Simulation-Based Evaluation of a Two-Stage Small-Scale

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Simulation based evaluation of a two-stage smallscale methanation unit for decentralized applications Michael Neubert, Jonas Widzgowski, Stefan Roensch, Peter Treiber, Marius Dillig, and Jürgen Karl Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02793 • Publication Date (Web): 30 Dec 2016 Downloaded from http://pubs.acs.org on January 5, 2017

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Simulation based evaluation of a two-stage smallscale methanation unit for decentralized applications Michael Neubert11*, Jonas Widzgowski1, Stefan Rönsch2,3, Peter Treiber1, Marius Dillig1, Jürgen Karl1 1

Friedrich-Alexander University of Erlangen-Nuremberg, Chair of Energy Process Engineering,

Fürther Str. 244f, D-90429 Nürnberg, Germany 2 DBFZ – Deutsches Biomasseforschungszentrum GmbH, Torgauer Straße 116, 04347 Leipzig, Germany 3 ErnstAbbe-Hochschule Jena, Carl-Zeiss-Promenade 2, 07745 Jena, Germany(es). Mail: [email protected], Phone: 0049 911 5302 9036

The present work aims for a simulation based evaluation of a two-stage methanation unit for the production of Substitute Natural Gas (SNG) in decentralized small-scale applications with low complexity. Equilibrium calculations reveal a remarkable impact of CO2 removal efficiency on final SNG composition with an optimum removal efficiency of 85 % for the examined synthesis gas. The first methanation stage consists of a polytropic fixed-bed methanation reactor and is implemented as a one-dimensional pseudo-homogeneous model in Aspen PlusTM with reaction kinetics from literature. The comparison of three different kinetic models reveals that reverse reaction of CO methanation has to be considered in the kinetic rate equations for appropriate modelling within a dynamic temperature range above 400°C in case of polytropic reactors. The

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1st methanation stage is examined with one kinetic model in terms of reactor geometry, varying GHSV and influence of the feed gas composition to determine limits in upscaling and avoidance of too high temperatures. A significant decrease of the reactor diameter favors the heat removal in case of polytropic reactor concept, whereas a higher GHSV causes higher outlet temperatures. The results show that an effective operation of the proposed methanation concept is limited by an appropriate heat removal.

Keywords: SNG, fixed-bed methanation, methanation kinetics, reactor modelling, simulation 1. Introduction Due to the focus on the use of renewable energy in Europe, intensive research takes place in the field of the production of Substitute Natural Gas (SNG) from biomass and in power-to-gas applications, which enables the storage of excess electricity within the natural gas grid. Additionally, the utilization of European lignite for SNG production is also possible which becomes favorable in terms of independence from energy suppliers and base load availability. The utilization of lignite for SNG production implies higher CO2 emissions than in case of biomass but is still superior to state-of-the art utilization in large-scale power plants. Because of the demand for high flexibility, limited feed-in capacities and public acceptance, small-scale decentralized methanation facilities are required. An essential criterion for the profitability of small-scale SNG facilities is a low process complexity, which has to be considered for the whole fuel-to-SNG process chain. The catalytic methanation of synthesis gas is strongly exothermic, causing the release of a considerable amount of heat during the reactions. However, for a high methane yield in chemical equilibrium low outlet temperatures are required. The standard approach for temperature control is a larger quantity of fixed-bed reactors with intermediate


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cooling. This cooling measure is assisted by modifying the synthesis gas composition by gas recycle or staged feed injection [1-3]. In contrast, to meet the requirement of a low process complexity, the number of methanation stages and installed equipment has to be reduced in small-scale applications. For this reason, SNG production in decentralized units has to be optimized with regard to the trilemma of decentralized methanation as depicted in Figure 1. Therefore, a tradeoff between thermodynamics (low temperature for high methane yield), reaction rates (full hydrocarbon conversion and high reaction rates) and process complexity (cleanliness of syngas) becomes necessary. The present work aims at the simulation-based evaluation of a simplified two-stage methanation unit with intermediate water removal in terms of CH4 content in SNG and temperature control.

complexity of process („cleanliness of syngas“)

trilemma of

decentralized methanation reaction rates („high temperatures for high reaction rates and high GHSV“)

thermodynamics („low temperatures for high CH4-yield“)

Figure 1. Trilemma of decentralized methanation 2. Fundamentals on methanation Synthesis gas derived from gasification of solid feed-stocks predominantly contains hydrogen (H2), carbon dioxide (CO2), carbon monoxide (CO), methane (CH4) and water (H2O). The main


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reactions in the methanation reactor are CO methanation (1), water-gas-shift reaction (WGS) (2) and Sabatier reaction (3) as linear combination of equations (1) and (2) (see Table 1). The occurring gas phase reactions are reversible, i.e. forward and reverse reactions take place simultaneously. Chemical equilibrium is characterized by a minimization of Gibb’s free energy of the total system. Figure 2 shows the equilibrium gas composition yi of a synthesis gas based on allothermal lignite steam gasification depending on temperature T. According to le Chatelier, due to the exothermic reaction and volume reduction of methanation reactions, high pressures, low temperatures and low water content in the feed increase the selectivity towards me-thane. As can be seen in Figure 2, temperatures below 260 °C are required for a high methane yield above 30 vol.-% and less than 2 vol.-% hydrogen in the product gas. Under certain conditions, the formation of solid carbon becomes significant even in thermodynamic equilibrium, which is considered by the Boudouard reaction (4). In general, the carbonaceous deposits exist in various configurations but for equilibrium calculations, graphitic carbon is assumed in general [4, 5].

0.8

p = 5 bar H2O

0.6

H2

yH2 < 0.02

yi [-]

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0.4

CH4

0.2

CO

CO2 0.0 200

300

400

500 T [°C]

600

700

800

Figure 2. Equilibrium gas composition for clean syngas from Table 3 3. State-of-the-art


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The following section gives a summary about commercial and research projects for the production of SNG and applied methanation technology. For more detailed overviews about technology development and methanation reactor concepts the reviews by Kopyscinski et al. [1] and Rönsch et al. [2] are recommended. The oil crisis of the 1970s led to intensive research on the production of SNG from solid fuels. As a consequence, the first commercial large-scale coalto-SNG plant was erected in North Dakota in 1984 [6]. Interest in the technology disappeared after the oil crisis due to a lack of economic viability. Not until the beginning of the 21st century, the desire for independence of gas imports in particular and an increasing environmental awareness led to returning interest in SNG producing processes [1]. A number of large scale coal-to-SNG projects have been realized since 2010 or are in development in the USA and Asia, especially China. Some of the most important of the known projects are listed in Table 2. naming the applied methanation technology. In large scale coal-to-SNG applications, Lurgi process, Haldor Topsoe’s TREMP process and HICOM process by the British Gas Corporation dominate the applications. All processes have in common that they consist of a series of catalytic adiabatic fixed-bed reactors with intermediate gas cooling and temperature control is carried out by an adjustment of synthesis gas composition through gas recycle, steam injection and staged feed injection. The process of Lurgi (today Air Liquide) contains two or three adiabatic fixed-bed reactors with intermediate gas cooling and gas recycling [7]. Similar to this is Haldor Topsøe’s TREMP (Topsøe’s recycle energy efficient methanation process). The high temperature catalyst of Haldor Topsøe (up to 700°C) allows the production of high temperature steam by cooling the product gases after the first stage [8]. The HICOM process (high combined shift methanation) combines shift and methanation within the first of four adiabatic fixed-bed reactors. Gas recycling is possible for the first two stages [9]. The VESTA process of Clariant and Foster


