Multi-Criteria Decision Matrix Method in the Risk Analysis of Biodiesel Production Processes

Renewable fuel technologies aim to mitigate the non-renewability of fossil fuels, challenges with increased energy demand, and the climate impact of fossil fuel emissions. However, before investing in renewable technologies, there need to be decision strategies that assess and identify the best alternatives according to stakeholder priorities. There is also a concern about whether the technologies that are the “most sustainable” effectively meet the acceptable risk requirements of stakeholders. In response to this question, a risk-adapted multi-criteria decision model was developed and compared to a sustainability study that evaluated five renewable diesel technologies, including Green Diesel I, II, and III; Fischer-Tropsch biodiesel, and the transesterification of biodiesel from vegetable oils. This thesis work provides essential stakeholder perspectives on the risk of these same five technologies and limits the use of probabilistic quantification approaches. Instead, this study uses reasonable assumptions to measure the indicator data objectively. These quantified indicators are considered a cost or benefit and allow adequate comparison of less mature technologies where historical data may be unavailable to more mature ones. This model uses the Analytical Hierarchy Process (AHP) decision strategy with stakeholder survey input to determine criteria and sub-criteria weightings, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) subsequently ranks the alternative technologies. The criteria evaluated from a risk perspective include process safety, environmental, economic, technological, and social risks. This risk assessment process has ranked technologies producing alternative fuel types. However, it can also compare and rank bioproduct and process intensification technologies to fossil-derived products and more traditional production techniques. Moreover, the central conclusion of this work is that an even more comprehensive tool is needed that combines risk and sustainability aspects. This conclusion is due to the sustainability study indicating Fischer-Tropsch diesel as the best option. At the same time, the present risk research revealed it as the option with the most significant comparative risk

Potential Routes for Thermochemical Biorefineries

This critical review focuses on potential routes for the multi-production of chemicals and fuels in the framework of thermochemical biorefineries. The up-to-date research and development in this field has been limited to BTL/G (biomass-to-liquids/gases) studies, where biomass-derived synthesis gas (syngas) is converted into a single product with/without the co-production of electricity and heat. Simultaneously, the interest on biorefineries is growing but mostly refers to the biochemical processing of biomass. However, thermochemical biorefineries (multi-product plants using thermo-chemical processing of biomass) are still the subject of few studies. This scarcity of studies could be attributed to the limitations of current designs of BTL/G for multi-production and the limited number of considered routes for syngas conversion. The use of a platform chemical (an intermediate) brings new opportunities to the design of process concepts, since unlike BTL/G processes they are not restricted to the conversion of syngas in a single-reaction system. Most of the routes presented here are based on old-fashioned and new routes for the processing of coal- and natural-gas-derived syngas, but they have been re-thought for the use of biomass and the multi-production plants (thermochemical biorefinery). The considered platform chemicals are methanol, DME, and ethanol, which are the common products from syngas in BTL/G studies. Important keys are given for the integration of reviewed routes into the design of thermochemical biorefineries, in particular for the selection of the mix of co-products, as well as for the sustainability (co-feeding, CO2 capture, and negative emissions).Ministerio de Educación FPU Program (AP2010-0119)Ministerio de Economía y Competitividad ENE2012-3159

Techno-Economic Studies of Coal-Biomass to Liquids (CBTL) Plants with CO2 Capture and Storage (CCS)

