• Energy Research

Process monitoring and forecasting are essential to ensure the efficiency of industrial processes. Although it is possible to model processes using phenomenological approaches, these are not always easy to apply and generalize due to the complexity of the processes and the high number of unknown parameters. This work aims to present a hybrid modeling architecture that combines a phenomenological model with machine learning models. The proposal is to enable the use of simplified phenomenological models to explain the basic principles behind a phenomenon. Next, the data-oriented model corrects deviations from the simplified model predictions. The research hypothesis consists of showing the benefits of integrating prior knowledge of chemical engineering in simplifying data-based models, enhancing their generalization and improving their interpretability. The gasification process of lignin biomass with supercritical water was used as a case study for this methodology and the variable to be observed was the production of hydrogen. The real experimental data of this process were augmented using Gibbs energy minimization with the Peng–Robinson equation of state, thus generating a more voluminous database that was considered as real process data. The ideal gas model was used as a simplified model, producing significant deviations in predictions (relative deviations greater than 20%). Deviations (∆H2 = H2real−H2predict) were used as the target variable for the machine learning model. Linear regression models (LASSO and simple linear regression) were used to predict ∆H2 and this variable was added to the simplified forecast model. This consisted of the hybrid prediction of the resulting hydrogen formation (H2predict). Among the verified models, the simple linear regression adjusted better to the values of ∆H2 (R2 = 0.985) and MAE smaller than 0.1. Thus, the proposed hybrid architecture allowed for the prediction of the formation of hydrogen during the gasification process of lignin biomass, despite the thermodynamic limitations of the ideal gas model. Hybridization proved to be robust as a process monitoring tool, providing the abstraction of non-idealities of industrial processes through simple, data-oriented models, without losing predictive power. The objective of the work was fulfilled, presenting a new possibility for the monitoring of real industrial processes.

In the conventional fermentation process to obtain butanol (a novel biofuel), product-induced toxicity results in a product stream with low concentration of butanol (∼13 g/L) and limits the concentration of the sugar solution to less than 60 g/L. As a result, steam-consuming operations such as mash sterilization, downstream product recovery (distillation), and wastewater treatment are energy-intensive and important economic drawbacks. Based on the correlation between energy consumption of the distillation unit and butanol concentration in the fermentation beer, the present research points out that improvements in biobutanol processing intended to increase the concentration of butanol in the beer should have a minimum target of 36 g/L. Moreover, due to the dramatic effect of butanol concentration on the wastewater footprint, the volume of the effluent stream can be reduced by 60% (from 72 to 29 L stillage/L butanol) if the minimum concentration target is reached instead of the usual butanol titer of 13 g/L. These correlations were used as the basis to discuss the impacts of today’s research works (genetic strain improvement, utilization of lignocellulosic biomass feedstock, and development of new process technologies) on the energy consumption for complete dehydration of butanol and on wastewater generation.

The techno-economics of greenfield projects of a first-generation sugarcane biorefinery aimed to produce ethanol, sugar, power, and n-butanol was conducted taking into account different butanol fermentation technologies (regular microorganism and mutant strain with improved butanol yield) and market scenarios (chemicals and automotive fuel). The complete sugarcane biorefinery with the batch acetone-butanol-ethanol (ABE) fermentation process was simulated using Aspen Plus®. The biorefinery was designed to process 2 million tonne sugarcane per year and utilize 25%, 50%, and 25% of the available sugarcane juice to produce sugar, ethanol, and butanol, respectively. The investment on a biorefinery with butanol production showed to be more attractive [14.8% IRR, P(IRR>12%)=0.99] than the conventional 50:50 (ethanol:sugar) annexed plant [13.3% IRR, P(IRR>12%)=0.80] only in the case butanol is produced by an improved microorganism and traded as a chemical.

The objective of this work is to introduce and demonstrate the technical feasibility of the continuous flash fermentation for the production of butanol. The evaluation was carried out through mathematical modeling and computer simulation which is a good approach in such a process development stage. The process consists of three interconnected units, as follows: the fermentor, the cell retention system (tangential microfiltration) and the vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The efficiency of this process was experimentally validated for the ethanol fermentation, whose main results are also shown. With the proposed design the concentration of butanol in the fermentor was lowered from 11.3 to 7.8 g/l, which represented a significant reduction in the inhibitory effect. As a result, the final concentration of butanol was 28.2 g/l for a broth with 140 g/l of glucose. Solvents productivity and yield were, respectively, 11.7 g/l.h and 33.5 % for a sugar conversion of 95.6 %. Positive aspects about the flash fermentation process are the solvents productivity, the use of concentrated sugar solution and the final butanol concentration. The last two features can be responsible for a meaningful reduction in the distillation costs and result in environmental benefits due to lower quantities of wastewater generated by the process.

