Optimisation of South Africa's biomass to bio-ethanol supply chain network

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dc.contributor.advisorIsafiade, Adeniyi Jideen_ZA
dc.contributor.advisorFraser, Duncanen_ZA
dc.contributor.authorMutenure, Mildreden_ZA
dc.date.accessioned2017-05-16T07:59:20Z
dc.date.available2017-05-16T07:59:20Z
dc.date.issued2016en_ZA
dc.description.abstractThis study is about the optimisation of bio-ethanol supply chains for economic and environmental objectives, using a mathematical programming approach. A superstructure presented as a Mixed Integer Linear Programme (MILP) model that adequately captures the key variables in South Africa's bio-ethanol supply chain network is developed. The MILP model accounts for food demand, geographical distribution of biomass cultivation areas and biomass diversity, feedstock, product and by-product distribution, product demand and tax subsidies. The study focuses on the use of sugarcane, bagasse and crop waste from maize, wheat, barley and sorghum in the production of bio-ethanol. In the supply chain, one processing technology for ethanol production is considered and one mode of transportation for both feedstock and products is considered. A detailed profitability analysis of the optimised MILP model is also provided. To account for the environmental impact of the supply chain, the model is integrated with life cycle analysis through multi-objective optimisation. The ε- constraint method is used to solve the multi-objective optimisation problem and Pareto analysis is done to check the trade-offs between the economic and environmental objectives, which is measured mainly by greenhouse gas emissions. In addition to greenhouse gas emissions, other impact categories namely eutrophication, human toxicity, acidification and global warming potential were also considered. Bio-ethanol production has been a subject of many studies. It is a renewable and potentially environment-friendly product, which after blending with petrol can be used as a fuel in the transport sector. The use of bio-fuels has the potential to relieve pressure on fossil-based fuels, and achieve a reduction in the emissions of greenhouse gases. The use of bio-fuel results in net savings in carbon dioxide gas emissions as plants absorb the carbon dioxide released during bio-fuel production during biomass cultivation. The bio-fuel industry worldwide, however, faces many challenges, which compromises its economic viability and commercialisation, especially where lignocellulosic biomass is to be used in bio-fuel production. These challenges include the uncertainty or discontinuous availability of biomass, fluctuations in market prices, high logistics and high maintenance costs of the processing equipment. The high logistics costs arise from the low density of the feedstock and from distribution of the feedstock, which is usually scattered over a wide area thereby making the process energy intensive. To overcome these challenges, an optimised supply chain network is required.en_ZA
dc.identifier.apacitationMutenure, M. (2016). <i>Optimisation of South Africa's biomass to bio-ethanol supply chain network</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Chemical Engineering. Retrieved from http://hdl.handle.net/11427/24312en_ZA
dc.identifier.chicagocitationMutenure, Mildred. <i>"Optimisation of South Africa's biomass to bio-ethanol supply chain network."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Chemical Engineering, 2016. http://hdl.handle.net/11427/24312en_ZA
dc.identifier.citationMutenure, M. 2016. Optimisation of South Africa's biomass to bio-ethanol supply chain network. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Mutenure, Mildred AB - This study is about the optimisation of bio-ethanol supply chains for economic and environmental objectives, using a mathematical programming approach. A superstructure presented as a Mixed Integer Linear Programme (MILP) model that adequately captures the key variables in South Africa's bio-ethanol supply chain network is developed. The MILP model accounts for food demand, geographical distribution of biomass cultivation areas and biomass diversity, feedstock, product and by-product distribution, product demand and tax subsidies. The study focuses on the use of sugarcane, bagasse and crop waste from maize, wheat, barley and sorghum in the production of bio-ethanol. In the supply chain, one processing technology for ethanol production is considered and one mode of transportation for both feedstock and products is considered. A detailed profitability analysis of the optimised MILP model is also provided. To account for the environmental impact of the supply chain, the model is integrated with life cycle analysis through multi-objective optimisation. The ε- constraint method is used to solve the multi-objective optimisation problem and Pareto analysis is done to check the trade-offs between the economic and environmental objectives, which is measured mainly by greenhouse gas emissions. In addition to greenhouse gas emissions, other impact categories namely eutrophication, human toxicity, acidification and global warming potential were also considered. Bio-ethanol production has been a subject of many studies. It is a renewable and potentially environment-friendly product, which after blending with petrol can be used as a fuel in the transport sector. The use of bio-fuels has the potential to relieve pressure on fossil-based fuels, and achieve a reduction in the emissions of greenhouse gases. The use of bio-fuel results in net savings in carbon dioxide gas emissions as plants absorb the carbon dioxide released during bio-fuel production during biomass cultivation. The bio-fuel industry worldwide, however, faces many challenges, which compromises its economic viability and commercialisation, especially where lignocellulosic biomass is to be used in bio-fuel production. These challenges include the uncertainty or discontinuous availability of biomass, fluctuations in market prices, high logistics and high maintenance costs of the processing equipment. The high logistics costs arise from the low density of the feedstock and from distribution of the feedstock, which is usually scattered over a wide area thereby making the process energy intensive. To overcome these challenges, an optimised supply chain network is required. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Optimisation of South Africa's biomass to bio-ethanol supply chain network TI - Optimisation of South Africa's biomass to bio-ethanol supply chain network UR - http://hdl.handle.net/11427/24312 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/24312
dc.identifier.vancouvercitationMutenure M. Optimisation of South Africa's biomass to bio-ethanol supply chain network. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Chemical Engineering, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/24312en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Chemical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherChemical Engineeringen_ZA
dc.titleOptimisation of South Africa's biomass to bio-ethanol supply chain networken_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMSc (Eng)en_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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