Due to insecurity in the crude oil supply and global warming, various alternative technologies for fuel production are being investigated. In this project, indirect, direct, and hybrid liquefaction routes are investigated for production of transportation fuels from coal and biomass. Indirect coal liquefaction (ICL) and direct coal liquefaction (DCL) technologies are commercially available, but both processes are plagued with high carbon footprint. Furthermore, significant amount of hydrogen is required in the DCL process leading not only to higher cost but resulting in considerable amount of CO2 production. Addition of biomass and application of carbon capture and storage (CCS) technologies are studied for reducing the carbon footprint. However, these two options can lead to higher capital and operating costs. Due to easy availability and low cost of the shale gas in the U.S., utilization of shale gas in the direct and hybrid routes was investigated for producing hydrogen at a lower cost with reduced CO2 emission in comparison to the traditional coal gasification route. Because the quality of the syncrude produced from ICL and DCL technologies vary widely, the hybrid coal liquefaction technology, a synergistic combination of ICL and DCL technologies, is investigated for reducing the penalty of downstream syncrude upgrading unit through optimal blending.;In the indirect CBTL plant, coal and biomass are first gasified to syngas. Then the syngas is converted to syncrude via Fischer-Tropsch (FT) synthesis. CO2 is captured from both raw syngas and FT vapor product. In the direct CBTL plant, coal and biomass are directly converted into syncrude in the catalytic two-stage liquefaction (CTSL) unit by adding hydrogen produced from gasification of coal/biomass/liquefaction residue or reforming of shale gas. Significant amount of CO2 that is generated in the hydrogen production unit(s) is captured to satisfy the target extent of CO2 capture. In the hybrid CBTL plant, pre-processed coal and biomass are sent to either syngas production unit or the CTSL unit. Produced syngas is sent either to FT unit or hydrogen production unit. Naphtha and diesel products from the FT unit and the CTSL unit are blended to reduce the syncrude upgrading penalty. Different CCS technologies are considered and optimized for the indirect, direct and hybrid CBTL plant depending on the sources of CO2 containing stream and corresponding CO2 partial pressure.;While several studies have been conducted for indirect CBTL processes, studies on direct and hybrid CBTL processes at the systems level and investigation of CCS technologies for these processes are scarce. With this motivation, high fidelity process models are developed for indirect, direct, and hybrid CBTL plants with CCS. These models are leveraged to perform comprehensive techno-economic studies. Contributions of this project are as follows: (1) development of the systems-level and equipment-level process models and rigorous economic models in Aspen Plus, Aspen Custom Modeler, Aspen Exchanger Design and Rating, and Aspen Process Economic Analyzer platforms, (2) sensitivity studies to analyze the impact of key design parameters (i.e. biomass/coal ratio, operating conditions of key equipment, extent of CCS, CCS technologies, blending ratio of the syncrude and products in the hybrid route) and investment parameters (i.e. price of coal and biomass, project life, plant contingency and plant capacity) on key efficiency measures, such as thermal and carbon efficiency, as well as economic measures, such as the net present value, internal rate of return and break-even oil price, (3) comparisons and analyses of trade-offs of indirect, direct, and hybrid CBTL technologies

Energy performance of Power-to-Liquid applications integrating biogas upgrading, reverse water gas shift, solid oxide electrolysis and Fischer-Tropsch technologies

Power-to-liquid (P2L) pathways represent a possible solution for the conversion of carbon dioxide into synthetic value-added products. The present work analyses different power-to-liquid options for the synthesis of Fischer-Tropsch (FT) fuels and chemicals. The FT section is integrated into a complete carbon capture and utilization route. The involved processes are a biogas upgrading unit for CO2 recovery, a reverse water gas shift, a solid oxide electrolyser and a Fischer-Tropsch reactor.The upgrading plant produces about 1 ton/h of carbon dioxide. The recovered CO2 is fed to either a reverse water gas shift reactor or a solid oxide electrolysis unit operating in co-electrolysis mode for the generation of syngas. The produced syngas is fed to a Fischer-Tropsch reactor at 501 K and 25 bar for the synthesis of the Fischer-Tropsch products, which are further separated into different classes based on their boiling point to yield light gas, naphtha, middle distillates, light waxes and heavy waxes. The developed process model uses a detailed carbide kinetic model to describe the formation of paraffins and olefins based on real experimental data. The effect of Fischer-Tropsch off-gas recirculation has been studied against a one-through option. Finally, energy integration of each configuration plant is provided. Results from process simulations show that the best model configurations reach a plant efficiency of 81.1% in the case of solid oxide electrolyser as syngas generator, and 71.8% in the case of reverse water gas shift option, with a global carbon reduction potential of 79.4% and 81.7%, respectively

Interaction between reaction and phase equilibria in the Fischer-Tropsch reaction.

