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Energy & Fuels 1998, 12, 90-94
Articles A New Method for Quantification of Fluidized Bed Agglomeration Tendencies: A Sensitivity Analysis Marcus O ¨ hman* and Anders Nordin Energy Technology Centre, Department of Inorganic Chemistry, Umeå University, PO Box 726, S-941 28 Piteå, Sweden Received March 25, 1997X
A new method for quantification of fluidized bed agglomeration tendencies for different fuels has been developed and evaluated. A bench scale fluidized bed reactor (5 kW), specially designed to obtain a homogeneous isothermal bed temperature, is used. The method is based on controlled increase of the bed temperature by applying external heat to the primary air and to the bed section walls. In addition, temperature homogeneity is secured by switching from normal fuel feeding to a propane precombustor. The initial agglomeration temperature is determined by onor off-line principal component analysis of the variations in measured bed temperatures (four values) and differential pressures (four). To determine potential effects of all the process related variables, an extensive sensitivity analysis was performed. Experiments were performed according to a statistical experimental design to evaluate the effects of eight different process analytical variables on the determined agglomeration temperature of a biomass fuel. The results showed that for a given fuel, the amount of bed material, heating rate, fluidization velocity, and air to fuel ratio during both “ashing” and heating did not influence the determined agglomeration temperature. Only ash to bed material ratio, the ashing temperature, and the bed material particle size had significant effects on the agglomeration temperature, but still the effects were relatively small. The agglomeration temperature of the fuel could be determined to 899 °C (avg) with a reproducibility of (5 °C (SD). The inaccuracy was determined to be (30 °C (SD). Based on the results, the method was standardized with respect to ash to bed material ratio, bed material particle size, and ashing temperature. Relative agglomeration temperatures of different fuels, fuel, and additive combinations can thus be determined with a high precision.
Introduction Biomass fuels contain varying amounts of elements which may reduce the melting point of the ash, for example potassium, sodium, sulfur, and chlorine. This may cause significant operational problems in combustion, such as formation of deposits in the furnace (slagging) and in the heat exchange sections (fouling). Due to the relatively low temperatures in fluidized bed combustion and gasification, these processes seem to be the most promising energy conversion techniques to reduce deposit formation using different solid fuels. However, bed agglomeration could be a potential problem, which in the most severe cases can result in total defluidization of the bed. Presently there are no reliable methods to determine bed agglomeration tendencies of different fuels, fuel combinations, or fuels with additives. Standard ash fusion tests1,2 are often used to predict the behaviour of the ash in different processes, but the methods have Abstract published in Advance ACS Abstracts, November 15, 1997. (1) DIN Pru¨fung no. 51730. Testing of solid fuels, determination of fusibility of fuel ash (In German), 1984. X
been extensively criticized in the literature.3-6 For example, it was shown by Stallman et al.7 that agglomeration often occurs at temperatures several hundred degrees below the initial deformation temperature of the ash, as determined by the ASTM ash fusion test. Other laboratory methods that have been used for ash melting predictions are shrinkage tests, based on dilatometric measurements8-10 and the electrical resistance (conductance) test, based on ionic mobility.8,11,12 Com(2) ASTM D 1857. Annual Book of ASTM Standards Pt 26; American Society for Testing and Materials: Philadelphia, PA, 1987; pp 263268. (3) Wall, T. F; Creelman, R. A.; Gupta, R. P.; Gupta, S.; Coin, C.; Lowe, A. Proc. 1995 Eng. Found. Ash Conf. 1995, 541-556. (4) Coin, C.; Kahraman, H.; Peifenstein, A. P. Proc. 1995 Eng. Found. Ash Conf. 1995, 187-200. (5) Gerald, P. H.; Huggins, F. E.; Dunmyre, G. R. Fuel 1981, 60, 585-597. (6) Huggins, F. E.; Deborah, A. K.; Gerald, P. H. Fuel 1981, 60, 577584. (7) Stallman, J. J.; Neavel, R. C. Fuel 1980, 59, 584-586. (8) Raask, E. J. Thermal Anal. 1979, 16, 91-102. (9) Smith, E. J. D. Journal Inst. Fuel 1956, 29, 253-260. (10) Manzoori, A. R. Thesis, University of Adelaide, 1990. (11) Frederikse, H. P. R.; Hosler, W. R. J. Am. Ceram. Soc. 1973, 56, 418-419. (12) Cumming, J W. J. Inst. Energy 1980, 53, 153-154.
