282001 Feed Flexible Process Optimization Model for Region Specific Sustainable Biorefining

Tuesday, October 30, 2012: 4:55 PM
336 (Convention Center )
Sumesh Sukumara1, Jeffrey R. Seay2, Dr. Fazleena Badurdeen3, William Faulkner4 and Joseph Amundson4, (1)Chemical and Materials Engineering, University of Kentucky, Lexington, KY, (2)Department of Chemical and Materials Engineering, University of Kentucky, Paducah, KY, (3)Institute for Sustainable Manufacturing, University of Kentucky, Lexington, KY, (4)University of Kentucky, Lexington, KY

Biofuels in recent years has emerged as one of the most promising alternatives to replace fossil fuel. Researchers around the world are working on developing new processes and improve existing ones to convert biomass into various marketable products. Integrated biorefining is a possibility which combines a slate of processes involving various feedstock to produce transportation fuel, electric power and other useful chemical products. Also, due to the seasonal and regional variability of feedstock, the overall supply chain has to be looked at carefully. Thus, a multidisciplinary economic model needs to be developed which incorporates various small models and allows each to exchange information. According to the existing literature and preliminary experiments performed its evident that transportation and processing cost share a significant portion of the overall cost of an integrated biorefinery. This novel contribution aims to show how a feed flexible process optimization model can be developed and interact with the overall region specific optimization model.

            Processing cost in a biorefinery is mainly due to the utilities and raw materials involved. The model developed applies various concepts of chemical engineering to minimize the utilities and maximize the profitability for any given process in a region. Various modules of the Aspen Engineering Suite are combined to achieve the required objective. The process optimization model to be described consists of two major processes to produce transportation fuel and power as end products. These models are first developed considering all the possible mass and heat streams involved to get various products. A thermal pinch analysis is performed to find the best possible heat integration practically possible for a process. Based on the optimum heat exchanger network the process simulations are changed accordingly and finally the capital costs are estimated for the process. The process optimization model developed transfers its data with a Visual Basic interface to the other models which eventually estimates the overall profitability of the process. This model will be validated using the Jackson Purchase region of Western Kentucky, which is not only rich in coal, lignocellulosic biomass and crop residue but also has large number of poultry farms, as a case study. The robust model developed can be run for various combinations of feedstock possible. These process simulation results coupled with the overall supply chain model can predict some critical conclusions like profitability, optimum feed ratio, utility requirement and also some sensitive process variable that effect the overall supply chain of the biorefining process. This innovative linking of various optimization models will help develop a large scale multivariable model for biorefining which will include all possible feedstocks for a given region and provide the option to choose from various available processes in the model based on the cost, demand and environmental regulations in a region. Hence the multiple feedstock process optimization model developed supports the overall supply chain model based on which investors can check the economics of a process and decide if an investment is worthy in a given region.


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See more of this Session: Sustainable Fuels From Renewable Resources II
See more of this Group/Topical: Sustainable Engineering Forum