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UBC Theses and Dissertations

The development of a techno-economic model to assess the effect of various process options on a wood-to-ethanol process Gregg, David John

Abstract

In the last twenty-five years there has been considerable interest in the potential for producing ethanol from biomass, particularly in processes involving enzymatic hydrolysis. Unfortunately these processes have not been proven in a fully-integrated system either technically or economically. Techno-economic models have been used in the past to provide assessments of both the process and subprocess maturity and the production cost of the product. Most of this work modelled hardwoods as the substrate and did not consider variable feedstock options. Past hardwood modelling results have shown that the front-end process steps (i.e. Pretreatment, Fractionation and Enzyme Hydrolysis) are both technologically immature and represent a large component (-60%) of the total product cost. In the initial parts of this work the economics and technical maturity of an enzyme based, hardwood-to-ethanol process were reassessed by evaluating the various technical and modelling developments that have been achieved over the past five years. A review of both the technical and past modelling efforts suggested that, due to the immaturity of the overall process and the large number of potential process and subprocess options that have to be considered, the techno-economic model should possess a high degree of flexibility. After evaluating the possibility of developing a new model which would incorporate these characteristics it was decided that two previous models could be combined and updated to provide the necessary flexibility. Consequently, the technical and economic knowledge of the past models was incorporated into a new STeam Explosion Assessment Model (STEAM) that was designed and built to include concepts such as encapsulation, modulation, object-oriented programming and a graphical interface. These characteristics were borrowed from current software development and flowsheet simulators to provide the necessary flexibility and ease of modification. The previously unassessed technical developments (e.g. S0₂ catalysis for steam pretreatment, supplemental lignin recovery via an additional peroxide wash and enzyme recycling, etc.) were also added to this new model. The influence of either a hardwood or softwood feedstock on the overall process and each of the process steps was also assessed. The model was first used to determine the maturity or level of definition of each of the process steps and the subsequent technical and economic impact of the changes on the individual steps and the overall process. Each of the process steps, with the exception of enzyme recycle, showed the potential to substantially reduce the production cost of ethanol. For example, technical benefits accruing from sulphur dioxide usage were substantial and easily overcame the implementation costs when hardwoods were used as the substrate. This technology provided an approximately $0.78/L enhancement over the non-S0₂ water-insoluble (WI) substrate and $0.98/L over the non-S02 water and alkali insoluble (WIA) substrate in hardwoods. Similarly the use of an acid catalyst during steam pretreatment allowed enzyme purchase costs to be reduced from 30% to 8% of the total production cost. However, the corrosive nature of S0₂, particularly at the higher levels anticipated with the softwoods, suggested a requirement for the use of exotic metals in the construction of the equipment. The extra capital to purchase and install zirconium vessels and pump elements indicated that, for both feedstocks, there was a lessening of the return resulting from the implementation of the S02 catalysis. This amounted to S0.07/L for hardwoods and $0.12/L reduction for softwoods. Other impacts identified by the model showed that supplementary lignin recovery, in the form of a peroxide wash following the water and alkali washes, provided major gains ($1.32/L and 105L/ODT) for the softwood feedstock and only minor gains ($0.06/L and 33L/ODT) for the hardwood. In a similar fashion the model first indicated that enzyme recycling could greatly reduce the proportion of total production cost attributed to enzymes (80% in hardwoods and 50% in softwoods). However, the net reduction in the ethanol production cost was only attained when the estimated implementation costs were waived. A flexible techno-economic model has been developed that can effectively model a "generic" hardwood/softwood-to-ethanol process. The model has indicated the difference and similarities of each of the process steps when different wood substrates are used as feedstocks. The model has also indicated which changes in the various process steps can have the most impact on the final cost of producing ethanol from wood substrates. In this way it provides a useful tool in directing where research and development efforts should be focussed to reduce the cost of producing ethanol from biomass feedstocks.

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