Simulation Of Circulating Fluidized Bed Reactors Using Aspen Plus

PII: SOO16-2361(97)00211-l

ELSEVIER

Fuel Vol. 77, No. 4, pp. 327-337, 1998 0 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0016-2361/98 $19.00+0.00

Simulation of circulating fluidized bed reactors using ASPEN PLUS R. Sotudeh-Gharebaagh,

R. Legros*, J. Chaouki and J. Paris

Department of Chemical Engineering, &o/e Polytechnique, Montrkal, PO, Canada H3C 3A7 (Received 4 April 1995; revised 18 August 1997)

PO Box 6079, Station

‘Centre-Vi//e’,

A comprehensive model is developed for the combustion of coal in a circulating fluidized bed combustor (CFBC). The proposed model integrates hydrodynamic parameters, reaction model and kinetic subroutines necessary to simulate coal combustion in a CFBC. Kinetic expressions were developed for the char combustion rates and the SO2 absorption in the bed using data from the literature. The reaction model, which considers only the important steps of coal combustion, was simulated using four ASPEN PLUS reactor models and several subroutines. The developed subroutines were then nested in the ASPEN PLUS input file, so that the CF’EK may be represented. The validity of the model was demonstrated using 14 different sets of operating conditions for the CANMET 0.8 MWth CFBC pilot plant. 0 1998 Elsevier Science Ltd. All rights reserved. (Keywords: ASPEN PLUS; CFBC; circulating fluidized bed reactors; fluidized bed combustion)

INTRODUCTION Circulating fluidized bed combustors (CFBCs) are considered as an improvement over the traditional methods associated with coal combustion. The CFBC exhibits several advantages over conventional coal combustion methods, especially when high sulfur coal is used’. Operation of CFBCs at industrial levels has confirmed many advantages that include fuel flexibility, broad turndown ratio, high combustion efficiency, low NO, emissions and high sulfur capture efficiency. These characteristics assure an ever-increasing number of successful commercializations of CFBC in power generation applications. Although CFBC technology is becoming more common from these commercial applications, there are some significant uncertainties in predicting their performance in large-scale systems. Technical knowledge about design and operation of CFBC is widely available for pilot plant and large scale units. However, little has been done in the field of mathematical modeling and simulation of combustion in CFBCs. This might be attributed to the fact that the combustion process occurring in a CFBC involves complex phenomena including chemical reactions, heat and mass transfer, particle size reduction due to combustion, attrition, fragmentation and other mechanisms, gas and solid flow structure, etc. Weiss et al.* introduced a CFBC model by dividing it into 11 blocks, each corresponding to a CSTR reactor for both gas and solid phase. Five of these blocks related to the CFBC riser. Basu et aL3 developed a CFBC model in which a plug flow regime for both the gas and solids is assumed. Lee and Hypanen4 presented a CFBC

*Corresponding author

model which considers the riser as a plug flow reactor for the gas phase and a CSTR reactor for the solid phase. The model also considers the feed particle size distribution and the attrition phenomena. Using a lumped-modeling approach, Arena et aL5 introduced the means for predictive calculation by dividing the CFBC riser into four blocks, each corresponding to a separate reactor. Three of these blocks related to the CFBC riser. The hydrodynamic parameters were considered uniform within each section and were used in various kinetic models to predict char conversion. Wong6 proposed a model for the hydrodynamics of CFBC risers to characterize the effect of the internal flow structure within the riser, the particle size distribution and the operating conditions on CFBC behavior. To estimate the axial voidage profile, a core-annulus model was developed. The predictive hydrodynamic model was then applied to a CFBC design. A comprehensive review of relevant work on the hydrodynamics of circulating fluidized bed risers is presented by Berruti et aL7 Moreover, Senior’ conducted some theoretical and experimental investigations to improve the understanding of the fluid and particle mechanics in the CFBC riser and to develop mathematical models to represent riser suspension flows. On the other hand, a few CFBC modeling efforts have been based on extension of bubbling AFBC hydrodynamic concepts’-’ ‘. Beyond those mentioned above, some modeling work have been developed using ASPEN (advanced system for process engineering). ASPEN was developed at the Massachusetts Institute of Technology (MIT) under a United States Department of Energy project to simulate coal conversion processes. It has now become a powerful tool for engineers to model chemical, power generation and other processes. The work of Young’* entails the modeling and simulation of AFBC using ASPEN. Herein, the ‘black

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box’ approach with one ASPEN PLUS stoichiometric reactor was used to calculate the mass balances based on given combustion and sulfur capture efficiencies. CFBC simulation work was also initiated at CERCHAR13 to provide the technical information required for the evaluation and optimization of CFBCs under steady-state condition in power generation applications. The study of pollutant emissions such as SO*, NO, and N20, as well as the ash composition leaving the CFBC was not included in this work; instead several ASPEN PLUS user subroutines were used in order to study the hydrodynamic, combustion and heat transfer phenomena in the bed. The approach used at CERCHAR is similar to that of Young’s, but was extended to cover CFBCs. Combustion Engineering Inc.14 also used ASPEN in modeling a Lurgi circulating fluid bed. The approach, similar to that of Young’s’* used here, has a low level of complexity since the goal was the calculation of the mass and energy balances for the CFBC. Up to now, modeling of CFBCs using a process simulator (such as ASPEN PLUS) has been limited to simple mass and energy balances, without predictive capabilities. ASPEN PLUS is widely accepted in the chemical industry as a design tool because of its ability to simulate a variety of steady-state processes ranging from single unit operation to complex processes involving many units. Consequently, ASPEN PLUS was chosen as a framework for the development of a CFBC process simulation. Since there is no CFBC model provided by ASPEN PLUS, we must develop our own using the tools offered by ASPEN PLus15,16. In addition to its conventional reactor models, ASPEN PLUS has the flexibility to allow the insertion of Fortran blocks and user kinetic subroutines into the simulation. In this work, several ASPEN PLUS reactor models interact with their corresponding user-written kinetic subroutines to perform calculation during the simulation. This flexible structure of ASPEN PLUS permits handling of complex processes, such as those occurring in a CFBC. Hence, an attempt is made to develop a model which includes several features that were neglected or simplified in the previous studies as outlined above, in order to produce a predictive tool. This paper presents the details of the modeling approaches taken to obtain a process simulation programme for coal combustion in a CFBC. MODELING APPROACHES In a typical CFBC used for coal combustion, crushed coal together with limestone or dolomite and ash particles are fluidized by the combustion air entering at the bottom of the bed and at one or several secondary air injection points. A large portion of the bed particles exits the riser of the CFBC with the flue gas due to the high superficial gas velocities utilized. The particles are then separated from the exhaust gas in a gas/solid separator (often a cyclone) and recycled into the riser to promote complete combustion of the coal. Because coal combustion in a CFBC is directly affected by its hydrodynamic parameters, both hydrodynamic and combustion models must be treated simultaneously to yield a predictive model for the CFBC. The description of the method followed in developing the hydrodynamic and reaction models is given below. Hydrodynamic model

