Fine-tuning genetic algorithm for photovoltaic-proton exchange membrane fuel cell hybrid system optimization

Abstract

European cities have established programs integrating the energy, transport and ICT sectors in order to deliver more efficient services for their populations. The paper tackles the study of feasibility to implement fuzzy logic control into an energetic hybrid system and to optimize the membership functions of the fuzzy logic controller for the Photovoltaic-Proton Exchange Membrane Fuel Cell hybrid system using genetic algorithm (GA). The paper deals with a fuzzy logic control strategy objective to produce electrical energy according to the demand, prone to the constraints and the dynamics of the physical load and intermittence of the energetic resource, by distributing the energy demand between the photovoltaic field and the Proton Exchange Membrane Fuel Cell system. Photovoltaic-Proton Exchange Membrane Fuel Cell is described in detail as well as system configuration and components' parameters. The second section devotes to demonstrating the design process of fuzzy logic control for Photovoltaic-Proton Exchange Membrane Fuel Cell hybrid System. Finally, the optimal control problem is addressed and genetic algorithm is introduced to help find a set of optimum parameters in the fuzzy logic controller, best results are obtained and good optimization of the hybrid system is highlighted.