reactivity and kinetic analysis of biomass during combustion

7/28/2019 Reactivity and Kinetic Analysis of Biomass During Combustion

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Energy Procedia 17 (2012) 869 – 875

1876-6102 © 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Hainan University.

doi:10.1016/j.egypro.2012.02.181

2012 International Conference on Future Electrical Power and Energy Systems

Reactivity and Kinetic Analysis of Biomass during

Combustion

Qing Wang*, Weizhen Zhao, Hongpeng Liu, Chunxia Jia, Hao Xu

Northeast Dianli University,Jilin City, China

Abstract

The combustion experiments of four different biomass samples were conducted under different heating rates using

the thermogravimetric analyzer. Combustion characteristic curves and combustion characteristic parameters were

acquired. The research results showed that the combustion process of biomass can be broadly separated into three

stages: evaporation of water, release and combustion of volatile, combustion of fixed carbon. The biomass has an

advantage of low ignition and burnout temperature, as well as high combustion rate. The result showed feasibility of

using the first order reaction model to solve the kinetic parameters of biomass combustion. The reactivity was

evaluated using the reactivity index, and the result showed that cornstalk has a superior reactivity while sawdust has

an inferior reactivity. Through comparison of model and experimental reactivity, it gives a farther explanation that

Coats-Redfern equation is suitable to analyze the biomass combustion reaction.

© 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [name organizer]

Keywords:biomass; combustion characteristics; kinetic parameter; reactivity

1.Introduction

Biomass refers to organic matter in addition to fossil fuel, and all derive from animal and plantmaterial which can be recycled. Biomass is the most widely existed material, and the total growth

biomass on earth each year is equivalent to 10 times of the current total world energy consumption, whileonly 1% of output was used as energy. Therefore, it has an enormous potential for development and application [1]. Biomass has a great yield in China every year but has a little use. As a kind of green

energy source, the biomass has many advantages, such as advance ignition and burnout, low pollution.Basing on China's basic national conditions and the level of development and utilization of biomass,direct combustion or the combustion with other fuels is a simple and practical way which can use biomassresources efficiently [2].

Many researchers had studied the combustion of biomass. J. E. Hustad et al. proposed that there is aconsiderable unused potential for energy production by the use of biomass through combustion,gasification and other conversion techniques, both for heating purposes, electricity production and for liquid fuel production [3]. P.-X. Thivel discussed two methodologies for analyzing and ranking the risks

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© 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Hainan University.



870 Qing Wang et al. / Energy Procedia 17 (2012) 869 – 875

in a semi-industrial pilot process that chemically converts miscellaneous waste using circulating fluidized bed combustion, and they suggested that fluidized bed combustion is currently one of the most promisingmethods of energy conversion, since it burns biomass very efficiently, and produces only very smallquantities of sulphur and nitrogen oxides [4].

2.Experimental

Combustion assays were carried out using thermogravimetric analyzer (Perkin Elmer Company,USA). Approximately, 8 mg of the previously ground and sieved samples were heated under high-puritynitrogen and oxygen in an 80/20 ratio at flow rate of 100 ml/min. The samples were heated from roomtemperature up to 850°C at previously selected constant heating rates (10, 20, 50 °C/min).Weight loss(TG) curves and weight loss rate (DTG) curves were obtained as a function of temperature. The sameexperiment was repeated at least twice to ensure the repeatability and the accuracy.

The cornstalk(CS), rice straw(RS), rice hull(RH) and sawdust(SD) used in this work was from JilinProvince, China. Particle size of samples was carefully prepared in the laboratory according to the ASTMstandards. Proximate analysis, ultimate analysis, and heating values of biomass are given in Table ĉ.

3.Fundamental Principle

The extent of conversion of sample combustion a is defined by the expression

T 0

f 0

.W W

W W D

(1)

Where W T is the weight of the sample at a given temperature T ; W 0 and W f refer to the weight at the beginning and the end respectively.