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Wheeler is another commercially available concept, which is based conceptually on the technology of Imperial Chemical Industries (ICI) and also contains several adiabatic fixed-bed reactors with intermediate cooling. In contrast to the aforementioned concepts, VESTA does not comprise any gas recycle since a high-temperature shift reactor adjusts the vapor content for cooling purposes [10]. Biomass utilization for the production of SNG predominantly takes place in Europe. The only industrial biomass-to-SNG facility is the GoBiGas project (Gothenburg Biomass Gasification) in Sweden producing SNG in a 20 MWSNG scale. The methanation is based on the TREMP process. [11] Within the project BioSNG a 1 MWSNG fluidized-bed methanation reactor was erected at the biomass gasifier in Güssing (Austria) and has been operated for about 6 months in 2009/2010. The cooled fluidized-bed reactor was based on the Comflux process and adapted by the Paul-Scherrer-Institute (PSI). [12] Other biomass-to-SNG research projects are carried out, exemplarily, by the Energy Research Center of the Netherlands (ECN) [13], TU Munich (TUM) [14], agnion [15], TU Graz [16] or TU Vienna [17]. The RFCS projects CO2freeSNG and CO2freeSNG2.0 at Friedrich-Alexander-University Erlangen-Nuremberg aim for similar decentralized concepts with lignite as fuel [18, 19]. Further research activities focus on new approaches for temperature control of methanation reactors (e.g. thermo-oil cooled reactors at Deutsches Biomasseforschungszentrum (DBFZ) [20] or flexible recycle ratio [21]). By applying cooled reactors, the number of methanation stages and the total plant complexity can be reduced, which is crucial for the profitability of small-scale applications. Recent developments concentrate on structured reactors [22-26], where Ineratec and Velocys represent two commercial actors. Due to the internal structure heat transfer capacities are improved and pressure drop is lowered compared to adiabatic fixed-bed reactors [25, 26]. Supported honeycomb catalysts with high thermal conductivity of the support material are a widespread


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form of structured reactors resulting in a reduced radial temperature profile [27]. Besides biomass-to-SNG, another field of small-scale application with cooled reactors is power-to-gas (ptg) technology. The overall idea of ptg is the utilization of surplus electricity for hydrogen production via electrolysis and further conversion to SNG by methanation with carbon dioxide, e.g. provided by a biogas plant [28]. The resulting SNG allows the seasonal electricity storage in grid relevant quantities. Audi e-Gas is the first industrial facility located in Werlte with an electrolysis input power of 6.3 MWel [2]. Methanation of CO2 from a near biogas conditioning plant takes place in a tube bundle reactor cooled by molten salt, delivered by MAN DWE and ETOGAS GmbH [29, 30]. In other projects ETOGAS is carrying out intensive research on cooled plate reactors for CO2 methanation in cooperation with the Center for Solar Energy and Hydrogen Research Baden-Württemberg (ZSW) [31, 32]. Further research activities are the projects HELMETH and DemoSNG, both coordinated by Karlsruhe Institute of Technology (KIT). HELMETH (Integrated High-Temperature Electrolysis and Methanation for Effective Power to Gas Conversion) focuses on the heat recovery of the methanation step through high pressure steam generation for high temperature electrolysis [33]. DemoSNG investigates the dynamic methanation of syngas from a biomass gasifier with additional H2 [34]. 4. Evaluation of a two-stage methanation unit based on equilibrium simulations 4.1 Process chain of CO2freeSNG2.0 in ternary diagram Within the scope of EU project CO2freeSNG2.0 (RFCS-CT-2013-0008) a mid-scale coal-toSNG process chain is investigated at the Chair of Energy Process Engineering (EVT), FriedrichAlexander University Erlangen-Nuremberg, applying experimental and simulation based approaches. The process consists of an allothermal steam gasifier, a chemical syngas scrubber


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for impurity and CO2 removal. This means, that in case of lignite as fuel with its typically high sulfur content the resulting sulfur concentration probably exceeds the level which is required in state-of-the art methanation units. But, as mentioned above in the introduction, an increased catalyst consumption could become acceptable in terms of lowering the investment costs, which are coupled to an additional ZnO/CuO sulfur guard bed. The scrubber temperature is a very sensitive parameter since it determines the equilibrium conditions and hence CO2 and H2S removal, the tar dew point and the water content in clean syngas with its impact on methanation, e.g. adiabatic synthesis temperature. One possibility for decoupling the water content in clean syngas from CO2 removal is the installation of a separate optional condenser after the scrubber, which cools the clean syngas slightly (see Figure 3). Downstream, the scrubber is followed by a two-stage methanation unit with intermediate water sequestration, which shifts the equilibrium in the 2nd stage further to methane. The specific required cooling flux in the condenser unit for the sample gas composition of Table 3 adds up to 16 % of the intermediate SNG power based on net heating value. This underlines that the heat integration of the intermediate condenser unit is crucial for the whole setup. The presented basic setup (Figure 3) with low complexity should provide grid injectable SNG from a point of thermodynamics. All process steps are investigated experimentally with a 5 kW methanation test rig and 5 kW or 100 kW gasifier and scrubber units. A representative syngas composition from lignite gasification in the 5 kW lab-scale gasifier at the Chair of Process Engineering is given in Table 3 (unpublished data). Typically, the raw syngas comprises a significant amount of many different higher hydrocarbons, so called tar compounds. At the same settings as the syngas composition in Table 3 was obtained Benzene (3800 mg/Nm3) and Naphthalene (630 mg/Nm3) accounted for more than 85% of the 25 species which are calibrated in gas chromatography analysis of solid phase adsorption samples. The first


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methanation stage is a polytropic fixed-bed reactor reforming in the reactor inlet zone all these tars, which are produced during fluidized-bed gasification and are not removed by condensation in the chemical scrubber unit (e.g. C6H6, C6H5-CH3) [15]. In polytropic operation the second part of the reactor is cooled to reach lower equilibrium conditions. From a technical point of view, the implications of biomass as fuel are less restrictive than the ones of lignite. Higher tar, methane and hydrocarbon production in biomass gasification affect the total SNG efficiency only slightly since the majority is converted and utilized in the polytropic fixed-bed methanation if the peak temperature is sufficiently high (~500°C) [15]. Additionally, the internal reforming and higher methane content even lowers adiabatic synthesis temperature and favor temperature control. On the other side, the higher sulfur content of lignite requires higher efforts for syngas cleaning, e.g. by additional guard beds. A subsequent water sequestration in a condenser removes water in the intermediate SNG before methane content is raised slightly and hydrogen content lowered in a second, isothermal methanation stage (Figure 4). Final gas conditioning only contains water sequestration. raw syngas CO2 removal (100-150°C)

condenser (optional)

CO2 + impurities (e.g. H2S, C6H6) intermediate SNG

clean syngas

1st methanation polytropic (300-550°C, ~ 5 bar)

2nd methanation isothermal (260°C, ~ 5 bar)

syngas heating

condenser

condenser

H2O

H2O

final SNG

Figure 3. Evaluated two-stage methanation concept Figure 5 shows these process steps in a ternary atomic diagram of the elements C, H, and O for 260°C and 5 bar. CO2-removal from raw syngas (blue dot) and the subsequent methanation steps


