Multi-objective optimization of SNG production from microalgae through hydrothermal gasification

The conversion of microalgae biomass into biofuels is a quite well explored field of research. Due to high photosynthetic efficiency, microalgae are considered as a potential feedstock for next-generations biofuel conversion processes. This paper addresses the thermochemical conversion of highly diluted microalgae feedstock into synthetic natural gas (SNG) through supercritical hydrothermal gasification. The complete conversion chain is modeled including the cultivation phase, settling ponds, centrifuges, catalytic hydrothermal gasification with salt separation unit and SNG purification system. Thermodynamic, economic and environmental models are considered for each process step, in order to solve a Mixed Integer Non Linear Programming (MINLP) optimization problem. The problem is solved by applying a two steps decomposition approach, using Multi Objective Evolutionary Algorithm with Mixed Integer Linear Programming (MILP). It is finally demonstrated that coupling microalgae cultivation systems with hydrothermal gasification (HTG) and waste energy recovery utilities leads to high energy/exergy efficiencies, emissions reduction and globally better sustainable processes.