Optimal Design and Evaluation of a Biogas-based Oxidative Coupling of Methane Process

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Optimal Design and Evaluation of a Biogas-based Oxidative Coupling of

Methane Process

vorgelegt von

Alberto Teixeira Penteado

ORCID: 0000-0002-0285-1744

von der Fakultät III - Prozesswissenschaften der Technischen Universität Berlin zur Erlangung des akademischen Grades

Doktor der Ingenieurwissenschaften - Dr.-Ing. -

genehmigte Dissertation Promotionsausschuss:

Vorsitzender: Prof. Dr. Tetyana Morozyuk

1. Gutachter: Prof. Dr.-Ing. habil. Jens-Uwe Repke 2. Gutachter: Prof. Ph.D. Flavio Manenti

Tag der wissenschaftlichen Aussprache: 30. April 2021 Berlin, 2021

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To my parents

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Acknowledgements

First and foremost I express my gratitude to the scientic committee consisting of Professors Jens-Uwe Repke, Flavio Manenti and Tetyana Morozyuk.

A special thanks to Prof. Repke for his scientic guidance that made this work possible, for providing the structure and funds necessary to carry out my research project and attend relevant conferences, and for enabling me to spend my time at his department and prot from exchange and collaboration with some of the most brilliant people I have ever met.

In addition, I would also like to thank Prof. Wozny for accepting me as a PhD student and guiding me in the beginning of this journey. Apart from my supervisors, one person has also contributed enormously for my work and development. A massive thank you to Erik Esche for all the discussions, support, and fun times in Berlin and during the several international workshops we've done together. I also thank Hamid Reza Godini for the fruitful cooperation, endless OCM discussions during tea sessions, and valuable input that always helped to expand my horizons.

During my time at dbta, I had the chance to meet many amazing people that made my work and my life better. Thank you Abigail, Andreas, Byungjun, Christian, David Krone, David Müller, Georg, Gerardo, Gregor, Hannes, Hen- ning, Ivo, Joris, Julian, Markus, Marlos, Matthias, Robert, Sandra, Saskia, Sören, Stephan, Thomas, and Volodymyr.

Finally, I could never have achieved this without the love and support from my family and friends. A special thanks to my family Julio, Sandra, and Paula, who always encouraged me to purse my dreams even when that meant living more than ten thousand kilometers apart from each other. Another special thanks to my girlfriend Chia-i for always being there for me and supporting me during the good and also tough times.

This study was nanced in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - (11946/13-0).

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Abstract

English Summary

Biogas is composed mostly of methane (CH4) and carbon dioxide (CO2) and it is a renewable energy carrier of increasing importance because it can complement other intermittent sources such as wind and solar quite well. Methane activation enables the production of valuable biochemicals and biofuels from biogas.

This thesis investigates bio-ethylene (C2H4) production via the Oxidative Cou- pling of Methane (OCM) contained in biogas by means of process modeling, simulation, and optimization followed by a techno-economic evaluation.

First-principles models are developed for the reaction and downstream separation steps of the Biogas-based Oxidative Coupling of Methane (BG-OCM) process. The reaction section applies adiabatic packed-bed reactors. The CO₂ removal is performed by amine absorption or by a hybrid process employing Gas-Separation Membranes (GSM) and absorption. The nal hydrocarbon separation is achieved by cryogenic distillation to recover the un-reacted methane and achieve polymer-grade bio-ethylene. Costing models are also developed to enable economic evaluation and optimization.

A new software package is implemented in Python to facilitate the stochastic and Surrogate-Assisted Optimization (SAO) using the process models developed in the software Aspen Plus. A new modication to the Probability of Improvement (PI) algorithm is proposed and applied to deal with failed simulations in SAO. Dierent process congurations and operating conditions are investigated and optimization is applied to the design of each section of the BG-OCM process individually. The reaction product yield is maximized and the utility and equipment cost for the separations is minimized.

The maximum achieved OCM reaction product yield with the biogas feed is 16.12 %, which is in accordance with recent developments in adiabatic packed bed reactors. The un-converted methane and the hydrogen (H2) and carbon monoxide (CO) by-products exit the proposed BG-OCM process in an o-gas stream, i.e., lights stream. This is an important side-product stream that is sold to be energetically recovered in an nearby Combined Heat and Power (CHP) plant. The optimal separation structure comprises a standalone amine-absorption process for removing CO₂ and a cryogenic distillation pro-

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cess applying turbo-expansion to reduce refrigeration utility cost. An economic evaluation is carried out to estimate bio-ethylene production cost considering utility, equipment, and educts costs and by-product revenues for a BG-OCM plant located in Brazil. A Monte Carlo simulation is applied in order to incorpo- rate uncertainty in the cost estimation. The estimated bio-ethylene production cost is 0.53±0.73USD kg_C⁻¹₂_H₄, which is below typical market values for fossil ethylene. The production cost is lower than a target value of 0.7 USD kg_C⁻¹

2H4

with a 55.2 % condence and lower than 1.73 USD kg⁻¹_C

2H4 with a 95 % condence. The revenue obtained by selling the lights stream as a side-product is very relevant and, thus the bio-ethylene production cost is found to be very sensitive to the assumed sales price for this stream. The sales price is assumed to be 40 %to100 % of the natural gas price in Brazil. Therefore, the proposed BG-OCM process can be feasible in locations with high prices for energy and petrochemicals like Brazil. Further work should focus on the utilization and valorization of the lights stream. Its carbon monoxide and hydrogen content can be converted to methane via Sabatier reaction and the stream can be recy- cled back to the OCM reactor to increase the ethylene output. Another option is the production of syngas as a by-product via methane reforming. These process technologies can generate incentive for the anaerobic treatment of organic residues and create new pathways for the material utilization of biogas in the production of biochemicals and biofuels.

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Deutsche Zusammenfassung

Biogas enthält hauptsächlich Methan (CH₄) und Kohlendioxid (CO₂) und ist ein wichtiger erneuerbarer Energieträger, da dieser schwankende Energiequellen wie Wind und Sonne gut ergänzt. Weiterhin könnte eine Methanaktivierung die Produktion hochwertiger Biochemikalien und Biotreibstoe aus Biogas er- möglichen. Diese Doktorarbeit untersucht die Herstellung von Bioethylen (C₂H₄) durch oxidative Kopplung von Methan, mit Biogas als Methanquelle, auf der Basis von Prozessmodellierung, -Simulation, und -Optimierung, gefolgt von einer Wirtschaftlichkeitsanalyse.

Phänomenologische Modelle sind für die Reaktion und das Downstreaming des Biogas-basierten OCM-Prozesses BG-OCM entwickelt worden. Der Reak- tionsteil nutzt adiabate Festbettreaktoren. Die CO₂-Abtrennung erfolgt en- tweder durch eine Aminabsorption oder durch einen hybriden Prozess beste- hend aus Gastrennmembranen und Absorption. Die Kohlenwasserstotrennung erfolgt auch weiterhin durch eine kryogene Destillation. Weiterhin sind Kosten- modelle für die Wirtschaftlichkeitsanalyse und -optimierung entwickelt worden.

Ein neues, in Python implementiertes Softwarepaket, ermöglicht die Opti- mierung durch stochastische und surrogatunterstützte Algorithmen mit Nutzung von Prozessmodelle in der kommerziellen Software Aspen Plus. Eine neue Mod- izierung der `Probability of Improvement' Methode wurde entwickelt und erfolgreich angewendet, um fehlgeschlagene Simulationen bei der surrogatunter- stützte Optimierung besser behandeln zu können. Unterschiedliche Prozesskon- gurationen und Betriebsbedingungen wurden untersucht und das Design jedes BG-OCM Prozessschritts wurde individuell optimiert bzw. die Produktaus- beute bei der Reaktion maximiert und die Hilfsmitteln- und Investitionskosten für die Produkttrennung minimiert.