The aim of the thesis is to describe the behaviour and performance of the Fischer–Tropsch (FT) reactor by considering the dynamic interaction between reaction equilibrium and vapour–liquid equilibrium (VLE) inside the reactor. There may be an equilibrium set up between species of either an olefin precursor or the olefins themselves which leads to the Flory-type distribution found in the FT reaction. Experimental results obtained show that VLE is attained inside an FT reactor. The measured vapour and liquid compositions (K-values) can be sufficiently described by Raoult’s law. Hydrocarbons with carbon number greater than 18 deviates from Raoult’s law. The deviations from Raoult’s law are due to diffusion limitations. Elaborate thermodynamic models could be used given the pure component parameters with relevant mixing rules for a higher degree of accuracy. VLE can explain the observed two-alpha product distribution in FT reactors. This further predicts a relationship between the two values of alpha that is consistent with the measured experimental results. Experimental results show that the average residence time increase with carbon number and the higher carbon number products have a longer residence time in the reactor. Products with a chain length of 22 and higher have the same residence time as the liquid. This suggests that VLE is the predominant cause for chain length dependencies of secondary olefin reactions in FT synthesis and diffusion limited removal of products is only significant for products with carbon number greater than 17. A mathematical model to describe the behaviour and performance of an FT reactor by considering the dynamic interaction between reaction and VLE was developed. The model results show that the rate of formation of component hydrocarbons is dependent on either the reaction rate or stripping rate, depending on which one is rate-limiting. Furthermore, that at steady state, the rate of formation of hydrocarbons is given by the stripping rate. Modelling an FT reactor as a reactive distillation column can explain a rate increment when the reactor is switched from Batch to CSTR mode and is also consistent with the observed two-alpha positive deviation product distribution observed experimentally and industrially

