Optimal Design and Synthesis of Algal Biorefinery Processes for Biological Carbon Sequestration and Utilization with Zero Direct Greenhouse Gas Emissions: MINLP Model and Global Optimization Algorithm

We develop a novel superstructure of algal biorefinery processes for biological carbon sequestration and utilization, encompassing off-gas purification, algae cultivation, harvesting and dewatering, lipid extraction, remnant treatment, biogas utilization, and algal oil upgrading stages. Based on the superstructure, we propose a mixed-integer nonlinear programming (MINLP) model to minimize the unit carbon sequestration and utilization cost and apply a tailored branch-andrefine algorithm based on successive piecewise linear approximation to globally optimize the resulting nonconvex MINLP problem efficiently. The minimum unit carbon sequestration and utilization cost of $1.48/ton of CO2 is obtained when the diesel price is $3.91/gal and feed gas is delivered to the biorefinery only during daytime at a flow rate of 5003.46 ktons/year corresponding to the carbon dioxide emission rate of a 600 MW coal-fired power plant. The resulting algal biorefinery design reuses all the CO2 produced within the process, leading to zero direct greenhouse gas emission of the entire process.