NEURO-FUZZY STRATEGIES FOR PREDICTION AND MANAGEMENT OF HYBRID PV-PEMFC BATTERIES SYSTEMS

Ntumba Marc-Alain Mutombo1; Freddie L. Inambao2*

Abstract: The development of hybrid renewable energy systems and the resulting non-linear behavior has led to the rise of artificial intelligence techniques to deal with modelling, prediction, management and control of energy conversion from various sources in the systems. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) for the management and control of the energy flow of a hybrid photovoltaic-fuel cells-battery system is implemented. The ANFIS structure obtained was compared to an artificial neural network (ANN). The results show that ANN provided good prediction in the management of the energy flow of the hybrid system but better results were obtained with ANFIS.  
Keywords: Photovoltaic, fuel cell, batteries, energy management, artificial neural network, adaptive neuro–fuzzy interference.