Production of ethanol fuel via syngas fermentation
Optimization of economic performance and energy efficiency
E. de Medeiros (TU Delft - BT/Bioprocess Engineering, University of Campinas)
HJ Noorman (TU Delft - BT/Bioprocess Engineering, DSM)
Rubens Maciel Filho (University of Campinas)
J.A. Posada-Duque (TU Delft - BT/Biotechnology and Society)
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Abstract
In this work, a model was developed to predict the performance of a bubble column reactor for syngas fermentation and the subsequent recovery of anhydrous ethanol. The model was embedded in an optimization framework which employs surrogate models (artificial neural networks) and multi-objective genetic algorithm to optimize different process conditions and design variables with objectives related to investment, minimum selling price, energy efficiency and bioreactor productivity. The results indicate the optimal trade-offs between these objectives while providing a range of solutions such that, if desired, a single solution can be picked, depending on the priority conferred to different process targets. The Pareto-optimal values of the decision variables were discussed for different case studies with and without the recovery unit. It was shown that enhancing the gas-liquid mass transfer coefficient is a key strategy toward sustainability improvement.
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