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Agent-Based Analysis of Biomass Feedstock Production Dynamics

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Abstract

The success of the bioenergy sector based on lignocellulosic feedstock will require a sustainable and resilient transition from the current agricultural system focused on food crops to one also producing energy crops. The dynamics of this transition are not well understood. It will be driven significantly by the collective participation, behavior, and interaction of various stakeholders such as farmers within the production system. The objective of this work is to study the system dynamics through the development and application of an agent-based model using the theory of complex adaptive systems. Farmers and biorefinery, two key stakeholders in the system, are modeled as independent agents. The decision making of each agent as well as its interaction with other agents is modeled using a set of rules reflecting the economic, social, and personal attributes of the agent. These rules and model parameters are adapted from literature. Regulatory mechanisms such as Biomass Crop Assistance Program are embedded in the decision-making process. The model is then used to simulate the production of Miscanthus as an energy crop in Illinois. Particular focus has been given on understanding the dynamics of Miscanthus adaptation as an agricultural crop and its impact on biorefinery capacity and contractual agreements. Results showed that only 60% of the maximum regional production capacity could be reached, and it took up to 15 years to establish that capacity. A 25% reduction in the land opportunity cost led to a 63% increase in the steady- state productivity. Sensitivity analysis showed that higher initial conversion of land by farmers to grow energy crop led to faster growth in regional productivity.

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Acknowledgement

This work has been funded by the Energy Biosciences Institute through the program titled “Engineering Solutions for Biomass Feedstock Production.

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Correspondence to Yogendra Shastri.

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Shastri, Y., Rodríguez, L., Hansen, A. et al. Agent-Based Analysis of Biomass Feedstock Production Dynamics. Bioenerg. Res. 4, 258–275 (2011). https://doi.org/10.1007/s12155-011-9139-1

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