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Modified Thermodynamic Equilibrium Model for Biomass Gasification: A Study of the Influence of Operating Conditions Maria Puig-Arnavat, Juan Carlos Bruno,* and Alberto Coronas Department of Mechanical Engineering, Universitat Rovira i Virgili, Avinguda Països Catalans, 26, 43007 Tarragona, Spain ABSTRACT: This paper presents a mathematical model for biomass gasification processes developed in the equation solver program Engineering Equation Solver (EES) with an implemented user-friendly interface. It is based on thermodynamic equilibrium calculations and includes some modifications to be adapted to a real process, in which only a partial approach to chemical equilibrium is achieved. The model can be used to predict the producer gas composition, yield, and heating value for a certain biomass with a specific ultimate composition and moisture content. It has been validated with published experimental data from different authors for downdraft, fluidized-bed gasifiers and different biomasses, showing good agreement between reported data and modeled values. In addition, it has been used to evaluate the influence of different operating parameters [equivalence ratio (ER), air preheating, steam injection, and oxygen enrichment] on producer gas. The model predicts the behavior of different kinds of biomass and becomes a useful tool to simulate the biomass gasification process by allowing its integration in complete energy supply systems, such as co-generation plants.

1. INTRODUCTION AND OBJECTIVES Nowadays, the awareness and concern about the depletion of fossil fuels, energy dependency, and global climate change have called for the development and research on reliable, affordable, and clean-energy sources. In this context, modern use of biomass is considered a very promising clean-energy option for reducing energy dependency and greenhouse gas emissions; biomass is considered to be CO2-neutral. In addition, it is the only renewable energy source that can directly replace fossil fuels because it is widely available and allows for continuous power generation and synthesis of different fuels and chemicals. Gasification is a highly efficient and clean conversion process that converts different feedstocks to a wide variety of products for various applications. In comparison to combustion, gasification has higher efficiencies in power production and a more efficient and better controlled heating.1 Gasification can be considered in advanced applications in developed countries and also for rural electrification in isolated installations or in developing countries. The gasification conversion process can be defined as a partial thermal oxidation, which results in a great proportion of gaseous products (carbon dioxide, hydrogen, carbon monoxide, water, and other gaseous hydrocarbons) and little quantities of char, ash, and several condensable compounds (tars and oils). Air, steam, or oxygen can be supplied to the reaction as gasifying agents. The quality of gas produced varies according to the gasifying agent used and operating conditions. The gas obtained covers a wide range of calorific values (CVs): low CVs (4−6 MJ/m3) result from the use of air as the gasifying agent, and medium or high CVs (12−18 or 40 MJ/m3) result when steam or oxygen is used. The operation of a biomass gasifier depends upon several complex chemical reactions, including several steps, such as pyrolysis, thermal cracking of vapors to gas and char, gasification of char, and partial oxidation of combustible gas, vapors, and char. These complicated processes, coupled with © 2012 American Chemical Society

the sensitivity of the distribution of the product to the operating conditions, called for the development of mathematical models. The main objectives of these models are to study the thermochemical processes during the gasification of the biomass and evaluate the influence of the main input variables on the producer gas composition and calorific value. Different kinds of models have been developed for gasification systems, including equilibrium, kinetic, and artificial neural networks. A detailed review of recent biomass gasification models is available elsewhere,2,3 and only a brief description is therefore given here. Equilibrium models predict the maximum achievable yield of a desired product from a reacting system, while kinetic models predict the progress and product composition at different positions in a reactor.2 Equilibrium models are less computationally intensive than kinetic models, and they are a useful tool for preliminary comparison. However, they cannot give highly accurate results in all cases. Equilibrium models usually overestimate the yields of H2 and CO, underestimate those of CO2, and predict an outlet stream free from CH4, tars, and char.3 Equilibrium models are considered a good approach when simulating entrained-flow gasifiers in chemical process simulators or for downdraft fixed-bed gasifiers, as long as high temperature and gas residence time are achieved in the throat. In contrast, updraft fixed-bed, dual fluidized-bed, and stand-alone fluidizedbed gasifiers should be modeled by revised equilibrium models or, in some extreme cases, by detailed rate-flow models.4 The objective of this paper is to develop a simple but rigorous gasification model for the design and simulation of a biomass gasification plant. This model, on the basis of thermodynamic equilibrium calculations, includes some modifications for adaptation to real processes, in which only a Received: November 16, 2011 Revised: January 16, 2012 Published: January 18, 2012 1385

