Biomass

Energy & Fuels 2009, 23, 3437–3445

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Use of a Predictive Model for the Impact of Cofiring Coal/Biomass Blends on Slagging and Fouling Propensity† Piotr Plaza,* Anthony J. Griffiths, Nick Syred, and Thomas Rees-Gralton Centre for Research in Energy, Waste and the EnVironment, School of Engineering, Cardiff UniVersity, The Parade, Cardiff CF24 3AA, U.K. ReceiVed NoVember 30, 2008. ReVised Manuscript ReceiVed March 11, 2009

The paper describes an investigation of slagging and fouling effects when cofiring coal/biomass blends by using a predictive model for large utility boilers. This model is based on the use a zone computational method to determine the midsection temperature profile throughout a boiler, coupled with a thermo-chemical model, to define and assess the risk of elevated slagging and fouling levels during cofiring of solid fuels. The application of this prediction tool was made for a 618 MW thermal wall-fired pulverized coal boiler, cofired with a typical medium volatile bituminous coal and two substitute fuels, sewage sludge and sawdust. Associated changes in boiler efficiency as well as various heat transfer and thermodynamic parameters of the system were analyzed with slagging and fouling effects for different cofiring ratios. The results of the modeling revealed that, for increased cofiring of sewage sludge, an elevated risk of slagging and high-temperature fouling occurred, in complete contrast to the effects occurring with the utilization of sawdust as a substitute fuel.

Introduction Pressure on the dwindling traditional economic fossil fuel reserves along with stringent environmental legislation, especially those associated with greenhouse gas production, has led to sectors such as that of power generation to reanalyzing the way in which they produce electricity. One such route is to cofire using a mixture of coal and a range of biomass sources. Currently, substitution rates have been conservative, typically operating at about 5%. However, within the European Union there is a drive to substantially increase the amount of substitution to around 20%. The technology of biomass cofiring in large pulverized coal-fired boilers seems to be the most costeffective way of biomass utilization due to the higher boiler efficiency in comparison with 100% firing biomass in smaller boilers. Limitations develop due to supply chain problems for the physical quantities of biomass needed. The byproduct of raising biomass thresholds can be operational problems associated with the generation of slagging and fouling and/or corrosion within pulverized fuel boilers. The ash deposition process driven by accumulation of molten/ sticky, sintered, or loosely condensed deposits on tube banks (derived from mineral matter of solid fuels) can lead to substantial financial losses to an operator as a result of reduced boiler efficiency, reduced availability (unplanned shut-downs), and high maintenance costs due to blockage, erosion, and corrosion.1,2 These operational boiler problems are often, but not exclusively (i.e., low silica ratios can cause severe slagging) caused mainly by utilization of high alkali content biomass fuels, † Impacts of Fuel Quality on Power Generation and Environment. * To whom correspondence should be addressed. Phone: +44 2920870597; e-mail: [email protected]. (1) Pronobis, M. Fuel 2006, 85, 474–480. (2) Plaza, P.; Hercog, J.; Hrycaj, G.; Krol, K.; Rybak, W. Predicting ash deposit formation during co-firing of coal with biomass, Success & Visions for Bioenergy: Thermal Processing of Biomass for Bioenergy, Biofuels and Bioproducts; Bridgwater A. V. Ed.; CPL Press: Newbury, UK, 2007.

whose fly ash behavior significantly differs from that of conventional fuels.1-8 Over the past 15 years, a number of full-scale investigations on ash-related problems when cofiring biomass with coal have been undertaken in European power plants.9-13 The problems have been more apparent in the demonstration and commercial projects involving the firing or the cofiring of biomass in smaller boilers and at higher cofiring ratios. Experience of cofiring were found in many countries and especially in the Nordic countries Denmark, Sweden, and Finland, which have a good biomass supply, contributing to favorable conditions for cofiring. However, according to Hansson et al.,14 Germany, followed by the (3) Gralton, T. R. The Development of a Prediction Tool for Utility Boiler Performance; Ph.D. Thesis, Cardiff University: Wales, UK, 2007. (4) Rahman, A. A. Studies of Co-firing with Biomass on a Two Stage Simulator for Utility Boilers; Ph.D. Thesis, Cardiff University: Wales, UK, 2006. (5) Syred, N.; Griffiths, A. J.; Rees-Gralton, T.; Wilcox, S. Progress in the development of a spreadsheet based model to aid diagnosis of slagging, fouling and corrosion problems in utility boilers, Presented at the 15th IFRF Member’s Conference, Pisa, Italy, June 13-15, 2007. (6) Miller, S. F.; Miller, B. G. Fuel Process. Technol. 2007, 88, 1155– 1164. (7) Zevenhoven-Onderwater, M.; Blomquist, J.-P.; Skrifvars, B.-J.; Backman, R.; Hupa, M. Fuel 2000, 79, 1353–1361. (8) Dyk, J. C.; Baxter, L. L.; Van Heerden, J. H. P.; Coetzer, R. L. J. Fuel 2005, 84, 1768–1777. (9) Hilpert, H. D.; Maier, J.; Scheurer, W.; Hein, K. R. G. Status Report on Firing Secondary Fuels in Europe, IFRF Doc No G 106/g/1; BioFlam Project; Velsen Noord, May 2006. Available at http://www.ifrf.net/. (10) Ja¨rvinen, T.; Alakangas, E. Cofiring of BiomasssEValuation of Fuel Procurement and Handling in Selected Existing Plants and Exchange of Information (COFIRING); VTT Energy, Finland, 2001, http://afbnet.vtt.fi. (11) Pedersen, L. S.; Nielsen, H. P.; Kiil, S.; Hansen, L. A.; DamJohansen, K.; Kildsig, F.; Christensen, J.; Jespersen, P. Fuel 1996, 1584– 1590, 75,13. (12) Hansen, L. A.; Nielsen, H. P.; Frandsen, F. J.; Dam-Johansen, K.; Hørlyck, S.; Karlsson, A. Fuel Process. Technol. 2000, 64, 189–209. (13) Wieck-Hansen, K.; Overgaard, P.; Larsen, O. H. Biomass Bioenergy 2000, 19, 395–409. (14) Hansson, J.; Berndes, G.; Johnsson, F.; Kja¨rstad, J. Energy Policy 2009, 37, 1444–1455.

