modeling circulating fluidized bed biomass gasifiers

Fuel Processing Technology 86 (2005) 1021–1053

www.elsevier.com/locate/fuproc

Modeling circulating fluidized bed biomass gasifiers.

A pseudo-rigorous model for stationary state

Jose Corella*, Alvaro Sanz

Department of Chemical Engineering, University "Complutense" of Madrid, 28040-Madrid, Spain

Received 11 June 2004; received in revised form 19 November 2004; accepted 19 November 2004

Abstract

A 1-dimensional model for an atmospheric circulating fluidized bed biomass gasifier (CFBBG)

under stationary state is presented in this paper. The model is based on the kinetic equations for the

reaction network solved together with mass and heat balances and with several hydrodynamic

considerations. Kinetics used include both our own kinetic data and published equations with some

corrective factors. The reaction network used involves twelve different reactions. A sub-model for

the tar generation-elimination in the CFBBG is included in the whole model. The model has an

academic structure, but several assumptions were made because of lack of accurate data in some

areas. The overall model has some empirical aspects and can therefore be considered as semi-

rigorous. Hydrodynamics in the model were checked with a survey carried out worldwide among the

existing pilot and commercial CFBBGs. The axial profiles of concentration of ten different species

(H2, CO, CO2, tar, char, . . .) and temperature can be calculated with this model which was conceived

to optimize both design and operation of CFBBGs.

D 2004 Elsevier B.V. All rights reserved.

Keywords: Reaction engineering; Energy; Fluidization; Mathematical modeling; Biomass gasification; Tar

1. Introduction

Thermochemical gasification of biomass generates a useful gas (a mixture of H2, CO,

CO2, CH4, small hydrocarbons,. . .) using a gasifying agent, usually air, also being the only

0378-3820/$ -

doi:10.1016/j.

* Correspon

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ding author. Tel./fax: +34 91 394 4164.

ress: [email protected] (J. Corella).

J. Corella, A. Sanz / Fuel Processing Technology 86 (2005) 1021–10531022

gasifying agent considered in this paper. Commercial biomass gasifiers are nowadays

facing serious problems, especially their economical feasibility: the energy from the

produced or gasification gas has to be competitive with natural gas which is abundant and

cheap. One biomass gasifier which can have some future is the atmospheric circulating

fluidized bed gasifier (CFBBG) with a few commercial units operating in the Netherlands,

Austria, Sweden, Finland and Germany [1]. The produced gas is bdirtyQ (contains some

tar) and usually it is directly fired in an adjoining combustor. Nevertheless, the most

promising future applications of the thermochemical gasification of biomass will require at

least both (i) generating a bquite cleanQ gas (to be fired in gas engines or turbines, for

example), and (ii) having no troubles in the gasifier (with a continuous non-stop

operation). These two facts require that the gasifier has an optimized design and operation

which does not occur very often. Although most gasifier manufacturers may claim that

their respective gasifiers are already optimized, a good model might help to optimize both

gasifier design and its operation. For this reason this work is devoted to develop a model

bas good as possibleQ for CFBBGs.There is huge amount of papers on hydrodynamics of CFBs which are very useful for

modeling CFBBGs, as the book edited by Grace et al. [2]. Concerning the modeling of

fluidized bed gasifiers, the field of coal is well ahead of that of biomass. There are a lot of

works (i.e., [3–16]) on modeling CFB coal combustors and gasifiers which contain very

valuable information and help to model CFBBGs. They were used in different parts of the

modeling of CFBBGs presented here. Nevertheless, it is well known and accepted that

thermochemical processing of biomass has some important differences with respect to the

processing of coal. Two of them are important for the CFBBG modeling: (1) biomass is

much more reactive than coals, it pyrolyzes very quickly and its ash content is usually very

low. For these and other reasons, another solid, sometimes called fluidizing, has to be used

in the gasifier. It is usually silica sand. Besides, an additive (dolomite, limestone,

olivine,. . .) is also used in the gasifier for tar cracking, alkali capture, etc., . . . The particlesize of these two solids (silica sand and additive) is an important variable in the process. (2)

Biomass gasification below 1000 8C always produces important amounts of tar whose

content in the flue gas has to be estimated with a good model for it to be it useful. Literature

on biomass is therefore more important for CFBBG modeling than coal, but it is less

abundant and the existing approaches are not yet as rigorous and developed as those for

coal. The literature on modeling biomass gasification in fluidized bed is much more related

to this work than that of coal but it is so scarce that it can be fully cited.

In modeling biomass gasification (with air) in bubbling fluidized beds (BFBBG),

Belleville and Capart [17] developed an empirical but quite interesting model which was

successfully applied to the biomass gasifier of Creusot Loire in Clamecy (France). Fan and

Walawender [18] and Van den Aarsen [19] reported two of the pioneering models, which

are well known today; Corella et al. [20] modeled some non-stationary states of BFBBGs;

Bilodeau et al. [21] considered axial variations of temperature and concentration and

applied their results to a 50 kg/h pilot gasifier; Jiang and Morey [22,23] introduced new

concepts in this modeling, especially related to the freeboard and the fuel feed rate; Hamel

and Krumm [24] provided interesting axial profiles of temperature, although their work was

mainly focussed on gasification of coal and did not give many details of their model;

Mansaray et al. [25,26] presented two models using the ASPEN PLUS process simulator

J. Corella, A. Sanz / Fuel Processing Technology 86 (2005) 1021–1053 1023

but referred to their specific bdual-distributor-typeQ BFBBG, limiting their usefulness.

Concerning modeling of BFBBGs with steam, Corella et al. [27] presented a model based

on the Kato and Wen model for fluidized beds. The main contribution of their model is that

it identifies, amongst the complex gasification reaction network, the four main (for

modeling purposes) chemical reactions. That model fits then the experimental gasification

data with only four parameters (chemical kinetic constants).

If there are only a few papers on modeling BFBBGs, literature on modeling CFBBGs is

even more scarce. The absence of details in the literature on CFBBG modeling is not

surprising because, besides the very few existing commercial CFBBGs, it was mainly

written for marketing purposes. Models claimed to exist can neither be checked nor used

by readers because most of the key information is missing. Most of the manufacturers and

users of CFB biomass gasifiers at commercial and pilot scales claim to operate a good own

model but not much more is said about it. Lurgi, ECN, TPS, IGT, etc.,. . . for instance,reported to have their own models but they did not provide details of such models. The

UMSICHT Institute in Oberhausen, Germany, [28] and University of Siegen in Germany

too [29,30] provided some data from their own models for CFBBGs, but what is

considered to be the core of such models is again missing from their papers. Kersen et al.

[31] recently provided a model for the pilot CFBBG at ECN but, as the same authors

recognized, it is an interpretation model which cannot be used for design and scale-up

purposes. Finally, the model for CFBBGs recently published by Liu and Gibbs [32], which

were also our partners on the same project that financed the work presented here, is similar

to the model presented in this paper, but theirs is manly addressed to NH3 and HCN

emissions.

A detailed and advanced model for CFBBGs does not exist in the open literature, up to

now. Such a model would be useful to optimize both the design and operation of a

CFBBG. The main aim of this paper is to develop a valuable model for CFBBGs and to

give a description of its main parts or sub-models. Results from the model are being

presented in the next paper [33].

