- Email: [email protected]
Kinetics of thermochemical conversion of the lignite coal in steam flow
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Energy Procedia 158 Energy Procedia 00(2019) (2017)2210–2214 000–000 www.elsevier.com/locate/procedia
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China
Kinetics of thermochemical conversion of the lignite coal in steam Kinetics ofThe thermochemical conversion of the lignite coal in steam 15th International Symposium Heating and Cooling flow on District flow Alexander Kozlov* Assessing the feasibility of using the heat demand-outdoor Alexander Kozlov* Kutateladze Institute of Thermophysics, Siberian Branch of the Russian Academy of Sciences, temperature function a long-term district heatofdemand forecast Academician Lavrentyev Avenue.1, Novosibirsk, 630090, Academy Russia Kutateladze Institute of for Thermophysics, Siberian Branch of the Russian Sciences, a,b,c
I. Andrić a
Academician Lavrentyev Avenue.1, Novosibirsk, 630090, Russia
*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
Abstract b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Abstract Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Thermal analysis was applied to determine the kinetic coefficients of the processes that occur in the gasifier. To this end the Thermal was applied to to run determine the kinetic of thermal the processes thatunder occurstrict in the gasifier. To this the conditionsanalysis for such processes were simulated in coefficients the furnace of analysis kinetic control. The end kinetic conditions processes to run were simulated in of thesolid furnace thermal analysis under strict kineticsoftware control. package The kinetic coefficientsfor of such the stages of thermochemical conversion fuelsofusing the NETZSCH Thermokinetics are coefficients theeffect stagesofofthe thermochemical solid fuels using thethe NETZSCH Thermokinetics software package Abstract of determined. The steam contentconversion in the gasofcomposition during thermochemical conversion of lignite coalare is determined. The effect on of the steam steam content content ininthe thecomposition gas composition the thermochemical conversion of lignite is established. Depending of theduring gas, competition of mechanisms of interaction of coal carbon established. Depending on the content in the composition of the as gas, competition of effective mechanisms of interaction of carbon District aresteam commonly addressed in the literature one of the most solutions for decreasing the char with heating steam isnetworks shown. char with steam shown. from the building sector. These systems require high investments which are returned through the heat greenhouse gasisemissions sales. Due to theElsevier changed climate conditions and building renovation policies, heat demand in the future could decrease, Copyright © 2018 Ltd. All rights reserved. © 2019 The Published by Elsevier Ltd. Copyright ©Authors. 2018 Elsevier Ltd. Allperiod. rights reserved. prolonging the investment return Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under of the of scientific committee of the 10th International Conference The main scope this paper is of toresponsibility assess the feasibility using the heat –demand – outdoor temperature function for on heatApplied demand Energy (ICAE2018). Peer-review underofresponsibility the scientific committee of ICAE2018 The 10th International Conference on Applied Energy. Energy (ICAE2018). forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Keywords: coal, thermal kinetics,period Ar/H2O buildingslignite that vary in bothanalysis, construction and typology. Three weather scenarios (low, medium, high) and three district Keywords: lignite coal, thermal kinetics, Ar/H2O renovation scenarios were analysis, developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. results showed that when only weather change is considered, the margin of error could be acceptable for some applications 1.The Introduction 1.(the Introduction error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error increased up to 59.5% the weather andinformation renovation scenarios combinationregularities considered). A key aspect of value numerical modeling of the (depending conversiononprocesses is the about quantitative The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the A key aspect of numerical modeling of the conversion processes is the information about quantitative regularities of chemical processes that take place during thermochemical fuel conversion. [1]. The precision of kinetic decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather of chemical processes that take place during thermochemical fuel conversion. [1]. The precision of kinetic coefficients determination preprograms the validity of estimates of the determined models. Development and of renovation scenarios considered). On the other function increased 7.8-12.7% per decadeDevelopment (depending on of the coefficients determination preprograms thehand, validity of intercept estimates of the for determined models. numerical modeling of the gasification processes is hampered by the insufficient knowledge about their mechanisms coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and numerical modeling of the gasification processes is hampered by the insufficient knowledge about their mechanisms improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +79041467899; fax: +7(383) 330-84-80. Cooling. address:author. [email protected] * E-mail Corresponding Tel.: +79041467899; fax: +7(383) 330-84-80. E-mail address: [email protected]