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(purple dots) are displayed. The phase equilibrium for formation of solid graphitic carbon is shown for 260°C (solid line) and 550°C (dotted line) [5], while the green colormap illustrates the equilibrium CH4 content on dry basis for a feed with corresponding C/H/O ratio to the 2nd methanation stage. The contour lines for CH4 content higher than 90 vol.-% (red solid line) and 95 vol.-% (red dotted line) in dry SNG describes the favorable range of final C/H/O ratio. With the proposed concept of Figure 3 the C/H/O ratio is only adjusted by CO2 removal and water sequestration as long as no solid carbon is formed. Hereby, the scrubber unit is represented separately by the CO2-removal (white filled purple dot) and simultaneous water condensation according to scrubber operating temperature (filled purple dots) which is assumed as 25 vol.-% H2O in clean syngas within the present work. The adjustment of C/H/O ratio in the scrubber aims for a shift of the final composition in the ternary diagram towards an area with high CH4 content (red solid line) and no formation of solid carbon in order to optimize the yield of CH4. During methanation the C/H/O ratio of the gas phase remains unchanged as long as no solid carbon is formed. 4.2 Optimization of CO2 removal by sensitivity analysis The CO2 removal efficiency 𝜂𝐶𝑂2 describes the share of removed CO2 in the scrubbing unit (5) and is defined as the difference of the initial carbon dioxide mole flow 𝑛𝐶𝑂2 ,0 and carbon dioxide mole flow in clean syngas 𝑛𝐶𝑂2 related to initial mole flow of carbon dioxide in the syngas. (5) 𝜂𝐶𝑂2 =

𝑛𝐶𝑂2 ,0 −𝑛𝐶𝑂2 𝑛𝐶𝑂2 ,0


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1 CH4

1st methanation stage

0.8

C(s)

0.6

yi,dry [-]

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2nd methanation stage

0.4 0.2

H2

CO2

0 0

0.2

0.4

0.6

0.8

1

ηCO2

Figure 4. Sensitivity analysis for product gas composition in dependence on CO2 removal efficiency of raw syngas (dry) from Table 3; 25 vol.-% H2O content, 5 bara

50 % ηCO2 (25 vol.-% H2O)

formation of solid C (in 2nd stage) CH4

optimum

feed 2nd stage 100 % ηCO2 (0.2 vol.-% H2O)

(ηCO2 = 85 %)

50 % ηCO2

100 % ηCO2 / 1st stage (25 vol.-% H2O)

100 % ηCO2 95 vol.-% CH4 in gas phase

CO2 removal

H2O

CO 90 vol.-% CH4 in gas phase clean syngas / 1st stage (25 vol.-% H2O)

H2O removal

CO2

optimum (ηCO2 = 85 %)

CH4

feed 2nd stage (0.2 vol.-% H2O)

CO2 removal

phase equlibrium solid carbon (550°C, graphitic)

raw syngas

phase equlibrium solid carbon (260°C, graphitic)

H2O


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Figure 1. CO2 removal and methanation in atomic ternary diagram; syngas composition from Table 3 (tars and other impurities neglected), CH4 equilibrium content in dry SNG yCH4,dry based on C/H/O ratio of gas phase at 260°C is shown as colormap, 5 bar As a first step, the influence of 𝜂𝐶𝑂2 on CH4 content in final SNG is studied by equilibrium calculations with Aspen PlusTM. Both methanation units are modelled as Gibbs reactors with equilibrium conditions at 260 °C and 5 bar without any pressure drop within the reactors. This equals a best case consideration which gives the highest SNG quality that is possible with the discussed setup. Intermediate water condensation takes place in a flash type gas-liquid separator at an operational temperature of 11°C providing nearly complete water sequestration and shifts the equilibrium in the 2nd stage further to methane. CO2 mole flow in clean syngas is varied in the simulations, while the ratio of the other gas constituents and the absolute water content were kept as a constant design specification. The outlet gas composition on dry basis for 1st and 2nd methanation stage depending on 𝜂𝐶𝑂2 is shown in Figure 4. It can be seen that CO2 removal efficiency has a remarkable impact on the product gas composition after 1st and 2nd methanation reactor and a distinct maximum of methane content can be observed with CO2 removal efficiency 𝜂𝐶𝑂2,𝑜𝑝𝑡𝑖𝑚𝑢𝑚 of 85 % for the investigated synthesis gas. This underlines that due to the high H2/CO ratio of 4.1 in raw syngas still a minor amount of CO2 in clean syngas for maximum methane yield is required. Hydrogen excess at higher removal efficiencies as well as carbon excess at lower removal efficiencies cause lower CH4 concentrations in final SNG. At very low CO2 removal the CH4 content is even lowered in the second methanation stage due to the formation of solid carbon which shifts remaining C-atoms from CH4 to CO2. These coherences can be graphically explained in a more detailed extract of the relevant part of the ternary diagram (Figure 5). Cases for 50, 85 and 100 % CO2 removal efficiency are indicated


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exemplarily. The CO2 removal efficiency strongly influences the C/H/O composition in the final SNG due to the leverage effect of the water sequestration between 1st and 2nd methanation stage (indicated by dotted lines). A full CO2 removal (𝜂𝐶𝑂2 = 100 %) results in a high hydrogen surplus indicated by a shift of final SNG towards H corner in the ternary diagram. Additionally, the ternary diagram also illustrates the reason for the formation of solid carbon within the second methanation stage in Figure 4 at CO2 removal below 85 %. Due to a low CO2 removal (𝜂𝐶𝑂2 = 50 %) the subsequent water sequestration leverages the C/H/O ratio tremendously above the phase equilibrium line and triggers remarkable formation of solid carbon. The formation of solid carbon in the 2nd stage even worsens if the temperature becomes significantly higher as is illustrated by the phase equilibrium for 550°C in Figure 5. In opposite to this, the optimum CO2 removal efficiency (85 % for the considered raw syngas) with maximum CH4 concentration in the final SNG shifts the C/H/O ratio of clean syngas in such a way that its stoichiometry could be expressed as a pure mixture of H2O and CH4. Since a mixture of H2O and CH4 is the product of a stoichiometric feed it reveals highest thermodynamic favor for methane production, whereby the resulting mixing ratio depends on the raw syngas composition. Therefore, it can be easily accessed graphically as the intersection of CO2 removal (connecting CO2 and syngas) with a mixture of CH4 and H2O (connecting H2O and CH4) in the ternary diagram. To give a ̂ /𝑂̂ ratio of raw syngas with fraction 𝑦̂𝑖 of mathematical expression for 𝜂𝐶𝑂2,𝑜𝑝𝑡𝑖𝑚𝑢𝑚 the 𝐶̂ /𝐻 species i is calculated in a general way from the raw syngas composition, equations (6 - 8). Tar species were neglected since the consideration of 3800 mg/Nm3 C6H6 and 630 mg/Nm3 C10H8 shifts the absolute C/H/O values of raw syngas less than 0.1 %. (6) 𝐶̂ =

𝑦̂𝐶𝑂 +𝑦̂𝐶𝑂2 +𝑦̂𝐶𝐻4 2𝑦̂𝐻2 +2𝑦̂𝐶𝑂 +3𝑦̂𝐶𝑂2 +3𝑦̂𝐻2𝑂 +5𝑦̂𝐶𝐻4


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̂= (7) 𝐻 (8) 𝑂̂ =

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2𝑦̂𝐻2 +2𝑦̂𝐻2𝑂 +4𝑦̂𝐶𝐻4 2𝑦̂𝐻2 +2𝑦̂𝐶𝑂 +3𝑦̂𝐶𝑂2 +3𝑦̂𝐻2𝑂 +5𝑦̂𝐶𝐻4 𝑦̂𝐶𝑂 +2𝑦̂𝐶𝑂2 +𝑦̂𝐻2𝑂 2𝑦̂𝐻2 +2𝑦̂𝐶𝑂 +3𝑦̂𝐶𝑂2 +3𝑦̂𝐻2𝑂 +5𝑦̂𝐶𝐻4