2. Basis of the model

2.1. Topology or description of the considered CFBBG

Atmospheric CFB biomass gasification nowadays is not yet a well established

technology. There are very few commercial gasifiers worldwide and each gasifier

manufacturer (TPS AB, Lurgi, Foster Wheeler Energy, Austrian Energy,. . .) has its owndesign. So far there is no consensus on the detailed design of a CFBBG. The selection

of a standard scheme for a CFBBG was therefore not an easy task. After a detailed

analysis of the existing technology, including the small CFBBG owned and handled by

the authors, the selected scheme for a CFBBG is shown in Fig. 1. Some aspects of it are

the following:

i) Although some CFB coal gasifiers do not have a dense bed at the bottom, the

CFBBG considered here has a bottom bed, which is quite important in biomass


gasification. It increases the heating transfer rate to the particles of biomass, and

decreases the tar yield [34]. Among the CFBBGs analysed by the authors, the ones

with a stationary bottom bed and a biomass feeding into it generate less tar than if

there is not such bottom bed or if the biomass is fed above it. An additive (D), such

as calcined dolomite (OCad OMg), limestone or related materials, is also considered

to be as stationary, permanent or fluidizing material, together with the silica sand (S).

This additive decreases the tar yield at the gasifier exit and prevents bed

agglomerations [35–37].

ε = 0.77

ε = 0.99

ε = 0.90Transition Zone

Htz

Bottom ZoneH

bt

HT

Biomass Feed

2nd Air

1st Air

Gas

H1

Pyrolysis

Mixing 2nd Air

H3

H2

H4

Dilute ZoneH

dz

H2nd

Fig. 1. Scheme for the selected CFBBG to be modeled.


ii) Biomass feeding point is located at the bottom of the gasifier, the biomass is fed

directly into the bottom bed.

iii) The stationary bed and main circulating material will be a mixture of silica sand and

20–30 wt.% of calcined dolomite [35].

iv) Air flow will be handled as the equivalence ratio, ER [total air flow fed to the

gasifier/stoichiometric (for total combustion)air flow]. The total air fed (to the

gasifier) is split into the primary and secondary air flows shown in Fig. 1. The

secondary air flow is located above the biomass feeding point; together with the

biomass feeding there could also enter some additional sealing air which would be

considered as secondary air. The height of such 2nd air flow inlet is called H2nd, Fig.

1. This secondary air flow is usually used to increase the temperature in the upper

part of the gasifier to decrease, by thermal reactions such as cracking, the tar content

in the gas flows. As a typical or reference case, the 2nd air flow is considered to be

the 20% of the ER value.

2.2. Scales studied for the CFBBG

Not only commercial CFBBGs are of interest. There are other CFBBG of smaller scale,

pilot and demo sizes, which have also been considered and covered by the modeling.

Three scales were therefore considered. They are indicated in Table 1, together with their

representative values.

The gasifiers corresponding to the three scales were considered to have the same area

specific throughput (=1740 kg biomass fed, as received/h m2 of gasifier cross-sectional

area in the dilute zone), weight hourly space velocity for the biomass (WHSV) [=1.9 (kg

biomass fed, as received)/h]/kg solids inventory in the CFBBG] and total height for the

riser (=14.8 m). These values have been selected from a careful analysis and survey of the

existing CFBBGs worldwide. The inner diameters in the dilute zone of the CFBBGs for

these three scales are 7.6 cm, 0.85 m, and 3.3 m, respectively.

2.3. Operation intervals considered

After a careful analysis of biomass gasification itself and of existing bed biomass

gasifiers, the intervals for the main operation variables were selected. These are shown in

Table 2. Most of the existing fluidized biomass gasifiers operate, or should be operated,

between the intervals or limits shown in Table 2.

Table 1

Scales studied for the CFBBG

Scale mB Basis/Reference i.d. HT

(kg a.r./h)Throughput

(kg a.r./h m2)

WHSV

(h�1)

Wsand+dolomite

(kg)

(m) (m)

Pilot 8.0 1740 1.9 4.2 0.076 14.8

Demo 1000 1740 1.9 520 0.85 14.8

Commercial 15000 1740 1.9 7760 3.3 14.8

Table 2

Intervals considered for the main operation variables

Parameters Intervals considered

ER: 0.20–0.45

Biomass moisture (wt.%): 5–30

Biomass flow rate (kg/h): 2–20,000

WHSV (h�1): 1.0–3.0

Throughput (kg biomass a.r./h m2): 1000–7000

2nd air flow (%): 0–40

2nd air inlet height (m): 5–10

uo (m/s): 2–10

T bottom bed (8C): 750–980


2.4. Inputs and outputs to/from the modeling

The inputs for the model are indicated in Table 3. They include the biomass to be

gasified, the air (gasifying agent), the gasifier design and the biomass feeding flow which

can be expressed in several ways: as mass flow rate (kg/h), as weight hourly space velocity

[WHSV in (kg biomass/h)/kg solids inventory in the CFBBG] or as throughput (kg

biomass/h m2 cross-sectional area in the dilute zone). Two important input data concerning

the biomass feedstock, particle size distribution and its alkali (K+Na) content (sintering or

agglomeration problems), are not directly handled by the model in its present state of

development. For now, these two parameters will have to be handled in parallel with the

model shown here.

Direct outputs from the model (the only ones presented in this paper) are the gas

composition, the gas yield, the tar content in the produced gas, the carbon (in biomass)

conversion to gas, and the temperatures both at the gasifier exit and inside the gasifier

(axial profiles and bottom bed temperatures). Experts in biomass gasification should be

able to draw some more and important (indirect) outputs from the above direct

outputs. For instance, the model, if understood well, enables an optimized design of a

CFBBG, possible revampings and improvements of existing CFBBGs, detection of

limits of operation and zones in which the gasifier operates badly. All these outputs

can appear quite ambitious but in fact they have already been applied by the authors

to some gasifiers with positive results and, therefore, these outputs are realistic for the

authors.

2.5. Strategy in this modeling

CFBBGs are quite complex reactors and their modeling is difficult. Besides the need to

know biomass gasification technology in depth, there is as yet not enough accurate data for

some aspects. More needs to be known on the kinetics of some reactions under gasification

conditions and on radial and axial profiles in the whole gasifier of the char and of the

charred biomass, which are required to develop a good model [38]. During the modeling

work the authors continuously experienced uncertainties and lack of accurate information.

Besides, a model must be checked with existing CFBBGs but this checking was very

difficult in our case. The manufactures of the few existing pilot and commercial CFBBGs

Table 3

Inputs and outputs from the model

Inputs. variables considered

Biomass Chemical analysis (C, H, O, N)

Moisture

Ash content

(Particle size. Content in potassium: constraints in operation temperatures

by possible agglomerations)

Air Preheating temperature

Volumetric or mass flow rate

Equivalence ratio primary air

secondary air flow

Moisture

Gasifier Topology. Size, shape and main dimensions

bBedQ composition (solids and particle sizes) inventory

Heights of feeding: 1st air

2nd air

biomass

Biomass feeding Mass flow rate (kg/h)

WHSV (h�1), [mass flow rate/mass of solids (inventory) in the gasifier]

Throughput

Outputs

Direct

Gas Composition (H2, CO, CO2, CH4, C2Hn, H2O, O2 contents)

Heating value (LHV, MJ/Nm3, dry basis)

Yield (Nm3/kg biomass daf)

Quality: tar content (g/Nm3)

Exit temperature

Carbon Conversion (%)

Content in exit fly ash

Temperature Longitudinal profiles

Exit

Bottom bbedQIndirect Optimized design of a CFBBG

Limits of operation, zones of bad-functioning

Maximize throughput

Possible rewampings of the CFBBGs

Optimized MW/m2


did not publish many details about their gasifiers, and a private worldwide survey carried

out by these authors did not provide enough data as was required.

Due to the complexity of handling all aspects required in a model for a CFBBG, Corella

and co-workers at the Universities of Saragossa and Madrid (Spain), after twelve years of

work on this modeling, have developed two different models for CFBBGs. Each one uses a

different approach. In order to develop a model, given that till now not enough accurate

basic or scientific information exists, several assumptions were made. Depending on where

such assumptions are introduced or localized, a different model can be generated. In this

paper only one model is presented. It is 1-dimensional and for CFBBGs under steady state.

