Optimal Biorefinery Resource Utilization by Combining Process and Economic Modeling
Multi-scale and/or multi-disciplinary approach to process-product innovation
Integrated Methodologies for Process Development (T3-7)
Keywords: Biorefining, process economics, process integration
The integrated biorefinery, which uses renewable feedstocks from the forest-based industries, has the opportunity to provide a strong, self-dependent, sustainable alternative for the production of bulk and fine chemicals from polymers, fiber composites and pharmaceuticals to energy, liquid fuels and hydrogen.
With such a wide range of processing steps and possible products, it is obvious that identification of the optimum process structure can not be done based on heuristics or rules of thumb. Depending on market prices and trends, the optimum allocation of resources and production capacity may switch between the different products. 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. Thus there is a need for systematic, reliable methods capable of incorporating different levels of process detail in the decision making framework.
In this work a mathematical optimization based framework is being developed, which enables the inclusion of profitability measures and other techno-economic metrics along with process insights and performance characteristics obtained from experimental and modeling studies. By utilizing process integration methods, the processing steps can be optimized to ensure efficient use of energy and materials resources while assuring an acceptable, minimal level of environmental impact through the use of EPA's WAR algorithm. A novel feature of the proposed framework is the decoupling of the complex models from the selection step, which enables adaptation to new developments within any of the processing steps and thus can incorporate novel innovative production processes in the decision-making framework. This decoupling enables more efficient solution of the production optimization/allocation problem as the non-linearities embedded in the process models have been removed. Collaboration with key stakeholders in industry, academia and government has been established enabling access to proprietary process specifics and business models. 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.
See the full pdf manuscript of the abstract.
Presented Thursday 20, 15:00 to 15:20, in session Integrated Methodologies for Process Development (T3-7).
