Energy Fuels 2010, 24, 5432–5440 Published on Web 09/17/2010
: DOI:10.1021/ef100712e
Full-Scale Numerical Investigation of a Selective Noncatalytic Reduction (SNCR) System in a 100 MW Utility Boiler with Complex Chemistry and Decoupling Approach Yu Lv, Zhihua Wang,* Junhu Zhou, and Kefa Cen State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China Received June 8, 2010. Revised Manuscript Received September 2, 2010
To efficiently model the selective noncatalytic reduction (SNCR) process in a larger utility boiler, a decoupling numerical simulation approach, to separately treat coal combustion and SNCR NOx reduction in the furnace, was presented in this study. The simulated boiler has a full capacity of 100 MW, and the SNCR system is installed at the height of the furnace arch, mainly including groups of reagent nozzles. Urea solution was used as a reactive reagent, so that a relatively complex chemistry, along with the eddy dissipation concept (EDC) model, was introduced to accurately mimic the NOxOUT process in turbulent flow. Simulations are validated with experimental measurements. The reaction temperature, reagent amount, and reagent droplet momentum effects on the SNCR performance, primarily NOx removal and NH3 slip, were investigated in detail. The results show that, only at certain temperature regions, NOx removal gives a continuous rise with the increase of the reagent amount but commonly with a more serious NH3 slip; increasing reagent droplet momentum can be an available technique to enhance the poor global mixing between reagent droplets and flue gas in such a large furnace space. In addition, an empirical optimization of the simulated SNCR system was conducted, and potential methods to benefit SNCR system design and operation were demonstrated, such as multi-level nozzle arrangement and the application of flat atomizers.
boilers1-4 over the last 20 years. Some commercial codes, such as Fluent 6.3, have been developed fairly well. However, few CFD cases have been reported in the aspect of full-scale SNCR research because of its complexity. Although Shin et al.5 and Kim et al.6 have investigated the SNCR process in a spacelimited oil-fired boiler and a waste incinerator, respectively, the one-step kinetics used for NOx formation and destruction, fuel combustion, and SNCR are too simplified and the NOx chemical source in turbulence is empirically given without solid theoretical foundation, eventually undermining their instructiveness. Some full-scale cases to model the SNCR process in municipal incinerators have recently been reported by Nguyen et al.7 and Liang and Ma.8 Both CFD results show excellent agreement with on-site measurements. Additionally, it is also found by Nguyen et al.7 that the droplet size distribution has a significant effect on SNCR performance. However, owing to the complexity of boiler geometry and coal combustion, a numerical study on the SNCR application at a coal-fired larger utility boiler has not yet been recorded in the literature. In the present study, an attempt to investigate the SNCR system at a 100 MW coal-fired boiler has been taken. A novel decoupling approach is presented to model the SNCR system more efficiently and tested by comparing to experimental data. A relatively complex mechanism for SNCR has been incorporated into CFD code. The effects of temperature, normalized stoichiometric ratio (NSR), and droplet momentum on SNCR performance, including NO removal and NH3
1. Introduction In the last 3 decades, how to control NOx efficiently and economically has been one of the most recurrent problems that puzzle researchers in the field of thermal power engineering. Some techniques aiming at the optimization of initial combustion organization have arisen, for example, staged-air combustion or dense-thin separation combustion. However, considering the more severe regulation trend of NOx emission, the limited reduction provided by those techniques seems to be insufficient. Post-combustion NOx control systems are more widely used independently or as a supplementary, which include selective catalytic reduction (SCR) and selective noncatalytic reduction (SNCR). In comparison, SNCR technology currently takes more advantages because of its simplicity and low operation cost and has been considered to be more suitable for developing countries, such as China. Nevertheless, in reality, it is very difficult to study SNCR processes at large utility boilers directly through measurement because of the limited experimental access. Even though some parameters can be measured, large space and strong turbulence cause a very poor accuracy and probably make the essential characteristics distorted. A more accurate and economical way is to resort to the technique of computational fluid dynamics (CFD) modeling, which has gained its reputation of being an effective method in solving problems related to full-scale *To whom correspondence should be addressed. Telephone: þ86-57187952443-8027. Fax: þ86-571-87953162. E-mail:
