Biomass gasification thermodynamic model including tar and char

Transcription

1 Agronomy Research 14(4), , 2016 Biomass gasiication thermodynamic model including tar and char V. Kirsanovs *, A. Žandeckis and C. Rochas Institute o Energy Systems and Environment, Riga Technical University, Azenes iela 12/1, LV-1048 Riga, Latvia * Correspondence: vladimirs.kirsanovs@rtu.lv Abstract. Biomass gasiication is a thermochemical process in which eedstock is heated to high temperatures in a condition o absence o oxygen. As a result, biomass is converted into the combustible syngas, which typically consists o carbon monoxide (CO), carbon dioxide (CO 2), hydrogen (H 2), methane (CH 4), nitrogen (N 2) and water vapour (H 2O). Biomass gasiication process simulation plays an important role in gasiication process comprehension and optimization. Typically, gasiication models have only one output low in the process mass balance, which represents the amount o the produced syngas. Tar and char also are signiicant products o gasiication process. This study presents a thermodynamic biomass gasiication model. The undamental distinction o the proposed model, comparing to other available models, is that tar and char also are taken into account in developed model. Gasiication process is aected by many actors. Similarly, the amount o produced tar and char can signiicantly vary depending on gasiier operation conditions. Literature review on the previous studies is done to determinate the most critical actors which aect tar and char ormation. Results show that temperature in the gasiier, equivalence ratio and uel properties have dominant eect on the products yield. Two regression models are elaborated to present the amount o the produced tar and char depending on independent variables. The achieved mathematical equations are added to the developed thermodynamic model o the gasiication process. Biomass gasiication process is simulated with dierent values o uel moisture and equivalence ratio. The results show that produced syngas amount, caloriic value and biomass energy conversion eiciency are more realistic ater tar and char including in the model. Key words: biomass gasiication, syngas, tar, char, mathematical model. INTRODUCTION Gasiication is a complex process or conversion o solids into to gaseous uels. Gasiication process consists o drying, pyrolysis, partial combustion and gasiication or reduction sub-processes. Produced gas typically contains 70% to 80% o the initial biomass energy, but residual energy is lost. (Blumberga et al., 2011) Eiciency o the gasiication process and produced gas properties depend on many mutual actors. Simulation tools are widely used or understanding and optimization gasiication process. Nowadays many gasiication models exist and describe the eect o operational parameters o the process, as well as uel properties. Thermodynamic equilibrium and kinetic models are the two most requently used simulation tools. In the study done by Baruah & Baruah (2014) these simulation approaches are discussed and compared. The 1321

2 inluence o gasiier design on the gasiication process can be analysed using kinetic models. Produced gas composition at speciic place in gasiier and deinite time can also be determined. (Gordillo & Belghit, 2011; Saravanakumar et al., 2011) Thermodynamic models are useul to predict chemical composition o the produced gas. The inluence o equivalence ratio, temperature in reactor and uel properties on the gasiication process can be successully simulated using thermodynamic models. (Jarungthammachote & Dutta, 2007; Sharma, 2008; Azzone et al 2012) This is one o the main advantages o the thermodynamic modelling. The global gasiication reaction is a base o the thermodynamic model. Fuel chemical composition, moisture content and equivalence ratio are the main input parameters determining composition o produced gas. Syngas is the main product o the gasiication process. Some amount o uel was converted to the tar and char also. In general, tar is a complex mixture o condensable organic substances, including light aromatics, polyaromatics, heterocycles, etc, that condense in the low-temperature zones o the gasiier and in downstream equipment. Tar is ormed in each zone o gasiier, orming the greatest part in pyrolysis zone, where temperature vary rom 200 to 500 C. Tar is undesired substance and can be a reason or many problems such as plugging the equipment because o condensation, ormation o tar aerosols, ormation o particulates or polymerizing on the surace o solid particles, as well as metal corrosion. (Ahmed et al., 2011). Char is typically produced at the pyrolysis stage and oten is the inal solid residue let over rom gasiication process. Char mainly consists o hydrogen and carbon and has high caloriic value. Char porosity is relative high and can vary in the range o 40 to 50% (Basu, 2010). Only in several models include tar and char in the gasiication process mass balance, typically as constant value. The aim o this study is get empirical relation o tar and char yield depending rom gasiier operation parameters and achieved equation including in the mathematical model. The determination o main actors which have eect on the tar and char yield must be done beore. Many studies available about tar and char ormation in the gasiication process. Sometimes dierent and even opposite eect o dierent actors on the tar and char yield can be ind. Tar and char ormation are depended rom many actors. This can be one o the main reason o dierent results between studies. Only results rom studies where one type gasiiers with similar gasiication agent used can be compared. The developed mathematical model describes gasiication process in the downdrat gasiier where air was used as gasiying agent. Only studies which analyse tar and char yield rom downdrat gasiier with air medium were used or regression model derivation. Tar yield rom downdrat gasiiers is lower in comparison with updrat and luidized bed gasiiers. Biomass gasiication with air agent promote higher tar concentration in the syngas than with steam or oxygen gasiication. The temperature increase promotes total tar content decrease in the syngas. Hydrocarbons conversion becomes more active because o heat released by the combustion reactions. (Basu, 2010; Erkiaga et al., 2014). The char yield also reduces due to temperature growth and is converted into gas through Boudouard reactions and thermal cracking reaction (Luo et al., 2012). On the other side, the signiicant growth o the temperature avours the decrease o the low heating value o the syngas. By increasing temperature, more carbon is oxidized to CO 2, which is incombustible. Syngas heating value goes down in the result. It is important to ind optimal temperature range 1322

