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Numerical modelling of a straw-fired grate boiler
Fuel 83 (2004) 1183–1190 www.fuelfirst.com
Numerical modelling of a straw-fired grate boiler Søren K. Kær* Institute of Energy Technology, Aalborg University, Pontoppidanstræde 101, DK-9220 Aalborg Ø, Denmark Received 24 July 2003; revised 8 December 2003; accepted 9 December 2003; available online 4 January 2004
Abstract The paper presents a computational fluid dynamics (CFD) analysis of a 33 MW straw-fired grate boiler. Combustion on the grate plays a key-role in the analysis of these boilers and in this work a stand-alone code was used to provide inlet conditions for the CFD analysis. Model predictions were compared with available gas temperature and species concentration measurements showing good agreement. Combustion of biomass in grate-based boilers is often associated with high emission levels and relatively high amounts of unburnt carbon in the fly ash. Based on the CFD analysis, it is suggested that poor mixing in the furnace is a key issue leading to these problems. q 2004 Elsevier Ltd. All rights reserved. Keywords: Grate-fired boilers; Biomass; Computational fluid dynamics; Mixing problems
1. Introduction In Denmark, as well as internationally, boiler manufacturers are set increasing demands for fuel-flexible and efficient boilers. Still more advanced design tools are needed to meet these demands and to this end the use of computational fluid dynamics (CFD) has increased. The usefulness of CFD in the design and trouble-shooting of pulverized coal fired boilers of a wide range of types and designs is fairly well established (see, for example, Ref. [1]). The analysis of grate-fired boilers, however, adds new challenges to the models available in most commercial CFD packages. A central issue is the modelling of the processes in the fuel layer as it burns on the grate. In straw-fired boilers, the fuel layer is relatively thick (about 0.5– 1.0 m initially) and the combustion process cannot be modelled by traditional CFD codes without extensive user modifications. In this paper, a stand-alone in-house code was used to generate boundary conditions for the CFD analysis of the freeboard following the same concept as in Refs. [2 – 5]. Out of these studies, straw combustion was only dealt with in Ref. [5]. There is very limited information in the literature about previous studies addressing CFD-based modelling of straw-fired boilers. The combination of a stand-alone bed model and a CFD code was, however, applied previously in the analysis of grate-fired boilers burning coal [6], waste * Tel.: þ45-9635-9263; fax: þ45-9815-1411. E-mail address: [email protected] (S.K. Kær). 0016-2361/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.fuel.2003.12.003
[6,7] and woody biofuels [2,8,9]. This paper investigates the two-step approach by comparison to full-scale measurements and provides insight into the processes controlling the combustion characteristics of grate-fired boilers.
2. Method 2.1. The numerical model The CFD prediction was carried out using CFX [10]. The fundamental principles of CFD are well documented and will not be discussed further. The computational domain was discretized using a structured mesh resolving the individual air injection nozzles. In the particular boiler modelled there are a total of 395 air nozzles that have a significant influence on the flow and combustion patterns. The grid used in this study comprised a total of about 600,000 cells. The platen secondary and tertiary super heaters in the first and second passes were modelled as slabs and the primary super heater tube banks in the third pass were accounted for using source terms in the momentum and energy equations to simulate heat transfer and pressure drop. The steady-state governing equations were solved using the SIMPLE algorithm and the effect of turbulence on the mean flow field was accounted for using the RNG k– 1 model. Radiative heat transfer was modelled using the discrete transfer model [10]. In grate-fired boilers, the dominant thermo-chemical fuel conversion takes place on the grate. A typical example of
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Fig. 1. Schematic of the fuel bed discretization used in the numerical model. Large arrows indicate overall flow direction.
a grate-fired boiler including the fuel layer modelled is given in Fig. 1. The discretization of the bed employed in the numerical model is also indicated. Conceptually, the bed model considers the fuel layer as a number of threedimensional volumes. Each of these volumes is divided into horizontal slabs. Gas and fuel properties are represented at a discrete node point located at the centre of each slab [11]. The heat released by heterogeneous combustion of entrained particles is insignificant and only gas combustion was considered in the CFD prediction. The bed model accounted for char oxidation. Gas combustion in the freeboard was modelled using the Eddy-Break-Up model and a two-step reaction mechanism with CO as the intermediate species. y Cx Hy Oz þ ði1 þ i2 ÞO2 ! xCO þ H2 O þ i2 O2 2 y ! xCO2 þ H2 O; 2 x y z x i2 ¼ i1 ¼ þ 2 ; 2 4 2 2 ð1Þ
2.2. The full-scale straw-fired boiler The combined heat and power plant at Masnedø in Denmark was commissioned in 1995 and supplies about 20 MJ/s of district heating to the local town, Vordingborg. The plant burns approximately 8.1 tons/h of straw or a mix of straw and wood chips corresponding to a total fired
Table 1 List of gas analysers used for the measurements [13] Gas
Analyser
O2 CO CO2 C x Hy NO SO2
H&B, Magnos 3 and 6G H&B, Uras 3G H&B, Uras 4 Signal, 3000 HM (FID) H&B, Radas 1G FR, NGA 2000
H and B, Hartmann and Braun; FR, Fisher Rosemount; FID, Flame Ionization Detector.
