Neural Fuzzy Networks for Optimal MPPT Control in PV Powered AC Loads

Abstract

Renewable energies are being more popular and viewed in some cases as a viable alternative to conventional sources of energy. A great number of renewable based applications have been developed to satisfy energy demand in different fields. This paper deals with the application of artificial intelligence in photovoltaic powered AC loads. Neural fuzzy networks are applied in order to optimize the energy produced by photovoltaic generators (PVG) and successfully improving the maximum power point tracking (MPPT) control. Simulation and experimental results will be given to demonstrate the efficiency and performance of the proposed control system.