Analysis of Membrane and Adsorbent Processes for Warm Syngas

ARTICLE pubs.acs.org/IECR

Analysis of Membrane and Adsorbent Processes for Warm Syngas Cleanup in Integrated Gasification Combined-Cycle Power with CO2 Capture and Sequestration David J. Couling, Kshitij Prakash, and William H. Green* Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 66-270, Cambridge, Massachusetts, United States

bS Supporting Information ABSTRACT: Integrated gasification combined cycle (IGCC) with CO2 capture and sequestration (CCS) offers a promising approach for cleanly using abundant coal reserves of the world to generate electricity. The present state-of-the-art synthesis gas (syngas) cleanup technologies in IGCC involve cooling the syngas from the gasifier to room temperature or lower for removing sulfur, carbon dioxide, and other pollutants, leading to a large efficiency loss. Here we assess the suitability of various alternative syngas cleanup technologies for IGCC with CCS through computational simulations. We model multicomponent gas separation for CO2 capture in IGCC using polymeric membranes and H2 separation from the syngas using both Pd-alloy based composite metallic membranes and polymeric membranes. In addition, we develop a pressure swing adsorption model to estimate the energy efficiency of regenerable sorbent beds for CO2 capture. We use our models with Aspen Plus simulations to identify promising design and operating conditions for membrane and adsorption processes in an IGCC plant. On the basis of our analysis, the benefits of warm gas cleanup are not as great as previously reported in the literature, and only CO2 separations performed using H2-permeable Pdalloy membranes and CO2 adsorbents produce overall higher heating value (HHV) efficiencies higher than that of Selexol. In addition, many of the technologies surveyed require a narrow operating range of process parameters in order to be viable alternatives. We identify desired material properties of membranes and thermodynamic properties of sorbents that are needed to make these technologies successful, providing direction for ongoing experimental efforts to develop these materials.

’ INTRODUCTION It is predicted that coal will continue to be a significant part of the world’s energy portfolio in the future, and its use will see continued growth, especially in the developing world.1,2 Unfortunately, a major problem with present coal technology is the high level of contaminants in the feedstock, including nitrogen and sulfur compounds, trace amounts of heavy metals, and a large amount of carbon, which is released as carbon dioxide. IGCC with CCS presents a method to achieve tight emission limits on criteria pollutants (NOx, SOx, CO, PM10) and mitigate greenhouse emissions by capturing CO2. All the commercially available syngas cleanup processes for IGCC with CCS involve cooling the stream to low temperatures and employing scrubbing with physical or chemical solvents for removing sulfur and CO2. A study carried out by Rubin et al.3 using the integrated environmental control model (IECM) developed by Carnegie Mellon University concluded a higher heating value (HHV) efficiency penalty of approximately 7 percentage points (i.e., about a 20% reduction in electricity sent to the grid) arises for CO2 capture using the Selexol process in an IGCC plant as compared to base case of no capture. The results of a similar analysis carried out by DOE/NETL,4,5 which assumed commercially available processes for syngas cleanup and carbon capture, predicted a similar reduction in net power output and a corresponding reduction in HHV thermal efficiency of 69 percentage points. It would be very desirable to avoid these predicted large reductions in net power output that translate to large increases in the capital and operating costs per kilowatt hour delivered to the r 2011 American Chemical Society

grid. In addition, the resulting increased coal consumption also corresponds to a need for more CO2 sequestration capacity, providing further incentive for more efficient CO2 separations. Prior studies have assessed different syngas cleanup and CO2 separation processes and identified opportunities to significantly improve the efficiency. Eastman Chemical and RTI6 predict that for IGCC without CCS, high temperature syngas cleanup can provide a HHV thermal efficiency improvement of 3.6 percentage points over low temperature cleanup. DOE/NETL also investigated high-temperature syngas cleanup for IGCC with CCS as part of a larger study on IGCC efficiency.7 They conclude that through the use of H2-permeable membranes the HHV thermal efficiency can increase by roughly 3.7 percentage points and decrease the cost of electricity by 1.3 cents/kWh. Our goal is to extend these previous analyses to include a wider variety of novel separation methods, namely sorbents and CO2-permeable membranes, for IGCC with CCS. Using our computational approach we identify favorable designs and operating conditions for each of these separation processes and provide an assessment of its viability in an IGCCCCS system. The methods for separating the CO2 from the syngas mixture can essentially be divided into five cases, as illustrated in Figure 1.

Received: February 10, 2011 Accepted: August 11, 2011 Revised: July 28, 2011 Published: August 11, 2011 11313

dx.doi.org/10.1021/ie200291j | Ind. Eng. Chem. Res. 2011, 50, 11313–11336

Industrial & Engineering Chemistry Research

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Figure 1. Schematics of (a) the base case solvent CO2 capture process and (be) the four variations of single-stage warm syngas cleanup that were evaluated in this work. More details on the specific technologies that correspond with these diagrams are given in the following sections.

The base case, Selexol, is shown in simplified form in Figure 1a. A syngas mixture consisting primarily of H2, CO2, and H2O enters the unit. The temperature is lowered, condensing the steam and producing heat (Q_ ). The CO2 and H2 are then separated using an absorption unit, which results in two streams at low temperature: one high-pressure H2 stream, and one lowpressure CO2 stream. The four remaining cases illustrate different possibilities for single-stage CO2 capture at elevated temperatures. According to the study by Eastman Chemical and RTI,6 a potentially large benefit of warm syngas cleanup is that the steam present in the original syngas mixture does not have the opportunity to condense. This steam then functions as the diluent in the IGCC gas turbine, effectively keeping the flame temperature low while reducing the amount of N2 diluent required for compression from the ASU. Following this logic, therefore, a promising CO2 capture technology is shown in Figure 1b, where the H2O present in the syngas partitions into the H2 stream. As an added benefit, the system shown in Figure 1b produces the CO2 stream at high pressure, reducing the energy consumption necessary to compress the CO2 stream for sequestration. A similarly promising technology is shown in Figure 1c. Here too the steam that is originally present in the syngas is not separated from the H2 stream that continues downstream to the gas turbine; the only difference in this case is that the CO2 product stream is produced at low pressure and the H2 product stream is produced at high pressure, which is the reverse case of Figure 1b. The remaining cases, Figure 1d and Figure 1e, are analogous to Figure 1b and Figure 1c, respectively, but in these cases the steam present in the syngas partitions to the CO2 stream instead of the H2 stream. Although these two cases potentially benefit from a reduced capital cost by operating at high temperature and greater efficiency, they do not have the tangible benefit of reducing the amount of N2 diluent. Therefore, although any technologies that fall into the categories of Figure 1d and Figure 1e may be promising, the benefit derived from them being performed at elevated temperatures is expected to be reduced relative to their counterparts in Figure 1b and Figure 1c.

We begin our analysis of specific CO2 separation technologies by briefly summarizing the current state of the technology for H2- and CO2-permeable membranes and CO2 sorbents. H2 Pd-Alloy Membranes. Two different types of H2 membranes have been extensively studied: Pd alloys, which do not permeate H2O and correspond to Figure 1d, and less-selective polymer or ceramic membranes, which generally correspond to Figure 1b. Several studies have reported high hydrogen permeance and selectivity in thin inorganic Pd-alloy composite membranes under conditions of high temperatures and pressures.811 The stability and permeation characteristics of Pd-alloy membranes have been investigated for application in water gas shift and steam reforming reactions to simultaneously achieve a high conversion and pure hydrogen production.8,12,13 Previous studies of the efficiency benefits of H2 membranes are mixed. A study by Amelio et al.,14 which compared using a Pd-based membrane for CO2 capture in IGCC against using a conventional physical absorption system suggested a 1.4 percentage point lower heating value (LHV) lower efficiency for the membrane reactor. On the contrary, Chiesa et al.15 predicted the thermal efficiency of IGCC using a Pd-alloy H2 membrane reactor for CO2 capture to be 1.5 HHV percentage points higher than IGCC with conventional physical absorption for CO2 capture. Although the source of the discrepancy between the two models is not immediately clear, the Chiesa model does include a greater degree of optimization in the steam cycle and the use of a catalytic oxidation unit to recover heating value from the retentate stream, both of which could be significant. Polymeric Membranes. Polymeric membranes separate species based on the differences in diffusivity and solubility of species in the polymer structure. An upper bound analysis for the separation of different binary gas pairs using polymeric membranes was done by Robeson.16,17 In general, polymeric membranes that are selective to H2 have higher selectivity at low temperatures, and as permeability increases with temperature the selectivity of the membrane deteriorates.16 There has been extensive discussion in the literature of the theoretical basis of this observed Robeson correlation.1820 For the case of H2/CO2 11314

dx.doi.org/10.1021/ie200291j |Ind. Eng. Chem. Res. 2011, 50, 11313–11336

Industrial & Engineering Chemistry Research separations, H2 is more permeable in many polymer membranes than CO2 owing to its smaller size and high diffusivity. However, CO2 has been shown to selectively transport over H2 in some polymers by virtue of its higher solubility and facilitated transport. Steam generally has a large permeability in the polymeric membranes, and here it is assumed that most of it diffuses to the permeate side. CO2 Membranes. As of now, no CO2 membranes have been demonstrated to perform with high selectivity at the high temperatures proposed for warm syngas cleanup. Polymeric membranes with facilitated transport having CO2 permeabilities as high as 9710 barrer (1 barrer =1011 (cm3 STP) cm cm2 s1 mmHg1 = 3.348 1016 mol m2 s1 Pa1) and showing CO2/H2 selectivities up to 500 have been reported at low temperatures and high relative humidity conditions.21,22 Although some polymeric CO2 membranes have high CO2/H2 selectivities, typically steam passes through the membranes as rapidly as CO2, so these correspond to Figure 1e. NETL researchers are reported to have recently fabricated and tested a supported ionic liquid membrane that is CO2 selective and stable at temperatures exceeding 573 K,23 but these membranes are still in their developmental stages. Grainger and Haag’s techno-economic evaluation of CO2 selective membranes for carbon capture, based on data published for an operating IGCC plant, concluded an HHV efficiency penalty of 10 percentage points compared to a nocapture case.24 By their evaluation, an IGCCCCS with CO2 membranes appears to be less efficient than an IGCCCCS with Selexol (as estimated by NETL4,5). H2 Membranes. The most promising among polymeric H2 membranes is a polybenzimidazole (PBI) membrane under development at DOE’s Los Alamos National Laboratory (LANL).25 It has demonstrated long-term hydrothermal stability up to 673 K, sulfur tolerance, and overall durability while operating in simulated industrial coal-derived syngas environments for over 400 days at 523 K.26 Previous studies of the efficiency benefits of this and other H2 polymer membranes are again mixed. Kaldis et al.27 evaluated hydrogen-selective low-temperature polymer and high-temperature ceramic membranes for precombustion CO2 capture and obtained an IGCC plant LHV efficiency of 814 percentage points lower than without capture. From this study it is not clear whether using H2 membranes improves or reduces overall IGCCCCS efficiency relative to conventional Selexol technology. A modeling analysis by Krishnan et al.25 comparing the HHV efficiencies of IGCC power plants with no CO2 capture, CO2 capture using Selexol, and CO2 capture using the PBI membrane found that the IGCCCCS efficiency is approximately 9 percentage points (HHV) lower using Selexol and 10 percentage points (HHV) lower using the PBI membrane. In other words, according to Krishnan et al., an IGCCCCS process based on PBI membranes would be slightly less energy efficient than existing technologies. By contrast, an analysis performed by Ku et al.28 found that the IGCC efficiency could be improved by 1.7 percentage points over Selexol through the use of a H2-permeable membrane and a catalytic oxidizer for the unburned fuel gas components. The source of the disagreement between the two studies is not completely clear; however, it may be caused in part by the fact that the Krishnan study uses a specific PBI membrane with known performance characteristics, and the Ku study identifies favorable characteristics of a hypothetical H2-permeable membrane, and as such the estimates of efficiencies for this hypothetical material may be high.

