ARTICLE pubs.acs.org/EF
Optimization of a Multiparameter Model for Biomass Pelletization to Investigate Temperature Dependence and to Facilitate Fast Testing of Pelletization Behavior Jens K. Holm,† Wolfgang Stelte,*,‡ Dorthe Posselt,§ Jesper Ahrenfeldt,‡ and Ulrik B. Henriksen‡ †
Chemical Engineering, DONG Energy Power A/S, Nesa Alle 1, DK-2820, Gentofte, Denmark Biosystems Department, Risø National Laboratory for Sustainable Energy, Technical University of Denmark-DTU, Frederiksborgvej 399, DK-4000, Roskilde, Denmark § IMFUFA-Department of Science, Systems and Models, University of Roskilde, DK-4000, Roskilde, Denmark ‡
ABSTRACT: Pelletization of biomass residues increases the energy density, reduces storage and transportation costs, and results in a homogeneous product with well-defined physical properties. However, raw materials for fuel pellet production consist of lignocellulosic biomass from various resources and are therefore different in their composition and structural properties. This has the consequence that different types of biomass require different processing conditions such as press channel length and moisture content. Nowadays the process optimization is mainly based on expensive and time-consuming “trial and error” experiments and personal experience. However in recent years, the utilization of single pellet press units for testing the biomass pelletizing properties has attracted more attention. The present study outlines an approach where single pellet press testing is combined with modeling to mimic the pelletizing behavior of new types of biomass in a large scale pellet mill. This enables a fast estimation of key process parameters such as optimal press channel length and moisture content. Second, the study addresses the question of the origin of the observed relationship between pelletizing pressure and temperature.
1. INTRODUCTION Plant biomass is an increasingly important source for heat and power production, both at industrial and domestic scales, resulting in an increasing global trade of biomass.1 One major problem with biomass utilization is its low energy density which increases handling, transportation, and storage costs.2 Another important issue is its inhomogeneous structure which can result in problems during automated feeding and combustion operations.3 One way to increase both energy density and structural homogeneity of the biomass is to compress it into pellets of defined size, density, and composition. Biomass pelletization is a mechanical process in which biomass is compacted to a fraction of its volume by applying high pressures at elevated temperatures. The bulk densities of biomass can be as low as 40150 kg/m3 for grasses and 150200 kg/m3 for wood chips.4,5 The pelletizing process increases the bulk density typically up to about 700 kg/m.3,6 Biomass pellets are usually produced in pellet mills of the ring or flat die type.3 The working principle is illustrated in Figure 1, showing two eccentrically installed rollers that compact the biomass in the compression zone and subsequently force it to flow into the cylindrical press channels of the matrix. Earlier studies have shown that the compression ratio c (length/diameter) of the press channels is one of the most influential parameters, determining the magnitude of the pressure (Px) generated in press channels.79 The pressure exerted by the rollers of the pellet press (PRoller) (Figure 1b) is limited within a certain range (set by the size and motor power of the mill), and when Px exceeds this range, the pellet mill will be blocked since the rollers are not able to provide the necessary pressure to push the material through the channels. The optimal r 2011 American Chemical Society
magnitude of Px is a trade-off between the necessary pressure to produce stable pellets and the energy uptake by the pellet mill. High Px increases the risk of fires due to heat development caused by high friction, results in unnecessary energy uptake of the pellet mill,7 lowers the production capacity, and shortens the life span on wear parts of the pellet mill. The different compositions of various biomass species directly affect the pelletizing properties and the ability to form stable pellets. Especially, the presence of hydrophobic extractives such as waxes found in the cuticula of many herbaceous biomass species have been shown to inhibit interparticle bonding resulting in poor mechanical properties of the produced pellets.10 The thermal transition of the biomass polymers from a glassy into a rubbery state and their subsequent flow and ability to form interparticle bridges has been shown to be of high relevance for the pelletizing process.10,11 In addition, it has been shown that the thermal transition temperature can be very different for different types of biomass.12 These are some of the reasons why pellet mills, set for a certain type of biomass, can be used for limited other biomass types. The process development, i.e. to find the optimal processing conditions to produce stable pellets with a high throughput and minimized energy consumption, is primarily based on expensive and time-consuming “trial and error” experiments. Hence it would be advantegeous to have a method that allows a quick and simple testing of different biomass types, e.g. allowing Received: April 13, 2011 Revised: July 5, 2011 Published: July 05, 2011 3706
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Figure 1. (a) Working principle of a ring matrix pellet press and (b) magnification of a press channel showing how biomass is compacted by the roller in the compression zone and subsequently flowing into the press channel where it is further compacted due to high friction between the biomass and the walls of the press channel.