Fig. 2. Location of the measurement ports used for gas temperature and species concentration measurements.
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Fig. 3. Schematic illustration of the lower section of a grate-fired boiler giving the operating conditions used in the simulations.
thermal rating of 33 MW and an electricity production of 8 MW. The boiler operates at an overall stoichiometric air to fuel excess ratio of about 1.3 corresponding to an oxygen concentration in the stack of just below 5 vol%. Several measurement programs were undertaken at Masnedø collecting experimental data on gas phase species concentrations, temperatures and ash deposits to determine combustion conditions [12,13] and deposit formation [14]. Measurements were always made after at least one full day of continuous operation on the same fuel. Pure straw firing and co-combustion with wood chips, olive pits and sheanuts (80% straw and 20% alternative fuel on a thermal basis) was investigated. In this context, only the pure straw runs were used. Temperature measurements were made with a suction pyrometer from the International Flame Research Foundation [13]. Combustion gases were extracted with a watercooled probe and run through particle filters and a cooling bath, where water was removed from the gas [13]. The concentrations of O2, CO2, CO, Cx Hy ; NO and SO2 were measured using the analysers listed in Table 1. Gas species concentrations and temperatures were measured at the locations shown in Fig. 2. The fuel and gas temperatures and flow rates used are summarized in Fig. 3. An overall straw bed density of 60 kg/m3 was used which is representative for the straw as it enters the furnace. The straw proximate and ultimate analyses used in the predictions are given in Table 2. The heat transfer surface temperatures were estimated from the process diagram of the boiler that operates at a pressure of 90 bars and a superheated steam outlet temperature of 520 8C. Fig. 4 summarizes the temperatures used. The saturation temperature of approximately
300 8C was used for the water walls. The primary super heater was divided into five sub-sections each representing a tube bank and the steam temperature was estimated in each section. A constant emissivity of 0.7 was used for all heating surfaces.
3. Results and discussion 3.1. Bed combustion results and CFD boundary conditions Fig. 5, showing the predicted mass fraction of char in the bed, illustrates the overall conversion process of the fuel bed. Only the first 5 m is shown as char burnout is almost complete at that point. The strong increase in char mass fraction close to the fuel feeding port indicates the onset of devolatilization. The process is initiated by flame radiation heating and moves from the top and downwards. The devolatilization front reaches the grate at a distance of about 1.5 m from the fuel feeding port. At that point, the char oxidation front starts moving from the bottom up. Compared to Table 2 The ultimate and proximate analyses used in the predictions Ultimate analysis
wt%
Proximate analysis
wt%
Carbon Hydrogen Oxygen Nitrogen Sulphur
44 5.9 49.5 0.7 0.15
Moisture Ash Fixed carbon Volatiles LHV as received
14 4.5 12 69.5 14.9 MJ/kg
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Fig. 4. Schematic showing the heat transfer surface temperatures used in the CFD analysis.
the devolatilization front, the char oxidation front is much wider due to oxygen diffusion being the limiting reaction process. The gas species mass fractions at the top of the bed used as inlet conditions for the CFD analysis are presented in Fig. 6. A large amount of volatiles leave the devolatilization zone of the bed unburnt due to highly sub-stoichiometric conditions. At positions further than 3 m, most of the char has burnt and the mass fraction of oxygen starts to increase while the mass fractions of the reaction products decrease. The gas phase temperature and velocity profiles at the top of the bed are shown in
Fig. 7. The gas temperature decreases from 800 8C in the initial stage of volatiles combustion to about 600 8C in the later. This is due to an acceleration of the devolatilization front that reduces the stoichiometry, i.e. the steeper the devolatilization front the less of the under-grate air is available. The acceleration can be identified from Fig. 5 as an increasingly steeper devolatilization front. In the char combustion region, the gas temperature increases almost linearly with the position on the grate. It peaks at a maximum of 1000 8C when the reaction front reaches the top of the bed at a position about 4 m from the fuel feeding port (Fig. 5).
Fig. 5. Two-dimensional illustration of the fuel bed char content. Only the first 5 m of the grate is included, as char burnout has almost completed at that point.
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Fig. 6. Chemical composition of the gas leaving the top of the fuel layer. These profiles were used as boundary conditions for the CFD analysis of the freeboard.
