IBP3171_10 SIMULATION OF BIOETHANOL PRODUCTION 1 2 Joseph McMullen , Larry Balcom
Copyright 2010, Brazilian Petroleum, Gas and Biofuels Institute - IBP This Technical Paper was prepared for presentation at the Rio the Rio Oil & Gas Expo and Conference 2010 , held between September, 1316, 2010, in Rio de Janeiro. This Technical Paper was selected for presentation by the Technical Committee of the event according to the information contained in the abstract submitted by the author(s). The contents of the Technical Paper, as presented, were not reviewed by IBP. The organizers are not supposed to translate or correct the submitted papers. The material as it is presented, does not necessarily represent Brazilian Petroleum, Gas and Biofuels Institute’ opinion, nor that of its Members or Representatives. Authors consent to the publication of this Technical Paper in the Rio Oil & Gas Expo and Conference 2010 Proceedings. Proceedings.
Abstract The production of biofuels has emerged as a worl dwide market that is becoming increasingly important, drawing public & scientific attention due in large part to the increased price of oil and the need for i ncreased energy security. The use of biofuels is important to reduce the reliance on non-renewable energy resources like oil and coal. Biofuels are important to serve future world energy needs which necessitates that simulation software vendors work closely with the biofuel producers to make sure t hat the software can help the biofuel plants perform at peak operating conditions. The production of biofuels can benefit from the recent advances in process simulation software that allow for the efficient and optimal process design, regulatory compliance, and operational analysis of the biofuels process. Computer simulation is an essential tool in the design and economic analysis of new bio-ethanol technologies. This paper will discuss the use of simulation software in the simulation of a bio-ethanol process based on the United States Department of Energy (DOE) B io-ethanol Pilot Plant design (National Renewable Energy Laboratory. The DOE Bioethanol Pilot Plant, a tool for commercialization. DOE/GO-102000-1114, September 2000).
1. Introduction The production of biofuels has emerged as a worl dwide market that is becoming increasingly important, drawing public & scientific attention due in large part to the increased price of oil and the need for i ncreased energy security. The use of biofuels is important to reduce the reliance on non-renewable energy resources like oil and coal. Biofuels are important to serve future world energy needs which necessitates that simulation software vendors work closely with the biofuel producers to make sure t hat the software can help the biofuel plants perform at peak operating conditions. The production of biofuels can benefit from t he recent advances in process simulation software that allow for the efficient and optimal process design, regulatory compliance, and operational analysis of the biofuels process. Of the many tools that are available to facilitate biofuels production, simulation software is one of the most effective. Simulation software gives engineers the ability to work with a process in the virtual world without the expense and time delays of testing it i n the real world. Simulation software tools help make the process as effi cient as possible during the design phase and minimize its envir onmental impact during operation. Recent enhancements to steady-state simulation software like PRO/II enable the addition of custom unit operation calculations via a Microsoft Excel spreadsheet. Since the development of the initi al proprietary correlations of the process is usually done in Excel, the use of the Excel unit operation allows the user to capitalize on the initial correlations and reuse the work they have already done in Excel. This can model any proprietary or specialized process that cannot be modeled using t raditional unit operations. Global production of biofuels is increasing to meet the increasing worldwide demand. The increased production is illustrated in Figure 1. Production increased roughly 270% between 2004 and 2008 from 560 thousand barrels per day to over 1.5 milli on barrels per day (U.S. Energy Informati on Administration. International Energy Statistics, Total Biofuels Production). The increase in biofuel consumption is illustrated in Figure 2. Consumption increased 278% between 2004 and 2008 from 488 thousand barrels per day to about 1.4 million barrels per day (U.S. Energy Information Administration. International Energy Statistics, Total Biofuels Consumption).