S0887-0624(97)00049-2 CCC: $15.00 © 1998 American Chemical Society Published on Web 01/12/1998
Quantification of Fluidized Bed Agglomeration Tendencies
Energy & Fuels, Vol. 12, No. 1, 1998 91
Figure 1. Illustration of the bench scale fluidized bed reactor.
pression tests based on compression strength measurements of sintered ash pellets13-15 and sieving tests7,16 have also been used for predictions of ash behavior. However, none of these laboratory methods address the ash transformations in a fluidized bed. A more relevant method would be to use a fluidized bed for actual bed agglomeration studies. Several such bench scale studies have previously been conducted to determine the agglomeration tendencies of different fuels.16,17-20 However, the most important individual parameter influencing the bed agglomeration is the actual bed or process temperature. In all the above bench scale studies, at least one unknown variable is introduced by the burning particles in the bed. The surface temperature of the burning particles may exceed the bed temperature by 40-600 °C, the largest difference being found for the smallest particles and highest particulate phase oxygen concentrations.21-25 Although West et al.,26 Basu and Sarka,27 and Gluck(13) Barnhart, D. H.; Williams, P. C. Trans. ASME 1956, 78, 12291236. (14) Hupa, M.; Skrifvars, B. J.; Moilanen, A. J. Inst. Energy 1989, 62, 131-137. (15) Skrifvars, B. J.; Hupa, M.; Hiltunen, M. Ind. Eng. Chem. Res. 1992, 31, 1026-1030. (16) Ergudenler, A.; Ghaly, A. E. Biomass Bioenergy 1993, 4, 135147. (17) Salour, D.; Jenkins, B. M.; Vafei, M.; Kayhaian, M. Biomass Bioenergy 1993, 4, 117-133. (18) Atakul, H.; Ekinci, E. J. Inst. Energy 1989, March, 56-61. (19) Dawson, M. R.; Brown, R C. Fuel 1992, 71, 585-592. (20) Manzoori, A. R.; Agerwall, P. K. Fuel 1992, 72, 1069-1075. (21) Roscoe, J. C.; Witkoswki, A. R.; Harrison, D. Trans. I. Chem. E. 1980, 59, 69-72. (22) LaNauze, R. D.; Jung, K.; Dent, D. C.; Joyce, T.; Tait, P. J.; Burgess, J. M. Proc. Int. Conf. Fluidized Bed Combust. 1987, 9, 707712. (23) Stubington, J. F. Chem. Eng. Res. Des. 1985, 63, 241-249. (24) Basu, P.; Halder, P. K. Fuel 1989, 68, 1056-1063. (25) Basu, P. Fuel 1977, 56, 390-392. (26) West, S. S.; Williamson, J.; Laughlin, M. K. Proc. Eng. Found. Ash Conf. 1993, 93-100. (27) Basu, P.; Sarka, A. Fuel 1983, 62, 924-926.