The 2nd model mentioned above is based on an empiric partitioning of the O2 (air) fed to


the gasifier, it does not consider axial profiles inside the CFBBG and is for non-stationary

states. The 1-dimensional model presented here might seem academic because it is based on

the Chemical Reaction Engineering (CRE) principles: chemical kinetics together with

mass, heat and momentum balances. A rigorous academic approach would contain more

than 20 parameters, some of them being absolutely unknown today [38]. Such unknown

parameters would be some kinetic parameters concerning in-bed tar appearance and

elimination and the ones concerning heterogeneities (plumes and radial gradients) existing

in the biomass and 2nd air flow feeding zones (i.e., [39]). Therefore, several assumptions

had to be made to solve and handle the initially very complex rigorous academic approach.

Making these experience based assumptions, the model became semi-rigorous. The degree

of empirism in it will decrease, hopefully, in the future when new and accurate information

(for CFB biomass gasifiers) is available.

The equations presented and solved here will basically be a set of kinetic equations for

the complex reaction network together with the mass balances for all the species or

reactants considered in such network. To calculate the values of all kinetic constants, axial

profiles of temperature are required. A lot of hydrodynamic considerations and details are

also required. These temperature profiles and hydrodynamic considerations will be

handled as sub-models and/or sub-routines in parallel with the main program.

A model without extensive good verification means nothing for these authors. Although

some experimental verification is usually not enough to demonstrate the validity and

usefulness of a model, it is absolutely required. For this reason, a lot of effort was made to

verify the model presented here. Such validation was carried out in two different ways: (1) a

worldwide survey with all the known commercial gasifiers manufacturers and owners

[AMERGAS, LURGI, TPS, ECN, UMSICHT, LAHTI, FOSTER-WHEELER E. Oy,

VARNAMO (Sydkraft), CLAMECY Plant,. . .]. Some of them do not exist nowadays, for

example, the gasification plant in Clamecy (France), but some useful information from such

plants were obtained years ago and were used in this work. Some information obtained from

some manufacturers and owners had a confidential character and cannot be explicitly shown

here. Nevertheless, it was used in several parts and steps of the modeling presented here.

Some data have also been obtained during the IEA Biomass Gasification task meetings.

(2) Some tests were carried out on small pilot plant scale to check this model. For that

objective, a BFB biomass gasifier at University Complutense of Madrid (UCM) was fully

modified by increasing its height and the biomass and air flow rates and connecting a

standpipe and an L-valve, thus generating a CFB. This CFB biomass gasifier was

presented in [37] and is shown in Fig. 2. Its main dimensions are (a) bottom zone: 70 mm

internal diameter (i.d.) and 1.2 m height; (b) a 2nd zone of 120 mm i.d. and 1.4 m height;

(c) upper zone: 150 mm i.d. and 2.2 m height. Temperatures were measured at different

heights with different thermocouples. Some tests were designed and carried out in this

CFBBG to check the model. This verification continues.

2.6. Species considered in the gasification reaction network

i) Concerning biomass, pine wood was selected as reference. The composition (dry,

ash free) was 50.0 wt.% C, 5.8 wt.% H and 44 wt.% O. Its weight formula was

C4.2H5.8O2.8.


ii) Gases. Air (in primary and secondary flows) and gases formed in the pyrolysis and

gasification reactions: H2, CO, CO2, CH4, C2H4 and H2O. H2O comes from biomass

and air mixtures and as a product in some reactions.

PRIMARY AIR

2

3

1

H2O

5

6

7

1. Hopper.2. Feeding system.3. Primary air inlet.4. Preheating zone.5. Secondary air6. Gasifier7. Additives inlet

4

Fig. 2. New small CFBBG pilot plant at UCM used to check the model.


iii) Tar. Although it is in gas phase and could be considered as one more gas, it will be

studied separately due to its importance in biomass gasification.

The first fast pyrolysis or devolatization generates a tar which will be called

tar1. In the bottom bed tar1 very quickly undergoes a lot of thermal

degradation reactions generating a tar called here tar2. It would be the one

detected if the CFB reactor was operated as pyrolizer, with an inert gas. In

a CFB gasifier this tar2 reacts, to some extent, with the primary air

generating a tar called btargasifQ. If, besides, there is a catalyst like calcined

dolomite (as it is the case considered here) in the bottom bed, this btargasifQundergoes some steam and dry (CO2) reforming reactions which decreases its

total amount and changes its composition. This new tar generated with in-bed

dolomite will be called btardolQ. The 2nd air flow in the dilute zone

additionally converts and transforms this tar (the btardolQ coming from the

bottom bed) to another tar which will be called btar2ndairQ. Not only the

amount of tar decreases but also its composition changes by the above

reactions [40]. To show the difference between the tars (tar2, targasif, tardol

and tar2ndair), the corresponding tar yields obtained in similar FB biomass

gasifiers using the same feedstock, pine wood chips, are shown in Fig. 3.

This Fig. 3 clearly shows how, at a given gasification temperature, the tar

yield depends very much on the existence of in-bed dolomite and on a 2nd

air flow.

Concerning tar composition, the 6-lump model for tar evolution (generation-

elimination) developed by Corella et al. [40–42] is now being applied to

study the axial profiles of the tar species. These axial profiles can be

handled by a sub-routine with 9 kinetic constants. This sub-routine, not used

in this paper, may be added or incorporated in the model presented here to

predict or calculate the axial profiles (in the riser) of the species present in

the tar.

The different tars existing in a CFBBG will be represented in this model by two

different species only:

– tar2, obtained from the devolatization+thermal reactions at the bottom bed

(see Eq. (1)). Its general formula is CxHyOz, with x=1 and y, z to be determined

from mass balances ( y/x for tar2 is less than 1 in the range of temperature

considered, according to Van den Aarsen [19]).

– tar4, generated by in-bed catalytic steam (and dry) reforming reactions (Eq.

(9)). Its general formula is CxU HyU with xU=yU.

The btotal or overall tar contentQ at the exit of the CFBBG will be the addition

of, first, the tar2 generated in the pyrolysis step (Eq. (1)) minus the tar2 reacted

by reactions (2) and (9), and, second, the tar4 generated by Eq. (9) minus the one

reacted by reaction (2b).

iv) Char. Two different compositions will be considered for the char:

– char2, generated in the devolatization+in-bed thermal reactions (Eq. (1)).

Its general formula is Cx VHy VOz V with xV=1 and yV, zV to be determined

from mass balances [(H/C)char2b(H/C)tar2b1, in the range of temperatures

considered].

700 750 800 8500

10

20

80

100

140

120

160

tar2ndairtardol

targasif

tar2

Gonzalez-Saiz [43] Narvaez et al. [36] Gil et al. [35] Lammers et al. [46], Kurkela [73]

Tar

yie

ld (

g/kg

bio

mas

s, d

af)

Bed temperature (°C)

`

Fig. 3. Tar yields after pyrolysis (tar2) and after atmospheric gasification with air (ER=0.24) without (targasif) and

with (tardol) in-bed dolomite, without and with (tar2ndair) secondary air flow.


– char3, generated in the gasification of char2 with CO2, reaction (11). Its general

Table 4

Compositio

Pyrolysis t

715

815

915

Averaged

formula was determined from analysis of this char obtained during the

experiments at UCM. It can be noticed that (H/C)char3N(H/C)char2.

The bchar concentrationQ inside and at the exit of the CFBBG will be the addition of

two contributions: first, the generated one by reaction (11) and the char3 unreacted in

reaction (3b), and second, the char2 unreacted in reactions (3) and (10).