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CO2 Adsorbents. Large quantities of carbon dioxide present in the syngas stream require a selective, regenerable sorbent in order to reduce raw material costs and the generation of large volumes of solid waste. The sorbent should also be mechanically stable to reduce the replacement costs associated with sorbent attrition. Careful attention must be paid not only to the ability of the sorbent to capture carbon dioxide but also the energy and capital costs needed for its regeneration. Many materials have been proposed as potential warm-temperature carbon dioxide sorbents, including alkali earth metal oxides, hydrotalcite, zeolites, and silicates,2932 but these materials generally suffer from low capacity at elevated temperatures or large energy penalties associated with their regeneration. CO2 sorbents used for pressure swing adsorption correspond to Figure 1c or Figure 1e, depending on the sorbent’s affinity for H2O. An evaluation performed by Ito and Makino estimated a 14.9% reduction in electricity output (or a reduction of 6.2 percentage points of efficiency) using pressure swing adsorption when compared to a no-capture case,33 making it potentially the most efficient option of all technologies studied in this work. Our Approach. Like all technologies in their incipient stage of development and implementation, there is uncertainty surrounding the performance of various sorbents and membranes for high temperature gas separation in IGCC. A traditional method to address this problem would be to experimentally test a large number of synthesized materials. This is not only costly and timeintensive, but also often incomplete because not enough is known about the optimal experimental operating conditions. In this paper we present an alternative approach in which computational techniques are employed first to help glean a better understanding of the separation processes and subsequently to guide experimental research. This is made possible by developing detailed numerical models of gas separation processes that are integrated with Aspen Plus to simulate the performance of IGCC with CCS. Here we present our results on promising operating conditions and desired material properties for membranes and sorbents suitable for CO2 capture.

’ MODELING WORK IGCC Process Simulation. Base Case: IGCCCCS Using Selexol. A simulation of IGCC with CO2 capture at high tempera-

ture was developed in Aspen Plus based on the base case IGCC flowsheet of Field and Brasington34 with a low-temperature Selexol process for CO2 capture. The overall design is based on the NETL report4,5 on coal to electricity conversion. Coal is fed to an entrained-flow, oxygen-blown, slurry-fed gasifier whose characteristics reproduce the TexacoGE Energy gasification technology. The coal slurry and the oxygen react in the gasifier at 5.6 MPa (815 psia) and 1643 K to produce syngas. The oxygen for the gasifier is supplied from a cryogenic air separation unit (ASU). The syngas consists primarily of hydrogen and carbon monoxide, with lesser amounts of water vapor and carbon dioxide, and small amounts of hydrogen sulfide, carbonyl sulfide, methane, argon, and nitrogen. The slag solids collect in the sump at the bottom of the gasifier and are removed periodically using a lock hopper system. Syngas is cooled from 1643 to 1033 K in a radiant cooler, and the heat transferred is used to generate high-pressure steam. The raw syngas is then quenched, that is, cooled by direct contact with a large liquid water stream, and saturated with water vapor. It then passes through a scrubber where a water wash is used to remove chlorides and particulate matter. The syngas 11315



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Figure 2. IGCC with CCS and warm syngas cleanup.

exiting the scrubber is adjusted to an H2O:CO molar ratio of 2:1 by adding high-pressure steam prior to the first water gas shift reactor (WGS) reactor, where its temperature increases to 693 K due to the exothermic nature of the reaction. Heat released at this temperature is also used to generate high-pressure saturated steam. A second, cooler stage of WGS is added to achieve higher overall conversion of CO to CO2. The WGS catalyst also serves to hydrolyze COS, thus eliminating the need for a separate COS hydrolysis reactor. To limit the scope of the project, the WGS conversion was held constant throughout the course of this study. However, Bhattacharyya et al.35 demonstrated that efficiency improvements of about 1.6 percentage points could be achieved if more global optimizations such as WGS conversion were taken into account. The syngas is then cooled to 312 K, removing most of the water present in the stream, by heating up feedwater and generating low pressure steam through a series of heat exchangers and knockout drums. The cooled syngas is fed to a two-stage Selexol process for acid gas removal, where H2S is removed in the first stage and CO2 is removed in the second stage of the absorption system. The CO2-rich stream is obtained at two different pressure levels and compressed to a final pressure of 150 bar for sequestration while the H2S stream is sent to the Claus unit for sulfur recovery. The decarbonized syngas, composed primarily of H2, is then run through an expansion turbine to recover energy and bring the pressure down to the delivery pressure of the gas turbine. The clean syngas is diluted with N2 from the ASU and enters the gas turbine burner. The amount of N2 diluent to be added is determined by the requirement of maintaining the appropriate lower heating value of the syngas feeding into the gas turbine burner to achieve sufficiently low NOx emissions (1535 ppmv at 15% O2)36 and to keep the temperature of the gas low enough to avoid blade failure. The decarbonized, diluted fuel undergoes combustion and power generation in an advanced GE 7FB class gas turbine. The amount of coal fed to the gasifier is specified so that the power output of the gas turbine is a constant 460 MW (such that the amount of thermal input is variable for each case simulated in this work). High-temperature flue gas exiting the gas turbine is

conveyed through the heat recovery steam generator (HRSG) to recover the large quantity of thermal energy that remains in the exhaust. The heat exchange between various streams in the HRSG section is modeled in Aspen Plus using two MHeatX blocks, which allow heat exchange between multiple process streams. One MHeatX block superheats HP and IP steam from the heat from the flue gas above 623 K, while the other block creates low pressure (LP) steam from the lower temperature flue gas and the lower quality heat available in the plant. IP steam is also generated through direct heat exchange with process heat in the IGCC plant. Both MHeatX blocks are specified within Aspen Plus to maintain a certain minimum approach temperature (at least 25 K for the HP block, and exactly 12 K for the LP block). The steam exiting the low pressure turbine is condensed and sent to a boiler feedwater mixer, where it is reheated and recycled. It is worth noting that although the MHeatX blocks help to make the heat transfer in the HRSG as efficient as possible, a full optimization of the heat integration was not performed in this work (either for the base case or warm syngas cleanup models described in future sections). Deeper analyses of the heat integration in the IGCC plant have been performed37 that show efficiency improvements of 1.7 percentage points HHV, but because all models were evaluated on this consistent basis in the HRSG, a full optimization was beyond the scope of this work. Further details on Aspen Plus modeling of each process can be found in the report by Field and Brasington.34 A full table that summarizes the assumptions and operating conditions used in the base case model is given in the Supporting Information. These parameters were also adopted to generate results from our simulations of IGCC with high temperature syngas cleanup, described in future sections. Hot Syngas Cleanup IGCCCCS Flowsheet. The main difference between the hot syngas cleanup flowsheet, shown in Figure 2, and the base case34 is the absence of a cooling section to lower the syngas temperature after the WGS reactors, since carbon capture and pollutant removal are accomplished using high temperature membrane or sorbent processes. A sulfur removal unit is placed upstream of the CO2 capture process, as many membranes and sorbents become inactive or poisoned in the presence of sulfur. 11316



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Table 1. Performance of Pd-Alloy Composite Membranes from Experimental Data in Literature membrane reference temperature (K)

Pd-23Ag Peters42 673

Pd-40Cu

Pd-40Cu

Roa44 638

Edlund45 673

PdNi Nam9 625

Pd-alloy Eltron46 713

thickness (μm)

2

1.3

15

1

100

permeance (mol m2 s1 Pa0.5)

1.1 103

7.5 104

1.76 103

7.14 104

1.2 104

permeability (mol m1 s1 Pa0.5)

2.2 109

9.75 1010

2.64 108

7.14 1010

1.2 108

A high-temperature ZnO-based adsorbent process developed by RTI38 is simulated for H2S and COS removal from the syngas in the form of ZnS. The sorbent is regenerated by oxidation in a stream of O2 supplied from the ASU to form SO2, which is reacted with a slip stream of syngas to yield elemental sulfur. The operating conditions for this process were estimated using documentation available from Eastman Chemical and RTI.39,40 The most relevant chemical reactions in this sorbent regeneration process are shown in eqs 1 and 2. ZnS þ

3 O2 f ZnO þ SO2 2

SO2 þ 2H2 f S þ 2H2 O

ð1Þ ð2Þ

The sulfur-free syngas is then fed into a membrane unit or a sorbent bed for CO2 capture at a temperature above the dew point of steam in the syngas. The fuel content of the decarbonized syngas is primarily H2, although there may be uncoverted CO or small amounts of hydrocarbons present as well, depending on the CO2 capture method used. Inerts such as N2 or steam may also be present. The CO2 and sulfur capture technologies are integrated into the HRSG section such that the steam requirement for these processes decreases the amount available for power generation. The fuel gas stream is then run through an expansion turbine and mixed with additional N2 diluent before entering the gas turbine burner. The amount of N2 diluent added in IGCCCCS with hot syngas cleanup is potentially lower than the base case due to the presence of steam in the syngas: not only can the steam take the place of the N2 diluent, but it may also decrease the total amount of diluent required, since its higher heat capacity relative to N2 increases its ability to keep the turbine temperatures low. Inorganic Pd-Alloy Membrane Model. Pd-alloy composite membranes have been widely reported to have a large H2 permeance with high selectivity as shown in Table 1. They have an asymmetric structure consisting of a thin Pd-alloy top layer and a support structure that provides the mechanical strength. The small thickness of Pd alloy on the support not only reduces the membrane’s cost but also increases the hydrogen permeation rate. Possible reduction of H2 permeance has been reported41,42 in the presence of H2O and CO, and there are stability concerns in high H2S environment.43 At equilibrium, the adsorption and desorption rates are equal, and in the limit of diffusion-limited permeation, the hydrogen flux can be written as P JH2 ¼ ðpH2 , 1 n pH2 , 2 n Þ l

ð3Þ

where n is equal to 0.5 for bulk diffusion of protons (for a derivation of this model, please see the Supporting Information). Note that different values of n have been reported in the literature,47 suggesting other processes could be rate limiting.