dx.doi.org/10.1021/ef2019462 | Energy Fuels 2012, 26, 1385−1394

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Figure 1. Screenshot of the modified equilibrium model, developed in EES software, including feed and product streams entering and leaving the different units considered. The numerical values of variables in a box are inputs for the model. constant can be defined as the true equilibrium constant multiplied by the degree of approach to equilibrium. In calibrating the model by Jayah et al.,9 the amount of methane predicted was adjusted to be equal to the amount of methane measured in the product gas. Jarungthammachote and Dutta6 used experimental data from other authors5,9,10 to modify their model. They calculated two coefficients for correcting the equilibrium constant of the water−gas shift reaction and methane formation reaction that improved the accuracy. The coefficients were obtained from the average value of the ratio of experimental data and calculated data from their model, for CH4 and CO. Other authors11 used the equilibrium model to predict the producer-gas compositions, product heating value, and cold gas efficiency for circulating fluidized-bed (CFB) gasification. To correct the deviations that they found between a real gasification process and chemical equilibrium, they developed a phenomenological model to modify the equilibrium to account for important non-equilibrium factors. As they knew from a pilot-plant study of the experimental carbon conversion, they applied empirical parameters to modify the carbon conversion. In this study, the modifications to the pure equilibrium model essentially consist of (1) adding a pyrolysis unit that uses correlations to predict the formation of gas, char, and volatiles in this step of the gasification process, (2) considering heat losses in pyrolysis and gasification units (these heat losses are estimated by the user as a percentage of biomass energy input to the system), (3) adding tar and char leaving the gasifier as a percentage of tar and char produced in the pyrolysis unit added, (4) considering particles leaving the gasifier and set by the user as mg N−1 m−3 in the producer gas, and (5) setting the amount of CH4 produced (for this reason, the equilibrium constant for the methane reaction is not taken into account). This modified equilibrium model is built into the equation solver program “Engineering Equation Solver (EES)”.12 EES has been found to be very suitable for modeling this kind of system, because it contains all of the necessary thermodynamic functions and it is possible for the model builder to make a user interface, which can make the model user-friendly. The gasification model is made up of a series of modules, each containing one process (biomass drying, pyrolysis, gasification, air preheating, and steam generation). In this gasification model, the user interface consists of a window, which contains drawings and tables

partial approach to chemical equilibrium is achieved. The model developed, which has been validated with experimental published data of other authors, provides the opportunity to evaluate different gasification processes as well as variations in fuel and operating conditions.

2. MATHEMATICAL MODEL The model presented in this paper is a modified equilibrium model based on equilibrium constants, while the process is considered stationary. First, a pure thermodynamic equilibrium model was developed following the procedure described elsewhere.5,6 This pure equilibrium model is based on mass and energy balances together with chemical equilibrium in the gas phase, using the water−gas shift reaction (eq 3) that results from the combination of Boudouard (eq 1) and water−gas (eq 2) reactions5,6 and the methane formation reaction (eq 4).

C + CO2 ↔ 2CO

(1)

C + H2O ↔ CO + H2

(2)

CO + H2O ↔ CO2 + H2

(3)

C + 2H2 ↔ CH 4

(4)

The chemical formula of feedstock was defined as CHxOyNz, and it can be calculated from the ultimate analysis of the biomass and the mass fractions of the carbon, hydrogen, oxygen, and nitrogen. Some assumptions were necessarily made,5,7 and the products leaving the gasifier were considered all gaseous (CO, CO2, H2, CH4, N2, and H2O). The main problems with this pure equilibrium model, as mentioned by other authors,3,6 is the overprediction of H2 and CO yields and underestimation of CO2. In addition, it predicts an exit stream free of CH4, tars, and char. These differences between predicted and experimental data can be explained by the fact that a real gasification system differs from an ideal reactor at chemical equilibrium. For this reason and to increase the accuracy of the results of the pure thermodynamic equilibrium model, some modifications were introduced. Other authors also previously developed modified or pseudo-equilibrium models. Gumz8 stated that a modified equilibrium 1386