The Reaction rate of biomass in the combustion process can be described by the following Arrheniusequation.

exp( ) ( ).d A E

f dT RT

D D

E

(2)

Where ȕ , A, E and R are heating rate, frequency factor, activation energy and gas constant respectively.f(Į) is mechanism function, and in this work the first order reaction f(Į)=1-Į which was used commonly in solid-phase decomposition reaction was adopted.

By rearranging Eq. (2) and integrating [5], one obtains

2

ln 1ln ln .

AR E

T E RT

D

E

ª º « »

¬ ¼(3)

Plot ln(-ln(1-Į)/T 2) vs. 1/T at the selected temperature range, and get the slope. Then, E and A values

can be obtained.Basing on Coats-Redfern equation, we regard ln(-ln(1-Į)/T

2) as the index which was used to evaluate

the reactivity of biomass combustion reaction. The biomass has a better reactivity when it has a greater reactivity index.

TABLE I. PROXIMATE A NALYSIS, ULTIMATE A NALYSIS AND HEATING VALUES OF BIOMASS

SampleProximate analysis (%) Ultimate analysis (%) Qnet,ar

(J/g) M ad V ad Aad FC ad C ad H ad N ad Oad S ad

CS 7.40 69.86 6.06 16.68 37.95 6.47 40.76 0.77 0.59 15286.78

RS 7.05 66.81 9.56 16.58 36.55 5.49 40.01 0.78 0.56 14468.90

RH 7.16 51.72 28.95 12.17 36.31 4.05 22.90 0.51 0.12 11453.77

SD 6.70 74.90 8.25 10.15 45.55 5.42 33.31 0.6 0.17 13617.06



Qing Wang et al. / Energy Procedia 17 (2012) 869 – 875 871

4.Results and Discussion

4.1.Analysis of combustion process

Fig. 1 and Fig. 2 shows the TG and DTG curves obtained from thermogravimetric experiments atthe heating rate of 20°C/min respectively. TableII shows the combustion characteristic parameters for all

samples. Ignition temperature T i was solved by using the method of TG-DTG extrapolation in thisresearch [6]. (d W/ d t )

imax is the maximum burning rate and the corresponding T

imax is the peak temperature

in stage i. Burnout temperature T h was defined as the temperature in which the weight of sample remainsunchanged.

Three pronounced regions were detected through the DTG curves of all samples. The first stagecorresponded to the water evaporation from initial temperature to 150°C. The second stage corresponded to the combustion of the pyrolytic volatile from 150 to 400°C. The third stage was due to the combustionof the fixed carbon from 400 to 600°C. The DTG curves of biomass combustion have two flammable

peaks, and the first peak value is larger and wider due to more volatile of biomass and the feature of porosity as well as the disorder of the carbon structure [7]. Therefore, flammable substance burned focusing on this stage. The combustion characteristic parameters obtained in this work were compared with references [8,9,10],and we know that biomass has the low ignition temperature and burnout

temperature. The ignition temperature and burnout temperature of biomass studied in this paper were260-300 °C and 530-580°C respectively, besides biomass has a higher reaction rate.

0 200 400 600 800 1000

0

20

40

60

80

100

W e i g h t ( % )

T (ć)

CS

RS

RH

SD

0 200 400 600 800 1000

-16

-14

-12

-10

-8

-6

-4

-2

0

2

W e i g h t l o s s r a t e ( % / m i n )

T (ć)

CS

RS

RH

SD

Figure 1. TG curves of the samples at the heating rate of 20°C/min. Figure 2. DTG curves of the samples at the heating rate of

20°C/min.