계산 과학적 접근을 통한 지속가능한 공정의 최적 설계 및 산업에의 응용

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 화학생물공학부, 2018. 2. 이원보.Recently, in the field of chemical engineering, many types of research based on high-performance computing have been combined with computer-aided process systems engineering. Therefore, various techniques of computational science such as computational fluid dynamics, optimization methodology, and machine learning have been applied to the problems of chemical reactor modeling and process optimization. Notably, in this advance computational science approach, the scope of research extends to non-traditional fields such as reactive research according to the 3D shape of the reactor that has not been easily solved in the past and surrogate model based optimization using machine learning. In this thesis, various methods are proposed to obtain the maximum profit with minimum cost by making a breakthrough design. In parallel, there is a growing demand for sustainable chemical processes in chemical engineering. Conventional chemical processes are highly dependent on oil prices, and unless a diverse portfolio is designed, the sustainability of their chemical industries can be violated because of the oil controlling from the Middle East or US. In addition, these crude oil based chemical processes and power plants generate a great deal of CO2. Therefore, it is not necessary to capture these CO2 and make only meaningless storage but to reproduce it as a product that can be used and make it economical carbon capture, utilization, and storage (CCUS) technology. To solve this series of processes, the Gas-to-Liquid (GTL) process and CCUS are being researched and developed in various ways. In this thesis, I will discuss the process modeling, optimizing, and designing the reactor and process using CFD, mathematical programming, machine learning, deep learning, and derivative-free optimization techniques in computational science. First of all, the Fischer-Tropsch microchannel reactor and 3-phase carbonation reactor, which are the key reactor of two most important processes of the sustainable process, the gas-to-liquid process (GTL) and the carbon capture, utilization, and storage (CCUS), are modeled by CFD. Also, we propose an integration platform of CFD model and process simulator and conduct research from the point of view of combining with existing process engineering. With these advanced reactor model, we propose a multi-objective optimization methodology using a stochastic optimization algorithm, a genetic algorithm (GA) with e-constraint method for simultaneously maximizing C5+ productivity and minimizing the temperature rise of a Fischer-Tropsch microchannel reactor. The main mixed integer nonlinear programming (MINLP) optimization problem is decomposed into an external CFD reactor model function and internal optimization constraints. The methodology is applied to the catalyst packing zone division, which is divided and packed with a different dilution ratio to distribute the heat of reaction evenly. The best solutions of the proposed optimizer are reproducible with different crossover fractions and are more efficient than other traditional non-convex constraint local solvers. Based on the Pareto optimal solution of the final optimizer with 4 zones, discrete dilution increases C5+ productivity to 22% and decreases ∆Tmax to 63.2% compared to the single zone catalyst packing case. Finally, several Pareto optimal solutions and sub-optimal solutions are compared and the results are documented in terms of C5+ productivity and maximum temperature increase. In process scale optimization platform, a modified DIRECT algorithm with a sub-dividing step for considering hidden constraints is proposed. The effectiveness of the algorithm is exemplified by its application to a cryogenic mixed refrigerant process using a single mixed refrigerant for natural gas liquefaction and its comparison with a well-known stochastic algorithm (GA, PSO, SA), and model based search algorithm (SNOBFIT), local solver (GPS, GSS, MADS, active-set, interior-point, SQP), and other hidden constraint handling methods, including the barrier approach and the neighborhood assignment strategy. Optimal solution calculated by the proposed algorithms decreases the specific power required for natural gas liquefaction to 18.9% compared to the base case. In the same chapter, heat exchanger network synthesis (HENS) has progressed by using mathematical programming-based simultaneous methodology. Although various considerations such as non-isothermal mixing and bypass streams are applied to consider real world alternatives in modeling phase, many challenges are faced because of its properties within non-convex mixed-integer nonlinear programming (MINLP). We propose a modified superstructure, which contains a utility substage for use in considering multiple utilities in a simultaneous MINLP model. To improve model size and convergence, fixed utility locations according to temperature and series connections between utilities are suggested. The numbers of constraints, discrete, and continuous variables show that overall model size decreases compared with previous research. Thus, it is possible to expand the feasible search area for reaching the nearest global solution. The models effectiveness and applications are exemplified by several literature problems, where it is used to deduce a network superior to that of any other reported methodology. In the case of plant-wide scale systems, a non-linear surrogate model based on deep learning is proposed using a variational autoencoder with deep convolutional layers and a deep neural network with batch normalization (VAEDC-DNN) for real-time analysis of the probability of death (Pdeath). VAEDC can extract representation features of the Pdeath contour with complicated urban geometry in the latent space, and DNN maps the variable space into the latent space for the Pdeath image data. The chlorine gas leak accident in the Mipo complex (city of Ulsan, Republic of Korea) is used for verification of the model. The proposed model predicts the Pdeath image within a mean squared error of 0.00246, and compared with other models, it exhibits superior performance. Furthermore, through the smoothness of image transition in the variable space, it is confirmed that image generation is not overfitting by data memorization. Finally, a pilot scale (1.0 BPD) compact GTL process comprising of reforming section, CO2 separating section and Fischer -Tropsch (FT) synthesis section is presented. Systematic design procedure adopted for the design of a modular 0.5 BPD microchannel FT reactor block design consisting of 528 process channels is described. On average 98.27% CH4 conversion to syngas in reforming section comprising of a pre-reformer unit and a tri-reformer unit, CO2 separation rate of 36.75 % along with CO/H2 reduction from 2.67 to 2.08 in CO2 membrane separation section comprising of three membrane separators, for the entire plant operation duration of 450 hr demonstrated successful and stable operation of pre-processing sections of the present pilot-scale compact GTL process. Parallel operation of FT microchannel reactor and multitubular fixed bed type FT reactor proved failure for latter due to reaction runaway, while the former showed stable operation with high CO conversion of 83% and successful temperature control (at 220 oC, 230 oC and at 240 oC during the 139 hr operation), which demonstrated the appreciable performance of KOGAS-SNU novel microchannel FT reactor. Furthermore, a tank agitator carbonation reactor in which the reaction between calcium oxide and carbon dioxide takes place is studied to understanding that how 6 design variables (the number of impeller, impeller type, D/T, clearance, speed, baffle) affect to the solid dispersion using CFD simulation.CHAPTER 1. Introduction 17 1.1. Research motivation 17 1.1.1. Chronological stages of development of process design 19 1.1.2. Current status of process systems engineering with computational science approach 21 1.1.3. Introduction to the sustainable process 23 1.2. Research objectives 25 1.3. Outline of the thesis 26 1.4. Associated publications 29 CHAPTER 2. Study of the Novel Reactor Models using Computational Science 30 2.1. Introduction 30 2.2. Gas-to-Liquid (GTL) Fischer-Tropsch (FT) reactor model 32 2.2.1. 2D axisymmetric computational fluid dynamics (CFD) based Fischer-Tropsch microchannel reactor single-channel model 37 2.2.2. 3D CFD based Fischer-Tropsch microchannel reactor multi-channel model 52 2.3. Carbon Capture, Utilization, and Storage (CCUS) multiphase carbonation reactor model 75 2.3.1. Rigorous reaction kinetics for carbonation based CCUS reactor 77 2.3.2. Eulerian multiphase model for carbonation reactor 92 2.4. CFD-Process integrated platform for simultaneous process and reactor design 105 2.4.1. Introduction 105 2.4.2. Model formulation 106 2.4.3. Result and discussion 112 2.4.4. Conclusion 116 CHAPTER 3. Optimization for the Unit, Process, and Plant-wide Systems 117 3.1. Introduction 117 3.2. Reactor systems scale optimization 119 3.2.1. Multi-objective optimization of microchannel reactor for Fischer-Tropsch synthesis using computational fluid dynamics and genetic algorithm 119 3.3. Process systems scale optimization 152 3.3.1. A modified DIRECT algorithm for hidden constraints optimization problem 152 3.3.2. Simultaneous synthesis of a heat exchanger network with multiple utilities using utility substages 200 3.4. Plant-wide systems scale modeling and optimization 233 3.4.1. Toxic gas release modeling for real-time analysis using variational autoencoder with convolution neural networks 233 CHAPTER 4. Industrial Applications 276 4.1. Optimal Design and Operation of Fischer-Tropsch Microchannel Reactor for Pilot Scale Compact Gas-to-Liquid Process 276 4.1.1. Pilot scale compact GTL process 277 4.1.2. Microchannel FT reactor design 286 4.1.3. Pilot plant experiment 287 4.1.4. Result and discussion 291 4.1.5. Conclusion 304 4.2. Industrial scale (40 tonCO2/day) CCUS carbonation reactor geometry design optimization 306 4.2.1. Design procedure and simulation set-up 310 4.2.2. Result and Discussion 313 4.2.3. Conclusion 332 CHAPTER 5. Concluding Remarks 334 5.1. Summary of Contributions 334 5.2. Future Work 337 Nomenclature 340 Reference 346 Abstract in Korean (국문초록) 360Docto