______________________________ BS Chemical Engineer, Masters Business, Product Manager – Invensys Operations Management 2 BS Chemical Engineer, Technical Sales Consultant – Invensys Operations Management 1
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Figure 1. Worl Biofuels Pro uction
Figure 2. World Bio uels Consumption by year Bioethanol is the m st common biofuel, account ing for in excess of 90% of total biofuel usage. Ethanol i typically used as a gasoline dditive to oxygenate the fuell, increasing the octane ratin , while also lowering the ve icle missions. Ethanol can be pr oduced from v arious biomass sources, suc as: corn fiber, sugar cane b gasse, grain s traws, wood and pap r wastes. The main technologies for these processes incl de: thermo-c emical pretre tment, enzymatic hydrolysis, an fermentation via a variety f natural and r ecombinant microbes, and diistillation. Bioethanol is wid ly used as a fuel additive in both the United States and Braziil. The United States uses fu l blends that are 5-10% ethanol, while fuel in Brazil must contain at least 2 % ethanol. Ethanol is also a potential fuel replacement f r contempora y asoline that could reduce the emission of reenhouse ga ses. New flex-fuel vehicles capable of running on ethanol -gas ixtures of up to 85% ethan l are becoming more preval nt with over million running worldwide. 2
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Bioethanol is an alcohol produced by fermenting sugars typically from plant materials like sugar cane or corn. However, recent advances in cellulosic biomass are enabling the production of bioethanol from trees or grass. T he difficult part is designing the bioethanol production process for optimal production and optimal economics. This i s an instance where simulation software can be used to alleviate the problem. Simulation software aids not only in the design of environmentally friendly and safe processes, but also helps reduce capital and operating costs. Process simulation software can also provide the functionality and flexibility required to model high fidelity biofuel processes wi th integrated correlations and reaction models. Process simulation software can be used to design improved heat recovery processes, reconcile process data, and verify operating conditions. Use of simulation software for the design of biofuels processes is good not only for the environment, but also for the bottom line. Computer simulation is an essential tool in the design and economic analysis of new bio-ethanol technologies. This paper will discuss the use of simulation software in the sim ulation of a bio-ethanol process based on the Unit ed States Department of Energy Bio-ethanol Pilot Plant design (National Renewable Energy Laboratory. The DOE Bioethanol Pilot Plant, a tool for commercialization. DOE/GO-102000-1114, September 2000). This simulation includes material recycles and thermal integration, as well as techniques to customize unit operations and integrate user created models of the hydrolysis and fermentation processes. This paper will outline examples of how process simulation software can be used for effi cient design and operation of a biofuels production plant.
2. Overview of Solution Steady-state simulation software is used in the conceptual and basic design phases of the plant life cycle, which is the ideal t ime to commit to green engineering because it can have the greatest impact on the long-term environmental impact of the process. Steady state simulation i s essential to understanding the process, as well as the environmental and business ramifications of different configurations. Simulation software provides the tools and flexibility to model the bio-ethanol process with high fidelity, and integrate proprietary correlations and reaction models. This simulation includes these processing steps: • Dilute acid hydrolysis of long chain carbohydrates to sugars • Fermentation of sugars to alcohols • Separate unit operations are used to provide several examples of integrating custom reactions & kinetics • Recovery of alcohols via vacuum distill ation The Excel unit operation provides the customization platform for the hydrolysis process and xylose fermentation. The conversion reactor and a calculator unit operation provide the customization for glucose fermentation. The Excel unit operation util izes existing or new spreadsheet models and integrates t hem into the simulation calculation sequence as a native unit operation. This allows simple integration of R&D correlations and mathematical models directly into the simulation without the cumbersome process of generating and compiling user added subroutines. Simply copy the provided interface sheet into your Excel file, and then browse to the workbook from within PRO/II. Link the feed stream and product stream cells to your Excel model using cell formulas, and the interface is complete and ready to be used in the software.
