Abstract
This work is concerned with process design and synthesis of an algal biorefinery for biological carbon sequestration and utilization under both economic and environmental criteria. We develop a superstructure of an algal biorefinery that consists of 11 processing sections and a plethora of state-of-the-art technology pathways, resulting in 7,800 processing routes in total. Based on the superstructure, a multi-objective mixed-integer nonlinear programming (MINLP) model is proposed to simultaneously minimize the unit carbon sequestration and utilization cost and unit global warming potential. Both unit objective functions are associated with one ton of carbon dioxide sequestered. In order to enhance the computation efficiency of solving the nonconvex MINLP, we propose a global optimization strategy that integrates a branch-and- refine algorithm based on successive piecewise linear approximations and an exact parametric algorithm based on Newton’s method. The global optimal solutions of this bi-criteria MINLP problem constitute a Pareto-optimal curve that reveals the trade-offs between the two objective functions. All of the optimal points on the Pareto-optimal curve select an open pond, poly-electrolyte flocculation, pressure filtration, a storage tank, butanol extraction, sodium-methoxide-catalyzed transesterification, and anaerobic digestion. The lowest unit carbon sequestration and utilization cost obtained is 1.64 $/t CO2, corresponding to a unit GWP of 412.90 kg CO2-eq/t CO2.
