Browsing by Author "Liebbrand, NH"

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    Techno-economic study for sugarcane basse to liquid biofuels in South Africa: a comparison between biological and thermological process routes
    (2010-08-04) University of Stellenbosch. Faculty of Engineering. Centre for Renewable and Sustainable Energy Studies; Liebbrand, NH; Knoetze, JH; Gorgens, J
    A techno-economic feasibility study was performed to compare biological and thermochemical process routes for production of liquid biofuels from sugarcane bagasse in South Africa using process modelling. Processing of sugarcane bagasse for the production of bioethanol, pyrolysis oil or Fischer-Tropsch liquid fuels were identified as relevant for this case study. For each main process route, various modes or configurations were evaluated, and in total eleven process scenarios were modelled, for which fourteen economic models were developed to include different scales of biomass input. Although detailed process modelling of various biofuels processes has been performed for other (mainly first world) countries, comparative studies have been very limited and mainly focused on mature technology. This is the first techno-economic case study performed for South Africa to compare these process routes using data for sugarcane bagasse. The technical and economic performance of each process route was investigated using the following approach: Obtain reliable data sets from literature for processing of sugarcane bagasse via biological pretreatment, hydrolysis and fermentation, fast and vacuum pyrolysis, and equilibrium gasification to be sufficient for process modelling. Develop process models for eleven process scenarios to compare their energy efficiencies and product yields. In order to reflect currently available technology, conservative assumptions were made where necessary and the measured data collected from literature was used. The modelling was performed to reflect energy-self-sufficient processes by using the thermal energy available as a source of heat and electricity for the process. Develop economic models using cost data available in literature and price data and economic parameters applicable to South Africa. Compare the three process routes using technical and economic results obtained from the process and economic models and identify the most promising scenarios. For bioethanol production, experimental data was collected for three pretreatment methods, namely steam explosion, dilute acid and liquid hot water pretreatment performed at pretreatment solids concentrations of 50wt%, 10wt% and 5wt%, respectively. This was followed by enzymatic hydrolysis and separate co-fermentation. Pyrolysis data for production of bio-oil via fast and vacuum pyrolysis was also collected. For gasification, data was generated via equilibrium modelling based on literature that validated the method against experimental data for sugarcane bagasse gasification. The equilibrium model was used to determine optimum gasification conditions for either gasification efficiency or syngas composition, using sugarcane bagasse, fast pyrolysis slurry or vacuum pyrolysis slurry as feedstock. These results were integrated with a downstream process model for Fischer-Tropsch synthesis to evaluate the effect of upstream optimisation on the process energy efficiency and economics, and the inclusion of a shift reactor was also evaluated. The effect of process heat integration and boilers with steam turbine cycles to produce process heat and electricity, and possibly electricity by-product, was included for each process. This analysis assumed that certain process units could be successfully scaled to commercial scales at the same yields and efficiencies determined by experimental and equilibrium modelling data. The most important process units that need to be proven on an industrial scale are pretreatment, hydrolysis and fermentation for bioethanol production, the fast pyrolysis and vacuum pyrolysis reactors, and the operation of a twostage gasifier with nickel catalyst at near equilibrium conditions. All of these process units have already been proven on a bench scale with sugarcane bagasse as feedstock. The economic models were based on a critical evaluation of equipment cost data available in literature, and a conservative approach was taken to reflect 1st plant technology. Data for the cost and availability of raw materials was obtained from the local industry and all price data and economic parameters (debt ratio, interest and tax rates) were applicable to the current situation in South Africa. A sensitivity analysis was performed to investigate the effects of likely market fluctuations on the process economics. A summary of the technical and economic performances of the most promising scenarios is shown in the table below. The bioethanol process models showed that the liquid hot water and dilute acid pretreatment scenarios are not energy self-sufficient and require additional fossil energy input to supply process energy needs. This is attributed to the excessive process steam requirements for pretreatment and conditioning due to the low pretreatment solid concentrations of 5wt% and 10wt%, respectively. The critical solids concentration during dilute acid pretreatment for an energy selfsufficient process was found to be 35%, although this was a theoretical scenario and the data needs to be verified experimentally. At a pretreatment level of 50% solids, steam explosion achieved the highest process thermal energy efficiency for bioethanol of 55.8%, and a liquid fuel energy efficiency of 40.9%. Both pyrolysis processes are energy self-sufficient, although some of the char produced by fast pyrolysis is used to supplement the higher process energy demand of fast compared to vacuum pyrolysis. The thermal process energy efficiencies of both pyrolysis processes are roughly 70% for the production of crude bio-oil that can be sold as a residual fuel oil. However, the liquid fuel energy efficiency of fast pyrolysis is 66.5%, compared to 57.5% for vacuum pyrolysis, since fast pyrolysis produces more bio-oil and less char than vacuum pyrolysis.