Keywords: Heat demand; Forecast; Climate change 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.158
2
Alexander Kozlov / Energy Procedia 158 (2019) 2210–2214 Kozlov A. / Energy Procedia 00 (2018) 000–000
2211
(which results in high variability of kinetic coefficients), as well as by the lack of uniform methods for obtaining and incorporating those coefficients [2]. The fuel conversion is a complex heterogeneous incomplete combustion process that integrates a big number of elementary stages which are quite difficult to investigate individually. Therefore, the problem of describing the fuel conversion mechanism is quite challenging [3]. In this regard, the majority of researchers approximate the fuel gasification kinetics by the first order reaction in a single-stage process without taking into consideration the individual tar formation, devolatilization, and char conversion, which results in large deviation of the predicted rates of the process under study from the measured values [4, 5]. The issue of obtaining reliable kinetic coefficients during the reaction of fuel with steam remains relevant. [6]. In this context, this paper studies the char conversion kinetics depending on the type and content of the reactant gas (steam) in the gas composition. 2. Experimental section The experimental studies were carried out with the help of the NETZSCH complex for simultaneous thermal analysis. This complex comprises the STA 449 F1 unit for thermal analysis, the QMS 403 C quadrupole mass spectrometer, and the PulseTA unit for pulse thermal analysis. Azey coal (lignite, bituminous) was used for this study. The proximate and ultimate analyses are given in table 1. Properties of coal were calculated by the method described in paper [7]. The coal was sieved to obtain particle sizes of 0.1 and 0.2 mm. Table 1. Coal properties. Coal Proximate (as rec’d basis, wt.%) Azey
Ultimate (daf basis. wt.%)
Moi.
VM
FC
ASH
C
H
O
N
S
12.2
35.4
47.0
7.6
77.6
4.5
17.0
0.7
0.1
Moi – moisture, VM – volatile matter, FC – fixed carbon, daf – dry ash free
The samples of lignite 20-30 mg each were placed into the alumina crucible that has a shape of a small plate. The flat shape of the crucible ensures that the oxidizer evenly reaches the char particles. The samples were heated at the rate of 10 °С/min, 15 °С/min and 20 °С/min from 35°С to the reaction termination temperature (which was indicated by no change in the sample mass as the temperature grew). During the process, the content of the reactant gas was varied in the gas composition. The maximum content of the reactant gas in the reactive medium was determined by the flow of argon that enters the thermal analysis device to protect the weight block. Argon was also used to control the active component concentration in the reactive medium. The end gaseous products were recorded within the mass range from 1 to 200 with ionization by electron impact at 70 eV. Calibration of the mass spectrometer signal was carried out by pulsing the corresponding calibration gases. The authors determined kinetic coefficients of the heterophase reaction at different stages of conversion process by using standard tools of thermal analysis. In general the problem of determining coefficients is reduced to choice of a hypothesis of the heterogeneous conversion that interprets an instrumentally obtained curve (or position of its individual points) most accurately. The program for determination of kinetic coefficients applies the multi-variant regression method, in which reaction characteristics are calculated by the numerical differentiation of reaction rate equation (1) on the basis of the Runge-Kutta method of order 5 by using the Dormand-Prince scheme: dx d
EA 1 x n RT
A exp
(1)
where x – conversion degree of the initial sample; А – pre-exponential factor, s-1; ЕА – activation energy, J/mole; n – apparent reaction order; R – universal gas constant, 8.314 J/mole K; τ – time, s; T – temperature, °С. In this case the sum minimum of squares of the conversion degree deviation for the calculated values from the thermogravimetrically measured values is calculated in accordance with the maximum similarity theorem by equation (2):
Alexander Procedia 158000–000 (2019) 2210–2214 Kozlov A. /Kozlov Energy/ Energy Procedia 00 (2018)
2212
S
1 N
iN1 xi ,exp xi ,cal
2 Min
3
(2)
where N – number of iterations. Change of temperature versus time is expressed by equation (3): (3) T T0 t
where Т0 – initial temperature, °С; β – sample heating rate, °С/min. Conversion degree of the sample is determined based on expression (4): x
m0 m
(4)
m0 m f
where m0 – initial sample mass, mg; m – current sample mass, mg; mf – final sample mass, mg. The process is divided into stages according to the technique in [8-12], and each can be described by equation (10) for the chosen hypothesis of mechanism. In the present work each stage of the thermochemical conversion process is described by the one-stage reaction of the n-th order. 3. Results and discussion Figure 1 shows thermograms of the steam lignite conversions obtained for various proportions of steam in the gas composition.