The hydrodynamic model enables the variation of the void fraction with height in the riser to be determined. The

328

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et al. general hypotheses of the hydrodynamic model along with the modeling procedure are presented below. General hypotheses of the hydrodynamic model. For steady state conditions, the assumptions regarding the hydrodynamic model are the following:

(1) The CFBC is naturally divided into two hydrodynamic regions: (i) a lower region-turbulent fluidized bed (dense bed); (ii) an upper region (dilute bed). The boundary between the two regions is defined by the height of the secondary air injection point. (2) There is perfect mixing of solids (individual ash, char particles and sorbents) in the lower region and in each zone of the upper region17. This assumption is justified by the high internal and external recirculation of solids in the bed. (3) Plug flow regime for gas is assumed in the bed. This is consistent with the results of gas backmixing ex eriments in the CFBC risers as reported in the literature p7. (4) The gas velocity throughout the bed is uniform and constant for each region of the bed. (5) For a given superficial gas velocity, the mean voidage in the lower region of the CFBC is constant. This assumption is justified by the results of experiments of Chehbouni et al. l8 for group B particles considering the lower region to be operated under the turbulent fluidization condition. (6) In the upper region of the CFBC, the voidage decreases with the vertical position along the riser. Modeling procedure. The model considers that the CFBC is divided into two regions: a dense lower region with a constant suspension density (turbulent fluidized bed) and a more dilute upper region with a decaying suspension density with height. Detail related to the gas-solid structures chosen to represent two regions of the riser are given below: Lower region of the CFBC.

The lower region is fluidized by the primary air supply. Kunii and Levenspiel’, Saraiva et al. ‘O,and Kwaulk et al. ’’treated the lower region of CFBC using the models developed originally for bubbling fluidized beds. This is inconsistent with the fact that the gas superficial velocity in this region is usually higher than a certain critical value, U,, where the region becomes turbulent18. At this condition, solid velocity, bubble diameters and velocities are quite different from the bubbling regime7,18. However, for simulation purposes, perfect mixing between the solids and the gas phases is assumed in this region. Under these conditions, the mean voidage of the dense region is considered constant and may be obtained using the correlation proposed by Kunii and Levenspiel’. Upper region of the CFBC. The upper region is suspended both by the combustion gases from the lower region and the secondary air supply which determines the boundary between the two regions. Hydrodynamic models, as proposed in most CFBC literature regarding the upper region, are classified into three broad groups’: (1) those predicting the axial profile of the solids suspension density but failing to predict the radial variation; (2) those assuming two or more regions considering either the core annulus or the

Circulating

cluster models to predict the radial variation; (3) those applying the fundamental equations of fluid mechanics to model gas-solid flow structure. Type 1 and 2 models, which are lumped models, can be easily coupled with reaction models to simulate a CFBC reactors. On the other hand, type 3 models, which are differential models, become rapidly tedious when coupled to reaction models because of the numerical complexity. For simulation purposes, we chose to apply the type 1 model to predict the mean axial voidage profile in the upper region of the CFBC, assuming that this region consists of two zones: an acceleration zone and a fully developed zone. In the acceleration zone, the axial voidage decreases with the vertical position along the riser’: e * - E(Z) E* -El

=e

-az

(1)

In the lumped modeling approach used in this work, the riser will be divided into a discrete number of intervals. Based on the void fraction variation in the acceleration zone given by eqn (I), the mean value of voidage in a certain riser interval between height Zi_l and Zi can be calculated using the expression proposed by Kunii and Levenspiel’: Ei=E*

1 - -&El

-e*)(exp-“z

-exp-“&-I)

i=2,3 (2)

In the fully developed zone, the mean axial voidage is estimated by the following equation: 1 (3)

E4 =

1+

(PG, U2Ps

where the slip factor Q is19: + = 1+ $

+ o.47fi4’

(4)

r The variation of void fraction illustrated in Figure 1.

with length in the riser is

Reaction model The reaction model allows for the determination of the chemical changes and the heat released during combustion. Since coal combustion in the CFBC is quite complex, only the major steps of coal combustion are considered in the model with some simplifying hypotheses. The general hypotheses of the reaction model along with the modeling procedure is presented below. General hypotheses of the reaction steady-state conditions, the assumptions reaction model are the following:

model. regarding

For the

(I) The coal and limestone are fed into the bottom of the bed at a uniform temperature”. This is largely encountered in industrial units operating at high feed rate, because in these conditions the temperature gradient within the feed is negligible. (2) Since the time required for volatile combustion is very short, the devolatilization process is considered instantaneous and to take place at the bottom of the bed’. (3) Char is uniformly distributed throughout the circulating bed.

fluidized bed reactors: R. Soutdeh-Gharebaagh

et al.