man et al.28 have determined agglomeration temperatures of ash or inorganic material without burning particles, there does not seem to be any well-documented, realistic, controlled and evaluated method available. The objectives of the present work were therefore to develop a new, realistic, accurate method to determine the bed agglomeration tendencies of different fuels in fluidized bed combustion and gasification and to determine the inaccuracy and reproducibility of the new method by utilization of a statistical experimental design including all important variables. The results showed that the new method can be used to determine the fuel specific agglomeration temperature with a reproducibility of (5 °C (SD) and an accuracy of (30 °C (SD). Experimental Section The Controlled Fluidized Bed Agglomeration Method. A bench scale fluidized bed combustor (5 kW) was constructed to enable realistic and highly controlled bed agglomeration tests with a homogeneous bed temperature (Figure 1). The pilot reactor is made of stainless steel (SS 2343), being 2 m high, and 100 mm and 200 mm in diameter in the bed and freeboard sections, respectively. A perforated stainless steel distributor plate with 1% open area and a total of 90 holes is used. The maximum temperature of the equipment is 1020 °C. To allow for a constant increase of the bed temperature, with a homogeneous temperature profile, much effort was focused on improving the bed section of the reactor as well as the controlling system. To keep the walls at the same temperature as the bed, the reactor is equipped with controlled electrical wall heating elements. An air preheater allowing primary air temperatures up to 1050 °C was constructed to control the bed temperature. Forced convection is utilized in a cyclone-like stainless steel cylinder equipped with Kanthal electric wall heating elements. All temperatures are controlled (28) Gluckman, M. J.; Yerushalmi, J.; Squires, A. M. Fluidization Technol. 1976, 2, 395-422.
92 Energy & Fuels, Vol. 12, No. 1, 1998
expt
bed material particle size (µm)
ashing temp (°C)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21c 22c 23c 24c
+ + + + + + + + 0 0 0 0 0 0 0 0
+ + + + + + + + 0 0 0 0 -
O ¨ hman and Nordin
Table 1. Experimental Design in Scaled Units ash to bed excess oxygen (% O2 dry) amount of bed material heating rate material (mL) ratio (%) (°C/min) ashing agglomrn + + + + + + + + 0 0 0 0 0 0 0 0
+ + + + + + + + 0 0 0 0 0 0 +
+ + + + + + + + 0 0 0 0 0 0 0 0
+ + + + + + + + 0 0 0 0 0 0 0 0
+ + + + + + + + 0 0 0 0 0 0 0 0
Ua/Umf b
agglomeration temp (°C)
+ + + + + + + + 0 0 0 0 0 0 0 0
889 893 843 856 901 882 863 843 920 880 898 915 907 871 930 904 930 939 940 933 924 923 913 921
a Actual fluidization velocity (m/s). b Minimum fluidization velocity (m/s). c Experiments added to the 28-4 design to obtain quadratic terms.
Figure 2. Illustration of a typical agglomeration test run. by Eurotherm temperature controllers and the maximum temperature deviation within the bed was determined to be less than (2 °C. Each experiment is started by normal fluidized bed combustion (“ashing”) of the fuel to obtain a sufficient amount of ash in the bed (Figure 2). Then the fuel feeding is stopped to avoid the uncertainties associated with the burning particle temperatures. Instead, the bed temperature is increased linearly by external heat in a homogeneous and controlled way. To maintain a combustion atmosphere in the bed during the external heating phase of the test, the primary air and propane are mixed and burned in a combustion chamber prior to the air distributor. Bed temperatures at four locations in the bed are measured by shielded thermocouples (type S) and differential bed pressures in four different regions are determined by differential pressure transducers. Further, the initial agglomeration temperature is more exactly determined by on- or off-line principal component analysis (PCA).29 PCA is a multivariate data space projection method with excellent graphical display capabilities of the major variation/covariation patterns in the multivariate data. Here, variations in all the measured variables (bed temperatures and pressures) can be simultaneously taken into account for the analysis. Plots as in Figure (29) Wold, S. Technometrics 1978, 20, 397.
Figure 3. Typical example of a principal component score plot, as an identification tool for initial agglomeration. 3 continuously illustrate the maximum variance (t[1], t[2]) in the bed related data, significantly facilitating the identification of the initiation temperature of the agglomeration process. The flue gas composition (O2, CO2, CO, NO, SO2, THC) is continuously analyzed using conventional instruments. Samples of ash and bed material for evaluation of agglomeration mechanisms may be collected as a function of time. Sensitivity Analysis. Our previous experimental agglomeration tests,30 using the proposed method, have indicated both realistic fluidized bed conditions and high reproducibility of the determined agglomeration temperature. However, to determine the effects of all potentially influential variables on the agglomeration temperature, a systematic sensitivity analysis was performed. The variables included in the study were bed material particle size, ashing temperature, amount of bed material, ash to bed material ratio, heating rate, excess air during the ashing phase, excess air during the external heating phase and fluidization velocity. To determine the effects of all these variables on the fuel-specific agglomeration temper(30) Nordin, A.; O ¨ hman, M.; Skrifvars, B-J; Hupa, M. Proc. 1995 Eng. Found. Ash Conf. 1995, 353-366.