Fig. 1. Thermograms of the lignite coal conversion in steam atmosphere (heating rate – 10°C/min)
The thermograms show that the coal conversion process includes three stages – drying, devolatilization and carbon residue conversion. Coal is dried at temperatures from 40°C to 180°С. Devolatilization takes place within the temperature range from 320 to 580 °С and is accompanied by release primarily of short hydrocarbons, СО, Н 2, СО2, Н2О into the gaseous phase. Kinetics of devolatilization at this stage is almost the same (Table 2). Meanwhile, the coal char conversion process largely depends on the reactive medium composition. Therefore, the further processing of the thermal analysis results was carried out only for the char conversion stage. In the steam medium within the temperature range 700 – 900°С the char carbon interacts with Н2О, forming СО, СО2 and Н2. Table 2 presents values of kinetic coefficients for the steam conversion calculated for different heating rates. Table 2. Kinetic coefficients for coal-steam conversion The content of 2 Heating Stage the reagent rate, °C/min gas, %, Parameters lgA, s-1 7.7 Ea, 132.2 kJ/mole Devolatilization 10 n 2.1 T, °C 300-540 lgA, s-1 1.9 char-steam
5
7
10
28
47
67
7.8 132.9
8.4 140.2
7.7 133.5
8 135.4
6.4 117.2
6.5 117.6
2.1 300-540 3.4
2.2 300-540 4.8
2.1 300-540 6.5
2.2 300-540 7
1.8 300-540 8.3
1.8 300-540 8.1
4
Alexander Kozlov / Energy Procedia 158 (2019) 2210–2214 Kozlov A. / Energy Procedia 00 (2018) 000–000
conversion
Devolatilization 15 char-steam conversion
Devolatilization 20 char-steam conversion
Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C
2213
106.9
132.6
159.3
189.4
197
220.3
218.6
0.5 680-985 5.7 106.2
0.6 680-940 7 122.4
0.8 680-940 7.4 127.6
0.8 680-900 7.6 124.3
0.8 680-880 6.6 117.9
0.9 680-880 6.1 111.3
0.9 680-880 5.8 108.8
1.7 300-540 1.8 102.5
2.1 300-540 2.8 121.1
2.3 300-540 3.5 131.5
1.9 300-540 4.1 143.8
1.8 300-540 6.2 182.1
1.8 300-540 6.6 189.3
1.7 300-540 7.2 200.2
0.6 680-1025 5.3 97.9
0.5 680-990 7.8 130.3
0.6 680-960 6.5 113.6
0.7 680-960 6.7 116.8
0.8 680-920 6.1 109.4
0.8 680-900 6.6 115.8
0.9 680-900 5.9 107.8
1.6 300-540 0.8 79.9
2.3 300-540 1.8 99.8
1.9 300-540 3 121.1
1.9 300-540 4.4 146.2
1.7 300-540 5.3 162.1
1.8 300-540 5.7 169.1
1.6 300-540 6.9 193.1
0.4 680-1050
0.5 680-1000
0.6 680-990
0.8 680-960
0.7 680-930
0.7 680-925
0.9 680-910
The mass-spectrometric measurements determined volume ratios of СО and СО2 in the composition of gas produced by the steam char conversion. Table 3 reflects the amount of the resulting СО and СО2 on the steam percentage in the gas composition. Table 3. Content of CO and СО2 in the gaseous phase depending on the steam share in the blast Heating rate, °C/min 10 15 20
Component, % vol. СО СО2 СО СО2 СО СО2 ̅̅̅̅ CO ̅̅̅̅̅̅ CO2
2 72.4 26.8 78.5 20.7 76.3 22.8
5 58.4 40.5 65.3 33.6 70.6 28.5
7 52.3 46.5 63 35.6 62.4 36.5
10 41.2 57.4 53.9 44.8 54.4 44.4
28 35.9 62.5 41.3 57.2 49.2 49.5
47 36.9 61.4 40.7 57.5 43.2 55.2
67 34.4 63.8 37.7 60.6 30.4 68.4
75.7
64.8
59.2
49.8
42.1
40.3
34.2
23.4
34.2
39.5
48.9
56.4
58.0
64.3
With increasing share of steam in the gas composition, the values of all the determined kinetic coefficients increase and the reaction completion temperature decreases. On the one hand, the observed change in the preexponential factor and the activation energy agrees with the kinetic data for the case of pure pyrolysis. On the other hand, the data obtained suggest that in the case of steam blasting, there is a competition between two alternative mechanisms of heterophase interaction of steam with carbon, as well as a homophase water-shift reaction. And