[email protected]. (1) Backreedy, R. I.; Jones, J. M.; Ma, L.; Pourkashanian, M.; Williams, A.; Arenillas, A.; Arias, B.; Pis, J. J.; Rubiera, F. Fuel 2005, 84, 2196–2203. (2) Vuthaluru, R.; Vuthaluru, H. B. Fuel Process. Technol. 2006, 87, 633–639. (3) Pallares, J.; Arauzo, I.; Dı´ ez, L. I. Fuel 2005, 84, 2364–2371. (4) Senior, C. L.; Sarofim, A. F.; Zeng, T.; Helble, J. J.; MamaniPaco, R. Fuel Process. Technol. 2000, 63, 197–213. r 2010 American Chemical Society
(5) Shin, M.; Kim, H.; Jang, D. Appl. Therm. Eng. 2007, 27, 2850– 2857. (6) Kim, H.; Shin, M.; Jang, D.; Ohm, T. Appl. Therm. Eng. 2004, 24, 2117–2129. (7) Nguyen, T. D. B.; Kang, T.; Lim, Y.; Eom, W.; Kim, S.; Yoo, K. Chem. Eng. J. 2009, 152, 36–43. (8) Liang, Z.; Ma, X. Waste Manage. 2010, DOI: 10.1016/j.wasman. 2010.05.006.
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Table 1. Air and Coal Particles Flow Distribution air-coal distribution
total primary air
total secondary air
tertiary air
returning air
overfire air
mass flow rate (kg/s) temperature (K) coal feeding (kg/s)
18.70 363 9.45
46.79 618 0.0
15.30 333 0.68
9.32 363 3.37
28.39 618 0.0
Table 2. Coal Elemental and Industrious Analysis proximate analysis [%, as received (ar)] moisture ash content volatile matter fixed carbon heat value (kJ/kg)
14.2 10.87 29.47 45.46 23197
ultimate analysis (% ar) carbon hydrogen oxygen nitrogen total sulfur
62.69 3.41 10.17 0.83 0.58
with extra water to make the mass fraction of urea adjustable. The two layers of reagent nozzles are installed at 24.5 and 28.5 m height, respectively. At each layer, five injectors are equipped in each sidewall and two injectors in the front and rear walls. One valve is used to control the total flow of urea solution in each layer. The installed nozzles are all solid-conetype, with 60° atomizing angle. The droplet diameter is around 100 μm, measured using a LS-2000 laser particle size analyzer produced by Beckman Coulter, Inc., Brea, CA, and can also be slightly adjusted by changing the atomizing pressure. O2 and NO concentrations were obtained using an Ultramat23 gas analyzer with a precision of 1%, while NH3 slip, the unconsumed NH3 leakage exiting the SNCR system, was sampled according to the conditional test method (CTM027) of the Environment Protection Agency in the U.S.A.
Figure 1. Modeled furnace and SNCR system.
slip, have been numerically studied. Additionally, the nozzle arrangement and type in use were empirically optimized by the numerical technique, which shows a potential enhancement of the applied SNCR system. 2. Description of Modeling Objects The simulated furnace and SNCR equipment belong to a 100 MW utility tangentially fired pulverized-coal boiler.9 The economical continuous rate of this boiler is 410 tons/h steam with 540 °C and 9.81 MPa at full capacity. As demonstrated in Figure 1, the staged-air supply strategy is adopted in the arrangement of the burner region and the mass flow and temperature of the provided air through all air nozzles are summarized in Table 1. Coal particles are injected into the furnace from primary-air, tertiary-air, and reburning-air nozzles, with the detailed amounts listed in Table 1. Shenhua bituminous coal is used in operation, and its analysis data are listed in Table 2. The coal particles are assumed to obey the Rosin-Rammler distribution, with a mean diameter of 75 μm, consistent with experimental data. Along the upper horizontal flue gas pass, there are four groups of panel superheater (SH), which are division SH, primary SH, final SH 1, and final SH 2, installed in sequence. Their surface areas are set to be equal to individual design values to account for the effect of inertial resistances, and the temperatures are set to be 943, 773, 763, and 673 K, respectively, which correspond to the averaged values based on automatic online detection. The wall temperature of the furnace is first set to be 700 K and is then slightly adjusted to fit the total heat flux through the furnace wall. This strategy was widely used in similar modeling.10,11 The SNCR system comprises urea dissolving, urea storage, and layers of atomizing injectors installed in the furnace wall. After urea is dissolved, the urea solution can be further diluted