The compositions of tar2 and char2, according to Van den Aarsen [35], depends on

the gasifier temperature, Table 4, and on the type and composition of the biomass used.

The chemical compositions of tar2, tar4, char2, char3 were calculated for a gasification

temperature of 850 8C, for a given biomass (pine wood was used as reference), and for

the Htar2/Hchar2 and Otar2/Ochar2 ratios (Ctar2/Cchar2 ratio is 1) indicated in Table 4.

n of tar2 and char2, according to Van den Aarsen [19]

emperature (8C) tar2 char2

CH0.81O0.20 CH0.25O0.14

CH0.75O0.13 CH0.21O0.12

CH1.00O0.17 CH0.14O0.14

CH0.85O0.17 CH0.20O0.13

Table 5

Calculated compositions for tar2, tar4, char2 and char3 (T=850 8C)

Specie Formula H/C

Biomass C4.2H5.8O2.8 1.40

tar2 CH0.85O0. . .17 0.85

tar4 C0.54H0.54 1.0

char2 CH0.20O0.13 0.20

char3 C0.30H0.15O0.46 0.50


Tar2, tar4, char2 and char3 compositions, calculated at 850 8C as reference, are shown

in Table 5.

3. CFBBG modeling

3.1. Reaction network considered

The most suitable reaction network for biomass gasification with air in a CFB was

previously discussed by Corella and Toledo [38]. Such a network contains all the reactions

which were considered relevant and it is shown below (reactions (1)–(12)). Axial profiles

of concentration for all the species considered in this network will be further obtained from

the model.

3.1.1. Reaction network considered for the zone between the biomass feeding point and the

2nd air inlet (zone which covers the bottom zone, the transition zone and part of the dilute

zone, Fig. 1)

Fast Pyrolysis:

(1)

Oxidation with the primary air of the products formed in the pyrolysis step:

tar2½CH0:85O0:17� þ q2 � 1stO2 ! e2 � COþ g2 � CO2 þ s2 � H2O ð2Þ

char2½CH0:20O0:13� þ q3 � 1stO2 ! e3 � COþ g3 � CO2 þ s3 � H2O ð3Þ

H2þ O1stO2 ! H2O ð4Þ

COþ O1stO2 ! CO2 ð5Þ

CH4 þ 1:51stO2 ! COþ 2 � H2O ð6Þ

C2H4 þ 31stO2 ! 2CO2 þ 2H2O ð7Þ


Steam reforming of methane:

CH4 þ H2OYCOþ 3 � H2 ð8Þ

Tar and char reforming reactions:

(9)

char2½CH0:20O0:13� þ s10 � H2O ! e10COþ d10H2 ð10Þ

char2½CH0:20O0:13� þ g11 � CO2 ! e11COþ u11char3bCxxHyyOzzc ð11Þ

3.1.2. Reaction network considered for the zone between the 2nd air inlet and the exit to

cyclone (part of the dilute zone, Fig. 1)

Besides the reactions given by Eqs. (2)–(11),

Oxidation with the secondary air of products coming from first zone of reaction:

tar4tCx00 � Hy00 bþ q2b � 2ndO2 ! e2b � COþ g2b � CO2 þ s2b � H2O ð2bÞ

char3tCxxHyyOzzbþ q3b � 2ndO2 ! e3b � COþ g3b � CO2 þ s3b � H2O ð3bÞ

Shift reaction:

(12)

The non fixed stoichiometric coefficients in these reactions were calculated by mass

balances for each of the components (C, H, O) in each chemical reaction. These

coefficients, for a temperature of 850 8C, are shown in Table 6.

3.2. Kinetic equations used for the chemical reactions involved in the reaction network

The set of kinetic equations for the reaction network given by Eqs. (1)–(12), used to

calculate the product distribution, is shown in Table 7. These equations originate both from

our own findings/research and from some published papers.

Table 6

Stoichiometric coefficients for T=850 8C

Eq. Stoichiometric coefficients

(1) b1=0.87; c1=0.45; d1=1.3; e1=1.5; g1=0.51, h1=0.47; p1=0.18

(2) q2=0.68; s2=0.31; e2=0.75; g2=0.25

(2b) q2b=0.60; s2b=0.26; e2b=0.093; g2b=0.42

(3) q3=0.58; s3=0.073; e3=0.75; g3=0.25

(3b) q3b=0.032; s3b=0 ; e3b=0.037; g3b=0.17

(9) d9=0.13; e9=0.35; s9=0.15 v9=1.2

(10) d10=0.45; e10=0.54; s10=0.38

(11) g11=1; e11=1.7; u11=1

Table 7

Reaction rates for the reaction network

Reaction Reaction rate (mol/m3 s) Parameters Reference

(1) y i=mo,i+m1,i ST+m2,iST2 Jiang and Morey [22,23],

Gonzalez-Saiz [43]

Zanzi et al. [66], Dai et al.

[67], Di Blasi et al. [68,69]

(2) r2=k2SCtar2SCO2k2=ftar2S(1-cv)1.58S 10

10S

exp(-24200/T)

Dryer and Glassman [44,45]

Lammers et al. [46]

(2b) r2b=k2S(ftar4/ftar2)SCtar4SCO2The same of (2) with

different value for the

kinetic constant


Lammers et al. [46]

(3) r3=k3ScvSUsSCchar2SCO2

or r3=k3VSpO2

0.53S(1-Xchar)

0.49

k3V=5.3S105Sexp(-15000/T) Janse et al. [47]

Fushimi et al. [50]

Kulasekaran et al. [71]

(3b) r3b=k3ScvSUsSCchar3SCO2The same of (3) with

different value for the

kinetic constant

Janse et al. [47]

Fushimi et al. [50]


(2), (3),

(2b),

(3b)

e2

g2¼ e3

g3¼ e2b

g2b¼ e3b

g3b

¼ 4:30exp � 3390=Tð Þ

Belleville and Capart [17]


Hayhurst and Parmar [70]

Cozzani et al. [72]

(4) r4=k4SCH2

2SCO2

/CCO k4=3.09S1011Sexp(-12000/T) Kim et al. [11]

(5) r5=k5SCCO SCO2k4=8.83S10

11Sexp(-12000/T) Kim et al. [11]

(6) r6=k6SyCH4

-0.5SyO2

1.5 k6=7.0S1011Sexp(-30200/T)ST Srinivasan et al. [7]

De Souza-Santos [63]

(7) r7=k7SCC2H4

0.7SCO2

0.8 k7=fC2H4S(1-cv)1.58S10

10S

exp(-24200/T)


Philippek et al. [64]

(8) r8=k8SCCH4SCH2O

k8=3S1005exp(-15000/T) Therien et al. [48]

Liu and Gibbs [32],

from Fletcher et al. [49]

(9) r9=k9SCtar20.25

SCH2O1.75 k9=f9S70.0Sexp(-2000/T) Gonzalez–Saiz [43]

(10) r10=k10SCchar2SCH2Ok10=2.0S10

5Sexp(-6000/T) Gonzalez–Saiz [43]

Fushimi et al. [50]

(11) r11=SSrW11 r11V =7.2SCCO2

0.83exp(-20000/T) Van den Aarsen [19]

Van den Aarsen et al. [51]

Tang et al. [65]

(12) r12 ¼ k12S CCOSCH2O � CCO2CH2

KW

S

� �

KW ¼ CH2SCCO2

CCOSCH2O

a) T N 1123 8C (equilibrium)

KW ¼ k12

k12V

¼ 0:0027exp � 3960=Tð Þ

Gonzalez–Saiz [43]

Xu and Froment [52]

Simell et al. [53]

b) Tb1123 8C (no-equilibrium)

KW ¼ k12k12V

¼ 520exp � 7230=Tð Þk12 ¼ 106exp � 6370=Tð Þ


Some comments on these kinetic equations:

1st) For reaction number 1 (fast pyrolysis in fluidized bed) a product distribution,

instead of a btypicalQ kinetic equation, was preferred because such product


distribution was obtained with the same type of biomass as the one considered

in this paper (small pine wood chips) and in a fluidized bed working under

experimental conditions similar to those used in a CFBBG. The values for the

parameters m0, m1, and m2 appearing in Table 7 are given in Table 8 for all

species. The units for yi, in equation for reaction 1, when calculating tar yield

and yield to char were [kg/kg daf] and when calculating H2, CO, CO2, CH4 and

C2H4 contents were [mol i/total mol, dry basis]. The authors are confident of

the validity of this equation and those m-values for this application. Never-

theless, it has to be pointed out how this product distribution may be quite

different for some other types of biomass, because the word bbiomassQ covers a

big spectrum of fuels which can be very different between themselves.