an estimation of the optimal press channel length and other key process parameters such as moisture content and particle size. The present work shows how this can be achieved by combining fast single pellet press tests with a modeling approach. In addition, the modeling makes it possible to get a better understanding of the temperature dependence of the physical parameters involved in the pelletization.
2. THEORY A theoretical model describing the physical forces in press channel, when a pellet is pressed through the die, has previously been published.8 The model is based on the observation that when a piece of wood is compressed in one direction, it tends to expand in the two other perpendicular directions. This phenomenon is known as Poisson’s effect and is measured as the Poisson ratio (υ). As wood is an orthotropic material, υ is different in each of the three principle directions. For simplicity, it is assumed that the wood fibers are oriented perpendicularly to the long direction of the die channel. Apart from υ, the model takes into account the compression ratio and the material specific sliding friction coefficient (μ). Furthermore, the model allows for inelasticity by introducing a constant prestressing term PN0.8 According to the model, the pelletizing pressure Px needed to press out a pellet of length x can be written as: Px ðxÞ ¼
PN0 2μυLR x=r ðe 1Þ υLR
ð1Þ
PN0 is the prestressing term, μ is the sliding friction coefficient, υLR is the Poisson’s ratio, r is the radius, and x is the length of the die channel. Equation 1 can then be fitted to the experimental data, obtained by measuring Px for different values of the press channel length (x). However, eq 1 contains three variable parameters (PN0, μ, and υLR) and having only one equation, it is not possible to fit all parameters in a single step, due to mutual correlations. Furthermore, values for μ and υ are not available in the literature for all types of biomass and not available for different temperatures and moisture contents either. The material specific parameter PN0 can only be determined experimentally. To solve this problem the present study describes a procedure where the parameters μ, υ, and PN0 are combined into two new parameters (U and J), that can be estimated based only on a few
Figure 2. Schematic diagram showing how simple and fast testing with a single pellet press (SPP) unit in combination with modeling can predict the performance of an industrial pellet mill, where testing otherwise would be expensive and time-consuming.
experimental trials using a single pellet press. The simplicity of this method allows faster testing of new types of biomass by easy estimation of the compression curves (Px vs c). The procedure is to introduce the compression ratio c = x/2r and the two combined parameters U = μPN0 and J = μυLR in eq 1 leading to U ð2Þ Px ðcÞ ¼ ðe4Jc 1Þ J It has been shown earlier8 that in the limit of small c (c , 1), eq 2 is given as Px ðcÞ = 4Uc for c , 1 ð3Þ In the limit of small c, U can be determined from the slope of the linear plot of Px as a function of c: dP 1 dP ¼ 4U w U ¼ ð4Þ dc 4 dc By the introduction of eq 4 one now has two equations and two unknowns (U and J); hence, a solvable system of equations has been obtained. 3707
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Energy & Fuels Following the presentation of the underlying theory, the general idea can now be explained with reference to Figure 2. A single pellet press unit (SPP-unit) is used to make pelletizing tests of the biomass in question at low compression ratios: 23 measurements in the linear region (c < 1) and 23 measurements in the intermediate region (c ∼ 4). The U parameter can now be obtained from the linear part of the pelletization pressure curve (given by the data points at c < 1) by applying eq 4. Subsequently, by using the obtained value of U, the J parameter can be obtained by fitting eq 2 to all the experimentally determined data points. This procedure is valid under the assumption that measurements can be made at sufficiently small compression ratios, thereby ruling out the importance of differences in Poisson’s ratios. Pelletizing tests performed with this method are carried out at much lower compression ratios than what is mainly the case for large-scale industrial pellet mills (c ∼ 78). This has some substantial time-saving benefits; Pellets made with the SPP unit have to be build up by sequentially loading small amounts of biomass into the unit, in order to simulate the loading process taking place in the ring matrix pellet mill.8 For long pellets (high c), this is a very time-consuming and often troublesome procedure, since it involves the measurement of potentially high pressures in a small tool like the single pellet press. The procedure introduces a degree of uncertainty due to extrapolation to high c values. However, it has previously been shown that the applied model provides an acceptable estimation of the pelletizing pressure at high c values.9 Furthermore, the benefits of not having to carry out measurements on long pellets, more than compensates the disadvantage. Second, the dependency on properties like temperature, moisture, and particle size of the U and J parameters can be evaluated separately, and hence, one can get an idea about the dependency on the underlying parameters, e.g. friction coefficient and Poisson’s ratio.
