9-14: Developing a flexible model of cradle to gate biomass processing with multiple technologies

Tuesday, May 3, 2011
Bryan D. Bals1, Pragnya Eranki2, Julie Sinistore3, Seungdo Kim2, Doug Reinemann3 and Bruce Dale2, (1)Great Lakes Bioenergy Research Center, Michigan State University, Lansing, MI, (2)Chemical Engineering and Materials Science, Michigan State University, Lansing, MI, (3)University of Wisconsin, Madison, WI
There is an urgent need for accurate environmental and economic models representing the entire logistical chain of biofuel production.  Models are often inflexibly designed, difficult to adapt, and intended for a single technology.  In particular, very little emphasis is placed on intermediate processing between the farm and the refinery gate, nor for multiple co-products or alternative products.  One approach to biomass logistics is to create Regional Biomass Processing Depots (RBPDs), intermediate rural industrial sites that process, densify, and upgrade biomass into multiple commodity products. 

We aim to develop a flexible model using GaBi Life Cycle Analysis software to provide rapid economic, environmental, and energetic analyses of multiple agricultural landscapes and technology packages.  Using crop modeling data from the Great Lakes Bioenergy Research Center (GLBRC), we will develop agricultural landscapes with sustainable nitrogen and carbon balances which provide ample biomass for energy and animal feeding practices.  This biomass will be processed in various scenarios (with and without RBPDs, at standalone biorefineries or co-located at coal-fired power plants, with and without alternate technologies for advanced co-products).  Process flows of each technology will be developed in GaBi while simultaneously used to develop preliminary cost/revenue models.  These processes will be adapted to each type of biomass, as well as combinations of technologies that can share resources such as heat integration.  By designing a flexible model to deal with the supply chain, virtually limitless analyses and sensitivities can be rapidly performed, identifying promising areas of research and further development.

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