Application of Neural Networks Technique in Renewable Energy Systems

Abstract

Artificial Intelligence (AI) techniques are increasingly used in various area due to their capability of handling complex systems specificities. Among the techniques of AI, Artificial Neural Networks (ANN) technique plays an important role. This technique is used in this work to perform important tasks encountered in Photovoltaic systems and in Wind Energy Systems: a) Maximum Power Point Tracking (MPPT) of Photovoltaic Generators, b) and wind energy resource assessment. It is shown how a neural network technique can be used to design an MPPT controller for photovoltaic generators, enabling to improve their efficiency, and how it is possible to assess the available and recoverable wind energy potential of a site, by means of finding an adequate distribution law of the wind speeds based on a neural model. The proposed methods are illustrated by simulation results which exhibit the advantages of using ANN techniques in Renewable Energy Systems.