3.2. Qualitative gas phase properties The velocity field and the combustion reaction pattern is governed by the locations of air injection nozzles, which represent an important means of controlling the combustion process. The gas phase properties all show a complex threedimensional variation that is difficult to illustrate in detail graphically. Fig. 8 shows the total reaction rate in a crosssection of the lower part of the furnace. The velocity field is illustrated in terms of superimposed velocity vectors. A general feature of the reaction pattern is the existence of very fast rates (dark colours) in the regions of air injection nozzles. The air jets provide favourable reaction conditions in terms of oxygen and high turbulence levels ensuring good mixing of the oxidant with volatiles and carbon monoxide. The fastest reaction rates are found around the ignition air nozzles (see Fig. 3). The location and design of these nozzles are essential parameters in controlling the combustion process in the furnace. The heat released by the fast reaction rates provides heat to the fuel layer below and initiates the drying and devolatilization processes. Consequently, these nozzles control and maintain the location of the reaction front in the fuel layer at a fixed position. This is important in order to obtain an acceptable degree of fuel burnout. The secondary air nozzles, at the level of the nose, provide the oxygen needed to complete burnout of volatiles and carbon monoxide. This can be identified from the region of fast reaction rates in the upper part of Fig. 8. A region of
Fig. 7. Velocity and temperature profiles at the top of the fuel layer. These profiles were used in the CFD analysis of the freeboard.
Fig. 8. Reaction rates and velocity vectors in the lower part of the furnace. Dark areas indicate fast reaction rates. Note that reactions are most intense near the air injection nozzles.
relatively high reaction rates is also found just above the main grate approximately half-way down. In this region of the bed, both carbon monoxide and oxygen are released (see Fig. 6) and a reaction occurs in the gas phase. 3.3. Heat transfer rates Fig. 9 shows the heat flux to the furnace water walls (the unit is W/m 2). As the heat flux is away from the computational domain, it is defined as being negative. The maximum value of the colour scale does not represent the maximum local value of the heat flux, which is approximately 2 200,000 W/m2. High heat fluxes are mainly found in the regions of fast reaction rates close to the air injection nozzles. High heat release rates and gas temperatures also characterize these regions. In particular, there is a large region of high heat fluxes around the secondary air nozzles and further up along the front and sidewalls. The overall heat transfer rates to the steam circuit are compared to operational data from the boiler in Table 3. There is a reasonable degree of correspondence with the operational data as a deviation of about 10– 15% is found at all locations except for the secondary super heater, where the predicted rate exceeds the operational data by more than 100%. The main reason is believed to be that the surface temperature is too low at this super heater. The surface temperature of the relatively thick deposit (up to 10 cm) [14] that forms on this super heater causes the real surface temperature to be significantly higher than suggested by the steam temperature alone. Fig. 10 illustrates the consequence of the too high heat flux in terms of the gas temperature. The too high heat transfer rates at the secondary super heater causes too low rates at both the tertiary and primary super heaters. The overall heat transfer rate to the steam circuit, however, only exceeds the data by 6%.
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Fig. 9. Wall heat fluxes in the furnace. The maximum absolute value of the legend does not correspond to the maximum predicted value of about 2200,000 W/m2.
3.4. Comparison with full-scale measurements Sampling of gas phase species as well as temperature measurements were undertaken at Masnedø CHP plant in November 1998 during straw firing [13]. Approximate locations of the measurement ports are illustrated in Fig. 2. The exact locations were difficult to establish except for the insertion length of the probe, which was reported to be 1.3 m. To illustrate the implications of not knowing the exact probe locations, the variation in predicted values within a distance of ^ 0.5 m from the estimated probe location is indicated by error bars in Fig. 10. Fig. 10 compares measured temperatures with calculated values. In regions of strong gradients, the uncertainty associated with changes in estimated probe location is considerable. The predicted temperatures are in very good correspondence with the measurements except at location 1, which is just above the grate. The calculated value is about 200 8C too high mainly due to the inlet value predicted by the bed model being too high. The measurement port is
located approximately at the location, where char burnout is completed. Most likely the difference can be ascribed to an inaccurate prediction of this location. This is supported by the observation that, during the measurements, the temperature at this measurement location varied several hundreds of degrees depending on the fuel load on the grate [13]. The standard deviations of the measurements have not been reported for the case of 100% straw firing, however, from standard deviations reported from measurements during co-firing with other biofuels it was estimated Table 3 Comparison of calculated heat fluxes with process data for the boiler
Water walls Super heater 1 Super heater 2 Super heater 3 Total
Calculated (MW)
Process data (MW)
Deviation (%)
18.6 5.7 2.6 1.3 28.1
17.5 6.3 1.2 1.5 26.5
6 210 117 217 6
S.K. Kær / Fuel 83 (2004) 1183–1190
Fig. 10. Measured and predicted gas temperatures. Error bars indicate estimated uncertainty related to locating the exact measurement locations.
to be within ^ 50 8C. The too low temperature predicted at position 5 is closely related to the over-predicted heat transfer rate at the secondary super heater (Table 3). Fig. 11 shows calculated and measured oxygen and carbon dioxide concentrations at the same locations. Error bars in Fig. 11 indicate the standard deviations of the concentration measurements. The uncertainty of the calculated value (related to the port location) has not been included, but from the variation of temperature it was estimated to be within ^ 15% of the local value. As for the temperatures, the agreement with measurements is favourable and in this case also at the first measurement port. The concentrations at location 6 and to a lesser extent location 4 are given almost exclusively by the overall stoichiometry of the combustion process and consequently they are fairly easy to capture by the model. At locations 1 and 3, the concentrations are influenced by local mixing rates and finite reaction rates and as such they are considerably more difficult to determine accurately. The influence from finite reaction rates can be identified from the co-existence of oxygen, carbon monoxide and volatiles at ports 1 and 3. Carbon monoxide and volatiles concentrations are compared to measured values in Fig. 12. When compared to the oxygen and carbon dioxide concentrations, the carbon monoxide and volatiles concentrations exhibit much larger standard deviations in the measurements. This is mainly due to combustion
Fig. 11. Comparison of measured and predicted oxygen and carbon dioxide concentrations. Error bars indicate the standard deviation in the experiments.