with the increase in the proportion of steam in the composition of the gas, the prevailing mechanism is the latter. This can explain the relatively sharp change in the observed order of the reaction. In addition, when the char is converted from a fraction of steam in the gas composition to 10%, a transitional combustion regime is realized, in which diffusion phenomena and sorption processes on the surface of the fuel particle are significant. With a further increase in the fraction of steam, the kinetic combustion regime is realized, at which the rate of reaction ceases to depend on the content of the oxidant in the gas composition
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Alexander Kozlov / Energy Procedia 158 (2019) 2210–2214 Kozlov A. / Energy Procedia 00 (2018) 000–000
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4. Conclusion We determined the effect of the gas composition on the conversion kinetics of the lignite coal. It was shown that the devolatiliztion rates little depend on the content steam in the reactive medium composition. The content steam significantly affects the rate and mechanism of the char residue decomposition. The steam char conversion with a low steam conversion (10%) entails domination of the heterophase interaction between the char and water steam, which then transforms into a homophase mechanism described by a water-shift reaction. Furthermore, the volumetric reaction model evolves into the grain model. Acknowledgements The research was performed at Kutateladze Institute of Thermophysics SB RAS under the support of Russian Science Foundation (Grant № 15-19-10025). References [1]. M. La Villetta, M. Costa, N. Massarotti, Modelling approaches to biomass gasification:A review with emphasis on the stoichiometric method, Renew. Sustain. En. Rev. 74 (2017) 71-88. 2. Z. Zhou, L. Chen, L. Guo, B. Qian, Z. Wang, K. Cen, Computational modeling of oxycoal combustion with intrinsic heterogeneous char reaction models, Fuel Process. Technol. 161 (2017) 169-181. 3. S. Iwaszenko, Using Mathematica software for coal gasification simulations – Selected kinetic model application, J. Sustainable. Mining. 14 (2015) 21-29. 4. E. Popova, A. Chernov, P. Maryandyshev, A. Brillard, D. Kehrlib, G. Trouvé, V. Lyubov, J-F. Brilhac, Thermal degradations of wood biofuels, coals and hydrolysis lignin from the Russian Federation: Experiments and modeling, Bioresource. Tech. 218 (2016) 1046-1054. 5. F. Wang, X. Zeng, Y. Wang, J. Yu, G. Xu, Characterization of coal char gasification with steam in a microfluidized bed reaction analyzer, Fuel Process. Technol. 141 (2016) 2-8. 6. A. Zoulalian, R. Bounaceur, A. Dufour, Kinetic modelling of char gasification by accounting for the evolution of the reactive surface area, Chem. Engin. Sc. 138 (2015) 281-290. 7. A.N. Kozlov, D.A. Scishchev, I.G. Donskoy, V.A. Shamansky, A.F. Ryzhkov, A technique proximate and ultimate analysis of solid fuels and coal tar, Thermal Anal. Calorimetry. 122 (2015) 1213-1220. 8. J.P. Sanders, P.K. Gallagher, Kinetic analyses using simultaneous TG/DSC measurements, Thermal Anal. Calorimetry. 82 (2005) 659-664. 10. H. Tanaka, M.E. Brown, The theory and practice of thermoanalitical kinetics of solid state reactions, Thermal Anal. Calorimetry. 80 (2005) 795-797. 11. E. Moukhina, Determination of kinetic mechanisms for reactions measured with thermoanalytical instruments, Thermal Anal. Calorimetry. 109 (2012) 1203-1214. 12. A.N. Kozlov, D.A. Svishchev, G.I. Khudyakova, A.F. Ryzhkov A kinetic analysis of the thermochemical conversion of solid fuels (A review), Solid Fuel Chemistry. 51 (2017) 205-213.
