Optimal engineered algae composition for the integrated simultaneous production of bioethanol and biodiesel

<p>The optimization of the composition of the algae for the simultaneous production of bioethanol and biodiesel is presented. We consider two alternative technologies for the biodiesel synthesis from algae oil, enzymatic or homogeneous alkali catalyzed that are coupled with bioethanol production from algae starch. In order to determine the optimal operating conditions, we not only couple the technologies, but simultaneously optimize the production of both biofuels and heat integrate them while optimizing the water consumption. Multi-effect distillation is included to reduce the energy and cooling water consumption for ethanol dehydration. In both cases, the optimal algae composition results in 60% oil, 30% starch, and 10% protein. The best alternative for the production of biofuels corresponds to a production price of 0.35 $/gal, using enzymes, with energy and water consumption values (4.00 MJ/gal and 0.59 gal/gal).</p

Energy and Water Optimization in Biofuel Plants

In this paper we address the topic of energy and water optimization in the production of bioethanol from corn and switchgrass. We show that in order for these manufacturing processes to be attractive, there is a need to go beyond traditional heat integration and water recycling techniques. Thus, we propose a strategy based on mathematical programming techniques to model and optimize the structure of the processes, and perform heat integration including the use of multi-effect distillation columns and integrated water networks to show that the energy efficiency and water consumption in bioethanol plants can be significantly improved. Specifically, under some circumstances energy can even be produced and the water consumption can be reduced below the values required for the production of gasoline.</p

Optimal Simultaneous Production of Bio-Ibutene and Bioethanol From Switchgrass

<p>In this work, we propose the optimal flowsheet for the production of i-butene from switchgrass. A superstructure embedding a number of alternatives is proposed. Two technologies are considered for switchgrass pretreatment, dilute acid and ammonia fibre explosion (AFEX) so that the structure of the grass is broken down. Surface response models are used to predict the yield. Next, enzymatic hydrolysis follows any of the pretreaments to obtain fermentable sugars, mainly xylose and glucose. I-butene is obtained by fermentation of the sugars. Next it is separated mainly from CO2 for which PSA or membrane separation are considered. However, xylose cannot be easily converted, and thus we also evaluate the possibility of using it to produce bioethanol. The problem is formulated as an MINLP with simultaneous optimization and heat integration. Finally, an economic evaluation is performed. The most promising process involves the use of dilute acid pretreatment and membrane purification of the i-butene. However, the decision related to the production of i-butene alone or the simultaneous production of i-butene and ethanol depends on the prices for bioethanol and for switchgrass.</p

Toward the optimal integrated production of biodiesel with internal recycling of methanol produced from glycerol

<p>In this article, we present the optimization of the production methanol from glycerol and its integration in the production of biodiesel from algae. We propose a limited superstructure where the glycerol from biodiesel is first reformed for which steam reforming and autoreforming are evaluated. The gas obtained is cleaned up and its composition is adjusted in terms of the ratio CO/H2 using three possible alternatives (bypass, PSA and water gas shift). Next, the removal of CO2 is performed by means of PSA and the syngas is fed to the methanol synthesis reactor and the products obtained are separated. This synthesis is coupled with the production of biodiesel from algae using heterogeneous catalyzed reaction based on previous results. The optimization of the system is formulated as a Mixed Integer Nonlinear Programming (MINLP) that is solved for the simultaneous optimization and heat integration of the production of biodiesel with recycle of methanol followed by water integration. The best process involves the use of autoreforming for a production cost of $0.66 gal−1, 3.65 MJ/gal of energy consumption and water consumption of 0.79 gal/gal. The integrated process is$0.2 gal−1 more expensive than the one that directly uses methanol but reduces in more than half the dependency of the process on fossil fuels.</p

Optimal use of Hybrid feedstock, Switchgrass and Shale gas, for the Simultaneous Production of Hydrogen and Liquid Fuels

<p>In this paper, we present a superstructure optimization approach for the integration of the simultaneous production of liquid fuels and hydrogen from switchgrass and shale gas. The process is based on Fischer-Tropsch technology in which the shale gas is reformed with steam, while the switchgrass is gasified and reformed (with steam or partial oxidation). The raw gas is cleaned up and its composition may be adjusted (using either water gas shift reaction or pressure swift adsorption). Next, the sour gases are removed before the liquid fuels are produced using an FT reactor. The heavy liquids are upgraded using hydrocracking to increase the yield towards FT-diesel. A sensitivity study on the raw material prices reveals that production costs for the biomass-shale gas facility are below $1/gal as long as biomass price is below$100/t and the price of the shale gas is not higher than $11.5/MMBTU. Furthermore, hydrogen is produced as long as the demand for liquid fuels can be met and there is enough shale gas available.</p