2nd) The selection of the rate expressions for reactions (2)–(12) was made after a deep

Table 8

Values

(from G

i (speci

H2

CO

CO2

CH4

C2H4

N2

Tar

Char

H2O

analysis of the abundant bibliography on most of these reactions. Their respective

reference or origin are given in Table 7. Since for some reactions there were

different possible kinetic equations in the literature and since there was no

discrimination method among those rival kinetic models, different references are

given in Table 7 for some reactions. When there were several possible kinetic

equations for a given reaction, the easiest or simplest one (1st order, for instance)

was preferred although several other kinetic equations could also be used for that

reaction.

3rd) Since some reaction rates originally had different units (the ones provided by the

corresponding authors) an important effort was made to adopt the same units in

all kinetic expressions. For this propose, a change of units which takes into

account variables such as pressure and temperature in the riser, voidage, density or

dolomite content in the considered zone, . . . had to be made in several kinetic

equations.

4th) Since most of the kinetic equations shown in Table 7 were obtained under gas

atmospheres and environment, such as the existence of calcined dolomite

(OCad OMg) which may have some catalytic effects for several reactions, different

to the ones existing in a CFB biomass gasifier, most of the rate equations shown in

of parameters m0, m1, and m2 for the fast pyrolysis of small pine wood chips in a bubbling fluidized bed

onzalez-Saiz [43] and Jiang and Morey [22,23])

es) m0 m1 m2

0.255 �4.47 10�4 4.54 10�7

0.255 5.44 10�4 �3.88 10�7

2.14 �3.53 10�3 1.55 10�6

�0.45 1.12 10�3 �5.47 10�7

�1.32 2.51 10�3 �1.15 10�6

0.118 �1.99 10�4 8.64 10�8

0.382 �2.16 10�4 0

2.09 �3.47 10�3 1.48 10�6

the corresponding to the initial biomass moisture

Table 9

Corrective factors used in the kinetic equations

Corrective factors Intervals considered

f2 0.6–1.7

f2b 1

f3 1.6

f4 0.5

f5 0.1–0.9

f6 0.1–1

f7 1

f8 2

f9 1.6

f10 0.4–0.7

f11 0.2–2

f12 0.3–0.7


Table 7 have to be understood as approximate, not exact ones. For this reason, and to

fit some experimental data from existing commercial CFBBGs, some corrective

factors ( fn) were introduced in the kinetic equations above. These corrective factors

are shown in Table 9. The value of 1 in Table 9 means that the corresponding kinetic

equation remains without modification.

3.2.1. Overall volumetric rate equations

Each i-th species (H2, CO, . . . , tar2, char2, . . . ) existing in the reaction network

indicated by Eqs. (1)–(12) appears in several reactions, sometimes as reactant, sometimes

as product. The overall or net rate of appearance (indicated by Ri) of the i-th species will

be the badequateQ addition, by the well known rules of Chemical Reaction Engineering, of

the rates for all the reactions in which such species appears.

The two main zones considered in the CFBBG (till the 2nd air feeding point and from

this point to the exit) were considered separately. Some examples of the calculation of these

overall reactions rate, for the zone between the biomass feeding point to 2nd air inlet, are

Rtar2 ¼ eq:1� r2 � r9 ð13ÞRchar2 ¼ eq:1� r3 � r9 � r10 � r11 ð14ÞRH2

¼ eq:1þ d8 � r8 þ d9 � r9 þ d10 � r10 � r4: ð15ÞRCO ¼ eq:1þ e2 � r2 þ e3 � r3 þ e6 � r6 þ e8 � r8 þ e9 � r9 þ e10 � r10 þ e11

� r11 � r5 ð16Þand from the 2nd air inlet to the gasifier exit.

Rtar2 ¼ � r2 � r9 ð17ÞRtar4 ¼ v9 � r9 � r2b ð18ÞRH2

¼ d8 � r8 þ d9 � r9 þ d10 � r10 þ r12 � r4 ð19ÞRCO ¼ e2 � r2þe2b � r2bþe3 � r3þe3b � r3bþe6 � r6þe8 � r8 þ e9 � r9 þ e10 � r10

þ e11 � r11 � r5 � r12 ð20Þ


3.3. Mass balances for all species

Two main assumptions were made:

1st) One-dimensional model. Piston or plug flow considered in the CFBBG for all the

species.

2nd) Steady-state operation.

Three different scales for the CFBBG were considered: pilot, demo and commercial

scales (see Section 2.2). The temperatures used, to calculate the values for all the kinetic

constants, come from the heat balances shown below. Pressure drop considered in the riser

is 0.10–0.20 atm (10.1–20.2 kPa) and the percentage of the 2nd air flow between 0% and

40% (standard: 20%). Two different units for the space time (s) were used in the mass

balances depending on the i-th species under consideration (gases, tars and chars). These

units for s are indicated in the notation.

3.4. Heat balances

Axial profiles of temperature (T) in the riser of a CFBBG are very important because all

kinetic constants in the set depend on temperature. To calculate a given kinetic constant at a

given height in the riser, the temperature at such height has to be known and to know such

axial temperature profiles several heat balances have to be made. The contours for such heat

balances are indicated in Fig. 4. For a given heat balance, the fuel gas composition has to be

known at the inlet and exit of this contour which, in turn, depends on the temperature in

such points. An iterative process therefore has to be used in each contour.

For a CFBBG under steady state the contours under consideration are shown in Fig. 4:

the bottom zone (contour 1, with the biomass feeding point in it), the 2nd air feeding zone

(contour 2), the zones of the riser with no feeding points (contours 3a and 3b) and the

whole riser (contour 4).

Once fixed the process conditions the axial profiles of T are calculated but, since the

heat released by each reaction in the network (Eqs. (1)–(12)) depends on its conversion

and this conversion depends on T, an iterative calculus has to be made in each contour. The

heat losses considered in each contour are the 2% of the overall heat released.

For a CFBBG under a non steady state (starting up period, changing in biomass feeding

flow, etc., . . .) the only contour considered was the whole gasifier (contour 4 in Fig. 4). In

this case all the gasifier was considered isotherm. The evolution of the only one bgasifiertemperatureQ then with time-on-stream, until a steady state was reached, was also calculated.

3.5. Hydrodynamic considerations and constrains

The hydrodynamics in a CFBBG are extremely complex because at least there are the

following four types of different solids in a CFBBG:

– Silica sand (S), as fluidizing material.

– Raw dolomite [(CO3)2CaMg] as additive for in-bed tar cracking and to prevent

agglomerations. At gasifier temperature the raw dolomite quickly calcinates to

Biomass

2nd Air

1st Air

Gas

Bottomashes

air conditionsTamb = 15 °C

rel. moisture = 30%

1st

3rd a

3rd b

2nd

4th

Heat losses

Fig. 4. Zones or contours where heat balances have been made.


