Dynamic Control Of Alternative Bioethanol Purification Processes

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2016Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2016Biyoetanol, biyokütleden biyokimyasal bir reaksiyonla genel olarak elde edilen alternatif bir yakıttır. Biyoetanol; temizleme, ekstraksiyon, işleme, sakarifikasyon, fermantasyon, damıtma ve dehidrasyon adımları ile üretilir. Etanol hammadde, katkı maddeleri ve çözücü olarak da kullanılabilir. Bu nedenle, biyokütleden elde edilen etanol geleceğin yakıtı olarak kabul edilmektedir. Avantajlarından en önemlisi çevre açısından yararlı olan, yenilenebilir enerji kaynaklarından üretilmesidir, bunun nedeni; benzinden daha düşük sera gazı emisyonlarını açığa çıkarmasıdır. Etanol aynı zamanda yüksek oktan sayısına, geniş yanıcılık sınırlarına ve benzinden daha yüksek buharlaşma ısıları vardır. Buna ek olarak, benzin katkı maddesi olarak kullanılabilir ve hatta doğrudan kullanılabilir.  Tez iki aşamadan oluşmaktadır. İlk aşamada, seçilen üç biyoetanol ayırma prosesi Aspen Plus'ta simüle edilmiştir. Proseslerin ilki ön yoğunlaştıncı kolon, ekstraktif kolon, solvent geri kazanım kolonu ve yoğunlaştırıcı kolonu içeren dört kolonlu bir prosestir. Birinci kolonda, fermentasyon suyundan % 85 etanol ve % 15 su içeren karışım elde edilirken, saf etanol üretmek için etilen glikol ikinci kolona gönderilir. İkinci kolonun distilatından susuz etanol elde edilirken, kolonun dip akımı çözücü geri kazanımı için bir sonraki kolona gönderilir. Solventin küçük bir miktarının, bu geri dönüşüm sırasında kaybını önlemek için telafi olarak makeup eklenir. Solvent geri kazanım kolonundan su ve azetropik karışım elde edilir. Buradaki azeotropik karışım ilk kolona geri gönderilir. Ikinci proses (CLR), üç kolondan oluşmaktadır: ön yoğunlaştıncı kolon, ekstraktif kolon, solvent geri kazanım kolonu. Dört kolonlu sistemden farkı bir kolon indirgenmesi bunu takiben üçüncü kolonun distilatının birinci kolona gönderilmesidir. Son proses SSVR denilen iki kolonlu prosestir. Burada ön derişiklendirme kolonu aynı çalışırken ekstraktif kolon buhar yan akımına sahiptir ve bu akımla birinci kolna dönüş yapar. Ektraktif kolonun distilatı saf etanol içerirken; dip akım solvent içerir ve sisteme geri beslenir. Aspen Dynamics'e gönderilmeden önce gerekli kolon boyutlandırılmaları yapılarak yapılar Aspen Dynamics'e gönderilir. Yeterli literatür araştırması sonucunda proseslere kontrol yapıları kurulmuştur. Yapılara ± %20 besleme akış ve %0.4 ve %0.6 mol besleme kompoziyonu distürbansı uygulanmaktadır ve veriler 10 saat boyunca toplanmaktadır. Elde edilen veriler sonucu MATLAB'te grafikler oluşturularak   incelenmiştir. Sistemlerin distürbanslara karşı verdiği cevaplar çok düşük değişimlere sahiptir ve kısa zamanda yatışkın hale ulaşmıştır. Sonuç olarak her üç yapının da dinamik davranışlarının iyi olduğu gözlemlenmiştir.Bioethanol is an alternative fuel obtained generally by biochemical reaction of biomass. Bioethanol is produced efficiently and economically with cleaning, extraction, treatment, saccharification, fermentation, distillation and dehydration steps of sugarcane, corn, wheat and cellulose, simultaneously. Ethanol can be used as raw material, additives and solvent, such as cosmetics, sprays, perfumery, paints, medicines, food, varnishes and explosives industries. Therefore, ethanol produced from biomass is regarded as the fuel of the future. Due to the fact that ethanol has important advantages like it is produced from renewable energy sources that are environmentally beneficial; it has the lower greenhouse gas emissions than gasoline. Ethanol has also a higher octane number, wider flammability limits, and higher heats of vaporization than gasoline. Furthermore, it can be used as additive with gasoline and also used directly. On the contrary, the major disadvantages of ethanol are including lower energy density, lower vapor pressure and miscibility with water. Several alternative processes are applied to produce bioethanol: ordinary distillation,  pervaporation, adsorption, pressure-swing distillation, extractive distillation, azeotropic distillation, liquid–liquid extraction, adsorption as well as hybrid methods combining these options. In this thesis, the simulation and control of bioethanol production processes using extractive distillation method  are studied. The thesis consists of two stages. In the first stage, the processes selected are simulated in Aspen Plus using the data in the relevant article. Three bioethanol separation processes formed by Errico et al have been selected. The first one is a four-column configuration which includes the preconcentrator column, the extractive distillation column, the solvent recovery column, and