Modeling and optimization of natural gas processing and production networks

Natural gas is a nonrenewable energy source, so it is important to use it and utilize it in a sustainable manner. Globally, about 25% of energy consumption is supplied and fulfilled by natural gas and this percentage will stay true for the foreseeable future. Today, the fluctuations in commodities prices and demands all necessitate the proper planning and coordination in natural gas industries. Moreover, the strict environmental regulations, continuous advancement in technologies and different customer requirements and specifications, all mandate seeking many pathway options and continuous evaluation of the technologies. Thus, the overall objective of this research is to provide a framework for the design, synthesis, analysis, and planning of a natural gas processing and production networks. The overall framework helps the decision maker in the natural gas industry to evaluate and select optimally the production pathways and utilization options by using the mathematical modeling and optimization techniques in order to maximize the value of natural gas resource. Toward this objective, a novel natural gas network has been synthesized for analysis and optimization. The developed network converts natural gas to LNG, condensate, LPG, gasoline, diesel, wax, and methanol as main products. The contributions of this dissertation fall mainly into three milestones; namely (1) simulation of natural gas network (2) mathematical formulation and optimization of the network and (3) sustainability assessment of the network. The first milestone addresses the rigorous steady state simulation of natural gas network. The simulation of key processing units helped in calculating accurately material and energy balances. Furthermore, the sensitivity analysis or what-if analysis was performed to determine the effect of different operating-parameters on products yield. The second milestone is the comprehensive mathematical formulation and optimization represented by both linear programming (LP) and mixed integer linear programming (MILP) models. Firstly, a deterministic operational LP model has been formulated and implemented on natural gas processing and production networks. Based on the yields obtained from the simulation, LP model was able to tackle different scenarios, such as, variations and fluctuations in natural gas flow rate, natural gas price, products price, and so on. Secondly, a comprehensive MILP model for the optimal design and operation of natural gas processing network was proposed. The MILP model addresses the different technologies and configurations available for the selection of key processing units. Also, it considers the different operating modes practiced in industry in terms of low, moderate, and severe restrictions to the specifications level. Thirdly, another MILP model for the optimal design and operation of natural gas production network has been developed. We were able to address the different routes for natural gas utilization. Finally, the third milestone is the sustainability assessment. The sustainability metrics or indicators were evaluated to investigate the sustainability dimensions and to address the economic, environmental, and societal aspects of the synthesized processing and production networks. The sustainability metrics proved to be useful in selecting pathways that are both economic and environmental friendly.1 yea