Development of a Kinetic Model for Industrial Entrained Flow Coal

Article pubs.acs.org/IECR

Development of a Kinetic Model for Industrial Entrained Flow Coal Gasifiers Feng Qian,*,† Xiangdong Kong,† Hui Cheng,† Wenli Du,† and Weimin Zhong*,‡ †

Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, and ‡Automation Institute, East China University of Science and Technology, Shanghai 200237, China ABSTRACT: The characteristics of the industrial Texaco entrained flow coal gasifier are numerically studied in this paper. A kinetic model is proposed by dividing the gasifier into two zones to obtain the temperature and product concentration distribution along the reactor. These two zones are the pyrolysis−combustion zone and the reduction zone. The pyrolysis− combustion zone is modeled using the stoichiometry method. A detailed investigation was carried out on the gasification reaction rates in the reduction zone. The particle swarm optimization technique is introduced in this paper to address the lack of heterogeneous reaction kinetic parameters based on the random pore model for the specific feed Shenfu coal, and the huge deviation of the industrial product gas composition from the theoretical composition at equilibrium state. With the evaluated optimum kinetic parameters, robust agreement is achieved between the model outputs and the industrial data. Moreover, a sensitivity analysis related to the O2-to-coal ratio and coal slurry concentration was carried out in light of the proposed model.

1. INTRODUCTION Coal gasification technology is being developed worldwide for a more efficient and clean use of coal with substantially reduced carbon dioxide and pollutant gas emissions.1 Entrainment flow coal gasification is regarded as a practical coal-utilizing technology due to its advantages of high carbon conversion with short residence time and fossil fuel versatility. Synthetic gas (syngas) is the major product of coal gasification, and is primarily a mixture of hydrogen and carbon monoxide. Syngas is a very flexible intermediate product that can be used either as fuel for electricity generation or as a raw material for synthetic fuel production. A viable model can provide a better understanding of gasifier characteristics and the complicated reaction phenomena in the reactor under high temperature and pressure. Many efforts have been devoted toward developing gasifier models through thermodynamic equilibrium modeling and the kinetic modeling approach. The pure equilibrium approach assumes the reactions in the gasifier reach a thermodynamic equilibrium state.2−6 Therefore, a closer prediction is easy to implement and provide when the reaction temperature is sufficiently high. Although equilibrium models are used in the preliminary study of process fundamentals, they pose difficulties in being adapted for process analyses and optimization procedures. Compared with equilibrium models, kinetic models are more accurate and could give more detailed information of the gasification processes. However, the use of kinetic models is more difficult and time-consuming in terms of coming up with a solution.7−12 In addition, kinetic gasification models are generally established for specific gasifiers and types of feed. The kinetic parameters derived from the literature are not applicable for different coal or gasifier types. Several studies were reported on reaction kinetic rate determination for pyrolysis and gasification processes using the parameter fitting approach.13−15 Researchers adopted different optimization methods to minimize errors between model results and experimental results in the search for optimal parameters for specific reacting conditions. © 2013 American Chemical Society

The current study proposes a model for an industrial Texaco down-flow entrained bed gasifier with a water quench section designed to treat up to 500 tons of coal per day as water slurry type. The gasifier is divided into two zones: (1) pyrolysis− combustion zone and (2) reduction zone. Detailed kinetic behaviors of pyrolysis and combustion reactions involved in the pyrolysis−combustion zone are not considered. The products of the pyrolysis−combustion zone are calculated using the stoichiometry method by assuming that all the volatiles are released and that the gasification agent oxygen is combusted completely. Beneath the pyrolysis−combustion zone is the reduction zone, where the char gasification reactions occur. The occurring reactions are regarded as the key procedures for reactor modeling. The random pore model (RPM)16,17 is utilized to depict the behavior of the heterogeneous char gasification reactions. Due to the differences of coal types and gasification circumstances, using the parameters derived from the literature will give mismatched results for the industrial process as aforementioned. This disparity necessitates the estimation of optimum kinetic parameters to model the specific commercial gasifier and Shenfu coal feed precisely. Recently, numerous efforts have been made to estimate the parameters using intelligent methods.18−22 In this article, industrial data and calculated values are compared, and optimum kinetic parameters are estimated using the standard particle swarm optimization (PSO) technique.23 This paper aims to develop a simplified one-dimensional industrial gasifier model that emphasizes the reaction behaviors in the reduction zone and to determine the corresponding optimal parameters. Sensitivity analysis is conducted to investigate the effects of the oxygen-toReceived: Revised: Accepted: Published: 1819