3. Decoupling Modeling Strategy The SNCR system is usually installed at the 800-1000 °C temperature region,12 which is near the furnace arch or exit at utility boilers. It is likely to need an unmanageable computational expense if we model coal combustion and the SNCR process as a whole because of the required numerous grids. Another incompatible problem will definitely come out that these two processes are totally in different reaction schemes and improperly described using the same model. Further, the operating condition for combustion is quite stable, so that, when the SNCR system is investigated at variable conditions, the extra computational expense will be consumed. Thus, it is urgent to decouple the SNCR system from the whole furnace when it is mainly focused. The decoupling approach comes from a simple idea that, by setting a split plane, the whole furnace can be divided into two parts, a lower furnace and an upper furnace. In the lower furnace, coal combustion is mainly concentrated, while the SNCR process is emphasized in the upper part. After the lower furnace is simulated, all information in the split plane will be inputted into the upper furnace simulation as a profile. However, the problem is whether this idea is applicable in physics. It is known that, as a post-combustion technique, SNCR has negligible influence on primary combustion. Mutually, combustion offers lots of combusting or ash particles that pass through SNCR system and cause influence. In essence, the particulate phase affects the flow field in terms of conservative equations by providing particle sources. To quantify this effect, a trial computation was first carried out
(9) Yang, W.; Zhou, Z.; Zhou, J.; Lv, H.; Liu, J.; Cen, K. Environ. Eng. Sci. 2009, 26, 311–317. (10) Fan, J.; Sun, P.; Zheng, Y.; Ma, Y.; Cen, K. Fuel 1999, 78, 1387– 1394. (11) Fan, J.; Qian, L.; Ma, Y.; Sun, P.; Cen, K. Chem. Eng. J. 2001, 81, 261–269.
(12) Wang, Z.; Lv, Y.; He, P.; Yang, W.; Zhou, J.; Cen, K. Proc. CSEE 2009, 29, 60–65 (in Chinese).
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Char combustion is calculated from the kinetics/diffusionlimited surface reaction model of Baum and Street.15 The P1 radiation model is used to account for radiation heat transfer in two parts of the furnace. For simplicity, the gas bulk in each cell is viewed as a gray body, with the absorption coefficient computed locally according to the weighted-sum-of-gray-gases model (WSGGM).16,17 All cases were run on the platform of Fluent. More detailed information about the used models can be found in the Fluent user manual.18 4.2. Chemical Model in the Lower Furnace. For the combusting bulk in the lower furnace, species mixing is much slower than chemistry; therefore, the mixed-is-burnt model, assuming infinite fast chemistry, is adequate to predict the homogeneous combustion. The instantaneous mixture fraction is used to represent the instantaneous mass fractions. The mean mass fractions of fuel, oxidant, and products are deduced from the mean and variance of the mixture fraction assuming the β probability density function (β-PDF). Because of the negligible impact on combustion, NOx formation, controlled by low-speed chemistry, is evaluated in the post-processing phase. Thermal NO is predicted using the extended Zeldovitch mechanism with the following equations:19,20
Figure 2. Reburning coal particle source distribution along with height.
and then mass, momentum, and enthalpy sources provided by particles of returning nozzles are distributed along the height, as shown in Figure 2. It is adequately far downstream from the burner region, if the split plane is chosen to be the 24 m height horizontal surface. Above this plane, the particle sources are all less than 3% of the corresponding total, quite negligible. Therefore, on the basis of the above analysis, the following assumptions are safely imposed to enable the decoupling approach: (1) The upper furnace has a negligible effect on the temperature and flow fields of the lower furnace; therefore, the iterative calculation between the separated two parts is not necessary. (2) Ash particles that entrance the upper furnace in practice do not influence the SNCR process. Thus, those particles in the modeling of the upper furnace are given no consideration. With regard to this modeling strategy, the meshes of the two parts should be separately treated. For the lower furnace modeling, the general size of computational grids is empirically set to be 100 mm, according to previous studies,10,11 and then the lower domain is discretized with nearly 650 000 structured hexahedral grids. For the upper furnace, unstructured computational grids are used because of the complex geometry. To test the effect of the grid size on SNCR simulations, two cases with different grid numbers, 830 000 and 1 140 000, were initially run before the formal numerical studies. Consequently, it was found that there were no significant disparities between two cases in terms of flow fields, temperature profiles, and species distributions. Thus, the case with fewer grids was employed to improve computation efficiency without losing accuracy.