10.1021/ef8010383 CCC: $40.75  2009 American Chemical Society Published on Web 04/14/2009

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U.K. and Poland, has the largest technical potential for cofiring with coal in the 27 member states of the EU. The pioneering straw cofiring campaign undertaken in the 1990s in Denmark revealed serious problems with slagging, fouling, and corrosion encountered in conventional boilers such as stoker-fired (up to 100% straw firing) and fluidized bed boilers (with up to 50% biomass on an energy basis).11-13 It has been established that the main reason for such operational problems lay in the high concentrations of potassium and chlorine in the annual crop biomass. According to refs 11 and 12, relatively limited fouling and slightly accelerated corrosion rates have been reported during cofiring of straw and coal in large pulverized utility boilers. It should be noted that the great majority of the pf projects have operated at cofiring ratios less than 10% (on heat input basis). However, when using around 20% straw, corrosion rate increased by 100-200%.13 To date, the requirements with respect to the use of diverse biomass fuels cofired at higher levels in existing large pf boilers has rapidly increased. In order to make the cofiring financially viable, operators need to ensure that minimal modifications to the combustion plant are needed and that electrical output remains unaffected while maintaining running costs at the existing level. Following these considerations, there is a need to develop a prediction tool that can allow operators to assess the safe, economical operating limits on the level of cofiring fuels that can be used in existing boilers. These are normally the most efficient and reliable operation of the boiler, without acceptable problems of slagging and fouling. In recent years, a number of CFD-based models/simulators including ash deposition phenomena have been developed.16-19 Nowadays, multipurpose CFD codes combine the modeling of turbulent flow in combustion systems with other combustion phenomena. These include advanced models of ash deposition with complex stages of ash behavior from ash formation, transport to the heat surfaces, deposition, and growth. The integration of CFD combustion modeling with advanced mineral matter chemistry, multicomponent, multiphase thermo-chemical equilibrium calculation, and advanced fuel analyses are the goal for the development of reliable complex simulation tools for accurate predictions of slagging and fouling processes. Despite the apparent advantages associated with CFD tools, these comprehensive models are too bulky for use in case studies with strongly variable fuel properties or those considering various possible design changes to the boiler and furnace. In addition to the expertise required and time taken to prepare the simulation, CFD models can at best take several hours or days to run and at worst several weeks. This makes it very difficult and time-consuming to evaluate the effect of even small changes to fuel specification. Indeed, most operators test new fuels in model 0.5-1 MW boiler simulators with residence time similar to large boilers, looking at slagging, fouling, corrosion effects, as well as a range of other parameters. This allows appropriate fuel blends to be developed, but it is expensive. When a cofiring approach or retrofitting an existing unit is considered, design engineers as well as the boiler’s management have to take into

The developed prediction tool is based on integration of two approaches consisting of a zone computational method to determine the temperature profile of a boiler, as well as ash thermo-chemical calculations to define and assess the risk of elevated slagging and fouling levels during cofiring of solid fuels. The first approach is based on the mathematical principles of the Russian standard zone method.21,22 The thermal furnace characteristics derived from simulations may help to find the optimal solutions for the furnace design, heating surface arrangement, and operational conditions within a relatively short period of time. The flue gas temperature profile predicted with sufficient accuracy in the boiler allows the derived temperature history for transformations of the mineral matter and indicates the potential for slagging and fouling. A zone-based model can be easily adapted to study the impact on thermal characteristics of the furnace of distribution of fuel, air, and any recirculating gases in the burner zones, including special cases of staged combustion and reduced boiler loads.22 The advantages of this method are flexibility with respect to the furnace geometry and fuel type, including fuel mixtures, as well as the opportunity of short computational time (a few minutes for a single case study) to optimize the model with respect to the fuel mixtures/air distribution. The schematic of a boiler as a series of zones is shown in Figure 1.