3. EXPERIMENTAL SECTION 3.1. Materials. Two different wood species were used for the experiments: Debarked Norway spruce (Picea abies, (L) Karst) and debarked European beech (Fagus sylvatica, L.). Both species were supplied as chips and processed in a hammer mill (Champion, CPM, USA), equipped with a 5 mm screen. Following comminuting, the moisture content of the samples was adjusted to 10% (wet basis) and stored in airtight containers before use. 3.2. Method. Small-scale pelletization tests are performed using a single pelletizing unit (SPP-unit) (designed and built at the workshop of the biomass gasification group, Risø-DTU). The SPP unit consisted of a cylindrical die made of hardened steel with a central channel. The unit was covered with heating elements and thermal insulation. The temperature was controllable between 20 and 180 °C, using thermocouples connected to a control unit. The end of the die could be closed using a backstop. Pressure was applied, and the force was measured using a load cell. In the present study, an SPP unit with an 8 mm channel diameter was used. The wood particles were loaded in sequential steps not exceeding 0.15 g per layer. Pellets were pressed using a compression tester (TTCC, Instron, USA) at a rate of 2 mm/s until the maximum pressure of 200 MPa was reached. The pressure was released after 5 s, the piston removed, and a new amount of sample was loaded and compressed. This procedure was repeated until the pellet had the desired length. It has to be noted, that during the single pellet pressing the material was in press channel for at about 5 min, so that a homogeneous heating of the pellet
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Figure 3. Linear relationship between pelletization pressure and compression ratio for beech at 20 °C. could be assumed. When the desired length was reached after the pellet was pressed, the backstop of the unit was removed and Px was determined by measuring the maximum pressure required to press the pellet out of the die. For the determination of U and J, all measurements were made at the following temperatures: 20, 40, 60, 80, and 100 °C. Determination of U. For each temperature, three measurements were made at three different compression ratios, all for c < 0.4. At each chosen compression ratio, the measurement was repeated three times, and the average value and standard deviation were calculated. Then a linear fit was made to the measurement points (including 0.0) and U was determined from the linear slope obtained from the fit, as described in the Theory section. Determination of J. For each temperature, three measurements were made at three different compression ratios, approximately at c = 1, c = 2, and c = 3. Measurements were repeated for some of the data points, showing that the standard deviation was less than 5%. The value of J was obtained by performing a nonlinear fit of eq 2 to all the experimentally determined data points, as described in the Theory section. In this fit, the previously determined value of U for each temperature was used as a constant in eq 2.
4. RESULTS AND DISCUSSION Figure 3 shows an example of the linear relationship between pelletizing pressure and compression ratio for short beech pellets at 20 °C. Generally, the measurements show good linearity up to compression ratios of 0.35 (R2 between 0.9 and 0.99). Hence it is reasonable to determine the U parameter from a linear leastsquares fit to the data points up to a compression ratio of c < 0.35. Obviously, the quality of the fit depends upon the number of data points used. With only four data points (including 0.0), the degree of precision of the measurements also plays a critical role. The three measured data points were based on five replicates (Error bars indicate standard deviations). The graphs in Figure 4 show the fitted U parameters obtained at different temperatures for beech and spruce. Each point is determined from linear least-squares analysis of the experimental data points up to c < 0.35. Linear trend lines have been added to the graphs for guidance. Figure 4 shows that the U parameter of beech decreases as the pelletizing temperature is increased and that the U parameter decreases in a linear manner. For spruce the U parameter is also decreasing as the temperature is increased, but the slope of the linear fit is about 5 times smaller. Hence the temperature dependence of the U parameter is not as strong for spruce as for beech. 3708
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Figure 6. J parameter as a function of temperature for beech and spruce. The fit of the J parameter for each temperature is based on the linear, temperature dependent value of U, given by the linear fits in Figure 4. Figure 4. U parameter as a function of temperature for beech and spruce. Linear trend lines are shown in the graph.