January 13, 2012 October 8, 2012 January 10, 2013 January 10, 2013 dx.doi.org/10.1021/ie301630x | Ind. Eng. Chem. Res. 2013, 52, 1819−1828

Industrial & Engineering Chemistry Research

Article

coal ratio (ROC) and coal slurry concentration on gasifier performance.

coal → α1CH4 + α2 H 2 + α3CO + α4CO2 + α5H 2O + α6char + α7 H 2S + α8 N2 + α9ash

2. PROCESS DESCRIPTION The Texaco gasifier runs at an elevated pressure. The coal slurry is atomized by a high-speed pure oxygen spray into the gasifier from the jets. The small coal slurry particles are rapidly accelerated, heated for a short period of time by flame, and then transported along the gasifier. Then, the particles are dried before being subjected to pyrolysis, combustion, and char gasification to generate syngas. Separating the actual process into pyrolysis−combustion and reduction zones can simplify the model and improve accuracy.24 Figure 1 shows the sketch

(1)

where αi is the number of moles of a species after devolatilization. The combustible pyrolysis products, such as CO, H2, and CH4, quickly react with the oxidant, and a large amount of heat is produced to heat coal rapidly to the pyrolysis temperature simultaneously. The extent to which the oxidant is completely or only partially depleted depends on the amount of volatile products produced and of oxygen. Generally, an overall excess of oxygen is needed to consume the volatile products completely. Therefore, the product char can react with the remaining oxygen to produce CO/CO2. Only eq 2 is considered in the char combustion process in this paper to simplify the solid−gas combustion reactions. The combustible gas CO in turn reacts in the gas phase with oxygen to produce CO2 and more heat. Once the temperature in the pyrolysis− combustion zone exceeds 2000 K, the pyrolysis and combustion reactions occur very quickly and can be instantaneous. Therefore, the detailed kinetics of pyrolysis and combustion can be neglected under these circumstances. The char combustion reaction is as follows: C(s) + 0.5O2 → CO

(2)

Beneath the pyrolysis−combustion zone is the reduction zone, where CO2 and H2O are reduced. The borderline is assumed to be at the location where the oxygen is exhausted. The gasification process in the reduction zone is key for syngas production in a gasifier. This region has three main heterogeneous reactions, namely, char−steam gasification, char−carbon dioxide, and char−hydrogen, and two homogeneous reactions, namely, the water gas shift reaction (WGS) and the methane steam reforming reaction (as shown in Figure 1). The possible products of the reduction zone are assumed to be CO, CO2, H2, CH4, H2S, and N2. H2S and N2 are assumed to be the final products for elemental sulfur and nitrogen in the reducing gasification system based on the trace amounts of sulfide and nitride in the products.

3. GASIFICATION REACTION KINETICS IN THE REDUCTION ZONE The slowest reactions in gasification that govern the overall conversion rate are the heterogeneous reactions with char.26 However, obtaining the gasification rate is difficult due to the combination of different mechanisms, such as mass transfer, chemical reaction, and heat transfer. A great deal of research has been carried out on the development of char gasification reaction rate models.27−31 Still, the reaction rate expressions adopted in the one-dimensional gasifier models rarely consider the mass transfer rates. The expressions of the overall reaction rates should consider the mass transfer among the gas phase, char particles, and the intrinsic kinetics. The final reaction rate of each heterogeneous reaction is calculated by32 the following:

Figure 1. Scheme of the physical model of the gasifier along with possible reactions.

of the physical model of the gasifier along with possible reactions in both zones. The pyrolysis−combustion zone is at the top of the gasifier, where pyrolysis and combustion reactions proceed. Pyrolysis is an extremely complex process due to the large number of chemical and physical transformations that occur rapidly and simultaneously.25 Pyrolysis can be simplified by eq 1:

Ri =

R i ,dR i ,k R i ,d + R i ,k

(3)

where Ri is the final reaction rate of the ith reaction, Ri,d is the bulk diffusion rate, and Ri,k is the apparent chemical reaction rate, which includes the effects of pore diffusion and the intrinsic reactivity of char. The value of Ri,d is given as follows: 1820

dx.doi.org/10.1021/ie301630x | Ind. Eng. Chem. Res. 2013, 52, 1819−1828

Industrial & Engineering Chemistry Research R i ,d = Ci

[(Ts + Tg)/2]0.75 dp

Pi

Article

4. MATHEMATICAL MODEL The process of gasification is isobaric. The pyrolysis− combustion zone immediately following the inlet of an entrainment gasifier is similar to a stirred tank reactor. The reduction zone is directly adjacent to the pyrolysis−combustion zone; thus, the vortex pattern rapidly dissipates, and plug flow can be assumed. The cell-in-series approach is employed to represent the hydrodynamics in the reduction zone. The size of the pyrolysis−combustion zone and the number of compartments in series are determined assuming a temperature profile based on the reference data for a similar reactor.10,12,36 Accordingly, the pyrolysis−combustion zone is assumed to be completely mixed and is taken to account for about 1/20 of the effective reactor size. Many experiments have been conducted to study the effect of the compartment number on the model predictions. In the present work, dividing the reduction zone into 50 compartments is found to be the most suitable. 4.1. Model of the Pyrolysis−Combustion Zone. Due to the high temperature of nearly 2000 K, the simulation of the pyrolysis and combustion processes is instantaneously and simultaneously considered. Reaction kinetics is not involved in this study. First, the composition of products after pyrolysis can be calculated by atomic equilibrium equations in light of ultimate element analysis and proximate analysis of the coal, i.e., the conservation equations for atomic C, H, O, N, S, and ash. The ratio of moles of CO and CO2 is assumed to be inversely related to their molecular mass to close the equations. The moles of the products after pyrolysis can be obtained by solving the equations. Second, when the combustible gases are completely burnt, the amount of residual oxygen can be calculated from the mass balance and stoichiometry:

(4)

where Ci is the diffusion coefficient of the ith reactant, Ci = 3 × 10−12 s K−0.7532, Ts is the absolute temperature of the particle, Tg is the absolute temperature of the bulk gas phase, dp is the particle diameter (in meters), and Pi is the partial pressure of the ith reactant (in pascals). The random pore model (RPM) is utilized to express intrinsic heterogeneous reaction kinetics. The RPM is known to be the most flexible in modeling the char gasification reactions as it can represent the behavior of the char gasification process that shows a maximum rate at certain conversion levels proved by experiments.28 Liu et al.33 found that the RPM gives a reasonable prediction of the char gasification rate in the entrained flow coal gasifiers. The RPM model can be described as34 follows: ⎛ E ⎞ dx = A 0, i exp⎜ i ⎟(1 − x) 1 − ψi ln(1 − x) P n dt ⎝ RTs ⎠

(5)

where x is the carbon conversion of each particle, ψi is the pore surface parameter, i represents the different heterogeneous reactions, A0,i is the frequency factor, Ei is the activation energy, R is the gas constant, n is the reaction order, and Ts is the solid particle temperature. The intrinsic chemical reaction rate Ri,k can be obtained from eq 5 based on stoichiometry. The particle diameter dp emerging in eq 4 depends on char conversion and decreases along the reactor length: ⎛ d p ⎞3 ⎜⎜ ⎟⎟ = 1 − x + ε ⎝ d p,0 ⎠

n r‐O2 = nO2 − 2α1 − 0.5α2 − 0.5α3

(6)

where nr‑O2 is the number of moles of the residual oxygen when the volatile parts have been completely burnt, and nO2 is the number of moles of the oxygen fed into the gasifier. About 50% of the excess oxygen reacts with char to form char monoxide. Subsequently, char monoxide reacts with balanced 50% of oxygen to generate CO2. The amount of CO as the intermediate product can be expressed by eq 9:

where dp,0 is the initialized particle diameter. The constant ε in eq 6 is assumed to be 1 × 10−4 to ensure convergence stability with a minimum value of dp. In addition to the three heterogeneous reactions mentioned above, two homogeneous ones are considered, namely, the WGS reaction and the methane steam reforming reaction depicted in Figure 1. The two reactions attain equilibrium at higher temperatures.10,11 Equilibria for the WGS reaction and the methane steam reforming reaction are given in ref 35. However, industrial measurements show that the water gas shift reaction is not at equilibrium in the commercial gasifier; i.e., the value of (yH2yCO2)/(yCOyH2O) for a real gasification system differs from the equilibrium constant. Two fixed values are used in the current work to account for the deviations from the theoretical equilibrium constants of the WGS reaction and the methane steam reforming reaction derived from ref 19 (Cf, the corrective factor). These values help in dealing with the predicted compositions in the actual process. The corrected equilibrium constants can be obtained according to eq 7. K = Cf K *

