Caliane Bastos Borba Costa

Bioelectricity versus bioethanol from sugarcane bagasse: is it worth being flexible?

BackgroundSugarcane is the most efficient crop for production of (1G) ethanol. Additionally, sugarcane bagasse can be used to produce (2G) ethanol. However, the manufacture of 2G ethanol in large scale is not a consolidated process yet. Thus, a detailed economic analysis, based on consistent simulations of the process, is worthwhile. Moreover, both ethanol and electric energy markets have been extremely volatile in Brazil, which suggests that a flexible biorefinery, able to switch between 2G ethanol and electric energy production, could be an option to absorb fluctuations in relative prices. Simulations of three cases were run using the software EMSO: production of 1G ethanol + electric energy, of 1G + 2G ethanol and a flexible biorefinery. Bagasse for 2G ethanol was pretreated with a weak acid solution, followed by enzymatic hydrolysis, while 50% of sugarcane trash (mostly leaves) was used as surplus fuel.ResultsWith maximum diversion of bagasse to 2G ethanol (74% of the total), an increase of 25.8% in ethanol production (reaching 115.2 L/tonne of sugarcane) was achieved. An increase of 21.1% in the current ethanol price would be enough to make all three biorefineries economically viable (11.5% for the 1G + 2G dedicated biorefinery). For 2012 prices, the flexible biorefinery presented a lower Internal Rate of Return (IRR) than the 1G + 2G dedicated biorefinery. The impact of electric energy prices (auction and spot market) and of enzyme costs on the IRR was not as significant as it would be expected.ConclusionsFor current market prices in Brazil, not even production of 1G bioethanol is economically feasible. However, the 1G + 2G dedicated biorefinery is closer to feasibility than the conventional 1G + electric energy industrial plant. Besides, the IRR of the 1G + 2G biorefinery is more sensitive with respect to the price of ethanol, and an increase of 11.5% in this value would be enough to achieve feasibility. The ability of the flexible biorefinery to take advantage of seasonal fluctuations does not make up for its higher investment cost, in the present scenario.

Assessing the production of first and second generation bioethanol from sugarcane through the integration of global optimization and process detailed modeling

Abstract There is a worldwide effort to make economically feasible the use of lignocellulosic biomass for production of biofuels. In sugarcane industry, cane juice (sucrose) is fermented for bioethanol production. Sugarcane bagasse is used as fuel in cogeneration systems, to produce steam and electric power to the plant, and the surplus of electric power may be delivered to the grid. The hydrolysis of bagasse to produce second generation ethanol poses a challenge: how much bagasse can be diverted, since the process must continue energetically self-sufficient. This work presents a computational tool developed within an equation-oriented process simulator that couples the simulation of first and second generation bioethanol production with a global optimization algorithm. The tool was robust, optimizing the steady state process in any economic scenario and for different process configurations. Four case studies are presented, and their implications on process internal demands and on the surplus electrical power are discussed.

Analysis of the particle swarm algorithm in the optimization of a three-phase slurry catalytic reactor

Abstract The Particle Swarm Optimization (PSO) method was employed to optimize an industrial chemical process characterized by being difficult to be optimized by conventional deterministic methods. The chemical process is a three phase catalytic slurry reactor (tubular geometry) in which the reaction of the hydrogenation of o-cresol producing 2-methyl-cyclohexanol is carried out. The optimization problem was formulated considering as input variables the operating conditions of the reactor and as objective function the maximization of productivity, subject to the environmental constraint of conversion. The process was represented by a multivariable non-linear rigorous mathematical model and in order to solve the optimization problem, the performance of the PSO algorithm was evaluated considering four sets of parameters values suggested by the literature. PSO demonstrated to be efficient and robust to solve the constrained optimization problem, independently of the values of the PSO parameters. The solution of the rigorous mathematical model of the reactor was associated with a high computational burden, and although the PSO algorithm presented high rate of convergence, the attempt to make possible the optimization in a timeframe suitable to real time applications failed because the algorithm lost robustness (fraction of the number of runs the algorithm reached the optimization goal) when run with a reduced number of function evaluations. Therefore, if this type of application is desired, simplified mathematical models with fast and simple numerical methods must be preferred.

Multi-objective Heat Exchanger Networks Synthesis Considering Economic and Environmental Optimization

Abstract In the present paper it is presented a model for the synthesis of HEN considering both economic and environmental features. The model presents a multi-objective mixed-integer non-linear programming (MINLP) formulation. The optimization problem aims to find the optimal HEN considering the total cost as well as the environmental impact minimization. Environmental aspects are incorporated to the objective function by considering Life Cycle Assessment (LCA), using SIMAPRO software. ReCiPe methodology is used and 18 impact categories from midpoint to endpoint are evaluated. An algorithm based on Particle Swarm Optimization (PSO) was developed to solve the model and a superstructure that considers the number of stages as an optimization variable is proposed. A literature case was chosen to test the model applicability. Results are better than the previously published ones, even considering environmental impacts. Furthermore, not all impact metrics are in conflict with the cost function.

Integrated tool for simulation and optimization of a first and second generation ethanol-from-sugarcane production plant

Abstract An integrated first and second generation ethanol production plant was simulated and optimized in an equation-oriented process simulator. Two optimization methods were used: ipopt, a deterministic algorithm, and PSO, a stochastic one. The optimization of cash flow and of ethanol production was carried out for three different pretreatments. PSO was able to solve the optimization problems, while ipopt did not converge. The objective functions exhibited opposite behavior, i.e. ethanol maximization leaded to lower cash flows for the considered economic scenario.