According to equation (5) the removal efficiency is a function of molar flows of CO2 in and out of the scrubbing unit and thus the CO2 concentration in clean syngas 𝑦̿𝐶𝑂2 can be calculated in dependence of raw syngas composition 𝑦̂𝑖 (9) 𝑦̿𝐶𝑂2 =

𝑦̂𝐶𝑂2 (1−𝜂𝐶𝑂2 ) 𝑦̂𝐻2 +𝑦̂𝐶𝑂 +𝑦̂𝐶𝑂2 (1−𝜂𝐶𝑂2 )+𝑦̂𝐻2𝑂 +𝑦̂𝐶𝐻4

̿ /𝑂̿ ratio of By substituting the CO2 concentration in clean syngas with equation (9) the 𝐶̿ /𝐻 ̅ /𝑂̅ ratio of a clean syngas can be calculated with respect to 𝜂𝐶𝑂2 . In a similar manner, the 𝐶̅ /𝐻 ̿ /𝑂̿ ratio of clean syngas. The solution mixture of CH4 and H2O is calculated and set equal to 𝐶̿ /𝐻 of this linear equation system (10) correlates the raw syngas composition 𝑦̂𝑖 with 𝜂𝐶𝑂2,𝑜𝑝𝑡𝑖𝑚𝑢𝑚 , which yields the maximum CH4 content in the final SNG for H2/CO ratios above 3.

(10) 𝜂𝐶𝑂2,𝑜𝑝𝑡𝑖𝑚𝑢𝑚 = 1 −

𝑦̂𝐻2 −3𝑦̂𝐶𝑂 4𝑦̂𝐶𝑂2

Lower H2/CO ratios in raw syngas require a complete removal of CO2 in order to maximize the CH4 yield. 5. Kinetic simulation of fixed-bed reactor for first methanation stage 5.1 Methanation kinetics and simulation model Applied catalysts for methanation reactions consist of an active compound, which is usually combined with a supporter to enlarge the catalyst surface area. The most commonly applied active metal for commercial methanation catalysts is nickel because of its high activity and selectivity as well as a comparatively low price [2]. A detailed overview over methanation


14

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Energy & Fuels

catalysts in general is e.g. given by Mills and Steffgen [35]. It is commonly accepted that a Langmuir-Hinshelwood reaction mechanism is responsible for CO methana-tion with dissociative adsorption of CO and H2 [36-38] but some authors suggest an Eley-Rideal mechanism - though the applied conditions in terms of pCO differ strongly [39, 40]. Yet, the detailed mechanism and rate determining step (RDS) is not clarified. Some publications favor the hydrogenation of C* or CH* at the surface as RDS, whereas others assume the formation of an intermediate COH* complex as rate determining step [41] which is supported by recent DFT calculations [42]. Sehested et al. [40] also discussed the dissociation of CO on only 5% of Ni surface as RDS. Kinetic approaches aim to describe the complex processes on the catalyst surface with mathematical expressions for the effective reaction rates of the overall equations (1), (2) and (3) only depending on measurable quantities. In the last decades various investigations on the kinetics of methanation catalysts have been published. An overview about published kinetic approaches for commercial nickel catalysts is given by Rönsch et al. [43]. The majority of the kinetic models have in common that they all follow a Langmuir-HinshelwoodHougen-Watson (LHHW) approach, which is based on the structure shown in equation (11). The rate equations and parameters are derived by fitting with experimental data.

(11) 𝑟 =

(𝑘𝑖𝑛𝑒𝑡𝑖𝑐 𝑓𝑎𝑐𝑡𝑜𝑟)∙(𝑑𝑟𝑖𝑣𝑖𝑛𝑔 𝑓𝑜𝑟𝑐𝑒) (𝑎𝑑𝑠𝑜𝑟𝑝𝑡𝑖𝑜𝑛 𝑒𝑥𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛)𝑛

For simulation models, the kinetic approaches of Xu and Froment [44] and Kopyscinski [45] are most frequently used. However, the kinetics published by Xu and Froment are not well suited for temperatures below 500 °C [43, 46] and Kopyscinski does not consider the reverse reaction of the CO methanation (steam methane reforming) as his experiments took place at nearly isothermal conditions in a fluidized bed methanation reactor within a temperature range of 280360 °C with equilibrium strongly on the product site [45]. For simulations in a dynamic


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Page 16 of 37

temperature range Rönsch et al. [43] recommend the kinetic models of Klose and Baerns [47] or Zhang et al. [48] with an adjustment of the driving force expression of the CO methanation equation to consider the influence of the reverse reaction at higher temperatures. The polytropic air-cooled fixed-bed reactor of the first methanation stage is implemented as pseudohomogeneous 1-D plug-flow reactor model in Aspen PlusTM with three different kinetic models. Aim of the model is an axial resolved computation of temperature, gas composition and heat removal. In the following, the kinetic model of Zhang et al. with the adjustment of Rönsch et al. ((12), (13)) for a commercial Ni/Al2O3-catalyst with 50 wt.-% Ni is introduced in detail. Additionally, the adjustments to fulfill the required form by Aspen PlusTM are presented. Reaction rates r are given in kmol kgcat-1 s-1 while the partial pressures p of the gas species have to be given in Pa. CO-methanation

(12) 𝑟1 =

−0,5 𝑝𝐶𝐻 ∙𝑝𝐻 𝑂 ∙𝑝𝐶𝑂 ∙𝑝−2 𝐻2 4 2 ) 𝐾𝑀𝑒𝑡ℎ 0,5 0,5 3 (1+𝐾𝐶 ∙𝑝𝐶𝑂 +𝐾𝐻 ∙𝑝𝐻 ) 2

0,5 2 𝑘1 ∙𝐾𝐶 ∙𝐾𝐻 ∙(𝑝𝐶𝑂 ∙𝑝𝐻2 −

water-gas-shift reaction:

(13) 𝑟2 =

𝑝𝐻 ∙𝑝𝐶𝑂 𝑘2 2) ∙(𝑝𝐶𝑂 ∙𝑝𝐻2 𝑂 − 2 𝑝𝐻 𝐾𝑊𝐺𝑆 2 −1 ) (1+𝐾𝐶𝑂 ∙𝑝𝐶𝑂 +𝐾𝐻2 ∙𝑝𝐻2 +𝐾𝐶𝐻4 ∙𝑝𝐶𝐻4 +𝐾𝐻2 𝑂 ∙𝑝𝐻2 𝑂 ∙𝑝𝐻 2

2

The rate coefficients ki (i = 1,2) and adsorption constants Kj (j = C, H, CO, H2, CH4, H2O) are defined as a function of temperature according to the Arrhenius and van’t Hoff equations (14) and (15) respectively. (14) 𝑘𝑖 = 𝑘𝑖0 ∙ exp (−

𝐸𝐴,𝑖 𝑅𝑇

)


16

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Energy & Fuels

(15) 𝐾𝑗 = 𝐾𝑗0 ∙ exp (−

∆𝐻𝐴𝑑𝑠,𝑗 𝑅𝑇

)

EA is the activation energy in J mol-1 and ∆HAds the adsorption heat of the species in J mol-1, R is the ideal gas constant in J mol-1K-1 and T the temperature in K. KMeth and KWGS represent the reaction equilibrium constants of CO methanation and water-gas-shift reaction which can be calculated by equations (16) and (17) according to Elnashaie and Elshishini [49]. Hereby, the unit of KMeth is changed to [Pa-2] if used in the term considering the reverse reaction in (12). 1

