Andrew J. McAloon

Determining the Cost of Producing Ethanol from Corn Starch and Lignocellulosic Feedstocks

The mature corn-to-ethanol industry has many similarities to the emerging lignocellulose-to-ethanol industry. It is certainly possible that some of the early practitioners of this new technology will be the current corn ethanol producers. In order to begin to explore synergies between the two industries, a joint project between two agencies responsible for aiding these technologies in the Federal government was established. This joint project of the USDA-ARS and DOE/NREL looked at the two processes on a similar process design and engineering basis, and will eventually explore ways to combine them. This report describes the comparison of the processes, each producing 25 million annual gallons of fuel ethanol. This paper attempts to compare the two processes as mature technologies, which requires assuming that the technology improvements needed to make the lignocellulosic process commercializable are achieved, and enough plants have been built to make the design well-understood. Ass umptions about yield and design improvements possible from continued research were made for the emerging lignocellulose process. In order to compare the lignocellulose-to-ethanol process costs with the commercial corn-to-ethanol costs, it was assumed that the lignocellulose plant was an Nth generation plant, built after the industry had been sufficiently established to eliminate first-of-a-kind costs. This places the lignocellulose plant costs on a similar level with the current, established corn ethanol industry, whose costs are well known. The resulting costs of producing 25 million annual gallons of fuel ethanol from each process were determined. The figure below shows the production cost breakdown for each process. The largest cost contributor in the corn starch process is the feedstock; for the lignocellulosic process it is the capital cost, which is represented by depreciation cost on an annual basis.

Dry-grind process for fuel ethanol by continuous fermentation and stripping.

Conversion of a high‐solids saccharified corn mash to ethanol by continuous fermentation and stripping was successfully demonstrated in a pilot plant consuming 25 kg of corn per day. A mathematical model based on previous pilot plant results accurately predicts the specific growth rate obtained from these latest results. This model was incorporated into a simulation of a complete dry‐grind corn‐to‐ethanol plant, and the cost of ethanol production was compared with that of a conventional process. The results indicate a savings of

Feasibility study for co-locating and integrating ethanol production plants from corn starch and lignocellulosic feedstocks

0.03 per gallon of ethanol produced by the stripping process. The savings with stripping result from the capacity to ferment a more concentrated corn mash so there is less water to remove downstream.

Enzymatic corn wet milling: engineering process and cost model

Analysis of the feasibility of co-locating corn-grain-to-ethanol and lignocellulosic ethanol plants and potential savings from combining utilities, ethanol purification, product processing, and fermentation. Although none of the scenarios identified could produce ethanol at lower cost than a straight grain ethanol plant, several were lower cost than a straight cellulosic ethanol plant.

Protease increases fermentation rate and ethanol yield in dry-grind ethanol production.

BackgroundEnzymatic corn wet milling (E-milling) is a process derived from conventional wet milling for the recovery and purification of starch and co-products using proteases to eliminate the need for sulfites and decrease the steeping time. In 2006, the total starch production in USA by conventional wet milling equaled 23 billion kilograms, including modified starches and starches used for sweeteners and ethanol production [1]. Process engineering and cost models for an E-milling process have been developed for a processing plant with a capacity of 2.54 million kg of corn per day (100,000 bu/day). These models are based on the previously published models for a traditional wet milling plant with the same capacity. The E-milling process includes grain cleaning, pretreatment, enzymatic treatment, germ separation and recovery, fiber separation and recovery, gluten separation and recovery and starch separation. Information for the development of the conventional models was obtained from a variety of technical sources including commercial wet milling companies, industry experts and equipment suppliers. Additional information for the present models was obtained from our own experience with the development of the E-milling process and trials in the laboratory and at the pilot plant scale. The models were developed using process and cost simulation software (SuperPro Designer®) and include processing information such as composition and flow rates of the various process streams, descriptions of the various unit operations and detailed breakdowns of the operating and capital cost of the facility.ResultsBased on the information from the model, we can estimate the cost of production per kilogram of starch using the input prices for corn, enzyme and other wet milling co-products. The work presented here describes the E-milling process and compares the process, the operation and costs with the conventional process.ConclusionThe E-milling process was found to be cost competitive with the conventional process during periods of high corn feedstock costs since the enzymatic process enhances the yields of the products in a corn wet milling process. This model is available upon request from the authors for educational, research and non-commercial uses.

Fermentation and costs of fuel ethanol from corn with quick-germ process

The effects of acid protease and urea addition during the fermentation step were evaluated. The fermentations were also tested with and without the addition of urea to determine if protease altered the nitrogen requirements of the yeast. Results show that the addition of the protease had a statistically significant effect on the fermentation rate and yield. Fermentation rates and yields were improved with the addition of the protease over the corresponding controls without protease. Protease addition either with or with added urea resulted in a higher final ethanol yield than without the protease addition. Urea addition levels >1200 ppm of supplemental nitrogen inhibited ethanol production. The economic effects of the protease addition were evaluated by using process engineering and economic models developed at the Eastern Regional Research Center. The decrease in overall processing costs from protease addition was as high as

Economic analysis of fuel ethanol production from winter hulled barley by the EDGE (Enhanced Dry Grind Enzymatic) process.

0.01/L (4 ¢/gal) of denatured ethanol produced.

Fractionation of Whey Protein Isolate with Supercritical Carbon Dioxide—Process Modeling and Cost Estimation

The Quick-Germ process developed at the University of Illinois at Urbana-Champaign is a way to obtain corn oil, but with lower capital costs than the traditional wet-milling process. Quick-Germ has the potential to increase the coproduct credits and profitability of the existing dry-grind fuel ethanol process, but the fermentability of the corn remaining after oil recovery has not been tested. Therefore, a series of pilot scale (50 L) fermentations was carefully controlled and monitored with unique methods for standard inoculation and automatic sampling. It was found that the concentration of suspended solids was significantly reduced in the Quick-Germ fermentations. When compared at the same concentration of fermentable sugars, the fermentation rate and yield were not statistically different from controls. When Quick-Germ was integrated into a state-of-the-art dry-grind fuel ethanol process, computer simulation and cost models indicated savings of approx

Estimating the cost of extracting cereal protein with ethanol

0.01/L of ethanol (

Computer simulation of energy use, greenhouse gas emissions, and process economics of the fluid milk process1

0.04/gal) with the Quick-Germ process. Additional savings associated with the lower suspended solids could not be quantified and were not included. However, the savings are sensitive to the price of corn oil.