Figure 3. Countercurrent membrane separation.

The transport mechanism described above with n = 0.5 was used to model hydrogen separation in a membrane module arranged in a countercurrent configuration. Nitrogen from the ASU is used as a sweep gas on the permeate side. A one-dimensional, steady state, isothermal model was developed assuming all gases other than hydrogen to have negligible permeance through the membrane. The membrane permeability chosen for our model was 2.2 109 mol m1 s1 Pa0.5, the same value given by Peters et al.42 This particular permeability value was measured in the presence of CO, CO2, and H2O and accounts for some of the competitive adsorption effects on the H2 permeability. In addition, mass transfer resistances in the gas phase were assumed to be negligible due to the low flux of H2 through the membrane. Within the framework of the IGCC model, the objective is to operate the membrane unit with a high hydrogen recovery to avoid wasting fuel and to obtain high purity CO2 for sequestration. Polymeric Membrane Model. Polymeric membranes are attractive because they can be manufactured into units with very high surface areas in the form of hollow fibers or as spiral-wound modules. The selectivity of most polymeric membranes depends on their ability to discriminate gas species by size, diffusivity, and solubility through the membrane structure. In dense, nonporous membranes, transport through the membrane is controlled by the solution-diffusion mechanism. Under this transport mechanism, the permeating molecules dissolve into the polymer membrane and then diffuse through the membrane, driven by a chemical potential gradient. When the driving force is the pressure difference across the membrane, the flux of a component is given as Ji ¼

Pi ðpio pil Þ l

ð4Þ

where Ji is the flux of component i, Pi is its permeability (in mol m1 s1 Pa1) and pio and pil are the partial pressure of component i at the feed and permeate interface. Pan’s48 model based on solution diffusion transport is the most widely accepted practical representation of multicomponent gas separation in polymeric hollow fiber membranes. A MATLAB model was developed adapting the computational scheme of Chowdhury et al.49 to solve Pan’s model for isothermal, countercurrent flow as shown in Figure 3. The local mole fraction of species i in the permeate stream at the membrane interface, yi, is generally different from that of the 11317



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bulk permeate stream, yi,p. The key assumption in this model is that for pressure-driven flow across membranes with an ultrathin skin and a highly porous supporting layer, the effect of backdiffusion from bulk, yi,p, to membrane interface, yi, is negligible, so yi is a function of the permeate and retentate pressures and the mole fractions on the retentate side. Further information regarding the development of the mole fractions in the permeate and retentate streams can be found in the Supporting Information. Note that Pan’s model is significantly different from the model used for Pd-alloy membranes,15,50 which assumes the opposite limit (fast back mixing relative to slow permeation through the membrane). In this respect Pan’s model is conservative, and the Pd-alloy membrane model is optimistic. Adsorption Model for CO2 SeparationRegeneration Using Steam. A pressure swing adsorption model was developed for the chemisorption of CO2 onto a hypothetical sorbent X. CO2 þ X h CO2 X

ð5Þ

To determine the energy penalty associated with sorbent regeneration, a numerical simulation of the adsorption cycle was developed for different pressure swing processes. The sorbent system was initially modeled as a transient, adiabatic fixed bed. To simplify the model, the adsorption process was assumed to be 1-dimensional with no radial gradients, and the Peclet number was considered to be sufficiently high (and the bed sufficiently uniform) that axial diffusion and dispersion could be neglected. The resulting model equations are listed below, assuming that the only adsorbing species in the system is CO2. A full description can be found in the Supporting Information. ! qsat dqi i Keq yi ðp=pref Þ ¼ kLDF ðq qi Þ ¼ kLDF qi 1 þ Keq yi ðp=pref Þ dt ð6Þ ε

∂C ∂ðuCÞ ¼ ε Fbed ∂t ∂z

ε

∂yi ∂yi F RT dqi ¼ εu bed yi p ∂t ∂z dt

∑i dti

ðεFgas Cp, gas þ Fbed Cp, solid Þ Fbed ΔHads

dq

ð7Þ

∑i dti dq

ð8Þ

∂ðuFgas Cp, gas TÞ ∂T ¼ε ∂t ∂z

∑i dti dq

∂p 150μm ð1 εÞ2 u0 1:75ð1 εÞFgas u0 ¼ ∂z ε3 d p ε3 d p 2

ð9Þ 2

ð10Þ

The variables of interest in this system are the gas phase mole fraction (yi), sorbent loading of species i (qi, in mol kg1), temperature (T), total gas phase concentration (C), pressure (p), and interstitial velocity (u). Definitions of the other symbols used in eqs 610 can be found in the Nomenclature section. Notice eq 10 refers to the superficial velocity u0, which is related to the interstitial velocity u by the equation u0 = εu. The above model equations were used to model the adsorption and desorption processes in a 5-stage cyclic operation: pressurization, adsorption, cocurrent rinse, countercurrent depressurization, and countercurrent desorption. These stages are detailed in the Supporting

Table 2. Parameters Used in Adsorption Model parameter ΔS

value 160 J mol1 K1

ε

0.4

dp

0.01 m

Fbed

800 kg m3

Cp,solid

1000 J kg1 K1

qsat CO2

9 mol kg1

kLDF

30 s1

dt L

3m 3.5 m

Information, but a few key parameters are repeated here. The cycle was configured so that about 93% of the CO2 was captured, leading to 90% overall capture for the IGCC plant. In addition, the countercurrent desorption step consisted of a pure steam stream (yH2O = 1) at the regeneration pressure (pregen) to desorb the CO2 until only 20% of the adsorbed CO2 remained. There are several operational parameters that can be varied in an effort to optimize the adsorption process. For example, if a high regeneration pressure (pregen) were selected, the CO2 product would be obtained at this higher pressure, decreasing the costs associated with its eventual compression for sequestration. However, a high pregen would also consume more process steam as a diluent for the regeneration of the sorbent bed. Similarly, specifying a 90% capture case could result in a more environmentally benign process, but may also result in a larger fraction of the product syngas ending up in the CO2 stream. The model parameters chosen for the sorbent bed are shown in Table 2. As was mentioned previously, the value of ΔS shown in Table 2 was taken as an average value of chemisorption of CO2.51 The values of ε, Cp,solid, and qsat CO2 were all chosen to represent a porous sorbent dispersed upon a solid support of moderately large heat capacity in order to minimize the temperature fluctuations due to adsorption and desorption. The maximum theoretical CO2 capacity for pure calcium oxide (a common sorbent) is 17.8 mol kg1, so dispersing this material upon an inert support lowers the theoretical maximum capacity accordingly. To simplify the model and to provide a lower bound of the time scale for mass transfer, the kLDF value was specified to be a near-equilibrium value of 30 s1. Depending on the parameters of the packed column and the sorbent particles, the true mass transfer coefficient may be several orders of magnitude smaller. This parameter, along with ε, Cp,solid, and qsat CO2, was varied within reasonable upper and lower bounds in order to explore the sensitivity of the model to the parameter values. These results will be discussed in the Results section. The size and dimensions of the adsorption column in all probability can significantly affect the performance of a real adsorption unit. These variables would likely have to be optimized along with the other parameters in order to yield the highest efficiency of the adsorption process. However, in an attempt to reduce the scale of the optimization problem, the varied parameters were limited to the pressure of regeneration (pregen), the standard-state adsorption enthalpy (ΔHads), and the inlet temperature of the syngas feed (Tfeed). The above equations and boundary conditions were then evaluated using a numerical integrator within MATLAB. Because we were interested in steady-state operation and we were not concerned with the transient effects of startup in the adsorption beds, we simulated a large number of cycles (150, in most cases) 11318



Figure 4. Sample asymptotic fit for average adsorption exit temperature.

Figure 5. Comparison of equilibrium bed capacity for adiabatic and isothermal cases.

to approach but not attain cyclic steady state. We then fit the trajectory of each output variable (e.g., the average exit temperature of adsorption) using a nonlinear optimization routine within MATLAB to estimate the cyclic steady-state behavior. A sample exponential fit is shown below in Figure 4. An interesting consequence of an adiabatic sorbent model is its effect on the CO2 capacity of the sorbent. Because the adsorption is exothermic, the bed temperature increases during the adsorption step, inhibiting further adsorption and decreasing the sorbent capacity. This effect is illustrated below in Figure 5. Figure 5 shows the equilibrium sorbent capacity as a function of the adsorption enthalpy, assuming yCO2 = 0.313. Because the temperature does not rise in the isothermal case, the maximum capacity is significantly higher. Therefore, in order to further investigate the effect of temperature variations in the bed, the pressure swing adsorption model was modified and simulated again using this isothermal case. We expect the true bed behavior to be somewhere in between these two extremes (although likely closer to the adiabatic limit due to practical issues regarding heat transfer in fixed-bed systems). However, by modeling both the adiabatic and isothermal limits we are able to effectively create upper and lower bounds for the temperature effects within the bed. To mitigate numerical instabilities that arose using this

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isothermal model, kLDF was reduced to 9 s1 for the isothermal case. However, this value is large enough to still be in the equilibrium limit (i.e., infinitely fast kinetics) in order to provide a reasonable “best case” for the bed performance. Additionally, the desorption step end criterion (detailed for the adiabatic case in the Supporting Information) was altered to 10% CO2 remaining on the bed in the isothermal case because the numerical stability of the problem did not allow us to satisfy both the 90% overall capture criterion and the original design parameter set at 20% CO2 remaining on the bed. The change to 10% remaining on the bed likely increases the amount of steam required during the desorption step (and therefore decreases the overall IGCC efficiency). However, the isothermal operation is expected to greatly decrease the amount of steam required in this desorption step. In particular, during adiabatic operation the desorption process is endothermic, and as the temperature lowers the amount of steam required rises because the CO2 is more stable in the adsorbed state at lower temperatures. By contrast, in the isothermal case the temperature does not decrease during the desorption step, allowing the steam requirement to stay at a relatively low value. Therefore, we expect the slight increase in steam required due to regeneration of the bed to 10% CO2 remaining to be small compared to this larger effect. Adsorption Model for CO2 SeparationRegeneration Using H2 Product. Although regenerating the bed using steam in the desorption step is an effective technique, it clearly decreases the amount of steam available for power generation. Therefore, a second cyclic pressure swing adsorption model was developed to investigate the effectiveness of using the H2 product as a purge gas in the desorption step. This method is similar to a Skarstrom cycle.52 A few cycle modifications were introduced in order to decrease the amount of H2 product lost to the CO2 stream, but the key difference in this cycle is the fact that the gas used to desorb the CO2 in the desorption step was not pure steam as before, but the H2 product exiting the column in the adsorption step. The full cycle description is available in the Supporting Information. The model equations in this H2 regeneration system are otherwise identical to those in the steam regeneration system. This system was also similarly modeled in both the adiabatic and isothermal limits to provide bounds on the temperature effect. Integration of Models with Aspen Plus. MATLAB programs performing simulations for membrane and sorbent separation processes were developed and integrated in Aspen Plus to predict their performance for CO2 capture in IGCC. A USER2 block in Aspen Plus linked to an Excel file was used to model customized high temperature CO2 separation processes. In the case of the membrane-based simulations, VBA code was developed to establish two-way communication between Excel and MATLAB. On the basis of the input operating conditions received from Aspen Plus into Excel, the MATLAB high-temperature membrane process model was executed, and the results were returned to Excel. In the case of the sorbent-based simulations, the total simulation time for the MATLAB sorbent model was too long to have the MATLAB model directly integrated within Aspen Plus. To overcome this problem, we tabulated output data for a variety of sorbent model parameters, detailed in Table 3. The explored parameter space for the H2 regeneration case was reduced compared to the steam regeneration case due to a decreased numerical robustness in the H2 regeneration model. However, the parameters chosen were those that yielded the most promising results in the steam regeneration case (see Results section), so we 11319