Integrated Production of 1G–2G Bioethanol and Bioelectricity from Sugarcane: Impact of Bagasse Pretreatment Processes

The industrial plant for production of second-generation (2G) ethanol from sugarcane bagasse will most probably be integrated to the already existing facilities for first-generation (1G) ethanol from sugarcane juice. This will allow lower investment costs, since the former would be able to take advantage of the existing infrastructure, setup for the later. Nevertheless, the exploitation of sugarcane bagasse as raw material must take into account that this biomass is also used as boiler fuel in order to produce steam to meet process demands. Additionally, steam demand is highly dependent on the pretreatment used. In this context, five pretreatments were chosen and an ethanol production process was proposed for each of them. Steam demand was calculated and used to determine the maximal bagasse that could be diverted from steam production. Among the pretreatments considered, the alkaline one presented the higher increase in ethanol production (5.7 L/tonne of sugarcane). This was due the almost complete cellulose hydrolysis and the lower steam demand of this process. On the other hand, pretreatment and hydrolysis reactor volumes were first and second higher, respectively, for this pretreatment. This suggests that, from an economic perspective, steam explosion (with a 2G ethanol production of 2.8 L/tonne of sugarcane) might be a better option.

Comparison among Proposals for Energy Integration of Processes for 1G/2G Ethanol and Bioelectricity Production

Abstract Brazil has an important role in the world market of ethanol production and the implementation of technologies of second generation ethanol will intensify its production. In this work Pinch Analysis was used in order to perform energy integration of processes for first and second generation (1G/2G) ethanol and bioelectricity production, using hydrothermal and diluted acid pretreatments of sugarcane bagasse, both including and not including pentoses fermentation step. Processes that include pentoses fermentation step, for both considered pretreatments, have higher ethanol production when compared to the ones that do not make use of hemicellulose fraction of bagasse to produce ethanol, but steam consumption increases in the same order of magnitude of ethanol production. For the four evaluated scenarios the application of energy integration demonstrated a reduction in energy consumption of more than 50% when compared to the corresponding cases without any energy integration and of more than 30% when compared to partially integrated processes, as commonly found in Brazilian industrial plants. Besides the economical advantage, due to the decrease in costs of hot and cold utilities, energy integrated processes increase bagasse availability for production of second generation ethanol.

A meta-heuristic approach for financial risks management in heat exchanger networks

Abstract Mathematical programming models for heat exchanger networks (HEN) synthesis generally do not take into account the fluctuations in the costs of commodities related to the plant operation. This work proposes to include such features in the HEN synthesis model by assuming utility production costs as uncertain and considering them as stochastic variables. These are discretized via Monte Carlo Simulation (MCS) with the Geometric Brownian Motion (GBM) model, which creates an appropriate number of scenarios throughout plant lifetime based on natural gas and electricity historical price data. The downside risk, which is a target based metric, is used for financial risks management. Multi-objective optimization (MOO) can be performed to better address trade-offs between solutions’ expected total annual costs (ETAC) and the chosen metric. A meta-heuristic two-level approach is adapted to handle such MOO. The developed scheme is based on the e-constraint method. Two costs targets are tested with downside risk. The number of scenarios with costs higher than the targets is reduced when compared with single ETAC optimization. The developed meta-heuristic solution method was able to efficiently perform MOO in a model with rather large number of scenarios, and is a good option for applying risk metrics including uncertainties in HEN synthesis.

Modelling and Analysis of a Soybean Biorefinery for the Production of Refined Oil, Biodiesel and Different Types of Flours

Abstract Soybean crushing and refining facilities, besides producing oil and meal, can also further process these products to generate energy or other products with commercial value. Therefore, these facilities are good candidates for a biorefinery concept application. From the degummed oil obtained after the extraction and degumming of soybean oil, there is the possibility of producing refined oil or biodiesel. From the meal also obtained from the extraction, it is possible to make soy protein concentrates (SPC) or soy protein isolates (SPI). For this reason, the aim of this work is to model a soybean crushing, refining and biodiesel production facility. For that, SuperPro Designer v. 9.0, a process design commercial software, was used with production process data collected from the literature. From the modelled process, it was possible to observe that yields from biodiesel or refined oil production are almost equal, but refined oil results in less residues generation and demands less energy. As for SPC and SPI production, SPI results in lower yields (~xa044% lower) and produces more residues when compared to SPC (~xa037-fold more). In addition, the model provides flexibility by varying the amount of raw material that can be diverted for the production of different products, so the production process can be adapted to changes in demands that occur in the market.

Process Alternatives for Second Generation Ethanol Production from Sugarcane Bagasse

Abstract In ethanol production from sugarcane juice, sugarcane bagasse is used as fuel for the boiler, to meet the steam and electric energy demand of the process. However, a surplus of bagasse is common, which can be used either to increase electric energy or ethanol production. While the first option uses already established processes, there are still many uncertainties about the techno-economic feasibility of the second option. In this study, some key parameters of the second generation ethanol production process were analyzed and their influence in the process feasibility assessed. The simulated process includes the enzymatic hydrolysis of sugarcane bagasse pretreated with liquid hot water, and the analyzed parameters were the solid consistency in the hydrolysis and pretreatment reactors and the hydrolysis reaction time. The solid consistency in the hydrolysis reactor had the highest influence on the economic feasibility of the process. For the economic scenario considered in this study, using bagasse to increase ethanol production yielded higher ethanol production costs compared to using bagasse for electric energy production, showing that further improvements in the process are still necessary.