Die maximal erreichte Produktausbeute bei der OCM-Reaktion liegt bei 16.12 % und entspricht aktuellen Entwicklungen mit adiabate Festbettreak- toren. Das nicht-umgewandelte Methan und die Nebenprodukte Kohlenmonoxid (CO) und Wassersto (H₂) treten im entwickelten Prozess in einem Leichtstrom auf, der ein wichtiges Nebenprodukt darstellt. Die optimale Trennkongura- tion enthält einen Aminabsorptionsprozess für die CO₂-Entfernung und einen kryogenen Destillationsprozess mit Turbo-Expansion, um die Kühlkosten zu reduzieren. Eine Wirtschaftlichkeitsanalyse schätzt die Produktionskosten für das Bioethylen auf Basis der Kosten für Hilfsmittel, Equipment und Edukte sowie Einkünfte von Nebenprodukte für eine BG-OCM Anlage in Brasilien ab. Hierbei wird eine Monte-Carlo-Simulation zur Abschätzung der Unsicher- heitsfaktoren bei der Kostenschätzung durchgeführt. Die daraus resultierenden Produktionskosten liegen bei 0.53±0.73USD kg_C⁻¹₂_H₄ und sind niedriger als typ-

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ische Marktwerte für das fossile Ethylen. Die Produktionskosten sind niedriger als ein Zielwert von 0.7 USD kg⁻¹_C

2H4 mit einem 55.2 % Kondenzfaktor und niedriger als1.73 USD kg⁻¹_C

2H4 mit einem95 %Kondenzfaktor. Nebeneinkünfte von dem Verkauf des Leichtstroms sind sehr relevant für die Wirtschaftlichkeit und daher wirkt der angenommene Verkaufspreis für diesen Strom sich stark auf die Produktionskosten für das Bioethylen aus. Der Verkaufspreis wurde als 40 % to 100 % des Erdgaspreises in Brasilien angenommen. Das BG-OCM Prozesskonzept kann an Orten mit sehr guter Verfügbarkeit von Bioressourcen für die Biogasherstellung und mit einem hohen Preis für Energie und Petro- chemikalien, wie z.B. Brasilien, wirtschaftlich erfolgreich sein. Weitere Unter- suchungen sollten sich auf die Verwertung des Leichtsstroms fokussieren. Deren Kohlenmonoxid- und Wasserstoanteilen können mittels Sabatier Reaktion zu Methan umgesetzt werden und dieser Strom dann wieder in den OCM Reak- tor zurückgeführt werden. Eine weitere Alternative wäre die Herstellung von Synthesegas als Nebenprodukt mittels Reformierung. Derartige Prozesstech- nologien können die Behandlung von organischen Restmitteln motivieren und erönen neue Wege für die stoiche Nutzung von Biogas für die Produktion von Biochemikalien und Biobrennstoe.

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Resumo em Português

Biogas é composto predominantemente de metano (CH₄) e dióxido de carbono C₂H₄e é um importante transportador de energia renovável, pois complementa bem outras fontes intermitentes como eólica e solar. A ativação de metano possibilita a produção de bioquímicos e biocombustíveis a partir do biogás.

Esta dissertação investiga a produção de bio-etileno (C₂H₄) via acoplamento oxidativo de metano OCM contido no biogás através de modelagem, simulação, e otimização de processos e de uma análise tecno-economica.

Modelos fenomenológicos são desenvolvidos para as etapas de reação e sepa- ração do processo OCM alimentado por biogás BG-OCM. A reação é realizada em reatores de leito xo em regime adiabático. A remoção de CO2 pode ser realizada por absorção com aminas ou por um processo híbrido utilizando mem- branas de permeação gasosa e absorção. A separação nal dos hidrocarbonetos é realizada por destilação criogênica. Modelos de custo também são desenvolvidos para possibilitar análises e otimizações econômicas.

Um novo software foi implementado em Python para facilitar a otimização estocástica e auxiliada por modelos substitutos com base nos modelos de processo implementados no software Aspen Plus. Uma modicação no algorítmo de Probabilidade de Melhoria PI foi proposta e aplicada para lidar com simulações mal-sucedidas. Várias congurações de processo e condições operacionais são investigadas e otimizações são aplicadas ao projeto de cada seção do processo BG-OCM individualmente. O rendimento de produto na reação é maximizado e o custo de utilidades e de equipamentos nas separações é minimizado.

O rendimento máximo de produto obtido na reação OCM é de16.12 %e está de acordo com desenvolvimentos recentes em termos de OCM em reatores de leito xo em regime adiabático. O metano não convertido bem como os sub- produtos hidrogênio (H₂) e monóxido de carbono (CO) saem do processo em uma corrente gasosa de componentes leves, que é um importante subproduto recuperado energeticamente em uma unidade de cogeração nas proximidades.

A estrutura ótima para a separação contempla uma unidade de absorção com aminas para remoção de CO2e uma unidade de destilação criogênica utilizando turbo-expansão para reduzir o custo de utilidades de refrigeração. Uma avali- ação econômica é realizada para estimar o custo de produção do bio-etileno considerando o custo de utilidades, equipamentos e matérias primas e as receitas de sub-produtos para uma planta de BG-OCM localizada no Brasil. Uma simulação Monte Carlo é realizada para incorporar as incertezas contidas nas estimativas de custo. O custo de produção resultante é 0.53±0.73USD kg⁻¹_C

2H4

e está abaixo de valores típicos de mercado para o etileno de origem fóssil. O custo de produção é menor ou igual a um valor alvo de0.7 USD kg⁻¹_C₂_H₄ com um

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fator de conança de55.2 %e menor ou igual a1.73 USD kg⁻¹_C

2H4 com um fator de conança de 95 %. Receitas obtidas com a venda da corrente de leves são importantes e, portanto o custo de produção do bio-etileno é altamente sensível ao preço dado à esta corrente. Para a análise, assumiu-se uma fração (40 %to 100 %) do preço do gás natural no Brasil. Portanto, o processo BG-OCM pro- posto pode ser viável em locais onde há disponibilidade de bio-recursos para a produção de biogás em larga escala e onde os preços de energia e petroquímicos são altos, como é o caso do Brasil. Trabalhos futuros devem focar na valorização da corrente de leves. O hidrogênio e monóxido de carbono podem ser conver- tidos em metano via reação de Sabatier e a corrente pode ser reciclada ao reator OCM. Outra opção é a produção de gás de síntese como sub-produto através da reforma de metano. Estas tecnologias podem criar incentivo para o tratamento anaeróbico de resíduos orgânicos e abrir novas rotas para a utilização material de biogas na produção de bioquímicos e biocombustíveis.

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Publications

This thesis is partially based on already published contributions. In the follow- ing these are divided into Journal articles, papers within conference proceedings, oral presentations without papers, and a list of all supervised theses. All contributions are ordered by date of publication.