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Table 3. Tabulated Values in 5-Stage Cyclic Adsorption Systems tabulated values,

tabulated values,

model variable

steam regeneration

H2 regeneration

yCO2 ΔHads (kJ mol1)

0.1, 0.2, 0.313 60, 65, 70,

0.25, 0.313 65, 70, 75,

pregen (atm)

1, 2, 3

1

Tfeed (K)

480, 505

505

75, 80, 85

80, 85

anticipated that we were limiting the parameter space to those parameters with the most potential. The syngas inlet temperature (Tfeed), sorbent binding energy (ΔHads), and regeneration pressure (pregen) are all specified within the Aspen Plus flowsheet. The model then interpolates the tabulated data based on the inlet mole fraction of CO2 (yCO2) to determine the values of the output variables. These variables include the amount of steam needed for the rinse and desorption steps, the amount of H2 lost to the CO2 stream, the average temperatures of the fuel gas and CO2 streams, the outlet pressure of the H2 stream after the adsorption step, and an estimate of the working capacity of the sorbent, based on the cycle parameters 1 and qsat CO2 = 9 mol kg . This shortcut lookup table model was used as the Excel-contained user model to represent the pressure swing adsorption unit within the Aspen Plus flowsheet. This strategy of using purpose-built unit operation models for membranes and adsorption processes and integrating them into Aspen Plus flowsheet models of the entire IGCC process as USER2 models has proven to be an effective means of exploring the performance of new technology options.

’ RESULTS AND DISCUSSION Pd-Alloy Membranes. The main alternative to removing the CO2 from the syngas is to separate the H2 using a membrane. We consider in the idealized case that only H2 permeates through the membrane. Therefore, a Pd-alloy membrane configuration falls under the category of Figure 1d in which the H2 is obtained at low pressure and the syngas steam remains mixed with the CO2 stream. The efficiency benefits of this configuration due to the elevated temperatures are lessened compared to that of configurations where the steam is mixed with the H2; however, the elevated temperatures are still beneficial in this case because they result in higher H2 permeability. Figure 6 plots the trade-off of achieving a higher hydrogen recovery against increase in membrane area, and consequently rise in cost, for different pressure ratios across the membrane. The pressure ratio is defined as the total pressure of the retentate stream divided by the total pressure of the permeate stream. From a process engineering standpoint, a low pressure ratio provides several advantages. For example, the mechanical strength of the membrane does not need to be as high when the pressures of the retentate and permeate are closer in magnitude. Also, a higher-pressure permeate stream reduces the costs of recompressing the permeate before it is fed to the gas turbine. However, as shown in Figure 6, the cost of the membrane is much lower if the pressure ratio is larger. The capital cost required for a Pd-alloy membrane can be variable, depending on the fabrication technology used and the membrane thickness required, but recent estimates of PdAg alloy membrane costs have yielded an

Figure 6. Cost of membrane for various pressure ratios, feed to sweep ratio 5:1, thickness 3 μm, cost of $2500 per m2.

approximate value of $4400 per m2.53 Alternatively, the H2 membrane developed by Eltron Research and Development is being manufactured at less than $200 per ft2 (= $2200 per m2),54 and the U.S. Department of Energy has specified its 2015 target H2 membrane cost to be less than $100 per ft2 (= $1100 per m2).55 For the purposes of our analysis, therefore, we assumed an intermediate membrane cost of $2500 per m2. We recognize that the actual membrane capital cost may vary by a factor of 2 in either direction, but we felt that a value of $2500 per m2 would provide a reasonable middle ground. This value is also advantageous because previous techno-economic analyses have specified $2500 per m2 to be a target capital cost based on a low H2 permeance similar to the value used in this work.56 The cost of the membrane is also heavily influenced by the desired recovery of the H2 product. Over most of the range the membrane area increases slowly with higher hydrogen recovery, but for very high recoveries (>98%) there is a faster increase in the membrane area as the hydrogen flux becomes very low. It is worth noting that the low fluxes associated with high recovery suggest the potential for a hybrid system. In this potential arrangement, the membrane could be used for the bulk of the separation, and then the remaining separation would be accomplished via some alternative method. Because we were concerned with the potential viability of various stand-alone CO2 separation technologies, no attempt has been made to evaluate such a hybrid process in this work. Assuming negligible mass transfer limitations in the gas phase, the driving force across the membrane module can be increased by using nitrogen from the ASU as a sweep gas to lower the partial pressure of H2 on the permeate side. It can be seen from Figure 7 that having a feed to sweep ratio of at most 5:1 sufficiently brings down the membrane area and the associated capital cost of the membrane unit for pressure ratios of 5 and 10. At a pressure ratio of 2, the feed to sweep ratio should be at most 2.5. At high feed to sweep ratios for this pressure ratio the membrane capital cost cannot be calculated because the partial pressure of H2 on the permeate side becomes greater than that of the retentate side, rendering further separation impossible. The feed to sweep ratios chosen here do not result in the correct amount of N2 diluent for the gas turbine, however, and as a result the remainder of the N2 is sent directly to the gas turbine. Because all the diluent N2 from the ASU eventually needs to be 11320



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Table 4. IGCC Efficiency Comparison between Selexol and High Temperature H2 Membrane for CO2 Capture at Pressure Ratios of 5 and 2. a cold cleanup, H2 membrane, H2 membrane, power summary (MW)

Pd-23%Ag

5

2

feed to sweep ratio

4.6

2.7

total power generated

737.1

760.6

749.7

gas turbine steam turbine

464.4 264.5

466.5 284.0

466.5 273.2

auxiliary

8.2

10.1

10.0

187.1

202.8

175.2

N2 compression

34.8

43.6

39.6

CO2 compression

28.3

9.7

9.7 125.9

124.0

149.5

net power output

550.0

557.8

574.5

thermal power input thermal efficiency (HHV)

1688 32.6%

1754 31.8%

1749 32.9%

auxiliary

compressed to the gas turbine delivery pressure (either with the H2 as a sweep gas or as a direct diluent), it is beneficial to add it at the membrane stage itself as a sweep gas to decrease the required membrane area. However, because the sweep gas needs to be heated to the temperature of the membrane unit, using additional sweep gas will decrease the overall energy efficiency. From a process simulation standpoint, using a highly selective hydrogen membrane for gas separations loses the steam diluent present in the syngas to the retentate stream. The hot and high pressure retentate mixture consisting of CO2, steam, and a small amount of other gases is first cooled and water is condensed out from the stream. This heat is used to generate low pressure steam. For the purpose of our analysis, we have assumed that if the CO2 purity is 95%) and simultaneously achieve the target of 90% CO2 removal, it is necessary to maintain the permeate pressure at approximately 2 atm or lower (pressure ratio of 20) for a membrane with CO2/H2 selectivity of 100. However, conventional polymer hollow fibers withstand pressure drops of only about 20 bar. To get a higher CO2 capture at a lower pressure ratio, the membrane selectivity would need to be improved. As shown in Figure 11, in order to obtain 90% recovery of high purity CO2 at a pressure ratio of 10 (still a pressure drop of approximately 35 bar), the membrane should have a minimum selectivity of 250. Alternatively, the total pressure of the retentate stream could be lowered to 20 bar, allowing the membrane to achieve the desired performance at the original selectivity. If this were implemented, the retentate H2 would need to be recompressed to the gas turbine delivery pressure of 31.7 bar. Figure 12 plots the maximum amount of high purity CO2 that can be captured by membranes of varying selectivities under different pressure ratios. If the membrane selectivity is poor then it limits the amount of high-purity CO2 that can be recovered for sequestration. The results indicate that a minimum selectivity of about 100 is necessary for polymeric CO2 membranes

CO2 membrane,

CO2 membrane,

Selexol

H2O rejecting

H2O permeating

αCO2/H2

500

500

αCO2/H2O

500

0.01

pressure ratio

20

20


737.1

733.8

735.6

gas turbine

464.4

462.2

465.7

steam turbine

264.5

255.2

255.7

auxiliary

8.2

16.4

14.2

187.1

164.4

181.4 34.6

total power consumed

Figure 11. CO2 capture by membranes of varying selectivity at a pressure ratio of 20. The target CO2 purity is 95%.

cold cleanup,

N2 compression

34.8

15.2

CO2 compression

28.3

36.3

35.0

auxiliary

124.0

112.9

111.8

net power output

550.0

569.4

554.2

thermal power input

1688

1762

1740

thermal efficiency (HHV)

32.6%

32.3%

31.8%

operating at 15 bar permeate pressure for meeting the target of 90% CO2 capture. Table 6 shows the potential improvement in IGCC efficiency by using a CO2 membrane that assumes permselectivities reported in literature for low temperature could be demonstrated at higher temperature IGCC conditions. If the designed membrane is selective only toward CO2 and not permeable to steam in the syngas, then the simulations predict a slight potential loss of 0.3 percentage points in thermal efficiency (HHV) (i.e., about 1% decrease in net power output) of IGCC with 90% CO2 capture when operating at a favorable pressure ratio. This configuration is identical to the case shown in Figure 1c: the CO2 stream is produced at low pressure, and the steam partitions with the highpressure H2 stream. However, although we would expect the potential gains in efficiency to be significant with this configuration, several competing factors limit its effectiveness. On one hand, because the H2O does not partition into the CO2 stream, it functions as a diluent in the gas turbine and reduces the cost for N2 compression. On the other hand, the CO2 stream is produced at a lower pressure than in the Selexol case, which increases the cost for CO2 compression. In addition, because the selectivity of 11323



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Figure 13. HHV efficiency for IGCC with CCS for H2O-permeating and H2O-rejecting membranes as a function of selectivity. The pressure ratio in both cases is 20.

