Modeling optimal alcohol production from various agricultural crops



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Texas Tech University


The ethanol industry of today faces the challenge of modernizing its operations by optimization. The goal of this research was to create a model that could be used by the distillery personnel as a means of increasing their operations output for a given input condition.

The approach to the model development was to study the weakness of three different features of the ethanol industry. First, the necessity of developing a model to predict microbial growth in the fermentation process was recognized. A model was developed assuming competition among the microbes and limited substrate, and verified with data obtained from ethanol producers.

The second feature of this optimization was the hypothesis that if a surplus of low pressure steam was available in the distillery, it could be used to pre-cook the crop. A study was conducted to evaluate the effects of thermally treating buffalo gourd roots in an attempt to decrease electrical power consumption during the grinding process. A model was derived to predict the pre-cooking effects on substrate grinding.

The optimization model was completed with an auxiliary consideration that can help to size the optimal required cultivated area and ethanol storage capacity.

Based on specific scenarios, it was concluded that optimization could help the distillery improve efficiency in the three aspects of the alcohol production microbial growth, grinding, and inventory. In optimizing these operations, additional benefits with a minimal capital investment could be obtained, making the alcohol industry more competitive.