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10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China
Kinetics of thermochemical conversion of the lignite coal in steam Kinetics ofThe thermochemical conversion of the lignite coal in steam 15th International Symposium Heating and Cooling flow on District flow Alexander Kozlov* Assessing the feasibility of using the heat demand-outdoor Alexander Kozlov* Kutateladze Institute of Thermophysics, Siberian Branch of the Russian Academy of Sciences, temperature function a long-term district heatofdemand forecast Academician Lavrentyev Avenue.1, Novosibirsk, 630090, Academy Russia Kutateladze Institute of for Thermophysics, Siberian Branch of the Russian Sciences, a,b,c
I. Andrić a
Academician Lavrentyev Avenue.1, Novosibirsk, 630090, Russia
*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
Abstract b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Abstract Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Thermal analysis was applied to determine the kinetic coefficients of the processes that occur in the gasifier. To this end the Thermal was applied to to run determine the kinetic of thermal the processes thatunder occurstrict in the gasifier. To this the conditionsanalysis for such processes were simulated in coefficients the furnace of analysis kinetic control. The end kinetic conditions processes to run were simulated in of thesolid furnace thermal analysis under strict kineticsoftware control. package The kinetic coefficientsfor of such the stages of thermochemical conversion fuelsofusing the NETZSCH Thermokinetics are coefficients theeffect stagesofofthe thermochemical solid fuels using thethe NETZSCH Thermokinetics software package Abstract of determined. The steam contentconversion in the gasofcomposition during thermochemical conversion of lignite coalare is determined. The effect on of the steam steam content content ininthe thecomposition gas composition the thermochemical conversion of lignite is established. Depending of theduring gas, competition of mechanisms of interaction of coal carbon established. Depending on the content in the composition of the as gas, competition of effective mechanisms of interaction of carbon District aresteam commonly addressed in the literature one of the most solutions for decreasing the char with heating steam isnetworks shown. char with steam shown. from the building sector. These systems require high investments which are returned through the heat greenhouse gasisemissions sales. Due to theElsevier changed climate conditions and building renovation policies, heat demand in the future could decrease, Copyright © 2018 Ltd. All rights reserved. © 2019 The Published by Elsevier Ltd. Copyright ©Authors. 2018 Elsevier Ltd. Allperiod. rights reserved. prolonging the investment return Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under of the of scientific committee of the 10th International Conference The main scope this paper is of toresponsibility assess the feasibility using the heat –demand – outdoor temperature function for on heatApplied demand Energy (ICAE2018). Peer-review underofresponsibility the scientific committee of ICAE2018 The 10th International Conference on Applied Energy. Energy (ICAE2018). forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Keywords: coal, thermal kinetics,period Ar/H2O buildingslignite that vary in bothanalysis, construction and typology. Three weather scenarios (low, medium, high) and three district Keywords: lignite coal, thermal kinetics, Ar/H2O renovation scenarios were analysis, developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. results showed that when only weather change is considered, the margin of error could be acceptable for some applications 1.The Introduction 1.(the Introduction error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error increased up to 59.5% the weather andinformation renovation scenarios combinationregularities considered). A key aspect of value numerical modeling of the (depending conversiononprocesses is the about quantitative The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the A key aspect of numerical modeling of the conversion processes is the information about quantitative regularities of chemical processes that take place during thermochemical fuel conversion. [1]. The precision of kinetic decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather of chemical processes that take place during thermochemical fuel conversion. [1]. The precision of kinetic coefficients determination preprograms the validity of estimates of the determined models. Development and of renovation scenarios considered). On the other function increased 7.8-12.7% per decadeDevelopment (depending on of the coefficients determination preprograms thehand, validity of intercept estimates of the for determined models. numerical modeling of the gasification processes is hampered by the insufficient knowledge about their mechanisms coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and numerical modeling of the gasification processes is hampered by the insufficient knowledge about their mechanisms improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +79041467899; fax: +7(383) 330-84-80. Cooling. address:author. [email protected] * E-mail Corresponding Tel.: +79041467899; fax: +7(383) 330-84-80. E-mail address: [email protected]