Journal Articles

1. Penteado, Alberto T.; Esche, Erik; Salerno, Daniel; Godini, Hamid R.;

Wozny, Günter (2016): Design and Assessment of a Membrane and Ab- sorption Based Carbon Dioxide Removal Process for Oxidative Coupling of Methane, Industrial & Engineering Chemistry Research, 55, 7473-7483 2. Penteado, Alberto; Kim, Mijin; Godini, Hamid R.; Esche, Erik; Repke, Jens-Uwe. (2018): Techno-economic evaluation of a biogas-based oxidative coupling of methane process for ethylene production, Frontiers of Chemical Science and Engineering, 12-4, 598-618

3. Godini, Hamid Reza; Azadi, Mohammadreza; Penteado, Alberto T.;

Khadivi, Mohammadali; Wozny, Günter; Repke, Jens-Uwe. (2019): A multi-perspectives analysis of methane oxidative coupling process based on miniplant-scale experimental data, Chemical Engineering Research and Design, 151, 5669

4. Rosa, Licianne P. S.; Pontes, Karen V.; Costa, Glória M. N., Pen- teado, Alberto T.; Esche, Erik; Repke, Jens-Uwe. (2020): An equation- oriented novel approach for modeling the falling lm absorber using rigorous thermodynamic and transport description, Chemical Engineering Research and Design, 159, 179194

5. Layritz, Lucia S.; Dolganova, Iulia; Finkbeiner, Matthias; Luderer, Gun- nar; Penteado, Alberto T.; Ueckerdt, Falko; Repke, Jens-Uwe. (2021):

The potential of direct steam cracker electrication and carbon capture &

utilization via oxidative coupling of methane as decarbonization strategies for ethylene production, Applied Energy, 296, 117049

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Conference Papers

1. Penteado, Alberto T.; Esche, Erik; Wilhelm, Robert; Godini, Hamid;

Salerno, Daniel; Tolksdorf, Gregor; Merchan, Victor Alejandro; Wozny, Günter (2016): Modeling, Simulation, and Economic Evaluation of a Hy- brid CO2 Capture Process for Oxidative Coupling of Methane, Computer Aided Chemical Engineering, 38, 1231-1236

2. Penteado, A.; Esche, Erik; Salerno, Daniel; Godini, Hamid R.; Repke, Jens-Uwe; Wozny, Günter (2016): The Systematic Design of CO2 Cap- ture Processes Applied to the Oxidative Coupling of Methane, Technical Transactions Mechanics, 1-M, 183-194

3. Wilhelm, Robert; Esche, Erik; Guetta, Zion; Penteado, Alberto; Repke, Jens-Uwe; Thielert, Holger; Wozny, Günter (2016): Development of a Mobile Pilot Plant for the Evaluation of Novel Scrubbing Liquids for the Absorption of CO2 from Industrial Gases, Technical Transactions Me- chanics, 1-M, 243-250

4. Salerno, Daniel; Godini, Hamid R.; Penteado, Alberto; Esche, Erik;

Wozny, Günter (2016): Techno-Economic Evaluation of an Oxidative Coupling of Methane Process at Industrial Scale Production, Computer Aided Chemical Engineering, 38, 1785-1790

5. Penteado, Alberto T.; Kim, Mijin; Godini, Hamid R.; Esche, Erik;

Repke, Jens-Uwe (2017): Biogas as a Renewable Feedstock for Green Ethylene Production via Oxidative Coupling of Methane: Preliminary Feasibility Study, Chemical Engineering Transactions, 61, 589-594 6. Penteado, Alberto T.; Schöneberger, Jan C.; Esche, Erik; Godini,

Hamid R.; Wozny, Günter; Repke, Jens-Uwe (2018): Sequential Flow- sheet Optimization: Maximizing the Exergy Eciency of a High-Pressure Water Scrubbing Process for Biogas Upgrade, Computer Aided Chemical Engineering, 43, 13291334

7. Godini, Hamid Reza; Azadi, Mohammadreza; Khadivi, Mohammadali;

Gharibi, Abolfaz; Jazayeri, Seyed M.; Salerno, Daniel; Penteado, A.;

Mokhtarani, Babak; Orjuela, Alvaro; Karsten, Tim; Wozny, Günter (2018):

Conceptual Process Design and Economic Analysis of Oxidative Coupling of Methane, Computer Aided Chemical Engineering, 44, 361366

8. Penteado, Alberto T.; Godini, Hamid R.; Esche, Erik; Lovato, Gio- vanna; Rodrigues, José Alberto D.; Repke, Jens-Uwe (2018): Optimal

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Design of a CO2 Removal Section for a Biogas-Based Oxidative Cou- pling of Methane Process, Blucher Chemical Engineering Proceedings, 1-5, 41514154

9. Rosa, Licianne P. S.; Pontes, Karen V.; Penteado, Alberto T.; Tolks- dorf, Gregor; Esche, Erik; Repke, Jens-Uwe (2018): Using MOSAIC- modeling and Cape-Open Interfaces for Property Calculations in Matlab, Blucher Chemical Engineering Proceedings, 1-5, 43924395

10. Penteado, Alberto T.; Esche, Erik; Weigert, Joris; Repke, Jens-Uwe (2020): A Framework for Stochastic and Surrogate-Assisted Optimization using Sequential Modular Process Simulators, Computer Aided Chemical Engineering, 47, 19031908

Oral Presentations Without Proceedings

1. Penteado, Alberto; Esche, Erik; Wozny, Günter (2015): Implementa- tion of a Customized Gas-Separation Membrane Model into Commercial Flowsheeting Software to Simulate a Hybrid CO2 Removal Process for Oxidative Coupling of Methane, AIChE Annual Meeting, Fall 2015, Salt Lake City, UT, USA

2. Penteado, Alberto; Kim, Mijin; Godini, Hamid R.; Esche, Erik; Speel- manns, Eva; Repke, Jens-Uwe (2016): Development of a Computation- ally Ecient Model of a Packed-Bed Membrane Reactor for the Oxidative Coupling of Methane, AIChE Annual Meeting, Fall 2016, San Francisco, CA, USA

Supervised Theses

1. Yarce, Gabriel (2016): Sustainable Synthesis of Poly-(Oxymethylene) Dimethyl Ethers (OME) based on CO2 and H2, Master's Thesis

2. Rosenstiel, Andreas (2018): Techno-economic study of a concentrated solar thermal plant with sulphur as thermo-chemical energy storage for base-load power generation and sulphuric acid recycling, Master's Thesis 3. Layritz, Lucia (2019): Direct electrication and carbon capture and utilization as climate mitigation strategies for ethylene production - A life cycle perspective, Master's Thesis

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4. Wuckert, Georg (2019): Experimentelle Untersuchung, Auslegung und Simulation eines Druckwechsel-Adsorptionssystems zur Separation eines H₂/O₂ Gasgemisches

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List of Figures

1.1 Biodigester in China with a production capacity of412 Nm³h⁻¹ from dry chicken excrement and pig manure (left). Bio-mixer for substrate conditioning and feeding (right). Photos kindly provided by Eco Erneuerbare Energien GmbH (www.eco-gmbh.eu) 9 1.2 Vinasse from ethanol production in a glass beaker. Photo kindly

provided by the Laboratory of Biological Wastewater Treatment from Mauá Institiute of Technology. . . 12 1.3 General process owsheet for the BG-OCM process . . . 32 1.4 Alternative integration options for the BG-OCM process . . . . 35 1.5 Process ow diagram for a hybrid membrane and absorption CO₂

removal process for OCM. CO2-rich streams are marked in red, lean amine streams are marked in light green, and rich amine streams are marked in dark green. . . 36 1.6 Flowsheet for the cryogenic distillation process applying the RSV

scheme. In the cold-box exchangers, hot streams (streams being cooled/condensed) are marked red and cold streams (streams being heated/evaporated) are marked blue. Based on Siluria Technologies, 2015 . . . 40 2.1 Schematic representation of a Packed-Bed Reactor with the dif-

ferential balance volume for the Plug-Flow Reactor model . . . 44 2.2 Simulation owsheet of the lab-scale OCM reactor set-up used

to compare model results with experimental data . . . 48 2.3 Methane conversion for dierent contact times in isothermal lab-

scale PBR at 700°C and 830°C. Comparison of reactor model predictions and experimental data from Stansch, Mleczko, and Baerns, 1997. . . 49 2.4 Ethylene yield for dierent contact times in isothermal lab-scale

