Liquid fuels produced from plant biomass could play a significant role in meeting our energy needs. Bio-fuels produce less greenhouse emissions than fossil fuels (1). In addition, fuels from lignocelluloses are likely to be substantially more efficient than corn derived fuels (2). The development of the infrastructure for producing fuels from biomass will have a substantial impact on the overall adoption of biomass based liquid fuels.
An important consideration in the design of a biorefiney network is the availability of feedstock. This factor is a driving force for decisions such as feedstock form, farmgate location, biorefinery processing locations, and biorefinery scale. With lignocellulosic biomass in particular, the performance of the network is subject to wide variability in crop yields. Thus, accurate predictions of the spatial variation in feedstock yields are of interest. This work integrates perennial feedstock yield modeling based on time dependent weather and environmental variables with MILP algorithms to examine the performance of various biorefinery configurations and their resilience to weather risk. The optimization model includes decisions such as selection of farmgate locations, processing scale, and scheduling of feedstock planting, harvesting, and biomass processing.
1.Huber G, Iborra S, Corma A. Synthesis of Transportation Fuels from Biomass: Chemistry, Catalysts, and Engineering. Chemical Reviews. September 2006.
2. Nano-sieve offers alternative to conventional separation techniques used in the petrochemical industry. Membrane Technology. May 2008.