Keywords: Heat demand; Forecast; Climate change 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018). 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.158
2
Alexander Kozlov / Energy Procedia 158 (2019) 2210–2214 Kozlov A. / Energy Procedia 00 (2018) 000–000
2211
(which results in high variability of kinetic coefficients), as well as by the lack of uniform methods for obtaining and incorporating those coefficients [2]. The fuel conversion is a complex heterogeneous incomplete combustion process that integrates a big number of elementary stages which are quite difficult to investigate individually. Therefore, the problem of describing the fuel conversion mechanism is quite challenging [3]. In this regard, the majority of researchers approximate the fuel gasification kinetics by the first order reaction in a single-stage process without taking into consideration the individual tar formation, devolatilization, and char conversion, which results in large deviation of the predicted rates of the process under study from the measured values [4, 5]. The issue of obtaining reliable kinetic coefficients during the reaction of fuel with steam remains relevant. [6]. In this context, this paper studies the char conversion kinetics depending on the type and content of the reactant gas (steam) in the gas composition. 2. Experimental section The experimental studies were carried out with the help of the NETZSCH complex for simultaneous thermal analysis. This complex comprises the STA 449 F1 unit for thermal analysis, the QMS 403 C quadrupole mass spectrometer, and the PulseTA unit for pulse thermal analysis. Azey coal (lignite, bituminous) was used for this study. The proximate and ultimate analyses are given in table 1. Properties of coal were calculated by the method described in paper [7]. The coal was sieved to obtain particle sizes of 0.1 and 0.2 mm. Table 1. Coal properties. Coal Proximate (as rec’d basis, wt.%) Azey
Ultimate (daf basis. wt.%)
Moi.
VM
FC
ASH
C
H
O
N
S
12.2
35.4
47.0
7.6
77.6
4.5
17.0
0.7
0.1
Moi – moisture, VM – volatile matter, FC – fixed carbon, daf – dry ash free
The samples of lignite 20-30 mg each were placed into the alumina crucible that has a shape of a small plate. The flat shape of the crucible ensures that the oxidizer evenly reaches the char particles. The samples were heated at the rate of 10 °С/min, 15 °С/min and 20 °С/min from 35°С to the reaction termination temperature (which was indicated by no change in the sample mass as the temperature grew). During the process, the content of the reactant gas was varied in the gas composition. The maximum content of the reactant gas in the reactive medium was determined by the flow of argon that enters the thermal analysis device to protect the weight block. Argon was also used to control the active component concentration in the reactive medium. The end gaseous products were recorded within the mass range from 1 to 200 with ionization by electron impact at 70 eV. Calibration of the mass spectrometer signal was carried out by pulsing the corresponding calibration gases. The authors determined kinetic coefficients of the heterophase reaction at different stages of conversion process by using standard tools of thermal analysis. In general the problem of determining coefficients is reduced to choice of a hypothesis of the heterogeneous conversion that interprets an instrumentally obtained curve (or position of its individual points) most accurately. The program for determination of kinetic coefficients applies the multi-variant regression method, in which reaction characteristics are calculated by the numerical differentiation of reaction rate equation (1) on the basis of the Runge-Kutta method of order 5 by using the Dormand-Prince scheme: dx d
EA 1 x n RT
A exp
(1)
where x – conversion degree of the initial sample; А – pre-exponential factor, s-1; ЕА – activation energy, J/mole; n – apparent reaction order; R – universal gas constant, 8.314 J/mole K; τ – time, s; T – temperature, °С. In this case the sum minimum of squares of the conversion degree deviation for the calculated values from the thermogravimetrically measured values is calculated in accordance with the maximum similarity theorem by equation (2):
Alexander Procedia 158000–000 (2019) 2210–2214 Kozlov A. /Kozlov Energy/ Energy Procedia 00 (2018)
2212
S
1 N
iN1 xi ,exp xi ,cal
2 Min
3
(2)
where N – number of iterations. Change of temperature versus time is expressed by equation (3): (3) T T0 t
where Т0 – initial temperature, °С; β – sample heating rate, °С/min. Conversion degree of the sample is determined based on expression (4): x
m0 m
(4)
m0 m f
where m0 – initial sample mass, mg; m – current sample mass, mg; mf – final sample mass, mg. The process is divided into stages according to the technique in [8-12], and each can be described by equation (10) for the chosen hypothesis of mechanism. In the present work each stage of the thermochemical conversion process is described by the one-stage reaction of the n-th order. 3. Results and discussion Figure 1 shows thermograms of the steam lignite conversions obtained for various proportions of steam in the gas composition.