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with input and output values, diagrams, and hot areas with links to other windows. For example, the pyrolysis unit is a hot area linked with another window where the user can select the pyrolysis correlations depending upon the gasifier design (downdraft or fluidized bed). This way of presenting input and output variables facilitates the user obtaining an overview of the operating conditions in a certain computation. Figure 1 shows a screenshot of this modified equilibrium model developed in EES and including all feed, product streams, and the different units considered. This implemented modified equilibrium model enables work with gasifying agents other than air. It is possible to use air, enriched air, or oxygen alone or combined with steam. Char and particles leaving the gasifier unit are considered to be composed primarily of carbon, and therefore, it was assumed to consist solely of carbon in the model. Char-specific enthalpy is determined by the regression created from a data set based on the enthalpy of graphite13

hchar (kJ/kg) = 0.0004T 2 + 0.8679T − 381.61

If the pyrolysis stage takes place in a fluidized bed, the correlations obtained by Gomez-Barea et al.19 will then be used. These correlations were selected because they are the only correlations for non-flash pyrolysis in a fluidized bed that could be found in the literature. The model also gives the opportunity not to use any of these correlations and to introduce the desired yields manually. It must also be taken into account that only correlations for wood pyrolysis are considered. However, it is also possible to extend the model by including pyrolysis correlations for other kinds of biomass and agricultural residues. The correlations used in this pyrolysis unit are as follows: (1) Wood pyrolysis in a fluidized bed:19

gas yield (mass %, db) ⎛ Tp ⎞ ⎛ Tp ⎞2 = 311.10 − 351.45⎜ ⎟ + 121.43⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠ char yield (mass %, db)

(5)

⎛ Tp ⎞ ⎛ Tp ⎞2 = − 15.03 + 50.58⎜ ⎟ − 18.09⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠

where T is the temperature measured in kelvin. Tar-specific enthalpy is calculated using a correlation obtained by applying the Joback method, and it is assumed that pyrolysis tar only consists of seven organic compounds: benzene, toluene, phenol, guaiacol, methylguaiacol, ethylguaiacol, and isoeugenol14

⎛ Tp ⎞ ⎛ Tp ⎞2 = − 196.07 + 300.86⎜ ⎟ − 103.34⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠

(T − 273.15) + 0.131(T − 273.15) − 1796.4

⎛ Tp ⎞ ⎛ Tp ⎞2 CO (vol %) = 240.53 − 225.12⎜ ⎟ + 67.50⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠

(6) where T is the temperature expressed in kelvin. Because not all carbon contained in biomass is converted into gas species, it is necessary to define the concept of carbon conversion efficiency (ηc) as

⎛ Tp ⎞ ⎛ Tp ⎞2 CH 4 (vol %) = −168.64 + 214.47⎜ ⎟ − 62.51⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠

(7)

Model parameters, such as pyrolysis temperature, percentage of pyrolysis char and tar leaving the gasifier, and heat losses in the gasifier, can be directly introduced by the user through the user interface, if the information is known, or adjusted automatically. These parameters are automatically adjusted using the experimental and modeled output gas composition for each data set. The least-squares technique is used as described in the equation below m

∑ (pi , j

i=1 j=1

(12)

(13)

/(total amount of carbon in the biomass inlet stream)

n

(11)

⎛ Tp ⎞ ⎛ Tp ⎞2 CO2 (vol %) = −206.86 + 267.66⎜ ⎟ − 77.50⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠

ηc (%) = (total amount of carbon in the gas outlet stream)

min ∑

(10)

liquid yield (mass %, db)

h tar (kJ/kg) = − 4.659 × 10−7(T − 273.15)3 + 0.00193 2

× 100

(9)

(14)