CO2 over H2 is not infinite, some H2 is lost to the permeate stream, reducing the total power output. The combination of all these effects actually leads to a predicted slight decrease in overall HHV efficiency relative to the base case. Furthermore, because most polymeric membranes at present show large permeability to steam (comparable to or greater than CO2 permeability), it is more reasonable to assume that a high temperature CO2 membrane would also allow steam to permeate to the low pressure side. This more realistic case corresponds to Figure 1e, and unsurprisingly the results suggest an even larger decrease in HHV efficiency of about 0.8 percentage points (i.e., about 23% decrease in net power output) of the IGCC plant with 90% CO2 capture. Note that in this case, one could condense the steam first, similar to the base case in Figure 1a, and operate the membrane at a somewhat lower temperature, without significantly changing the efficiency. This would also improve the membrane selectivity. Currently, even with a somewhat optimistic CO2/H2 selectivity of 500, neither a H2O-permeating nor a H2O-rejecting membrane results in an HHV efficiency greater than that of Selexol. We increased the selectivity in both cases in an attempt to identify a critical selectivity at which the overall HHV efficiency becomes greater than that of Selexol. We recognize that these values are estimates owing to the fact that Selexol is a wellestablished technology while the CO2 membrane is hypothetical. Nevertheless, this analysis is useful as a best guess to guide future synthesis efforts. The results are shown in Figure 13. The critical selectivity in the H2O-rejecting case is equal to approximately 1000. By contrast, the efficiency penalty in the H2O-permeating case is still too great; even at αCO2/H2 = 8000, where virtually no H2 permeates across the membrane, the overall efficiency is 0.2 percentage points lower than that of Selexol. This suggests that a potentially significant area of research would involve the development of CO2 permeable membranes that are impermeable to H2O. Figure 14a plots the IGCC thermal efficiency for different operating pressure ratios as a function of the amount of CO2 captured (H2O-permeating case). Operating at high permeate pressures means a lower compression load for captured CO2 and hence a higher IGCC efficiency. However high permeate pressure also implies a lower driving force for the CO2 flux leading to

Figure 14. IGCC HHV efficiency and associated capital expenditure for different permeate pressures as a function of CO2 capture level, using CO2 membranes with αCO2/H2 = 500, αCO2/H2O = 0.01.

higher membrane area and associated capital expenditure for achieving the same separation. The relationship between the carbon capture percentage and overall IGCC efficiency seems to be essentially linear for high pressure ratios, but at low pressure ratios the increased carbon capture percentage is accompanied by a dramatic decline. The lowest point of the decline occurs when the target purity spec of 95% is reached. In other words, if the CO2 capture level were higher than 80% for a pressure ratio of 5, for example (see Figure 14a), the purity of the CO2 stream would fall below the 95% limit. This occurs because the membrane area has dramatically increased in size at lower pressure ratios, allowing valuable species like H2 to permeate through the membrane along with the CO2, further decreasing the overall efficiency. This increase in membrane area can be further seen in Figure 14b, which shows the corresponding capital expenditure associated with different operating pressure ratios as a function of CO2 capture level. Higher CO2 capture implies larger membrane length and consequently higher capital expenditure. The cost of a polymeric membrane is significantly less than that of a Pd-alloy membrane, with the favorable characteristics of polymers often leading to a cost of about $10$30 per m2.58 Because the desired material for 11324



Figure 15. Capital cost of membrane unit with varying H2 permeability for a membrane thickness of 3 μm, pressure ratio of 40, and H2/CO2 selectivity of 40, assuming a cost of $50 per m2.

these polymeric membranes is still relatively unknown, we assumed a slightly higher cost of $50 per m2 in our analysis. Even with this conservative cost estimate, however, the capital cost for many membrane modules (plus sulfur removal) is still much lower than the $247 mil. required for the Selexol process,5 with the acknowledgment that these membrane capital cost estimates have a large degree of uncertainty associated with them. It can be seen that in order to achieve high purity 90% CO2 capture while simultaneously meeting the sequestration purity target for CO2 (>95%), the membrane module should be operated at a pressure ratio of 20 to get maximum gain in energy efficiency and to keep the capital cost well below that of Selexol. Such a membrane unit is estimated to have a capital cost of around $33 mil. and an overall IGCCCCS thermal efficiency of 31.8% (HHV). In the case of partial CO2 capture (70% capture), it is optimal to operate the membrane module at a lower pressure ratio of about 5. The pressure ratio of 5 cannot work for the 90% capture case, however, because the purity of the CO2 stream drops below the 95% target at around 80% capture. The cost of the membrane unit for partial capture is estimated to be $33 mil. with an IGCC thermal efficiency of 33.3% (HHV). Polymeric Membranes for H2 Separation. The polymer membrane model was used to simulate H2 separation from the syngas using a H2 selective polymer membrane. In order to efficiently separate the large amount of H2 present in the syngas it is essential to have a membrane with high permeability so as to achieve the separation within a reasonable membrane area. Figure 15 shows the estimated cost of the membrane unit to obtain a desired recovery of H2 from the syngas for H2 membranes as a function of their permeability. To achieve a high enough H2 recovery at a moderate cost for a 3 μm thick membrane, the permeability of H2 should be in excess of 2000 barrer. Alternately, improvements in the membrane polymer material need to be made to reduce the thickness of hollow fibers while maintaining the mechanical strength to withstand high pressures. Any reduction in membrane thickness would increase the H2 permeance by the same magnitude. At present hollow fibers are known to withstand a pressure drop of around 15 to 20 bar across the membrane. Figure 16 shows the maximum amount of CO2 captured using a H2 permeable membrane as a function of H2/CO2 selectivity. The calculations suggest that the membrane should have a H2/CO2

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Figure 16. CO2 capture with varying H2/CO2 selectivity and hydrogen recovery of 99%.

Figure 17. Upper bound for H2/CO2 separation with polymeric membranes along with recently reported exceptions. Reprinted with permission from ref 23. Copyright 2008 Elsevier.

selectivity of at least 20 to achieve a partial CO2 capture between 50%70% based on reasonable pressure ratios. This is higher than Robeson’s upper limit of selectivity for polymer membranes having permeability in the range of 1000 barrer. However, as illustrated in Figure 17, the high temperature PBI-based mixedmatrix (inorganic and polymer) membrane has been reported to exceed the Robeson upper bound by demonstrating a selectivity of 40 for H2 permeability in the range of 100 barrer. With this material, the membrane thickness is only about 3 μm which makes H2 permeance higher than other comparable polymer membranes. Therefore, the relatively low permeability of PBI is acceptable. The membrane selectivity is still too low to achieve 90% capture but with continued development it could be a good candidate for partial CO2 capture. Figure 18 shows the predicted IGCC thermal efficiency (HHV) with CO2 capture using a high temperature PBI based membrane. Even for a partial CO2 capture case (approximately 75% capture) the membrane provides a lower efficiency than the base case cleanup using the Selexol process, likely due to the large amount of H2 lost in the retentate CO2 stream. In addition, if a higher CO2 capture level is attempted by operating the reactor at a greater pressure ratio, then membrane operation becomes more inefficient and the efficiency drops even further below the base case. In order to reach higher capture levels while maintaining the same energy efficiency benefit, the membrane selectivity 11325



Figure 18. IGCC thermal efficiency (HHV) for different capture levels using H2 polymeric membrane. H2/CO2 selectivity of 40, H2 permeability of 100 barrer,25 thickness of 3 μm, and H2 recovery of 99%.

needs to be further improved to about 100 as predicted in Figure 16. We note that our results agree with those of Krishnan et al.25 in that they predict the use of H2-permeable polymer membranes to result in a lower efficiency than Selexol. It is important to note that for these polymeric H2 membrane calculations we assumed that the steam rapidly permeates through the membranes along with the H2. Therefore, as with the polymeric CO2 membrane calculations, we assumed a selectivity of H2 over H2O of much less than unity (αH2/H2O = 0.01). The steam and H2 from the syngas are obtained at a low pressure on the permeate side and then need to be compressed to the gas turbine delivery pressure. This corresponds to a separation case of Figure 1b with H2/H2O stream obtained at a low pressure. As discussed earlier, this configuration is actually a potentially favorable one from an efficiency standpoint; not only does the H2O partition with the H2 stream, but the CO2 stream is also produced at high pressure, reducing the CO2 compression costs. Therefore, if a suitable membrane could be developed with high enough H2/CO2 selectivity such that the purities of the resultant streams are acceptably high, the gains in efficiency could be significant. We should stress, however, that the pressure drop across the membrane should be low enough to avoid substantial recompression energy to bring the permeate to the gas turbine delivery pressure. If the pressure drop across the membrane is high, therefore, it might be favorable to operate the membrane unit at a lower temperature after condensing the steam as in Figure 1a to benefit from improved selectivity of H2 membranes at low temperatures. Higher H2 selectivity would achieve a higher level of CO2 capture, and the heat generated on cooling the syngas can be used to generate low pressure steam. Also, the cooled syngas feeding to the membrane unit would have a higher inlet concentration of H2 that would increase the driving force across the membrane leading to a lower membrane area for the same H2 recovery. Adsorbents for CO2 Separation. To find the properties of the optimal sorbent, the enthalpy of adsorption was varied to predict the amount of steam required for regenerating the bed for a 90% CO2 capture case. As mentioned in the previous sections, the entropy of CO2 adsorption was taken from literature51 to be a constant value of 160 J mol1 K1, based on an average value of different Group I and Group II metals.

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Steam Regeneration. The overall thermal efficiency of the cyclic process was generally determined by two factors: the amount of steam needed for the rinse and desorption steps, and the amount of H2 lost into the CO2 stream after the rinse step. In general, the total amount of steam required by the process increased as |ΔHads| or as the sweep gas pressure during the desorption step (pregen) became larger in magnitude, as shown in Figure 19. Interestingly, the steam requirement also increased at |ΔHads| = 60 kJ mol1 in the isothermal case. The contours for the adiabatic case, |ΔHads| = 60 kJ mol1, Tfeed = 505 K, and pregen = 1 atm are not plotted because it was not possible to achieve 90% CO2 capture in the adsorbent bed with those parameters in the given column geometry. The fraction of H2 lost to the CO2 stream (see Figure 20) also tended to increase with |ΔHads| and pregen, but only in the adiabatic case. Therefore, this increase is likely due to temperature effects within the bed. The amount of H2 lost is likely related to the dispersal of the CO2 concentration front during the adsorption step. If the concentration front is sharp, meaning that a large fraction of CO2 is near the outlet of the bed, then the rinse step will be very short in duration, and if this rinse time is shorter than the residence time in the adsorption bed, then some of the H2 will not be displaced into the product stream. This H2 remaining in the bed will likely be wasted as a component of the CO2 sequestration stream. As Figure 20 shows, this fraction of H2 lost tends to hit a minimum at low values of |ΔHads|, although this value increases slightly at |ΔHads| = 60 kJ mol1. In all likelihood, the integration end criteria for each step of the PSA cycle (detailed in the Supporting Information) could be optimized for each value of ΔHads in order to minimize the amount of H2 lost to the CO2 stream. Even if this were undertaken, however, the high values of |ΔHads| would still be at a disadvantage due to the increased amount of sweep steam required. The working capacity at different operating conditions in both the adiabatic and isothermal cases was determined by calculating the total amount of CO2 adsorbed during each cycle and dividing it by the mass of sorbent in the bed. A plot of the calculated working capacity as a function of ΔHads is shown in Figure 21 for a regeneration pressure of 1 atm and a saturated capacity of 9 mol kg1. The computed numbers are in the usual range. For example, modified CaO is reported to have a working capacity of 6 mol kg1, while hydrotalcite is reported to have a working capacity of 0.8 mol kg1.30,59 Figure 21 proves the claim suggested by Figure 5 that temperature effects within the bed greatly affect the working capacity. One might expect that the working capacity should increase as ΔHads becomes larger in magnitude; larger values of |ΔHads| translate to more negative values of ΔGads, causing the CO2 to bind more strongly to the sorbent. This is exactly the behavior that is observed in an isothermal bed. However, although the initial capacity of the sorbent markedly increases with |ΔHads| in an adiabatic bed, the working capacity decreases for large |ΔHads|. A large binding energy raises the temperature of the bed more upon adsorption, decreasing the equilibrium amount adsorbed. It is also interesting to note that the largest working capacity predicted by the adiabatic model is a bit lower than that reported by Hufton et al. for the SEWGS process;59 perhaps that process is not perfectly adiabatic, or the |Sads| for hydrotalcite is a bit smaller than the 160 J mol1 K1 assumed here. It is a great advantage to employ some sort of heat transfer technique to operate the column closer to the isothermal limit— this not only dramatically improves the working capacity, it also improves the thermal efficency. 11326



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Figure 19. Sweep steam required as a function of pregen and ΔHads for an inlet temperature of 505 K and yCO2 = 0.313 for both the adiabatic and isothermal cases. Each contour represents the ratio of the moles of H2O needed per mole of CO2 removed. The color scale is constant between the two figures, but the steam to CO2 ratio reaches as high as 8 in the isothermal case.