(4) Since char combustion is slower, it is assumed to occur after all the volatile products have been burned2’. This is an acceptable hypothesis considering the very short time required for volatile combustion, (5) Burning coal particle and gas temperatures are considered constant and equal to the bed temperature. This is a simpliying hypothesis considering the fact that the coal particle temperature is higher than the temperature in gas media. (6) The contribution of the cyclone and the circulation loop on the overall combustion process is neglected. Arena et al5 have considered the cyclone as a reaction block in their simulation, but due to the small particle residence time in the cyclone and the lack of excess oxygen in the recirculation loop, the hypothesis appears reasonable. (7) Char particles are assumed to bum with a constant diameter. This diameter is the mean char particle diameter based on the experimental particle size distribution. (8) The attrition rate constant for char particles in the CFBC is smal15. Therefore, the attrition-assisted combustion rate is deemed negligible. (9) The effects of the primary fragmentation of coal and the secondary fragmentation of char in the overall coal combustion process are neglected5. (10) Any char particle size reductions caused by ash particles or the walls of the CFBC are neglected. For simulation purposes, the comModeling procedure. bustion of coal particles can be modeled using the following reactions:

(1) devolatilization and volatile combustion; (2) char combustion; (3) NO, formation; (4) SO2 absorption.These reaction steps occur in the different regions of the riser which can be divided into a number of individual reactors. To carry out the required calculations for each of those reactors, ASPEN PLUS reactor blocks were selected and combined in a program flowsheet representing the CFBC. The CFBC riser is divided into two regions: a lower region and an upper region. The lower region is represented by a single CSTR (continuous stirred tank reactor), while in the upper region a plug flow regime for both gas and solid phases is assumed. A series of CSTR reactors are used to simulate the corresponding plug flow regime in the upper region2’. The number of CSTR in series is determined based on the hydrodynamic description of the upper region. As mentioned previously, this region is divided into two zones, a fully developed zone and an acceleration zone. One CSTR reactor simulates the fully developed zone. Since the height of the acceleration zone predicted by model is relatively high with a considerable solid fraction variation, this zone is then modeled using two CSTR reactors with a different mean solid fraction for each reactor. With these arguments, the use of four CSTR reactors in ASPEN PLUS is justified. Figure I shows the mean solids fraction (1 - Ei) corresponding to the four reactors (lower region and three sections of the upper region). The reactors are numbered as 1 for the lower region reactor and 2, 3 and 4 for the three upper region reactors. Description of reaction steps involved in each reactor, with the corresponding ASPEN PLUS unit operation blocks, are presented below.

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fiuidized

Reactor number .j................................ I I

I (l-e3

I I

- -

-MepnsolidfktionUinthekm#tion

@

Upper&on

@

I

et al. hydrogen content of the coal is found in the volatile matter. The volatile carbon fraction (X,) reacts to form CO only during the volatile combustion process because of the oxygen depletion in the lower region of the riser. (ii) The coal hydrogen content is entirely consumed during the volatile combustion process. (iii) The coal sulfur content is assumed to be converted completely to SO2 during the volatile combustion process. Char combustion kinetic model. The char particles resulting from the devolatilization process consist of the remaining carbon fraction (1 - X,) and ash only. These particles are then burned to produce a mixture of CO and CO*. Three main reactions for char combustion are considered here 24:

c+@**co

c+co*=+2co

_--

1(l-e,) I

I I I I

;

Lowetregion 0

+

b

Solid fraction,(1e)

Figure 1

Variation of

void fraction with height in the riser

Devolatilization and volatile combustion. When coal is introduced into a CFBC, it decomposes into two parts: hydrogen-rich volatile and char. The char remains in the bed and burns slowly. Based on the plume model, coal devolatilization and complete combustion of the volatile occur at the feed entry point23. Two steps will then be considered in the simulation: decomposition and volatile combustion. Decomposition. In this step, coal is converted into its constituting components such as carbon, hydrogen, sulfur, nitrogen and ash. This step occurs in the lower region reactor only and RYTELD (ASPEN PLUS yield reactor) is used to model this process by speciying the yield distribution vector according to the coal ultimate analysis. Volatile combustion. To simulate the volatile combustion step, three reactions are considered in the model:

= PcharrC(

1 -

fi)

EC)Fsolid,

i

CO,

H2 + $02 * H20 These reactions occur in the lower region reactor only where the coal is introduced and RSTOIC (ASPEN PLUS Stoichiometric reactor) is used to model the volatile combustion process. The combustion of the volatile matter is based on the following hypotheses: (i) Considering that the volatile matter (VM) in the coal, (obtained from a proximate analysis) consists exclusively of carbon, hydrogen and sulfur, the fraction of total coal carbon associated to volatile combustion is given by X, = VM - H - S, where H and S are the fraction of hydrogen and sulfur in the coal. This supposes that the entire

77 Number

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(5)

k,, can be expressed by an Arrhenius form as follows: k,, = kolexp The following equation is used to calculate the mean particle radius based on the experimental particle size distribution: 1 t

s+o**so*

Fuel 1998 Volume

i( 1 -

3v02kcrFchar, rl,i

(7)

rc= m

c+$**co

330

These reactions occur in the entire riser, hence in the four CSTR reactors, and RCSTR (ASPEN PLUS CSTR reactor) is used to model this process. This block requires the knowledge of the reaction kinetic model which is presented below. The first and third reactions are heterogeneous and the second is homogeneous. Since the temperature of the burning particles in the CFBC is not sufficiently high, the effect of the third reaction on the combustion rate is 10w*~, and this reaction is neglected in the model. For the remaining two reactions, the reaction rate expressions must be developed. The first reaction is a gas-solid reaction and the chemical changes take place on both the external and the internal surface of the char particles’. The following expression for the char combustion rate, to form CO, per unit volume of the ith interval is obtained25.

r,(k)

Carbon monoxide produced during the heterogeneous combustion of char reacts with 02 in the homogeneous gas phase reaction to form CO*. Factors contributing to CO emission levels are the bed temperature, 02, CO and Hz0 concentration. The following ex ression is used for the CO combustion rate in the model 2g : rco,i=

1.18* x

10’3f&6~~o( &)exp

(-F)CEi

NO, formation.

(8)

Staged combustion remains an attractive

Circulating fluidized bed reactors: R. Soutdeh-Gharebaagh

method for reducing NO, emissions in various combustion systems. For staged combustion in a CFBC, the air used for the combustion is divided into two or more streams: the first one is supplied through the bottom air distributor and secondary air streams are injected in the upper region of the riser. NO, formations in combustion processes result from a combination of a thermal generation process and fuel nitrogen oxidation. At very high temperatures, thermal generation of NO, from the air nitrogen becomes very important, while at low temperatures found in a CFBC, the dominant source of NO, is fuel nitrogen oxidation. It is also important to emphasize the complexity involved in NO, chemistry within the CFBC because of many catalytic reactions involving, for example, char, ash and sorbent particles. Therefore, the total NO, formation in the CFBC can be calculated by the following formula which considers the thermal generation and fuel nitrogen oxidation as detailed below: ]N0,1,,,,1 = ]NOx]thermar+