(15) Nielsen, H. P.; Frandsen, F. J.; Dam-Johansen, K. Energy Fuels 1999, 13, 1114–1121. (16) Ma, Z.; Iman, F.; Lu, P.; Sears, R.; Kong, L.; Rokanuzzaman, A. S.; McCollor, D.; Benson, S. A. Fuel Process. Technol. 2007, 88, 1035–1043. (17) Xu, M.; He, X.; Azevedo, J. L. T.; Carvalho, M. G. Int. J. Energy Res. 2002, 26, 1221–1236. (18) Diez, L. I.; Cortes, C.; Campo, A. Applied Thermal Engineering 2005, 25, 1516–1533. (19) Mueller, Ch.; Selenius, M.; Theis, M.; Skrifvars, B.-J.; Backman, R.; Hupa, M.; Tran, H. Proc. Combust. Inst. 2005, 30, 2991–2998.

(20) Hotell, H. C.; Sarofim, A. F. RadiatiVe Transfer; McGraw Hill: New York, 1967. (21) Kouznetsov, N. V.; Mitor, V. V.; Dubovsky, I. E.; Karasina, E. S. Thermal calculation of steam boilers: NormatiVe Method [in Russian]; Moscow: Energiya, 1973. (22) Kouprianov, V. I. Energy 2001, 26, 839–853. (23) Hesselmann, G. Modelling of pulVerized coal fired furnaces with adVanced combustion systems by integrated performance, Final Technical Report, Contract No JOF3-CT95- 0005, Mitsui Babcock Energy Ltd.: Renfrew, Scotland, UK, 1998.

account a large number of potential problems and case studies related to the efficiency and reliable operation of the boiler furnace. In such cases, the models should be simple, capable of incorporating experimental data, since a rapid response is required so that numerous runs can be conducted. With sufficient accuracy, the required thermal characteristics of the furnace can be obtained within a relatively short period of time, with the aid of zone-based engineering computational models.20-23 Still the most popular in technical calculations are the Russian standard zone method and the more advanced Hottel zone method originally proposed in 1958 by Hottel and Cohen, which are used to calculate temperature and heat flux profiles/radiative heat transfer in the boiler/furnace.20,21 After reviewing many different approaches to the modeling16-23 of pulverized coal and biomass fuel combustion, the onedimensional model based on the Russian standard zone method has been chosen as a basis for further development to include the convective section of the boiler as well as thermo-chemical calculations of ash behavior to predict slagging and fouling propensity. The aim of the research was to develop a generic slagging and fouling predictor tool for use in large utility boilers when cofiring biomass/coal blends. This should be capable of giving relatively quick responses when simulating the effects of different fuel types and operating conditions while being easily implemented for varied furnace types. Modeling Approach

Impact of Cofiring on Slagging and Fouling

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furnace thermal efficiency coefficient is highly dependent on both ash properties and deposition potential. After transformation of the thermal energy balance equation the following general formula is obtained for temperature at the outlet of the zone:21,22 ˙ Air,ijcpAirtAir,i ˙ B,i(∆βLHV + if) + 2M 2M + ˙ B,i+1VCi+1 + RkFk 2M ˙ B,iVCi - RkFk 2RkFk 2M ti + t ˙ B,i+1VCi+1 + RkFk ˙ B,i+1VCi+1 + RkFk d 2M 2M

ti+1 )

σ0εf(Ti)4 ˙ B,i+1VCi+1 + RkFk 2M

Figure 1. Schematic of a boiler as a series of zones.

Figure 2. Thermal energy balance of a zone in the furnace.

Alongside the physical modeling of the boiler, a complementary development of a thermo-chemical module that utilizes the FactSage chemical database was used. This was designed to investigate the phase distribution of the complex me´lange of ash-based compounds that are formed in the atmosphere of the high-temperature boiler. The developed model indicates the propensity of a given fuel to foul or slag by analyzing the proportion of the ash that is in the solid and molten (liquid) phase under various boiler operating conditions.3,5 Furnace Section of the Boiler. Zone-based models work by dividing the furnace into a series of control volumes across which the energy balance equations are written, resulting in a system of algebraic nonlinear equations in terms of the outlet temperature of each zone, allowing the radiative heat flux distribution to be predicted. The heat streams are delivered into the burner/furnace zones ˙ B), by preheated air (Q ˙ Air), and by heat from by burning fuel (Q ˙ FG,i, as shown in flue gas flowing out from the previous zone Q Figure 2. The general thermal balance of each zone in the furnace can be written by the following formula:21,22 ˙ Con - Q ˙ FG,i+1 ) 0 ˙B + Q ˙ Air - Q ˙ Rad - Q ˙ FG,i + Q Q

