(119a) Biomass Feedstock Production and Provision: A System Level Optimization Approach

The success of biomass based sector depends critically on an efficient, cost-effective and sustainable biomass feedstock production system supporting the biorefinery. Spatially distributed collection of the low energy density feedstock demands a highly efficient system to ensure cost competitiveness. Further challenges arise as seasonal availability of energy crops must support year-round demand to operate refinery on a continuous basis. Consequently, an integrated system level analysis is necessary to coordinate various feedstock production related tasks. Such an analysis should incorporate not only planning level (long term) but also management and operational level (short term) aspects. This work presents the research conducted in developing a feedstock production optimization model as a step in developing such a framework. The breadth level optimization model incorporates different tasks such as harvesting, packing, storage, biomass handling and transportation that are essential for feedstock production. The objective is to determine the optimal configuration of the feedstock production system on a regional basis. The decision variables include the design/planning level decisions such as equipment selection and transportation mode selection, as well as the management level decisions such as daily farm management and transportation fleet scheduling. This leads to the formulation of a mixed integer linear programming (MILP) problem. An economic objective function is formulated and established techniques from mathematical programming are used to solve the computationally challenging problem. Other performance indicators such as energy consumption and greenhouse gas emissions are also tracked for comparison. The model has been applied for the case of switchgrass production as the energy crop in southern Illinois. The results show the farm size distribution has a major impact on the delivered cost, farm management activities as well as machine selection decisions. On-farm covered storage is observed to be the most preferred storage option. It is observed that integrated farm management as well as optimized harvesting schedule leads to significant cost savings, while improvements in packing and transportation technologies lead to greatest benefits to the system. The system level optimization model is then extended to explore the effect of optimizing individual stake-holder benefits. The overall goal of the model development work is to provide a decision support platform for the individual stake-holders such a farmers, storage elevators, transportation company, biorefinery as well as policy makers.