~1WQlfuel

V205, is often present in fly ash from heavy oil combustion, for example. However, in our case such an element was not present and it is therefore correct to assume negligible SO2 to SO3 conversion. Since CaCOs is unstable under CFBC conditions, the calcination process is assumed to occur instantaneously and completely in the lower region of the bed. The second reaction, representing the SOi capture in the riser, is considered to occur in both the lower and the upper regions. The corresponding fractional conversion for SO2 (Xso,, i) is calculated using a Fortran program according to the CaO conversion model presented below. RSTOIC is then used to model the capture of sulfur in the riser from the calculated value Of Xso*,i. The fractional conversion of CaO to CaS40 is strongly affected by the physical and chemical properties of limestone, hydrodynamic parameters, mass transfer resistance, temperature, reactive concentration, particle conditions, and can size distribution (PSD) and operatin % from the following be calculated according to Couturier expression:

where cy, = Overall fuel nitrogen

to NO, conversion

1+

factor

Vcao -I __,

x CaO,i’ X(O
et al.

< 1)

3acyS02,i

(e”” - 1)

R,Kv

-- 1

RS

‘I

3aCYso,,i KV (9)

Thermal generation ([NO,] thermal). Three main reactions are used to represent this process in the model:

Considering the ideal gas law for the combustion products in the riser, the total gas concentration is expressed by: P C=---.RlTb

;N~+&*NO

(10)

The values of parameters N2 + &02 * N20 REQUIL (ASPEN PLUS equilibrium reactor) is used to predict the amount of thermal NO, formed during coal combustion based on equilibrium conditions considering the nitrogen present in the riser. Fuel nitrogen oxidation ([NO,] fuel). The NO, formation via fuel nitrogen oxidation is modeled using the following overall reaction:

a I and a! may be written as*‘:

a, = 3.33 * 10e4eyR\

(11)

CY= 35D”.3 P

(12)

Using eqn (9), the moles of SO2 removed per unit v,Ollume become

VCaOFl

rso~*i =

1 _

E,Au

*

100

1+

3oCYsoz,,

(e”” - 1)

R&v RSTOIC block is used to calculate the fuel nitrogen oxidation with a given value of o, which is taken from the literature. The NO, formation calculations are then applied in each of the four reactors using the combined REQUIL and RSTOIC blocks. SO2 absorption. The SO2 capture by limestone represented by the following ureactions:

can be

CaCOs =+ CaO + CO2

CaO + SO2 + &

3 CaS04

The formation of SOI to SO3 is assumed to be instantaneous. In CFBC reactors, the maximum concentration of SO3 is governed by the thermodynamic and kinetic considerations. Equilibrium conditions predict a certain conversion of SO2 to S03. However, kinetic considerations predict very a small reaction rate without the presence of a catalyst for the SO2 to SO3 conversion. Such a catalyst,

X

(13) 3aCYS02,i -

j&

I

If the sorbent particles in the bed are well mixed, their residence time is independent of particle size*‘. Therefore, the mean residence time is expressed by ?I =W%p-

ALI 6

and

(15) where (lo)

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331

Circulating

Table

fluidized

1

R. Soutdeh-Gharebaagh

bed reactors:

The reactor

models

description

utilized

in

et al.

the

simulation’5”6 Reactor block

Description To simulate a reactor by speciying yield distribution data or correlation when reaction stochiometry and kinetics are unknown To simulate a reactor with the unknown or unimportant reaction kinetic and Imown stoichiometry by speciying the extent of reaction or the fractional component of the key component To handle any number of simultaneous or series reactions To model CSTR reactors with known reaction kinetic To require user supplied kinetics subroutine when solids, such as char, are participating in the reactions To calculate simultaneous phase chemical equilibrium by solving stoichiometric chemical and phase equilibrium equations To be convenient to the known reaction stoichiometry when only a few reactions approach equilibrium

RYIELD

RSTOIC

RCSTR

REQUIL

Table 2

OnceGo,, i is calculated for the ith reactor, it is used as the fractional conversion of the key component necessary to run the RSTOIC block corresponding to this reactor. Calculations start at the first reactor (lower region) and continue upward until the top of the riser. SIMULATION

RESULTS

AND MODEL VALIDATION

The process simulation program for a CFBC was developed using four ASPEN PLUS reactor blocks-KYIELD, RSTOIC, RCSTR and REQUIL-to represent the phenomena identified in the coal combustion process. A detailed description of the ASPEN PLUS reactor blocks along with their re uirement is given in the ASPEN PLUS user manualsq5,t6. A brief description of the reactor blocks is given in Table 1. Table 2 presents the reactor model parameters and input variables required for the simulation. Considering the reaction and hydrodynamic models, the entire CFBC system is divided into three sub-flowsheets: lower, upper and sep-flowsheets. The first sub-flowsheet represents the dense region, the first reactor of the riser, where the phenomena associated with coal devolatilization and volatile combustion, char combustion, NO, formation, limestone calcination and SO2 capture take place. The

The reactor model parameters utilized in the simulation Reactor block

Input variables

(1) RYIELD

Tbr

(2) RSTOIC

Tb, P, Xc, Xn, Xs chemical

(3) RCSTR

Ts, P, ri,,, rco,, chemical reactions

(3) NQ formation

(4) REQUIL

Tb, P chemical

(4) SO* capture

(5) RSTOIC

Tbr

Phenomena (I) Devolatilization

and volatile combustion

(2) Char combustion

Since SO2 is well mixed in each interval overall SO* balance gives

of the bed, an

-5 @so,, I - rso,,I)

Ysoz,I =

(17)

GUI

and YSO*,i

WRso,,i -

rso2,J i

z

(18)

1

=

cu2

where

(19) and R so*,i = The eqns The then

(1 - Xso,, i - I Yc

32AAL

wsi#l

(20)

value of Yso2,i is calculated by simultaneous solving of (13) and (17) for i = 1, or eqns (13) and (18) for i f 1. fractional sulfur capture for each reactor (Xso,J can be calculated from

(21)

&02.i=1-

332

[ Fc,j$fzi_,J

Fuel 1998 Volume

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(22)

p.

p,

Fti)

