(573ae) Biorefinery Product Allocation Using a Flexible Optimization Framework | AIChE

(573ae) Biorefinery Product Allocation Using a Flexible Optimization Framework

Authors 

Yuan, W. - Presenter, Auburn University
Bommareddy, S. - Presenter, Auburn University


The forest based industries of the nation possess tremendous unrealized potential for the production of multiple, high-value added products from renewable biomass resources. These products range from bulk and fine chemicals through polymers, fiber composites and pharmaceuticals to energy, liquid fuels and hydrogen. This concept of an integrated biorefinery has the opportunity to provide a strong, self-dependent, sustainable alternative for the production of chemicals and fuels. A fundamental requirement to achieve this vision is the availability of concentrated, low-cost, easily available biomass resources as inputs into the biorefinery. Changing market conditions may dictate a dynamic optimum for the allocation of resources and production capacity, resulting in a myriad of possible long-term product portfolios and a need for a net present value perspective which takes into account the time value of money. Economic market analysis, predictive financial modeling, and optimization under uncertainty are tools that can be used to determine the sensitivity of a decision-making framework to market fluctuations. By constructing simulation models for various biorefining processes, determining variable and fixed cost components of these processes, and combining this cost data with information on expected return and market conditions, firms interested in biorefining will be able to determine the effects of changes in shareholder value as a result of deciding which products to pursue among the many biorefinery possibilities. This can be done while assuring an acceptable, minimal level of environmental impact through the use of EPA's WAR algorithm. An inherent benefit of the proposed framework comes from the decoupling of the complex models from the selection step, which results in the ability to adapt to new developments within any of the processing steps and thus also incorporate novel innovative production processes in the decision-making framework. In this way, experimental and theoretical efforts can supplement each other in a synergistic manner, by providing direction and data for continued work. This contribution will illustrate the strategy for developing the decision making framework as well as highlighting the flexibility of the framework to utilize data from technological breakthroughs in the field of biorefining.