Figure 20. Unburned H2 as a function of pregen and ΔHads in the adiabatic model at two adsorption temperatures, 480 and 505 K, and yCO2 = 0.313. Each contour represents the fraction of total H2 produced that is lost to the CO2 product stream.

The HHV thermal efficiency calculated for each ΔHads and pregen in the adiabatic case is shown in Figure 22. In both the Tfeed = 480 K and Tfeed = 505 K cases the efficiency tends to decrease with increasing |ΔHads| or pregen. At low values of |ΔHads|, however, the trends become less predictable. For Tfeed = 480 K, the overall efficiency is greatest at the lowest value of |ΔHads| (60 kJ mol1), but the maximum efficiency actually occurs at pregen = 2 atm. This suggests that at these low values of |ΔHads| the benefit derived from reduced CO2 compression costs at a higher pregen actually offsets the costs associated with a greater steam requirement. For Tfeed = 505 K, however, the maximum efficiency is actually achieved at |ΔHads| = 65 kJ mol1. This is likely due to the slight increase in H2 lost to the product stream at |ΔHads| = 60 kJ mol1, shown in Figure 20b, coupled with the increase in steam required for the desorption step, shown in Figure 19a.

Although the HHV efficiency is larger at |ΔHads| = 60 kJ mol1 for Tfeed = 480 K, we suggest that the best value for both temperatures is actually |ΔHads| = 65 kJ mol1. First of all, as |ΔHads| decreases it becomes increasingly unlikely that our assumption of ΔSads = 160 J mol1 K1 is valid, since a weaker enthalpy of adsorption likely implies a greater amount of surface entropy, leading to a smaller value of |ΔSads|. If a smaller value of |ΔSads| were assumed for the |ΔHads| = 60 kJ mol1 case, the overall HHV efficiency would decrease accordingly. This is illustrated in Figure 23, in which the parameters for the |ΔHads| = 60 kJ mol1 cases are calculated assuming ΔSads = 100 J mol1 K1. Even if the ΔSads = 160 J mol1 K1 assumption were valid at all values of |ΔHads|, a target value of |ΔHads| = 60 kJ mol1 is still not ideal from an economic perspective. As shown in Figure 21, the working capacity of the bed actually decreases for |ΔHads| = 60 kJ mol1 by over 25%. This lower working 11327


Industrial & Engineering Chemistry Research capacity implies a CO2 sorbent bed (and pressurized vessel to contain it) that is at least 25% larger, which may not be worthwhile for the marginal gains in efficiency. The HHV efficiency was also calculated for the isothermal case (assuming ΔSads = 160 J mol1 K1 for all values of |ΔHads|). The results are shown in Figure 24. Although the trend of efficiency decreasing with increasing |ΔHads| continues with the isothermal case, the efficiency is much less dependent on pregen. In fact, the maximum HHV efficiency predicted by this model actually occurs at |ΔHads| = 65 kJ mol1 and pregen = 3 atm. The range of ΔHads plotted in this isothermal case is slightly smaller than that of the adiabatic case because the amount of steam required increases dramatically at high |ΔHads| (see Figure 19b). The amount of steam required actually increases so much that there is not enough steam generated in the HRSG section to fulfill the regeneration requirement. As a result, those infeasible values of ΔHads are not plotted here. A breakdown of the simulation estimate of the IGCC plant efficiency using the optimal conditions for both the adiabatic and

Figure 21. Working capacity as a function of ΔHads at a feed temperature of 505 K, a regeneration pressure of 1 atm, and yCO2 = 0.313 for both the adiabatic and isothermal cases.

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isothermal cases is shown in Table 7. This separation process can be categorized under Figure 1c where the H2/H2O stream is obtained at a high pressure with additional steam required for CO2 capture. Therefore, the potential gain in efficiency is larger because the H2O partitions with the H2 stream. This net gain is partially offset because the total power generated actually decreases with this configuration when compared to the base case, since extra steam is diverted from the steam cycle to the sorbent bed for regeneration. Nonetheless, the adsorbent process results in a favorable change in the HHV efficiency, shown in Table 7: an essentially identical HHV efficiency in the adiabatic case, and an increase of 0.6 percentage points in HHV thermal efficiency in the isothermal case. This improvement is due to both the reduction in N2 compression and the removal of the auxiliary power loads that are normally present in the Selexol process. Several of the parameters chosen for the adsorption model could potentially have a significant effect on the HHV thermal efficiency; for example, a lower heat capacity for the solid would lead to increased temperature fluctuations during the adsorption and desorption cycles, potentially affecting the overall working capacity and the exit temperatures of the process gas streams. In order to attempt to quantify the effect of this and other parameters, we performed a brief sensitivity study of the effect of changes in void fraction (ε), solid heat capacity (Cp,solid), saturation capacity (qsat), and mass transfer coefficient (kLDF) on the adiabatic sorbent with the optimal parameters shown in Table 7. The upper and lower bounds for each parameter varied depending on the amount of uncertainty associated with each one; for example, although it is reasonable to assume that ε is known within 10%, kLDF could easily vary by an order of magnitude. The upper and lower bounds of each parameter are summarized in Table 8, and the corresponding efficiency results are in Figure 25. These results show that the effect of changes in each parameter is usually bounded by roughly 0.5 percentage points in HHV thermal efficiency. This indicates that small changes to these parameters can be significant, but usually not critical in terms of the overall estimate of the HHV thermal efficiency. It is interesting to note that the parameter qsat is not monotonic in this data range. This results from a competing effect of increased steam

Figure 22. HHV thermal efficiency of IGCCCCS system using chemisorption of CO2 for carbon capture as a function of pregen and ΔHads at two different syngas feed temperatures (adiabatic case). Regeneration is accomplished using steam at Tsteam = Tinlet (480 or 505 K). Each contour represents the overall HHV thermal efficiency of the process (%). 11328



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Figure 23. HHV thermal efficiency of IGCCCCS system using chemisorption of CO2 for carbon capture as a function of pregen and ΔHads at two different syngas feed temperatures (adiabatic case). Regeneration is accomplished using steam at Tsteam = Tinlet (480 or 505 K), and ΔSads is assumed to be 100 J mol1 K1 when |ΔHads| = 60 kJ mol1. Each contour represents the overall HHV thermal efficiency of the process (%).

Figure 24. HHV thermal efficiency of IGCC system using chemisorption of CO2 for carbon capture as a function of pregen and ΔHads at two different syngas feed temperatures (isothermal case). Regeneration is accomplished using steam at Tsteam = Tinlet (480 or 505 K). Each contour represents the overall HHV thermal efficiency of the process (%).

requirement for higher values of qsat but a slight increase in H2 lost to the CO2 stream at lower values of qsat. As before, an optimization of the bed geometry could likely alleviate the loss of H2 product, but because the effect on the overall HHV efficiency is small, such an optimization was not performed here. H2 Regeneration. Like the steam regeneration case, the HHV efficiency of the IGCC plant when using H2 regeneration was determined by the amount of steam required by the process (here, just in the rinse step) and the amount of H2 lost to the CO2 product stream. On the one hand, because there is no steam used in the desorption step, we would expect the HHV efficiency to increase. However, in order to conform to the 90% CO2 capture constraint, more H2 was lost to the CO2 product stream than in the steam regeneration case. Figure 26 shows the amount of H2 lost to the CO2 product stream at yCO2 = 0.313. This fraction of unburned H2 could likely be reduced through further optimization of the pressure swing adsorption cycle for

each value of ΔHads; however, it is unlikely to be completely eliminated because the desorption step needs to be long enough in duration for the H2 sweep gas to displace much of the CO2 from the vapor phase in the adsorption column. Because the vapor phase in the column also includes some H2 gas at the beginning of the desorption step, invariably some of this H2 will be displaced into the CO2 stream as well. Unfortunately, this lost H2 has a significant impact on the HHV efficiency of the IGCC process, as illustrated in Figure 27. Clearly, the overall IGCC efficiency shown in Figure 27 is inversely related to the fraction of H2 lost to the product stream in Figure 26. The isothermal case tends to produce higher efficiencies than the adiabatic case, likely due to the desorption step being more efficient (due to the absence of a decrease in temperature), and therefore resulting in less H2 lost to the CO2 stream. A summary of the optimal adiabatic and isothermal cases is shown in Table 9. 11329



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Table 7. Optimal Sorbent Performance for Adiabatic and Isothermal Cases optimal sorbent cold cleanup,

adiabatic

isothermal

Selexol

case

case

ΔHads

65 kJ mol1

65 kJ mol1

pregen Tinlet

1 atm 505 K

3 atm 480 K 723.9

power summary (MW)


737.1

723.1

gas turbine

464.4

461.3

460.6

steam turbine

264.5

239.4

241.9

auxiliary

8.2

22.4

21.4

187.1

162.2

147.5

N2 compression

34.8

10.1

5.8

CO2 compression auxiliary

28.3 124.0

41.9 110.2

30.0 111.7


net power output

550.0

560.9

576.4

thermal power input

1688

1716

1734


32.6%

32.7%

33.2%

Figure 25. Sensitivity analysis of perturbing ε, Cp,solid, qsat, and kLDF from their base case values of ε = 0.4, Cp,solid = 1000 J kg1 K1, qsat = 9 mol kg1, and kLDF = 30 s1.