Energy optimization of Hydrogen production from biomass

In this paper we address the conceptual design for the production of hydrogen from switchgrass. The process is modeled as a mixed-integer non linear programming problem (MINLP) for a superstructure embedding two different gasification technologies, direct and indirect, and two reforming modes, partial oxidation or steam reforming, gas cleaning and a water gas shift reactor (WGSR) with membrane separation is used to obtain pure hydrogen. Given the small number of structural alternatives, the problem is solved by constraining the binary variables of the MINLP so as to select each gasifier and reforming mode yielding four NLP's. Next, the energy is integrated, and finally, an economic evaluation is performed. It is shown that indirect gasification with steam reforming is the preferred technology providing higher production yields than the ones reported in the literature for hydrogen from natural gas and at a potentially lower and promising production cost 0.67$/kg.</p

Energy optimization of bioethanol production via gasification of switchgrass

In this article, we address the conceptual design of the bioethanol process from switchgrass via gasification. A superstructure is postulated for optimizing energy use that embeds direct or indirect gasification, followed by steam reforming or partial oxidation. Next, the gas composition is adjusted with membrane-PSA or water gas shift. Membrane separation, absorption with ethanol-amines and PSA are considered for the removal of sour gases. Finally, two synthetic paths are considered, high alcohols catalytic process with two possible distillation sequences, and syngas fermentation with distillation, corn grits, molecular sieves and pervaporation as alternative dehydration processes. The optimization of the superstructure is formulated as an mixed-integer nonlinear programming problem using short-cut models, and solved through a special decomposition scheme that is followed by heat integration. The optimal process consists of direct gasification followed by steam reforming, removal of the excess of hydrogen and catalytic synthesis, yielding a potential operating cost of $0.41/gal. </p

Review of optimization models for integrated process water networks and their application to biofuel processes

<p>This paper provides an overview of recent development in the area of optimal synthesis of process water networks in which a major goal is to reduce the freshwater consumption by the reuse and recycle of process and treatment streams. The recent models can globally optimize these networks through mixed-integer nonlinear programming techniques. We discuss the application and impact of these techniques to biofuel plants, which are known to consume large amounts of water.</p

Optimal integration for biodiesel production using bioethanol

<p>The production of biodiesel from algae is optimized using bioethanol following four different transesterification paths: alkali, enzymatic, and heterogeneous catalysts and supercritical conditions. The reactors are modeled using response surface methodology based on experimental results from the literature. These reactor models are implemented together with short-cut methods for the other equipment (distillation columns, gravity separators, etc.) in order to recover the ethanol, separate the polar and nonpolar phases, and purify the glycerol and biodiesel produced to formulate the problem as a superstructure of alternatives. The aim is to simultaneously optimize and heat integrate the production of biodiesel using ethanol in terms of the reaction technology and the operating conditions. The optimal conditions in the reactors differ from the ones traditionally used because these results take the separation stages into account. In terms of the optimal process, the alkali catalyzed process is the most profitable, while the enzymatic one is also promising due to the lower consumption of energy and water, although it requires significant enzyme cost. </p

A Simple Heuristic for Reducing the Number of Scenarios in Two-stage Stochastic Programming

In this work we address the problem of solving multiscenario optimization models that are deterministic equivalents of two-stage stochastic programs. We present a heuristic approximation strategy where we reduce the number of scenarios and obtain an approximation of the original multiscenario optimization problem. In this strategy, a subset of the given set of scenarios is selected based on a proposed criterion and probabilities are assigned to the occurrence of the reduced set of scenarios. The original stochastic programming model is converted into a deterministic equivalent using the reduced set of scenarios. A mixed-integer linear program (MILP) is proposed for the reduced scenario selection. We apply this practical heuristic strategy to four numerical examples and show that reformulating and solving the stochastic program with the reduced set of scenarios yields an objective value close to the optimum of the original multiscenario problem.</p