3 or gasiier operation to produce high syngas yield without signiicant decrease o the syngas heating value (Sanz & Corella, 2006). From the other side gasiication temperature is aected by many parameters, like equivalence ratio, moisture content o uel, uel chemical composition, reactor design, etc. Temperature in the gasiier cannot be changed without changing one or several input parameters and has strong correlation with mentioned parameters. Temperature should be considered as a dependent variable in the result. In the thermochemical models interactive calculation is applied to determine gasiication temperature at which energy balance o the global gasiication reaction is ulilled. Equivalence ratio is one o the most signiicant parameters aecting gasiication process eiciency and syngas composition. Equivalence ratio is the ratio o the actual air/uel ratio to the stoichiometric air/uel ratio. Equivalence ratio is 1 or the ideal combustion and typically ranges rom 0.2 to 0.4 or biomass gasiication. The growth o the air/uel ratio promotes increase o the activity o the combustion reactions. Temperature in the reaction zone goes up in the result. Many studies results present that there is a strong correlation between equivalence ratio and temperature (Pellegrini & Oliveira, 2007; Ghassemi & Shahsavan-Markadeh, 2014). Ji et al. (2009) and Guo et al. (2013) determined tar content decreasing, but Fiaschi & Michelini (2001) present char reduction with air/uel ratio increase. The similar situation is with uel moisture. The eect o moisture has inluence on tar and char yield and temperature in the gasiier reactor (Pellegrini & Oliveira, 2007; Karamarkovic & Karamarkovic, 2010). The higher the uel moisture, the higher energy amount is used to evaporate water rom the biomass and less energy is available or endothermic reactions. The temperature in the gasiier goes down in the result and promotes growth o the tar and char yield. The tar content growth rom 14.4 g m -3 to 20.7 g m -3 and temperature decrease rom 795 C to 748 C was ound out when the uel moisture increased rom 15% to 34% in the study done by Guo et al. (2013). There are also some another actors which have inluence on the tar and char yield - eedstock particle size (Mohammed et al., 2011), high concentration o volatile matters (Min et al., 2003), lignin content in the uel (Saw & Pang, 2013; Amirabedin et al., 2014) and uel chemical composition. Model represent gasiication process o wood chips with constant properties. The eect o uel chemical composition was presented in the previous study (Kirsanovs & Žandeckis, 2015a). It was determined that chemical composition and ash content in the uel have eect on the gasiication temperature. Thereore, the uel chemical composition inluence on the gasiication process can be represented due relationships o temperature in the gasiier and tar and char yield. MATERIAL AND METHODS Literature review conirm that tar and char ormation depends rom temperature in gasiier, equivalence ratio and uel properties. Table 1 summarizes the studies which present eect o gasiication operation parameters and uel properties on the tar and char ormation. Table present the ranges o gasiication temperature, air/uel ratio, biomass moisture and ash content in biomass in the studies. Fuel moisture and ash content in some studies are constant in the experiments. 1323