the concentrator column. In first column, fermentation broth is converted into the azeotropic mixture, and also the mixture is sent to the second column to produce pure ethanol using ethylene glycol as a solvent. While this is obtained from the distillate   of the second column, the bottom of the column is sent to the next column for solvent recovery. A small amount of fresh solvent is added as make up to prevent any losses of solvent during this recycle. The distillate of the solvent recovery column is separated as water and an azetropic mixture and also the mixture is turned back to the first column in the last column. The second configuration is called conventional separation sequences with liquid recycle (CLR) and also consists of three columns: preconcentrator, extractive and solvent recovery column. While the same sequences occurs in both preconcentrator and extractive column, changes are made in the solvent recovery column. The solvent is obtained from the bottom of the solvent recovery column and is turned to the second column (extractive column) not to the first column. The last configuration is called SSVR, includes two column: preconcentrator column and extractive column. The preconcentrator column is performed same in the other processes. In the extractive column, , pure ethanol is obtained from the distillate, the solvent is recovered at the bottom. The vapor side stream includes a mixture of water and ethanol and also is turned to the preconcentrator column. Before being sent to Aspen Dynamics, column sizing is applied to the columns of these three structures to determine the diameter and length of the vessel. Then, the procedure for "exporting" is performed. Three process control structure has been established by examining the control structure in the literature. In the control structures of four column and three column configurations: reflux drum levels for all columns are controlled by manipulating the distillate flow rates in the first configuration. In the CLR and SSVR, the control of the partial condenser is applied. The base levels for all columns except the solvent recovery column are controlled by manipulating the bottoms flow rates. The base level for  recovery column is controlled by manipulating the makeup flow rate. The top pressures of both columns are controlled by manipulating the corresponding condenser duties. The entrainer flow rate is ratioted to the azeotropic feed and the ratio is controlled by manipulating the bottoms flow rate of the recovery column. Reflux ratios are held constant in each column at their nominal values during disturbances. The fresh feed to the preconcentrator column is flow control in order to guarantee the constant flowrate. The entrainer feed temperature is controlled by manipulating cooler duty. The reboiler duties of both columns are used to control the temperature in a particular stage of each column.   In the two column process, reflux drum level for extractive column is controlled by manipulating the distillate flow rate. The reflux drum level for preconcentrator column is controlled by manipulating reflux. The base level for preconcentrator column is controlled by manipulating the bottoms flow rates. The base level for second column is controlled by manipulating the makeup flow rate. The top pressures of both columns are controlled by manipulating the corresponding condenser duties. The entrainer flow rate is ratioted to the azeotropic feed and the ratio is controlled by manipulating the bottoms flow rate of the recovery column. Reflux ratio is held constant in extractive column at their nominal values during disturbances. Distillate flow rate of the preconcentrator column is ratioed to the reflux flow rate. The fresh feed to the preconcentrator column is flow control in order to guarantee the constant flowrate. The entrainer feed temperature is controlled by manipulating cooler duty. The reboiler duties of both columns are used to control the temperature in a particular stage of each column. The temperature of the vapor sidestream is controlled by manipulating the bottom of the second column. After the design of the structures, two type distorbances are given to the processes: ethanol composition disturbances and Fresh feed flow disturbances. Ethanol composition disturbances, from 5 to 6 mol% ethanol and from 5 to 4 mol% ethanol, for 10 hours. Therefore, fresh feed flow disturbances of ±20% are applied for 10 hours. The results are recorded and shown by using MATLAB. Dynamic responses of the all systems are given in the Figures. The designed three control structures are affected from disturbance with small changes and soon stabilize and so the systems give good dynamic behaviours.Yüksek LisansM.Sc

