Waste-to-bioethanol supply chain network: A deterministic model
•A decision-making strategy for organic waste to bioethanol SCN is developed.•Techno-Economic Assessment of bioethanol SCN is considered.•A deterministic programming model for bioethanol SCN is developed.•A case study of bioethanol SCN in South Korea in 2030 is presented. Bioethanol (bio-EtOH) is co...
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| Vydáno v: | Applied energy Ročník 300; s. 117381 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
15.10.2021
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| ISSN: | 0306-2619, 1872-9118 |
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| Abstract | •A decision-making strategy for organic waste to bioethanol SCN is developed.•Techno-Economic Assessment of bioethanol SCN is considered.•A deterministic programming model for bioethanol SCN is developed.•A case study of bioethanol SCN in South Korea in 2030 is presented.
Bioethanol (bio-EtOH) is commonly used as a renewable biofuel additive for gasoline. A novel technology producing bio-EtOH from anaerobic digestion of organic waste (OW) has recently attracted attention. This work presents a deterministic mixed integer linear programming model for the optimal location of OW-based bio-EtOH biorefineries. The proposed model considers OW treatment location, bio-EtOH biorefineries, and truck transport links as a supply chain network (SCN) approach. The objective function of the developed model is to minimize the total bio-EtOH levelized cost (ELC) while satisfying the model constraints consisting of equalities (e.g., mass and energy balances for the bio-EtOH biorefinery) and inequalities (e.g., capacity of the bio-EtOH refinery, truck transport) to meet the regional demands of bio-EtOH. To validate the optimization model, a case study based on a real scenario for South Korea in 2030 was conducted for different bio-EtOH blending rates (E10, E20, E85, E100). The case study results indicate that ELC of E10 containing 10% bio-EtOH from OW products combined with gasoline is USD 3.65/gallon. As the blending rate of bio-EtOH increases, ELC increases to USD 4.36/gallon for E20, USD 8.99/gallon for E85, and USD 10.05/gallon for E100. The optimization results can help determine SCN strategies for an OW-based biofuel economy. |
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| AbstractList | Bioethanol (bio-EtOH) is commonly used as a renewable biofuel additive for gasoline. A novel technology producing bio-EtOH from anaerobic digestion of organic waste (OW) has recently attracted attention. This work presents a deterministic mixed integer linear programming model for the optimal location of OW-based bio-EtOH biorefineries. The proposed model considers OW treatment location, bio-EtOH biorefineries, and truck transport links as a supply chain network (SCN) approach. The objective function of the developed model is to minimize the total bio-EtOH levelized cost (ELC) while satisfying the model constraints consisting of equalities (e.g., mass and energy balances for the bio-EtOH biorefinery) and inequalities (e.g., capacity of the bio-EtOH refinery, truck transport) to meet the regional demands of bio-EtOH. To validate the optimization model, a case study based on a real scenario for South Korea in 2030 was conducted for different bio-EtOH blending rates (E10, E20, E85, E100). The case study results indicate that ELC of E10 containing 10% bio-EtOH from OW products combined with gasoline is USD 3.65/gallon. As the blending rate of bio-EtOH increases, ELC increases to USD 4.36/gallon for E20, USD 8.99/gallon for E85, and USD 10.05/gallon for E100. The optimization results can help determine SCN strategies for an OW-based biofuel economy. •A decision-making strategy for organic waste to bioethanol SCN is developed.•Techno-Economic Assessment of bioethanol SCN is considered.•A deterministic programming model for bioethanol SCN is developed.•A case study of bioethanol SCN in South Korea in 2030 is presented. Bioethanol (bio-EtOH) is commonly used as a renewable biofuel additive for gasoline. A novel technology producing bio-EtOH from anaerobic digestion of organic waste (OW) has recently attracted attention. This work presents a deterministic mixed integer linear programming model for the optimal location of OW-based bio-EtOH biorefineries. The proposed model considers OW treatment location, bio-EtOH biorefineries, and truck transport links as a supply chain network (SCN) approach. The objective function of the developed model is to minimize the total bio-EtOH levelized cost (ELC) while satisfying the model constraints consisting of equalities (e.g., mass and energy balances for the bio-EtOH biorefinery) and inequalities (e.g., capacity of the bio-EtOH refinery, truck transport) to meet the regional demands of bio-EtOH. To validate the optimization model, a case study based on a real scenario for South Korea in 2030 was conducted for different bio-EtOH blending rates (E10, E20, E85, E100). The case study results indicate that ELC of E10 containing 10% bio-EtOH from OW products combined with gasoline is USD 3.65/gallon. As the blending rate of bio-EtOH increases, ELC increases to USD 4.36/gallon for E20, USD 8.99/gallon for E85, and USD 10.05/gallon for E100. The optimization results can help determine SCN strategies for an OW-based biofuel economy. |
| ArticleNumber | 117381 |
| Author | Kwon, Oseok Han, Jeehoon |
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| Cites_doi | 10.1039/C6RA10003A 10.1016/j.biortech.2013.01.007 10.1016/j.apenergy.2019.113482 10.1016/j.apenergy.2019.114235 10.1627/jpi.63.196 10.1016/j.jclepro.2018.08.061 10.1126/science.1246748 10.1016/j.apenergy.2020.115653 10.1039/D1EE00850A 10.1016/j.apenergy.2016.12.091 10.1039/C3GC41511B 10.1016/j.ijhydene.2011.04.001 10.1021/ie200344t 10.1039/c4nj00134f 10.1016/j.apenergy.2020.115884 10.1016/j.apenergy.2015.05.047 10.1016/j.biortech.2015.01.135 10.1016/j.mcat.2018.01.030 10.1016/j.wasman.2014.11.019 10.3390/en11061551 10.1039/D0EE00812E 10.1039/C7GC02368E |
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publication-title: Bioresour Technol doi: 10.1016/j.biortech.2015.01.135 – volume: 448 start-page: 78 year: 2018 ident: 10.1016/j.apenergy.2021.117381_b0065 article-title: Acetic acid hydrogenation to ethanol over supported Pt-Sn catalyst: Effect of Bronsted acidity on product selectivity publication-title: Molecular Catalysis. doi: 10.1016/j.mcat.2018.01.030 – volume: 36 start-page: 147 year: 2015 ident: 10.1016/j.apenergy.2021.117381_b0055 article-title: Composition variability of the organic fraction of municipal solid waste and effects on hydrogen and methane production potentials publication-title: Waste Manage doi: 10.1016/j.wasman.2014.11.019 – volume: 11 start-page: 1551 year: 2018 ident: 10.1016/j.apenergy.2021.117381_b0060 article-title: Increasing Profits in Food Waste Biorefinery—A Techno-Economic Analysis publication-title: Energies. doi: 10.3390/en11061551 – volume: 13 start-page: 2233 year: 2020 ident: 10.1016/j.apenergy.2021.117381_b0025 article-title: Sustainable development of biorefineries: integrated assessment method for co-production pathways publication-title: Energy Environ Sci doi: 10.1039/D0EE00812E – volume: 19 start-page: 5214 year: 2017 ident: 10.1016/j.apenergy.2021.117381_b0100 article-title: An integrated strategy for catalytic co-production of jet fuel range alkenes, tetrahydrofurfuryl alcohol, and 1,2-pentanediol from lignocellulosic biomass publication-title: Green Chem doi: 10.1039/C7GC02368E |
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| Title | Waste-to-bioethanol supply chain network: A deterministic model |
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