O þ N2 hNO þ N
ð1Þ
N þ O2 hNO þ O
ð2Þ
N þ OHhNO þ H
ð3Þ
in which the O, OH, and H concentrations are calculated from partial equilibrium assumption. Fuel NO stems from two parts, volatile N released during the volatile devolatilization and char N oxidized during char combustion. In the present work, volatile N is assumed to form HCN or NH3 at first and then reduced to N2 by NO or oxidized to NO by O2, while char N is believed to be directly converted to NO, as a result of desorption of oxidized char nitrogen atoms.21 Furthermore, prompt NO is neglected because it is significant only in very fuel-rich conditions and accounts for a quite small portion of the total NO formed in this furnace. 4.3. Chemical Model in the Upper Furnace. After urea is released from aqueous droplets, it first decomposes to NH3 and HNCO before reacting with NO. These two products both reduce NO through a complex chemical path; therefore, a detailed SNCR kinetics with 173 steps and 31 species, initially proposed by Rota et al.,22 is necessarily used to predict the SNCR process. However, the mechanism of Rota et al. encloses all possible SNCR reducing paths related to multiple reagents, which makes computation unmanageable. Because one more species involved means one more controlling equation that should be solved, to adopt this mechanism more efficiently, a reduced one with only 12 steps and 16 species is accordingly developed by Lv et al.23 and finally integrated to CFD modeling. Because of the unconventional representation of the reduced mechanism, the Fluent user-defined function (UDF) interface is necessarily employed. The reduced mechanism was obtained on
4. Model Introductions 4.1. Overall Models. The SIMPLE method is used to solve the time-averaged conservation equations for mass, momentum, enthalpy, and species. A standard k-ε model13 is employed as closure of turbulent Reynolds equations. Coal particles and urea solution droplets are traced using the Lagrangian method and stochastic tracking model with the consideration of the influence of turbulent fluctuations on particulate trajectories. Devolatilization is modeled using the single-step model proposed by Badzioch and Hawskley,14 which assumes that the rate of production of volatile species is described by a first-order reaction and the rate constant is expressed in an Arrhenius form.
(15) Baum, M.; Street, P. J. Combust. Sci. Technol. 1971, 3, 231–243. (16) Raithby, G.; Chui, E. J. Heat Transfer 1990, 112, 415–423. (17) Chui, E.; Raithby, G. Numer. Heat Transfer, Part B 1993, 23, 269–288. (18) Fluent, Inc. FLUENT 6.3 User’s Guide; Fluent, Inc.: Lebanon, NH, 2006. (19) Flower, W. L.; Hanson, R. K.; Kruger, C. H. Proc. Combust. Inst. 1974, 15, 823–832. (20) Monat, J. P.; Hanso, R. K.; Kruger, C. H. Proc. Combust. Inst. 1978, 17, 543–552. (21) Lockwood, F. C.; Romo-Millanes, C. A. J. Inst. Energy 1992, 65, 144–152. F.; Morbidelli, M. Chem. Eng. (22) Rota, R.; Antos, D.; Zanoelo, E. Sci. 2002, 57, 27–38. (23) Lv, Y.; Wang, Z.; Zhou, J.; Cen, K. Energy Fuels 2009, 23, 3605– 3611.
(13) Launder, B. E.; Spalding, D. B. Lectures in Mathematical Models of Turbulence; Academic Press: London, U.K., 1972. (14) Badzioch, S.; Hawsksley, P. G. W. Ind. Eng. Chem. Process Des. Dev. 1970, 9, 521–530.