OCad OMg. Calcined dolomite (D) has a density half of that of the raw dolomite and a

softness three times higher than the raw material dolomite. So, in fact, raw dolomite and

calcined dolomite should be considered, both chemically and physically, as two

different solids for hydrodynamics studies.


– Biomass, which usually contains very different types of particles (from different

origins) each having different shape factors.

– Char, charred biomass and ash from biomass, with a very low density and high

softness. They very easily erode at the bottom bed by the effect of the abrasive silica

sand. When gasifying, the particle sizes of the biomass, charred biomass, char and ash

change very much and very quickly [54].

The hydrodynamics of this mixture of solids in a CFBBG is very complex [58] and will

not be well known until a lot of the remaining work is done in future. Some hydrodynamic

aspects taken into account in the modeling of CFBBGs are the following:

1st) The zone between the inlet of the primary air and the biomass feeding point (height

H1, see Fig. 1) is difficult to model: the axial profiles of biomass and chars (char1,

char2 and char3) are not yet well known. Since there is a stationary fluidized bed in

that zone [61], it might be supposed that there would be back-mixing for all species

in solid phase, as biomass and chars. Nevertheless, chars, and also biomass, have

such a low density compared with the one of the bfluidizing materialQ (silica sand

and additive) that there is a near instantaneous segregation of the chars once

generated in the pyrolysis zone, just above the biomass feeding point. Aznar et al.

[55] studied this fast segregation and published a lot of axial profiles of the char and

of some types of biomass in binary, ternary and quaternary mixtures. Until other

even more accurate axial profiles for char and biomass are published, the axial

profiles for char and biomass published by Aznar et al. [55] will be the ones used to

calculate the extent of the reactions and the resulting profiles of the gases in that

zone.

2nd) The comminution and carry over of the calcined dolomite in a CFBBG occurs by

different simultaneous mechanisms, as studied by Aznar and co-workers [56]. They

found the reason why 1 to 3 wt.% (respect to the biomass fed) of dolomite has to be

continuously fed to the gasifier to replace the dolomite lost by elutriation. They also

established why an enough good behaviour of a CFBBG occurs when there is a 20–

30 wt.% of dolomite in its bottom bed. The remaining 70–80 wt.% is silica sand. The

char and ash content in the bottom bed is usually very low (1–4 wt.%) and can be

omitted when calculating the weight hourly space velocity (WHSV) of the biomass

[(kg biomass fed/h)/kg solids inventory (S+D)] in the CFBBG.

3rd) To get realistic data on hydrodynamics in commercial and in big (pilot, demo)

biomass gasifiers, a worldwide survey was carried out among all the existing

CFBBG manufacturers and owners. Most of them provided to the authors some

important values, sometimes confidentially, about the following parameters in which

their gasifiers operate:

– WHSV [weight hourly space velocity, (kg/h)/kg inventory] from 1 to 3 h�1.

– Throughputs (kg/h m2 cross-sectional area): between 1000 and 7000 kg/h m2.

– Superficial gas velocities: 2–10 m/s.

– Mean residence times for the gas in the bottom and in the dilute zones: 1 and 3 s,

respectively, on average.

– etc . . . (gas compositions, for instance).


In the solution of the model shown here, all this information was taken into

account. This information defined the limits of operation or constrains of the whole

model. It was one of the main verifications (in the calculations carried out in the

model) shown in Fig. 8.

4. Model development

The simultaneous solution of the mass and heat balances with the kinetics and the

hydrodynamic aspects was very complex. Although certain details are omitted some

important results are given below:

4.1. Heat balances and the axial profiles of temperature

Some results concerning the axial profiles of temperature are

1) Axial temperature profiles obtained from the model are of the same type as the few

already existing in the literature for CFBBGs [28,57]. They were also confirmed by

the measurements made in the small CFBBG shown in Fig. 2.

2) From the bottom of the gasifier until the 2nd air flow inlet point

(H1+Hbt+Htz+H3 in Fig. 1) the temperature decreases because the endothermal

reactions in this zone consume more heat than that provided by the simultaneous

exothermal ones. Nevertheless, one simplifying assumption can be made, at a

first attempt, to facilitate further calculations in that zone: an average temperature

can be considered in this zone. This average temperature is calculated supposing

that all devolatilization occurs there and that all the 1st air reacts in this zone. To

give one example, the temperatures in the bottom zone for different ER values

are shown in Table 10 for a 2nd air flow of 20% of the total air flow, a biomass

moisture of 15 wt.% and a 1st air flow preheated to 250 8C before feeding it to

the CFBBG. These temperatures are the ones at the lowest part of Fig. 5.

Temperatures at the bottom zone for several other process conditions will be

shown in our next paper [33].

3) One very important fact concerning the axial profiles of temperature (in the riser) is

the increase of T (DT) because of the secondary air flow in the upper (dilute) zone.

Such increase of temperature may also appear when the particle size of the biomass

fed is very low. In that case it is carried out from the bottom bed by the flue gas and

partially combusted, if there is still some O2 left there, in the upper (dilute) zone, as

van der Drift and van Doorn [57] demonstrated at the ECN (The Netherlands) pilot

Table 10

Standard bottom zone temperature depending on the ER value (secondary flow=20% of ER; biomass

moisture=15%; preheated air temperature=250 8C)

ER 0.20 0.25 0.30 0.35 0.40 0.45

Tb . bed (8C) 824 837 850 863 877 890

Total ER0.20

16

14

12

10

8

6Ris

er H

eigh

t (m

)

4

2

0

800 850 900 950 1000 1050

0.250.300.350.400.45

Fig. 5. Longitudinal profiles of temperature for different total ER values with a 2nd air flow of 20% of total air.


plant. The reference (or average) DT by the 2nd air addition calculated for several

percentages of this 2nd air is shown in Fig. 6.

4th) In the upper part of the riser, from the 2nd air inlet point till the gas exit point,

there is a continuous decrease of the temperature. The heat consumed by the

endothermal reactions there, together with the heat lost by the walls, is usually

not compensated by the heat released by the exothermal reactions occurring with

the O2 fed in the 2nd air flow. Again it can be assumed, as a first attempt and to

facilitate some further calculations, that the upper zone of the riser is isothermal,

with an average temperature in it. The simplified axial profiles of temperature in

the riser of the CFBBG for the case of a 2nd air flow of 20% of the total air,

and for a 2nd air inlet height of 6 m are shown in Fig. 5. These simplified

profiles can be used in the whole model when more precise or accurate profiles

0 10 20 30 40

0

50

100

150

200

∆T (

= T

exit-

Tb.

bed)

2nd air flow (%)

Fig. 6. Difference of temperature (DT) used as reference between the averaged in the upper zone and in the

bottom zone of the CFBBG, for different percentages of 2nd air flow.


cannot be calculated. In fact, in the present state of development of this model

and with the existing data, the axial profiles of T cannot be calculated with

accuracy for some experimental conditions (i.e., for some types of feedstocks or

for some particle size distributions of the biomass). In such circumstances a

simplified two-zone temperature profile, as the ones shown in Fig. 5, can be

used. In such cases, the temperature is considered constant from the biomass

feeding point until the 2nd air feeding point. Then, there is an increase of T (DT)

by the 2nd air addition (which depends on the percentage of 2nd air used) and

then, from the 2nd air feeding point to the exit of the riser, the temperature is

considered constant. Only two calculations (not easy sometimes) are needed in

this simplified approach: the temperature in the bottom zone and the DT value by

the secondary air flow.

4.2. Hydrodynamics of the CFBBG

Some noticeable comments about modeling the hydrodynamics in the CFBBG are:

1) Although it is well known how in CFBs there is a continuous, along their axis or

height, variation of voidage (e) or solids fraction, the gasifier was considered as composed

by the following three zones (see Fig. 1):

– bottom zone, with a height of Hbt. The reference porosity in this zone is 0.77.