⎛ Tp ⎞ ⎛ Tp ⎞2 H2 (vol %) = 234.97 − 257.01⎜ ⎟ + 72.50⎜ ⎟ ⎝ Tref ⎠ ⎝ Tref ⎠

(15)

where Tp is the pyrolysis temperature (°C) and Tref = 500 °C. (2) Correlations for conventional pyrolysis of wood in a fixed-bed reactor obtained from experimental data:17

− wi , j)2

gas yield (mass %, db)

(8)

= − 1.09 × 10−6Tp3 + 0.0022Tp2 − 1.392Tp + 288.534

where p is the yield of the gas species (CO, CO2, H2, and N2) calculated by the model and w is the corresponding experimental value. n is the number of data points. The minimization is carried out by the variable metric method available in EES. 2.1. Pyrolysis Unit. The main objective of this modeling unit is to determine the yields of char, tar, and volatiles produced during pyrolysis and to determine the composition of the light gas. For this reason, experimental data from several authors15−19 have been studied to obtain correlations for predicting these parameters as a function of the pyrolysis temperature. After different experimental data for biomass pyrolysis are reviewed and because different yields on products are obtained, two different correlations were considered when modeling this unit, depending upon the type of reactor and pyrolysis. Calculated correlations from the experimental data by Fagbemi et al.17 are used to model the pyrolysis stage in a fixed-bed reactor (downdraft, updraft, etc.). These experimental data were selected because they cover a wide range of temperatures and are also in good agreement with the results obtained by other authors.15,16

(16)

tar yield (mass %, db) = 1.33 × 10−6Tp3 − 0.0028Tp2 + 1.797Tp − 339.139

(17)

char yield (mass %, db) = − 6.6 × 10−7Tp3 + 0.00137Tp2 − 0.93579Tp + 230.5279 (18) water yield (mass %, db) = 2.54 × 10−7Tp3 − 5.24 × 10−4Tp2 + 0, 335Tp − 40.883 (19)

CO (vol %) = 0.0371Tp + 19.961 1387

(20)


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CO2 (vol %) = 0.000143Tp2 − 0.27808Tp + 139.948

(21)

CH 4 (vol %) = −9 × 10−5Tp2 + 0.1221Tp − 25.206

(22)

H2 (vol %) = 0.04694Tp − 16.96286

(23)

where Tp is the pyrolysis temperature (°C). In addition to these correlations, the energy, mass, and molar balances for each element (C, H, O, and N) are set and used to calculate pyrolysis products. The energy balance was formulated to include an overall heat loss of the pyrolysis unit. This estimation of the heat losses can be fixed by the user as a percentage of the product of dry biomass mass flow entering the system (kg/h) and its lower heating value (LHV) (kJ/kg).

3. RESULTS AND DISCUSSION 3.1. Validation of the Model with Experimental Data. A previous literature review2 compared the theoretical results of equilibrium models to experimental data, mainly for air-blown downdraft gasifiers. However, in this study, we selected the published experimental data for downdraft and fluidized-bed gasifiers operating with different biomass types and different gasifying agents. The error in the comparisons between predicted and experimental values is estimated by the root-mean-square (rms) value for each set of data, as given below rms =

Figure 2. Comparison of predicted results from the modified equilibrium model to experimental data from Jayah et al.9 for a downdraft gasifier.

ature is adjusted at 500 °C, and no tar and char production is considered. Heat losses of 5% of the energy input have been taken into account. The comparison between the predicted values and experimental data is presented in Figure 3. Figure 3

∑in (experimenti − model i)2 n

(24)