4 Table 1. Summary o previous studies which present tar and char ormation at the biomass gasiication process Gasiication Biomass moisture, Ash content in Air/uel ratio temperature % biomass, w-%, dr Reerences 930 1, Gai & Dong, , Dogru et al., 2002a Sarket & Nielsen, Sheth & Babu, , Striūgas et al., ,009 1, Dogru et al., 2002b 870 1, Lv et al., Atnaw et al., 2013 Data analysis is perormed using STATGRAPHICS Centurion sotware and shows that there are correlations between tar and char yield and gasiication operation parameters and uel properties. The irst mathematical equation below represents gasiication temperature, air/uel ratio and biomass moisture eect on the tar yield. (see Eq. 1) Tar yield was presented as relation o tar mass at the exit o gasiier to total uel and air mass input. The mass o the uel and air injected in the gasiier is similar with total product mass output rom gasiier. The second equation shows the connection between char yield and gasiication temperature, air/uel ratio, uel moisture and ash content (see Eq. 2). Char yield was presented as relation o char mass at the exit o gasiier to total uel mass input. w tar = ( sqrt(t)) AF W (1) w Char = ( T) AF W A (2) where: w tar is tar mass concentration, wt%; w char is char mass concentration, wt%; T is temperature in the gasiier, C; AF is ait/uel ratio; W is uel moisture content, wt%; A is ash content in the uel, wt%, on dry basis. Analysis o both models is presented in Table 2. Results show that temperature is most inluential parameter on the indicator in Model I and II. This is mostly due to signiicant inluence o temperature on the tar and char yield. R-Squared statistic indicates that the model as itted explains and variability o tar and char yield. Standard error o the estimate is low and especially or model I, so it can be used to predict limits or new observations. The mean absolute error is the average value o the residuals and also is lower or model I. Table 2. Data analysis o the regression model Reg. model Depended variable R 2, % Adjusted. R 2, % Standard error o estimate Mean absolute error I Tar II Char

5 Two achieved equations are integrated in the modiied thermodynamic model o the gasiication process. Model detailed description can be ound in the previous studies (Kirsanovs & Žandeckis, 2015a; Kirsanovs & Žandeckis, 2015b). Global gasiication reaction is a base o the created thermodynamic model. CO, CO 2, H 2, CH 4, N 2 and H 2O vapour make syngas composition in the model. The inclusion o tar and char in the model is the main dierence rom previous models. Air is used as gasiication agent in this model. Fuel and ambient temperatures are constant. Fuel properties like chemical composition and ash content are constant in the model or all scenarios and represent typical wood rom orest with or without bark. Model validation with others studies also was described in the earlier papers. Model was based on the global gasiication reaction, where tar and char were also included (Eq. 3): CH O N x y z + wh O+ m( O N ) = n H + n CO n CO + n CH + n HO + ( z+ 3.76m) N + n tar+ n char The carbon, hydrogen and oxygen balances in the model were presented as (Eq. 4 6): CO + CO = 2 CH 4 (3) n n + n -1 0 (4) nh + n + 4n - x- 2w 0 (5) 2 2 H = 2O CH 4 nco + n + n - w- 2m- y 0 (6) 2 CO = 2 H2O The mass balance consists rom two input and or output lows. Fuel and air are input lows, but syngas, tar, char and ash are output lows (Eq. 7). Tar and char mass were calculated using achieved equations 1 and 2. m + m = m + m + m + m (7) air s where: m uel mass; m air air mass; m s syngas mass; m t tar mass; m c char mass; m ash ash mass. Three input and three output lows orm the energy balance in the model (Eq. 8). The main energy was injected with uel heating value. Some energy goes to gasiier with air and uel sensible energy. The dominant share o energy leaves gasiier with syngas heating value, but some energy was removed rom syngas sensible heat. The remaining energy belong to heat losses. Heat losses rom gasiier hot suraces, heat removed rom tar and char are main energy losses ways. where: syngas energy; E E uel energy; s E s s syngas energy; as t s c ss ash + E + E = E + E + E (8) E s uel sensible energy; E l heat losses. l E a s air sensible energy; E s 1325

