Modeling and analysis of a hybrid-energy system using fuzzy cognitive maps

A hybrid energy system is an excellent solution to the problem of not being able to meet the power demand using a single energy source. Such a system incorporates a combination of one or more renewable energy source (RES) such as solar photovoltaic, wind-energy, geothermal, and could also have a conventional generator for backup. This paper discusses different system components of a hybrid energy system and develops a theoretical model to find an acceptable combination of energy components. A theoretical model of a hybrid energy system, using Fuzzy Cognitive Maps (FCMs) and learning algorithms, is presented. FCMs perform well even with missing data and despite nonlinearities, which such systems usually have. The simulation results verified the effectiveness and reliability of the proposed hybrid energy system.