PBR at700°Cand830°C. Comparison of reactor model predictions and experimental data from Stansch, Mleczko, and Baerns, 1997. . . 50 2.5 Schematic representation of an envelope type membrane module. 52

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2.6 Graphical representation of the solution diusion mechanism aross a dense membrane. Adapted from (Ohlrogge and Ebert, 2012) . 52 2.7 Balance Volume: Membrane Cell . . . 55 2.8 Pressure drop calculated by Equation 2.18 (line) and experimen-

tal measurements from (Stünkel, 2013) (circles) for dierent inlet supercial gas velocities . . . 55 2.9 Analysis on the number of nite elements required to solve the

membrane module model . . . 57 2.10 Parity plots of simulation and experimental results for CO2 re-

moval and C₂H₄ recovery using PIM module. Simulations performed with the ACM model developed in this work and the experimental data is used as published in (Stünkel, 2013). . . . 58 2.11 Solubility of ethylene in water as a P-x diagram at 310.881K,

360.901K, and 394.238K. Experimental data (crosses) from (Davis and McKetta, 1960), model predictions with tted parameters (continuous lines) and with APV-100 BINARY parameters (dashed lines). . . 62 2.12 Solubility of Ethylene in aqueous MEA at dierent concentra-

tions, atmospheric pressure, and at288 Kand298 K: Model predictions (dots with trend line) and experimental data from (Sada and Kito, 1972) (crosses) . . . 62 2.13 Solubility of Carbon Dioxide in 30 wt% aqueous MEA solution

at313 K,353 K, and393 K: Model predictions and experimental data from (Jou, Mather, and Otto, 1995). . . 63 2.14 Vapor-liquid equilibrium of methane and ethylene as a P-xy dia-

gram at150.014 Kand190.012 K. Model predictions and experimental data from (Miller, Kidnay, and Hiza, 1977) . . . 65 2.15 Vapor-liquid equilibrium of ethylene and ethane as a P-xy dia-

gram at 233.182 K and 263.1524 K. Model predictions and experimental data from (Fredenslund, Mollerup, and Hall, 1976) . 65 2.16 Installed equipment cost of packed columns. Cost estimates by

APEA (dots) and by correlation (surface) . . . 70 3.1 Graphical representation of the optimization framework . . . . 75 3.2 Iterative minimization of a one-dimensional unconstrained func-

tion by the original PI method. Iterations 0 and 1. . . 81 3.3 Iterative minimization of a one-dimensional unconstrained func-

tion by the original PI method. Iterations 2 and 3. . . 82

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List of Figures 3.4 Iterative minimization of a one-dimensional unconstrained func-

tion by the enhanced PI method described by Jones, 2001. Iter- ation 0. . . 84 3.5 Iterative minimization of a one-dimensional unconstrained func-

tion by the proposed enhanced PI method using SHGO to locate all maxima of the PI function. Iteration 0. . . 84 3.6 Simulation Flowsheet of the HDA Process. Main process streams

(black), light gases streams (blue), heavies streams (purple). . . 89 3.7 HDA process optimization case solved by the enhanced PI method.

Rigorous function evaluations (black dots), optimum (magenta dot), surrogate model (surface with color scale) (Penteado et al., 2020). . . 92 3.8 Convergence map for the HDA process optimization case. Prob-

ability of a simulation belonging to the class converged (color map) computed with kNN classication and k = 3, converged simulations (dots), failed simulations (crosses) (Penteado et al., 2020). . . 92 4.1 Membrane cascade congurations considered in the previous stud-

ies. Adapted from (Penteado et al., 2016b) . . . 95 4.2 Sensitivity study for the inuence of the absorption pressure on

the operating costs for feed composition II and standalone absorption. Reproduced from (Penteado et al., 2016b)) . . . 96 4.3 Superstructure and optimal process conguration for the gas

quenching, rst compression, amine-based CO₂removal, and second compression steps of the BG-OCM process. Blank equipment and dashed line streams are not employed in the optimal process conguration. Adapted from (Penteado et al., 2018a). . 98 4.4 Process simulation owsheet for the BG-OCM process in Aspen

Plus v10 . . . 101 4.5 Payback period and ethylene production as a function of the

biogas feed ow for biogas-based OCM plants. The biogas plant numbers are listed in Tables 1.6 and 1.5. . . 101 4.6 Simulation owsheet for the OCM reaction section implemented

in Aspen Plus . . . 103 4.7 Light-o curve for the rst OCM Packed-Bed Reactor R-01 under

the optimal conditions obtained with DE . . . 108 4.8 Peak temperature for the rst OCM Packed-Bed Reactor R-01

under the optimal conditions obtained with DE . . . 109

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4.9 Light-o curve for the rst OCM PBR of this work in comparison to results from (Pirro et al., 2018) under total pressure of 150 kPa, methane to oxygen ratio of 12, contact time of 3.45 kgcats mol⁻¹_CH

4, no gas-phase dilution, gas-hourly-space- velocity of 35 000 h⁻¹, and using dierent catalysts . . . 109 4.10 Installed equipment cost for each equipment category in the

OCM reaction section . . . 111 4.11 Simulation owsheet of the hybrid CO2 removal process imple-

mented in Aspen Plus . . . 114 4.12 Simulation owsheet of the optimal CO₂ removal process using

standalone absorption . . . 118 4.13 Yearly utility cost rates for the CO₂removal section using the op-

timal standalone absorption conguration and the hybrid membrane + absorption conguration . . . 120 4.14 Installed equipment cost for the CO₂ removal section using the

optimal standalone absorption conguration and the hybrid membrane + absorption conguration . . . 120 4.15 Total annualized cost per mass of ethylene for the CO2 removal

section of the BG-OCM process . . . 122 4.16 Simulation owsheet of the conventional distillation section using

only external refrigeration . . . 128 4.17 Simulation owsheet of the external refrigeration system for the

conventional distillation section . . . 129 4.18 Simulation owsheet of the distillation section with RSV . . . . 131 4.19 Simulation owsheet of the external refrigeration system for the

distillation section with RSV . . . 132 4.20 Stream temperature proles in the pre-cooling multi-stream plate

n heat exchanger (MHX1) within the RSV distillation scheme 134 4.21 Utility cost rates for the distillation section using the traditional

and RSV schemes . . . 136 4.22 Equipment cost for the distillation section using the traditional

and RSV schemes . . . 136 4.23 Total annualized cost for the distillation section using the tradi-

tional and RSV schemes . . . 138 4.24 Inlet and outlet material and energy ows considered for the

economic evaluation . . . 141

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List of Figures A.1 Methane conversion for dierent contact times in isothermal lab-

scale Packed-Bed Reactor at 700°C and 830°C. Comparison of reactor model predictions and experimental data from (Stansch, Mleczko, and Baerns, 1997). . . 158 A.2 Oxygen conversion for dierent contact times in isothermal lab-

scale Packed-Bed Reactor at 700°C and 830°C. Comparison of reactor model predictions and experimental data from (Stansch, Mleczko, and Baerns, 1997). . . 158 A.3 Ethylene yield for dierent contact times in isothermal lab-scale

Packed-Bed Reactor at 700°C and 830°C. Comparison of reactor model predictions and experimental data from (Stansch, Mleczko, and Baerns, 1997). . . 159 A.4 Ethane yield for dierent contact times in isothermal lab-scale

