Growth of a biomass-to-biofuels industry has the potential to reduce oil imports, support agriculture and forestry growth, foster a domestic biorefinery industry, and reduce greenhouse gas emissions compared to gasoline. Successful development of biofuels involves Process Systems Engineering challenges at various scales, including elucidation of complex chemical systems for upgrading biomass in terms of mechanisms, kinetics and thermochemistry, design of novel reactors and reactor networks, synthesis and optimization of novel process flow sheets, and supply chain optimization at the enterprise level. None of these aspects exist in isolation; each choice impacts the others and has an important role in the overall economic potential. The aim of this thesis has been to approach these multi-scale challenges by developing optimization models for biofuel supply chain and product design problems, specifically mixed integer linear programs.
The biofuel supply chain optimization problems were formulated to determine economical and environmentally efficient biomass processing facility locations and capacities, simultaneously with biomass harvest and distribution. Focus was put on the production of biofuels in the Midwestern United States from grain, agricultural residues, energy crops and wood resources, and the feasibility of meeting governmental biofuel mandates in 2015. The product design problem investigated was for the production of blended gasoline with biomass-derived components. The strategy consists of i) constructing an exhaustive network of reactions consistent with an input set of chemistry rules and ii) using the network information to formulate and solve an optimization problem that yields an optimal product distribution and the sequence of reactions that synthesize them. This was applied to identify potential renewable oxygenates and hydrocarbons obtained from heterogeneous catalysis of biomass that can be blended with gasoline to satisfy ASTM specifications.