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Table 3. Simulation Results Validation simulation prediction
experimental measurement
2.5 207
2.4 201
1285 197 82.3
1237 189 88.4
1826 1652 1593 1453 1403 1370
1796 1683 1556 1452 1392 1354
O2 concentration at the furnace exit (%) NO concentration at the furnace exit (ppm, dry) temperature at the furnace exit (K) wall heat flux (MW) total heat flux through SHs (MW) central temperature at 13 m height cross-section (K) at 17 m height cross-section (K) at 20 m height cross-section (K) at 24 m height cross-section (K) at 26 m height cross-section (K) at 28.5 m height cross-section (K)
Figure 3. Comparisons of the temperature (lines) and NO concentration (points) at the combustion region between prediction and measurement.
the basis of sensitivity analysis and quasi-stable-state assumption and was strictly tested in various operating conditions. Further, the detailed kinetics can be found in the appendix of the paper by Lv et al.,23 and the species gradients at the wall boundary are set to 0 in the UDF. The interaction between the chemical process and turbulence is handled through the eddy dissipation concept (EDC) model.24 It is assumed that reaction occurs in small turbulent structures with fine scales. The lengthen fraction and characteristic duration of these fine scales is modeled as25 0:25 υε ξ ¼ Cξ 2 ð4Þ k τ ¼ Cτ
0:5 υ ε
ports located around walls. A gas-extracting thermocouple with a water-cooling system is horizontally put into the furnace at a 2 m distance from the wall at each detection port. As summarized in the figure, prediction also shows a good agreement with measurement. Figure 4 shows the scalar profiles in the blank case. It is obvious that the NO distribution has an intimate relationship with flame shape and oxygen profile. A higher NO concentration is normally found at the locations with a higher temperature and oxygen concentration. Because of the staged-air supply, over-fire air (OFA) is provided in the relatively lower temperature region, avoiding further NO formation. The characteristics of the temperature profile, species field, and NO emissions presented here are qualitatively consistent with the previous research,10,11,26,27 which substantiates validity and reliability of the models used in the simulations. 5.2. Cases with SNCR Operation. We tend to study the critical factors that influence the overall performance of the SNCR system in this modeled boiler and find an efficient way to improve it. Thus, four cases are designed to investigate temperature, NSR (reagent amount), and droplet momentum effects on the SNCR performance. Cases 1 and 2 aim to test the SNCR system response when it runs at different temperature regions and NSRs. Case 3 is used to take insight into the droplet momentum effect on the SNCR performance by changing droplet mass flow, with the control of case 4, which tends to adjust droplet size. With the convenience of decoupling simulation, all cases listed in Table 4 are run only in the upper part of the modeled boiler. 5.2.1. Operations at Different Temperature Regions. Figure 5 shows the NO and NH3 distributions when the SNCR system runs at different temperature regions. When urea solution droplets are injected at the 28.5 m level (case 1), it is evident that NH3 is carried nearer the furnace center, where the NO concentration is much higher, which causes a higher NO removal. Meanwhile, in the horizontal gas pass, the SNCR process in this case transfers into a diffusion mode. NH3 consumption becomes quite slow, and local high NH3 slip is observed at the exit. When urea solution droplets are injected at the 24.5 m level (case 2), released NH3 tends to be fast exhausted in exposure to high temperature and extra oxygen, undermining NO reduction. In this case, there is no problem related to NH3 slip. In both cases, the tangential momentum residual of the flue gas stream has an obvious
ð5Þ
where Cξ is the volume fraction constant, equal to 2.1377, Cτ is a time scale constant, equal to 0.4082, υ denotes kinematics viscosity, and k and ε are the turbulent kinetic energy and turbulent kinetic energy dissipation rate, respectively, which are evaluated in the turbulence model. Then, as for each cell, the species variations over time τ* at the fine-scale portion ξ* of the whole volume are added to the corresponding conservation equations as the chemical sources.
5. Results and Discussion 5.1. Blank Case and Modeling Validation. The simulation results are compared to the experimental data in aspects of heat flux, section temperature level, and species concentrations at the furnace exit, as summarized in Table 3. The temperature levels at different cross-sections are demonstrated using the central temperatures detected at the corresponding cross-sections. It is shown that the deviations between the predicted temperatures and the measured temperatures are all controlled within 4%, representing a better accuracy compared to previous studies.10,11 Meanwhile, good agreement between simulation and experiment is observed in terms of O2 and NO concentrations at the boiler exit. The difference between the predicted value and the measured value is less than 5%. In summary, the good consistency shown in the above comparisons forms a sound basis for SNCR prediction and further investigation. Figure 3 shows a quantified comparison between simulation and experiment, which focuses on the combustion region. At this region, detection is conducted through 12 (24) Magnussen, B. F. On the structure of turbulence and a generalized eddy dissipation concept for chemical reaction in turbulence flow. Proceedings of the 19th American Institute of Aeronautics and Astronautics (AIAA) Meeting; St. Louis, MO, 1981. (25) Gran, I. R.; Magnussen, B. F. Combust. Sci. Technol. 1996, 119, 191.