Packed-Bed Reactor at 700°C and 830°C. Comparison of reactor model predictions and experimental data from (Stansch, Mleczko, and Baerns, 1997). . . 159 A.5 Carbon Dioxide yield for dierent contact times in isothermal

lab-scale Packed-Bed Reactor at 700°Cand830°C. Comparison of reactor model predictions and experimental data from (Stan- sch, Mleczko, and Baerns, 1997). . . 160 A.6 Carbon Monoxide yield for dierent contact times in isothermal

lab-scale Packed-Bed Reactor at 700°Cand830°C. Comparison of reactor model predictions and experimental data from (Stan- sch, Mleczko, and Baerns, 1997). . . 160 A.7 Solubility of Hydrogen in Water at310.891 K,366.459 K,422.004 K

and 477.554 K: Model predictions and experimental data from (Gillespie and Wilson, 1980). . . 161 A.8 Solubility of Nitrogen in Water at 273 K, 353 K, and 433 K:

Model predictions and experimental data from (Baranenko et al., 1990). . . 162 A.9 Solubility of Methane in Water at313.15 Kand373.29 K: Model

predictions and experimental data from (Kiepe et al., 2003). . . 162 A.10 Solubility of Ethylene in Water at 311 K, 360 K, and 394 K:

Model predictions and experimental data from (Davis and McK- etta, 1960). . . 163 A.11 Solubility of Ethane in Water at311 K,378 K, and444 K: Model

predictions and experimental data from (Culberson and McK- etta, 1950). . . 163

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A.12 Solubility of Carbon Monoxide in Water at 310 K and 366 K: Model predictions and experimental data from (Gillespie and Wilson, 1980). . . 164 A.13 Solubility of Carbon Monoxide in Water at 298 K, 348 K, and

393 K: Model predictions and experimental data from (Lucile et al., 2012). . . 164 A.14 Solubility of Hydrogen in MEA at 323 K, 373 K, and 423 K:

Model predictions and experimental data from (Kling and Mau- rer, 1991). . . 165 A.15 Solubility of Methane in aqueous MEA with3 kmol m⁻³at298 K,

348 K, and398 K: Model predictions and experimental data from (Carroll et al., 1998). . . 165 A.16 Solubility of Ethylene in aqueous MEA with dierent concen-

trations, atmospheric pressure, and at 288 K and 298 K: Model predictions and experimental data from (Sada and Kito, 1972). 166 A.17 Solubility of Ethane in aqueous MEA with3 kmol m⁻³ at298 K,

348 K, and398 K: Model predictions and experimental data from (Jou and Mather, 2006). . . 166 A.18 Solubility of Carbon Dioxide in 30 wt% aqueous MEA solution

at313 K,353 K, and393 K: Model predictions and experimental data from (Jou, Mather, and Otto, 1995). . . 167 D.1 Simulation owsheet for the BG-OCM reaction section with op-

timal conditions . . . 173 D.2 Light-o curve for the second OCM Packed-Bed Reactor R-02

under the optimal conditions obtained with DE . . . 176 D.3 Light-o curve for the second OCM Packed-Bed Reactor R-02

under the optimal conditions obtained with DE . . . 176 E.1 Simulation owsheet of the optimal CO₂ removal process us-

ing standalone absorption 1: compression and membrane sub- section. Simulation warnings are due to by-passed equipment. . 184 E.2 Simulation owsheet of the optimal CO2 removal process using

standalone absorption 2) absorption and desorption sub-section.

Simulation warnings are due to by-passed equipment. . . 185 E.3 Installed cost of packed columns. Cost estimates by APEA (dots)

and by correlation (surface) . . . 189 E.4 Installed cost of compressors. Cost estimates by APEA (dots)

and by correlation (lines) . . . 189

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List of Figures E.5 Installed cost of shell & tube heat exchanger E-201. Cost esti-

mates by APEA (dots) and by correlation (lines) . . . 190 E.6 Installed cost of shell & tube heat exchanger E-202. Cost esti-

mates by APEA (dots) and by correlation (lines) . . . 191 E.10 Installed cost of plate & frame heat exchanger E-304. Cost esti-

mates by APEA (dots) and by correlation (lines) . . . 192 E.14 Installed cost of U-tube reboiler of column C-304. Cost estimates

by APEA (dots) and by correlation (lines) . . . 193 E.15 Installed cost of pumps P-201, P-301, and P-302. Cost estimates

by APEA (dots) and by correlation (lines) . . . 193 F.1 Simulation owsheet of the conventional distillation section using

only external refrigeration . . . 210 F.2 Simulation owsheet of the external refrigeration system for the

conventional distillation section . . . 214 F.3 Simulation owsheet of the distillation section with RSV . . . . 220 F.4 Simulation owsheet of the external refrigeration system for the

distillation section with RSV . . . 228 F.5 Stream temperature proles in the demethanizer condenser multi-

stream plate n heat exchanger (MHX2) within the RSV distillation scheme . . . 250 F.6 Stream temperature proles in the C2-splitter condenser plate

n heat exchanger (MHX3) within the RSV distillation scheme 250 If not stated otherwise, all images, graphics or gures in this thesis were created by the author himself.

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List of Tables

1.1 Typical methane-rich gas compositions from dierent sources . 10 1.2 Biogas and biomethane potential in the state of São Paulo, Brazil.

Data extracted from the interactive map entitled Biogas, Biomethane, and Electrical Power in São Paulo (Coelho et al., 2019) . . . 11 1.3 Major biogas contaminants and the issues associated with them

according to (Ryckebosch, Drouillon, and Vervaeren, 2011) . . 13 1.4 Summary of the main desulfurization methods applied in the

biogas industry . . . 17 1.5 Estimated methane production for the biogas plants* . . . 21 1.6 List of reported large capacity biogas plants worldwide . . . 22 1.7 Range of experimental conditions and validity for the kinetic

model by Stansch, Mleczko, and Baerns, 1997 . . . 27 2.1 Range of experimental conditions for the lab-scale isothermal

PBR utilized by Stansch, Mleczko, and Baerns, 1997 and reproduced in the simulations for comparison . . . 49 2.2 Range of experimental conditions applied by (Stünkel, 2013) and

used to regress the permeance calculation parameters . . . 58 2.3 Summary of utility conditions and costs . . . 67 2.4 Biogas production cost . . . 68 2.5 Cost drivers selected for equipment cost correlations . . . 70 3.1 Solution of the HDA process optimization case by dierent algo-

rithms (Penteado et al., 2020) . . . 91 4.1 Dierent reactor gas outlet compositions considered as feed for

the design of the hybrid CO₂ removal process in the previous studies . . . 94 4.2 Biogas feed conditions assumed for the preliminary techno-economic

evaluations (Penteado et al., 2018b) . . . 100 4.3 Biogas feed conditions for the reaction section optimization in

Section 4.2 . . . 102 4.4 Table of decision variables and bounds for the OCM reaction

section optimization . . . 104

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4.5 Optimization results obtained with the dierent algorithms . . 106 4.6 Decision variable values for each optimization solution . . . 106 4.7 Decision variables and bounds for the CO₂ removal cost mini-

mization case study. Block and stream numbers correspond to those in Figure 4.11 . . . 116 4.8 Decision variable values for the CO₂ removal cost minimization 119 4.9 Resulting design for the absorption and desorption columns and

the estimated pressure drop for the standalone absorption conguration . . . 123 4.10 Distillation gas feed stream conditions . . . 126 4.11 Product purity and recovery constraints implemented as design-

specs for the demethanizer and C2-splitter columns . . . 126 4.12 Total utility cost rates in USD year⁻¹ for each utility category

and process section. Negative values imply utility export with revenue generation . . . 141 4.13 Total equipment cost in USD for each equipment category and

process section. . . 142 4.14 Flow rates, cost ranges, and cash ows for all educts and side

products of the BG-OCM process . . . 144 4.15 Stream results for the lights by-product stream . . . 147 4.16 Comparison between natural gas characteristics specied by ANP