26830 𝐾

(16) 𝐾𝑀𝑒𝑡ℎ = 1.026676∙1010 ∙ exp ( (17) 𝐾𝑊𝐺𝑆 = exp (

4400 𝐾 𝑇

𝑇

− 30.11)

− 4.063)

The kinetic rate equations (12) and (13) follow a LHHW approach and can be directly implemented in the Aspen PlusTM simulation environment as reaction set (type LHHW) with two kinetic type reactions. The reacting phase of each reaction was set to Vapor, the rate basis to Cat (wt) and the [Ci] basis in the driving force expression is calculated on partial pressure. As can be seen from the numerator in (12) and (13) the driving force expression consists of two terms which have to be defined separately within the Aspen environment. The expression 𝐾

1

𝑊𝐺𝑆/𝐶𝑂

is

the driving force constant in the second term and the related coefficients A and B are derived by transforming equations (16) and (17) in the shape of equation (18). Analogous, the equations for adsorption constants Kn (n = C, H, CO, H2, CH4, H2O) have to be transformed according to (18) to meet Aspen input requirements. (18) ln(𝐾𝑛 ) = 𝐴𝑛 +

𝐵𝑛 𝑇

+ 𝐶𝑛 ∙ ln(𝑇) + 𝐷𝑛 ∙ 𝑇

The exponent of the denumerator in (12) and (13) defines the adsorption expression exponent in Aspen as three and two, respectively, for r1 and r2.


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All necessary original parameters taken from Rönsch et al. as well as the derived modified Aspen input data are summarized in Table 5. The models of Xu & Froment and Kopyscinski (model 12b) were implemented in a similar manner and the relevant Aspen input data derived from the original data [44, 45] is given in the appendix. 3.2 Comparison of kinetic models with measured data The cylindrical polytropic fixed-bed methanation reactor with commercial Ni (~50 wt.-%) catalyst at the Chair of Process Engineering is cooled with a co-current air flux over an outer cooling jacket divided into three separated cooling zones. This setup is modelled in Aspen PlusTM by a series of three plug-flow-reactors. The heat transfer coefficients between air and reactor wall are calculated according to VDI Heat Atlas through the correlation for a concentric annual gap (dh = 13.9 mm) and air flow conditions (Pr100°C = 0.686) in each cooling compartment. Reactor geometry and composition of the bottle mixed synthesis gas of the laboratory test run are given in Table 4. The presented CH4 concentrations over the axis of the fixed bed reactor in Figure 6a) have been measured consecutively at five gas sampling ports. A fully automated slider which shifts slowly and quasi-stationary a mounted thermocouple in a thermowell in the reactor center makes a continuous and smooth measurement of axial temperature profile possible. The experimental feed gas composition differs from the one in table 3 since the undertaken experiments had another objective than the analysis of the discussed process setup within this publication. Simulations of the 1-D pseudo-homogenous model have been carried out with the three kinetic models of Xu & Froment, Kopyscinski (model 12b) and Zhang et al. with the adjustment of Rönsch et al. Figure 6 shows the results for the axial temperature T(z) profile and methane yCH4 content in comparison with measured data keeping the same boundary conditions for plausibility check. The lab-scale reactor is designed to obtain a


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polytropic temperature profile with a distinct peak near the reactor inlet, which allows the conversion of higher hydrocarbons within the methanation unit [50]. Figure 6 emphasizes that the kinetic models of Xu & Froment as well as of Kopyscinski are not suitable for simulations within the investigated temperature range between 250 and 550 °C. The model of Kopyscinski is limited to temperatures below 360 °C because it does not consider the reverse reaction (steam methane reforming), which gains influence at higher temperatures. Consequently, the reaction rate of CO methanation rises continuously with increasing temperature causing a very fast conversion at the reactor inlet above thermodynamic equilibrium composition for the related temperature. The reaction rate within the kinetic model of Xu and Froment is very low at the temperature 282 °C at the reactor inlet. The exothermic methanation is not initiated and no methane is produced as can be seen in Figure 6. The model of Xu & Froment was derived for steam methane reforming above 600 °C and is not valid within the temperature range of the present work. x Tmax

T(z) [°C]

800

measured data Zhang/Rönsch Xu/Froment Kopyscinski

600 400 200

a)

0

zmax

0.5 0.4

yCH4,dry [-]

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Energy & Fuels

1st cooling zone

0.3 0.2

2nd cooling zone

0.1

3rd cooling zone

b)

0 0

200

400

600

axial reactor position [mm]


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Figure 6. T(z) and yCH4 for different kinetic models and measured data; synthesis gas and reactor geometry acc. to Table 4; GHSV = 1300 h-1; Tin = 282 °C, pin = 1.013 bar Contrarily, the simulation results based on the kinetic model of Zhang et al. with the adjustment of Rönsch et al. show a reasonable match with the measured data for the temperature profile as well as the methane content. The remarkable bumps in the simulated trend curves result from the change of cooling conditions at the begin of each cooling zone. Exact match with measured data is not e-pected as the used catalyst for the experiments is not mandatorily the same as the catalyst investigated by Zhang et al. and heat conductivity in the thermowell smooth the measured temperature profile. The most remarkable deviation from experimental data in Figure 6 is the higher temperature maximum and its shift towards the reactor inlet, which correlates with the deviation of yCH4 in Figure 6 b). The simulation is based on a model for an effective reaction rate, which is derived experimentally within a limited temperature range. Macro kinetic influences like pore diffusion and heat transport are not covered in detail as the activation energy of reaction is much higher than activation energy of diffusion, the reaction rate will increase much faster than diffusion coefficient with rising temperature according to Arrhenius equation [51, 52]. Consequently, limitations caused by diffusion will gain higher influence at temperatures exceeding the validated temperature range. For this reason, the effective reaction rate in the simulation is expected to be higher than in practice near the temperature maximum. It should be pointed out that the three investigated kinetic models gain very high reaction rates and with the applied boundaries rather equilibrium conditions are established than kinetic limitations. Nevertheless, the implemented methodology permits an eased investigation of scale-up opportunities with altered operating conditions. 5.3 Kinetic simulation results


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The overall objective of the conducted kinetic-based simulations is the quantitative analysis of fundamental coherences within fixed-bed methanation over a wide temperature range. Therefore, a 1-D pseudo homogeneous model gives sufficient accuracy [46, 53]. By use of the model, the following aspects regarding a fixed-bed methanation are investigated: -

Reactor geometry

-

Gas hourly space velocity and scale-up

-

Influence of feed gas composition

For comparability of the results all following simulations are carried out with a uniform synthesis gas composition (see Table 3) measured at EVT’s lab-scale gasifier. Based on the results of chapter 4.2, a CO2 removal of 85 % is assumed while water content in clean syngas is set to 25 vol.-%.In a first step, the reactor diameter was varied, while the reactor volume was kept constant by adapting reactor length under adiabatic conditions. Therefore, the GHSV according to (19) remained constant but superficial velocity varied. The results in Figure 7 show the axial position zmax where the adiabatic temperature Tmax is reached as illustrated in Figure 6 a). The adiabatic synthesis temperature states the maximum temperature which can be reached when equilibrium of a certain gas composition at specific inlet temperature and operating pressure is established. Hence, it is independent of geometry and power input and has to be lower than applicable catalyst temperature to avoid sintering. The axial position zmax, where the adiabatic temperature Tmax is reached increases with reduced diameter. This can be explained with the reduced ratio of catalyst mass per axial reactor compartment, since the same total catalyst mass is distributed over an enlarged reactor length. As reaction rate expression within


21

Energy & Fuels

the applied kinetic model refers to catalyst mass a lower conversion is achieved within the same axial compartment. 200 axial position of adiabatic temperature [mm]

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pin Tin GHSV Tmax (adiabatic)

150 100

= 5 bar = 300°C = 100 000 h-1 = 663°C

50 0

0

10

20 30 40 reactor diameter [mm]

50

60

Figure 7. Axial position of adiabatic temperature in polytropic reactor depending on reactor diameter; total reactor volume constant according to Table 4; clean syngas as in Table 3 Furthermore, the scale-up capability of the fixed-bed reactor was investigated by increasing the gas hourly space velocity (GHSV), while the reactor geometry was kept constant according to Table 4. GHSV is defined as the synthesis gas volume flow at standard conditions divided by the reactor volume according to (19) and is a measure for the reactor load.