(26) Dı´ ez, L.; Cortes, C.; Pallares, J. Fuel 2007, 87, 1259–1269. (27) Choi, C. R.; Kim, C. N. Fuel 2009, 88, 1720–1731.
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Figure 4. Scalar profiles of the blank simulation case without SNCR: (a) temperature, (b) O2 mole fraction, and (c) NO mole fraction.
Figure 5. Scalar profiles: (a) NO mole fraction and (b) NH3 mole fraction in case 1 with NSR = 1.4 and (c) NO mole fraction and (d) NH3 mole fraction in case 2 with NSR=1.4.
tangential momentum also forms a block for droplet penetration and reagent diffusion, which produces some NH3 pools at the marginal region downstream. 5.2.2. Temperature and NSR Effects. Figure 6 shows surfaceaveraged NO and NH3 concentrations along with flue gas pass at various NSR conditions. It is clear that NH 3 is consumed much faster in case 2 than in case 1 because of the increase of the reaction temperature. However, as NSR rises from 1.4 to 2 in case 2, the NO mole fraction does not give a drop but shows a significant increase. The reason seems that the produced NO amount from NH3 oxidization has surpassed the reduced amount at that condition. In contrast, the NO mole fraction in case 1 experiences a continuous decrease with the increase of NSR, which proves that its temperature
Table 4. Cases Designed To Study SNCR Operation case number
injector layer (m)
droplet size (μm)
total mass flow (m3/h)
NSR
1 2 3 4
28.5 24.5 28.5 28.5
100 100 158 50-250
1.6 1.6 1.1-2.0 1.6
1.0-2.2 1.0-2.0 1.3 1.2
influence on the SNCR performance. When flue gas passes through the horizontal pass, the gas temperature on the right side is significantly higher than that on the left, as seen in Figure 4a. This leads to a faster NH3 consumption on the right, and a more serious NH3 remnant appears on the left side of the exit, as well-shown in Figure 5b. Further, the 5436
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Figure 6. Surface-averaged NO and NH3 mole fractions along the flue gas pass: (a) case 1 and (b) case 2.
disperse by the central gas stream; therefore, in this section, we tend to see whether droplet momentum variation can lead to an improvement of the SNCR performance. There are two ways to adjust the droplet momentum in Fluent, by changing the total mass flow rate and the droplet size, which are separately studied in cases 3 and 4. Figure 8 shows the relationships between the SNCR performance and these two methods. Globally, with the increase of droplet momentum, both methods offer better SNCR performance, reduction of NH3 slip, and increase of NO removal. However, after the droplet size rises to a certain value, the NO removal curve begins to go down, as shown in Figure 8b, corresponding to case 4. To find the controlling mechanism behind the above phenomena, droplet spatial distributions, two-phase mixings, and droplet local thermal states are investigated at different conditions. Figure 9 shows the areas covered by droplets with different sizes, well-indicating the effect of the droplet size on droplet spatial distribution in the SNCR system. The covered area is obviously enlarged along with the increase of the droplet size, and it means droplets are more homogeneously mixed with flue gas at global scale. However, the SNCR performance also relies on micro-scale mixing.28 Here, effective micro-scale mixing between reagent droplets and flue gas is quantified using the surface area of reactive droplets per volume N P SiP i¼1 ð6Þ S ¼ V
Figure 7. NO removal and NH3 slip vary with the NSR value.