where n is the number of data points. 3.1.1. Experimental Data from Downdraft Gasifiers. Published experimental data from three different authors and gasifiers has been selected.9,20,21 The data from Jayah et al.9 has already been used by other authors6,21−23 to validate their models. The experimental test rig used to collect data was an 80 kWth downdraft test gasifier with an inner reactor diameter of 0.92 m and a length of 1.15 m. Rubber wood was used as the feed material for the study. To predict the results and because of the lack of some information in the papers of authors, the model parameters were adjusted by minimizing the sum of the differences between the experimental and predicted results for producer gas composition. In this case, the model accounts for no biomass drying, air preheating, and heat losses. The pyrolysis unit temperature has been adjusted to 440.5 °C, and a percentage of char leaving the pyrolysis unit has been set to match the amount of char leaving the gasifier and measured by the authors (38%). The CH4 percentage leaving the gasifier is given as an input to the model. The comparison between experimental and predicted data is shown in Figure 2. From this figure, it can be concluded that the modified equilibrium model predicts with good accuracy the producer gas composition for all gas species involved, although the differences for H2 are slightly higher than for the others. The rms values obtained are 1.26, 0.99, 2.71, and 2.91 for CO, CO2, H2, and N2, respectively. This modified equilibrium model has also been validated with the experimental data from Erlich and Fransson20 for wood, sugarcane bagasse from sugar/alcohol production, and empty fruit bunch (EFB) from palm-oil production in a simple constructed pellet-fired downdraft gasifier of about 20 kWth. As with the data of the previous authors, the model parameters have been adjusted automatically and no biomass drying and air preheating have been considered. The pyrolysis unit temper-

Figure 3. Comparison of predicted results from the modified equilibrium model to experimental data from Erlich and Fransson20 for a downdraft gasifier.

shows that the predicted results generally agree with the experimental data. The rms values obtained are 1.1, 1.0, 1.4, and 0.2 for CO, CO2, H2, and N2, respectively. These values are lower than those obtained in the previous case (Figure 2). Finally, the experimental results presented by Gautam21 for a mobile 25 kWe downdraft gasifier for sawdust, commercial wood, and woodchips were also used to validate the model. Experimental data and predicted data for a reported gasification temperature of 800 °C, pyrolysis temperature of 416 °C, and 7% of heat losses are given in Figure 4. As observed, the developed model is able to predict the producer gas 1388


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gasification. The rms values are very similar in both parts of Table 1, which means that predictions have the same precision in both cases. It can be seen that predictions for H2 yields are better for downdraft gasifiers than for fluidized-bed gasifiers, with a higher rms value. However, the model predicts reasonably well the values for CO2 and CO yields. As a result, it can be concluded that the modified equilibrium model also predicts reasonably good values for fluidized-bed gasifiers, although its predictions are better for downdraft gasifiers. 3.2. Effect of Operating Parameters on Producer Gas Composition and LHV. After the developed model was validated with data reported by various researchers, it was used to predict the effect of different operating parameters [equivalence ratio (ER), air preheating, steam injection, and oxygen enrichment] on producer gas composition and LHV. These predictions are compared to those reported by other authors.25−31 Different biomass and model parameter values are used in the different cases studied for this reason. 3.2.1. Effect of ER. The ER is defined as the ratio of the moles of oxygen supplied to the gasifier to those required for stoichiometric combustion. Figure 5 shows the variation of producer gas composition as a function of the ER in an adiabatic gasifier of woodchips with a moisture content of 10%. In an autothermal gasifier such as this one, the gasification temperature depends upon the amount of air fed to the gasifier (Figure 6). In consequence, varying the ER or gasification temperature has the same effect on producer gas composition, heating value, and gasification efficiency. For this reason, only ER is plotted against producer gas composition and LHV. These results were compared to those published by Plis and Wilk,25 Mathieu and Dubuisson,26 and Baratieri et al.27 The three models and the model herein show the same qualitative and quantitative tendencies. The percentage of CH4 remains very low and decreases when the ER increases. The H2 percentage decreases from 22.5 to 6.5% when the ER increases from 0.3 to 0.6; the same behavior was observed by Plis and Wilk,25 with a decrease for the same range of ER values from 20 to 6.5%. While H2 decreases, CO2 increases slightly from 8.6 to 11.6% (from 8.5 to 11.3% for Plis and Wilk25) and the CO percentage decreases from 26.2 to 16.5% in this model and from 25.9 to 16.6% for Plis and Wilk.25 If 3% of the total heat input is considered to be heat losses and 2% of carbon is also lost in the ash, as Doherty et al.28

Figure 4. Comparison of predicted results from the modified equilibrium model to experimental data from Gautam21 for a downdraft gasifier.