Fig. 1. Thermograms of the lignite coal conversion in steam atmosphere (heating rate – 10°C/min)
The thermograms show that the coal conversion process includes three stages – drying, devolatilization and carbon residue conversion. Coal is dried at temperatures from 40°C to 180°С. Devolatilization takes place within the temperature range from 320 to 580 °С and is accompanied by release primarily of short hydrocarbons, СО, Н 2, СО2, Н2О into the gaseous phase. Kinetics of devolatilization at this stage is almost the same (Table 2). Meanwhile, the coal char conversion process largely depends on the reactive medium composition. Therefore, the further processing of the thermal analysis results was carried out only for the char conversion stage. In the steam medium within the temperature range 700 – 900°С the char carbon interacts with Н2О, forming СО, СО2 and Н2. Table 2 presents values of kinetic coefficients for the steam conversion calculated for different heating rates. Table 2. Kinetic coefficients for coal-steam conversion The content of 2 Heating Stage the reagent rate, °C/min gas, %, Parameters lgA, s-1 7.7 Ea, 132.2 kJ/mole Devolatilization 10 n 2.1 T, °C 300-540 lgA, s-1 1.9 char-steam
5
7
10
28
47
67
7.8 132.9
8.4 140.2
7.7 133.5
8 135.4
6.4 117.2
6.5 117.6
2.1 300-540 3.4
2.2 300-540 4.8
2.1 300-540 6.5
2.2 300-540 7
1.8 300-540 8.3
1.8 300-540 8.1
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Alexander Kozlov / Energy Procedia 158 (2019) 2210–2214 Kozlov A. / Energy Procedia 00 (2018) 000–000
conversion
Devolatilization 15 char-steam conversion
Devolatilization 20 char-steam conversion
Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C lgA, s-1 Ea, kJ/mole n T, °C
2213
106.9
132.6
159.3
189.4
197
220.3
218.6
0.5 680-985 5.7 106.2
0.6 680-940 7 122.4
0.8 680-940 7.4 127.6
0.8 680-900 7.6 124.3
0.8 680-880 6.6 117.9
0.9 680-880 6.1 111.3
0.9 680-880 5.8 108.8
1.7 300-540 1.8 102.5
2.1 300-540 2.8 121.1
2.3 300-540 3.5 131.5
1.9 300-540 4.1 143.8
1.8 300-540 6.2 182.1
1.8 300-540 6.6 189.3
1.7 300-540 7.2 200.2
0.6 680-1025 5.3 97.9
0.5 680-990 7.8 130.3
0.6 680-960 6.5 113.6
0.7 680-960 6.7 116.8
0.8 680-920 6.1 109.4
0.8 680-900 6.6 115.8
0.9 680-900 5.9 107.8
1.6 300-540 0.8 79.9
2.3 300-540 1.8 99.8
1.9 300-540 3 121.1
1.9 300-540 4.4 146.2
1.7 300-540 5.3 162.1
1.8 300-540 5.7 169.1
1.6 300-540 6.9 193.1
0.4 680-1050
0.5 680-1000
0.6 680-990
0.8 680-960
0.7 680-930
0.7 680-925
0.9 680-910
The mass-spectrometric measurements determined volume ratios of СО and СО2 in the composition of gas produced by the steam char conversion. Table 3 reflects the amount of the resulting СО and СО2 on the steam percentage in the gas composition. Table 3. Content of CO and СО2 in the gaseous phase depending on the steam share in the blast Heating rate, °C/min 10 15 20
Component, % vol. СО СО2 СО СО2 СО СО2 ̅̅̅̅ CO ̅̅̅̅̅̅ CO2
2 72.4 26.8 78.5 20.7 76.3 22.8
5 58.4 40.5 65.3 33.6 70.6 28.5
7 52.3 46.5 63 35.6 62.4 36.5
10 41.2 57.4 53.9 44.8 54.4 44.4
28 35.9 62.5 41.3 57.2 49.2 49.5
47 36.9 61.4 40.7 57.5 43.2 55.2
67 34.4 63.8 37.7 60.6 30.4 68.4
75.7
64.8
59.2
49.8
42.1
40.3
34.2
23.4
34.2
39.5
48.9
56.4
58.0
64.3