(1)

In each zone in the furnace heat is absorbed by wall furnace tubes, especially by radiation (QRad). Convection (QCon) is usually neglected in the furnace but is considered when the platen superheater is situated at the outlet of the furnace. The effectiveness of heat transfer depends on flame emissivity and furnace thermal efficiency coefficient (Ψ). Furthermore, the

[( ) ] Ti+1 Ti

4

+ 1 × (ΨF) (2)

˙ B and M ˙ Air are the fuel and air flow rate (i, i+1 denote where M the inlet and outlet of current zone), respectively; ∆β is the fuel burnout in the current zone; LHV is the lower heating value of the fuel; if is the sensible heat of fuel delivered into the zone; VC is the specific heat of the flue gas (derived based on the amount of fuel burned); jcpAir is mean specific heat of the air at the temperature tAir; σ0 is the Stefan-Boltzmann constant; εf is the effective emissivity of the furnace; t and T are the temperatures of flue gas (in °C and K, respectively); ΨF is effective refractory surface in the zone; Fk is the convective heat exchange surface of the platen superheater and furnace wall; Rk is the convective heat transfer coefficient (flue gas-tube surface); and td is the temperature of surface deposit. An iterative technique is used for convergence of the predicted temperature at the zone outlet. The obtained thermal balance equations for zones in the furnace can be very dependent on specific conditions of heat release and transfer in each zone. In the burner zones each burner row is considered as a separate zone into which fuel flows at the given rate and the degree of fuel burnout achieved in the previous zone is also considered. Furthermore, the specific heat of combustion products (VCi+1) is calculated as a cumulative parameter depending on the actual total fraction of fuel burnout by the current furnace level, including the current zone. A detailed description of the procedure for estimating fuel burnout rate along the height of the furnace as well as other relevant properties and characteristics used in thermal balance equation are described in refs 21 and 22. As far as the accuracy of the zone-based method is concerned, according to literature reviews,22 this is estimated at about (3% (or (50 °C for the temperature in burner zones) and of (5% ((60 °C for the temperature at the furnace outlet) for various fuels and furnace types. For these industrial applications the predicted furnace characteristics are sufficiently accurate to be used for further calculations related to furnace design, retrofitting, fuel changes, and, for instance, to investigate the likelihood of slagging occurring in the furnace when cofiring biomass/ coal blends. Convective Section of the Boiler. In convective sections of the boiler, each zone represents one of the boiler’s heat exchangers (superheater, reheater, economizer, air preheater) for which the thermal balance equation was written. The temperature of the flue gas at the outlet of the zone ti+1 was obtained by the preliminary calculation of its enthalpy, by resolving first the thermal balance eq 3 and then by the comparison with the modeling flue gas enthalpy functions as shown in eq 5 is as follows:

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˙ Con Q ˙B M

IFG,i+1 ) IFG,i -

(3)

˙ BΨzkH∆t ) D ˙ Steam ·(h2(t2, p2) - h1(t1, p1)) (4) ˙ Con ) M Q Enthalpy(λ, ti+z) - IFG,i+1 ) 0 f ti+1 ) ?

(5)

where IFG,i+1 and IFG,i are the enthalpies of flue gas in the ˙ B is a fuel flow rate; previous and current zone, respectively; M ˙ Con is a convective heat stream absorbed by heat exchangers; Q H is a heat transfer surface; and ∆t is a logarithmic mean temperature difference. From the above system of equations an assessment of the impact of cofiring coal/biomass blends on the temperatures of superheated/reheated steam was conducted. These parameters can vary, dependent on generally different heat transfer conditions occurring in convective parts of the boiler during cofiring of specific fuel blends, due to the changes of the flue gas properties (velocity, viscosity, etc.) as well as ash deposition. The key point is associated with the estimation of overall heat transfer coefficient k which is affected by the fouling tendency of the ash. In order to predict the fouling tendency, the thermal effectiveness number Ψz (defined as a quotient of overall heat transfer coefficients in real and in ideal-clean conditions) has been used based on Pronobis’s empirical correlations.1 These correlations have been derived from experimental tests carried out in pulverized fuel fired Polish steam boilers and are valid for heating surfaces covered with loose or slightly sintered deposits. Although Pronobis’s correlations are dependent on tube arrangements (relative transverse/ longitudinal pitch, the outer tube diameter), flue gas velocity between the tubes, mean flue gas temperature in the tube bundle, and fraction of fly ash particles bigger that 30 µm, the main impact on the value of thermal effectiveness number is the quality of fly ash determined by the base-to-acid (B/A) ratio. For technical calculation in some cases it is more convenient to use a nondimentionalized form of the thermal effectiveness number by means of the quotients ΨzΣ/ΨzΒ, where ΨzΣ describes the fouling by simultaneous biomass and coal firing and ΨzB is that by coal combustion only. Assuming a mean value of the respective exponent for in-line and staggered tube arrangement, Pronobis1 suggests using a relative thermal effectiveness number, which varies as follows:

[ ]

(B/A)Σ ΨzΣ ) ΨzB (B/A)B

-0.354

(6)

The above empirical correlations were incorporated into the model to assess the impact of ash deposition on both the heat transfer and the boiler’s heat transfer parameters, including the amount of water injected into the attemperators. Thermo-Chemical Analysis. Besides empirically derived correlations to predict ash fouling tendency, more advanced thermo-chemical analyses were also used in the predictor to investigate ash melting behavior in the atmosphere of the hightemperature boiler. The propensity of a given fuel to foul or slag was indicated by analyzing the proportion of the ash that is in the solid or molten (liquid) phase corresponding to the wide range of temperatures occurring in the boiler.3,5 It is postulated that all of the ash with a melt fraction between 15 and 70% are sticky and thus may accumulated on the heat transfer surfaces, contributing to deposit formation. Collection of these particles on the tube banks can lead to deposit growth and can raise the external surface temperature until more than

70% of the deposit is liquid, in which state all new particles transported to the molten surface flow off and cause severe slagging.19 To estimate a specific fuels mixture ash behavior, thermodynamic equilibrium analysis was conducted, which is based on the minimization of total Gibbs free energy of a system of chemical compounds. However, it is well-known that not all mineral matter of coal and biomass can achieve equilibrium in a such short residence time (3-5 s) at the high temperatures in the boiler. Under these conditions the fusion or partial fusion of quartz and silica particles can occur and, at high temperatures, interactions to form alkaline silicates are also present. On the other hand, quantification of release of the most abundant biomass alkali elements such as Cl, K, and S, responsible in the main part for the ash-related problems, is still challenging and has been very carefully investigated in different thermal conversion systems.24-26 The main goal of the recently ongoing research is to understand mechanisms and improve the capability to predict the alkalis released from fuel and retained in the bottom ash under various combustion conditions. It can be partially achieved by a fuel chemical fractionation technique that is based on a leaching procedure of the fuel elements in aqueous solutions that are gradually made stronger. However, more accurate results regarding the quantification and kinetic of alkali release can be achieved by undertaking several experiments under well-controlled laboratory combustion conditions (in high temperature drop tubes for pf boilers or fix-bed reactors-grate boilers). The generated ash and slag samples are then extracted for more sophisticated ash analyses, which can include the mass balance of released/bonded elements and thermal analysis (TGA/DTA) or scanning electron microscopy in combination with energy dispersive X-ray diffraction (SEM-EDX, XRD) of partially molten slags to assess their thermodynamic states (amount of amorphous/molten phase) of transformed mineral matter.24-26 For this work, the chemical fractionation approach has been applied for pulverized combustion conditions. From analysis of the literature, it was thus assumed that only the reactive ash fraction (leachable in water and ammonium acetate) and 15% part of nonreactive ash (leachable in hydrochloric acid and residue) of biomass and coal combustion can reach equilibrium state during combustion in pulverized fuel fired boilers.27 This approach is based on laboratory investigations for coal/ biomass combustion, which indicates that alkali ash compounds vaporized at elevated temperatures can interact with the surface of nonreactive silica particles. This gives rise to low-melting temperature alkali silicates and contributes to the melt phase that occurs in the boiler. Taking this as a basis, in the model developed it was assumed (according to Nutalapati et al.)27 that all the ash particles are spherical, are of 10 µm diameter, and at high temperatures the same proportion of particles are reacting. Furthermore, the average thickness of the reacting layer was assumed to be 0.3 µm26 which corresponds to around 15% in volume or mass basis for 10 µm sized nonreactive particles.26,27 The 14 most common elements present in solid fuels were introduced into the thermo-chemical equilibrium analysis (C, H, O, N, S, Si, Al, Fe, Ca, Mg, Na, K, Cl, P). The following (24) Knudsen, J. N.; Jensen, P. A.; Dam-Johansen, K. Energy Fuels 2004, 18, 1385–1399. (25) Frandsen, F. J.; van Lith, S. C.; Korbee, R.; Yrjas, P.; Backman, R.; Obernberger, I.; Brunner, T.; Jo¨ller, M. Fuel Process. Technol. 2007, 88, 1118–1128. (26) Wibberley, L. J.; Wall, T. F. Fuel 1982, 61, 93–99. (27) Nutalapati, D.; Gupta, R. P.; Moghtaderi, B.; Wall, T. F. Fuel Process. Technol. 2007, 88, 1044–1052.