Figure 7. Pelletizing pressure of beech as a function of compression ratio for different temperatures of the press channel. Figure 5. J parameter as a function of temperature for beech and spruce. The fit of the J parameter for each temperature is based on the corresponding U value given in Figure 4.
The fitted value of U obtained from the linear part of the compression curve (c < 0.35) is now used to fit the J parameter, using a least-squares fit to all the measured data points. During this fit, the previously fitted value of U (given in Figure 4) at the specific temperature is kept constant. Figure 5 shows the fitted values of the J parameter as function of temperature for beech and spruce. Judged from the appearance of the data of both beech and spruce, there seems to be no systematic correlation between the J values and the temperature. However, the variations in the J values are relatively small in comparison with the absolute values, up to a maximum of 12%. It is clear from the data in Figures 4 and 5 that the variation of U and J shows unsystematic changes as the temperature is increased. This indicates that the temperature dependence of U and J, i.e. μ, PN0, and υLR, is not simple and might be influenced by mutually related effects of the three parameters. Hence a useful approach may be to assume a simplified temperature behavior of U and J and then evaluate how this affects the ability
of the model to describe the temperature dependency of the experimental data points. As a first step, it is of interest to see if the variation of the J parameter is correlated with the variation of the U parameter. This is done by assuming that the U parameter follows the linear fit as given in Figure 4, i.e. for each temperature, the value of U is calculated based on the linear equation given in Figure 4. Figure 6 shows the fitted values of J obtained when U is forced to follow the linear fit given in Figure 4. The J parameter of both beech and spruce is still varying with temperature, but the variations are smaller. The next step is to assume that the value of J is constant in the investigated temperature range. From looking at the data of J in Figure 6 this may be a reasonable approach. The final step is to verify that the assumptions (linear temperature dependence of U and a constant value of J) are justified. Hence by using the linear dependency of U and the constant value of J, the model is recalculated and compared with the experimental data. This is shown in Figures 7 and 8 for beech and spruce, respectively. Figure 7 shows experimentally obtained data points (connected with dotted lines to guide the reader) along with the corresponding solid curves obtained from the modeling. The model curves are based on eq 2, with U values obtained from 3709
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Figure 8. Pelletizing pressure of spruce as a function of compression ratio for different temperatures of the press channel.
Figure 4 and with the value of J taken as the average value over the temperature range given in Figure 6. As indicated in the figure legend, an additional model curve (dashed line) has been inserted in the figure, where the J value is not the average value, but the actual value determined at 100 °C. The same procedure is used for the data in Figure 8 (spruce data), with the only difference that the average value of J was able to fit all data points, obtained at the different temperatures. Figure 7 shows that by assuming a linear temperature dependency of U and a constant value of J, the model is able to describe the measured data of beech well. Only at 100 °C, the model shows a significant deviation from the experimental data points. This is caused by the rather abrupt increase of J at 100 °C (Figure 6). As shown in Figure 7, when using the actual value of J at 100 °C and not the average value (0.2957 instead of 0.2669), the model is also able to describe the data obtained at 100 °C. Based on the experimental data, it seems that the Poisson ratio is not linearly correlated with the temperature in the whole investigated temperature range, which might be explained with the glass transition of lignin which has earlier been determined to be at about 90100 °C for the raw material used in the present study and similar moisture content.12 Figure 8 shows the experimental data and the matching model curves for the spruce data. Again, The U parameter is forced to follow the linear relation given for spruce in Figure 4 and J is taken as constant (J = 0.2413). As with beech, the agreement between the experimental data and the model curves is good. Figures 7 and 8 show that the temperature dependence of the pelletization pressure can be modeled satisfactorily by using the modeling approach described above, i.e. by letting the temperature dependence of U be a linear function of the temperature and by letting J be approximated by a constant. On the basis of this, U is shown to decrease with increasing temperature. At 20 °C, the U parameter of beech is higher than the corresponding U value for spruce, but as the negative slope of beech is steeper, the U parameter of beech takes on the smallest value at 100 °C. By comparing Figures 7 and 8, it is clearly seen that the curves in Figure 8 are overlapping. This is an important result, showing that pelletization of beech is more temperature sensitive than pelletization of spruce as a function of compression ratio. As shown earlier,7 this implicates that at compressions ratios relevant for large-scale pellet mills, the temperature and type of
