Modeling and Optimization of Biological Desulfurization from Sugarcane-Residue Biogas via the THIOPAQ^® Process

Biogas is a promising source of renewable energy, particularly when produced from agro-industrial residues such as sugarcane waste. However, its utilization requires efficient H₂S removal to reduce equipment corrosion, toxicity, and catalyst deactivation. This study provides a comprehensive simulation and economic optimization of the THIOPAQ^® process for desulfurization of biogas from sugarcane residues. The process was simulated in Aspen Plus v.15 with the ENRTL-RK thermodynamic model. Three biogas compositions derived from sugarcane straw, bagasse, and filter cake were evaluated using data obtained from a local biogas plant. The process was optimized using a particle swarm optimization algorithm. In all optimization cases, the resulting biogas had an H₂S concentration of 5.00 mg/Nm³, corresponding to the upper limit imposed by the optimization model constraints. Bagasse-derived biogas had the lowest process cost (621.66 × 10³ USD/yr), followed by filter cake-derived biogas (651.85 × 10³ USD/yr) and straw-derived biogas (680.83 × 10³ USD/yr). The optimization results indicated that higher CO₂ and H₂S concentrations in the biogas and NaOH flow rates in the desulfurization process are associated with increased operating costs. Overall, the combined simulation and optimization strategy provides an effective approach to evaluate and improve the THIOPAQ^® process for biogas desulfurization from different sugarcane residues.