Separation of binary homogeneous azeotropic mixtures using pervaporation.

Masters Degree. University of KwaZulu-Natal, Durban.The separation of mixtures containing homogeneous azeotropes is often complex and requires the use of enhanced distillation techniques. This leads to a significant increase in capital and operating costs. The use of membrane separation techniques to separate azeotropic mixtures is favoured over extractive distillation, azeotropic distillation and absorption as this is an effective low energy and low-cost alternative. Pervaporation is a membrane-based separation technique often used in industry to dehydrate alcohol-water azeotropes, to remove water from organic solvents or to remove organics from water. The process requires a liquid feed at a pressure high enough to maintain its phase while being depleted of components contained within the feed to form a liquid retentate. A membrane is typically selective for one component with finite permeability for the remaining components in the feed. A vapour phase must be maintained on the permeate side of the membrane by applying a vacuum downstream thereby creating a pressure gradient. A pervaporation unit generally consists of a series of membrane cells grouped together in modules, and interstage heat is applied to the feed of subsequent modules. This investigation focused on the dehydration of alcohols (ethanol, propan-1-ol and propan-2-ol) using a poly(vinyl alcohol) based membrane. An experimental study on ethanol-water under various operating conditions was performed. The effect of permeate pressure (2‒5 kPa), feed temperature (338.15‒348.15 K) and feed water concentration (1‒5 wt.%) are reported in terms of flux and permeate quality. Results confirmed that pervaporation is a suitable method to break an azeotrope. Due to technical issues encountered with the equipment, the experimental determination of pervaporation performance was not pursued further. This prompted an extensive simulation study whereby semi-empirical models were developed for the alcohol-water systems using Aspen Custom Modeler® before exporting to Aspen Plus® for simulation and optimization. Dehydration of an industrial grade propan-2-ol aqueous solution (85 wt.% propan-2-ol) using pervaporation was then rigorously simulated as the final objective, as this is not explored in detail in the literature. Various interstage heat temperatures (363.15, 368.15, 373.15 K) and module arrangements (3, 5 and 8 cells per module) were considered to produce the required retentate stream of less than 2 wt.% water. A total of nine design cases were developed to meet the industry purification requirements (>98 wt.% propan-2-ol in retentate). An economic evaluation (inclusive of operating, investment, and maintenance cost) of the separation was performed. It was confirmed that a membrane setup of 3 modules with 3 cells per module including interstage heating to 373.15 K presented the lowest. total cost of 174.27 $/t. This arrangement provided the most feasible configuration for propan-2-ol dehydration using a PVA-based membrane and when compared to azeotropic distillation from literature, it was found that a saving of 34% could be achieved using pervaporation, assuming a pre-concentrator cost of 1/3 of the total process costs from the literature studies. The comparative economic analysis performed across various processes was based on the total cost per ton of propan-2-ol product, which served as a standardized cost. Two procedural assumptions were applied; an operational time of 300 days per year and 24 hours a day for an industrial plant, and a production rate of 257.69 kg.h-1 propan-2-ol, as per the optimal design case

