Process Systems Engineering
Optimal integration for biodiesel production using bioethanol
Article first published online: 13 JUL 2012
DOI: 10.1002/aic.13865
Copyright © 2012 American Institute of Chemical Engineers (AIChE)
Additional Information
How to Cite
Severson, K., Martín, M. and Grossmann, I. E. (2013), Optimal integration for biodiesel production using bioethanol. AIChE J., 59: 834–844. doi: 10.1002/aic.13865
Publication History
- Issue published online: 20 FEB 2013
- Article first published online: 13 JUL 2012
- Accepted manuscript online: 7 JUN 2012 02:39PM EST
- Manuscript Revised: 24 MAY 2012
- Manuscript Received: 7 FEB 2012
Funded by
- NSF. Grant Number: CBET0966524
- Center for Advanced Process Decision-Making at Carnegie Mellon University
- Abstract
- Article
- References
- Cited By
Keywords:
- energy;
- biofuels;
- biodiesel;
- mathematical optimization;
- algae
The production of biodiesel from algae is optimized using bioethanol following four different transesterification paths: alkali, enzymatic, and heterogeneous catalysts and supercritical conditions. The reactors are modeled using response surface methodology based on experimental results from the literature. These reactor models are implemented together with short-cut methods for the other equipment (distillation columns, gravity separators, etc.) in order to recover the ethanol, separate the polar and nonpolar phases, and purify the glycerol and biodiesel produced to formulate the problem as a superstructure of alternatives. The aim is to simultaneously optimize and heat integrate the production of biodiesel using ethanol in terms of the reaction technology and the operating conditions. The optimal conditions in the reactors differ from the ones traditionally used because these results take the separation stages into account. In terms of the optimal process, the alkali catalyzed process is the most profitable, while the enzymatic one is also promising due to the lower consumption of energy and water, although it requires significant enzyme cost. © 2012 American Institute of Chemical Engineers AIChE J, 59: 834–844, 2013

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