Biomass to Ethanol Process
VENT
Excel
1
XYLO_FERMENT
XYLO_FEED
COL_OVERHEAD
FERM_PROD_2
FERM_OVER 2 3
GAS_REMOVAL FEED_RATIOS
4 5
CELLULOSE
6 HYDRO_FEED
ACID
CAT_FEED PREHEATER
Excel
M1
HYDROLYSIS
RECYLCE_H2O
S9
SUGARS HYDR_PROD
7
RX_CONV COOLER
8 9
SC1 GLUC_FEED
COL_FEED
FERM_PROD RECY_2_COL
F1
10 11
COL_PREHEAT
RECYCLE
12
GLUC_FERMENT
13
COL_TABLE
14 15
SP1
16 MATBAL_TABLE
17 18 19
HX_TABLE
20 21
S1 COL1
22 M2 COL_BOTTOMS WASTE
DRY_ALCOHOLS REGEN_H2O
MOL_SIEVES
Figure 3. PRO/II model of bioethanol production
3. Implementation Details 3
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3.1. Hydrolysis Processes There are several technologies for hydrolysis, but all convert the long chain carbohydrates (cellulose and hemicellulose) to sugars and soluble oligomers for microbial digesti on. This simulation simplifies the hydrolysis reactions down to the 2 main sugars produced: xylose (fro m hemicellulose), and glucose (from cellulose). T he dilute acid process is modeled by the addition of di lute sulfuric acid to the biomass f eed, and heating of the reaction mass t o 437 °F (225 °C) to drive the reaction, and release the sugars. Typically this phase uses multiple staged reactors to optimize the production of sugars and minimize byproducts. Additional heat exchangers and reactors can be added to match process requirements. The “strong acid” process can be modeled in this same way, as can the much less energy intensive enzymatic hydrolysis process. The Excel unit operation conversion reactor template i s used to model the hydrolysis reactions. Reactions are defined by entering the molar quantities involved under each reaction column. Negative quantities are reactants, and positive quantities are products. The base component name is identified in the “Base Component” row (row 10). The conversion percent is entered in the “Conversion Mole %” row (r ow 11) for each reaction. “Conversion Mole %” i s the amount of the base component that will be reacted. The conversion amount can be a fixed number, a cell formula, or be transferred from PRO/II. In addition it may be calculated within Excel via a mathematical model, or a Visual Basic program. Any of the tools available to you within Excel can be employed to create the data you need in the most efficient manner possible.
Figure 4. Excel unit operation depicting a digester unit 3.2. Fermentation Processes The xylose and glucose streams are split for demonstration purposes. In many process, co-fermentation is done to consume both sugars in the same process vessel. Different microbes can be used to digest each type of sugar, 5carbon and 6-carbon. Also recombinant bacterium engineered to be able to convert both types of sugars to ethanol and other useful products are being developed and improved. In either case, it is a reasonable modeling simplif ication to separate the sugars, and handle the conversion processes in s eparate unit operations, each having its own kinetics model. From a process standpoint, these reactions would be happening in the same vessel. 3.3. Glucose Fermentation Glucose fermentation is carried out in a standard conversion reactor unit operation. This simplified reaction set is defined in the PRO/II reactions data entry window. This is intended to be an illustrative example; a full reaction set for most microbes would be far more complex.
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Figure 5. Data entry window in PRO/II for reaction definitions The reaction set is referenced in the conversion reactor configuration. This allows multiple unit operations on the same flowsheet to use the same reaction set. This not only reduces data entry tasks, but also ensures a consistent s et of reactions are used throughout the flowsheet to prevent data entry errors.
Figure 6. Date entry window in PRO/ II for the conversion reactor The Extent of Reactions data entry window allows the reactions to be reordered, and have their conversion rate defined by an included quadratic equation, or by an external value via the “Define” feature. This configuration uses both methods to illustrate the possible techniques.
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Figure 7. Extent of reaction data entry window in PRO/II The define feature allows simple equations to specify the conversion rate for reactions in the conversion reactor unit operation. The methanol reaction i n the conversion reactor is defined as the “R2” value in the “RX_CONV” calculator unit operation. The define data entry window shows the name of the variable as it is defined in the calculator unit operation for clarity.
Figure 8. Reaction definition window in PRO/II linking the reaction to calculated results The calculator unit operation allows a custom equation to be associated with the reaction conversion rate. In this example, the conversion rate is varied based on the reactor inlet temperature. The biological activity function is approximated by a linear equation spanning the temperature range of 50 deg °F to 180 deg °F, with peak activity at 115 deg °F. This activity function is calculated with this small FORTRAN program.