&CO,

3

reactions

reactions X,o,. i chemical reactions

second sub-flowsheet represents the dilute region of the riser which is divided into three intervals; each one represented by an individual reactor. Since the devolatilization and volatile combustion process is assumed to take place exclusively in the lower region, only char combustion, NO, formation and SO2 capture are considered to occur in each reactor of the upper region. The last sub-flowsheet contains two unit operation blocks, CYCLONE and FSPLIT. CYCLONE is used to represent the gas/solid separation at the riser outlet. To maintain the required level of solid inventory in the bed, a solid drain valve, represented as FSPLIT in ASPEN PLUS, is used. The resulting solid stream from CYCLONE is fed to FSPLIT where it is divided into two streams; the first one is recycled into the lower region of the riser and the second one exits the system to satisy the material balance. Along with the unit operation blocks provided by ASPEN PLUS, several complete Fortran programs and an external subroutine for the kinetic models were used in the simulation. The Fortran codes contain the following four blocks which are required to complete the model. The first is the external kinetic subroutine block, ‘KINETIC’, developed for both heterogeneous gas/solid and homogeneous gas phase reactions. The second Fortran block, called ‘KESTIME’, when integrated with the ASPEN PLUS input file, calculates the residence time of char particles in the CFBC. This calculation is required in order to execute the ‘KINETIC’ subroutine. The third block, ‘HYDRO’, is inserted into the ASPEN PLUS input file to calculate the mean void fraction in each section of the upper region and in the dense bed of the riser. The fourth block of Fortran codes,

Circulating

B2

~2,

B3

fluidized

-

&B4

Bl7

s2n

FSPLIT

??

B16

#s&y

CYCLOM

simulation

diagram

$1 ‘I

B9

z

BS S1Q

RSm1c

-

REQUIL

for the CFBC

Value of the fixed parameters used in the simulation

Gordon and Amundsonz4 Gordon and Amundsot? Couturie? Wang’ Couturier” Wong6 Wang’ Wang’ Gordon and Amundson24 Desai et a1.27

El = 1.247*10* (J kmole-‘) kO, = 1.55*10’ (m s-‘) Kv = 8*10e4 [kmole (m’ s-‘)-‘I Vcao = 1.69*10-’ (m’ kmole-‘) y = - 0.0226 Ec = 0.30, E, = 0.52 pchar = 1500 (kg m-‘) pL = 2710 (kg m-‘) ps = 800 (kg m-‘) A = 0.13 m2 CFBC geometery L = 6.7 m Dr = 0.405 m

and output

Input variables Cross-sectional area (A) Height of the bed (L) Height of the dense bed (L,) Superficial gas velocity Solid circulation flux (Gs) Temperature (Tb) Pressure (P) Coal (feed rate, PSD, analysis) Limestone (feed rate, Ca/S, PSD) Air (flowrate, SIP, composition)

variables

Table 5 Run

Source

Parameter

Kinetic constants, physical properties and fixed parameters value

R4

All squareblocksarc givenby ASPEN PLUS

A comprehensive

List of the input

Rl

mdro,IMtimcdKilldics~)

a

Table 4

BS

et al.

HYDRODYNAMIC AND KINETIC MODELS

I-

Table 3

s4

R. Soutdeh-Gharebaagh

:

1

Figure 2

bed reactors:

of the model

Output variables Combustion efficiency Sulphur capture efficiency NO, and CO emission levels Outlet O2 concentration and flow rate Hydrodynamic parameters positions and voidages)

(interval

02 and CO concentrations

profiles

Outlet gas stream composition and flowrate Outlet solid stream composition and flowrate

‘SO2’, calculates the sulfur capture efficiencv in each section of the upper region aid in the dense bed. A comprehensive simulation diagram for the CFBC is illustrated in Figure 2. Table 3 gives the value of the parameters used in the simulation. The input and output variables of the process simulation program are summarized in Table 4.

The CFBC

operating

Th

6)

1140 1106 1146 1155 1155 1187 1180 1192 I183 1155 1152 1109 1105 1104

cab

Fcoai

(kg h-‘) 1 2 3 4A 4B 5 6 7 8 9 10 11 12A 12B

conditions”

Data

67.30 70.20 64.60 74.90 62.10 61.20 60.40 65.10 63.30 66.60 66.30 70.00 69.80 70.00

(k;‘?) 19.20 15.90 13.20 23.50 16.10 17.60 16.60 17.90 17.80 17.90 18.10 18.20 18.00 18.70

F,,,

SIP

LI (m)

0.45 0.43 0.43 0.43 0.43 0.42 0.41 0.85 0.85 0.86 0.86 0.84 0.85 0.85

1.37 2.59 2.59 1.37 1.37 2.59 2.59 1.37 1.37 1.37 2.59 2.59 1.37 I .37

(kg h-‘) 2.28 1.70 1.61 2.38 1.97 2.13 2.07 2.10 2.10 2.10 2.06 1.91 2.08 2.15

799.0 832.0 778.0 807.0 796.0 757.0 749.0 768.0 773.0 792.0 791.0 836.0 734.0 831.0

Simulation convergence One important feature of a CFBC is the recirculation of solids, captured by the cyclone at the top of the riser and recycled back to the base of the riser. Therefore, the simulation flowsheet, which contains the recycle loop, must be solved iteratively and the tear streams, convergence methods and calculation sequence must be specified. ASPEN PLUS can perform all these functions automatically or the user can supply them. To achieve convergence of the recirculation stream in the simulation, we used the classical bounded Wegstein method, which normally converges rapidly15. It should be mentioned that for convergence to occur, the value of the tear stream variables needs to be correctly initialized. Such an initialization will enable a rapid convergence of the tear streams. Thus, to initialize the tear stream variables (see Figure 2), a greater G, value was considered for the initial tear stream flux. Since the char conversion during one pass in the riser is less than lo%, the initial amount of char in the tear stream was considered

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Circulating fluidized bed reactors: R. Soutdeh-Gharebaagh

et al.

Q8 1000 !z B 2

800

F .fi

800 400

0 94

92

90

Q8

Q8

100

Expeflmental Combustion Efficiency(W) Figure 3 efficiency

Between the predicted and experimental combustion

0

Equation24 (proposedcorrelation)

0

Equation8 (originalcorrelation)

g 200 8 150 t k 100 50 0 L 50

100

mntal Figure 4 co

150

200

250

300

350

co @pm)

Comparison between the predicted and experimental

approximately 10 times the carbon fraction in the coal feed rate. This procedure ensured a rapid and stable convergence process. Model validation In order to validate the proposed model, 14 different sets of operating data from various CANMET runs*’ were used to validate the simulation (see Table 5). A detailed description of the CANMET 0.8 MWth CFBC pilot plant is presented by Desai et ~1.~~.The predicted simulation results in terms of combustion efficiency, emission levels of CO, SO2 and NO, and 2O and CO concentration profiles are compared with the experimental data. The results are detailed below.

