(226c) Sensitivity and Uncertainty Analysis of Updated Corn Stover to Ethanol Process Design and Economic Models

Tao, L., National Renewable Energy Laboratory
Humbird, D., National Renewable Energy Laboratory
Aden, A., National Renewable Energy Laboratory
Tan, E. C. D., National Renewable Energy Laboratory

The Energy Independence and Security Act of 2007 (EISA 2007)1 mandates 36 billion gallons per year of renewable fuel by 2022, of which 15 billion gallons are traditional or corn-based, and 16 billion are derived from cellulosic biomass. In order for cellulosic biofuel production to ramp in 2012 as dictated by the EISA, it becomes increasingly important to understand its production economics. This information is used to predict the cost-competitiveness of cellulosic biofuels with petroleum-derived fuels and corn ethanol. A number of different conversion technologies exist for the conversion of cellulosic biomass to a liquid fuel. Our (National Renewable Energy Laboratory, NREL) efforts have been focused on both biochemical and thermochemical conversion to ethanol. In biochemical conversion, biocatalysts such as enzymes and microorganisms are used along with heat and chemicals to first convert biomass to an intermediate mixed sugar stream and then to ethanol or other fermentative biofuel. Researchers of NREL have described such processes in technical and economic detail in two previous design reports (Aden et al. 20022; Wooley et al. 19993). We have updated the ongoing process design in the last AIChE meeting, with the most current data and integration efforts at NREL as well as research funded by the US Department of Energy (DOE), and other sources (e.g., industry, academia). In this paper, alternative process conditions and parameters influencing the biofuel production cost are studied using sensitivity and uncertainty analysis. We have focused our studies on three major areas, feedstock compositional variability, yield variability and financial assumptions variability. Different feedstocks (or compositional variation of the same feedstock) can have a significant impact on equipment design, raw material utilization, utilities, and overall process economics. Feedstock compositional variability data was taken from a previous NREL study that evaluated compositions for 508 commercial hybrid corn stover samples collected from 47 sites in eight Corn Belt states after the 2001, 2002, and 2003 harvests (Templeton, et al., 2009)4. Monte Carlo analysis is carried out in order to assess the probability distribution of the production cost in order study potential interactions among parameters studied. The target of this sensitivity analysis is to provide an understanding of the impact of likely process variables and how these might be controlled to a definable degree.


(1) EISA. EISA of 2007 Calls for Additional Production of Biofuels. http://www.renewableenergyworld.com/rea/partner/stoel-rives-6442/news/ar.... 2007.

(2) Ibsen, K., Jechura J, Neeves, K., Sheehan, J., Wallace, R. Lignocellulosic Biomass to Ethanol Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis For Corn Stover. 2002. NREL Report NREL/TP-510-32438, http://www.nrel.gov/docs/fy02osti/32438.pdf

(3) Wooley, R., Ruth, M., Glassner, D., Sheehan, J. Process Design and Costing of Bioethanol Technology: a Tool for Determining the Status and Direction of Research and Development. Biotechnology Progress, 1999, 15(5), 794-803.

(4) Templeton D.W., Sluiter A.D., Hayward T.K. Hames B.R., and Thomas S.R., Assessing Corn Stover Composition and Sources of Variability via NIR, Cellulose, 16(4), 2009.