo Cerda-Villafana, Sergio Ledesma-Orozco
The output power of Photovoltaic (PV) arrays presents a
nonlinear behavior. Its maximum power point varies with the
cell’s temperature and solar radiation. It is due to this situation
that Maximum Power Point Tracking (MPPT) methods have
been proposed and used in order to maximize the PV array
output power. This paper presents an artificial neural network
(ANN) combined with the classic Perturbation and Observation
(P&O) algorithm to accelerate the search of such Maximum
Power Point. Simulations generated using Matlab/Simulink
show the improvement compared to the P&O alone and the
hardware implementation, using a 16-bit microcontroller
corroborates these findings. Full Text
| 
