Neuro-fuzzy structure applied in maximum power point tracking in photovoltaic panels

This work proposes an adaptative neuro-fuzzy inference system (ANFIS) method to model the behavior of solar photovoltaic (PV) module. The performance of the solar PV module is greatly influenced by various environmental factors and it is therefore necessary to operate the PV module at its optimal point ensuring that maximum power is extracted from the PV source. Several fixed step and variable step maximum power point tracking (MPPT) algorithms have been proposed in the literature. This paper presents a simple and fast MPPT method based on a structure that combines the agility of neuro-fuzzy system which a self-tuning and the precision of the perturb and observe (online method) (P&O), providing reduced oscillation, this way improving the power control efficiency.