Agglomeration Phenomena during the Fluidized Bed Combustion of Olive Husk

Transcription

1 Agglomeration Phenomena during the Fluidized Bed Combustion of Olive Husk 1 F. Tartaglione, 2 A. Cammarota, 2 R. Chirone, 2 F. Scala 1 Dipartimento di Ingegneria Chimica - Università Federico II, Naples - I T A L Y 2 Istituto di Ricerche sulla Combustione - C.N.R., Naples - ITALY ABSTRACT The fluidized bed combustion of a biomass residue (olive husk) common in the Mediterranean area has been investigated in a bench scale reactor. The focus of the study was the high propensity of this fuel to give rise to bed agglomeration problems during combustion, as a consequence of the high potassium content of the ash. Bed agglomeration times and temperature/pressure gradients were measured at different operating conditions. In addition, a new diagnostic tool based on the measurement of the dynamic pressure signal inside the bed was tested for its capability to predict the bed agglomeration onset. INTRODUCTION The attractiveness of biomass fuels as a renewable and CO 2 -neutral energy source has prompted research on technologies suitable for burning this class of fuels. Among the others, fluidized bed combustion (FBC) has been indicated as one of the most promising ones [1-2], because of its fuel flexibility, high combustion efficiency and low environmental impact. However, a number of operational problems, mostly related to the fate of volatile matter (mixing/segregation, spatial burning profiles) [3] and of the ash components (fouling, slagging, bed agglomeration/defluidization) [4-6], call for deeper investigation on the combustion behavior of these fuels. In particular, the occurrence of bed agglomeration and defluidization has been often reported during operation of combustors fuelled with biomass, eventually leading to unscheduled boiler shutdown. Alkali, which are abundant in the ash of most biomass fuels, are responsible for the formation of melts in combination with the inert bed material. Despite a considerable research effort has been devoted to this subject [7-9], the mechanisms of ash-bed material interaction and of bed agglomeration are not as yet well understood. Several research works have demonstrated that the fluidized bed combustion of most biomass fuels takes place with extensive generation of carbon fines [10-12]. This is a consequence of the tendency of these fuels to yield highly porous or even incoherent chars after pyrolysis that are very susceptible to attrition along with combustion. Attrited char may experience, upon further burn-off, peak temperatures largely exceeding the bed temperature. Modifications of the ash constituents, like softening, melting or even vaporization, might occur even at nominal bed temperatures at which no such change in mineral matter would take place. The combination of attrition-induced generation of fines particles and combustion-induced overheating of the same char particles can be responsible for the formation of ash-layered bed material eventually leading to bed agglomeration and defluidization. The present study was directed to investigate the fluidized bed combustion of olive husk, a biomass residue of the olive oil production industry, common in the Mediterranean area. This fuel has shown a high propensity to give rise to unwanted bed agglomeration problems during combustion, as a consequence of the high potassium content of the ash. The experimental work aimed at evaluating the characteristic times of bed agglomeration during combustion and the influence of the main operating variables (temperature and excess air) on this 1

2 phenomenon. Temperature/pressure gradients along the bed height were also measured during the runs to monitor the effectiveness of bed mixing. In addition, a new diagnostic tool based on the measurement of the dynamic pressure signal inside the bed was tested for its capability to predict the bed agglomeration onset. Fig. 1 Experimental apparatus. 1) Thermocouple; 2) Temperature PID controller; 3) Preheater; 4) Thermocouple and pressure transducer; 5) Acquisition data unit; 6) Personal computer; 7) Gas analyzers; 8) Condenser; 9) Filter; 10) Cyclone; 11) Gas distributor; 12) Mass flow controller; 13) Ceramic heaters; 14) Windbox; 15) Fuel -air mixer; 16) Screw feeder; 17) Fuel hopper. EXPERIMENTAL Apparatus The experimental apparatus, sketched in Fig.1, consisted in a cylindrical fluidized bed, a set of pressure transducers, a set of thermocouples, a fuel feeding system, a gas analysis system and a data acquisition unit. The reactor was made by a stainless-steel tube with a inner diameter of m and a height of 2 m. The vessel was fitted with a low-pressure-drop distributor plate made of a set of steel mesh (mesh size about 50 µm). The windbox was packed with ceramic rings to act as gas preheater. The distributor and the windbox packing attained uniform fluidizing gas feeding into the fluidized bed. The vessel was equipped with five tubes flush to the column wall located at a distance z from the distributor plate equal to 0.045, 0.095, 0.145, 0.245, m. The tube located at z = m was used for fuel feeding, those located at z = 0.045, 0.145, m were fitted with a pressure tap and a thermocouple, while the tube located at z = m was fitted only with a thermocouple. The flue gas exiting the combustor was directed to a high efficiency cyclone for fine particles collection. After the cyclone the flue gas was sampled for gas analysis. A paramagnetic analyzer and three NDIR analyzers were used for on-line measurement of O 2, CO, CO 2 and CH 4 concentrations, respectively, in the exhaust gases. The combustor was electrically heated by means of ceramic mat heaters. The reactor temperature was controlled by a PID controller driven by the signal from the thermocouple inserted in the bed nearby the column wall by means of the tube located at z equal to m. The fluidizing gas was preheated to 500 C in an electrical heater driven by a PID controller. The fluidization column was equipped with an air-assisted solids metering/feeding system for 2