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Fuel 1998 Volume

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I

1

I

I

I

I

400

800

800

1000

1200

1400

Waa Figure 5 so2

so2 @pm)

Comparison between the predicted and experimental

vc=l-

250

0

I

200

Combustion eficiency. In order to estimate combustion efficiency, the two outlet streams, S20 and S22 (see Figure 2), are used. These streams contain small amount of unburnt char particles that controls the combustion efficiency (vc), which is defined as

350 300

0

4

Total rate of carbon in the outlet stream ( Total rate of carbon in the feed stream 1 (23)

Thirteen sets of expenmental data reported values for the combustion efficiency were used to compare with the model predictions. In Figure 3, it is found that the model consistently overpredicts the combustion efficiency. The differences between the predicted values and experimental data, which are less than 3%, are related to the value calculated for the cyclone efficiency. ASPEN calculated 99.99% efficiency for the cyclone used in the pilot plant, which is generally higher than that reported experimentally. Consequently, the carbon content of the fly ash predicted by the model becomes substantially smaller than the experimental value. This smaller amount of carbon in flyash causes the model to overestimate the combustion efficiency. CO emission levels. Although CO combustion rates have been widely studied1*6*24,2 , the extension of these expressions to CFBC conditions is limited. The validity of the proposed CO combustion rates from the literature was examined by inserting them into the simulation program. Following the simulation results, a new correlation, similar to the Robinson’s expression26, with two adjustable parameters wa;proposed to predict the CO range reported by Desai et al. :

(24) with /3, = 1.8 * lOI p* = 0.21

Circulating

These parameters were obtained by fitting the CANMET experimental data. However, more data from various sources are required in order to confirm this correlation. The CO emission levels predicted by the model ranged from 119 to 271 ppm, while the experimental data varied between 112 and 3 16 ppm. Therefore, the model based on the new correlation estimates CO emission levels relatively well. The comparison between predicted and experimental CO levels is presented in Figure 4.

ii

%

200 150

100

0 0

50

100

150

200

250

300

350

Ew=tm~tNO,(ppm)

Figure 6

Comparison

between the predicted

R. Soutdeh-Gharebaagh

et al.

NO, emission levels. As mentioned earlier, two formation mechanisms were considered in the modeling of NO, formation in the CFBC: thermal generation and fuel nitrogen oxidations. Thermal generation was calculated considering equilibrium conditions, while NO, formation from fuel nitrogen oxidation was calculated using an overall conversion factor (cY~)from the literature. Since the aim of this work was not to study the NO, formation and reduction processes in detail, this overall approach was taken to simulate the fuel nitrogen oxidation. Fuel nitrogen conversion entails relatively complex reactions schemes involving several heterogeneous reaction steps and therefore attains a lower overall conversion26. Typical values of fuel N2 to NO, conversion factors, as reported by Legros et CZZ.*~ and Becker et d3’, vary approximately between 0.05 to 0.25, depending on coal properties, feed particle size distribution, excess air level and operating conditions. In our simulation, a value from that interval, which gave the best agreement between predicted and experimental NO, was chosen as the overall conversion factor. As reported in most CFBC literature, the results also confirmed that thermal NO, formation, which leads to between 18 and 65 ppm of NO,, is unimportant compared to that of fuel nitrogen oxidation which approximately lies between 84 and 104 ppm of NO,. The predicted emission levels ranged from 130 to 267 ppm, while NO, emissions for the experimental CFBC ranged from 107 to 309 ppm.27. Figure 6 appears to indicate a reasonable agreement between predicted and experimental NO,. The difference between experimental data and those of the simulation prediction is attributable to the fact that a constant value of CY I = 0.05 is used throughout the entire simulation. In recent years, several comprehensive studies have been reported6.3 ’-34 regarding NO, formation and reduction processes. These were conducted to develop an improved understanding of the fundamental nature of NO, chemistry and underlying physical processes in CEBCs, and to support the needs for experimental work in this field. Emphasis is

8 %

bed reactors:

observed between predicted and experimental SO* concentration in the flue gas.

SO* emission levels. The Ca/S molar ratio ranged between 1.6 and 2.3 for the various runs considered. Such values of Ca/S are usually considered sufficient to achieve reasonably high sulfur capture efficiencies. Without using any fitting parameters, Figure 5 shows the close agreement

‘:

fluidized

and experimental

NO,

9

8

6-

.g

5-

_ 2500 Redi*edCOConcartration(ppm)

0

-

8 2000

E

p

i E

$!' 3-

2-

0 .. *.'..Q

l0 0

I

I

I

I

1

2

3

4

- 1500

E

- 1000

0" "

- 500 _. .... .-...._._.. 00 I I 5

6

BedHeight

Figure 7

O2 and CO concentration

profiles within the CFBC predicted by the model

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Circulating

fluidized

bed reactors:

R. Soutdeh-Gharebaagh

also given to develop reliable techniques to control NO, emissions from fluidized bed combustion. For example, many published studies suggest that NO, emissions could be controlled by adding chemical components such as carbon monoxide, char hydrogen, ammonia, unburnt hydrocarbons and limestone due to the catalytic reactions found in CFBC32V33. The emission data 02 and CO concentration profiles. from the CANMET CFBC pilot plant used to validate the model consisted only of flue gas concentration and did not include the various gas concentration profiles along the riser. However, since the model can predict these concentration profiles within the riser, oxygen and carbon monoxide profiles were chosen to be compared qualitatively with data from the literature. The overall trends observed in experimental concentration profiles along the riser height are in close agreement with those predicted by the model. In the lower region a significant change in the oxygen concentration is found, while in the upper region there is a gradual decrease in the oxygen concentration. The CO concentration is constantly high in the lower region, while it sharply decreases in the upper region due to the injection of secondary air. Typical O2 and CO concentration profiles provided by Hansen et a1.35 and experimental data reported by Brereton et al.33 and Grace et al.34 are similar with those predicted by the present model. In Figure 7, the predicted profiles are presented. Due to the relatively high dense bed found at the bottom of the CFBC reactor, Brereton et al.33 and Grace et aZ.34 have not measured the O2 and CO concentrations. Therefore, the experimental data have only been reported for the upper region. Since the operating and bed design data reported in those references differ with that of CANMET, the predicted concentration profiles have been compared qualitatively with the trend reported in these references. CONCLUSION

et al.

providing a scholarship to Mr R. Sotudeh-Gharebaagh. Helpful discussions from F. Preto and E. J. Anthony are also appreciated. We greatly acknowledge Aspen Technology for having granted special permission for the use of the ASPEN PLUS under the condition of the academic licensing agreement.

