(204l) Optimal Design of a Bioethanol Supply Chain Utilizing a Biochemical Production Pathway Via An MILP Model | AIChE

(204l) Optimal Design of a Bioethanol Supply Chain Utilizing a Biochemical Production Pathway Via An MILP Model

Authors 

Raftery, J. - Presenter, Texas A&M University
Karim, M. N., Texas A&M University



Petroleum derived energy sources such as gasoline are generally expensive, nonrenewable, and can negatively impact the environment during production and use. Because of this, green energy alternatives have been investigated. At the forefront of these alternatives is the production of ethanol from lignocellulosic biomass. Mainstream production of biologically derived ethanol is done via gasification and pyrolysis using a syngas intermediate. An alternative conversion method is done via a biochemical reaction pathway, converting the plant material to simple sugars that can be further processed into ethanol. However, this process must be able to compete with the production levels and efficiency of the thermochemical pathway as well as the current petroleum industry.

Our research focuses on the supply chain optimization of bioethanol production utilizing biochemical pathways and sugar intermediates. Our current interest includes the effects of various pretreatment methods, used in the enzymatic saccharification and fermentation of cellulosic biomass, on the economic viability of the bioethanol production supply chain. Pretreatment of the biomass involves the breakdown of lignin and the rigid cell wall, leading to greater accessibility of enzymes to the cellulosic material in further downstream processing. Many pretreatment options have been widely studied, each requiring different considerations in process development. Our research focuses on four of these technologies, ammonia fiber explosion (AFEX™), liquid hot water, alkali and dilute acid, as investigated within the Biomass Refining Consortium for Applied Fundamentals and Innovation (CAFI).[1][2]We investigate these pretreatment methods, while also considering various types of biomass feedstocks, to determine an optimal configuration of the supply chain network that gives the most competitive ethanol selling price.

To do this, a mixed integer linear program for the entire supply chain is developed and optimized. This model takes into account multiple plant size, pretreatment and feedstock options, the capital and operating costs associated with these options, and the cost of transportation of raw materials and final products. For this model, three different biomass alternatives, corn stover, switchgrass and wood, are investigated as feedstocks to the process. Supply and demand limits are set on the amount of biomass available for processing and the ethanol produced. The solution to this mixed integer linear program yields the optimal configuration of a biochemical ethanol supply chain that gives the lowest ethanol selling price to maintain process profitability.

  1. Tao, Ling et al. “Process and Technoeconomic Analysis of Leading Pretreatment Technologies for Lignocellulosic Ethanol Production Using Switchgrass.” Bioresource Technology 102.24 (2011): 11105–11114
  2. Elander, Richard T. et al. “Summary of findings from the Biomass Refining Consortium for Applied Fundamentals and Innovation (CAFI): corn stover pretreatment.” Cellulose 16.4 (2009): 649–659.

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