TABLE II. COMBUSTION CHARACTERISTICS PARAMETERS OF SAMPLES UNDER HEATING R ATE OF 20 °C/MIN

SampleT i

(°C)

T h(°C)

T 1max

(°C)

(dW/ dt )1max

(%/min)

T 2max

(°C)

(dW/ dt )2max

(%/min)

CS 261 535 308 13.49 475 4.57

RS 257 564 313 11.56 492 3.65

RH 276 568 322 9.49 495 2.89

SD 293 578 357 14.86 512 3.73

4.2.Analysis of combustion characteristics at different heating rates

Cornstalk was taken, for example, to analyze the impact of heating rate on the combustioncharacteristics. Fig. 3 and Fig. 4 showed the TG and DTG curves for cornstalk obtained fromthermogravimetric experiments at different heating rates. Table III shows the combustion characteristic

parameters. It was observed that there is a lateral shift to higher temperatures for TG and DTG curves




with the addition of heating rate. Meanwhile, T i, T h, T 1

max, and T 1

max also increased with the increasing of heating rate. This is because the temperature gradient between inside and outside is greater, whichdoes not favor release of volatile matter. Moreover, there is less burning time so it isdisadvantageous to burn out. However, the burning rate (d W/ d t )

1max and (d W/ d t )

2max increased with

the increasing of heating rate, which was due to stronger thermal shock acquired in short time, thusthe reaction rate of samples with oxygen accelerated.

0 200 400 600 800 1000

0

20

40

60

80

100

W e i g h t ( % )

7ć

ćPLQ

ćPLQ

ćPLQ

Figure 3. Combustion TG curves of cornstalk at various heating rates

0 200 400 600 800 1000

-35

-30

-25

-20

-15

-10

-5

0

5

W e i g h t l o s s r a t e ( % / m i n )

7ć

ćPLQ

ćPLQ

ćPLQ

Figure 4. Combustion DTG curves of cornstalk at various heating rates

TABLE III. COMBUSTION CHARACTERISTICS PARAMETERS OF CORNSTALK AT VARIOUS HEATING R ATES

Heating rate

(°C/min)

T i(°C)

T h(°C)

T 1max

(°C)

(dW/ dt )1max

(%/min)

T 2max

(°C)

(dW/ dt )2max

(%/min)

10 251 509 296 6.59 456.15 2.54

20 261 535 308 13.49 475.23 4.57

50 284 676 335 31.66 534.78 5.04

4.3.Analysis of kinetic parameters

We analyzed the kinetic parameter in the volatile combustion stage and fixed carbon burning stage

respectively without regard to the water evaporation. Theactivation energy and frequency factor calculated from the slope of the Coats- Redfern plots are included in Table IV together with their corresponding linear regression coefficients. It can be seen from Table IVthat the correlation coefficient of this test is very high, so it shows that the first order kinetic model isfeasible. Biomass has lower activation energy in this work, which aggres reasonably well with thosereported in the references [11,12].




4.4.Reactivity evaluation

The reactivity index in the volatile combustion stageand fixed carbon burning stage from curves plotted as a function of temperature T for the samples isshown in Fig. 5 respectively. Fig. 5 represents that the reactivity index increased with the addition of temperature for all samples we studied, and the main cause was that the addition of temperature provided

more energy. The reactivity index of four kinds of biomass was compared in this work. Descending order of the reactivity index in the volatile combustion stage is rice straw, cornstalk, rice hull and sawdust,while in fixed carbon burning stage it is cornstalk, rice hull, rice straw and sawdust. Taken together,cornstalk has a better reactivity in the whole stage while sawdust has a worse reactivity.

Cornstalk was taken, for example, to analyze reactivity of different heating rate. The reactivity indexin the volatile combustion stage and fixed carbon burning stage from curves plotted as a function of temperature T for cornstalk at different heating rates is shown in Fig. 6 respectively. Fig. 6 shows that thereactivity index decreased with the addition of heating rate for all samples we studied, and the main causewas that the addition of heating rate led to less heating time, so the reaction can not be carried outsufficiently. Therefore, the addition of heating rate is bad for the reactivity of cornstalk.

Fig. 7 shows the comparison curves of experimental and model reactivity index in the volatile

combustion stage and fixed carbon burning stage respectively. The results indicated that there are some

differences in model and experiment values at the beginning temperature region, and except this theycoincided very well. Therefore, it shows that Coats-Redfern equation is suitable to analyze the biomass

combustion reaction.