3 continuous injection of the fuel at the bottom of the bed. The feeding system consists of a fuel hopper mounted over a screw feeder that further delivers the powder in a mixing chamber where a swirled air flow pneumatically conveys the fuel within the bed. Fluidizing and fuel feeding air flows were metered with two high precision mass flow controllers. The column was equipped with three high-precision piezoresistive electronic pressure transducers, characterized by a high temporal resolution. These transducers were used to measure the gas pressure profile along the fluidized bed height. The acquisition data unit consisted of a personal computer equipped with a 16 bit A/D data acquisition board characterized by a high sample rate. The acquisition data unit allowed to measure temperature and pressure signals at a pre-set sampling frequency of 100 Hz. Materials Technical air was used both as primary fluidizing gas and to assist fuel feeding. Quartz sand, sieved in the size range µm, was used as bed inert material. The bed inventory was kept constant at 3.3 kg. The fuel used was olive husk, whose properties are reported in Tab.1. This fuel is characterized by a high potassium content in the ashes. The particle size of the fuel was in the range µm. Procedures Steady combustion tests were carried out at a constant fluidization velocity of 0.5 m/s. Bed temperature was fixed at either 850 C or 900 C. The combustor start up was accomplished by electrically heating the bed of inert sand. When the bed temperature reached a value of 750 C the fuel feeding was started. The fuel feed was adjusted in the range kg/h to reach the desired excess air value (in the range %). During the run temperature, pressure and gas concentration data were continuously logged in the PC. Every min elutriated material collected at the cyclone was measured and analyzed for carbon concentration, for calculation of the unburned carbon flow rate at the exhaust. The run ended when agglomeration of the bed occurred, as indicated by a jump in the temperature and pressure profiles within the bed. The total time interval from the beginning of the fuel feeding till the agglomeration onset was recorded. After the end of the run the bed was discharged from the combustor, weighed and sieved for agglomerates separation. Selected agglomerate samples were observed under a scanning electron microscope (SEM) and subjected to energy dispersive X-ray (EDX) elemental analysis. Particle density, g/cm LHV, kcal/kg 4173 Proximate analysis (dry basis), % w moisture volatiles f i x e d c a r b o n ash 4.43 Ultimate analysis (dry basis), % w c a r b o n h y d r o g e n 5.46 n i t r o g e n 1.25 s u l f u r 0.09 ash 5.09 oxygen (diff) Ash composition, % w CaO MgO 1.8 K 2 O Na 2 O 1.74 F e 2 O Al 2 O SiO P 2 O S O Tab. 1 Properties of olive husk. 3

4 Temperature, C H=45 mm H=145 mm H=245 mm Relative pressure, mm H 2 O H=45 mm H=145 mm H=245 mm Time, s Time, s Fig. 2 Temperature profiles in the bed. Fig. 3 Pressure profiles in the bed. T=900 C; e=56%. T=900 C; e=56%. RESULTS AND DISCUSSION Figure 2 reports typical profiles of the temperature measured at three different heights within the bed during a steady combustion run. The bed temperature was fairly constant during the run varying within ±10 C from the set point. It can be observed that the higher thermocouple (z = m) measured a temperature slightly lower than the other two. This is probably a consequence of heat dispersion from the bed surface to the colder freeboard. It is interesting to note that the other two thermocouples measured approximately the same temperature during the first period of the run. However, at a certain point (t 8500 s, for this run) the two temperatures diverged, the central thermocouple measuring a higher temperature. This indicates that bed mixing is less uniform in the second period of the run. Suddenly at t s (for this run) the bed agglomerated: the temperature measured by the lower thermocouple peaked down, while the other two peaked up. Figure 3 reports the average gas pressure profiles measured at the three different bed heights during the same run. All the pressures increased with time during the run. This is the consequence of accumulation of ash in the bed, being absent a drain flow. Also in this case the curves can be divided into two periods: at the same point as before (t 8500 s) the slope of the curves changed, probably indicating a faster accumulation of ashes in the bed in the second period. Upon agglomeration (t s) all the pressures peaked down because of the onset of bed channeling. All the combustion runs carried out with olive husk showed a similar qualitative behavior of temperatures and pressures. However, these variables could not be used for agglomeration prevention purposes being the quantitative changes different from run to run. A new quantity was therefore tested for its capability to predict agglomeration onset, i.e. as an early warning variable. In particular, the variance of the instantaneous pressure measurement data was used for this purpose during the runs. This quantity is defined as the mean value of the squared difference between the instantaneous pressure and the average pressure calculated within a definite time interval. This interval was fixed to 30 s, in order to have a real time indication of the variance. In separate blank test runs it was checked that this interval was large enough to have realistic and accurate values in the present conditions, by comparing with calculations made with time intervals up to 10 min. Figure 4 reports the pressure variance measured at the two upper bed heights during the same run. It is clearly seen that while in the first period of the run the variance was approximately constant, in the second period it steadily decreased until bed agglomeration. A 60% decrease of the variance was measured at the agglomeration onset. 4

