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Energy Crop Market Development and Resilience Analysis Using an Agent-Based Model

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2011 Louisville, Kentucky, August 7-10, 2011  1110694.(doi:10.13031/2013.37281)
Authors:   Yogendra Shastri, Luis Rodriguez, Alan Hansen, K.C Ting
Keywords:   Biomass feedstock, agent-based model, resiliency, development, Miscanthus

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 BCAP (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 time dynamics of the adaptation of Miscanthus 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. 25\% reduction in the land opportunity cost led to 63\% increase in the steady state productivity. Sensitivity analysis on the model parameters was conducted to determine the factors having a significant impact on the dynamics of this system.

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