16-2008 and those obtained for the light gases stream . . . 147 4.17 Best and worst case scenarios for the ethylene production cost . 148 4.18 Bio-ethylene production cost in USD kg_C⁻¹

2H4 resulting from the Monte Carlo simulation with dierent condence levels . . . 150 D.1 Stream results for the BG-OCM reaction section with optimal

conditions . . . 174 D.2 Utility cost for each equipment in the BG-OCM reaction section 177 D.3 Installed equipment cost per equipment category in the BG-OCM

reaction section . . . 177 D.4 Installed equipment cost in USD for each equipment in the BG-OCM

reaction section . . . 178 D.5 Equipment specication for jacketed heat exchangers in the OCM

reaction section . . . 178 D.6 Equipment specication for shell & tube heat exchangers in the

OCM reaction section . . . 179 D.7 Equipment specications for the furnaces in the BG-OCM reac-

tion section . . . 180

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List of Tables D.8 Equipment specications for the reactors in the BG-OCM reac-

tion section . . . 181 E.1 Material and energy balances for the optimal CO₂ removal pro-

cess conguration using standalone absorption . . . 195 E.2 Utility cost for each equipment in the BG-OCM CO₂removal sec-

tion for standalone absorption and hybrid membrane-absorption process congurations . . . 205 E.3 Equipment cost in USD per equipment type for the Absorption

and Hybrid process congurations . . . 206 E.4 Equipment cost in USD for each equipment in the Absorption

and Hybrid process congurations . . . 207 F.1 Material and energy balances for the distillation section using

the traditional distillation scheme . . . 211 F.2 Material and energy balances for the refrigeration section of the

distillation section using the traditional distillation scheme . . . 215 F.3 Material and energy balance for the distillation section with RSV

scheme . . . 221 F.4 Material and energy balance for the refrigeration section of the

distillation section with RSV scheme . . . 229 F.5 Utility consumption and cost rates for every unit in the tradi-

tional and RSV distillation schemes . . . 232 F.6 Utility consumption and cost rate for dierent categories for the

traditional and RSV distillation schemes . . . 233 F.7 Installed equipment cost in USD for each equipment type in the

traditional and Recycle Split Vapor (RSV) distillation schemes 234 F.8 Installed equipment cost in USD for each equipment in the tra-

ditional and RSV distillation schemes . . . 235 F.9 Equipment specications for horizontal drums in the traditional

distillation scheme . . . 236 F.10 Equipment specications for centrifugal gas compressors in the

traditional distillation scheme . . . 237 F.11 Equipment specications for shell and tube heat exchangers in

the traditional distillation scheme . . . 238 F.12 Equipment specications for vertical drums in the traditional

distillation scheme . . . 239 F.13 Equipment specications for columns in the traditional distilla-

tion scheme . . . 240

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F.14 Equipment specications for U-tube heat exchangers in the traditional distillation scheme . . . 241 F.15 Equipment specications for centrifugal pumps in the traditional

distillation scheme . . . 242 F.16 Equipment specications for turbo-expanders in the traditional

distillation scheme . . . 242 F.17 Equipment specications for turbo-expanders in the RSV distil-

lation scheme . . . 243 F.18 Equipment specications for centrifugal gas compressors in the

RSV distillation scheme . . . 244 F.19 Equipment specications for shell and tube heat exchangers in

the RSV distillation scheme . . . 245 F.20 Equipment specications for vertical drums in the RSV distilla-

tion scheme . . . 246 F.21 Equipment specications for U-tube heat exchangers in the RSV

distillation scheme . . . 247 F.22 Equipment specications for plate n heat exchangers in the RSV

distillation scheme . . . 248 F.23 Equipment specications for columns in the RSV distillation

scheme . . . 249

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List of Acronyms

ACM Aspen Custom Modeler^® AD Anaerobic Digestion

ANP Agência Nacional do Petróleo, Gás Natural e Biocombustíveis APEA Aspen Process Economic Analyzer^®

ASU Air Separation Unit

Bbop a framework for Black-Box Optimization with sequential modular simulators

BG-OCM Biogas-based Oxidative Coupling of Methane CAPEX Capital Cost or Expenditure

CS Carbon Steel

COM Component Object Model CHP Combined Heat and Power

CHPC Combined Heat, Power and Chemicals

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DE Dierential Evolution EDH Ethane Dehydrogenation EoS Equation of State

ESs Evolution Strategies FBR Fluidized-Bed Reactor GA Genetic Algorithm GHG Green-House Gas

GSM Gas-Separation Membranes gpu Gas Permeation Units

GPR Gaussian Process Regression

HETP Height Equivalent to a Theoretical Plate HDA Hydrodealkylation

HPWS High-Pressure Water Scrubbing HPS High-Pressure Steam

IAST Ideal Adsorbed Solution Theory

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List of Tables kNN k-Nearest Neighbor

LCA Life-Cycle Analysis or Assessment LCI Life-Cycle Inventory

LHHW Langmuir-Hinschelwood-Hougen-Watson HHV Higher Heating Value

LHV Lower Heating Value LPS Light Pressure Steam

MADS Mesh-Adaptive Direct Search MDEA N-Methyl Diethanolamine

MEA Monoethanolamine (IUPAC: 2-aminoethan-1-ol) MPS Medium Pressure Steam

NG-OCM Natural Gas-based Oxidative Coupling of Methane NRTL Non-Random Two Liquid

OCFE Orthogonal Collocation on Finite Elements OCM Oxidative Coupling of Methane

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OPEX Operating Cost or Expenditure OS Operating System

OSBL Outside Battery Limits

PEOM Poly-(ethylene oxide) Membrane PBR Packed-Bed Reactor

PBMR Packed-Bed Membrane Reactor PFR Plug-Flow Reactor

PI Probability of Improvement PIM Polyimide Membrane PR Peng-Robinson

PSA Pressure-Swing Adsorption PSO Particle Swarm Optimization PtG Power-to-Gas

PZ Piperazine

RAM Random-Access Memory

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List of Tables RBF Radial-Basis Function

RK Redlich-Kwong

SAO Surrogate-Assisted Optimization

SLSQP Sequential Least-Squares Programming SM Sequential-Modular

SHGO Simplicial Homology Global Optimization SQP Sequential Quadratic Programming

SS Stainles Steel

syngas Synthesis Gas, i.e., a gaseous stream composed of mostly CO and H2

RSV Recycle Split Vapor TAC Total Annualized Cost

TGO Topographical Global Optimisation TUB Technische Universität Berlin VLE Vapor-Liquid Equilibrium

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1 Introduction and Motivation

Biogas and landll gas are methane-rich gas mixtures obtained through the Anaerobic Digestion (AD) of organic matter. Biogas plays an important role in enabling low-carbon energy mixes. It is a great complement to other renewable energy sources such as solar and wind power, because its production is rather independent from climatic factors. It is estimated that AD of wastes can lead to a10 % to 13 %reduction in current global Green-House Gas (GHG) emissions through the replacement of fossil fuels and management of organic waste, crop burning, and deforestation (European Biogas Association, 2019). In fact, the European Union aims to achieve a 20 %share of renewable energy sources by 2020, with biogas representing at least a quarter of this amount (Holm-Nielsen, Al Seadi, and Oleskowicz-Popiel, 2009). The trend is expected to continue due to the new European Green Deal, which set targets of at least 50 % emission reductions by 2030 and carbon neutrality by 2050 (European Comission, 2019).