(19) 𝐺𝐻𝑆𝑉 = 𝑉

𝑉𝑆𝑡𝑑.

𝑟𝑒𝑎𝑐𝑡𝑜𝑟

Figure 8 illustrates the axial position where the adiabatic temperature Tmax is reached in dependence of the GHSV. As can be seen, the axial position where the adiabatic temperature Tmax is established shifts linearly with the GHSV, since the conversion per catalyst mass is constant for same conditions according to the applied kinetic model. At higher GHSV, and therefore also higher superficial velocity, an increased ratio of unconverted feed gas at the same axial reactor position slows down the increase of temperature and the related reaction rates.


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axial position of adiabatic temperature [mm]

Page 23 of 37

100 80 60 pin = 5 bar Tin = 300°C diameter = 27.6 mm Tmax (adiabatic) = 663°C

40 20 0

GHSV [h-1]

Figure 8. Axial position of maximal temperature in polytropic reactor depending on GHSV; reactor geometry according to Table 4; synthesis gas composition according to Table 3 For the case that cooling through the outer surface area within the main reaction zone is applied, the total removed heat within the reaction zone correlates with the axial position zmax in Figure 8 if convective cooling is assumed as constant. Since the total released heat varies in the same way with the GHSV a cooling through the outer surface does not change the maximum reached temperature. It should be mentioned that these considerations are only valid for a 1-D model, whereas in reality radial heat transport makes analysis difficult. Apart from cooling through the outer surface, maximum temperatures exceeding the catalyst specifications can also be avoided by adjustment of the feed gas composition. In the simplified methanation concept within the present work (Figure 3), this is done by an adapted CO2 removal and water content.

750°C

1st methanation 700°C 650°C 600°C 550°C


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Figure 9. Tadiabatic depending on CO2 removal of raw syngas (dry) from Table 3 and H2O content; Tin = 300°C, p = 5 bar Figure 9 summarizes the adiabatic methanation temperature for a feed, which is based on the raw syngas (dry) from Table 3 with varied CO2 removal and water content. As can be seen, Tadiabatic is strongly influenced by the water content in the feed, since the reachable conversion in equilibrium is reduced and more vapor has to be heated. This operating map illustrates intuitively the approach of cooling by increased steam content as it is done e.g. in the VESTA concept [10]. Contrarily, CO2 acts mainly as dilution of the product gas resulting in a decreased influence on adiabatic synthesis temperature. The adiabatic synthesis temperature (663°C) in Figure 9 of the investigated clean syngas composition with optimum CO2 removal and 25 vol.-% H2O content (Table 3) exceeds the maximum tolerable operation temperature of many common Ni methanation catalysts. In case of polytropic methanation of clean synthesis gas from Table 3 the applied cooling in the outer double-jacket (Table 4) reduces the maximum temperature slightly to 655°C as the results in Figure 10 show. This indicates that the applied cooling has a minor influence on maximum occurring temperatures and is insufficient to remove a relevant share of the released heat in the main reaction zone. Rather, the major part of catalytic fixed bed is used for slow cooling and simultaneous shift towards equilibrium composition. The situation even worsens if the GHSV is increased, because the low cooling flux densities only yield a marginal temperature decrease in the fixed bed. The increased average temperature in the fixed bed leads, apart from reduced conversion, to a higher convective heat removal. But a higher GHSV releases additional heat of reaction, thus only a significant lower proportion of the released heat is removed. The simulation results show that heat management is the key issue for polytrophic methanation


24

Page 25 of 37

reactors. For a suitable scale-up via GHSV increase both, the specific surface area per catalyst mass as well as the cooling flux density, have to be tremendously increased above the experimental conditions. Hence, the spatial combination of heat release and removal in structured reactors with a liquid as cooling agent seems to be superior to the investigated air-

300 600

13000 h-1

200 T(z) Q cool

400

1st cooling zone

200 0

1300 h-1

100 2nd cooling zone

3rd cooling zone

0

200 400 axial reactor position [mm]

600

accumulated heat removal Qcool [W]

cooled fixed bed concept.

T(z) [°C]

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Energy & Fuels

Figure 10. Axial temperature profile for reactor geometry of Table 4 and clean syngas composition of Table 3 6. Conclusion and outlook Aim of this work was the simulation-based evaluation of a simplified two-stage methanation unit with intermediate water removal, which shifts the equilibrium in the 2nd stage further to methane. Equilibrium simulations show a remarkable impact of CO2 removal efficiency on final SNG composition with a distinct optimum at 85 % and more than 90 vol.-% CH4 content, which could be explained intuitively in ternary C/H/O-diagrams. The adiabatic synthesis temperature and its axial reactor position were examined by kinetic based simulations, whereby the comparison of different kinetic models revealed that reverse reaction of CO methanation has to be considered for polytropic methanation above 400 °C. In particular, the water content in the


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Energy & Fuels

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Page 26 of 37

feed to the 1st stage is critical for control of maximum temperature in the first methanation reactor. The main reaction zone with the majority of released reaction heat is very close to the reactor inlet up to a GHSV of several ten thousand due to the fast reaction kinetics. The results underlined, that heat removal of the applied air-cooled polytropic fixed-bed methanation is insufficient to avoid temperatures exceeding the maximum catalyst temperature. Nevertheless, it should be pointed out that the maximum temperature is very sensitive to the reactor diameter and cooling concept. If both parameters are well designed, also tubular reactor concepts could suite a scale-up of polytropic methanation. For future experimental studies a new, structured, reactor concept should be considered, which allows for utilization of the thermodynamic potential of two-step methanation with intermediate water removal that avoids excess temperatures at the same time. Acknowledgments This research is carried out in the framework of the EU Project “CO2freeSNG2.0” (Ref. RFCSCT-2013-0008) funded by the research fund for coal and steel (RFCS). The authors would like to acknowledge the support provided by the European Union. References [1]

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Jonathan Lefebvre, Praseeth Prabhakaran, and Siegfried Bajohr. Review on methanation - from fundamentals to current projects. Fuel, 166:276–296, Feb 2016.


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[12] Michael Seiffert, Stefan Rönsch, Ralf Schmersahl, Martin Zeymer, Stefan Majer, Christian Pätz, and Martin Kaltschmitt. Biosng – demonstration of the production and utilization of synthetic natural gas (sng) from solid biofuels. project report, 2009. [13] G. A. Almansa, L.P.L.M Rabou, C. M. van der Meijden, A. van der Drift. ECN System for MEthanation (ESME). 23rd European Biomass Conference and Exhibition, Vienna, 2015. [14] S. Fendt, M. Gaderer, and H. Spliethoff. Dezentrale herstellung von synthetischem erdgas (sng) aus dem produktgas eines allotherm betriebenen biomassevergasers. Technical report, Technical University of Munich, 2014. [15] Thomas Kienberger, Christian Zuber, Kevin Novosel, Christoph Baumhakl, and Jürgen Karl. Desulfurization and in situ tar reduction within catalytic methanation of biogenous synthesis gas. Fuel, 107:102 – 112, 2013. [16] Moritz Husmann, Michael Müller, Christian Zuber, Thomas Kienberger, Viktoria Maitz, and Christoph Hochenauer. Application of bao-based sulfur sorbent for in situ desulfurization of biomass-derived syngas. Energy Fuels, 30(8):6458–6466, Aug 2016. [17] Michaela Fraubaum, Heimo Walter, and Christian Zuber. Kinetic modeling of a combined tar removal and methanation reactor for biogenous synthesis gas at medium temperature conditions. Fuel Processing Technology, 141:159–166, Jan 2016. [18] Jonas M. Leimert, Peter Treiber, and Jürgen Karl. The heatpipe reformer with optimized combustor design for enhanced cold gas efficiency. Fuel Processing Technology, 141:68–73, Jan 2016.