5 Pressure variance, (mm H 2 0) H=145 mm H=245 mm Ash weight fraction, % C 900 C Time, s Excess air, % Fig. 4 Pressure variance profiles in the bed. Fig. 5 Weight fraction of ash in the bed T=900 C; e=56%. upon agglomeration. Figure 5 reports, as a function of the excess air value, the weight fraction of ashes in the bed at the end of each combustion run, calculated as the total ash inlet with the fuel feed minus the total elutriated ash and divided by the final bed weight (sand + ash). It is seen that, irrespectively from the excess air value, a well defined ash content was necessary to agglomerate the bed, only dependent on the bed temperature level. In particular, ~3% and ~2.3% ash contents were measured for the runs carried out at 850 C and 900 C, respectively. This result is in line with previously reported data that indicate an important effect of a bed temperature increase to enhance the agglomeration tendency of the bed. Figure 6 shows the measured agglomeration time for all the combustion runs, as a function of the excess air. It is clearly observed that faster agglomeration occurred with a higher temperature and with a lower excess air. This second effect is a consequence of the larger fuel feed rate when a lower excess air value is adopted. Figure 7 reports the pressure variance reduction upon agglomeration for all the combustion runs, as a function of the excess air. It is seen that a fairly constant value around 60% was measured for all the runs at both bed temperature values. This result seems to indicate that the pressure variance could be used with confidence to predict the onset of agglomeration. Further experiments with different fluidizing velocities and sand sizes, however, are needed to confirm the usefulness of this quantity. Figure 8 shows a typical agglomerate found in the bed after the end of the run. It clearly shows a hollow structure, indicating that a burning fuel particle was inside and initiated the agglomeration process. Many zones of the agglomerate appear to be fused and re-solidified. EDX analysis showed a significant potassium enrichment in the agglomerate, especially in the fused contact points between the sand particles. This confirms that the agglomerate is formed because the sand surface composition reach the silica-potassium eutectic point, leading to extensive melting. Agglomeration time, min C C Excess air, % Pressure variance reduction, % C C Excess air, % Fig. 6 Agglomeration time as a funct ion Fig. 7 Pressure variance reduction upon of excess air. agglomeration. 5

6 Fig. 8 SEM micrograph of a typical agglomerate. CONCLUSIONS The steady fluidized bed combustion of a biomass residue (olive husk) common in the Mediterranean area was investigated in a bench scale reactor. This fuel had a high propensity to give rise to bed agglomeration problems during combustion, as a consequence of the high potassium content of the ash. Bed agglomeration characteristic times were measured, together with temperature/pressure profiles within the bed at different operating conditions. Results showed that during the runs both temperature and pressure profiles changed because of decrease of mixing and ash accumulation in the bed. Agglomeration occurred when a critical ash content in the bed was reached depending on the bed temperature, but not on the excess air. A new diagnostic tool based on the measurement of the dynamic pressure signal inside the bed was tested for its capability to predict the bed agglomeration onset. The technique resulted fairly accurate under the present operating conditions, but further experiments with different fluidizing velocities and sand sizes are needed to confirm its usefulness. ACKNOWLEDGEMENTS The support of Mrs. C. Zucchini and Mr. S. Russo in SEM/EDX analysis is gratefully acknowledged. The authors are grateful to ENEL Produzione-PSI-Ricerca for providing olive husk samples. REFERENCES 1. Saxena, S.C., Jotshi, C.K.: P r o g E n e r g y C o m b u s t S c i, 20: 281 (1994). 2. Anthony, E.J.: Prog Energy Combust Sci, 21: 239 (1995). 3. Scala, F., Salatino, P.: C h e m E n g S c i, 57: 1175 (2002). 4. Natarajan, E., Ohman, M., Gabra, M., Nordin, A., Liliedahl, T., Rao, A.N.: Biomass Bioen e r g y, 15: 163 (1998). 5. Jenkins, B.M., Baxter, L.L., Miles Jr., T.R., Miles, T.R.: F u e l P r o c e s s T e c h, 54:17 (1998). 6. Skrifvars, B., Backman, R., Hupa, M., Sfiris, G., Abyhammar, T., Lyngfelt, A.: F u e l, 77:65 (1998). 7. Latva-Somppi, J., Kauppinen, E.I., Valmari, T., Ahonen, P., Gurav, A.S., Kodas, T.T., Johanson, B.: Fuel Process Tech, 54:79 (1998). 8. Skrifvars, B., Backman, R., Hupa, M.: Fuel Process Tech, 56:55 (1998). 9. Ohman, M., Nordin, A., Skrifvars, B., Backman, R., Hupa, M.: E n e r g y F u e l s, 14:169 (2000). 10. Salatino, P., Scala, F., Chirone, R.: Proc Combust Inst, 27:3103 (1998). 11. Scala, F., Salatino, P., Chirone, R.: E n e r g y F u e l s, 14:781 (2000). 12. Chirone, R., Salatino, P., Scala, F.: Proc Combust Inst, 28:2279 (2000). 6