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Energy & Fuels, Vol. 12, No. 1, 1998 93
Table 2. Factors and Their Design Levels levels
bed material particle size (µm)
ashing temp (°C)
amount of bed material (mL)
ash to bed material ratio (%)
heating rate (°C/min)
0 +
160-200 200-250 250-355
720 760 800
350 400 450
3 6 9
1 3 5
ature, a fractional factorial design (28-4) was used.31 In addition, the design was expanded with four new experiments (no. 21-24 in Table 1) to determine the most important nonlinear terms. Practical ranges of the different variables were determined by initial trial experiments and the upper and lower levels for the factors were chosen to cover about 80% of the practically possible experimental domain (Table 2). Hereby, any potential discrepancies between bench and full scale behavior will also be indicated. The results from an initial experimental design showed that about 30% of the total ash in the fuel stayed in the bed, independent of the other operating variables in the reactor. These initial runs also showed that less than 1.5% of ash in the bed is sufficient for agglomeration to occur. Ash concentrations of 3, 6, and 9% in the bed were therefore chosen for the study. Combustion (“ashing”) temperatures of 720, 760, or 800 °C were used and excess oxygen levels were maintained at 4, 6, or 8%dry. The fuel flow rate was controlled by a screw feeder and a vibrator to obtain a constant combustion temperature. Subsequent to the normal combustion phase, the temperature was externally raised at a rate of 1, 3, or 5 °C/ min (Figure 2). During the external heating phase, the air to fuel ratio was controlled to give excess oxygen concentrations of 8, 10, or 12%dry and the fluidization velocity was chosen to be 3, 4, and 5 times that of minimum fludization velocity. The reason for the higher oxygen concentrations during the external heating phase was that lower values resulted in an excessively high bed temperature. The minimum fluidization velocity was determined experimentally as a function of temperature, amount of bed material, and bed material particle size. The minimum fluidization velocity was found to be 7 cm/s and was not significantly affected by any of the variables within the studied experimental domain. In Table 1 the final experimental design is shown in coded units. To minimize the effect of uncontrolled factors and time trends, the experiments were performed in randomized order. Fuel and Bed Material Used. A biomass fuel was chosen because of the relatively homogeneous nature of these fuels.32 From a previous study,30 we determined the critical agglomeration temperature of an olive fuel to be 940 °C, which seemed to be a suitable “starting point” for a sensitivity analysis. The olive fuel was pelletized to a diameter of 10 mm and a length of 5-10 mm and then sieved prior to the experiments, so that the fraction of fines in the feed could be kept less then 2%. The fuel characteristics are summarized in Table 3. Quartz sand, with more than 98.9% SiO2, was used as bed material.
Results and Discussion The resulting agglomeration temperatures are presented in Table 1. A polynomial was fitted to the measured data by multiple regression, and the effects of the different variables are presented in the form of scaled regression coefficients for the different variables and the significant interaction terms (Table 4). The scaling makes the coefficients directly intercomparable, and a large numerical value indicates a strong influence, (31) Box, G. E. P.; Hunter, W. G.; Hunter, J. S. Statistics for experimenters; An introduction to design, data analysis and mode building; Wiley: New York, 1978. (32) Nordin, A. Biomass Bioenergy 1994, 6, 339-347.