The application of the developed prediction tool was investigated for a 618 MW thermal wall-fired pulverized coal boiler, cofired with a typical medium volatile bituminous coal and two substitute fuels such as sewage sludge and sawdust; standard analyses are presented in Table 1. The chemical ash analysis was extended to chemical fractionation of fuels to divide the ash into reactive and nonreactive fractions. The reactive fraction of ashes, which was introduced along with 15% of the nonreactive part into the equilibrium model, was derived from a literature review as an average for similar types of fuels.6-8,27,28 The investigated fuels differ significantly from each other, especially in terms of the type and composition of their mineral matter. When compared to coal and sewage sludge ashes, biomass ash typically contains more chlorine and alkali metals but less sulfur, minerals, and total ash. The clean wood materials are particularly rich in Ca, Si, and K. Although the total mineral matter contents in biomass fuels are lower, a much higher proportion of the mineral material is in the water and acetatesoluble fractions (e.g., K, Na, Cl, S, and usually Zn and Pb evaporate to over 80%) and is considered to contribute to the formation of the fine/aerosol material. The volatilized-from-

biomass-fuels alkali metals (K, Na) in the presence of chlorine, sulfur, and silica undergo many undesirable reactions during combustion, which can lead to ash-related problems. On the one hand, the alkali reactions with silica (likely to occur at temperatures above 1300 °C) form alkali silicates that melt or soften at low temperatures. On the other hand, the reactions of alkali with sulfur and chlorine form alkali sulfates and chlorides, which are directly responsible for the formation of the corrosive deposits in the convective section of the boiler. The major ash-forming elements present in sewage sludge are Si, Al, Ca, P, and usually Fe derived from the phosphorus precipitation step in the wastewater treatment plan. In general, sewage sludge is not known to be a difficult fuel with respect to alkali problems.29 The potassium is present in both soluble and more stable forms, in a total contrast to the wood (sawdust), which contains more potassium in the ash (included mostly in the soluble part) and elevated amounts of calcium. Much of the Si and Al found in the sewage sludge originates in zeolites derived from detergents such as washing powder. The wastewaterderived alumina silicates (zeolites) are well-known to have good adsorption properties at high temperatures and may possibly bind vaporous metal species in combustion.29 However, high levels of iron and phosphorus in sewage sludge and relatively high ash content may classify this fuel as problematic in terms of high slagging potential. When analyzing the slagging propensity of the ashes obtained from cofiring of biomass with coal, it is clear that the alkali metals are powerful fluxes for alumino-silicates present in solid fossil fuels. It is quite likely, therefore, that biomass cofiring will lead to reduce the ash fusion temperatures, and as a consequence to increase the slagging potential, which depends on the level of fluxing agents in blended fuel and on the cofiring ratio. As far as fouling in the convective pass of coal-fired boilers is concerned, the major mechanism responsible for ash deposition is driven by a volatilization and condensation of sodium compounds (included in the soluble part in coal). The potassium is mostly present in coal as a constituent of clay minerals and is less likely to be released by volatilization in combustion. Predicted Temperature Profile. The predicted temperature profiles in the boiler for pure coal firing and blends with two types of substituted fuel (sewage sludge and sawdust) for 20% cofiring ratio are presented in Figure 3. The results show a lower gas temperature for cofiring in the furnace and, correspondingly, a slightly higher level in the convective section of the boiler compared with pure coal combustion. This is due to the different radiative properties and lower adiabatic temperatures of the gaseous combustion products for biomass that affect the combustion and heat transfer in the furnace. The temperature rise in the convective section of the boiler is caused mainly by increasing ash deposition due to the higher content of base compounds in the biomass ash. The derived profile for pure coal agrees quite well with that predicted by CFD. Analyzing the impact of cofiring on flue gas temperature in the convective part of the boiler must take into account two opposing factors affecting the heat transfer. On the one hand, the convective heat transfer can significantly vary depending on the quantity of exhaust gases produced and different (usually higher) velocities of the flue gas. On the other hand, positive effects on heat transfer due to higher velocities can be reduced by increased ash deposition. The impact of cofiring on both the nondimensionalised relative heat transfer coefficients (for clean

(28) Tortosa Masia´, A. A.; Buhre, B. J. P.; Gupta, R. P.; Wall, T. F. Fuel 2007, 86, 2446–2456.

(29) Pettersson, A.; Zevenhoven, M.; Steenari, B.-M.; Åmand, L.-E. Fuel 2008, 87, 3183–3193.

