Water Pinch Analysis of a Lignocellulosic Ethanol Production Process - Development of an Excel application for multiple contaminants

Abstract

The renewable fuels industry is faced with significant challenges related to increasing concerns about global warming and environmental impact. Bio-ethanol is a renewable fuel produced in large quantities, and its productions needs to be improved continuously, in particularly with respect to fresh water usage and waste-water effluent. This thesis uses a methodology for establishing targets and identifying design configurations for reduced fresh water usage and waste water effluent for a lignocellulosic bio-ethanol production plant. One of the major challenges for this type of analysis is the ability to take multiple contaminants into account. The objective of this thesis was to develop an analysis tool that is able to handle up to three types of contaminants. The work resulted in an application for Microsoft Excel that calculates targets for the minimum fresh water usage and waste water effluent release of a given process and proposes a water network configuration that is able to achieve these targets. The tool is based on methodologies proposed by Zhang et al. (2013). A simpler analysis and design tool with the capacity to handle a single contaminant only based on Foo (2013) was also developed for comparison purposes. Trying to perform a water pinch analysis revealed problems related to setting reasonable constraints for the maximum level of contaminant concentrations that the process units in the ethanol production process can tolerate. The results presented should only be considered as preliminary suggestions for opportunities to improve this type of process. For the lignocellulosic bio-ethanol process investigated, the single contaminant analysis tool indicates that the fresh water usage could be decreased by up to 23%. However, when three different types of contaminant are considered in the analysis, the potential fresh water savings are reduced to 13%, which underlines the importance of considered multiple contaminants in the analysis. The potential savings presented for single contaminants are on the same order of magnitude as numbers found in the literature.