An intelligent MPPT approach based on neural-network voltage estimator and fuzzy controller, applied to a stand-alone PV system

This paper presents an intelligent maximum power point tracking (MPPT) method for a stand-alone photovoltaic (PV) system using artificial neural networks (ANN) modelling and a fuzzy logic controller (FLC). The ANN is trained for various conditions of solar irradiance and temperature to estimate the MPP voltage. This voltage is then used by the FLC as a reference voltage to generate the appropriate control signal for the DC-DC converter. The proposed technique is implemented in Matlab/Simulink and compared with the conventional method of incremental conductance (IncCond). Simulation results show a good performance of the ANN based fuzzy MPPT controller.