REFERENCES 1

2

3

4 5

6

7

8

9

10

A model was developed for the combustion of coal in a circulating fluidized bed using the ASPEN PLUS simulator. To provide such a CFBC model, several ASPEN PLUS unit operation blocks were combined and, where necessary, kinetic expressions and hydrodynamic model were developed using data and models from the literature. The developed models were then inserted into the flowsheet to provide a complete representation of the CFBC. The resulting model was used to predict the performance of the CANMET CFBC pilot plant in terms of combustion efficiency, emission levels of CO, SO2 and NO,, and 02 and CO concentration profiles. The predictions of CO and NO, were achieved using two and one fitting parameters, respectively. The agreement between the model prediction and experimental data is satisfactory but more experimental data are still required to confirm the proposed CFBC model in order to make it more comprehensive and reliable. The model can now be used to represent a CFBC unit in various process simulation flowsheets such as power generation plants.

11

12

13 14

1.5 16 17

18

ACKNOWLEDGEMENTS

19

This project was supported by CANMET, part of Energy, Mines and Resources, Canada. This financial assistance is gratefully acknowledged. Special thanks are due to the

20

Ministry

336

of Culture

and

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Congalidis, J. P. and Georgakis, C., Multiplicity patterns in atmospheric jluidized bed coal combustors. Chem. Engng Sci., 1981, 36, 1529. Weiss, V., Fert, F. N., Helmerich, H. and Janssen, K., Muthematical modelling of circulating jluidized bed reactors by reference to solid decomposition reaction and coal combustion. Chem. Engng Prog., 1987, 22, 79. Basu, P., Sett, A. and Gbordzoe, E.A.M., A simplified model for combustion of carbon in a circulating fluidized bed combustor, in FBC comes of Age, ed. J.P. Mustonen. ASME, New York, 1987, pp. 738-742. Lee Y.Y. and T. Hyppanen, in FBC Technology for Today, ed. A.M. Manaker. ASME, New York 1989, pp. 753-764. Arena, U., Malandrion, A. and Massimilla, L., Modelling of circulating jluidized bed combustion of a char. Can. J. Chem. Engng, 199 1,69,860. Wong, R., Modelling the hydrodynamic of circulating fluidized bed risers. M.A.Sc Thesis, the University of Calgary, Canada, 199 1. Berruti, F., Chaouki, J., Godfroy, L., Pugsley, T. S. and Patience, G. S., The hydrodynamics of circulating fluidized beds: a review. Can. J. Chem. Engng, 1995,73, 579. Senior R. C., Circulating fluidised bed fluid and particle mechanics: modelling and experimental studies with application to combustion. Ph.D. dissertation, The University of British Columbia, Vancouver, Canada, 1992. Kunii D. and Levenspiel, O., Flow modelling of fast fluidized beds, in CFB Technology III, ed. P. Basu, M. Horio and M. Hasatani. Pergamon, Oxford, 1991, pp. 91-98. Saraiva, P. C., Azevdo, J. L. T. and Carvalho, G., Mathematical simulation of a circulatingjuidized bed combustor. Combust. Sci. Technol., 1993, 93, 233. Kwaulk, M., Ningde, W., Youchu, L., Bingyu, C. and Zhiyuan, S., Fast Fluidization at ICM, Circulating Fluidized Bed Technology, 1987, pp. 33-45. Young, B. E., Technico-economic evaluation of atmospheric fluidized bed combustion in steam production. M.Sc.A Thesis, Queen’s University, Canada, 1986. Paffenbarger, J., Analyse des Procedes a Lit Fluidise avec ASPEN et USRFBC. CERCHAR, France, 1991. Wysk, S. R., Modelling a LURGI circulating fluid bed using ASPEN. ASA 82-11, Combustion Engineering, Inc., Windsor, 1982. Aspen Technology, ASPEN PLUS Solids Manual. Cambridge, MA, 1988. Aspen Technology, ASPEN PLUS Notes on Inte$aces and User Models. Cambridge, MA, 1985. Grace, J. R., Contacting modes and behaviour classification of gas-solid and other two phase suspensions. Can. J. Chem. Engng, 1986,64,353. Chehbouni, A., Chaouki, J. Guy, C. and Klvana, D., Characterization of the flow transition between bubbling and turbulent fluidization. I. and EC RESEARCH, 1994, pp. 1889- 1896. Patience, G. S. and Chaouki, J., Gasphase hydrodynamic in the riser of a circulating jiuidized bed. Chem. Engng Sci., 1993,48, 3 195. Couturier, M. F., Sulphur dioxide removal in fluidized bed combustors. Ph.D. Dissertation, Queen’s University, Kingston, Ontario, Canada, 1986.

