Determining optimal size reduction and densification for biomass feedstock using the BioFeed optimization model

The benefi ts of particle size reduction and mechanical densifi cation of biomass feedstock for storage, transportation, and handling must be assessed in relation to the systemic costs and energy consumption incurred due to these operations. The goal of this work was to determine the optimal levels of size reduction and densifi cation through a combination of modeling and experimental studies. Size reduction and densifi cation data for Miscanthus and switchgrass were generated using a two-stage grinding process and the energy requirement and bulk densities for the particle sizes between 1 mm and 25.4 mm were determined. Increase in bulk density through compression by a pressure of 1.2 MPa was also measured. These data were used within BioFeed, a system-level optimization model, to simulate scenarios capturing the possibilities of performing size reduction and densifi cation at various stages of the supply chain. Simulation results assuming size reduction at farms showed that the optimal particle size range for both Miscanthus and switchgrass was 4–6 mm, with the optimal costs of $54.65 Mg–1 and $60.77 Mg–1 for Miscanthus and switchgrass, respectively. Higher hammer mill throughput and lower storage costs strongly impacted the total costs for different particle sizes. Size reduction and densifi cation of biomass at the county-specifi c centralized storage and pre-processing facilities could reduce the costs by as much as $6.34 Mg–1 for Miscanthus and $20.13 Mg–1 for switchgrass over the base case. These differences provided the upper bound on the investments that could be made to set-up and operate such systems. © 2014 Society of Chemical Industry and John Wiley & Sons, Ltd Supporting information may be found in the online version of this article.