Integration of flux balance analysis and techno-economic-environmental analyses to optimize bioethanol production by extractive fermentation

• Grant number: 24/02416-4
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: July 01, 2024
• End date: February 28, 2027
• Field of knowledge: Engineering - Chemical Engineering - Chemical Process Industries
• Principal Investigator: Felipe Fernando Furlan
• Grantee: Gabriel Baioni e Silva
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

In recent decades, biofuels have emerged as alternatives to fossil fuels, with the aim of mitigating global challenges related to energy security and greenhouse gas emissions. In Brazil, the compulsory blending of anhydrous ethanol into gasoline has considerably boosted the production and use of this biofuel, helping to reduce emissions. Despite the environmental advantages, ethanol production faces challenges, such as the inhibition of microbial growth due to high ethanol concentrations. Extractive fermentation has emerged as a promising approach to optimizing production, allowing the continuous removal of ethanol during the process and reducing its inhibitory effect. This study aims to investigate optimal control strategies for extractive fermentation, taking into account the techno-economic and environmental aspects of operating the industrial process. The methodology involves collecting and validating initial kinetic parameters, developing a surrogate model with a techno-economic and environmental analysis of a standard plant, implementing a dynamic metabolic flow model and integrating the models to optimize the process. The models developed will generate techno-economic and environmental indicators to determine optimal operating conditions. This will include evaluating the yield of the process, providing a detailed overview of the performance of extractive fermentation. Economic indicators such as Net Present Value (NPV) and Internal Rate of Return (IRR) will be calculated to determine the economic viability of the process. Life cycle analysis will be carried out to assess environmental impacts. Integrating the indicators with optimization techniques will make it possible to estimate optimum operating conditions in order to maximize economic indicators. The results will be validated experimentally, providing perspectives for improving the process, making it more efficient and sustainable.