excess oxygen (% O2 (dry)) ashing agglomrn 4 6 8
8 10 12
U/Umf 3 4 5
Table 3. Characteristics of Fuel and Bed Material olive flesh dry substance asha HV (MJ/kgfuel) Ca Ha Na Sa Cla Oa a
85.6 9.9 16.0 50.2 6.3 1.4 0.14 0.15 32.1
b
SiO2 Al2O3b Fe2O3b MgOb CaOb K2Ob Na2Ob P2O5b
ash (550 °C)
bed material
36.2 3.60 4.25 12.4 18.2 18.2 1.70 4.00
98.9 0.181 0.123 0.129 0.123 0.0599 0.0400 0.7) indicate that the model has a good predictive ability.33 From the four center points, the reproducibility of the method was determined to be better than 5 °C (SD). The results showed clearly that the variables amount of bed material, heating rate, air to fuel ratios, and fluidization velocity had no significant effects on the determined agglomeration temperature. The ash to bed material ratio, ashing temperature, and bed material particle size showed significant effects, but still these effects were relatively small. Further, the small but significant interaction effect (β2β3) between ashing temperature (β2) and ash to bed material ratio (β3) is (33) Eriksson, L.; Hermens, J. L. M.; Johansson, E.; Verhaar, H. J. M.; Wold, S. Aquatic Sci. 1995, 57, 1015-1621.
94 Energy & Fuels, Vol. 12, No. 1, 1998
O ¨ hman and Nordin
Table 4. Scaled Coefficients for the Agglomeration Temperature term
coefficient
constant (β0) bed material particle size (β1) ashing temperature (β2) ash to bed material ratio (β3) amount of bed material (β4) heating rate (β5) excess oxygen (ashing) (β6) excess oxygen (agglomeration) (β7) U/Umf (β8) β12 β32 β2β3 or β1β8
935.6 -6.0 -6.3 16.2 no significant effect no significant effect no significant effect no significant effect no significant effect -20.8 -27.7 14.1
confounded with the interaction effect β1β8. Although we cannot exclude the latter’s importance, the fact that fluidization velocity has no effect significantly reduces the probability that β1β8 would be significant. The reason for the influences, although relatively small, of ash to bed material ratio, bed material particle size, and ashing temperature remains unclear. Possible explanations include (i) influence of the ash to bed material ratio on the fluid dynamics in the bed during agglomeration, (ii) influence of the actual process temperature on the chemical speciation during the normal combustion procedure, and (iii) variations in elemental losses during the ashing procedure. If the method is further standardized with respect to bed material particle size, ashing temperature and ash to bed material ratio (for example, 200-250 µm, 760 °C, and 6% respectively), relative fuel specific agglomeration temperatures can be determined with a high precision ((5 °C, SD). Based on the effects of the maximum variation in the studied variables, the maximum inaccuracy of the method was estimated to be (30 °C (SD). This standardized method has recently been used for several biomass fuels,34 and their agglomeration temperatures are presented in Figure 4, where both precision and inaccuracy are illustrated with error bars. This may be compared with the inaccuracy of several hundred degrees for the standard ASTM test.5-7 (34) O ¨ hman, M.; Nordin, A.; Skrifvars, B. J.; Hupa, M. Submitted for publication in Energy Fuels.
standard error
P (%)
confidence interval (0.95)
5.9 2.7 2.6 2.7
0 4.0 2.9 0
12.5 5.7 5.6 5.7
6.6 6.6 2.7
0.6 0 0
14.1 14.1 5.7
Conclusions In conclusion, the controlled fluidized bed agglomeration test seems to be a valuable and accurate method to determine agglomeration tendencies for different fuels, and fuel and additive combinations. In contrast to the existing standard methods, the proposed method comprises also the important fate and transformations of the ash-forming elements in an actual fluidized bed process. By the systematic approach, we have shown that the different process-related variables influence the agglomeration temperature only marginally. Hereby, the agglomeration temperature for the olive fuel could be determined to 899 °C (avg) with a reproducibility of (5 °C (SD) and an estimated inaccuracy of (30 °C. Further, the present and previous results30,34,35 indicate that the fuel specific bed agglomeration temperature is mainly determined by the chemical characteristics and thereby the melting behavior of the ash and the bed material. Acknowledgment. Professor Mikko Hupa is acknowledged for the stimulating discussion during initiation of the work. Financial support given by the Swedish National Board for Industrial and Technical Development (NUTEK) is gratefully acknowledged. EF970049Z (35) Skrifvars, B. J.; O ¨ hman, M.; Nordin, A.; Hupa, M. Submitted for publication in Energy Fuels.
