Application of Artificial Intelligence for the Supervision of a Multi-source System

Renewable energy sources offer unlimited potential for clean electricity production and their usage is rapidly growing. Hybrid energy systems incorporate various sources, requiring efficient control and supervision mechanisms. In this regard, this study proposes an artificial intelligence-based energy management system, utilizing fuzzy logic control, for a hybrid wind/photovoltaic system with battery storage. The proposed approach adjusts the system output to supply the load demand, offering benefits of precise control of the battery's state of charge (SOC) across five states. This is a marked improvement over traditional management systems that rely on two SOC states, namely SOCmin-SOCmax.