Current biogas utilization pathways are solely energetic, i.e., biogas is directly combusted in gas engines for CHP generation or, by removing CO₂ and other trace components, biogas is upgraded into biomethane to replace natural gas in several applications (Sun et al., 2015). Methane activation enables new pathways for biogas utilization via chemical routes such as syngas and ethylene. The Combined Heat, Power and Chemicals (CHPC) concept can potentially lead to more exible biogas processing plants with better economic and environmental performances (Previtali et al., 2018).

The OCM reaction (Equation 1.1) is the catalytic oxidation of methane (CH4) into ethylene (C₂H₄), which is a precursor component of major importance for the production of chemicals and polymers, e.g., polyethylene. Ethylene is com- monly produced from oil-derived naphtha or ethane via the energy-intensive steam cracking process. Thus, a BG-OCM process enables the production of a conventional building block from sustainable resources. It substitutes a fossil by a renewable feedstock and a thermochemical by a catalytic process, which is in-line with the principles of green chemistry (Anastas and Warner, 1998).

The biogas-based production of syngas and downstream products like methanol and dimethyl ether have already been considered to some extent in other recent studies (Chen et al., 2017; Previtali et al., 2018). However, to the best knowl- edge of the author, no study has previously considered a BG-OCM process.

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CH₄+1

2O₂−−→ 1

2C₂H₄+ H₂O (1.1)

The main goal and scientic contribution of this work is to conceptualize a Biogas-based Oxidative Coupling of Methane (BG-OCM) process from treated biogas to polymer-grade ethylene and to evaluate the techno-economic feasibility for its industrial-scale implementation. This is achieved by means of process modeling and simulation, followed by cost estimations and economic evaluations. Methodological contributions to the eld of process systems engineering with focus on optimization with sequential-modular owsheet simulators are also pursued in order to enable the optimal design of the industrial-scale plant.

The intermediate goals of this work are to:

Develop and validate rst-principles models for the most relevant reaction and separation units of the BG-OCM process in Aspen Plus v10

Develop a framework for optimal process design based on the simulation models and allowing for a exible choice of optimization methods

Develop new surrogate-assisted optimization methods suitable for sequential- modular owsheet simulations

Perform the conceptual design of an industrial-scale BG-OCM plant and apply the framework to determine the cost-optimal process conguration and operating conditions

Estimate the bio-ethylene production cost and compare it to that of conventional fossil-based ethylene

Identify technical and economic limitations of the process concept to guide further development and implementation

This thesis is structured in ve chapters plus appendices. Chapter 1 provides an introduction on current biogas and OCM technologies and motivates their combination. Chapter 2 describes the process models developed and used to simulate and evaluate the BG-OCM process. Chapter 3 provides details on the methods developed and applied to optimally design the BG-OCM plant.

Chapter 4 describes the optimal design and the techno-economic analysis of the industrial-scale plant. Chapter 5 summarizes and concludes the major results and ndings of this work.

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1.1 Biogas

Biogas is composed mostly of methane and carbon dioxide (CO₂). Minor amounts of oxygen, nitrogen, water, hydrogen sulde, ammonia, siloxanes, and other components may be also present. Table 1.1 reports dierent compositions found in literature for methane-rich gases produced from several dierent substrates, i.e., landll gas, sewage gas, farm biogas, and natural gas. Due to its high methane content, biogas is often combusted for heat and electricity production.

1.1.1 Substrates

Several feedstock or substrates can be used for biogas production, such as agricultural waste, manure, landll, or energy crops. Figure 1.1 shows a biogas plant based on animal waste as well as the mixer used for the substrate conditioning, i.e., crushing and mixing, and feeding. In 2014, Germany produced 66 %of its biogas based on maize silage and a total of 88 %from energy crops (Scheftelowitz et al., 2015). In emerging countries, this raises serious concerns regarding food and energy competition.

Brazil has a large biofuels industry with estimated bioethanol and biodiesel productions of 34.45×10⁹L and 5.8×10⁹L in 2019 respectively (Flake and Barros, 2019). These generate large amounts of agricultural solid and liquid waste, which is a potential substrate for biogas production. Coelho et al., 2019 mapped biogas and biomethane production potential in the state of São Paulo,

Figure 1.1: Biodigester in China with a production capacity of 412 Nm³h⁻¹ from dry chicken excrement and pig manure (left). Bio-mixer for substrate conditioning and feeding (right). Photos kindly provided by Eco Erneuerbare Energien GmbH (www.eco-gmbh.eu)

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Table1.1:Typicalmethane-richgascompositionsfromdierentsourcesSource(Rasi,Veijanen,andRintala,2007)(Sunetal.,2015)GasLandllSewageFarmBiogasLandllBiogasNaturalTypeGasGasPlantGasfromADGasCH447-5761-6555-5835-6560-7085-92CO237-4136-3837-3815-4030-400.2-1.5O2<1<1<110-N2<1-17<2<1-2150.20.31H2S36-115<0.136-1690-1000-40001.1-5.92Benzene0.6-2.30.1-0.30.7-1.32Toluene1.7-5.12.8-11.80.2-0.7H20-30H2O1-51-5NH351002TotalCl5100HeavyHydrocarbons009GiveninppmvGiveninmgNm −3

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1.1 Biogas

Table 1.2: Biogas and biomethane potential in the state of São Paulo, Brazil. Data extracted from the interactive map entitled Biogas, Biomethane, and Electrical Power in São Paulo (Coelho et al., 2019)

Production Potential in 1×10⁹Nm³year⁻¹ Substrate Biogas Biomethane

Animal waste 0.4 0.2

Landll 1.7 0.9

Sugar-cane waste 14.7 7.8

Total 16.8 8.9

Brazil, and some of these results are shown in Table 1.2. The biogas production potential from sugar-cane waste, i.e., vinasse, lter cake, and straws, represent around87 %of the total. In recent years, researchers have been putting signif- icant eort to develop new methods to eciently treat these waste materials via AD and also to disseminate and raise awareness of this potential within the sugar-cane industry but also with other stakeholders. Biogas production from waste resources is still largely underutilized in Brazil with a current estimated production of1.02×10⁹Nm³year⁻¹. However, recent legislation changes made in 2015 favor distributed electric power generation and since led to the instal- lation of 149 new plants and a138 %increase in biogas production (2015-2018) (Pacheco et al., 2019).

Vinasse, in particular, is a by-product of the bioethanol industry of major relevance, because it is generated in large proportions (≈ 12 LvinasseL⁻¹_ethanol) and may cause water and soil pollution, if not treated properly (Coelho et al., 2018). Figure 1.2 shows a glass lab beaker containing vinasse, which is a dark pasty liquid waste stream from the alcohol distillation step and contains organic solids, minerals, sugars, alcohol, and other volatile components (Coelho et al., 2018). It used to be discarded in water bodies, which provoked bacterial growth due to its organic load, but this was prohibited in 1978. Since then, it is mostly (by 98 %) used for irrigation and fertilization in the sugar-cane industry, but this must follow strict regulations and inspections to avoid excessively high concentrations and possible groundwater contamination. AD is an eective way of reducing the organic load of vinasse, while simultaneously producing biogas as a renewable energy source. Moraes, Zaiat, and Bonomi, 2015 present a review of the main challenges and perspectives of vinasse treatment via AD.

The study concludes that it is a viable method, but synergetic actions by the government and environmental agencies as well as the support of the scientic community are required for industrial implementation to take place.

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Figure 1.2: Vinasse from ethanol production in a glass beaker. Photo kindly provided by the Laboratory of Biological Wastewater Treatment from Mauá Institiute of Technology.