Table 1. Standard Analyses of Investigated Solid Fuels proximate analysisa, %

coal

sewage sludge

sawdust

fixed carbon, % volatile matter, % moisture, % ash, % LHV, kJ/kg

51.0 33.3 4.2 11.5 27 000

2.75 36.72 11.72 48.81 9100

9.4 55.0 34.9 0.7 10 935

ash analysis (total/reactive fraction), % SiO2 Al2O3 TiO2 Fe2O3 CaO MgO K2O Na2O SO3 P2O5 Clb

43.7/0 24.7/0 0.97/0 10.20/0 5.80/15 3.80/10 3.22/5 0.86/60 5.7/0 0.27/0 0.1/100

34.9/0 12.2/0 0.4/0 19.0/20 11.5/30 2.1/50 2.7/25 1.1/70 0.8/70 7.25/10 0.2/100

26.13/1 4.52/0 0.44/0 1.76/0 44.1/25 5.29/60 10.8/100 2.54/100 2.09/90 2.32/1 1.43/100

a As received. b Based on the elemental analysis of the fuels assuming that the capture of chlorine in ash is 100%.28

phases were considered in the calculations with respect to their likely presence and likely significance as driving factors in the slagging and fouling: Liquid solutions (2): • Silicate melt (SLAG-A): major oxide components: SiO2Al2O3-CaO-MgO-FeO(Fe2O3) + additional components Na2O, K2O + S (as dissolved sulfide ion) • Salt melt (SALT-F): (K, Na)(SO4, CO3, Cl, OH) Solid solutions (5): • (Na, K)2(SO4, CO3) (ss) • (Na, K)(Cl) (ss) • Complex silicates (wollastonite, olivine, mulite) Stoichiometric compounds (214): • 96 solid compounds • 118 gas compounds Derived specific melt phase characteristics of cofiring blends are then combined with predicted temperature profiles in the boiler for indicating the boiler regions where deposition is likely. Results and Discussion

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Figure 3. Predicted temperature profile.

Figure 4. Impact of cofiring on (a) relative heat transfer coefficient calculated for clean heat surfaces and (b) fouling tendency of ashes (relative effectiveness number).

Figure 5. The melt phase characteristics of the investigated fuels.

heat surfaces) and fouling tendency of ash (relative thermal effectiveness number) calculated for the primary superheater of the investigated boiler are shown in Figure 4. In spite of increasing the overall heat transfer coefficient for higher cofiring ratio, the ash fouling factor seems to have a more significant impact, especially for coal/sewage sludge blends, causing the decrease of heat transfer while giving higher temperatures in the boiler’s convective section. As a consequence of biomass cocombustion, the temperature profile of the combustion gas can vary, changing the boiler efficiency as well as the boiler’s operational temperatures for superheated/reheated

steam and the streams of spray water injected into the attemperators. Slagging and Fouling Characteristics. The relationship between the temperature of the flue gases, the percentage substitution, and the potential for slagging and fouling was derived using a thermo-chemical analysis based on the FactSage5.4 databases. Figure 5 shows the amount of predicted melt base phase for the investigated fuels derived from two mechanisms: melting of complex compounds (mainly silicates) as shown in Figure 5a and from condensation of alkali salts as highlighted in Figure 5b.



Figure 6. Predicted slagging and fouling characteristics when cofiring coal/sewage sludge blends.

Figure 7. Predicted slagging and fouling characteristics when cofiring coal/sawdust blends.

Figure 8. Mass flows of spray water injected to attemperators.

The slagging and fouling potential has been assessed by calculating the amount of molten phase in the condensed ash approaching the tube banks. As experimentally shown (according to Tran et al.),30 the ash deposition ratios increase rapidly when the percentage of molten phase in the condensed ash is around 15%. Thus, this value was set up as a baseline for likely

slagging and high-temperature fouling presence in the boiler. In the case of the high- and low-temperature fouling predictions, these are more complex since the combined mechanisms (inertial (30) Tran, H. N.; Mao, X.; Kuhn, D. C. S.; Backman, R.; Hupa, H. Pulp Paper Can. 2002, 103 (9), 29–33.

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Figure 9. Predicted boiler efficiency and a flue gas temperature at the outlet of boiler.

impact, condensation etc.) can be significant and can contribute to ash depositions. For this work, the changes in the amount of molten phase (g/kg fuel) in condensed ash were analyzed to assess the trend and scale of likely ash deposition for cofired different fuel blends. The highest potential for slagging was observed for sewage sludge due to both the melt phase ratio close to or exceeding 15% (in the range of 1200-1800 °C) and high ash content in comparison with other investigated fuels. The results obtained also indicated that sewage sludge may generate elevated risk of high temperature fouling, in contrast to the sawdust whose slagging/fouling characteristics are relatively benign. The relationship between the amount of melt phase occurring as a function of predicted gas temperature along the average gas path of the boiler for 10 and 20% of sewage and sawdust cofiring ratio are presented in Figures 6 and 7. For both cofiring fuels and analyzed substitution ratios there may be a risk of slagging occurring in the region of the platen superheater (SH2) where the level of melt phase is about 15%. The main impact on this is the ash melting characteristic of the base fired fuel (coal), which produces results on the borderline of slagging occurring in the SH2 region (Figure 5). The differences arise from the quantitative analysis of the melt phase per mass of fired fuel. Higher ratios of cofiring of sewage sludge may cause increases in the amount of slag per kg of fuel, as well as an increased risk of elevated fouling in the SH3 and RH2 regions while in turn reducing fouling in RH1 caused by condensation of alkali salts from coal combustion. An analysis of the melt phase distribution in the boiler for sawdust cofiring shows the positive impact of higher substitution ratios on reducing slagging, as there is a decrease in the melt