6 The cold-gas eiciency o gasiication process is relation between produced syngas heat o combustion to input energy with biomass and expressed in model as (9) (Basu, 2010): LHV g Vg h cold = (9) LHV m where: η cold the eiciency o the gasiication process, %; LHV g lower caloriic value o the syngas, kj Nm -3 ; V g volume o the produced syngas, Nm 3 ; Q s sensible heat o syngas, kj m -3 ; m the mass o the uel as ired basis kg. The hot-gas eiciency take into account produced gas sensible heat also. Sensible heat is depending rom syngas temperature ater gasiier and ater cooling (10) (Basu, 2010): LHV g Vg + Qs Vg h hot = (10) LHV m where: η hot the eiciency o the gasiication process, %; Q s sensible heat o syngas. RESULTS The eect o gasiication operational conditions on the gasiication temperature, produced syngas amount, syngas heating value and syngas sensible or latent heat, as well as gasiication process eiciencies are analysed. Gasiication process is simulated using previous model without tar and char and modiied model, which includes gasiication process subproducts. It is done to compare models and to represent the dierence between the results o modelling. Equivalence ratio and uel moisture are chosen as independent variables. Equivalence ratio vary in range rom 0.2 to 0.4. Three typical values o the amount o water in the biomass 10%, 20% and 30% were taken or uel moisture. First o all, the yield o the produced tar and char in comparison to total output low are calculated (see Fig. 1). The results show that tar and char mass concentration is maximal at low equivalence ratio. Tar and char yields decrease rom 4.2% and 6.1% respective at equivalence ratio 0.2 to 0.3% and 2.6% at equivalence ratio 0.4 using biomass with 10% moisture content. Fuel moisture growth promotes the increase o tar and char content. Tar and char yields go up rom 4.2% and 6.1% respective with uel moisture content 10% to 5.0% and 8.8% with moisture content 30% at equivalence ratio 0.2. Signiicant gasiication temperature reducing with uel moisture growth is the main reason o it. 1326

7 Tar/char, wt.% Equivalence ratio 10% W_tar 20% W_tar 30% W_tar 10% W_char 20% W_char 30% W_char a) b) Figure 1. Eect o the equivalence ratio and uel moisture content on the tar and char yield (a); and temperature and syngas higher caloriic value (b), where: 10%W uel moisture 10%; 20%W uel moisture 20%; 30%W uel moisture 30%; temp temperature in gasiier, C; LHV syngas lower caloriic value, MJ Nm 3. Temperature o oxidation zone and temperature in the gasiier in general decrease with biomass moisture growth. More energy rom uel is used to evaporate water. The oxidation reaction activity goes down due uel moisture increase also. Gasiication temperature reduced rom 535 C respective with uel moisture content 10% to 515 C with moisture content 30% at equivalence ratio 0.2. At the same time gasiication temperature increase rom 535 C at equivalence ratio 0.2 to 985 C at equivalence ratio using biomass with 10% moisture content. The carbon monoxide and hydrogen content in the produced syngas goes down with uel moisture increase. Lower heating value o syngas goes down in the result rom 6.7 MJ Nm 3 with uel moisture content 10% to 5.3 MJ Nm 3 with moisture content 30% at equivalence ratio 0.2. The increase o equivalence ratio promotes the growth o the gasiication temperature. Methane concentration rapidly goes down and causes the decrease o syngas heating value too. The volume o the produced gas is lower ater tar and char including in the model. Fig. 2 shows dierence in the syngas amount between previous model, where tar and char were not included and modiied model with tar and char. The results show that the amount o syngas is lower using modiied model. Produced syngas low increases 1.5 times rom 1.5 Nm 3 kg -1 to 2.5 Nm 3 kg -1 and more with equivalence ratio increase rom 0.2 to 0.4. Amount o produced incombustible CO 2 and N 2 also increases due ER growth and promote decrease o heating value o syngas. The amount o produced syngas goes down with uel moisture growth. Temperature in the gasiier has dominant eect on the sensible heat o syngas. The higher is gasiication temperature the higher is sensible heat o produced gas. This is the main reason that sensible heat o syngas is higher or uel with lower moisture content and at high equilibrium ratios. Sensible heat o syngas is lower or scenarios where tar and char were included in the model, because the total amount o the syngas goes down. 1327

