Mariano Martín

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.

Energy, Water and Process Technologies Integration for the Simultaneous Production of Ethanol and Food from the entire Corn Plant

Abstract This contribution presents the simultaneous integration of different technologies for converting different parts of the corn plant, and integration of energy, water and feedstocks. The traditional dry-grind process is used for obtaining ethanol from corn grains, whilst for the conversion of corn stover to ethanol, gasification using two different paths of syngas conversion is taken into account: syngas fermentation (thermo-biochemical path) and catalytic mixed alcohol synthesis (thermo-chemical path). These processes are modelled in the Mixed-Integer Process Synthesizer (MIPSYN) using mass and energy balances and conversion constraints. Short cut models for the more complex process units are obtained from the detailed ones, as developed by Martin and Grossmann (2011) . The results show that the best integrated process when using the entire corn plant is a combination of the dry-grind process and thermo-chemical conversion. For the base case (18 kg/s of grain and 10.8 kg/s of stover), the optimal scheme is comprised of dry-grind and thermo-chemical conversion technologies. The best integrated process requires only 17 MW of energy, 50 MW of cooling and 1.56 L/L of freshwater, with an ethanol production cost of 0.41

Energy optimization of hydrogen production from lignocellulosic biomass

/kg. In the thermal conversion, the integration of energy plays the more important role when reducing production costs. Since the thermo-chemical path enables better heat integration, it is preferred over the thermo-biochemical in spite of the higher yield and sharing of equipment, when using the syngas fermentation path.

A simple heuristic for reducing the number of scenarios in two-stage stochastic programming

Abstract 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 NLPs. 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

Role of μ-opioid receptors in insulin release in the presence of inhibitory and excitatory secretagogues

/kg.

Superstructure optimization of Lignocellulosic Bioethanol plants

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 scenarios in the reduced set. 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.

Multi-period Synthesis of a Biorefinery's Supply Networks

In mouse pancreatic islets incubated under static conditions, the inhibitory effects on glucose-evoked insulin release induced by adrenaline (1 microM), clonidine (2 microM) and UK 14,304 (brimonidine, 0.001-1 microM) were abolished by naloxone (30 nM). Only CTOP (D-Phe-Cys-Tyr-D-Trp-Orn-Thr-Phe-Thr-NH(2), 0.1 microM), a very selective mu-opioid receptor antagonist, blocked the response to UK 14,304. Glucose-induced insulin secretion was attenuated by both beta-endorphin (0.01 microM) and endomorphin-1 (0.1 microM). Naloxone and CTOP prevented these inhibitory responses. The stimulatory effect of glibenclamide (1 microM) was also reduced by endomorphin-1. However, when islets were incubated in the presence of K(+) (30 mM), carbachol (100 microM) or forskolin (0.1 microM), neither the inhibitory effect induced by UK 14,304 was reversed by naloxone, nor endomorphin-1 altered the responses promoted by the excitatory agents. Thus, alpha(2)-adrenoceptor stimulation might inhibit glucose-induced insulin secretion by releasing endogenous opioids. Mu-Opioid receptor activation and opening of K(ATP) channels could be involved in the response.

Large-Scale Biorefinery Supply Network – Case Study of the European Union

Abstract In this paper we present the superstructure optimization for the production of bioethanol via gasification of lignocellulosic material, switch grass. We describe the alternatives considered for the superstructure, which mainly include two types of gasification, different clean up processes and two different synthetic paths, catalytic and fermentation. We optimize the superstructure using a special decomposition technique. The results obtained are promising for the profitability of lignocellulosic ethanol since the energy consumed (20MW) and the production cost (0.66

BIOpt: A library of models for optimization of biofuel production processes

/gal) are both lower than the optimized values for corn-based bioethanol plants.

A multi-objective optimization approach for the selection of working fluids of geothermal facilities: Economic, environmental and social aspects

Abstract This contribution presents a multi-period synthesis of an optimally-integrated regional biorefinerys supply networks, based on a Mixed-Integer Linear Programming (MILP) model. The production processes from different sources of biomass include first, second, and third generations of biofuels such as bioethanol, biodiesel, hydrogen, Fischer-Tropsch (FT)-diesel, and green gasoline. The aim is to maximize the economically optimal utilization of seasonal and year-round continuously harvested raw materials from regionally-located available biomass resources, by considering the competition between fuels and food production. The proposed multi-period MILP model enables efficient bioenergy network synthesis and optimization. Economically optimal solutions are obtained, with optimal selection of technologies, raw materials, intermediate and final products, and the timely-optimal planning of harvesting, biofuels production, storage, and logistics.