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.
Similar content being viewed by others
References
Perlack RD, Wright LL, Turhollow AF, Graham RL, Stokes BJ, Erbach DC (2005) Biomass as feedstock for bioenergy and bioproducts industry: the technical feasibility of a billion-ton annual supply. Tech. Rep. DOE/GO-102005-2135, ORNL/TM-2005/66 Oak Ridge National Laboratory, TN
Somerville C (2006) The billion-ton biofuels vision. Science 312:1277
Koonin SE (2006) Getting serious about biofuels. Science 311:435
Cushman JH, Easterly JL, Erbach DC et al (2003) Roadmap for agriculture biomass feedstock supply in the United States. Tech. Rep. DOE/NE ID - 11129 U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Biomass Program U.S. Department of Energy, Energy Efficiency and Renewable Energy, Washington, DC
Somerville C, Young H, Taylor C, Davis S, Long S (2010) Feedstocks for lignocellulosic biofuels. Science 329:790–792
Rossi AM, Hinrichs CC (2011) Hope and skepticism: farmer and local community views on the socio-economic benefits of agricultural bioenergy. Biomass Bioenergy 35(4):1418–1428
Jain A, Khanna M, Erickson M, Huang H (2010) An integrated biogeochemical and economic analysis of bioenergy crops in the Midwestern United States. Glob Change Biol Bioenergy 2:217–234
Khanna M, Dhungana B, Clifton-Brown J (2008) Costs of producing Miscanthus and switchgrass for bioenergy in Illinois. Biomass Bioenergy 32:482–493
Walsh M, De La Torre Ugarte D, Shapouri H, Slinsky S (2003) Bioenergy crop production in the United States. Environ Resour Econ 24:313–333
De La Torre Ugarte DG, Ray D (2000) Biomass and bioenergy applications of the POLYSYS modeling framework. Biomass Bioenergy 18:291–308
Shastri Y, Hansen A, Rodriguez L, Ting K (2011) Development and application of BioFeed model for optimization of herbeceous biomass feedstock production. Biomass Bioenergy 35(7):2961–2974
Shastri Y, Hansen A, Rodriguez L, Ting K (2011) Optimization of Miscanthus harvesting and handling as an energy crop: BioFeed model application. Biol Eng 3(1):37–69
Sokhansanj S, Mani S, Turhollow A et al (2009) Large-scale production, harvest and logistics of switchgrass (Panicum virgatum L.)—current technology and envisioning a mature technology. Biofuel Bioprod Bioref 3:124–141
Bitra VS, Womac AR, Igathinathane C et al (2009) Direct measures of mechanical energy for knife mill size reduction of switchgrass, wheat straw, and corn stover. Bioresour Technol 100(24):6578–6585
Burns J, Fisher D, Pond K (1993) Ensiling characteristics and utilization of switchgrass preserved as silage. Postharvest Biol Technol 3(4):349–359
Ravula P, Grisso R, Cundiff J (2008) Comparison between two policy strategies for scheduling trucks in a biomass logistic system. Bioresour Technol 99:5710–5721
Mapemba LD, Epplin FM, Huhnke RL, Taliaferro CM (2008) Herbaceous plant biomass harvest and delivery cost with harvest segmented by month and number of harvest machines endogenously determined. Biomass Bioenergy 32:1016–1027
Petrolia DR (2008) The economics of harvesting and transporting corn stover for conversion to fuel ethanol: a case study for Minnesota. Biomass Bioenergy 32(7):603–612
Tyndall JC, Berg EJ, Colletti JP (2011) Corn stover as a biofuel feedstock in Iowa’s bio-economy: an Iowa farmer survey. Biomass Bioenergy 35(4):1485–1495
Paulrud S, Laitila T (2010) Farmers’ attitudes about growing energy crops: a choice experiment approach. Biomass Bioenergy 34(12):1770–1779
Rämö AK, Järvinen E, Latvala T, Toivonen R, Silvennoinen H (2009) Interest in energy wood and energy crop production among Finnish non-industrial private forest owners. Biomass Bioenergy 33(9):1251–1257
Wen Z, Ignosh J, Parrish D, Stowe J, Jones B (2009) Identifying farmers’ interest in growing switchgrass for bioenergy in southern Virginia. J Ext 47(5):1–10
Villamil MB, Silvis AH, Bollero GA (2008) Potential Miscanthus’ adoption in Illinois: information needs and preferred information channels. Biomass Bioenergy 32(12):1338–1348
Jensen K, Clark CD, Ellis P et al (2007) Farmer willingness to grow switchgrass for energy production. Biomass Bioenergy 31(11–12):773–781
