Enabling Production of Algal Biofuels by Techno-Economic Optimization of Co-Product Suites - Kruger, Jacob S.; Wiatrowski, Matthew; Davis, Ryan E.; Dong, Tao; Knoshaug, Eric P.; Nagle, Nick J.; Laurens, Lieve M. L.; Pienkos, Philip T. (Frontiers in Chemical Engineering, 2022)
Recent techno-economic analysis (TEA) has underscored that for algal biofuels to be cost competitive with petroleum fuels, co-products are necessary to offset the cost of fuel production. The co-product suite must scale with fuel production while also maximizing value from the non-fuel precursor components. The co-product suite also depends on algal biomass composition, which is highly dynamic and depends on environmental conditions during cultivation. Intentional shifts in composition during cultivation are often associated with reduced biomass productivity, which can increase feedstock production costs for the algae-basedl biorefinery. The optimal algae-basedl biorefinery configuration is thus a function of many factors. We have found that comprehensive TEA, which requires the construction of process models with detailed mass and energy balances, along with a complete accounting of capital and operating expenditures for a commercial-scale production facility, provides invaluable insight into the viability of a proposed algal biorefinery configuration. This insight is reflected in improved viability for one algal biorefining approach that we have developed over the last ten years, namely, the Combined Algal Processing (CAP) approach. This approach fractionates algal biomass into carbohydrate-, lipid-, and protein-rich fractions, and tailors upgrading chemistry to the composition of each fraction. In particular, transitioning from valorization of only the lipids to a co-product suite from multiple components of high-carbohydrate algal biomass can reduce the minimum fuel selling price (MFSP) from more than $8/gallon of gasoline equivalent (GGE) to $2.50/GGE. This paper summarizes that progress and discusses several surprising implications in this optimization approach.