composition and also the higher heating value (HHV) (not plotted) with good accuracy for different types of biomass feedstock. From the comparison of the predicted and experimental data for these three different cases and different biomasses, it can be concluded that the model predicts the behavior of downdraft biomass gasifiers and different biomasses reasonably well. 3.1.2. Experimental Data from a Fluidized-Bed Gasifier. Campoy24 conducted an experimental research study in an atmospheric pressure bubbling fluidized-bed biomass gasification pilot plant of 100 kWth. Experimental results for wood pellets and using different gasifying agents are used for validating this model with fluidized-bed gasifiers. The model is adjusted on the basis of a reported air preheating temperature of 400 °C, pyrolysis temperature of 600 °C, heat losses of 7% of energy input, and 42 and 21% of pyrolysis char and tar, respectively, leaving the gasifier. The experimental and predicted values are presented in Table 1. The table is divided into two parts, with the first accounting for air biomass gasification and the second accounting for air−steam biomass

Table 1. Comparison of Predicted Results from the Modified Equilibrium Model to Experimental Data from Campoy24 for a Bubbling Fluidized-Bed Gasifier gas heating valve (MJ N−1 m−3, dry basis)

gas composition (vol %, dry basis) model dry biomass (kg/h) 20.5 15 11.5 17.5 19.1 15 15 12.2 12.2

3

−1

air (N m h ) 17 17 17 rms 17 15.5 17 17 17 17 rms

steam (kg/h)

experimental24

model

CO

0 0 0

20.3 18.7 13.6

3 5 3.2 6 2.5 5.1

16.6 14.3 15.4 12.4 12.9 11.1

experimental24

model

CO2 18.2 17.6 15.8

14.6 13.9 15.9

13.8 11.5 15.0 11.9 15.4 13.8

16.3 19.0 16.2 18.4 16.7 18.1

1.9

0.6 1389

model

H2 14.2 14.9 15.1

18.4 11.3 5.0

16.9 18.6 16.2 18.6 15.9 17.0

17.6 22.6 14.5 14.9 8.4 10.3

0.8

2.2

experimental24

LHV 13.2 12.6 8.7

6.7 5.4 4.1

14.6 16.2 14.0 16.2 11.9 13.3

5.8 6.3 5.2 5.1 4.3 4.2

3.8

3.5

experimental24 5.9 5.4 4.8 0.6 5.2 5.3 5.1 5.1 4.9 4.8 0.6


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Figure 5. Effect of the ER on the composition and LHV of producer gas for gasification in adiabatic conditions of woodchips with a 10% moisture content.

found when studying hemlock woodchip gasification, the results presented in Figure 7 would be obtained. The tendencies observed are in good agreement with those observed by the authors.28 CO and H2 reach a maximum, and their content decreases steadily after these peaks. CO2 decreases rapidly to an ER of 0.35 and then increases slowly. CH4 decreases and eventually reaches 0 between an ER of 0.4 and 0.45. As Doherty et al.28 stated, these trends may be explained as follows: (1) The Boudouard reaction (eq 1) is endothermic. As a result, the production of CO rises when the temperature rises. The amount of available char for the Boudouard reaction is enough for ERs up to 0.35. However, for ERs higher than 0.35, the available char is insuficient; therefore, CO decreases, while CO2 increases. (2) The water−gas reaction (eq 2) is also endothermic. For this reason, increasing the ER and temperature results in a higher consumption of char and H2O to produce more CO and H2. (3) The methane reaction (eq 4) is exothermic. The production of CH4 decreases with the increase of the ER and gasification temperature. This leaves more H2 in the gas. (4) CO2 is produced through the reaction of CO and the available O2. (5) The CO shift reaction is exothermic. This reaction produces

Figure 6. Effect of the temperature on the ER in adiabatic conditions when increasing the temperature for woodchip gasification with a 10% moisture content.