The OCM process can, therefore provide a new alternative pathway for the utilization of biogas derived from vinasse AD and enable the production of bio-ethylene. The potential biogas production via vinasse AD in the state of São Paulo is huge and it is also a highly industrialized state. It hosts 22 % of Brazilian population and is located in the Southwest region together with Rio de Janeiro, Minas Gerais, and Espírito Santo states, which altogether host 42 %of the national population (Instituto Brasileiro de Geograa e Estatística, 2019). The market for ethylene-based products such as chemicals and polymers is, therefore, also large.

1.1.2 Biogas Contaminants

Due to the additional components listed in Table 1.1, biogas often requires some processing prior to its use. The removal of minor contaminants (all components except CH4 and CO2) is hereinafter called biogas treatment. The removal of carbon dioxide is often referred to as biogas upgrade and the resulting gas biomethane. An overview of issues caused by the dierent biogas contaminants in typical biogas applications is presented in Table 1.3.

It is essential to discuss about the potential implications of the contaminants towards the application intended within this thesis. Water, nitrogen, oxygen, and carbon dioxide are already present in the OCM system and are not concerning. Dust is undesired, but can be easily ltered out. Therefore, siloxanes, ammonia, and hydrogen sulde are the most concerning contaminants.

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1.1 Biogas

Table 1.3: Major biogas contaminants and the issues associated with them according to (Ryckebosch, Drouillon, and Vervaeren, 2011)

Contaminant Issues

Carbon Dioxide Low caloric value

Water Corrosion due to acid formation Hydrogen Sulde Corrosion and toxicity

Dust Deposition and clogging of equipment Siloxanes Formation of SiO₂ in combustion chamber Oxygen or Air Formation of explosive atmospheres

Ammonia Corrosion

Siloxanes are organic compounds containing SiO bounds, which are employed in hygiene products, pharmaceuticals, cosmetics, textiles, and paper coatings due to its low-ammability, low surface tension, thermal stability, hy- drophobicity, compressibility, and low toxicity (Abatzoglou and Boivin, 2009).

Siloxanes, due to their origin, are present in landl gas or biogas from urban treatment facilities, but not in agricultural biogas. Therefore, they are not a concern for biogas derived from vinasse AD.

Ammonia (NH₃) is formed through AD of nitrogen-containing molecules in substrates. Although several authors mention the presence of ammonia in biogas, very little is discussed about its implications on the biogas utilization and possible removal methods. This is mainly because most of the processes required to remove other components, mainly H2S, can simultaneously remove NH₃. The same is valid for other trace components like benzene, toluene, chlo- rine compounds, and heavy hydrocarbons, which are only mentioned by Rasi, Veijanen, and Rintala, 2007. The relevant literature on biogas treating, discussed in Chapter 1.1.3, focuses largely on H₂S and CO₂ removal.

Hydrogen Sulde (H2S) is formed through the AD of any sulfur-containing molecules in the substrate. Due to its highly corrosive, toxic, and malodorous nature, it must be removed from biogas prior to most applications. Besides that, if biogas is combusted, H2S is oxidized into SOx (Equations 1.2 and 1.3), which has strictly regulated emissions in most regions. Therefore, for the complex heterogeneous catalytic process investigated in this thesis, it is likely that a ne H2S removal is required. This can be achieved through the methods described in Chapter 1.1.3. However, even traces of H₂S (fewppm_v) can potentially still be harmful to the catalyst, reaction, or the process.

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H₂S_(g)+3

2O_2(g) −−→SO_2(g)+ H₂O_(g) (1.2) SO_2(g)+1

2O_2(g) −−↽−−⇀SO_3(g) (1.3) Eects of Hydrogen Sulde to OCM Catalyst and Process

A single reference has been found in literature dealing with the eect of sulfur components to OCM reactors (Campbell et al., 1992). Experimental investi- gations have been carried out with 6 ppmv to 200 ppmv of H2S at750°C and 900°C with a CH₄:O₂ ratio of 9:1 and dierent space velocities on a lab-scale quartz glass reactor packed with lanthanum oxide (La₂O₃) catalyst. The main conclusions of the study are reported below:

H₂S and all other sulfur components are likely oxidized to sulfur dioxide (SO₂) and sulfur trioxide (SO₃)

At750°C, the catalyst is poisoned by the SOx species due to the formation of surface sulfates (La₂(SO₄)₃)

The selectivity towards C2 products is almost unaected by catalyst poisoning until methane conversion drops signicantly

The catalyst poisoning is controlled by temperature, contact time, and sulfur concentration

The poisoning could be reversed by increasing the reactors' temperature to 900°C

It is, therefore expected that even low concentrations of H₂S will slowly reduce catalytic activity and reduce methane conversion during process operation. The upstream biogas treatment unit must therefore ensure a very ne sulfur removal in order to mitigate this eect. If the catalyst performance drops signicantly, catalyst re-activation (re-oxidation) can be achieved by operating the reactor at a higher temperature.

A small amount of SOx species would also be present in the reactor outlet stream. Among those, SO₃ is more concerning due to the formation of sulfuric acid (H2SO4) in the presence of water (Equation 1.5). At the high temperatures for OCM (700°Cto 900°C), the SO₂ oxidation reaction equilibrium (Equation 1.3) is largely shifted towards the educt side (Campbell et al., 1992). Cooling of the gases in the downstream shifts the equilibrium towards SO3, but the kinetics are rather slow and typically require a catalyst, e.g., vanadium(V) oxide (V₂O₅) is employed industrially for sulfur dioxide oxidation in sulfuric

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1.1 Biogas acid plants. This means that the sulfur components in the reactor outlet would be largely comprised of SO₂ with smaller amounts of SO₃, H₂SO₃, and H₂SO₄ all in gaseous form.

SO2(g)+ H2O(g)−−↽−−⇀H2SO3(g) (1.4) SO_3(g)+ H₂O_(g)−−↽−−⇀H₂SO_4(g) (1.5) In the OCM reactor downstream, the gas stream is usually quickly cooled down in a transfer-line heat exchanger by generating high-pressure steam followed by additional heat recovery steps in gas-gas heat-exchangers. A similar problem has been described for a coal-based oxy-fuel combustion process (Belo et al., 2014). In that particular case, recycling the ue gases to the combustion step leads to a four-fold increase in SOx concentrations compared to regular air combustion. The higher SO3 concentration increases the gas' dew point temperature, which reduces the amount of heat that can be recovered in the boiler prior to acid condensation. Hence, special care must be paid to the design and operation of the heat-exchangers in the downstream of the OCM reactor in order to avoid acid condensation and corrosion issues. The nal gas cooling step is achieved in a quench column (direct contact heat-exchanger) with process water. The wash and cooling to around 45°Cwould ensure the removal of the trace sulfur components from the gas stream, but this column and internals should be constructed in acid-resistant materials and the water purge stream must be dealt with accordingly.

Further experimental studies regarding the eect of dierent H2S concentrations to various OCM catalysts under varying operating conditions are required in order to further investigate potential issues. This is also relevant for natural gas-based OCM given that traces of this component may also be present.

1.1.3 Biogas Treatment

The amount and nature of biogas contaminants depends on the substrate and the selection of an appropriate treatment method depends on several factors such as the gas composition, specic requirements for the application, avail- ability of infrastructure and utilities, plant size, and also applicable regulations.

The removal of H₂S is often a priority given its toxic and corrosive nature. Also, several of the desulfurization methods will simultaneously remove other components.

Several methods are currently employed in industry for desulfurization during or after digestion. A brief overview based on the review papers of (Ryckebosch,

Optimal Design and Evaluation of a Biogas-based Oxidative Coupling of Methane Process