– transition or splash zone, with a height of Htz and e=0.90.– dilute zone, with Hdz of height and e=0.99. Secondary air is fed into this zone.


An exit zone may also be considered, if required. Other values for the porosities might

also be used but these ones were considered as acceptable or representative; they are the

averaged values from the published porosities for similar CFB reactors.

2) Clouds and strands of particles which may lead to a different velocity-behaviour of

the gas and of the solids were not considered. Besides, the behavior of the solids is

different in very slim reactors compared with wide commercial reactors. These facts,

which have been very well studied in coal combustors for instance, have not yet been

studied enough in biomass gasifiers. These phenomena are therefore recognized, but a

piston flow (1-dimensional model) has always been used in the model. Some errors are

recognized at this point in the model but this situation is acceptable until more useful data

concerning CFBBGs are available.

3) Biomass devolatization once biomass enters into the bottom bed in the CFBBG,

although it is very fast, it is not instantaneous. There is some evidence that a plume or

something like a small jet of gas is formed (i.e., [39]). The flow in such feeding zone is not

an academic piston or plug flow [39] and today there is not enough information published

for a good sub-model for this zone. It will remain as one of the main unknowns or weak

points of this model.

Something similar occurs with the 2nd air flow and its mixing with the upwards flow. It

is not instantaneous and generates a lot of effects (i.e., [74]). The authors think, from their

own experience, that the bmixing zonesQ above both the biomass and 2nd air feeding

points should be at least 1 m height each. Nevertheless, to facilitate handling the

mathematics in the present model, it was considered that such feeding of biomass and 2nd

air occurs at just bone point or heightQ, as Fig. 1 indicates. In real CFBBGs, however, the

space above these points has a lot of heterogeneities. For instance, the pipe(s) for the

biomass feeding has sometimes 0.50 m diameter, it is therefore not just a point. When

examining longitudinal profiles for this model, it will have to be remembered that such

two bpointsQ (biomass and 2nd air injection) are not bpointsQ but zones of around 1 m

height.

4) The heights of the different zones are indicated in Fig. 1. From the works of

Schlichthaerle and Werther [75], Malcus et al. [76], etc., . . . the standard values consideredin this paper for these zones are H1=1.5 m; H2=1.0 m; H4=0.5 m; HT=14.8 m. Although

Hbz and Htz (see Fig. 1) vary with the air flow rate or ER value, these heights were

considered constant, 1.4 m each one, for all ER values. Nevertheless, all these heights are

variables in the model and can be varied to adapt it to a existing gasifier.

5) The terminal velocity (ut) of the solids was calculated by well established and known

methods, recently refined and applied by Hartman et al. [59] to the raw and calcined

dolomites. ut for the four main solids (in the riser of the gasifier there could be another

ones as big stones and irons too) existing in a CFBBG are shown in Fig. 7. The flue gas

considered for such calculation was air at 850 8C and 1.1 atm of total pressure. The particle

density and shape factor (very difficult to know for biomass char in a CFBBG under

operation) of the solids considered are shown in Fig. 7. Since the biomass, the charred

biomass and the char (and ash) usually have a broad spectrum of shape factors and of

densities, a zone, instead of a line, was considered for the reacting biomass in this figure.

If the superficial gas velocity at the exit of the riser of the CFBBG is 4 m/s, for instance,

Fig. 7 indicates how a silica sand of 0.5–1.0 mm would remain at the bottom bed, not

5

4

SILICASAND

RAWDOLOMITE

CALCINEDDOLOMITE

WOODCHIPS

CHAR FROM THEWOOD CHIPS

LEAFS

Silica sand, 2.6g/cm3, φ=0.9

Raw dolomite, 2.4g/cm3, φ=0.8

Calcined dolomite, 1.3g/cm3, φ=0.9

Wood chips, 0.85g/cm3, φ=0.4

Leafs, 0.5g/cm3, φ=0.1

Ash from wood, 0.2g/cm3

Ter

min

al v

eloc

ity (

m/s

)

3

3

2

2

1

10

0 5

dp (mm)6 7 98 104

Fig. 7. Terminal velocity of the main solids existing in a CFB biomass gasifier (calculated for air, at 850 8C and at

a total pressure of 1.1 atm).


transported (its ut is higher than 4 m/s). A raw dolomite of 0.6–1.0 mm would

initially remain in the bed as well, but once and quickly calcined it would be

elutriated out. Biomass, char and charred biomass particles below 1.0 cm

approximately (depending on its initial shape, density and degree of charring) would

be transported out from the bottom bed first and then out of the riser. Fig. 7 is

interesting for the CFBBG modeling. For instance, the very important mean residence

time of both gasification gas and biomass in the bottom bed can be varied by

changing the bottom bed height which (for a given ER or superficial gas velocity)

depends not only on the inventory of solids (kg of S+D) but mainly on their particle

size distributions. Depending on their particle sizes they will generate a bed at the

bottom of the CFBBG or carried out. Since the particle densities of the silica sand and

of the raw dolomite are fixed, their particle sizes remain as the main variable which

can be varied (between some intervals only) to increase or decrease the mean gas

residence time in the bottom bed. This will modify, in turn, the composition, yield and

quality (tar content) of the gas exiting the bottom zone. So, a good choice of the

particle size distributions of both sand and dolomite is of paramount importance in the


CFBBG design and operation. Consequently, these particle sizes are very important in

this modeling.

6) The main or first cyclone as well as a second and in-series high efficiency cyclone,

usually required for some applications of the produced gasification gas, were taken into

account but are not reported in this paper. The content of particles in the produced gas

mainly refers to the top of the riser and not of the flue gas hence leaving the whole

gasification unit. The calculus of the particle content in the fuel gas after the whole

CFBBG still has a considerable error. In fact, the overall particle content is due to different

solids (char, ash, calcined dolomite, etc. . .) and some of these contributions (to the whole

content in particles) have not been deeply studied yet [56].

7) Char recirculation: the total conversion of the char produced in a CFFBG is not

produced in one pass of the solid through the riser [60]. The char is recycled in the

CFBBG until the (highest) final conversion is obtained.

The internal recycling of solids causes a spread in the residence time of the particles;

some pass only once through the riser while others are recycled several times [60]. Some

assumptions in the calculus of the char conversion include:

– The inlet to the riser of the recycled char stream is made at the same height as the

biomass feeding point.

– The char composition in the recycled stream is the same as that at the outlet of the riser.

– The conversion of the total char, the one generated in the pyrolysis step and the

recycled stream of char, in each passage in the riser is the same in each passing.

Several other hydrodynamic considerations were also used, but are not included here to

keep this paper within limits.

4.3. Calculation procedure

The overall model is protected and for reference purposes it will be called Al-CoreR.The flow diagram for the overall solution of the Al-CoreR program is shown in Fig. 8. For

its solution, the following inputs must be given:

– Biomass (B): flow rate, moisture and ash content, and its ultimate analysis daf (C,H,O

wt.%).

– Operational conditions: pressure, inventory or weight of bed material (assumed 30

wt.% dolomite and 70 wt.% silica sand), and temperature at inlet of bottom bed.

– Inlet Air: ER, temperature of preheating, ambient temperature, relative moisture and

2nd/1st air flows.

– Gasifier topology: main dimensions, wall thickness or weight of the gasifier (which is

needed in a heat balance), etc . . .

The flow diagram for the solution of the Al-CoreR program is shown in Fig. 9 with

some more detail. Some procedural steps are given below.

It is necessary to make a first assumption for the axial profile of voidage (e) and for the

volumetric flow rate of the flue gas along the gasifier height (Q1).