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Fig. 12. Comparison of measured and predicted carbon monoxide and volatiles concentrations. Error bars indicate the standard deviation in the experiments.
fluctuations introduced by grate vibrations [13]. Obviously, the steady-state model used in this work cannot capture such time-dependent phenomena. However, it may be possible to capture the carbon monoxide concentration peaks, found during grate vibration, by altering the boundary conditions at the grate to simulate these conditions. This option has not been investigated in further detail. 3.5. Mixing pattern and operational implications As mentioned above, the overall oxygen concentration in the stack is approximately 5 vol% suggesting relatively high excess oxygen. This value is even in the lower end of the range typical for grate-fired boilers. Still, most of these boilers suffer from high CO emissions and a high amount of unburned carbon in the fly ash. Based on the predictions reported here, and a number of similar boilers modelled by the author, there are significant indications that these problems may be partly due to poor mixing between the bulk flue gas flow and the air being injected mainly through the secondary air ports. Fig. 13 shows predicted oxygen concentrations in a cross-section of the furnace. Dark areas represent low oxygen concentrations. Please note that the colouring was chosen to provide good resolution of low concentration regions by decreasing the maximum value to a mass fraction of 6%. There is a clear striation of the flow with very low oxygen concentrations in the centre part of the boiler and relatively high concentrations near the walls. The low oxygen alley in the centre has, at the same time, high velocities and high temperatures (the latter has not been shown in this paper). Consequently, not only does the gases mix poorly leading to high CO levels but the particles entrained in the flue gas travel either in a low temperature region with slow char oxidation rates or in a relatively high temperature region with low oxygen. At the location where the oxygen profile begins to even out in the second pass the temperature is too low for CO and residual carbon in the fly ash to be oxidizing at any significant rate. It is believed that the poor mixing experienced in these boilers is often a result of the relatively small diameter of the secondary air ports
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S.K. Kær / Fuel 83 (2004) 1183–1190
influenced by the gas temperature predicted by the bed model. Species concentrations (O2, CO2, CO and volatiles) were also in good correspondence with the measurements. In conclusion, it is suggested that the relatively poor mixing in the furnace between the bulk flow and the secondary air jets is partly responsible for the high concentration of CO and unburnt carbon in the fly ash typical for grate-fired boilers.
Acknowledgements The Danish Energy Research Program and Babcock and Wilcox Vølund Aps, Denmark supported part of this work. Robert van der Lans from the CHEC research group at the Danish Technical University is thanked for providing the experimental data used for model validation.
References
Fig. 13. Cross-section showing oxygen concentration and velocity vectors. Please note that the maximum oxygen concentration was set to a mass fraction of 0.06 to improve the resolution of low concentrations.
providing poor penetration of the jets into the bulk flow. A relatively simple solution to this problem would be to use fewer nozzles with a larger diameter.
4. Conclusions A simulation procedure to grate-fired boilers based on a combination of an in-house code for the bed combustion modelling and CFX for the freeboard processes was validated against full-scale measurements from a strawfired boiler. The overall heat transfer predictions were in relatively good agreement with process data from the boiler except at the secondary super heater, where the predicted heat transfer rate exceeded the data by more than 100%. This was mainly ascribed to the wall surface temperature used as boundary condition in the CFD analysis being too low. The gas phase temperatures compared favourably with the measurements at all locations except one just above the grate. The temperature level at this location is strongly
[1] Stopford PJ. Recent applications of CFD modelling in the power generation and combustion industries. Appl Math Model 2002;26: 351 –74. [2] Scharler R, Obernberger I. Numerical modeling of biomass grate furnaces. Proceedings of the Fifth International Conference on Industrial Furnaces and Boilers, Porto, Portugal, April; 2000. [3] Larfeldt J, Tao L, Berge N. Development of an engineering tool for design and optimisation of biomass combustion in grate-fired boilers. Proceedings of the Fifth International Conference on Industrial Furnaces and Boilers, Porto, Portugal, April; 2000. [4] Radulovic P, Ghani M, Smoot L. Fuel 1995;74(4):582–94. [5] van der Lans R, Pedersen LT, Jensen A, Glarborg P, Dam-Johansen K. Biomass Bioenergy 2000;19(3):199 –208. [6] Dong W, Blasiak W. Energy Convers Manage 2001;42:1887–96. [7] Shin D, Choi S. Combust Flame 2000;121(1/2):167–80. [8] Griselin N, Bai XS. IFRF Combust J 2000; October 2000; article 200009. [9] Scharler R, Obernberger I, La¨ngle G, Heinzle J. CFD analysis of air staging and flue gas recirculation in biomass grate furnaces. Proceedings of the First World Conference and Exhibition on Biomass for Energy and Industry, Seville, Spain, June; 2000. [10] CFX 4.2 Solver Manual. CFX International, AEA Technology plc., 8.19 Harwell Laboratory, Oxfordshire OX11 0RA, UK. [11] Kær, SK. Numerical investigation of deposit formation in straw-fired boilers. PhD Thesis, Institute of Energy Technology, Aalborg University, Denmark, 2001. [12] Pedersen LT. CHEC report 9809. Denmark: Department of Chemical Engineering, Technical University of Denmark; 1998. (in Danish). [13] van der Lans RP. CHEC report 9914. Denmark: Department of Chemical Engineering, Technical University of Denmark; 1999. October. [14] Hansen LA, Nielsen HP, Frandsen FJ, Dam-Jchansen K, Hoerlyck S, Karlsson A, Fuel Process Technol 2000;64:189– 209.