Guckenheimer J, Ottino J (2008) Foundations for complex systems research in the physical sciences and engineering. Tech. Rep. National Science Foundation
Lucia A (2010) Multi-scale methods and complex processes: a survey and look ahead. Comput Chem Eng 34:1467–1475
Li J, Kwauk M (2003) Exploring complex systems in chemical engineering—the multi-scale methodology. Chem Eng Sci 58:521–535
Ottino J (2003) Complex systems. AIChE J 49(2):292–299
Srbljinovic A, Skunca O (2003) An introduction to agent based modelling and simulation of social processes. Interdisciplinary Description of Complex Systems 1(1–2):1–8
Kempener R, Beck J, Petrie J (2009) Design and analysis of bioenergy networks: a complex adaptive systems approach. J Ind Ecol 13(2):284–305
Beck J, Kempener R, Cohen B, Petrie J (2008) A complex systems approach to planning, optimization and decision making for energy networks. Energy Policy 36:2795–2805
Bing Z, Qinqin Y, Jun B (2010) Policy design and performance of emissions trading markets: an adaptive agent-based analysis. Environ Sci Technol 44:5693–5699
Happe K, Kellermann K, Balmann A (2006) Agent-based analysis of agricultural policies: an illustration of the Agricultural Policy Simulator AgriPoliS, its adaptation and behavior. Ecol Soc 11(1):49–74
Lobianco A, Esposti R (2010) The regional multi-agent simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies. Comput Electron Agric 72:14–26
Julka N, Srinivasan R, Karimi I (2002) Agent-based supply chain management—1: framework. Comput Chem Eng 26:1755–1769
Scheffran J, BenDor T (2009) Bioenergy and land use: a spatial-agent dynamic model of energy crop production in Illinois. Int J Environ Pol 39(1–2):4–27
Bunn DW, Oliveira FS (2007) Agent-based analysis of technological diversification and specialization in electricity markets. Eur J Oper Res 181:1265–1278
Jennings NR (2000) On agent-based software engineering. Artif Int 117:277–296
Booch G (1994) Object-oriented analysis and design with applications. The Benjamin/Cummings Publishing Company, Redwood City
Stubbs G (2010) Biomass crop assistance program (BCAP): status and issues. Tech. Rep. Congressional Research Service
Heaton E, Voigt T, Long S (2004) A quantitative review of comparing the yields of two candidate C4 biomass crops. Biomass Bioenergy 27:21–30
Kempener R, Kaufmann P, Stagl S, Stirling A, Perez K (2009) The role of agricultural diversity and rural sustainable development: a dynamic systems approach. Tech. Rep. Austrian Institute for Regional Studies and Spatial Planning
Bellmann A (1997) Farm-based modelling of regional structural change: a cellular automata approach. Eur Rev Agric Econ 24(1):85–108
Shastri Y, Hansen A, Rodriguez L, Ting K (2011) A novel decomposition and distributed computing approach for the solution of large scale optimization models. Comput Electron Agric 76(1):69–79
Heaton E, Clifton-Brown J, Voigt T, Jones M, Long S (2004) Miscanthus for renewable energy generation: European union experience and projections for Illinois. Mit Adapt Strat Glob Change 9(4):433–451
Jones M, Walsh M (eds) (2001) Miscanthus for energy and fibre. James & James (Science Publishers) Ltd., London
Lewandowski I, Scurlock JM, Lindvall E, Christou M (2003) The development and current status of perennial rhizomatous grasses as energy crops in the US and Europe. Biomass Bioenergy 25:335–361
Clifton-Brown J, Stampfel PF, Jones M (2004) Miscanthus biomass production for energy in Europe and its potential contribution to decreasing fossil fuel carbon emissions. Glob Chang Biol 10:509–518
Lewandowski I, Clifton-Brown J, Scurlock J, Huisman W (2000) Micanthus: European experience with a novel energy crop. Biomass Bioenergy 19(4):209–227
Acknowledgement
This work has been funded by the Energy Biosciences Institute through the program titled “Engineering Solutions for Biomass Feedstock Production.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
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
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12155-011-9139-1