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Impacts of facility size and location decisions on ethanol production cost

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  • Kocoloski, Matt
  • Michael Griffin, W.
  • Scott Matthews, H.

Abstract

Cellulosic ethanol has been identified as a promising alternative to fossil fuels to provide energy for the transportation sector. One of the obstacles cellulosic ethanol must overcome in order to contribute to transportation energy demand is the infrastructure required to produce and distribute the fuel. Given a nascent cellulosic ethanol industry, locating cellulosic ethanol refineries and creating the accompanying infrastructure is essentially a greenfield problem that may benefit greatly from quantitative analysis. This study models cellulosic ethanol infrastructure investment using a mixed integer program (MIP) that locates ethanol refineries and connects these refineries to the biomass supplies and ethanol demands in a way that minimizes the total cost. For the single- and multi-state regions examined in this study, larger facilities can decrease ethanol costs by $0.20-0.30 per gallon, and placing these facilities in locations that minimize feedstock and product transportation costs can decrease ethanol costs by up to $0.25 per gallon compared to uninformed placement that could result from influences such as local subsidies to encourage economic development. To best benefit society, policies should allow for incentives that encourage these low-cost production scenarios and avoid politically motivated siting of plants.

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  • Kocoloski, Matt & Michael Griffin, W. & Scott Matthews, H., 2011. "Impacts of facility size and location decisions on ethanol production cost," Energy Policy, Elsevier, vol. 39(1), pages 47-56, January.
    • Handle: RePEc:eee:enepol:v:39:y:2011:i:1:p:47-56
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    17. Piradee Jusakulvijit & Alberto Bezama & Daniela Thrän, 2022. "An Integrated Assessment of GIS-MCA with Logistics Analysis for an Assessment of a Potential Decentralized Bioethanol Production System Using Distributed Agricultural Residues in Thailand," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
    18. Schmidt, J. & Schönhart, M. & Biberacher, M. & Guggenberger, T. & Hausl, S. & Kalt, G. & Leduc, S. & Schardinger, I. & Schmid, E., 2012. "Regional energy autarky: Potentials, costs and consequences for an Austrian region," Energy Policy, Elsevier, vol. 47(C), pages 211-221.
    19. Gonela, Vinay & Zhang, Jun & Osmani, Atif & Onyeaghala, Raphael, 2015. "Stochastic optimization of sustainable hybrid generation bioethanol supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 1-28.
    20. Holland, R.A. & Eigenbrod, F. & Muggeridge, A. & Brown, G. & Clarke, D. & Taylor, G., 2015. "A synthesis of the ecosystem services impact of second generation bioenergy crop production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 30-40.
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    22. Bekkering, J. & Hengeveld, E.J. & van Gemert, W.J.T. & Broekhuis, A.A., 2015. "Designing a green gas supply to meet regional seasonal demand – An operations research case study," Applied Energy, Elsevier, vol. 143(C), pages 348-358.
    23. Haji Esmaeili, Seyed Ali & Szmerekovsky, Joseph & Sobhani, Ahmad & Dybing, Alan & Peterson, Tim O., 2020. "Sustainable biomass supply chain network design with biomass switching incentives for first-generation bioethanol producers," Energy Policy, Elsevier, vol. 138(C).

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