(8)

nCO = n r‐O2

(9)

where nCO is the number of moles of CO. Third, except for the inert gases H2S and N2, the products of the pyrolysis−combustion zone can be obtained from eqs 10−12:

(7)

nC = α6 − n r‐O2

(10)

nCO2 = α1 + α3 + α4 + n r‐O2

(11)

n H2O = 2α1 + α2 + α5

(12)

where nC, nCO2, and nH2O indicate the number of moles of char, CO2, and H2O, respectively. Finally, the temperature calculations of gas and solid at the exit of the pyrolysis−combustion zone are expressed by eqs 13 and 14.

where K is the final equilibrium constant for the homogeneous reactions in this work, and K* is the theoretical equilibrium constant from ref 35. Cf is practical to compensate for the deviation from the theoretical equilibrium. 1821



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solid phase heat balance

gas phase heat balance

∑ (WgmCp,gmTg)z +Δz

(WC s p ,sTs)z p − b − (WC s p ,sTs)0 = (AcAz p − b)[eFσ(Tg 4 − Ts 4) + hc p − b(Tg − Ts)] + 0.5nCOΔHgs‐CO

m

= −(AcAΔz)[eFσ(Tg − Ts 4) + hc(Tg − Ts)] 2

(13)

+ aA∑ ( −ΔHj)rj − Hloss,g‐w Δz

In eqs 17 and 18, hc is the convection and conduction heat transfer coefficient and Hloss,g‑w is the heat exchange per unit area of the reactor wall, which is assumed to be constant. Stokes’ law is applied for the solid flow in the gasifier, which is due to the small solid particle size and the low Reynolds number obtained by eq 19. The gas flow rate is calculated using the global mass balance of the produced gas during the calculation process. The coal gasifier model can be established by combining those for combustion−pyrolysis and the reduction zone:

∑ (WgmCp,gmTg)z p − b − ∑ (WgmCp,gmTg)0 m 4

= −(AcAz p − b)[eFσ(Tg − Ts 4) + hc p − b(Tg − Ts)] + (2α1ΔHg1 + 0.5α2ΔHg2 + 0.5α3ΔHg3 (14)

In eqs 13 and 14, Wg is the gas flow rate, Ac is the contact area between the gas and the solid per unit volume of the reactor, zp−b is the pyrolysis−combustion zone size; hcp−b is the convection and conduction heat transfer coefficient in the pyrolysis−combustion zone, m is the mth component of the gas phase, and Hg‑loss is the heat loss in the pyrolysis−combustion zone consisting of heat consumed by pyrolysis, drying, and heat transport from the gas to the reactor. The viewing factor, F, for radiation heat transfer between gas and coal particles, and the emissivity, e, are assumed to be 1.0 and 0.9, respectively. 4.2. Model of the Reduction Zone. The reduction zone is divided into compartments where the local variables (hydrodynamic, kinetic, and thermodynamic variables) are evaluated. Compartments are solved sequentially with the output of the Nth compartment considered as the input for the (N + 1)th one. The mass balances for solid particles and gas are illustrated in eqs 15 and 16.

Rep = ρg d p

(15)

gas phase mass balance 2

Wgm , z +Δz − Wgm , z = AΔz∑ vm , jrj + ΔR sg j

(16)

In eqs 15 and 16, Δz is the cell size, ΔRsg indicates the gas components produced by the solid−gas reactions in the current cell, and i and j are the reactions in the solid and gas phases, respectively. The energy balances in the reduction zone can be described by eqs 17 and 18. solid phase heat balance

dz

= AcA[eFσ(Tg 4 − Ts 4) + hc(Tg − Ts)] 3

+

∑ (−ΔHi)ri/vs i

μg

(19)

