Optimisation de l'ensemble convertisseur-générateur-commande intégré à un système de micro-cogénération thermo-mécano-électrique

The work of this thesis aims to study a system of micro-cogeneration innovative structure powered by a free piston Stirling engine "double effect." This system is characterized by a strong coupling between the thermo-mechanical parts and the mechanico-electrical part, provided by a linear induction generator tubular solid mover. In fact, the compression piston also acts as the mover of the electrical machine. The non-linear thermo-mechanical model of the Stirling engine "double effect" allowed to identify the optimal mode of coupling between the engine and the electric generator. Then, the study of the electric generating portion focused on numerical and experimental validation of the electromagnetic model by solving Maxwell's equations in magneto, the identification of parameters of the linear machine combining theoretical methods with experimental tests and finally on the experimental embodiment of the vector field oriented control to control said load system in oscillatory. Then the chain of electronic power converters that connects the generator to the home network system has been studied in order to adapt to the constraints of power generation network. Then, a "virtual test bed" of the overall system was made using Matlab / Simulink so as to implement the non-linear thermo-mechanical model of the Stirling engine "double effect", the dynamic model of the generator tubular linear induction, the model of static converters and related commands : PID position control, vector oriented in flow control and PFC control. The "virtual test bed" was used to validate the coupling models, the performance of controls and the stable operation of the system in oscillatory mode. Then, under the assumption of a command / control of the perfect system, a comprehensive model for the "average instantaneous values" called "energy hub" was established. This model is fast execution, consistent with a "multi-objective" optimization tool "multivariate". Finally, the study of optimal design of the complete electromechanical chain system based on genetic algorithm NSGA-II gave several significant solutions to maximize the electric power fed into the grid and to minimize the total cost of the chain . Time optimal efficiency of the system was also considered at the end of this thesis.