Worldwide, there are various feedstocks such as straws, corn stover, sugarcane bagasse, sweet sorghum bagasse (SSB), grasses, leaves, whey permeate, household organic waste, and food waste (FW) that can be converted to valuable biofuels such as butanol. For the present studies, an economic analysis was performed to compare butanol production from three feedstocks (SSB; FW; and yellow top presscake, YTP or YT) using a standard process and an advanced integrated process design. The total plant capacity was set at 170,000–171,000 metric tons of total acetone butanol ethanol (ABE) per year (99,300 tons of just butanol per year). Butanol production from SSB typically requires pretreatment, separate hydrolysis, fermentation, and product recovery (SHFR). An advanced process was developed in which the last three steps were combined into a single unit operation for simultaneous saccharification, fermentation, and recovery (SSFR). For the SHFR and SSFR plants, the total capital investments were estimated as $213.72 × 106 and $198.16 × 106, respectively. It was further estimated that the minimum butanol selling price (using SSB as a feedstock) for the two processes were $1.14/kg and $1.05/kg. Therefore, SSFR lowered the production cost markedly compared to that of the base case. Butanol made using FW had an estimated minimum selling price of only $0.42/kg. This low selling price is because the FW to butanol process does not require pretreatment, hydrolysis, and cellulolytic enzymes. For this plant, the total capital investment was projected to be $107.26 × 106. The butanol selling price using YTP as a feedstock was at $0.73/kg and $0.79/kg with total capital investments for SSFR and SHFR of $122.58 × 106 and $132.21 × 106, respectively. In the Results and Discussion section, the availability of different feedstocks in various countries such as Brazil, the European Union, New Zealand, Denmark, and the United States are discussed. Additionally, the use of various microbial strains and product recovery technologies are also discussed.

Abstract n-Butanol produced from renewable resources has attracted increasing interest, mostly for its potential use as liquid biofuel for transportation. Process currently used in the industry (Acetone–Butanol–Ethanol fermentation – ABE) faces major technical challenges, which could be overcome by an alternative production through ethanol catalysis. In this study, both routes are evaluated by means of their financial viabilities and environmental performance assessed through the Virtual Sugarcane Biorefinery methodological framework. Comparative financial analysis of the routes integrated to a first and second generation sugarcane biorefinery shows that, despite the drawbacks, ABE process for fermentation of the pentoses liquor is more attractive than the catalysis of ethanol to n-butanol and co-products. n-Butanol use as fuel demonstrated favorable environmental results for climate change as figures showed over 50% reduction in greenhouse gas emission compared with gasoline.

AbstractEthyl levulinate is a diesel additive that has received special attention recently due to its potential for production in large quantities from inexpensive feedstocks. Several processes have been developed for the conversion of biomass into levulinic acid and ethyl levulinate, and an economic analysis of these routes would indicate the main hindering factors of their commercialization. This Review focuses on filling this gap in current knowledge by gathering data from scientific papers and patents to create a simulation to analyze processes by focusing on the production of ethyl levulinate in nine countries or regions across the globe. The key indicator to analyze the economic feasibility of ethyl levulinate production is a comparison of its minimum selling price to the local wholesale price of diesel on an energy basis. Processes simulated in Brazil, China, and India presented promising results with feedstocks such as sugarcane bagasse and rice residues. Also, the integration of ethyl levulinate production into existing ethanol plants is a factor that may improve process economics. Overall, this Review specifies key factors in economic and environmental performances of the processes to indicate research topics that could achieve high impact on industrial‐scale processes once matured.

In this work, mathematical modeling was employed to assess the dynamic behavior of the flash fermentation process for the production of butanol. This process consists of three interconnected units as follows: fermentor, cell retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). Based on the study of the dynamics of the process, suitable feedback control strategies [single input/single output (SISO) and multiple input/multiple output (MIMO)] were elaborated to deal with disturbances related to the process. The regulatory control consisted of keeping sugar and/or butanol concentrations in the fermentor constant in the face of disturbances in the feed substrate concentration. Another objective was the maintenance of the proper operation of the flash tank (maintenance of the thermodynamic equilibrium of the liquid and vapor phases) considering that oscillations in the temperature in the tank are expected. The servo control consisted of changes in concentration set points. The performance of an advanced controller, the dynamic matrix control, and the classical proportional-integral controller was evaluated. Both controllers were able to regulate the operating conditions in order to accommodate the perturbations with the lowest possible alterations in the process outputs. However, the performance of the PI controller was superior because it showed quicker responses without oscillations.