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biomass has a large impact on the pelletization pressure. One consequence is that it is not possible to start up a cold mill directly on beech, since the low temperature during start-up results in high pressures in press channels. It has previously been shown that the friction work decreases in a linear manner when the temperature was increased from 40 °C to around 100 °C. Furthermore, it was shown that the decrease in friction work was significantly faster for beech than for pine.13 This supports the findings in this study, showing that the U parameter expresses a similar temperature dependence. The specific slopes of the linear trend lines and the positions of the crossing points may vary according to wood species, moisture and extractives content and particle size distribution. Stelte et al.7 have shown that particle size distributions dominated by small particles increase the pelletizing pressure compared to more coarse distributions. The lower temperature dependence of the U parameter of spruce compared to beech is likely to be related to the higher extractives content of spruce compared to beech.14 The role of extractives on the frictional properties has previously been described.1416 If the extractives are able to lubricate the press channel walls even at room temperature, this by itself may suppress the temperature dependence. According to the definitions of the U and J parameters (U = μPN0 and J = μυLR), it might be speculated that the temperature dependence is mostly related to the friction coefficient μ and the Poisson ratio υLR. The prestressing pressure PN0 may not express a significant temperature dependence in the investigated range (20100 °C), as the permanent inelastic deformation of the biomass material is more likely to be a consequence of the high pressure applied. On the other hand, the Poisson ratio may be more temperature dependent due to the softening of the fibers. One may even speculate that the Poisson ratio increases as the temperature is raised, thus explaining why the J parameter appears to be constant over the investigated temperature range. This may simply be a consequence of the opposite temperature dependence of the friction coefficient and the Poisson ratio. As shown in Figure 7, the model curve deviates significantly from the experimental data at 100 °C. Hence, the assumption of a linear temperature dependence of U and no temperature dependence of J is not justified. This can be explained due to several phenomena occurring at temperatures around 100 °C. Previous work has shown that the glass transition of lignin in wood at the given moisture content takes place between 90 and 100 °C.12 This changes the physical properties of the material and this effect is not accounted for in the model. Furthermore, the influence of extractives and water evaporation has an influence on the physical properties of the biomass and its pelletizing properties.7 To take these effects into account in the modeling requires further studies.
5. CONCLUSIONS In the present work, we have demonstrated that the modified model is able to fit experimental pelletization pressure data, obtained with a single pellet press on beech and spruce at temperatures between 20 and 100 °C. By utilizing the linear dependence of the pelletization pressure as a function of the compression ratio (c) for small values of c along with a fit to data at higher c values, it is possible to unambiguously determine two parameters U and J that are combinations of the three physical parameters μ, PN0, and υLR (U = μPN0 and J = μυLR). 3710
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Energy & Fuels It is shown that acceptable fits to the experimental data can be obtained, if the U parameter is forced to follow the fitted linear temperature dependence and the J parameter is fixed at a constant value, taken as the mean value in the investigated temperature range. Even though this may seem like a crude simplification, it results in a good agreement between model and experimental data and allows for an easy prediction of the pelletization behavior at higher compression ratios, relevant for large scale pellet mills. The U parameter is shown to decrease in a linear manner as the temperature in increased. Furthermore, the decrease is more pronounced for beech than for spruce. This is likely to be related to the higher extractives content in spruce compared to beech.14 The extractives in spruce may to some extent play down the temperature dependence of the frictional properties, resulting in a smaller slope of the U curve. The J parameter shows only minor temperature dependence. This may be a consequence of two opposite working effects; reduced friction and induced impact of Poisson’s effect, due to softening of the fibers. Looking into a future where more and more biomass species and residues will be evaluated as potential raw materials for fuel pellet production, the need for efficient and reliable testing methods will increase. Together with the development of the mechanical testing methods there is a need to obtain a better understanding of the physical mechanisms involved in pelletization, and as the present study suggests, a modeling approach is an important and necessary step on the way.
