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Our main objective is to evaluate the performance of a new method to optimize the energy management of a production system composed of six cogeneration units using artificial intelligence. The optimization criterion is economic and environmental in order to minimize the total fuel cost, as well as the reduction of polluting gas emissions such as COx, NOx and SOx. First, a statistical model has been developed to determine the power that the cogeneration units can provide. Then, an economic model of operation was developed: fuel consumption and pollutant gas emissions as a function of the power produced. Finally, we studied the energy optimization of the system using genetic algorithms (GA), and contribute to the research on improving the efficiency of the studied power system. The GA has a better optimization performance, it can easily choose satisfactory solutions according to the optimization objectives, and compensate for these defects using its own characteristics. These characteristics make GA have outstanding advantages in iterative optimization. The robustness of the proposed algorithm is validated by testing six cogeneration units, and the obtained simulation results of the proposed system prove the value and effectiveness of GA for efficiency improvement as well as operating cost minimization.

Our objective through this work is to purify the biogas produced by a methanisation process in order to be valorized in a cogeneration unit. The studied biogas is mainly composed of methane 60% and carbon dioxide 39%. The treatment will increase the quality of the biogas by decreasing the percentage of CO2, in order to improve the energetic properties of the gas mixture (PCI). Several biogas purification and bio-methane production processes are commercialized. The choice of the technical and economic optimum is strongly linked to the quality and quantity of biogas to be purified, the quality of the desired bio-methane, depends on the type of methanisation, the nature and regularity of the substrate supply, but also on the local conditions of implantation. In this part of our research project, we are interested in the study, dimensioning and modeling of a CO2 capture unit by chemical absorption, constituted by a packed column. The solvent used is the secondary amines in mixture with the primary amines.

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