Plaza et al.

phase per fuel mass. Only a relatively small increase of fouling is noticed in the RH2 and SH1 regions of the boiler. It is a quite likely that the predictor’s slagging predictions are underestimated, in terms of the amount of molten phase existing in the region of the boiler where temperature exceeds 1300 °C. It is due to the fact that the current model analyzes the melting behavior of only those silicates that may interact with gaseous alkali species at elevated range of temperatures. For this work, according to the literature, it was assumed that 15% of total nonreactive ash can react with gaseous alkalis, reach equilibrium conditions, and contribute to the molten phase.27 However, under these conditions the remaining alumina silicates and other iron-based species may be partially molten as well, even without reaction with volatilized alkalis.26 In this case, more sophisticated correlations regarding the kinetic parameters of mineral matter transformation, in particular related to viscosity changes, should be incorporated into the model, a development for the future. Prediction of the viscosity of complex silicates as a function of relevant parameters such as the residence time, size of the particles, and the given temperature regime is highly challenging. Additional kinetic characteristics would improve the slagging predictions, in particular for the fuel mixtures with high silica content, such as coals, and for low levels of biomass cofiring. Boiler’s Operational Parameters. Different heat transfer conditions for cofiring may lead to changes in the boiler efficiency as well as the temperatures of superheated/reheated steam causing necessary changes to the spray water injected into the attemperators. Predicted mass flows of the spray water needed to cool down the superheated/reheated steam to the system design levels are shown in Figure 8. Analyzing the results, it was observed that for higher cofiring ratio of sewage sludge the steam superheated temperatures decrease, whereas for 5% substitution the reheated steam temperature fell below the nominal value. For sawdust cofiring the opposite was predicted, revealing that for higher cofiring ratio the temperature is raised and more injected water is needed to obtain design temperatures for the superheated steam. The reason for this is related to better heat transfer conditions in the convective section (despite slightly increased deposition) due to increase velocity and heat transfer coefficient in comparison with pure coal. The predicted boiler’s efficiency for different cofiring ratios for sewage sludge and sawdust is presented in Figure 9. Calculations revealed that 20% sewage sludge cofiring may lead to a decrease of efficiency up to 4%, which results in around 25 MW thermal of lost power. The lower efficiency drop for sawdust cofiring suggests that this renewable fuel may be used without causing operation problems. The largest impact on efficiency arises from the temperature at the outlet of the boiler (behind the air heater), which was predicted to be about 50 °C higher due to ash deposition and worsened heat transfer conditions for 20% sewage sludge cofiring. Conclusions Slagging and fouling effects when cofiring coal/biomass blends can, at high levels of substitution, reduce boiler efficiency and availability. The development of reliable and relatively quick response prediction tools will allow operators of large pulverized coal fired utility boilers to increase the use of diverse biomass fuels cofired in existing boilers by pinpointing potential areas of elevated slagging and fouling risk. The efficient integration of a zone-based method with thermo-chemical calculations can lead to such a prediction tool.


However, it should be always kept in mind that there are several limitations to thermodynamic equilibrium analysis applied to ash behavior during cofiring. The knowledge of the kinetics of the transformation of mineral mater from solid fuels and their blends is crucial to conducting really reliable equilibrium analysis and obtaining correct indicators. Chemical fractionation of the ashes from biomass fuels and input into the model of only the reactive fraction plus part of nonreactive ash is one of the attempts of approaching the real equilibrium state of the ash mixture that can exist in high-temperature pulverized fuel boilers. Experimental measurements are still needed for this matter, especially with relation to coal/biomass ash mixture behavior.


In spite of the mentioned limitations, the thermodynamic equilibrium calculation is a powerful tool when combined with the zone-based model. It provides a useful guide to at least the qualitative nature of ash transformation history in the boiler and can successfully indicate furnace regions where slagging and deposition is likely. Acknowledgment. The support of the European Union for the “INECSE” programme is gratefully acknowledged via contract No. MEST-CT-2005-021018. The work originated from the PowerFlam 1 and 2 programmes with the support of the European Union, ENEL, Italy, EDF, France, and Electrabel Belgium. EF8010383

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