470769 Use of Multi-Objective Optimization for Selecting Optimally Integrated Biorefinery Processes
In this study, a systematic process design methodology which incorporates process optimization and energy integration is applied to assess the thermo-economic performance, the environmental impact and the energy requirement for several processing pathway options. A superstructure of process models in a lignocellulosic biorefinery converting the feedstock in sugars (biochemical conversion) and syngas (thermochemical conversion) platforms for different bio-based fuels and valuable chemicals is developed. The heat recovery is represented by characterizing the process units energy requirement using pinch analysis.
Multi-objective optimization is implemented, using different objective functions such as economic and environmental criteria that are simultaneously considered to show the trade-offs between these conflicting objectives. Different performance targets are established to compare the alternative designs, to increase the utilization of biogenic carbon and to understand the best combination of products and the synergies between them. The overall design problem is formulated as mixed integer linear programming (MILP) optimization problem and epsilon-constraint method is combined with integer cut constraints (ICC) algorithm to systematically generate the list of competing options in a Pareto front. The results of the proposed approach provide a set of non-dominated solutions (i.e., Pareto front), and each solution shows different biorefinery configuration. Finally, these trade-off solutions can be used as a decision support for engineers and decision-makers to identify the best biorefinery pathways.
Keywords: Integrated Biorefinery Systems, Process Design, Process Integration, Multi-Objective Optimization