PhD Final Defense – Maria Florencia Bianco

Advancing Biorefinery Deployment Through End-to-End Spatial Modeling of Facility Siting and Biomass Supply Strategies

Advisor: Professor Jeremy S. Guest

Abstract

The expansion of biomass-derived fuels and chemicals requires coordinated scale up of feedstock cultivation, harvesting, storage, transportation, and processing. Central to this expansion are biorefineries, whose substantial capital requirements call for careful decisions about where they should be located, how large they should be, and how to secure sufficient feedstock for year-round operation. These decisions are interconnected: regional biomass availability influences facility location and scale, while harvesting, storage, and procurement strategies affect feedstock requirements and production costs. Evaluating these connections is necessary to understand the economic feasibility and environmental implications of biorefinery deployment. This dissertation develops integrated, open-source modeling frameworks that connect feedstock production and supply with biorefinery performance to support these engineering decisions.

This dissertation is organized into three contributions: (Chapter 3) developing a modeling framework to link feedstock supply with existing processing infrastructure; (Chapter 4) developing a spatial optimization framework to coordinate biorefinery deployment across scales; and (Chapter 5) developing an integrated supply-chain and processing framework to plan seasonal feedstock supply. In our first study, spatial analysis of switchgrass- and miscanthus-derived ethanol supplying alcohol-to-jet production at existing petroleum refineries was used to evaluate sustainable aviation fuel (SAF) production across 1,000 candidate locations in the rainfed United States. The analysis identified tradeoffs between minimum selling price and carbon intensity (CI), demonstrating that the lowest-cost locations did not necessarily provide the greatest emissions reductions. Both feedstocks yielded lower modeled CI than conventional aviation fuel across the evaluated conditions and compared favorably with reported values for corn-derived SAF, although production costs remained a barrier to deployment. However, ethanol transportation contributed

relatively little to SAF costs, supporting deployment strategies that connect favorable biomass production regions with existing petroleum-refinery infrastructure.

In our second study, spatial optimization was combined with surrogate models of biomass logistics and refinery economics to evaluate the deployment of facilities producing fuels and chemicals at different scales. The results demonstrated the importance of accounting for shared biomass resources and differences in facility feedstock requirements. Smaller facilities offered greater siting flexibility, while larger facilities more strongly influenced regional biomass demand. Alternative collection-area representations produced relatively small differences in estimated costs but affected facility locations and spatial configurations. These findings support coordinated deployment planning across production scales and show that spatial assumptions can affect facility placement even when their effects on estimated costs are small.

Finally, in our third study, biomass supply-chain modeling was connected to ethanol process simulation to evaluate how miscanthus harvesting, storage, and procurement decisions affect production costs and contracted-feedstock reliability under uncertainty. Harvest timing, physical biomass losses, and yield variability influenced biomass requirements and supply strategies, and the lowest-cost strategy did not necessarily provide the desired reliability. Storage-related composition changes and dispatch rules generally had smaller economic effects under the conditions evaluated. Together, these findings demonstrate the importance of evaluating cost–reliability tradeoffs while selecting modeling detail according to the planning question.

Together, these contributions provide tools and insights for evaluating biorefinery deployment across locations, production scales, and biomass supply strategies. By connecting planning decisions to economic, environmental, and supply reliability outcomes, this work supports the engineering design and assessment of biomass-derived fuel and chemical production systems.