level is more favorable for NO removal. The primary problem involved in case 1 is the NH3 slip, much more serious than that in case 2. From Figure 6, we can also see that the SNCR process has become very slight at the horizontal gas pass, where the temperature is relatively low. Therefore, the best reaction zone in this boiler furnace is at the vertical region above 28.5 m; thus, we should focus on this region when attempting to optimize the SNCR system. Figure 7 gives a summary for NO removal and NH3 slip in the above two cases. The predicted NO removal generally follows the measured NO removal. After NSR reaches the value of 1.4, NO removal grows more slowly in case 1 while directly showing a sharp decrease in case 2. Another characteristic worthy notice is that, even in case 1, considered more favorable for the SNCR process, the increase of NO removal with NSR is far less than a linear relationship. As for NH3 slip in case 1, a significant increase appears with the increase of NSR. This stems from the fact that, at the later stage of SNCR, diffusion controls species transportation in this case, as analyzed in section 5.2.1, so that increasing the reagent will definitely increase NH3 slip because of the limited residence time and very long reaction time. However, in case 2, the high reaction temperature largely reduces the reaction time and consumes reagent very quickly. Thus, it is noticed that the NH3 slip out of the SNCR system is quite negligible at all tested NSR conditions. 5.2.3. Droplet Momentum Effects. On the basis of the above analysis, the reaction region in case 1 is more adaptable for NO removal and droplets are largely blocked to
where V is the grid volume and SPi is the surface area of the ith particle at the evaluated grid, with the unit of S being cm2/m3. This parameter is only applicable on grids with the local temperature larger than 1073 K, where SNCR has started working. Then, droplet-covered grids in each operation are all investigated, and the distributions of S values in those grids are summarized in Figure 10. Figure 10 indicates that, as the droplet diameter increases, first effective mixing is greatly enhanced because of the improvement of the droplet local temperature and amounts of droplets joining in SNCR and then begins to plummet, which follows the well-known mixing principle. As known, a larger S value indicates a larger local reagent source and faster mixing between volatilized reagent and local flue gas and is also usually combined with a relatively higher reaction (28) Østberg, M.; Dam-Johansen, K.; Johnsson, J. E. Chem. Eng. Sci. 1997, 52, 2511–2525.
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Figure 8. NO removal and NH3 slip vary with the (a) droplet mass flow and (b) droplet diameter.
Figure 9. Top views of the covered areas by droplets with a diameter value of (a) 50 μm, (b) 158 μm, and (c) 250 μm.
Figure 10. Effective mixing parameter S and droplet local temperature distributions when droplets with different sizes are employed: (a) 50 μm, (b) 158 μm, and (c) 250 μm.
removal gives an increasing tendency in Figure 8a. Nevertheless, because the momentum of each droplet does not change, the droplet spatial distribution does not change as well as the droplet local thermal states. Thus, when the reaction becomes more complete in the droplet-covered volume with better micro-scale mixing, the effect on NO removal becomes less obvious. This mechanism is wellverified in Figure 8a, in which NO reduction tends to finally approach a limit with the increase of total injecting mass flow. 5.3. SNCR System Optimization. According to the above results and discussion, the droplet cover area is very limited on the basis of this nozzle arrangement. Thus, we are quite curious about whether an optimized arrangement of nozzles
temperature. Accordingly, when the droplet size rises from 50 to 158 μm, enhanced effective mixing between reagents and flue gas, combined with better droplet spatial distribution, leads to a better global performance. However, when the droplet size finally reaches 250 μm, effective mixing becomes significantly small, as shown in Figure 10c, which eventually makes the reaction between volatilizing reagents and NO not adequately quick. Also, in light of the too hot atmosphere around droplets in the specific spatial distribution (Figure 9c), it is a reasonable consequence that a slight decrease of NO removal appears. As the total mass flow increases, the number of reagent droplets rises up accordingly and then the effective mixing between urea and NOx is largely improved, so that NO 5438
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can largely improve the SNCR performance. Consequently, we tend to empirically optimize the nozzle arrangement according to the flow and temperature characteristics of the simulated furnace. The number of used nozzles is kept the same with the above work. Figure 11 shows the covered volume of temperature 1173-1373 K, considered to be the most effective range for the SNCR process. Thus, injected droplets are expected to cover this volume to enhance global mixing, finally leading to high NOx reduction and low NH3 slip. The volume shape enlightens us to design a multi-level arrangement for nozzles, so that 14 nozzles are divided into two groups, 8 nozzles at 25 m for surrounding NOx and 6 nozzles at 30 m to reduce central NOx. The 8 nozzles at 25 m plane are arranged in a central symmetric way, while the 6 nozzles at 30 m elevation are installed based on the distorted
