An integrated optimization model for switchgrass-based bioethanol supply chain
► Mathematical model for optimizing cost of a switchgrass-based biofuel supply chain. ► Loose chop is the optimal switchgrass harvest method compared to traditional bales. ► Biorefinery location is dictated by the transportation cost of biomass and biofuel. Bioethanol produced from lignocellulosic f...
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Published in: | Applied energy Vol. 102; pp. 1205 - 1217 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Kidlington
Elsevier Ltd
01-02-2013
Elsevier |
Subjects: | |
Online Access: | Get full text |
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Summary: | ► Mathematical model for optimizing cost of a switchgrass-based biofuel supply chain. ► Loose chop is the optimal switchgrass harvest method compared to traditional bales. ► Biorefinery location is dictated by the transportation cost of biomass and biofuel.
Bioethanol produced from lignocellulosic feedstock show enormous potential as an economically and environmentally sustainable renewable energy source. Switchgrass (panicum virgatum) is considered as one of the best second generation feedstock for bioethanol production. In order to commercialize the production of switchgrass-based bioethanol, it is essential to design an efficient switchgrass-based bioethanol supply chain (SBSC) and effectively manage the logistics operation. This paper proposes an integrated mathematical model to determine the optimal comprehensive supply chain/logistics decisions to minimize the total SBSC cost by considering existing constraints. A case study based on North Dakota state (ND) in the United States illustrates the application of the proposed model. The results demonstrate that by using only 61% of the available marginal land for production of switchgrass feedstock, 100% of the annual gasoline energy equivalent requirement of ND can be economically and sustainably met from the produced bioethanol. Sensitivity analysis is conducted to provide insights for efficiently managing the entire SBSC and minimizing the total cost. |
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Bibliography: | http://dx.doi.org/10.1016/j.apenergy.2012.06.054 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0306-2619 1872-9118 |
DOI: | 10.1016/j.apenergy.2012.06.054 |