Numerical modelling of a straw-fired grate boiler Søren K. Kær* Institute of Energy Technology, Aalborg University, Pontoppidanstræde 101, DK-9220 Aalborg Ø, Denmark Received 24 July 2003; revised 8 December 2003; accepted 9 December 2003; available online 4 January 2004
Abstract The paper presents a computational fluid dynamics (CFD) analysis of a 33 MW straw-fired grate boiler. Combustion on the grate plays a key-role in the analysis of these boilers and in this work a stand-alone code was used to provide inlet conditions for the CFD analysis. Model predictions were compared with available gas temperature and species concentration measurements showing good agreement. Combustion of biomass in grate-based boilers is often associated with high emission levels and relatively high amounts of unburnt carbon in the fly ash. Based on the CFD analysis, it is suggested that poor mixing in the furnace is a key issue leading to these problems. q 2004 Elsevier Ltd. All rights reserved. Keywords: Grate-fired boilers; Biomass; Computational fluid dynamics; Mixing problems
1. Introduction In Denmark, as well as internationally, boiler manufacturers are set increasing demands for fuel-flexible and efficient boilers. Still more advanced design tools are needed to meet these demands and to this end the use of computational fluid dynamics (CFD) has increased. The usefulness of CFD in the design and trouble-shooting of pulverized coal fired boilers of a wide range of types and designs is fairly well established (see, for example, Ref. [1]). The analysis of grate-fired boilers, however, adds new challenges to the models available in most commercial CFD packages. A central issue is the modelling of the processes in the fuel layer as it burns on the grate. In straw-fired boilers, the fuel layer is relatively thick (about 0.5– 1.0 m initially) and the combustion process cannot be modelled by traditional CFD codes without extensive user modifications. In this paper, a stand-alone in-house code was used to generate boundary conditions for the CFD analysis of the freeboard following the same concept as in Refs. [2 – 5]. Out of these studies, straw combustion was only dealt with in Ref. [5]. There is very limited information in the literature about previous studies addressing CFD-based modelling of straw-fired boilers. The combination of a stand-alone bed model and a CFD code was, however, applied previously in the analysis of grate-fired boilers burning coal [6], waste * Tel.: þ45-9635-9263; fax: þ45-9815-1411. E-mail address: [email protected] (S.K. Kær). 0016-2361/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.fuel.2003.12.003
[6,7] and woody biofuels [2,8,9]. This paper investigates the two-step approach by comparison to full-scale measurements and provides insight into the processes controlling the combustion characteristics of grate-fired boilers.
2. Method 2.1. The numerical model The CFD prediction was carried out using CFX [10]. The fundamental principles of CFD are well documented and will not be discussed further. The computational domain was discretized using a structured mesh resolving the individual air injection nozzles. In the particular boiler modelled there are a total of 395 air nozzles that have a significant influence on the flow and combustion patterns. The grid used in this study comprised a total of about 600,000 cells. The platen secondary and tertiary super heaters in the first and second passes were modelled as slabs and the primary super heater tube banks in the third pass were accounted for using source terms in the momentum and energy equations to simulate heat transfer and pressure drop. The steady-state governing equations were solved using the SIMPLE algorithm and the effect of turbulence on the mean flow field was accounted for using the RNG k– 1 model. Radiative heat transfer was modelled using the discrete transfer model [10]. In grate-fired boilers, the dominant thermo-chemical fuel conversion takes place on the grate. A typical example of
1184
S.K. Kær / Fuel 83 (2004) 1183–1190
Fig. 1. Schematic of the fuel bed discretization used in the numerical model. Large arrows indicate overall flow direction.