5. OPTIMIZATION OF THE HETEROGENEOUS REACTION KINETIC PARAMETERS Parameter estimation is critical in modeling. The gasification reaction in the reduction zone is the rate-determining step in the coal gasification process and the most important factor in evaluating gasifier performance.31,34 The mass and energy balance equations in the reduction zone can be solved only after the parameters associated with them are obtained. Determining the intrinsic kinetic parameters is critical in establishing the gasification model. In this study, the kinetic parameters for the three heterogeneous reactions and the Cf values for the two homogeneous reactions need to be estimated. The char reaction rate greatly depends on the coal type and gasification circumstances. Most studies about the RPM are based on experiments under atmospheric pressure or with a packed bed reactor at specific conditions. Thus, the kinetic parameters obtained in the literature cannot express the natural behavior of the heterogeneous reaction in the industrial process. However, determination of the optimal reaction rate parameters is difficult due to the nonlinearity of the models. Therefore, the PSO technique is used to optimize the kinetic parameters of the char gasification reactions. The PSO technique performs robustly for systems that have large parameter spaces containing many local optima, especially when no obvious starting value exists for the optimization problems.23,37 The PSO method is a population-based search algorithm. In this method, each individual, often called a particle, represents a candidate solution in the feasible space of the optimization problem. Each particle is characterized by its position and current velocity. The fitness function or the objective function is introduced to assess the quality of the particle location, and this process is called fitness evaluation. Each particle flies through the search space with an adaptable velocity that is dynamically modified by combining the best position found so far by itself, namely, pbest, and the best position found by any

3

dWs = −∑ ri /vs dz i

|vg − vs|

where Rep is the Reynolds number of the dimensionless particle.

solid phase mass balance

d(WC s p ,sTs)

(18)

j

+ 0.5nCOΔHg1)(1 − Hg‐loss)

∑ (WgmCp,gmTg)z 4

gas phase heat balance

m

−

m

(17) 1822



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6. RESULTS AND DISCUSSION The industrial data are taken from a Texaco down-flow entrained bed gasifier that is designed to treat up to 500 tons of coal per day as water slurry type, at an operating pressure of 4.0 MPa, and with an exit temperature between 1400 and 1700 K. The industrial data were gathered by averaging the measurements in 1 min. The obtained data went through steady-state identification and gross error detection to eliminate noisecontaining data. The typical Shenfu coal with an average particle diameter of 80 μm is used in the gasifier as feed. Proximate and ultimate analyses of the Shenfu coal are given in Table 1.

member of the particle’s topological neighborhood, namely, gbest, with several random perturbations. The cognitive acceleration factor determines the magnitude of the random forces in the degree of pbest, whereas the social acceleration factor determines the magnitude of the random forces in the degree of gbest. These learning strategies are known to belong to the flying experience. This process is repeated until a userdefined stopping criterion is reached. The PSO is briefly described as follows:23 1. Initialization. Create a population array of particles with random positions and velocities in the search space. 2. Main Loop. (a) For each particle i, evaluate the desired optimization fitness yi at current position xi. (b) Compare each particle’s fitness evaluation with the best function result so far, which is called pbesti. If yi is better, then update pbesti to the current value, and make pi equal to the current location xi. (c) Identify the particle in the neighborhood with the best success so far, and then assign its index to the variable g. (d) Update the velocity vi and position xi of the particle according to the following equation:

Table 1. Properties of Shenfu Coal proximate anal. of coal (dry basis, wt %)

(20)

where ω is the inertia weight factor, c1 and c2 are the cognitive and social acceleration factors, respectively, and r1 and r2 are the random numbers uniformly distributed in the range [0,1]. 3. Cycle. Repeat from step 2 until a certain termination criterion is met. Fitting the model to industrial data involves searching for the kinetic parameters that minimize the error criterion, which is generally the sum of squared differences between the outputs calculated by the proposed model and those from the industrial measurements. The deviations considered here as the objective function are given by

volatile

ash

C

H

O

N

S

ash

58.9

33.9

7.2

74.56

5.31

11.48

0.99

0.46

7.2

Table 2. Calculated Char Gasification Reaction Kinetic Parameters for Shenfu Coal by PSO parameter

