Degree Type

Dissertation

Date of Award

2017

Degree Name

Doctor of Philosophy

Department

Agricultural and Biosystems Engineering

Major

Agricultural and Biosystems Engineering

First Advisor

Kurt A. Rosentrater

Abstract

With the rapid development of agricultural biorefinery and bioprocessing, economic efficiency and environmental effects have gradually been very popular studies in the advanced research of industrial process. As an important section of bioprocessing, the corn-based ethanol industry and oil refinery processes have been discussed fully, with details of technology, including material, reaction control, equipment and industrial applications. However, there are few studies of engineering economy and environmental effects on these processes and related products. In addition, most bioprocess research separately treats either economic efficiency or environmental effect, which lacks efficiency and comprehensiveness. Because of these obstacles, an efficient tool and software for engineering economics and environmental research is still being investigated.

Due to the reasons above, this dissertation focused on techno-economic analysis (TEA) and environmental impact assessment (EIA) on the industrial corn-based ethanol process, advanced corn-soybean bio-refining and distillers dried grains with solubles (DDGS) separation process. This dissertation is prepared in a paper format, and is comprised of six chapters, as follows:

The first chapter conducted initial techno-economic analysis (TEA) for a corn-based ethanol plant using data from 1982 to 2016. This study tested various procedures to assess the factors that affect ethanol plant profit, such as cost of corn, DDGS, ethanol, gas, electricity and so on. By using the updated U.S. Department of Agriculture (USDA) model, this study demonstrated the bioprocess modeling used to assess the economic performance of bioethanol plant systems, which provided a starting point for the analysis of advanced corn-soybean biorefinery.

The second chapter expanded the scale of the first study model from 40 million gallons of ethanol per year to 120 million gallons of ethanol per year, and compared the effects to efficiency and profits during various scales. Similar to the first manuscript, this model was constructed using SuperPro Designer, and considered purchase and sale prices of materials and products, as well as estimated fixed costs, capital costs, revenues, and profits. This study provided a starting point for the analysis of advanced corn-soybean bio-refining in the future.

The third chapter focused on advanced corn-soybean bio-refining using techno-economic analysis (TEA). By using the data of enzyme-assisted aqueous extraction processing (EAEP), this study demonstrated using the updated USDA model to simulate the corn-soybean bio-refining systems, and discuss the feasibility of industrial application for this technology. In addition, this chapter explored the difference in economic effects with original corn-based ethanol plants.

The fourth chapter collected processing data from the previous three manuscripts, and utilized a method with a simple structure to easily assess environmental impacts. This method focused on the material or process steps that caused most of the potential environmental burden. Environmental impact assessment (EIA) concentrated more on the corn-based ethanol process itself, and was less time-consuming than complicated life cycle assessment (LCA).

The fifth chapter determined techno-economics analysis of DDGS fractionation using a destoner to separate nutrients. Mathematical models were built for conducting techno-economic analysis (TEA), which allowed for estimations of capital costs, annual operating costs, annual revenues, and net profits. The techno-economics of the base case ethanol plant were examined by adjusting material and market costs, and estimating fractionation efficiencies and fraction prices based on protein content. This study demonstrated the possibility of using a destoner to fractionate DDGS to produce higher economic returns.

Copyright Owner

Weitao Zhang

Language

en

File Format

application/pdf

File Size

201 pages

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