The SO2 that is generated in eq 1 is then converted to elemental sulfur via the direct sulfur recovery process (DSRP), shown below in eq 2. SO2 þ 2H2 f S þ 2H2 O

Table 8. Parameter Values Investigated in Sensitivity Analysis parameter

lower bound

base case

upper bound

ε

0.36

0.40

0.44

Cp,solid

800

1000

1200

qsat

6

9

12

kLDF

3

30

100

The H2 regeneration case is therefore more or less equivalent to the Selexol base case in energy efficiency, especially in the isothermal case where the amount of H2 lost to the CO2 stream is less than 1%. One interesting thing to note, however, is that the trade-off between H2O required for regeneration and regeneration pressure that existed in the steam regeneration case does not exist here. Namely, if the adsorption column could be adequately designed to minimize the amount of H2 lost to the CO2 stream and the column could be regenerated at pressures greater than 1 atm, then the HHV efficiency would increase. A hypothetical example of this is shown in the rightmost column of Table 9. Here pregen is only raised to 2 atm, but the amount of H2 lost to the CO2 stream is maintained at the same level as the optimal isothermal case. In this hypothetical case, the HHV efficiency increases by 0.5 percentage points. It is therefore most advantageous with regard to HHV efficiency to design the adsorption column to be regenerated at as high a pressure as possible while keeping the amount of H2 lost to the CO2 stream less than 1%. A Note on Warm Sulfur Removal. Throughout this work, our evaluation of the various warm CO2 removal technologies has been based upon the sulfur removal technology being developed by RTI and Eastman Chemical. The pertinent reactions for the adsorption and regeneration processes are H2 S þ ZnO h ZnS þ H2 O ZnS þ

3 O2 f ZnO þ SO2 2

ð11Þ ð1Þ

ð2Þ

From an economic perspective, it may be worthwhile to produce elemental sulfur in this manner, since sulfur is a salable byproduct. From an efficiency standpoint, however, the process is losing 2 mols of H2 for every mole of sulfur within the coal, decreasing the power output of the gas turbine. Because we are using a relatively high-sulfur coal (approximately 3 wt %, as shown in the Supporting Information), this amount of H2 is significant. Table 10 shows the flow rates of hydrogen exiting the water gas shift reactor and entering the gas turbine for two different cases. The first column shows the flow rates for the base case Selexol flowsheet; the second column shows the flow rates for the isothermal CO2 adsorption (with steam regeneration) case, |ΔHads| = 65 kJ mol1 and pregen = 1 atm. The latter case was selected to be a suitable representative “warm cleanup” case due to the fact that no H2 is predicted to be lost in the CO2 product stream. Interestingly, even though the H2 flow rate entering the gas turbine is approximately the same in each case, the flow rate exiting the WGS unit is approximately 2% higher in the adsorbent case. This decreases the potential HHV efficiency because more coal is needed (i.e., greater thermal input) to produce the same amount of hydrogen and achieve the same amount of power output. To overcome this problem, one potential solution is to replace the RTI DSRP step with a simple wet flue gas desulfurization (FGD) step. The pertinent reaction for the FGD process is SO2 þ

1 O2 þ CaCO3 2

þ 2H2 O f CaSO4 3 2H2 O þ CO2

ð12Þ

The product generated from this FGD reaction is gypsum, which has a small market value due to its use in the manufacture of concrete and drywall. The FGD process, however, is not without its own limitations. Specifically, this process introduces an additional raw material cost in the limestone sorbent (CaCO3). 11330



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Figure 26. Unburned H2 as a function of ΔHads in both the adiabatic and isothermal models at Tfeed = 505 K, pregen = 1 atm, and yCO2 = 0.313.

Figure 27. IGCC HHV efficiency for adiabatic and isothermal cases with H2 regeneration (Tfeed = 505 K and pregen = 1 atm).

Table 9. Optimal Sorbent Performance for Adiabatic and Isothermal Cases with H2 Regeneration. The Asterisk (/) Refers to a Hypothetical Case in Which the Conditions Are the Same as the Isothermal Case with pregen = 2 atm optimal sorbent power summary (MW)

cold cleanup, Selexol

ΔHads pregen

adiabatic case

isothermal case

isothermal case*

70 kJ mol1 1 atm

65 kJ mol1 1 atm

65 kJ mol1 2 atm


737.1

734.4

735.7

737.6

gas turbine

464.4

461.2

461.3

461.3

steam turbine

264.5

253.0

255.5

257.4

auxiliary

8.2

20.2

18.9

18.9 156.7

187.1

166.6

164.8

N2 compression

-34.8

9.2

9.8

9.8

CO2 compression auxiliary

28.3 124.0

45.2 112.2

43.3 111.7

35.1 111.8

net power output

550.0

567.8

570.9

580.9

thermal power input

1688

1750

1743

1743


32.6%

32.4%

32.8%

33.3%


11331



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Because the price of gypsum is highly variable, it is often estimated at $0 per ton for conservative economic analyses. The limestone, meanwhile, can be estimated to cost $15 per ton.60 On the basis of the flow rate of sulfur entering the FGD unit, this translates to an additional operating cost of approximately 0.05 cents per kWh, not counting transportation costs. Assuming the additional operating cost is acceptable, the FGD process still presents an additional technical challenge in that it produces more CO2. To maintain an overall CO2 capture rate of 90%, this CO2 must be accounted for in some manner. It is worth noting that alternative warm sulfur capture technologies, such as the production of sulfuric acid, do not produce CO2 as a byproduct and may as a result be more promising than the FGD process. The FGD process is useful as an illustration of a relatively simple alternative to the DSRP process, however, and a result will be the only process described in detail here. We Table 10. H2 Flow Rates in Both the Selexol Base Case and the Isothermal Co2 Adsorbent Case H2 flow rate (kmol hr )

Selexol

mol m3

Cp,gas

gas phase heat capacity

J mol1 K1

Cp,solid dp

solid phase heat capacity sorbent particle diameter

J kg1 K1 m

dt

adsorption vessel diameter

m

ΔHads

enthalpy of adsorption

J mol1

J

molar flux

mol m2 s1 s1

warm cleanup,

m

isothermal adsorbent

l n

membrane thickness pressure exponent

m

16200

scenario 1 scenario 2 scenario 3 scenario 4

ASU compressor (MW)

75.5

74.8

70.4

70.4

CO2 compression (MW) CO2 purity

42.3 99%

42.2 99%

50.2 89%

41.4 99%

net power output (MW)

567.4

563.0

561.3

570.6

thermal power input (MW)

1732

1694

1694

1693


32.8%

33.2%

33.1%

33.7%

Table 12. IGCCCCS Efficiency Improvement for Promising CO2-Separation Technologies Identified in This Work Using FGD Process isothermal adsorbent

membrane (H2O-rejecting (ΔHads = 65 kJ mol1, αCO2/H2 = 500,

ratio = 2) pressure ratio = 20)

pregen = 3 atm, Tfeed = 480 K)

p

pressure

Pa

pregen

sweep gas pressure during

Pa

P Q_

permeability heat generation

W

qi

sorbent loading of species i

mol kg1

q*i qsat i

sorbent loading of species i at equilibrium saturation capacity of species i

mol kg1 mol kg1

R

universal gas constant

J mol1 K1

ΔSads

entropy of adsorption

J mol1 K1

T

temperature

K

t

time

s

u

interstitial gas-phase velocity

m s1

u0

superficial gas-phase velocity

m s1

yi yi

bulk gas phase mole fraction of species i local permeate mole fraction of species i

z

axial direction length variable

sorbent regeneration

Table 11. Results Summary for Sulfur Capture Scenarios

(pressure

concentration

axial length of membrane or sorbent bed

15800

(HHV)

C

linear driving force rate constant

15800

thermal efficiency

units

L

15700

CO2 membrane

description

equilibrium constant

exiting gasifier

Pd-alloy

symbol

Keq

entering gas turbine

parameter

Table 14

kLDF

cold cleanup,

1

envisioned four scenarios in which the additional CO2 separation could occur. Scenario 1: Isothermal adsorbent case with RTI sulfur removal, O2-fired ZnS oxidation, and DSRP for sulfur recovery (no FGD) Scenario 2: Isothermal adsorbent case with RTI sulfur removal, O2-fired ZnS oxidation, and O2-fed FGD for sulfur

mol m1 Pan s1

m

Greek symbols α

selectivity

ε

void fraction

sulfur removal via DSRP

32.9%

32.3%

33.2%

μm

viscosity

Pa s

sulfur removal via FGD

33.7%

32.6%

34.1%

F

density

kg m3

Table 13. Summary of HHV Efficiencies and Uncertainties for Most Promising IGCCCCS Technologies. a Selexol HHV efficiency est. uncertainty

32.6%

Pd-alloy membrane

CO2 membrane (H2O-rejecting,

isothermal adsorbent (ΔHads = 65 kJ mol1,

(pressure ratio = 2)

αCO2/H2 = 500, pressure ratio = 20)

pregen = 3 atm, Tfeed = 480 K)

32.9%

32.3%

33.2%

model specific

0.5%

steam optimization

1.7%

1.7%

1.7%

global integration

1.6%

1.6%

1.6%

1.6%

summary

32.6 ( 3.8%

32.9 ( 3.3%

32.3 ( 3.3%

33.2 ( 3.8%

0.5% 1.7%

a

H2 polymer membranes are not listed because they were unable to achieve 90% CO2 capture. The model specific uncertainty for Selexol (due to uncertainty in the vaporliquid equilibrium data) is estimated to be 0.5%, and the model specific uncertainty for adsorbents (due to uncertainty in model parameters) is estimated to be 0.5% from the sensitivity analysis. 11332


Industrial & Engineering Chemistry Research capture. The CO2-containing exhaust stream from the FGD unit is fed directly into the CO2 compression block in the Aspen Plus flowsheet to maintain 90% capture Scenario 3: Isothermal adsorbent case with RTI sulfur removal, air-fired ZnS oxidation, and air-fed FGD for sulfur capture. The CO 2 -containing exhaust stream from the FGD unit is fed directly into the CO 2 compression block in the Aspen Plus flowsheet to maintain 90% capture Scenario 4: Isothermal adsorbent case with RTI sulfur removal, air-fired ZnS oxidation, and air-fed FGD for sulfur capture. The CO2-containing exhaust stream from the FGD unit is vented to the atmosphere. To compensate, the CO2 adsorption unit is modified to capture additional CO2 in the Aspen Plus flowsheet to maintain 90% capture. Each scenario was then tested within the Aspen Plus framework in order to evaluate its overall IGCCCCS efficiency. The results of each scenario are shown in Table 11. Unsurprisingly, there is a slight decrease in ASU compressor power in the air-fed FGD scenarios (scenarios 3 and 4) due to the reduced need for high-purity O2. Of the 4 scenarios, only scenario 3 is not feasiblenot only are the CO2 compression costs significantly higher (due to the presence of N2 in the CO2 stream), but also the purity of the CO2 stream is well below the target purity of 95%. If air-fed ZnS oxidation and FGD processes are used in conjunction with additional CO2 capture, however (see scenario 4), the potential gain in efficiency is as much as 1.1 percentage point HHV! To further illustrate this point, Table 12 depicts the gains in efficiency for the most promising technologies surveyed in this work when an FGD unit is employed instead of the DSRP process. Both the H2-permeable Pd-alloy membrane and the isothermal adsorbent show similar gains in HHV efficiency. The gains from the CO2-permeable membrane are reduced due to an increase in the amount of H2 permeating through the membrane when the CO2 capture percentage is increased. On the basis of the favorable results of the two most promising CO2 separation technologies, however, a careful evaluation of the trade-off between the additional operating cost of the FGD unit and the gains in efficiency need to be performed in order to select the proper sulfur recovery technique.