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[25] Kriston P. Brooks, Jianli Hu, Huayang Zhu, and Robert J. Kee. Methanation of carbon dioxide by hydrogen reduction using the sabatier process in microchannel reactors. Chemical Engineering Science, 62(4):1161–1170, Feb 2007. [26] Zhihong Liu, Bozhao Chu, Xuli Zhai, Yong Jin, and Yi Cheng. Total methanation of syngas to synthetic natural gas over ni catalyst in a micro-channel reactor. Fuel, 95:599–605, May 2012. [27] S. Bajohr, D. Schollenberger, D. Buchholz, T. Weinfurtner, and M. Götz. Kopplung der ptg-technologie mit thermochemischer biomassevergasung: Das kic-projekt „demosng“. gwf Gas+Energie, 155:470–475, 2014. [28] S. Bajohr, F. Graf, and M. Götz. Bewertung der kopplung von ptg-konzepten mit einer biomassevergasung. gwf - Gas+Energie, 154:222–227, 2013. [29] S. Rieke. Power-to-gas: Aktueller stand. presentation, ReBio e.v., 17th June 2013. [30] M. Lehr. Tubular reactors with pressurized liquid cooling, April 29 2010. DE Patent 102007024934. [31] S. Rolf. Patent DE 102014010055, Verfahren zum Betreiben eines Reaktors, 2016. [32] F. Marold. Patent DE102014010055, Plattenförmiger Wärmetauscher, 2016. [33] M. Gruber, S. Harth, D. Trimis, S. Bajohr, O. Posdziech, J. Brabandt, and W. Köppel. Integrated high-temperature electrolysis and methanation for effective power to gas conversion. In Gasfachliche Aussprachetagung, Essen, 2015.


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[34] F. Graf. Demosng - neues reaktorkonzept für die methanproduktion. gwf-Gas Erdgas, 12:18–19, 2015. [35] G. Alex Mills and Fred W. Steffgen. Catalytic methanation. Catalysis Reviews, 8(1):159– 210, Jan 1974. [36] R Hayes. A study of the nickel-catalyzed methanation reaction. Journal of Catalysis, 92(2):312–326, Apr 1985. [37] R.Z.C. van Meerten, J.G. Vollenbroek, M.H.J.M. de Croon, P.F.M.T. van Nisselrooy, and J.W.E. Coenen. The kinetics and mechanism of the methanation of carbon monoxide on a nickelsilica catalyst. Applied Catalysis, 3(1):29–56, Jun 1982. [38] R.Yadav and R. G. Rinker. Step-response kinetics of methanation over Ni/Al2O3 catalyst. Industrial & Engineering Chemistry Research, 31:502 – 508, 1992. [39] Th. Kammler and J. Küppers. Methanation of carbon on ni(100) surfaces at 120 k with gaseous h atoms. Chemical Physics Letters, 267(3-4):391–396, Mar 1997. [40] Jens Sehested, S Dahl, Joachim Jacobsen, and Jens R. Rostrup-Nielsen. Methanation of co over nickel: Mechanism and kinetics at high h 2 /co ratios. J. Phys. Chem. B, 109(6):2432–2438, Feb 2005. [41] J.W.E. Coenen, P.F.M.T. van Nisselrooy, M.H.J.M. de Croon, P.F.H.A. van Dooren, and R.Z.C. van Meerten. The dynamics of methanation of carbon monoxide on nickel catalysts. Applied Catalysis, 25(1-2):1–8, Aug 1986. [42] Jan Kopyscinski, Tilman J. Schildhauer, Frédéric Vogel, Serge M.A. Biollaz, and Alexander Wokaun. Applying spatially resolved concentration and temperature measurements in


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a catalytic plate reactor for the kinetic study of co methanation. Journal of Catalysis, 271:262– 279, 2010. [43] S. Rönsch, J. Köchermann, J. Schneider, and S. Matthischke. Global reaction kinetics of CO and CO2 methanation for dynamic process modeling. Chem. Eng. Technol., 39(2):208–218, Jan 2016. [44] Jianguo Xu and Gilbert F. Froment. Methane steam reforming, methanation and water-gas shift: I. intrinsic kinetics. AIChE J., 35(1):88–96, Jan 1989. [45] Jan Kopyscinski. Production of synthetic natural gas in a fluidized bed reactor. PhD thesis, Paul-Scherrer-Institut, 2010. [46] D. Schlereth and O. Hinrichsen. A fixed-bed reactor modeling study on the methanation of CO2. Chemical Engineering Research and Design, 92(4):702–712, Apr 2014. [47] J. Klose and M. Baerns. Kinetics of the methanation of carbon monoxide on an aluminasupported nickel catalyst. Journal of Catalysis, 85(1):105–116, Jan 1984. [48] Jie Zhang, Nouria Fatah, Sandra Capela, Yilmaz Kara, Olivier Guerrini, and Andrei Y. Khodakov. Kinetic investigation of carbon monoxide hydrogenation under realistic conditions of methanation of biomass derived syngas. Fuel, 111:845 – 854, 2013. [49] S. S. E. H. Elnashaie and S. S. Elshishini. Modelling, simulation, and optimization of industrial fixed bed catalytic reactors, volume 7 of Topics in chemical engineering. Gordon and Breach Science Publishers, 1993.


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[50] Christoph Baumhakl. Substitute Natural Gas Production with direct Conversion of Higher Hydrocarbons. PhD thesis, Technical Faculty of Friedrich-Alexander-University ErlangenNuremberg, Nuremberg, 2014. [51] E. Müller-Erlwein. Chemische Reaktionstechnik. Springer Verlag, 2015. [52] Wladimir Reschetilowski. Einführung in die Heterogene Katalyse. Springer-Verlag, 2015. [53] Maria Sudiro, Alberto Bertucco, Gianpiero Groppi, and Enrico Tronconi. Simulation of a structured catalytic reactor for exothermic methanation reactions producing synthetic natural gas. 20th European Symposium on Computer Aided Process Engineering, pages 691–696, 2010. Table 1. Relevant reaction equations for methanation Reaction equation

∆𝐻𝑅0 [kJ/mol]

(1)

3 H2 + CO ⇌ CH4 + H2O

- 206

(2)

H2O + CO ⇌ CO2 + H2

- 41

(3)

4 H2 + CO2 ⇌ CH4 + 2 H2O

- 165

(4)

2 CO ⇌ C + CO2

- 173


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Table 2. Selected coal-to-SNG plants (own research)

Project

Location

Methanation technology

Year of startup

USA Great Plains Synfuel

North Dakota

Lurgi

1984

Cash Creek Generation

Kentucky

HICOM

2012

Southern Illinois Coalto-SNG Facility

Illinois

TREMP

2013

More than 10 further projects erected or announced in USA China Qinghua

Yili, Xinjiang

TREMP

2013

Xinwen

Yili, Xinjiang

HICOM

2013

Huineng

Ordos

TREMP

2013

CNOOC

Shandong

TREMP

2013

PetroChina

Wuhai

TREMP

2013

Datang

Fuxin, Liaoning

HICOM

2014

China Power Invest. Corp.