Figure 7. Effect of the ER on the composition of producer gas for hemlock woodchip gasification with a moisture content of 11.7%, assuming 3% heat losses and 2% carbon losses. 1390


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an ER = 0.29, the air could be heated to 850 °C because the gasification temperature stays below 967 °C. Figure 9 shows the predicted product gas composition for the same operating conditions as Figure 8. Increasing the temperature favors the products of endothermic reactions and simultaneously the reactants of exothermic reactions. For low ERs, the air temperature has a higher influence on the product gas composition. For example, over the air temperature range, CO and H2 contents increased by 5.5 and 5.4 percentage points, respectively, for an ER of 0.29. However, for an ER of 0.35 (not plotted), CO and H2 contents increased by only 4 and 0.1 percentage points, respectively, for the same temperature range. The air temperature also has a significant influence on composition but only to a certain level, after which additional preheating has little effect. For both of the ERs mentioned above, this level is reached at about 700 °C, which agrees with Lucas et al.,30 who reported an increase of the H2 content with an increasing air preheating temperature but no rise between 700 and 830 °C. Yang et al.31 also refer to a critical air temperature at which air preheating is no longer efficient if the aim is to maximize the yield of gaseous products. As expected,26,28 the LHV and cold gas efficiency were also observed to increase when the air inlet temperature increased. 3.2.3. Effect of Steam Injection. The influence of steam injection on the gasifier performance was studied (Figure 10) for an ER of 0.34 and compared to the results presented by Doherty et al.28 The steam injection rate was varied from 0 to 10.5 kg/h, as performed by Doherty et al.28 The producer gas LHV decreased slightly from 5.25 to 5.14 MJ/kg. Because steam injection rises the H2O content, a lower LHV is obtained. CO and CH4 are shifted and reformed, respectively, with the contents of the additional H2O, decreasing and producing more CO2. The main effect of steam injection is the rise in the H2 content, which, in this case, increases by 1% over the range of steam injection. Doherty et al.28 observed a slight increase in cold gas efficiency, from 66.1 to 66.5%, while a slight decrease of 1% for the same whole range is observed here. Increasing steam injection decreases the gasifier temperature because of highly endothermic reforming and water−gas reactions, unless heat is supplied from an external source. As stated by Doherty et al.,28 a decrease in the temperature is undesirable because this would degrade the performance of the gasifier and could lead to a high tar yield. For this reason, air preheating should be taken into account when using high moisture fuels and/or steam injection. 3.2.4. Effect of Oxygen Enrichment. The effect of oxygen enrichment in the air on producer gas composition and LHV was also studied, and the results are presented (Figure 11). Figure 11 shows how the composition of producer gas changes with the oxygen fraction in the air for woodchip gasification, with an initial moisture content of 10%, ER = 0.3, and no air preheating. The N2 yield decreases as the oxygen fraction increases, as expected. The methane content is very low, at a percentage of less than 1%. The percentage of hydrogen in the producer gas increases continuously with the oxygen fraction, from about 25 to 32%, for an increase in the oxygen fraction from 25 to 50%. A similar tendency is also observed for CO, but in this case, the increase is from 30 to 42%. CO2 remains more or less constant at around 10%. In addition, the reaction temperature increases from 1100 to 1200 K when the oxygen fraction increases from 25 to 50%. For the same increase in the oxygen fraction, the LHV of the producer gas increases from 6 to 7.8 MJ N−1 m−3. The increase of LHV is due to the increase

less CO2 and H2 at higher temperatures. This means that less CO and H2O are used. (6) The steam−methane reforming reaction reduces CH4. This reaction is endothermic; therefore, an increase of the temperature benefits the forward reaction. 3.2.2. Effect of Air Preheating. Air preheating is useful to achieve a higher conversion efficiency of the gasification process. The gasification temperature is increased by the sensible heat in the air. This increase in the temperature influences the product gas composition, LHV, and gasifier cold gas efficiency by increasing the production of combustible gases, CO, and H2. For this reason, air preheating can be considered as an alternative and more economical approach compared to oxygen-blown systems. However, to increase the overall efficiency of the process, the heat required for air preheating should be recovered from the gas cooling section of the plant. The size of the plant is reduced when hightemperature air is used as an oxidant because a smaller volume of air is needed to bring the gasifier to the required operating temperature.29 In addition, the size of the reactor and gas cleanup system needed are also reduced. Figure 8 shows the influence of air preheating on the gasification temperature for hemlock woodchips with moisture

Figure 8. Effect of air preheating on the gasification temperature for hemlock woodchip gasification with a moisture content of 11.7% and ER = 0.29.