INPUTS

B, E R ( ... )

OUTPUTS

Axial profiles ofT (°C)

Gas comp. (% vol.)

LHV of gas (MJ /Nm3)

Gas yield(Nm3/kg daf,dry basis)

Tar content (g /Nm3)

Char concentration (g/kg S+D )

Hydrodynamics:ε and char axial profiles

WHSVTotal gas flow in the riser (Q).Sup. gas velocities, profilesMean gas residence times

Heat balancesTemperature at inlet of bottombed T1 (°C) - depending of ER

Resolution of kinetics +mass balance eqns. (for

each specie)

[ 1 ][ 2 ][ 3 ].. .

[ 1 2 ]

TXta r

C ch a r

.. .Xo

2

at exit of the gasifier

Q2

= Q1

YE S

NO

Checking withexp. data

NO TGOOD

OK

i

g

2P

RQ Σ·

·= n

T

ig

1i X

TR

VPn ·

·

·=

Fig. 8. Simplified flow diagram of calculation for the overall solution of the 1st, 1-dimensional pseudo-rigorous

model.


It is also assumed that the inlet air is heated at the bottom bed from the preheated air

temperature, of around 250–350 8C, to the temperature at which the gasifier operates in the

bottom bed.

When the mass balance for all the species is solved, the composition (vol.%) of the gas

species, char concentration and volumetric flow rate of gas (Q2) are obtained. Two zones

of resolution have been considered (1st: bottom zone–transition zone–part of dilute zone;

2nd: rest of the dilute zone).

In the 1st zone of resolution, two steps in series have been considered: the first

one is the fast pyrolysis; with Eq. (1) the product distribution are obtained (see

Section 3.2., kinetic equations used). The results from the fast pyrolysis are used in

MODULE 3Dilute zone

SOLUTION: Subroutine 4

MODULE 2Transition, bottom zoneand part of dilute zone


MODULE 1Bottom Zone-Pyrolysis


Xio

, Cchar0 Xi0: initial molar fraction of the components after the

pyrolysis, for H2, CO, CO2, CH4, C2H4, H2O, N2, tar

XiA: molar fraction of the components before 2nd airinlet, for H2, CO, CO2, CH4, C2H4, H2O, N2, tar

Xi: final molar fraction of the components, for H2, CO,

CChar,0: char concentration after the pyrolysis

char concentration before 2nd inlet

char concentration at riser exit

in g char / (kg sand + dolomite)



INPUTS: B, ER, ...(As a function of the riser height)Supposed gas temperatureSupposed riser voidage, total gas flow

Subroutine 1: Pyrolysis reactions

Subroutine 2: Oxidation of products from pyrolysis

Subroutine 3: Tar - char reactions and steam reforming of methane

Subroutine 4: Oxidation of products from the bottom bed

Subroutine 6: Shift reaction

Xi, Cchar,Q2

OUTPUTS: X1, Cchar, total gas flowLHV, C content in fly ashgas field

YES

Q1 = Q

1'Q

1 = Q

1'

XiA, CcharA, Q1'NO

Q2 = Q1'

Subroutine 5: Tar - char reactions and steam reforming of methane

START

INPUTS

Supposed Q1

1st O2

(air)

2nd O2

(air)

XiA, CcharA, Q1'

Q1'=Q2

NO

STOP

OUTPUTS

CChar,A:

CChar:

YES

Subroutine 3

Subroutine 5Subroutine 6

CO2, CH4, C2H4, H2O, N2, tar

Fig. 9. Flow diagram for the solution of the mass balances.


second step as initial conditions for the resolution of mass balances for oxidation, tar

and char steam reforming and methane reactions. The values obtained at the exit of the

first zone are used as initial conditions for the resolution of the mass balances in the 2nd

zone. A fourth–fifth order Runge–Kutta method has been used to solve the mathematical

problem.


The volumetric flow rate of gas was considered constant along each zone. A

volumetric flow rate of gas is assumed for the entry point of each zone and it is used to

calculate the gas composition, tar content and char concentration at the end of that zone.

The volumetric flow rate of gas is calculated then for the end of the zone. If the

calculated volumetric flow rate of gas is not the same as the first value, Q1pQ1V, themass balance is repeated until the two values agree. The volumetric flow rate of gas

finally calculated for the first zone is used as the flow rate entering into the second one,

then repeating the same calculation.

The solution of the heat balance is carried out simultaneously with the kinetics and the

mass balances.

The char concentration in the flue gas was calculated in a two-step process:

– Char concentration is calculated along the gasifier height without considering its

recycling to the riser (first step).

– Once fixed the efficiency (99% for instance) of the (first) cyclone, the char recycled to

the bottom of the riser is known. The recycled (to the riser) char is taken into account in

a second step for an improved calculation.

When the kinetics and the mass and heat balances are solved, the axial profiles for

tar content, char concentration, gas composition and LHV are obtained as model

outputs. Besides, tar and char contents, C content in fly ash, gas composition, gas yield

and LHV at the gasifier exit are obtained at very different operating conditions. Results

from the model for very different operating conditions are shown in our next paper

[33].

Notation

b,d Reaction orders for the species i and w.

B Biomass flow rate, kg daf/h.

cv Volumetric fraction of solids, dimensionless.

Ci Concentration of the i-th species in the gas phase, mol/m3.

daf Dry, ash free.

ER Equivalence ratio, air fed/stoichiometric air, dimensionless.

fn Corrective factor in some kinetic equations.

i (from (1)–(10)): H2,CO, CO2, CH4, C2H4, H2O, O2, tar, char.

j Air, if the specie i considered is a gas; Bdaf, if the specie i is tar or char.

kn Kinetic constant of the n-th reaction, units depending on the considered reaction.

mB Biomass flow rate (kg a.r./h).

ni Total moles of all the species in the flue gas, mol.

P Pressure in the riser, atm.

Q Volumetric gas flow rate, m3/h.

R Ideal gas constant, J/mol K (and also atm l/mol 8C in R appearing in Fig. 8).

Ri Overall reaction rate of the i-th species, units depend on the species considered.

rj Rate of the j-th reaction, units (given by the authors who provided each rate)

depend on the reaction and species considered.


T Temperature, K.

tg Mean residence time of the gas, s.

uo Superficial gas velocity at the bottom of the gasifier (gas inlet), m/s.

ut Terminal velocity of the particle, m/s.

W Mass of sand and dolomite in the gasifier (kg).

WHSV Weight hourly space velocity for the biomass [(kg biomass fed a.r.)/h]/kg solids

inventory in the CFBBG.

xi Molar fraction of the i-th species. For char, it is char concentration [kg char/kg

(sand+dolomite)].

xw Molar fraction of w, botherQ gas species which affect to the kinetics of the i-th

species. For char, it is char concentration [kg char/kg (sand+dolomite)].

yi Yield to the i-th species. For the gas species [H2,CO,CO2,CH4,C2H4,H2O, O2] its

units are (mol i/mair in3). For tar and char its units are (mol i/kg Bdaf).

Greek symbols

e Voidage in each zone of the riser, dimensionless.

s Space-time, based on m3 of riser (mR3) when the i-th species considered is a gas

component [units then: mR3/(mair,in

3/h)], or based on mass of sand and dolomite

(S+D) in the whole gasifier(WS+D) when the i-th species considered is tar or char

[units then: kgS+D/(kg Bdaf/h)].

Acknowledgment

This work was carried out under the EC-financed project no. JOR3-CT98-0306. A.

Sanz thanks J.I. Civicos for his personal help in performing this modelling. Scientific

discussions with Dr. Hao Liu from University of Leeds (Chem. Eng. Dept.) have been very

stimulating for the development of this model.

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modeling circulating fluidized bed biomass gasifiers

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