On-line identification of fermentation processes for ethanol production

被引:5
|
作者
Camara, M. M. [1 ]
Soares, R. M. [1 ,2 ]
Feital, T. [1 ,2 ]
Naomi, P. [3 ]
Oki, S. [3 ]
Thevelein, J. M. [3 ,4 ]
Amaral, M. [3 ]
Pinto, J. C. [1 ]
机构
[1] Univ Fed Rio de Janeiro, COPPE, Programa Engn Quim, CP 68502, BR-21941972 Rio De Janeiro, RJ, Brazil
[2] OptimaTech, Rio De Janeiro, RJ, Brazil
[3] Global Yeast, Rio De Janeiro, RJ, Brazil
[4] VIB, Dept Mol Microbiol, Kasteelpk Arenberg 31, B-3001 Leuven Heverlee, Flanders, Belgium
关键词
Dry grind corn ethanol; SSF process; Ethanol fermentation; Soft sensor; Process monitoring; SIMULTANEOUS SACCHARIFICATION; PARAMETER-ESTIMATION; DATA RECONCILIATION; RENEWABLE ENERGY; CORN MASH; BIOPROCESS; OPTIMIZATION; MODEL; BIOMASS; STARCH;
D O I
10.1007/s00449-017-1762-6
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. This new tool provides a great support for decision-making and opens a new range of opportunities for industrial optimization.
引用
收藏
页码:989 / 1006
页数:18
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