Table IV Kinetic Parameters for Combustion of BiomassSample temperature range

(°C)

activation energy

E (kJ/mol)

frequency factor

A (min-1)

linear regression coefficients

CS130-383 62.39 1.42×105 0.9706

383-555 124.02 2.36×108 0.9444

RS142-390 62.20 1.44×105 0.9686

390-586 102.06 3.49×106 0.9864

RH154-388 78.09 2.97×106 0.9879

388-586 98.61 2.19×106 0.9811

SD150-400 75.07 1.08×106 0.9859

400-597 108.40 7.62×106 0.9769

100 150 200 250 300 350 400

-24

-22

-20

-18

-16

-14

-12

-10

l n - l n ( 1 - a ) / T 2

T (ć)

&6

56

5+

6'

400 440 480 520 560 600

-20

-18

-16

-14

-12

-10

l n - l n ( 1 - a ) / T 2

T (ć)

CS

RS

RH

SD

a) The volatile combustion stage b) The fixed carbon burning stageFigure 5. The reactivity for all samples under heating rate of 20°C/min




150 200 250 300 350 400

-24

-22

-20

-18

-16

-14

-12

-10

l n - l n ( 1 - a ) / T 2

T (ć)

ćPLQ

ćPLQćPLQ

400 440 480 520 560 600 640 680

-20

-18

-16

-14

-12

-10

l n - l n ( 1 - a ) / T 2

T (ć)

ćPLQ

ćPLQ

ćPLQ

a) The volatile combustion stage b) The fixed carbon burning stage

Figure 6. The reactivity of cornstalk at different heating rates

100 150 200 250 300 350 400

-22

-20

-18

-16

-14

-12

-10

l n - l n ( 1 - a ) / T 2

T (ć)

Experimental

Model

400 440 480 520 560

-20

-18

-16

-14

-12

-10

l n - l n ( 1 - a ) / T 2

T (ć)

Experimental

Model

a) The volatile combustion stage b) The fixed carbon burning stage

Figure 7. Comparison of the model and experimental reactivity

5.Conclusions

y Biomass is easy to ignite and burn out. This is in part due to the generally higher volatile content and

lower ash content. Three pronounced regions were detected for all samples: water evaporation, volatile

combustion and fixed carbon burning. The combustion reacts mainly in the volatile combustion stage.

y Ignition temperature, burnout temperature and the peak temperature of cornstalk increase with the

addition of heating rate, which is disadvantageous to biomass combustion, but the reaction rate

accelerate at higher heating rate.

y The activation energy and frequency factor for samples was analyzed by Coats-Redfern equation and

the first order model. The result shows the feasibility by this method. Biomass studied in this work has

the lower activation energy.

y Reactivity of biomass is very important for the development and optimization of combustion systems.

The results showed that cornstalk has a better reactivity in the whole stage while sawdust has a worse

reactivity, and the addition of heating rate is bad for the reactivity of cornstalk. Through comparison of

model and experimental reactivity, it gives a farther explanation that Coats-Redfern equation is

suitable to analyze the biomass combustion reaction.

References




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[2] H. P. Chen, B. Li, H. P. Yang, “Status and Prospect of Biomass Combustion Technology,” Industrial Boiler(China),

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[3] J. E. Hustad, O. Skreiberg, O. K. Sonju, “Biomass Combustion Research and Utilization in IEA Countries,” Biomass

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[9] S. G. Sahu, P. Sarkar, N. Chakraborty, “Thermogravimetric assessment of combustion characteristics of blends of a

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[11] O. Senneca, “Kinetics of pyrolysis, combustion and gasification of three biomass fuels,” Fuel Processing Technology,

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[12] Y. Zhaosheng, M. Xiaoqian, L. Ao, “Kinetic studies on catalytic combustion of rice and wheat straw air- and

oxygen-enriched atmospheres,by using thermogravimetric analysis,” Biomass& Bioenergy, vol. 32, 2008, pp. 1046-1055.

reactivity and kinetic analysis of biomass during combustion

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