2 ⎡m ⎛ j ⎛ T j − T j ⎞2 Ci ,sim − Cij,ind ⎞ ⎢ ⎟⎟ + ⎜ g,sim j g,ind ⎟ f = ∑ ⎢∑ ⎜⎜ j ⎜ ⎟ C Tg,ind ⎠ ⎝ ⎠ i ,ind j=1 ⎣ i=1 ⎝ l

j ⎛Xj ⎞2 ⎤ char,sim − Xchar,ind ⎥ ⎟⎟ + ⎜⎜ j ⎥ Xchar,ind ⎝ ⎠⎦

fixed carbon

6.1. Optimization Results. The standard PSO technique is used to obtain the optimum model parameters based on the data set collected from the industrial gasification process. In this model, the parameters of Ψ, A0, E, and Cf need to be estimated. However, the RPM has the same structural parameter Ψ for the same coal with different gases. In the experiments, the parameters for PSO algorithm are settled as follows: the initial population size N = 50, the maximum iteration number G = 100, the inertia weight factor ω = 0.729, and the cognitive and social acceleration factors c1 and c2 are both set at 1.494. Other parameters involved in the experiments are chosen empirically. The calculated optimum kinetic parameters of the heterogeneous reactions based on the RPM in the reduction zone are listed in Table 2.

vi⃗ ← ωvi⃗ + c1r1(pi ⃗ − xi⃗ ) + c 2r2(gi⃗ − xi⃗ ) xi⃗ ← xi⃗ + vi⃗

ultimate anal. of coal (dry basis, wt %)

Ψ A0,1 E1 (kJ/mol) A0,2 E2 (kJ/mol) A0,3 E3 (kJ/mol) Cf1 Cf2

(21)

where f is the objective function, i is the ith dry product gas component (available in the industrial measurements, including CO, CO2, CH4, and H2), j is the data point, and Ci is the volume fraction of component i. Gas composition is measured online by a gas chromatographic analyzer at the exit of the water scrubber, and the carbon conversion is calculated from the carbon residue analysis conducted by an analyst from the plant. The cooling rate in the quench coolers is very high (around 30 000 K/s). The temperature in the quench cooler is sufficiently low to stop the kinetics of the water gas shift reaction. Operational experience suggests that very little to no reaction occurs in the quench cooler and scrubber. Therefore, the gas composition measured at the exit of the water scrubber is approximately equal to that at the exit of the gasifier.

reaction

estd value

95% confidence limit

− C + H2O

12 1.26 × 107 226.08 2.03 × 105 169.03 1.22 × 103 166.87 1.11 0.76

0.11 4.12 × 105 7.32 5.483 × 103 5.88 94.3 3.1 0.05 0.12

C + CO2 C + H2 CO + H2O CH4 + H2O

The optimized kinetic parameters are then applied to simulate the industrial gasifier under different operating conditions, and the output component concentrations are obtained. Detailed information of the operating conditions for these runs is given in Table 3. The current study compares the calculated CO, H2, and CO2 mole fractions on a dry basis and carbon conversion using the present model with optimized kinetic parameters, as well as that with the parameters from ref 34 due to a lack of RPM parameters for the Shenfu coal and from industrial data. The parity plots are shown in Figures 2−5. Figures 2−4 show the distributions of CO, CO2, and H2 in the product syngas, in which y1CO, y1CO2, and y1H2 denote the volume fractions of CO, CO2, and H2 based on the optimized kinetic 1823



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Table 3. Experiment Conditions of the Texaco High Pressure Gasifier case run run run run run run run run run run run run run run

1 2 3 4 5 6 7 8 9 10 11 12 13 14

slurry feed rate (m3/h)

slurry concn (wt %)

O2 flow rate (Nm3/h)

31.14 30.82 31.02 29.36 30.98 30.63 30.55 28.76 28.23 27.99 27.17 27.95 27.84 29.14

57.6 58.8 59.2 61.7 62.0 61.6 59.0 58.2 57.9 58.4 58.5 60.1 59.5 60.2

15 028.75 15 119.04 15 214.66 15 106.51 15 891.96 15 716.53 15 003.69 14 197.59 14 133.98 14 210.19 13 942.81 14 684.71 14 236.02 14 971.66

Figure 4. Comparison of industrial volume fractions of H2 with model predictions.

Figure 5. Comparison of industrial carbon conversions with model predictions.

