Artificial Neural Networks Based Power Management Scheme with Enhanced Stability for a Solar Panel/Wind Turbine Generator/Fuel cell/Battery/ Power Supply Designed for Industrial Loads

Abstract

Renewable energy systems are becoming more prevalent in today's society, as opposed to conventional energy systems. PV systems, in particular, and wind energy conversion systems (WECS) are playing an increasingly important role in meeting the world's energy demands. The efficiency of these types of renewable energy systems is being attempted to be enhanced through the use of various ways. Intelligent system designs, as opposed to conventional ways, appear to be more beneficial in terms of increasing the efficiency of renewable energy sources. Artificial neural networks (ANNs) have a wide range of applications in the Modelling, simulation, and control of renewable energy systems, to name a few. ANNs are simple to utilize and deploy in the development of renewable energy system designs. Solar PV, wind energy conversion systems, and hybrid renewable energy systems, which combine PV and WECS, are discussed in this research using artificial neural networks. The use of neural network structures in these types of systems has been demonstrated to be beneficial.