期刊
BIOCHEMICAL ENGINEERING JOURNAL
卷 124, 期 -, 页码 13-25出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.bej.2017.04.008
关键词
Second generation bioethanol plant; Nonlinear model-based optimization; Uncertainty and sensitivity analysis; Steam pretreatment; Enzymatic hydrolysis; C5 and C6 co-fermentation
Second generation biorefineries transform lignocellulosic biomass into chemicals with higher added value following a conversion mechanism that consists of: pretreatment, enzymatic hydrolysis, fermentation and purification. The objective of this study is to identify the optimal operational point with respect to maximum economic profit of a large scale biorefinery plant using a systematic model-based plantwide optimization methodology. The following key process parameters are identified as decision variables: pretreatment temperature, enzyme dosage in enzymatic hydrolysis, and yeast loading per batch in fermentation. The plant is treated in an integrated manner taking into account the interactions and trade-offs between the conversion steps. A sensitivity and uncertainty analysis follows at the optimal solution considering both model and feed parameters. It is found that the optimal point is more sensitive to feed-stock composition than to model parameters, and that the optimization supervisory layer as part of a plantwide automation system has the following benefits: (1) increases the economical profit, (2) flattens the objective function allowing a wider range of operation without negative impact on profit, and (3) reduces considerably the uncertainty on profit. (c) 2017 Elsevier B.V. All rights reserved.
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