Yili, Xinjiang

TREMP

2015

More than 15 further projects erected or announced in China Asia without China POSCO

Gwangyang, South Korea

TREMP

2014

Jamnagar Gas

Gujarat, India

TREMP

2015


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Energy & Fuels

Table 3. Measured raw syngas composition (dry) from 5 kW lab-scale allothermal fluidized-bed steam gasifier (N2 free; σ = 5, T = 830°C, p = 5 bara) and calculated resulting gas compositions in downstream units for best case assumptions

clean raw raw syngas syngas syngas (wet) (dry) (wet) ηCO2: 0.85

intermed. SNG (dry) ηCO2: 0.85

final SNG (dry) ηCO2: 0.85

H2

[%] 56.0

28.0

54.0

6.9

3.4

CO

[%] 13.5

6.8

13.0

~0

~0

CO2 [%] 26.0

13.0

3.7

0.9

~0

CH4 [%] 4.5

2.3

4.3

92.2

96.6

H2O [%] -

50

25

-

-

Table 4. Feed gas composition and reactor geometry for plausibility checks feed

H2

CO

CO2

CH4

N2

H2O

[vol.-%]

29.4

10.4

13.2

4.0

3.0

40.0

d

Ltotal

zone 1 zone 2 zone 3

27.6

600

100

200

300

α [Wm-2K-1]

15

12

9

Tcool,in [°C]

20

20

20

Tcool,out [°C]

158

278

211

reactor geometry size [mm]


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Table 5. Data from literature and Aspen input data for the kinetic model of Zhang et al. with adjustments of Rönsch et al.

parameter

𝑘1

𝑘1∗ = 𝑘1 ∙ 𝐾𝐶 ∙ 𝐾𝐻2

original data [43] with transformed dimensions

unit

Aspen parameter

103000 𝐽/𝑚𝑜𝑙 ) 𝑅𝑇

[

29000 𝐽/𝑚𝑜𝑙 ∙ exp (− ) 𝑅𝑇

[

62000 𝐽/𝑚𝑜𝑙 ∙ exp (− ) 𝑅𝑇

𝑘𝑚𝑜𝑙 ∙ 𝑃𝑎 −1 [ ] 𝑘𝑔𝑐𝑎𝑡 ∙ 𝑠

1.94 ∙ 107 ∙ exp (−

𝑘𝑚𝑜𝑙

𝑘𝑔𝑐𝑎𝑡 ∙𝑠

]

𝑘𝑚𝑜𝑙∙𝑃𝑎 −1,5

9.13 ∙ 10

−8

𝑘2

2.18 ∙ 10

−2

𝐾𝐶

42000 𝐽/𝑚𝑜𝑙 1.83 ∙ 10−6 ∙ exp ( ) 𝑅𝑇

[𝑃𝑎 −0,5 ]

𝐾𝐻

16000 𝐽/𝑚𝑜𝑙 5.06 ∙ 10−5 ∙ exp ( ) 𝑅𝑇

[𝑃𝑎 −0,5 ]

𝐾𝐶𝑂

70650 𝐽/𝑚𝑜𝑙 8.23 ∙ 10−10 ∙ exp ( ) 𝑅𝑇

[𝑃𝑎 −1 ]

82900 𝐽/𝑚𝑜𝑙 ∙ exp ( ) 𝑅𝑇

[𝑃𝑎 −1 ]

𝑘𝑔𝑐𝑎𝑡 ∙𝑠

38280 𝐽/𝑚𝑜𝑙 6.65 ∙ 10−9 ∙ exp ( ) 𝑅𝑇

[𝑃𝑎 −1 ]

𝐾𝐻2𝑂

88680 𝐽/𝑚𝑜𝑙 1.77 ∙ 10 ∙ exp (− ) 𝑅𝑇

-

𝐾𝑀𝑒𝑡ℎ 1 𝐾𝑊𝐺𝑆

1.027 ∙ 1010 ∙ exp (30,11 −

exp (4.063 −

4400 ) 𝑇

26830 ) 𝑇

𝑘20 = 2.18 ∙ 10−2 𝐸𝐴,2 = 62 𝑘𝐽/𝑚𝑜𝑙 𝐴𝐶 = −13.209

𝐴𝐻 = −9.892

𝐴𝐶𝑂 = −20.918 𝐵𝐶𝑂 = 8497.20

𝐾𝐶𝐻4

1

∗ 𝐸𝐴,1 = 29 𝑘𝐽/𝑚𝑜𝑙

𝐵𝐻 = 1924.35

6.12 ∙ 10

5

𝑘1∗0 = 9.13 ∙ 10−8

𝐵𝐶 = 5051.42

𝐾𝐻2

−14

]

𝐴𝐻2 = −30.425 𝐵𝐻2 = 9970.53 𝐴𝐶𝐻4 = −18.829 𝐵𝐶𝐻4 = 4604.01 𝐴𝐻2𝑂 = 12.084 𝐵𝐻2𝑂 = −10665.70

[𝑃𝑎2 ]

𝐴𝑀𝑒𝑡ℎ = 53.162 𝐵𝑀𝑒𝑡ℎ = −26830

-

𝐴𝑊𝐺𝑆 = 4.063 𝐵𝑊𝐺𝑆 = −4400

𝐶 = 0 and 𝐷 = 0 for all parameters


36

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Energy & Fuels

Appendix Xu/Froment [44]

Kopyscinski (model 12b) [42]

k1

𝑘10 = 3.664 ∙ 1014 ; 𝐸𝐴,1 = 240.1 𝑘𝐽/𝑚𝑜𝑙

k1

𝑘10 = 3.437 ∙ 106; 𝐸𝐴,1 = 74.1 𝑘𝐽/𝑚𝑜𝑙

k2

𝑘20 = 5.414 ∙ 10−3; 𝐸𝐴,2 = 67.1 𝑘𝐽/𝑚𝑜𝑙

k2

𝑘20 = 9.619 ∙ 1014 ; 𝐸𝐴,2 = 161.6 𝑘𝐽/𝑚𝑜𝑙

k3

𝑘30 = 8.828 ∙ 1013 ; 𝐸𝐴,3 = 243.9 𝑘𝐽/𝑚𝑜𝑙

KC

𝐴𝐶 = −11.730; 𝐵𝐶 = 7357.2

KCO

𝐴𝐶𝑂 = −20.915; 𝐵𝐶𝑂 = 8497.2

KOH

𝐴𝑂𝐻 = −15.010; 𝐵𝑂𝐻 = 8733.0

KH2

𝐴𝐻2 = −30.420; 𝐵𝐻2 = 9971.1

Kα

𝐴𝛼 = −2.370; 𝐵𝛼 = 777.6

KCH4

𝐴𝐶𝐻4 = −18.827; 𝐵𝐶𝐻4 = 4604.3

Keq

𝐴𝑒𝑞 = 4.063; 𝐵𝑒𝑞 = −4400.0

KH2O

𝐴𝐻2𝑂 = 12.080; 𝐵𝐻2𝑂 = −10666.3

K1

𝐴1 = −53.162; 𝐵1 = 26830.0

K2

𝐴2 = 4.063; 𝐵2 = −4400.0

K3

𝐴3 = −49.099; 𝐵3 = 22430.0


37

Simulation-Based Evaluation of a Two-Stage Small-Scale

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