’ CONCLUSIONS Using our computational approach we have evaluated the suitability of membrane- and sorbent-based syngas cleanup processes. We have arrived at desired operating conditions for these processes and desired properties of sorbent and membrane materials. The efficiencies of each technology at its desired operating conditions are summarized in Table 13. In Table 13, the uncertainties due to steam optimization and global integration were estimated based on the improvements achieved by Bhattacharyya et al. and Botros and Brisson, respectively. We acknowledge that due to the limitations of our numerical models, a lack of optimization of the overall IGCC flowsheet, and some uncertainties surrounding many of the model parameters, the absolute HHV efficiencies of the IGCC processes calculated in this work may be inaccurate by even several percentage points HHV. However, because many of these limitations are the same in each model studied, we feel that the efficiency differences between the different technologies captured within this study are correct.

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Some of the CO2 capture technologies investigated here show promise. Prior reports suggest that conducting the separations at high temperature provides a large HHV efficiency advantage. However, we find that conducting the separations at high temperature is only advantageous for CO2 sorbents and potentially H2permeating Pd-alloy membranes, and to achieve an efficiency significantly higher than Selexol, a different sulfur handling technique is required. In addition, the gains in efficiency due to the cleanup occurring at elevated temperatures only arise in a narrow window of operating parameters. Of the technologies surveyed, only H2O-impermeable CO2 polymeric membranes, H2O-permeable H2 polymeric membranes, and CO2 adsorbents fall into one of the “favorable” categories shown in Figure 1b and Figure 1c for cleanup at elevated temperatures. Of these, the membranes with the proper permeabilities and selectivities for significant gains in efficiency have not yet been demonstrated, and the CO2 adsorbents only offer a gain in efficiency over the Selexol process for certain combinations of ΔHads and pregen. In terms of development, Pd-alloy based composite H2 membranes are the closest to implementation in a high temperature IGCC process, but they only offer a potential gain in efficiency over the Selexol process (estimated to be 32.6% HHV by Field and Brasington34) if they are operated at a pressure ratio of 2 or lower. The estimated capital cost for such a unit, assuming a cost of $2500 per m2, is high, although still slightly lower than the Selexol capital cost. In this regard the Eltron H2 membrane shows potential due to its relatively lower cost. At higher pressure ratios, however, Pd-alloy membranes do not offer any savings in efficiency over Selexol due to the lost heating value of the CH4 and CO in the syngas stream. It also should be noted that purity of the CO2 stream of 93% is below the target sequestration purity of 95%, so additional processing would likely be required to bring the stream up to specifications. In addition, further work is needed to improve and verify their stability and performance in the presence of impurities like sulfur, CO, and Hg present in a coal gasification environment. Further study could also include process simulations of hybrid technologies in which Pd-alloy membranes recover a fraction of H2, and then an alternative technology recovers the remainder. This could allow the unburned carbon species like CO and CH4 to remain in the fuel gas stream, which would lead to higher overall efficiencies. At their current level of development, polymeric H2 membranes are not promising candidates for CO2 capture at elevated temperatures, despite the reduction in capital cost. The estimated HHV efficiency of these membranes is lower than that of Selexol, even in the partial capture case (the estimated IGCCCCS HHV thermal efficiency of 30.9% for 74% CO2 capture). The main impediments to their success seem to be the H2/CO2 selectivities, especially at high temperature, which are currently still too low for 90% capture. Recent research on PBI membranes shows promising advancement toward their successful application at the temperatures needed for implementation in an IGCC plant. A target selectivity of αH2/CO2 = 100 was estimated to make H2 polymeric membrane separation efficient for 90% CO2 capture. Similarly, CO2-permeable polymer membranes are also ineffective for warm-temperature CO2 separations. On the basis of our analysis, the CO2/H2 selectivities in current CO2-permeable membranes are still much too low. Simulations show that a CO2/H2 membrane selectivity of 100 is necessary for 90% 11333


Industrial & Engineering Chemistry Research capture of high purity CO2, assuming the membrane can withstand a pressure ratio of 20. From an efficiency standpoint, however, the selectivity needs to be even higher in order to greatly reduce the amount of H2 lost to the CO2 product stream. Unfortunately, even a selectivity of 500 is not large enough to make the CO2 membrane separation process more efficient than Selexol. In addition, at their current development high selectivity CO2 membranes have been demonstrated to perform only at low temperatures with high relative humidity conditions, and these membranes are permeated by H2O. The loss of this H2O from the H2 stream also leads to a large decrease in efficiency. As a result, membranes which pass CO2 but reject H2 and H2O at temperatures greater than 500 K with high CO2/H2 selectivities would be most valuable, but to our knowledge no materials with this property have been identified yet. CO2 sorbents have shown the most promise of all the technologies surveyed in this work. Various sorbents have been reported in the literature to have a potential for CO2 capture but very few have shown the high capacity needed to capture large amounts of CO2 with the easy regeneration required to make their use energetically efficient. A major challenge is reducing the temperature variations within the adsorption column, as evidenced by both the increased HHV efficiency and sorbent working capacity during isothermal operation. If a better sorbent material with more optimal properties is identified, it could provide a promising solution for high temperature CO2 capture in the near future. A standard state enthalpy change of adsorption of 65 kJ mol1 (resulting in a standard Gibbs free energy change of approximately 17 kJ mol1) and regeneration pressure of 1 atm was found to yield roughly the same HHV efficiency as Selexol (a gain of 0.1 percentage points) in the adiabatic case. During isothermal operation this efficiency could be raised by an additional 0.6 percentage points, making it a promising alternative to Selexol. If the regeneration were performed using H2 instead of steam, a major process challenge is reducing the amount of H2 lost to the CO2 product stream. However, if a proper adsorption cycle could be developed with regeneration occurring above 1 atm, the gains in efficiency could be significant due to the savings in CO2 compression costs. Further research should be directed toward synthesizing candidate materials with this binding energy and optimizing the adsorptiondesorption cycle in order to improve the working capacity. Testing is required to verify the new sorbents are durable through many adsorptiondesorption cycles and that they are not degraded by other components of the IGCC syngas.

’ NOMENCLATURE Symbols along with their definition and units are shown in Table 14. ’ ASSOCIATED CONTENT

bS

Supporting Information. Information about the process conditions assumed in the base case model and more detailed information about the mathematical equations used for the membrane and adsorbent models; Aspen Plus files and detailed documentation for H2-permeable membranes (Pd-alloy and polymeric), CO2-permeable membranes, and CO2 adsorbents (adiabatic and isothermal models for both steam regeneration and H2 regeneration), as well all necessary Excel and MATLAB

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files. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected].

’ ACKNOWLEDGMENT The authors thank Randall Field and Robert Brasington for their insight and support. We also thank BP for funding this research and AspenTech for the use of Aspen Plus in the execution of this research. ’ REFERENCES (1) Katzer, J.; Ansolabehere, S.; Beer, J.; Deutch, J.; Ellerman, A.; Friedmann, S.; Herzog, H.; Jacoby, H.; Joskow, P.; McRae, G.; Lester, R.; Moniz, E.; Steinfeld, E. The Future of Coal; Massachusetts Institute of Technology: Cambridge, MA, 2007. (2) International Energy Outlook; Energy Information Administration: Washington, DC, 2010; DOE/EIA-0484. (3) Rubin, E.; Chen, C.; Rao, A. Cost and Performance of Fossil Fuel Power Plants with CO2 Capture and Storage. Energy Policy 2007, 35, 4444–4454. (4) Cost and Performance Baseline for Fossil Energy Plants: Bituminous Coal and Natural Gas to Electricity Final Report; U.S. Department of Energy, Office of Fossil Energy: Washington, DC, 2007; NETL, DOE/ NETL-2007/1281. (5) Cost and Performance Baseline for Fossil Energy Plants: Bituminous Coal and Natural Gas to Electricity Final Report; U.S. Department of Energy, Office of Fossil Energy: Washington, DC, 2010; NETL, DOE/ NETL-2007/1397. (6) Schlather, J.; Turk, B. Comparison of a New Warm-Gas Desulfurization Process versus Traditional Scrubbers for a Commercial IGCC Power Plant. Gasification Technologies Conference, San Francisco, CA, 2007. (7) Current and Future Technologies for Gasification-Based Power Generation, Vol. 2: A Pathway Study Focused on Carbon Capture Advanced Power Systems R&D Using Bituminous Coal; U.S. Department of Energy, Office of Fossil Energy: Washington, DC, 2009; NETL, DOE/NETL2009/1389. (8) Peters, T.; Tucho, W.; Ramachandran, A.; Stange, M.; Walmsley, J.; Holmestad, R.; Borg, A.; Bredesen, R. Thin Pd23% Ag/Stainless Steel Composite Membranes: Long-Term Stability, Life-Time Estimation and Post-Process Characterisation. J. Membr. Sci. 2009, 326, 572–581. (9) Nam, S.; Lee, S.; Lee, K. Preparation of a Palladium Alloy Composite Membrane Supported in a Porous Stainless Steel by Vacuum Electrodeposition. J. Membr. Sci. 1999, 153, 163–173. (10) Roa, F.; Way, J.; McCormick, R.; Paglieri, S. Preparation and Characterization of PdCu Composite Membranes for Hydrogen Separation. Chem. Eng. J. 2003, 93, 11–22. (11) Edlund, D.; McCarthy, J. The Relationship between Intermetallic Diffusion and Flux Decline in Composite-Metal Membranes: Implications for Achieving Long Membrane Lifetime. J. Membr. Sci. 1995, 107, 147–153. (12) Tong, J.; Matsumura, Y.; Suda, H.; Haraya, K. Experimental Study of Steam Reforming of Methane in a Thin (6 μM) Pd-Based Membrane Reactor. Ind. Eng. Chem. Res. 2005, 44, 1454–1465. (13) Basile, A.; Chiappetta, G.; Tosti, S.; Violante, V. Experimental and Simulation of Both Pd and Pd/Ag for a Water Gas Shift Membrane Reactor. Sep. Purif. Technol. 2001, 25, 549–571. (14) Amelio, M.; Morrone, P.; Gallucci, F.; Basile, A. Integrated Gasification Gas Combined Cycle Plant with Membrane Reactors: Technological and Economical Analysis. Energy Convers. Manage. 2007, 48, 2680–2693. 11334


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