Figure 2. Comparison of industrial volume fractions of CO with model predictions.

based on the optimized kinetic parameters and Conversion2 denotes the calculated carbon conversion based on the kinetic parameters derived from ref 34. The predictions of the present model show a close fit with the real volume fractions of CO, H2, and CO2, and carbon conversion. For the volume fractions of the product gas, the maximum relative error between the calculated one and the industrial measurement is about 6.3%. For the carbon conversion, the relative error is less than 1.1%. Therefore, the present model with its optimum kinetic parameters listed in Table 2 is reliable, given the operating conditions of this study. Figures 6 and 7 show the model predictions in the form of temperature profiles, carbon conversion profile, and species concentration profiles along the axis distance of the gasifier at a specified condition. The gasifier is operated at 4.0 MPa, with a coal slurry flow rate of 28.8 m3/h, a slurry concentration of 60%, and an oxygen flow rate of 14 619 Nm3/h. Figure 6 shows the temperature profiles for solid and gas and the carbon conversion profile. Two peaks are observed in the temperature profiles of the solid and gas. These maximum points are associated with the point at which the oxygen is completely consumed and combustion reactions end. As long as oxygen exists in the bulk gas, a significant temperature difference will be observed between the coal particles and the bulk gas. After oxygen depletion, the temperatures decrease

Figure 3. Comparison of industrial volume fractions of CO2 with model predictions.

parameters, respectively, and y2CO, y2CO2, and y2H2 denote the model predictions with the parameters derived from ref 34, respectively. Figure 5 shows the carbon conversion distribution, whereby Conversion1 denotes the calculated carbon conversion 1824



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Figure 6. Calculated temperature profiles and carbon conversion profile at a specified condition.

Figure 8. Effect of the ROC on (a) temperature and carbon conversion and (b) product gas compositions.

Figure 7. Calculated product gas composition profiles (wet basis) at a specified condition.

gasifier become faster. A higher temperature accelerates char gas reactions. Hence, the carbon conversion approaches unity. The product gas composition fraction of each component and the efficient syngas yield at various ROCs are shown in Figure 8b. As the ROC increases, the CO composition considerably increases whereas H2 rapidly decreases. The reason is that a higher operating temperature makes the water shift reaction move to the direction where more CO is generated and suppresses H2 generation. Moreover, the composition of the syngas has a maximum value when the ROC is around 0.99. At this point, an increase of CO composition and a decrease of H2 composition balance and create an optimization point. Simulation results show a decreasing trend for CO2 when the ROC is less than 0.99. Trends will be reversed if the ROC is higher than 0.99 as a result of the increase in oxygen supply. 6.3. Effect of Slurry Concentration. The effects of the coal slurry concentration ranging from 56 to 68% on gasification performance are likewise investigated. In previous literature,10−12,36 analyses on slurry concentration were carried out at a fixed ROC. However, the change of the coal slurry concentration causes the amount of supplied oxygen to vary with it at a fixed ROC. Therefore, the effect of coal slurry concentration is examined through three cases shown in Table 4.

along the reduction zone, and the difference between the solid and gas temperatures drops. This drop in temperature is due to char gasification reactions, which are endothermic reactions that become predominant in the reduction region. The changes in gas composition over the reactor length are illustrated in Figure 7. In the pyrolysis−combustion zone, any methane, hydrogen, or carbon monoxide produced is immediately consumed in the gas phase. In the initial combustion period, the concentrations of steam and carbon dioxide increase and show maxima after the oxygen is exhausted, whereas the concentrations of CO, hydrogen, and methane decrease to zero. Only when the oxygen concentration falls to zero do hydrogen and CO appear in the bulk gas. Subsequently, CO and hydrogen formation occur, and the concentrations of both increase along the length of the reduction zone. Meanwhile, the concentrations of steam and CO2 decrease toward the exit of the reactor. 6.2. Effect of O2-to-Coal Ratio. The effects of feed oxygen on gasifier performance are studied using the proposed model at 4.0 MPa, with a coal slurry flow rate of 28.8 m3/h and a coal slurry concentration of 60%. In Figure 8a, the carbon conversion and the gasification temperature are plotted as a function of the ROC. With increase in the ROC, the gasification temperature rises, and the reaction rates in the 1825



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Table 4. Three Methods To Change the Slurry Concentration case number 1 coal slurry constant flow rate O2 feed constant flow rate ROC

changing with coal slurry concentration

2 changing with coal slurry concentration constant constant

3 constant changing with coal slurry concentration constant

Figures 9, 10, and 11 show the effects of the coal slurry concentration on the carbon conversions, gasification temper-

Figure 10. Effect of coal slurry concentration on (a) temperature and carbon conversion and (b) product gas composition for case 2.

the slurry concentration. In both cases 2 and 3, the simulation results show similar performances, which can be observed in Figures 10 and 11. The gasification temperature slightly rises, whereas the carbon conversion remains unchanged due to the decrease of heat needed for slurry water evaporation. In both cases, the mole fraction of CO increases. However, the mole fraction of H2 exhibits the opposite trend due to the compromise between the increasing temperature and the exothermic water gas shift reaction. Based on all three cases, the increase of coal slurry concentration improves the efficient gas yield. However, the carbon conversion decreases in case 1. The amount of dry coal treated in the industrial process is fixed. Thus, the method described in case 2 can provide a better performance for optimization.