Circulating

21

22 23

24 25

26 27

28

29

30

31

32

33

34

35

Rajan. R., Krishnan, R. and Wen, C. Y., Simulation of fiuidized bed combustors-part II. In Fluidizatioti application to coal conversion process. AIChE Sym., 1978, 74, 112. Levenspiel, O., Chemical Reaction Engineering. 2nd ed. Wiley, New York, 1972. LaNauze R. D., in Fundamentals of Coal Combustion, in Fluidization, 2nd ed., ed. J. F. Davidson, R. Clift and D. Harrison. Acadamic, New York, 1985, pp. 63 l-674. Gordon, A. L. and Amundson, N. R., Modelling ofjuidized bed reactor--IV. Chem. Engng Sci., 1978,31, 1163. Sotudeh-Gharebaagh, R., Simulation of a circulating fluidized bed combustor using ASPEN PLUS. M.Sc.A Thesis, Ecole Polytechnique de Montreal, Canada, 1994. Robinson, W. D., The Solid Waste Handbook: a Practical Guide. Wiley, New York, 1986. Desai, D. L., Lau, I. and Anthony, E. J., Study of NzO formation in CRL’s circulating fluidized bed combustor. Final report, ERL’s, CANMET, Ottawa, 1991. Desai, D. L., Friedrich, F. D. and Lee, C. K., Pilot-scale circulating fluidized bed combustion research facility at CCRL’s. CANMET, Ottawa, 1990. Legros, R., Brereton, C. M. H., Lim, C. J., Li, H., Grace, J. R. and Anthony, E. J., in Combustion characteristics of different fuels in a pilot scale circulating fluidized bed combustor. 12th International Conference on FBC, Proceedings, Vo1.2, ed. Lynn N. Rubow. ASME, New York, 1993, pp. 66 l-666. Becker, H. A., Code, R. K., McCleave, R. and Stephenson, J. R., Pilot plant studies of fluidized coal combustion. Ontario, Technical Report QFBC.TR.85. I, Kingston, Canada, 1985. Zhao, J., Nitrogen oxide emissions from circulating fluidized bed combustion. Ph.D. Dissertation, University of British Columbia, Vancouver, Canada, 1992. Furusawa, T., Koyama, M. and Tsujimura, M., Nitric oxide reduction by carbon monoxide over calcined limestone enhanced by simultaneous sulfur retention. Fuel, 1985, 64, 413. Brereton, C., Grace, J. R., Lim, C. J. Zhu, J., Legros, R., Muir, J. R., Zhao, J., Senior, R. C., Luukos, A., Numaru, N., Zhang. J. and Hwang, I., Environmental aspects, control and scale-up of circulating fluidized bed combustion for application in western Canada. University of British Columbia, Final report, prepared for Energy, Mines and Resources Canada, 199 1. Grace, J. R., Brereton, C. M. H., Lim, C. J., Legros, R., Zhao, J., Senior, R. C., Wu, R. L., Muir, J. R. and Engman, R., Circulating fluidized bed combustion of western Canadian fuels. UBC, Final report, prepared for Energy, Mines and Resources Canada, 1989. Hanson, P. F. B, Dam-Johansen, K., Bank, L. H. and Ostergaard, K.. Sulphur retention on limestone under fluidized bed combustion conditions-an experimental study. Proceedings of the 11th International Conference on FBC, ed. E. J. Anthony. ASME, New York, 1991.

NOMENCLATURE

c Cd?

CO? DP D, El

W) F,,‘

cross-sectional area of bed (m’) decay constant (m-l) parameter defined in eqn (9) (s-l) unit operation blocks given by ASPEN PLUS, Figure 2, (I = 1, 2, 3,...,17) combustion gas concentration (kmole m-‘) calcium to sulfur ratio concentration of oxygen (kmole m -‘) average sorbent surface particle diameter (cm) riser diameter (m) apparent activation energy (J kmole-‘) yield distribution vector mass Rowrate of air (kg h-‘)

fluidized

bed reactors:

R. Soutdeh-Gharebaagh

et al.

Fat,I

primary air mass flowrate (kg h-‘) secondary air mass flowrate (kg h-‘) mass flowrate of coal (kg s-‘) Fc flux of the char particles entering the ith interval (kg s-‘) FdlK, mass flowrate of coal (kg h-‘) FL-,,, mass flowrate of limestone in the feed (kg s-‘) Fl F lhnr mass flowrate of limestone in the feed (kg h_-‘) F \“ld., flux of solids entering the ith interval (m- s ‘) mole fraction of CO fco mole fraction of Hz0 fH!O mole fraction of O2 fo2 Froude number F, particle Froude number F* net solids circulation flux (kg mm2 riser s-‘) G, reactor number i volumetric rate constant [kmole (m’ s-‘)-‘I IK” pre-exponential factor (m s-‘) kol k chemical reaction rate constant (m s-‘) LL’ height of the bed (m) height of dense bed (m) LI P bed pressure (atm) weight fraction vector of char particles in the recirculation stream P(k) R universal gas constant [kcal (kmole K-‘)-‘I universal gas constant [atm cm-3 (gmole K-‘)-‘I RI RI four reactors representing the riser (I = 1,2,3,4) universal gas constant [J (kmole K-l)] 4 mean sorbent particle radius (cm) RS Rso,., rate of SO2 per unit volume of the ith interval (kmole me3 s-‘) mean coal particle radius (m) rc coal particle radius vector (m) rc(k) CO combustion rate per unit volume of the ith interval YC0.I [kmole (m’s_‘)-‘] char combustion rate per unit volume of the ith interval r1.r [kmole (m’ s-‘)-‘I rso,, mole of SO2 removed per unit volume of the ith interval [kmole (m’ s-‘)-‘I stream number, Figure 2 (J = 1,2,3,. .,22) SJ SIP secondary to primary air ratio bed temperature (K) Tb temperature of the char particles (K) T, mean residence time of sorbent particles in ith interval of the bed (s) t, superficial gas velocity (m s-‘) Ul superficial gas velocity in the dilute bed (m 8) u2 onset of the turbulent regime (m s-‘) UC molar volume of CaO (m’ kmole-‘) vc.0 sulfur weight fraction in the dry-based coal W, fractional conversion of carbon in the volatile combustion xc fractional conversion of hydrogen in the volatile combustion XH fractional conversion of sulfur in the volatile combustion xs fractional conversion of CaS04 in the dense bed &co, fractional conversion of CaO in the ith interval &Tao,, Xso,. , fractional sulfur capture in the ith interval of the riser YSO?., mole fraction of SO2 in the ith interval Z riser height (m) corresponding distance for the ith interval above the lower region Z, (m) corresponding distance for the i - I th interval above the lower Z,-I region (m) Fwr-2

Greek letters external mass transfer coefficient (cm s-‘) overall N? to NO I conversion factor parameter used in eqn (I 1) (cm-‘) hight of the ith interval (m) volume fraction occupied by sorbent particles char porosity porosity of particle after the calcination mean voidage of the lower region mean voidage of the fully developed zone mean axial voidage in the ith interval of the riser axial voidage in the acceleration zone axial voidage at saturated conditions combustion efficiency effectiveness factor density of char particles (kg mm3) density of limestone particles (kg m-‘) density of bed solids particles (kg m-j) slip factor

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