Design and Scheduling of a Bioreactor System Model for Production of 2G Ethanol

Typ
Examensarbete för masterexamen
Master Thesis
Program
Innovative and sustainable chemical engineering (MPISC), MSc
Publicerad
2019
Författare
Wallin, Elin
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Sammanfattning
During the past 50 years, CO2 emissions have increased by 90 %. Combustion of fossil fuel for energy and transportation and emissions from industrial processes are the two major contributors to these increased CO2 emissions [14]. Because of increasing energy demand and the desire to reduce the CO2 emissions, research to decrease our dependence on fossil-based products has grown during recent years. A way to decrease CO2 emissions is to substitute fossil-based products with biomass-based products [18]. One of the products that can be produced from biomass is bioethanol. The process of converting biomass to bioethanol require multiple procedures due to the complex structure of the raw material [18]. These procedures can be classi ed into the following sections; pre-treatment section, bioreactor section and downstream section. In this thesis economic evaluation of a fed-batch bioreactor system, comprising of a yeast propagation procedures and a procedure for sacchari cation and fermentation (SSF), has been the focus. To make an economical comparison between di erent scheduling cases a batch operating model in SuperPro Designer (SPD) was developed. A batch model has the advantage compared to a continuous model to give a more detailed analysis of the bioreactor section that accounts for the fed-batch behaviour and to account for time-dependency and sequencing of events. The results from the model created indicates that there are economic advantages, decreased annual operating cost and equipment cost, to be gained from optimized scheduling of the process. Results from variation in reaction time for SSF and reactor volume shows that both these impacts the scheduling. Optimizing the scheduling of a industrial-scaled process based on data from lab-scale tests may be problematic since the time required for a certain process, such as SSF, may be di erent depending on the size of the process. If the time required to get high enough conversion in a SSF process increases for a a larger process the scheduling may be unfeasible, which gives that more reactors has to be purchased and included in the layout of the plant. The conclusion is therefore that scheduling using data from small-scale should allow for some exibility.
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Kemiska processer , Energisystem , Bioenergi , Livsvetenskaper , Chemical Process Engineering , Energy Systems , Bioenergy , Life Science
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