a grate-fired boiler including the fuel layer modelled is given in Fig. 1. The discretization of the bed employed in the numerical model is also indicated. Conceptually, the bed model considers the fuel layer as a number of threedimensional volumes. Each of these volumes is divided into horizontal slabs. Gas and fuel properties are represented at a discrete node point located at the centre of each slab [11]. The heat released by heterogeneous combustion of entrained particles is insignificant and only gas combustion was considered in the CFD prediction. The bed model accounted for char oxidation. Gas combustion in the freeboard was modelled using the Eddy-Break-Up model and a two-step reaction mechanism with CO as the intermediate species. y Cx Hy Oz þ ði1 þ i2 ÞO2 ! xCO þ H2 O þ i2 O2 2 y ! xCO2 þ H2 O; 2 x y z x i2 ¼ i1 ¼ þ 2 ; 2 4 2 2 ð1Þ
2.2. The full-scale straw-fired boiler The combined heat and power plant at Masnedø in Denmark was commissioned in 1995 and supplies about 20 MJ/s of district heating to the local town, Vordingborg. The plant burns approximately 8.1 tons/h of straw or a mix of straw and wood chips corresponding to a total fired
Table 1 List of gas analysers used for the measurements [13] Gas
Analyser
O2 CO CO2 C x Hy NO SO2
H&B, Magnos 3 and 6G H&B, Uras 3G H&B, Uras 4 Signal, 3000 HM (FID) H&B, Radas 1G FR, NGA 2000
H and B, Hartmann and Braun; FR, Fisher Rosemount; FID, Flame Ionization Detector.
Fig. 2. Location of the measurement ports used for gas temperature and species concentration measurements.
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Fig. 3. Schematic illustration of the lower section of a grate-fired boiler giving the operating conditions used in the simulations.
thermal rating of 33 MW and an electricity production of 8 MW. The boiler operates at an overall stoichiometric air to fuel excess ratio of about 1.3 corresponding to an oxygen concentration in the stack of just below 5 vol%. Several measurement programs were undertaken at Masnedø collecting experimental data on gas phase species concentrations, temperatures and ash deposits to determine combustion conditions [12,13] and deposit formation [14]. Measurements were always made after at least one full day of continuous operation on the same fuel. Pure straw firing and co-combustion with wood chips, olive pits and sheanuts (80% straw and 20% alternative fuel on a thermal basis) was investigated. In this context, only the pure straw runs were used. Temperature measurements were made with a suction pyrometer from the International Flame Research Foundation [13]. Combustion gases were extracted with a watercooled probe and run through particle filters and a cooling bath, where water was removed from the gas [13]. The concentrations of O2, CO2, CO, Cx Hy ; NO and SO2 were measured using the analysers listed in Table 1. Gas species concentrations and temperatures were measured at the locations shown in Fig. 2. The fuel and gas temperatures and flow rates used are summarized in Fig. 3. An overall straw bed density of 60 kg/m3 was used which is representative for the straw as it enters the furnace. The straw proximate and ultimate analyses used in the predictions are given in Table 2. The heat transfer surface temperatures were estimated from the process diagram of the boiler that operates at a pressure of 90 bars and a superheated steam outlet temperature of 520 8C. Fig. 4 summarizes the temperatures used. The saturation temperature of approximately
300 8C was used for the water walls. The primary super heater was divided into five sub-sections each representing a tube bank and the steam temperature was estimated in each section. A constant emissivity of 0.7 was used for all heating surfaces.
3. Results and discussion 3.1. Bed combustion results and CFD boundary conditions Fig. 5, showing the predicted mass fraction of char in the bed, illustrates the overall conversion process of the fuel bed. Only the first 5 m is shown as char burnout is almost complete at that point. The strong increase in char mass fraction close to the fuel feeding port indicates the onset of devolatilization. The process is initiated by flame radiation heating and moves from the top and downwards. The devolatilization front reaches the grate at a distance of about 1.5 m from the fuel feeding port. At that point, the char oxidation front starts moving from the bottom up. Compared to Table 2 The ultimate and proximate analyses used in the predictions Ultimate analysis
wt%
Proximate analysis
wt%
Carbon Hydrogen Oxygen Nitrogen Sulphur
44 5.9 49.5 0.7 0.15
Moisture Ash Fixed carbon Volatiles LHV as received
14 4.5 12 69.5 14.9 MJ/kg
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S.K. Kær / Fuel 83 (2004) 1183–1190
Fig. 4. Schematic showing the heat transfer surface temperatures used in the CFD analysis.
the devolatilization front, the char oxidation front is much wider due to oxygen diffusion being the limiting reaction process. The gas species mass fractions at the top of the bed used as inlet conditions for the CFD analysis are presented in Fig. 6. A large amount of volatiles leave the devolatilization zone of the bed unburnt due to highly sub-stoichiometric conditions. At positions further than 3 m, most of the char has burnt and the mass fraction of oxygen starts to increase while the mass fractions of the reaction products decrease. The gas phase temperature and velocity profiles at the top of the bed are shown in
Fig. 7. The gas temperature decreases from 800 8C in the initial stage of volatiles combustion to about 600 8C in the later. This is due to an acceleration of the devolatilization front that reduces the stoichiometry, i.e. the steeper the devolatilization front the less of the under-grate air is available. The acceleration can be identified from Fig. 5 as an increasingly steeper devolatilization front. In the char combustion region, the gas temperature increases almost linearly with the position on the grate. It peaks at a maximum of 1000 8C when the reaction front reaches the top of the bed at a position about 4 m from the fuel feeding port (Fig. 5).