7. CONCLUSION By dividing the gasifier into pyrolysis−combustion and reduction zones, this work proposes a new model for an industrial Texaco entrained flow coal gasifier. A standard PSO technique is applied to estimate the reaction parameters in the reduction zone. The temperature profiles in the solid and gas phases over the gasifier length, as well as the carbon conversion and the product concentrations, are obtained. The present model can properly predict the behavior of the industrial entrainment coal gasifier to improve process performance. On the basis of the proposed model, a sensitivity analysis related to

atures, and product gas compositions for these three cases, respectively. In Figure 9 for case 1, with the increase of slurry concentration, the gasification temperature and carbon conversion decrease simultaneously. The reason is that the ROC decreases as the coal slurry concentration increases when the input O2 flow rate and coal slurry rate remain constant. In this condition, the average temperature in the reactor decreases and consequently reduces the char gasification reaction rates. The composition of CO increases significantly, whereas that of CO2 decreases. In addition, H2 changes slightly with respect to 1826



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for Outstanding Young Scholars (61222303), and the Shanghai Leading Academic Discipline Project (B504).

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the practical operating variables, such as the ROC and coal slurry concentration, is carried out. The increase of the ROC significantly increases carbon conversion and the temperature of the reactor. For a given slurry concentration, an optimal ROC that maximizes the efficient gas yield exists. Furthermore, the effects of coal slurry concentration are analyzed three ways. With the increase of coal slurry concentrations, the composition of the efficient gas in the product gases increases, and the CO concentration sharply increases. Keeping the ROC constant offers an advantage of changing the coal slurry concentration in the industrial processes. In addition, the slurry concentration should be large enough to enhance the yield of the effective compositions in the product gas.

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NOTATION A0 = pre-exponential index At = cross-sectional area of reactor (cm2) Ac = contact area between the gas and the solid per unit volume of reactor (m2/m3) Cj = diffusion coefficient of the jth rate (K−1) Cf = corrective factor Cp,g, Cp,s = specific heats of gas and solid, respectively (J/ kg·K) c1, c2 = cognitive and social acceleration factors, respectively Di, Do = inside and outer gasifier diameters, respectively (cm) dp = particle size (m) E = activation energy (kJ/mol) e = emissivity of gas ΔH = enthalpy of the reaction (J/mol) Hloss = heat loss hcp−b = convection heat transfer coefficient in the pyrolysis− combustion zone (J/m2·K) Hg‑loss = heat loss in the pyrolysis−combustion zone Hloss,g‑w = heat exchange per unit area of reactor wall (J/m·s) hc = convection and conduction heat transfer (J/m2·K) K = equilibrium constant n = number of moles (mol/s) P = pressure (Pa) R = gas constant (J/mol·K) Ri = net rate of generation or consumption of species i due to chemical reactions (mol/m3·s) r1, r2 = random numbers t = time (s) Tg = gas-phase temperature (K) Ts = solid-phase temperature (K) u = velocity (m/s) Wg = gas flow rate (mol/s) Ws = solid flow rate (mol/s) x = carbon conversion y = volume fraction z = height (m) zp−b = height of the pyrolysis−combustion zone (m)

Greek Symbols

α = constant αi = mole fraction of ith species after devolatilization μ = kinetic viscosity (kg/m·s) ρ = density (kg/m3) σ = Stefan−Boltzmann constant (J/m2·s·K4) Ψ = structural parameter ω = inertia weight factor

AUTHOR INFORMATION

Subscripts

Corresponding Author

*E-mail: [email protected] (F.Q.); [email protected] (W.Z.). Tel.: 86-21-64252060 (F.Q.); 86-21-64251250 (W.Z.). Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work is supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (Key Program U1162202; 61174118, 21276078), the National Science Fund

d = diffusion g = gas i = ith reaction j = jth reaction k = intrinsic m = mth component

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