With increasing share of steam in the gas composition, the values of all the determined kinetic coefficients increase and the reaction completion temperature decreases. On the one hand, the observed change in the preexponential factor and the activation energy agrees with the kinetic data for the case of pure pyrolysis. On the other hand, the data obtained suggest that in the case of steam blasting, there is a competition between two alternative mechanisms of heterophase interaction of steam with carbon, as well as a homophase water-shift reaction. And with the increase in the proportion of steam in the composition of the gas, the prevailing mechanism is the latter. This can explain the relatively sharp change in the observed order of the reaction. In addition, when the char is converted from a fraction of steam in the gas composition to 10%, a transitional combustion regime is realized, in which diffusion phenomena and sorption processes on the surface of the fuel particle are significant. With a further increase in the fraction of steam, the kinetic combustion regime is realized, at which the rate of reaction ceases to depend on the content of the oxidant in the gas composition
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4. Conclusion We determined the effect of the gas composition on the conversion kinetics of the lignite coal. It was shown that the devolatiliztion rates little depend on the content steam in the reactive medium composition. The content steam significantly affects the rate and mechanism of the char residue decomposition. The steam char conversion with a low steam conversion (10%) entails domination of the heterophase interaction between the char and water steam, which then transforms into a homophase mechanism described by a water-shift reaction. Furthermore, the volumetric reaction model evolves into the grain model. Acknowledgements The research was performed at Kutateladze Institute of Thermophysics SB RAS under the support of Russian Science Foundation (Grant № 15-19-10025). References [1]. M. La Villetta, M. Costa, N. Massarotti, Modelling approaches to biomass gasification:A review with emphasis on the stoichiometric method, Renew. Sustain. En. Rev. 74 (2017) 71-88. 2. Z. Zhou, L. Chen, L. Guo, B. Qian, Z. Wang, K. Cen, Computational modeling of oxycoal combustion with intrinsic heterogeneous char reaction models, Fuel Process. Technol. 161 (2017) 169-181. 3. S. Iwaszenko, Using Mathematica software for coal gasification simulations – Selected kinetic model application, J. Sustainable. Mining. 14 (2015) 21-29. 4. E. Popova, A. Chernov, P. Maryandyshev, A. Brillard, D. Kehrlib, G. Trouvé, V. Lyubov, J-F. Brilhac, Thermal degradations of wood biofuels, coals and hydrolysis lignin from the Russian Federation: Experiments and modeling, Bioresource. Tech. 218 (2016) 1046-1054. 5. F. Wang, X. Zeng, Y. Wang, J. Yu, G. Xu, Characterization of coal char gasification with steam in a microfluidized bed reaction analyzer, Fuel Process. Technol. 141 (2016) 2-8. 6. A. Zoulalian, R. Bounaceur, A. Dufour, Kinetic modelling of char gasification by accounting for the evolution of the reactive surface area, Chem. Engin. Sc. 138 (2015) 281-290. 7. A.N. Kozlov, D.A. Scishchev, I.G. Donskoy, V.A. Shamansky, A.F. Ryzhkov, A technique proximate and ultimate analysis of solid fuels and coal tar, Thermal Anal. Calorimetry. 122 (2015) 1213-1220. 8. J.P. Sanders, P.K. Gallagher, Kinetic analyses using simultaneous TG/DSC measurements, Thermal Anal. Calorimetry. 82 (2005) 659-664. 10. H. Tanaka, M.E. Brown, The theory and practice of thermoanalitical kinetics of solid state reactions, Thermal Anal. Calorimetry. 80 (2005) 795-797. 11. E. Moukhina, Determination of kinetic mechanisms for reactions measured with thermoanalytical instruments, Thermal Anal. Calorimetry. 109 (2012) 1203-1214. 12. A.N. Kozlov, D.A. Svishchev, G.I. Khudyakova, A.F. Ryzhkov A kinetic analysis of the thermochemical conversion of solid fuels (A review), Solid Fuel Chemistry. 51 (2017) 205-213.