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Abstract Decision-making in fuel ethanol production faces many uncertainties arising from raw material and product price fluctuations, and process parameter changes. This study analyzes how to reduce the costs and improve the overall efficiency even with these system uncertainties using two types of system uncertainty optimization models with these factors. The research uses a cellulosic ethanol system as a sample case to analyze the design margin problems in the design phase and the raw-material structural problems in the operating phase. The analysis uses stochastic chance-constrained programming model. The results show that uncertainty optimization is more reasonable than certainty optimization, and that the model can reduce costs as well as enhance the system risk resistance.
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Keywords
ethanol
uncertainty
optimization
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Fund: |
Issue Date: 15 May 2014
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[1] |
Herrera S. Industrial biotechnology—A chance at redemption[J]. Nature Biotechnology, 2004, 22(6): 671-675.
url: http://dx.doi.org/10.1038/nbt0604-671
|
[2] |
Mitchell C P. Development of decision support systems for bioenergy applications[J]. Biomass and Bioenergy, 2000(18): 265-278.
|
[3] |
Cardona C A, Sanchez O' J. Fuel ethanol production: Process design trends and integration opportunities[J]. Bioresource Technology, 2007, 98(12): 2415-2457.
url: http://dx.doi.org/10.1016/j.biortech.2007.01.002
|
[4] |
Guo Y, Hu S Y, Li Y R, et al.Optimization and analysis of a bioethanol agro-industrial system from sweet sorghum[J]. Renewable Energy xxx (2010): 1-8.
|
[5] |
Azapagic A. Life cycle assessment and its application to process selection, design and optimisation[J]. Chemical Engineering Journal, 1999, 73(1): 1-21.
url: http://dx.doi.org/10.1016/S1385-8947(99)00042-X
|
[6] |
Azapagic A, Clift R. Life cycle assessment and multiobjective optimisation[J]. Journal of Cleaner Production, 1999, 7(2): 135-143.
url: http://dx.doi.org/10.1016/S0959-6526(98)00051-1
|
[7] |
Azapagic A, Millingtona A, Collett A. A methodology for integrating sustainability considerations into process design[J]. Chemical Engineering Research and Design, 2006, 84(6): 439-452.
url: http://dx.doi.org/10.1205/cherd05007
|
[8] |
Liu B D. Uncertain Programming[M]. New York, USA: John Wiley & Sons, 1999.
|
[9] |
Jeremy C J. Technology assessment of biomass ethanol: A multi-objective, lifecycle approach under uncertainty [D]. Cambridge, USA: Massachusetts Institute of Technology, 2006.
|
[10] |
Huang Y X, Chen C W, Fan Y Y, et al.Multistage optimization of the supply chains of biofuels[J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46(6): 820-830.
url: http://dx.doi.org/10.1016/j.tre.2010.03.002
|
[11] |
Leduc S, Starfelt F, Dotzauer E. Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden[J]. Energy, 2010(35): 2709-2716.
|
[12] |
Martina M, Grossmanna I E. Superstructure optimization of lignocellulosic bioethanol plants[J]. Computer Aided Chemical Engineering, 2010, 28: 943-948.
url: http://dx.doi.org/10.1016/S1570-7946(10)28158-0
|
[13] |
Beynon M J, Munday M. Considering the effects of imprecision and uncertainty in ecological footprint estimation: An approach in a fuzzy environment[J]. Ecological Economics, 2008, 67(3): 373-383.
url: http://dx.doi.org/10.1016/j.ecolecon.2008.07.005
|
[14] |
Tan R R, Ballacillo J B. A fuzzy multiple-objective approach to the optimization of bioenergy system footprints[J]. Chemical Engineering Research and Design, 2009(87): 1162-1170.
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