Maximum Power Point Tracking Method Based on Perturb and Observe Coupled with a Neural Network for Photovoltaic Systems Operating Under Fast Changing Environments

Abstract

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.

Keywords

• maximum power point tracking
• photovoltaic
• neural network
• perturbation and observation