O USO DA PLATAFORMA ASPEN DYNAMICS COMO FERRAMENTA COMPUTACIONAL NO PROCESSO DE PARTIDA DE COLUNAS EXTRATIVAS

Abstract. A partida para uma coluna de destilação pode ser compreendida pelo período que se inicia no momento em que a matéria-prima é introduzida no equipamento, até a completa estabilização do processo. O estudo da etapa de partida para os processos de separação vem, ao longo do tempo, se tornando cada vez mais importante, uma vez que essa operação representa um dos processos mais complexos observados na prática industrial. Por esta razão, a coluna extrativa utilizada no processo de desidratação do etanol utilizando etilenoglicol como solvente foi utilizada como estudo de caso. O presente trabalho teve como objetivo simular a etapa de partida para o sistema sob investigação, como também o de avaliar seu comportamento dinâmico, evidenciando a importância dessa ferramenta computacional no ensino de engenharia. As simulações foram desenvolvidas com o auxílio dos softwares computacionais Aspen Plus e Aspen Plus Dynamics. De forma geral, pode-se concluir que o respectivo trabalho evidenciou a importância da simulação computacional como ferramenta auxiliar na assimilação e na aprendizagem dos conceitos de engenharia. Keywords: Simulação, Partida, Coluna extrativ

Towards improved ethanol production from lignocellulosic biomass

Ethanol from biological feedstock has emerged as a promising alternative for the generation of energy from renewable sources in order to mitigate the damages caused by the gas emissions associated to the consumption of fossil fuels. In many countries, ethanol is already being produced at industrial scale from different biological raw materials. However, there are some technical issues related to this process that need to be addressed and one of the major problems is the high heat requirements which makes this process less competitive against well-established fuels. This work proposes an optimisation methodology based on a dynamic approach to improve the overall efficiency of the process by considering new configurations and designs that allow the reduction of operating costs, usage of utilities, the size of units, etc. The work initially provides an introduction to the concept of fuels and the current global scenario regarding their production and consumption. Next, a general review of biofuels is given, in particular the production of ethanol from corn stover and the different units involved in this process. Additionally, mathematical formulations of the different units in the process are presented including detailed kinetic models and dynamic mass and energy balances. These models are first validated and then used in the construction of an overall model of the entire process which so far has not been available in open literature. This thesis also presents the development of an empirical mathematical model of an organophilic membrane for ethanol removal from aqueous solutions to increase the separation rates of ethanol in the process. Finally, this works presents the optimisation of the ethanol production process considering the implementation of heat storage units to reduce the consumption of utilities such as steam and cooling water by reducing the Total Annualised Cost (TAC). The results obtained show that the implementation of heat integration in the process can achieve a reduction of 7 % in the TAC and 10 % in the total energy consumption. These results indicate that ethanol production from corn stover with the use of energy storage is a viable alternative for energy generation that can become part of the main market of the production of green technologies