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pressure and its dependency on the processing conditions. Fuel 2011; DOI10.1016/j.fuel.2011.05.011, in press. (8) Holm, J. K.; Henriksen, U. B.; Hustad, J. E.; Sorensen, L. H. Toward an understanding of controlling parameters in softwood and hardwood pellets production. Energy Fuels 2006, 20 (6), 2686–2694. (9) Holm, J. K.; Henriksen, U. B.; Wand, K.; Hustad, J. E.; Posselt, D. Experimental verification of novel pellet model using a single pelleter unit. Energy Fuels 2007, 21 (4), 2446–2449. (10) Stelte, W.; Holm, J. K.; Sanadi, A. R.; Barsberg, S.; Ahrenfeldt, J.; Henriksen, U. B. A study of bonding and failure mechanisms in fuel pellets from different biomass resources. Biomass Bioenergy 2011, 35 (2), 910–918. (11) Kaliyan, N.; Morey, R. V. Natural binders and solid bridge type binding mechanisms in briquettes and pellets made from corn stover and switchgrass. Bioresour. Technol. 2010, 101 (3), 1082–1090. (12) Stelte, W.; Clemons, C.; Holm, J. K.; Ahrenfeldt, J.; Henriksen, U. B.; Sanadi, A. R. Thermal transitions of the amorphous polymers in wheat straw. Ind. Crops Prod. 2011, 34 (1), 1053–1056. (13) Nielsen, N. P. K.; Gardner, D. J.; Poulsen, T.; Felby, C. Importance of temperature, moisture content, and species for the conversion process of wood into fuel pellets. Wood Fiber Sci. 2009, 41 (4), 414–425. (14) Nielsen, N. P. K.; Gardner, D. J.; Felby, C. Effect of extractives and storage on the pelletizing process of sawdust. Fuel 2010, 89 (1), 94–98. (15) Nielsen, N. P. K.; Holm, J. K.; Felby, C. Effect of fiber orientation on compression and frictional properties of sawdust particles in fuel pellet production. Energy Fuels 2009, 23, 3211–3216. (16) Nielsen, N. P. K.; Nørgaard, L.; Strobel, B. W.; Felby, C. Effect of storage on extractives from particle surfaces of softwood and hardwood raw materials for wood pellets. Eur. J. Wood Prod. 2009, 67, 19–26.
’ AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected]. Phone: +45 2132 5175.
’ ACKNOWLEDGMENT The present study was conducted under the framework of the Danish Energy Agency’s EFP project: “Advanced understanding of biomass pelletization” ENS-33033-0227. The authors wish to thank Vattenfall A/S, DONG Energy A/S, and the Danish Energy Agency for financial support. ’ REFERENCES (1) Sikkema, R.; Steiner, M.; Junginger, M.; Hiegl, W.; Hansen, M. T.; Faaij, A. The European wood pellet markets: current status and prospects for 2020. Biofuels Bioprod. 2011, 5, 250–278. (2) Kumar, A.; Cameron, J. B.; Flynn, P. C. Biomass power cost and optimum plant size in western Canada. Biomass Bioenergy 2003, 24 (6), 445–464. (3) Obernberger, I.; Thek, G. The pellet handbook - The production and thermal utilisation of biomass pellets; Earthscan: London, 2010. (4) Mani, S.; Tabil, L. G.; Sokhansanj, S. Effects of compressive force, particle size and moisture content on mechanical properties of biomass pellets from grasses. Biomass Bioenergy 2006, 30 (7), 648–654. (5) Chevanan, N.; Womac, A. R.; Bitra, V. S. P.; Igathinathane, C.; Yang, Y. T.; Miu, P. I.; Sokhansanj, S. Bulk density and compaction behavior of knife mill chopped switchgrass, wheat straw, and corn stover. Bioresour. Technol. 2010, 101 (1), 207–214. (6) Kaliyan, N.; Morey, V. Densification of biomass; VDM Verlag: Saarbr€ucken, 2008. (7) Stelte, W.; Holm, J. K.; Sanadi, A. R.; Ahrenfeldt, J.; Henriksen, U. B. Fuel pellets from biomass: The importance of the pelletizing 3711
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