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Figure 9. Calculator unit in PRO/II definition 3.4. Xylose Fermentation Xylose fermentation is modeled using customized kinetics i n the Excel unit operation conversion reactor template. Its reactions are defined i n the Excel reactor model in the same way as the hydrolysis process. However, the conversion rates for the four reactions are calculated based on inputs from the Excel unit operation, and a kinetics model in the Excel workbook. The base reaction rates are specified in the parameters section of the PRO/II Excel unit operation. The ratios between the different reactions are set, and passed to Excel.
Figure 10. Depiction of link from PRO/II to Excel calculations of reactions Then, the actual conversion values are calculated based on the fermenter inlet temperature. The rate of conversion is represented by a normal distribution around the optimal temperature of 115 deg °F. Any appropriate correlation can be used that best fit s your actual process or lab data.
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Figure 11. Graphical fermentation rate used for the reaction Once the correlation is entered in Excel, the overall conversion rate can be calculated. Fermentation Rate Calculation Inlet Temp:
119.7
(deg F)
Curve X:
0.35923
(Sigma)
Curve Y:
0.3740
(Probability)
Actual Fermentation Rate:
2.083%
(% Conversion / hr)
Total Fermentation Capacity:
200,000
(lb-mol)
Inlet Flowrate:
69.8
(lb-mol/min)
Residence Time:
48
(hr)
Residence Time:
1.99
(days)
Overall Fermentation %:
99.5%
Figure 12. Tabular fermentation rate used for t he reaction Each individual conversion rate is calculated from the overall conversion rate based on the inlet temperature and the base rates for each reaction that was passed to Excel from the PRO/ II Excel unit operation.
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Figure 13. Excel spreadsheet integration custom kinetic data into PRO/II via the Excel unit operation Using this methodology, sophisticated kinetics and custom correlations can be easily integrated into PRO/II to embed your process knowledge into the simulation. 3.5. Separation Processes Standard unit operations model the downstream separations processes to refine the alcohols produced into saleable fuel grade material. A low pressure flash tank is used t o produce an improved water stream for recycle t o the process inlet, followed by a distillation column to provide the bulk of the material separations. Energy integration operations are modeled quite easily with the simple heat exchanger unit operation by connecting process streams to both the hot and cold sides. Calculated duties can also be linked between heat exchangers where it i s impractical to show the process streams connected to the same heat exchanger.
4. Data Analysis & Conclusions Simulation software also gives users the ability to analyze their design to optimize t he process by using case studies to evaluate the use of heat integration, various operating conditions, various operating configurations, or different raw material compositions. Integration wi th Excel automates these case studies so that they can be run sequentially and so that the data can be evaluated easily in a side-by-side comparison. The value of analyzing the process in the design phase is that the overall operating and capital costs can be mi nimized with new processes and existing processes can be optimized with various configurations. Optimizing the plant profit by decreasing capital costs and lowering operating costs is an important aspect i n only making the process as environmentally friendly as possible, and is an integral step in ensuring that the process is economically feasible in the long-run.
5. Simulation Benefits The example in this paper provides a starting point for anyone interested in exploring the design and operation of a bioethanol facility. While the process in the paper is a fai rly good representation of the bioethanol production process, the purpose of the example is to demonstrate proper simulation techniques that can applied to biofuel processes. This model was not t uned to any particular actual biofuels application. As a process design is developed, additional details can be added to the s imulation model to provide a more accurate depiction of an actual biofuels 9
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application or to add information for equipment sizing, project costing, or full economic analysis of the bioethanol process. The techniques provided in this example give the user all the base capability needed to complete this work in an efficient and effective manner. Simulation software is an invaluable tool in understanding your process. Regardless the brand of simulation software used, i t has proven to be an important tool i n the oil and gas industries.
6. References National Renewable Energy Laboratory. The DOE Bioethanol Pilot Plant, a tool for commercialization. DOE/GO102000-1114, September 2000 U.S. Energy Information Administration. International Energy Statistics, Total Biofuels Production, http://tonto.eia.doe.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=79&pid=79&aid=1 U.S. Energy Information Administration. International Energy Statistics, Total Biofuels Consumption, http://tonto.eia.doe.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=79&pid=79&aid=2
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