Computer-Aided Sustainable Process Synthesis-Design and Analysis

Processyntese involverer undersøgelse af kemiske reaktioner, der er nødvendige for at producere det ønskede produkt, udvælgelse af separationsteknikker nødvendige for downstream forarbejdning, samt beslutninger om sekvensering af de involverede separationsprocesser. For en effektiv og fleksibel designtilgang, er der behov for en systematisk måde at identificere de typer af opgaver og operationer, der skal udføres, den tilsvarende design af operation-udstyr, deres konfiguration, masse-energistrømme m.v., hvilket giver et optimalt processkema. På grund af det faktum, at processynteseproblemer er af natur kombinatoriske og med flere mulige løsninger, er der blevet foreslået en forskellige metoder til at overkomme dette. Men løsningen til ethvert syntese-design problem er afhængig af søgningsområdet af alternativer og kriterierne for procesydeevne, som i de fleste tilfælde er påvirket af økonomiske faktorer. Dette arbejde fokuserer på udvikling og anvendelse af et computerstøttet platform for bæredygtig syntese-design og analyse af processkemaer ved at generere mulige alternativer, der dækker hele søgningsområdet og omfatter analyseværktøjer for bæredygtighed, LCA og økonomi. Syntesemetoden er baseret på en gruppebidragsbaseret hybridmetode, hvor kemisk processkemaer syntetiseres på samme måde som atomer eller grupper af atomer syntetiseres til dannelse af molekyler i computerstøttet molekylært design (eng: CAMD) teknikker. Byggestenene i et processkemasyntese problem er betegnet som procesgrupper, som repræsenterer en enkelt eller et sæt af enhedsoperationer, der er udvalgt på metoder baseret på termodynamiske grundlag. Disse byggesten kombineres derefter under anvendelse af regler for tilslutningsmuligheder for at generere alle de mulige processkemaalternativer. Den største fordel ved at repræsentere processkemaer med procesgrupper er, at udførelsen af hele processen kan vurderes fra bidragene fra de enkelte procestrinsgrupper mod processkemaegenskaberne (f.eks forbrugt energi). De udviklede processkemaegenskabsmodeller omfatter energiforbrug, carbon footprint, produktudvinding, produktrenhed osv. På denne måde er hele listen over mulige kemiske processkemaer hurtigt genereret, screenet og udvalgt til yderligere analyse. I det næste trin, er udformningen af de mest lovende processkemakandidater udført gennem en omvendt simulationsmetode, hvor designparametre for enhedsoperationer i processkemaet er beregnet ud fra udvalgte definitioner af procesgrupper. I næste fase analyseres det valgte design, til at identificere begrænsninger eller flaskehalse (hot-spots) ved hjælp af en omfattende analysemetode bestående af økonomiske, livscyklus og bæredygtigheds faktorer, der omsættes til procesdesignmål. I den afsluttende fase identificeres hot-spotsne, som er målrettet til den samlede procesforbedring og til at skabe innovative designs. I dette arbejde er den udviklede platform testet sammen med de tilhørende metoder og værktøjer gennem tre casestudier med relation til både kemiske og biokemiske industri med henblik på at fastslå anvendelsesmulighederne af platformen. I hvert af tilfældene er de mange alternativer og litteraturdesignene hurtigt genereret og evalueret. I alle de testede casestudier var de endelige designs, der genereres af platformen, nye og mere bæredygtige.Process synthesis involves the investigation of chemical reactions needed to produce the desired product, selection of the separation techniques needed for downstream processing, as well as taking decisions on sequencing the involved separation operations. For an effective, efficient and flexible design approach, what is needed is a systematic way to identify the types of tasks-operations that need to be performed, the corresponding design of the operation-equipment, their configuration, mass-energy flows, etc., giving an optimal flowsheet. Due to the fact that process synthesis problems are by nature combinatorial and open ended, a number of different solution approaches have been proposed. However the solution for any synthesis-design problem is dependent on the search space of alternatives and the process performance criteria which in most cases are influenced by economic factors. This work focuses on the development and application of a computer-aided framework for sustainable synthesis-design and analysis of process flowsheets by generating feasible alternatives covering the entire search space and includes analysis tools for sustainability, LCA and economics. The synthesis method is based on group contribution and a hybrid approach, where chemical process flowsheets are synthesized in the same way as atoms or groups of atoms are synthesized to form molecules in computer aided molecular design (CAMD) techniques. The building blocks in flowsheet synthesis problem are called as process-groups, which represent a single or set of unit operations that are selected by employing a thermodynamic insights based method. These building blocks are then combined using connectivity rules to generate all the feasible flowsheet alternatives. The main advantage of representing the flowsheet with process-groups is that, the performance of the entire process can be evaluated from the contributions of the individual process-groups towards the selected flowsheet property (for example, energy consumed). The developed flowsheet property models include energy consumption, carbon footprint, product recovery, product purity etc. In this way, the entire list of feasible chemical process flowsheets are quickly generated, screened and selected for further analysis. In the next stage, the design of the most promising process flowsheet candidates is performed through a reverse simulation approach, where the design parameters of the unit operations in the process flowsheet are calculated from selected process-groups definition. In the next stage the selected design is analyzed, for identifying process limitations or bottlenecks (hot-spots) using a comprehensive analysis method consisting of economic, life cycle and sustainability factors that are translated into design targets. In the final stage the identified hot-spots are targeted for overall process improvement and to generate innovative designs. In this work the developed framework along with the associated methods and tools is tested through three case studies related to both chemical and biochemical industry in order to ascertain the applicability of the framework. In each of the cases numerous alternatives of novel and designs reported by others are quickly generated and evaluated. In all the case studies tested, the final design generated by the framework was novel and more sustainable