content of 11.7%, heat losses of 3%, and carbon loss of 2%. The results showed that the gasification temperature increased almost linearly with the air temperature for all ERs.22,28 As Doherty et al.28 stated, there is a limit on the level of air preheating for each ER. This limit is imposed by the effectiveness of the heat-exchange equipment and the operating temperature constraints of the reactor. For fluidized-bed gasifiers, the operating temperature should not be above 1000 °C, to avoid reaching the ash melting temperature. This would bring agglomeration and defluidization problems. Air preheating at high ERs is limited to a low level. According to this model, for a CFB at an ER = 0.37, an air temperature of no more than 170 °C would be recommended because the corresponding gasification temperature is 978 °C. In the case of 1391


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Figure 9. Effect of the air inlet temperature on the composition of producer gas of hemlock woodchip gasification with a moisture content of 11.7% and ER = 0.29.

Figure 10. Effect of steam injection on the composition of producer gas of hemlock woodchip gasification with a moisture content of 11.7% and ER = 0.34.

Figure 11. Effect of oxygen enrichment on the composition of producer gas for woodchip gasification with a moisture content of 10% and ER = 0.3.

4. CONCLUSION AND FINAL REMARKS

in the amount of CO and H2. The results are in good agreement with those obtained by Babu and Sheth.

A model for biomass gasification has been developed in this study. It is based on thermodynamic equilibrium calculations

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and includes some modifications to be adapted to a real process, in which only a partial approach to chemical equilibrium is achieved. It is a simple but rigorous model implemented in the equation solver program EES, with a user interface that makes the model user-friendly and facilitates the user obtaining an overview of the operating conditions in a certain computation. The model can be used to predict the final producer gas composition and its main characteristics, such as the heating value, for a certain biomass with a defined ultimate composition and moisture. It has been validated with the data reported by various researchers for downdraft, fluidized-bed gasifiers and different biomasses and shows good agreement with the experimental data. In addition, it has been used to evaluate the influence of different operating parameters on producer gas, presenting the following conclusions: (1) For an adiabatic process, increasing the ER also entails increasing the gasification temperature and decreasing the LHV of producer gas. (2) The use of high-temperature preheated air allows for the use of a smaller volume of air to become the same temperature in the gasifier bed and, in consequence, achieves downsizing of the plant. However, it has been proven that the air temperature has a significant influence on composition only up to a certain level, and it is limited by the effectiveness of the heat-exchange equipment and the operating temperature constraints of the reactor. (3) Steam injection in biomass gasification increases the H2 content of producer gas. (4) The LHV, CO, and H2 yields of producer gas increase when the oxygen fraction of air increases. In conclusion, the model helps to predict the behavior of different biomass types, can be adapted to different gasifier designs by changing the values of the model parameters, and is a useful tool for preliminary calculations, design, and operation of biomass gasifiers. It is also a first step and can be used as an input to the combustion model of an internal combustion engine or another gas to energy engine to model a whole biomass co- or tri-generation plant.

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pj = yield of the gas species j (CO, CO2, H2, and N2) calculated by the model rms = root mean square T = temperature (K) Tp = pyrolysis temperature (°C) x, y, and z = normalized coefficient of atomic hydrogen, oxygen, and nitrogen for the biomass molecule wj = experimental yield of the gas species j (CO, CO2, H2, and N2) ηc = carbon conversion efficiency (%)

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AUTHOR INFORMATION

Corresponding Author

*Telephone: +34-977257891. Fax: +34-977559691. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank the European Commission for the financial support received as part of the European Project Polycity (Energy Networks in Sustainable Communities, TREN/ 05FP6EN/S07.43964/51381).

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NOMENCLATURE C, H, O, and N = carbon, hydrogen, oxygen, and nitrogen fractions in biomass (dry basis) CV = calorific value (kJ/kg) ER = equivalence ratio hchar = specific enthalpy of char (kJ/kg) htar = specific enthalpy of tar (kJ/kg) HHV = higher heating value (kJ/kg) LHV = lower heating value (kJ/kg) m = number of gas species in the producer gas n = number of data points 1393


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