temperature profile. Such arrangement is made according to critical judgment and experience. Different from the above simulation, here, we assume that the nozzle outlet can be located closer to the furnace center without regarding the availability of nozzle material. The inside nozzle length is 1 m for the low nozzle group and 1.5-2 m for the high nozzle group. Considering the system simplicity, the injection conditions for all nozzles are kept consistent. Three cases were run as listed in Table 5. As given in Table 5, the NO removals of optimized cases 1 and 2 are 62.7 and 78.1%, respectively, much larger than the corresponding values in non-optimal cases with the same NSR. Furthermore, we need to not pay much concern for the NH3 slip because it is low enough. Another potential advantage of using an optimized multi-level nozzle system is that NO removal increases at a much quicker speed with the increase of NSR compared to the prediction and measurement in case 2. Optimized case 3 aims to test whether a proper modification to the nozzle form can lead to an improvement of the SNCR performance. An increasing atomizing angle is expected to enlarge the covered area at a horizontal direction of every single nozzle; meanwhile, a flat shape guarantees a more centralized droplet stream at the horizontal plane, so that global mixing can be enhanced without sacrifice of micro-mixing according to the above discussion. Consequently, this modification turns out to be a farewell effect, resulting in a 8% increase of NO removal and a slight fall of NH3 slip. Figure 12 shows NO and NH3 profiles in the simulation result of optimized case 3. After optimization, this SNCR system nearly reduces NO completely, with negligible NH3 slip just in the flue gas steering region. Although there are some spots with high NH3 concentrations, they appear in the higher temperature region and give no damage to heating surfaces. 6. Conclusions Modeling of a SNCR system in a 100 MW coal-fired utility boiler is carried out using CFD commercial solver Fluent. An initially developed reduced mechanism of NOxOUT is integrated into CFD code to account for complex chemical paths
Figure 11. Covered volume by the most favorable temperature for SNCR. The transparent deep-green iso-surface corresponds to 1173 K. The deep-red iso-surface corresponds to 1373 K.
Figure 12. NO and NH3 profiles in optimized case 3: (a) NO mole fraction and (b) NH3 mole fraction. Table 5. Simulation Conditions and Results of the Optimized Cases optimized case
nozzle geometry (atomizing angle)
NSR
total flow rate (m3/h)
droplet diameter (μm)
NO reduction (%)
NH3 slip (ppm)
1 2 3
solid cone (60°) solid cone (60°) flat (120°)
1.2 1.6 1.6
1.68 1.68 1.68
158 158 158
62.7 78.1 86.3
14 23 20
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Energy Fuels 2010, 24, 5432–5440
: DOI:10.1021/ef100712e
Lv et al.
involved. To lead to a computation economic and efficient investigation, a decoupling simulation strategy is adopted. Overall, the model results showed good agreement with experimental data, which provides a solid validation for the modeling strategy, assumptions, and sub-models applicability. The temperature level, NSR, and momentum effects on SNCR system operation are the main focus. Some important conclusions are summarized as follows: (1) The vertical furnace above 28.5 m height, combined with the flue gas steering chamber, is the most favorable region for the SNCR process, where the temperature level can lead to a continuous improvement of NO removal as NSR increases. However, NSR should be controlled within a certain limit, if NH 3 slip is taken into consideration. (2) Increasing droplet size can improve the SNCR performance because of the better mixing and stronger reactivity. However, when the droplet size is too large, poor micro-mixing between
the reagent and flue gas may undermine NO removal. (3) Increasing total mass flow of injected droplets can also result in better SNCR performance by improving micro-mixing. (4) Optimization of nozzle arrangement and nozzle features in the SNCR system, according to the obtained insights, can be the potential techniques to improve the overall performance. The systematical method presented here would be useful for other similar studies. Furthermore, the obtained results would prove to be of practical value to benefit the design, transformation, and optimization of this type of SNCR system. Acknowledgment. The authors thank Prof. Yang for providing experimental data for modeling validation and express sincere gratitude to the National Natural Science Foundation of China (50806066) and the National Science Foundation for Distinguished Young Scholar (50525620) for financial support.
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