Fig. 5. Two-dimensional illustration of the fuel bed char content. Only the first 5 m of the grate is included, as char burnout has almost completed at that point.
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Fig. 6. Chemical composition of the gas leaving the top of the fuel layer. These profiles were used as boundary conditions for the CFD analysis of the freeboard.
3.2. Qualitative gas phase properties The velocity field and the combustion reaction pattern is governed by the locations of air injection nozzles, which represent an important means of controlling the combustion process. The gas phase properties all show a complex threedimensional variation that is difficult to illustrate in detail graphically. Fig. 8 shows the total reaction rate in a crosssection of the lower part of the furnace. The velocity field is illustrated in terms of superimposed velocity vectors. A general feature of the reaction pattern is the existence of very fast rates (dark colours) in the regions of air injection nozzles. The air jets provide favourable reaction conditions in terms of oxygen and high turbulence levels ensuring good mixing of the oxidant with volatiles and carbon monoxide. The fastest reaction rates are found around the ignition air nozzles (see Fig. 3). The location and design of these nozzles are essential parameters in controlling the combustion process in the furnace. The heat released by the fast reaction rates provides heat to the fuel layer below and initiates the drying and devolatilization processes. Consequently, these nozzles control and maintain the location of the reaction front in the fuel layer at a fixed position. This is important in order to obtain an acceptable degree of fuel burnout. The secondary air nozzles, at the level of the nose, provide the oxygen needed to complete burnout of volatiles and carbon monoxide. This can be identified from the region of fast reaction rates in the upper part of Fig. 8. A region of
Fig. 7. Velocity and temperature profiles at the top of the fuel layer. These profiles were used in the CFD analysis of the freeboard.
Fig. 8. Reaction rates and velocity vectors in the lower part of the furnace. Dark areas indicate fast reaction rates. Note that reactions are most intense near the air injection nozzles.
relatively high reaction rates is also found just above the main grate approximately half-way down. In this region of the bed, both carbon monoxide and oxygen are released (see Fig. 6) and a reaction occurs in the gas phase. 3.3. Heat transfer rates Fig. 9 shows the heat flux to the furnace water walls (the unit is W/m 2). As the heat flux is away from the computational domain, it is defined as being negative. The maximum value of the colour scale does not represent the maximum local value of the heat flux, which is approximately 2 200,000 W/m2. High heat fluxes are mainly found in the regions of fast reaction rates close to the air injection nozzles. High heat release rates and gas temperatures also characterize these regions. In particular, there is a large region of high heat fluxes around the secondary air nozzles and further up along the front and sidewalls. The overall heat transfer rates to the steam circuit are compared to operational data from the boiler in Table 3. There is a reasonable degree of correspondence with the operational data as a deviation of about 10– 15% is found at all locations except for the secondary super heater, where the predicted rate exceeds the operational data by more than 100%. The main reason is believed to be that the surface temperature is too low at this super heater. The surface temperature of the relatively thick deposit (up to 10 cm) [14] that forms on this super heater causes the real surface temperature to be significantly higher than suggested by the steam temperature alone. Fig. 10 illustrates the consequence of the too high heat flux in terms of the gas temperature. The too high heat transfer rates at the secondary super heater causes too low rates at both the tertiary and primary super heaters. The overall heat transfer rate to the steam circuit, however, only exceeds the data by 6%.
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Fig. 9. Wall heat fluxes in the furnace. The maximum absolute value of the legend does not correspond to the maximum predicted value of about 2200,000 W/m2.
3.4. Comparison with full-scale measurements Sampling of gas phase species as well as temperature measurements were undertaken at Masnedø CHP plant in November 1998 during straw firing [13]. Approximate locations of the measurement ports are illustrated in Fig. 2. The exact locations were difficult to establish except for the insertion length of the probe, which was reported to be 1.3 m. To illustrate the implications of not knowing the exact probe locations, the variation in predicted values within a distance of ^ 0.5 m from the estimated probe location is indicated by error bars in Fig. 10. Fig. 10 compares measured temperatures with calculated values. In regions of strong gradients, the uncertainty associated with changes in estimated probe location is considerable. The predicted temperatures are in very good correspondence with the measurements except at location 1, which is just above the grate. The calculated value is about 200 8C too high mainly due to the inlet value predicted by the bed model being too high. The measurement port is
located approximately at the location, where char burnout is completed. Most likely the difference can be ascribed to an inaccurate prediction of this location. This is supported by the observation that, during the measurements, the temperature at this measurement location varied several hundreds of degrees depending on the fuel load on the grate [13]. The standard deviations of the measurements have not been reported for the case of 100% straw firing, however, from standard deviations reported from measurements during co-firing with other biofuels it was estimated Table 3 Comparison of calculated heat fluxes with process data for the boiler
Water walls Super heater 1 Super heater 2 Super heater 3 Total
Calculated (MW)
Process data (MW)
Deviation (%)
18.6 5.7 2.6 1.3 28.1
17.5 6.3 1.2 1.5 26.5
6 210 117 217 6
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Fig. 10. Measured and predicted gas temperatures. Error bars indicate estimated uncertainty related to locating the exact measurement locations.
