Techno-Economic Feasibility Analysis of Sustainable Bioenergy Feedstock Production Using Optimization and Simulation Models

Sunday, October 16, 2011
Exhibit Hall B (Minneapolis Convention Center)
Yogendra Shastri, Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Energy Biosciences Institute, Urbana, IL

Biomass feedstock production and provision are important components of the biomass based energy sector. Low
energy density, seasonal availability and distributed supply create unique challenges that need to be
addressed effectively. Multiple inter-dependent operations as well as novel technologies make the
determination of the optimal system configuration non-trivial. It must also be ensured that the feedstock
production system is sustainable and resilient. Systems theory provides an ideal platform to address these
challenges by enabling a systematic analysis using a computational and informational science platform. This
work conducts such an analysis of the feedstock production system using systems theory based tools such as
optimization and simulation. An optimization based decision making framework named BioFeed has been developed
that optimizes various feedstock production operations as a single system. A unique feature of this mixed
integer linear programming (MILP) model is the integration of the design as well as operational decisions in a
single framework. The model was successfully used to study the production of switchgrass and Miscanthus in
Illinois (US). The results indicated that biomass pre-processing significantly affected the total production
cost which varied between 45-65$/Mg. Sensitivity analysis quantified the systemic impact of technology
improvements and thus identified important technologies within the system. Trade-offs between cost and energy
consumption were also highlighted. A novel computational scheme combining mathematical programming and
agent-based modeling has been developed to solve this highly complex model in a computationally efficient
manner. Results showed an order of magnitude reduction in simulation time. Moreover, the optimal solution was
within ±5\% of the rigorous MILP solution. The presentation will also discuss the development of an
agent-based model using the theory of complex adaptive systems to study the dynamics of the production system.
Results showed that up to 15 years might be required to reach steady regional productivity and the dynamics
are strongly dependent on the stakeholder participation and attributes.

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