8 Syngas, Nm 3 kg Sensible heat, MJ kg Equivalence ratio 10% W_prev 20% W_prev 30% W_prev 10% W_mod 20% W_mod 30% W_mod a) b) Equivalence ratio 10% W_prev 20% W_prev 30% W_prev 10% W_mod 20% W_mod 30% W_mod Figure 2. Eect o the equivalence ratio and uel moisture content(w) on the produced gas volume (a); and syngas sensible heat (b), where: prev previous model; mod modiied model including tar and char. The eiciency is one o the main criteria describing perormance o the gasiication process. Eiciency o the gasiication process typically is described using cold gas and hot gas eiciency. Fig. 3 presents calculated cold and hot gas eiciencies o the gasiication process or all six scenarios. The syngas caloriic value decrease due to equivalence ratio and uel moisture content growth. Cold gas eiciency o the gasiication process goes down in the result. The data rom modiied model show that cold gas eiciency doesn t go down or opposite go up with equivalence ratio increase rom 0.2 to The signiicant tar and char yield decrease is the main reason o it. The uel moisture increase on 10% promote decrease o cold gas eiciency on the average by 3.5%. The growth o equivalence ratio rom 0.2 to 0.4 promote decrease o cold gas eiciency on the average by 19% and 15% using previous and modiied models respectively. Cold eiciency, % Equivalence ratio 10% W_prev 20% W_prev 30% W_prev 10% W_mod 20% W_mod 30% W_mod a) b) Hot eiciency, % 80 Figure 3. Eect o the equivalence ratio and uel moisture content(w) on the gasiication process cold eiciency (a); and hot eiciency (b) Equivalence ratio 10% W_prev 20% W_prev 30% W_prev 10% W_mod 20% W_mod 30% W_mod 1328

9 Data rom previous model show that the hot gas eiciency goes down rapidly at lower equivalence ratio too, but ater achieving the critical point was more over constant. Signiicant syngas volume and sensible heat increase at high equivalence ratios are the main reason o it. The achieved data rom modiied model present some hot gas eiciency growth with equivalence ratio increase rom 0.2 to The urther eect o equivalence ratio decrease was more over similar with results rom previous model. CONCLUSIONS The eects o temperature, equivalence ratio and uel properties on the tar and char ormation are analysed, using articles available rom literature. Tar and char have a strong impact on the produced syngas properties and gasiication process eiciency. Tar and char yield should be included in the mass balance o the biomass gasiication process to get achieved data rom thermodynamic model closer to real data. Two models are proposed to present the mathematical connection between temperature in gasiier, air/uel ratio, uel properties and tar and char yield during gasiication process using collected studies. Data analysis shows that the models have a suicient correlation between the variable. The achieved equations are integrated in the thermodynamic model o gasiication process. The eect o equivalence ratio and uel moisture is determined using the developed gasiication process model. The results show that air/uel ratio growth promotes decrease o tar and char yield. The increase o temperature in the reactor is the main reason o it. Growth o the temperature has negative eect on the produced syngas caloriic value. Fuel moisture increasing has the opposite inluence on the tar and char yield. Temperature in the gasiier reduces due to the biomass moisture growth, that avours the increase o the tar and char yield. The modiied model with included tar and char values is compared with previous model. The results show that eiciency o gasiication process lowers. Modiied model show that equivalence ratio 0.25 can be optimal value or gasiication process. Previous model show that the lower is equivalence ratio the higher is gasiication process eiciency, because don t take into account tar and char eect on the process. Data rom new model is closer to data rom real systems ater tar and char including in the model. ACKNOWLEDGEMENTS. The work has been supported by the National Research Program Energy eicient and low-carbon solutions or a secure, sustainable and climate variability reducing energy supply (LATENERGI). REFERENCES Ahmed, A., Salmiaton, A., Choong, T. & Wan Azlina, W Review o kinetic and equilibrium concepts or biomass tar modelling by usind Aspen Plus. Renewable and Sustainable Energy Reviews 52, Amirabedin, E., Pooyanar, M., Rahim, M.A. & Topal, H Techno-environmental assessment o co-gasiication o low-grade Turkish lignite with biomass in a trigeneration power plant. Environmental and Climate Technologies 13, Atnaw, S.M., Kueh, S.C. & Sulaiman, S.A Study on tar generated rom downdrat gasiication o oil palm ronds. The Scientiic World Journal 2014,

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