to be within ^ 50 8C. The too low temperature predicted at position 5 is closely related to the over-predicted heat transfer rate at the secondary super heater (Table 3). Fig. 11 shows calculated and measured oxygen and carbon dioxide concentrations at the same locations. Error bars in Fig. 11 indicate the standard deviations of the concentration measurements. The uncertainty of the calculated value (related to the port location) has not been included, but from the variation of temperature it was estimated to be within ^ 15% of the local value. As for the temperatures, the agreement with measurements is favourable and in this case also at the first measurement port. The concentrations at location 6 and to a lesser extent location 4 are given almost exclusively by the overall stoichiometry of the combustion process and consequently they are fairly easy to capture by the model. At locations 1 and 3, the concentrations are influenced by local mixing rates and finite reaction rates and as such they are considerably more difficult to determine accurately. The influence from finite reaction rates can be identified from the co-existence of oxygen, carbon monoxide and volatiles at ports 1 and 3. Carbon monoxide and volatiles concentrations are compared to measured values in Fig. 12. When compared to the oxygen and carbon dioxide concentrations, the carbon monoxide and volatiles concentrations exhibit much larger standard deviations in the measurements. This is mainly due to combustion
Fig. 11. Comparison of measured and predicted oxygen and carbon dioxide concentrations. Error bars indicate the standard deviation in the experiments.
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Fig. 12. Comparison of measured and predicted carbon monoxide and volatiles concentrations. Error bars indicate the standard deviation in the experiments.
fluctuations introduced by grate vibrations [13]. Obviously, the steady-state model used in this work cannot capture such time-dependent phenomena. However, it may be possible to capture the carbon monoxide concentration peaks, found during grate vibration, by altering the boundary conditions at the grate to simulate these conditions. This option has not been investigated in further detail. 3.5. Mixing pattern and operational implications As mentioned above, the overall oxygen concentration in the stack is approximately 5 vol% suggesting relatively high excess oxygen. This value is even in the lower end of the range typical for grate-fired boilers. Still, most of these boilers suffer from high CO emissions and a high amount of unburned carbon in the fly ash. Based on the predictions reported here, and a number of similar boilers modelled by the author, there are significant indications that these problems may be partly due to poor mixing between the bulk flue gas flow and the air being injected mainly through the secondary air ports. Fig. 13 shows predicted oxygen concentrations in a cross-section of the furnace. Dark areas represent low oxygen concentrations. Please note that the colouring was chosen to provide good resolution of low concentration regions by decreasing the maximum value to a mass fraction of 6%. There is a clear striation of the flow with very low oxygen concentrations in the centre part of the boiler and relatively high concentrations near the walls. The low oxygen alley in the centre has, at the same time, high velocities and high temperatures (the latter has not been shown in this paper). Consequently, not only does the gases mix poorly leading to high CO levels but the particles entrained in the flue gas travel either in a low temperature region with slow char oxidation rates or in a relatively high temperature region with low oxygen. At the location where the oxygen profile begins to even out in the second pass the temperature is too low for CO and residual carbon in the fly ash to be oxidizing at any significant rate. It is believed that the poor mixing experienced in these boilers is often a result of the relatively small diameter of the secondary air ports
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influenced by the gas temperature predicted by the bed model. Species concentrations (O2, CO2, CO and volatiles) were also in good correspondence with the measurements. In conclusion, it is suggested that the relatively poor mixing in the furnace between the bulk flow and the secondary air jets is partly responsible for the high concentration of CO and unburnt carbon in the fly ash typical for grate-fired boilers.
Acknowledgements The Danish Energy Research Program and Babcock and Wilcox Vølund Aps, Denmark supported part of this work. Robert van der Lans from the CHEC research group at the Danish Technical University is thanked for providing the experimental data used for model validation.
References
Fig. 13. Cross-section showing oxygen concentration and velocity vectors. Please note that the maximum oxygen concentration was set to a mass fraction of 0.06 to improve the resolution of low concentrations.
providing poor penetration of the jets into the bulk flow. A relatively simple solution to this problem would be to use fewer nozzles with a larger diameter.
4. Conclusions A simulation procedure to grate-fired boilers based on a combination of an in-house code for the bed combustion modelling and CFX for the freeboard processes was validated against full-scale measurements from a strawfired boiler. The overall heat transfer predictions were in relatively good agreement with process data from the boiler except at the secondary super heater, where the predicted heat transfer rate exceeded the data by more than 100%. This was mainly ascribed to the wall surface temperature used as boundary condition in the CFD analysis being too low. The gas phase temperatures compared favourably with the measurements at all locations except one just above the grate. The temperature level at this location is strongly
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