Energy & Fuels 1993, 7,746-754
746
Predicting Ash Behavior in Utility Boilers Steven A. Benson,* John P. Hurley, Christopher J. Zygarlicke, Edward N. Steadman, and Thomas A. Erickson Energy and Environmental Research Center, University of North Dakota, P.O. Box 9018, Grand Forks, North Dakota 58202-9018 Received April 8,1993. Revised Manuscript Received September 8,199P
In recent years, significant advances have been made in the development of methods to predict ash behavior in utility boilers. This paper provides an overview of methods used to assess and predict ash formation and deposition. These prediction methods are based on a detailed knowledge of ash formation and deposition mechanisms that has been obtained through bench, pilot, and field testing and detailed coal and ash characterization. The paper describes advanced methods of coal and ash analyses and the advantages of these methods over conventional methods. The advanced coal characterization methods provide sufficient data to predict size and composition distribution of fly ash. The composition and size data are used as inputs to mechanistic models which ultimately predict deposition propensities in various locations of utility boilers. Advanced indices based on advanced coal analysis data have also been developed and are being applied to predict convective pass fouling tendencies.
Introduction Ash formation, ash deposition on heat-transfer surfaces, and ash collectability have been examined for many years, resulting in voluminous literature. However, a precise and quantitative knowledge of the chemical and physical transformations of the inorganic components in coal during combustion has not been obtained, owing to the inability to obtain quantitative analyses of the inorganic composition of coal and resultant ash and the complexity of the physical and chemical processes involved. At the present time, accurate prediction of the fate of the inorganic constituents during combustion as a function of coal composition and combustion conditions is not possible using currently accepted methods of analysis. For example, the bulk composition of the coal ash (produced under ASTM ashing conditions) is used in most methods as a crude guide to predict the behavior of inorganic constituents of a specific coal during combustion. While the ASTM ashing technique can be used to predict average properties of the ash, all of the inorganic components are combined and allowed to interact during the ashing process. The bulk chemical analysis often proves inadequate when examining ash behavior. Examination of fly ash produced during coal combustion shows that many different types of particles are present, each having its own composition and, probably, its own behavior in combustion systems. The wide variation of fly ash types is related to the wide variability in the abundance and distribution of inorganic constituents in the coal. The extent of ash-related problems depends upon the quantity and association of inorganic constituents in the coal and combustion conditions. The inorganic constituents are distributed within the coal matrix in several forms, including organicallyassociated inorganic elements, coal-bound (included) minerals, and coal-free (excluded) minerals. The types of inorganic components depend upon the rank of the coal and the environment in which the coal Abstract published in Adoance ACS Abstracts, October 15, 1993.
was formed. During combustion, the inorganic materials are transformed into inorganic gases, liquids, and solids. These species produced during the combustion process are referred to as intermediates. Studies of the final ash product (fly ash) indicate a bimodal size di~tribution.'-~ The submicron-size particles form as a result of homogeneous condensation of flame-volatilizedspecies. Flamevolatilized species may also condense heterogeneously on the surfaces of large particles. The larger particles, sometimes referred to as residual ash, are largely derived from mineral grains. The compositionand size distribution of the larger particles result from transformations or interactions between discrete mineral grains in higherrank coals. In lower-rank coals, both the interaction of the organically associated elements with mineral grains and mineral-mineral interactions occur. Ash-Forming Constituents in Coals. The ashforming components in coals have been referred to as mineral matter, minerals, inherent/extraneous ash, and other names by the many individuals who work with coal. The range of nomenclatures of the inorganic constituents in coal is as diverse as the perspectives of the individuals describing them. In this paper, the term inorganic constituents will be used to describe all ash-forming constituents in coal, including both organically associated inorganic species and mineral grains. The inorganic constituents in coal occur as discrete minerals, organically associated cations, and cations dissolved in pore water. The fraction of inorganic constituents that are organically associated varies with coal rank. Low-rank coals (subbituminous and lignitic) have high levels of oxygen relative to high-rank coals. Ap(1)Sarofim, A. F.;Howard, J. B.; Padia, A. S. The Physical Transformation of the Mineral Matter in Pulverized Coal Under Simulated Combustion Conditions. Combust. Sci. Technol. 1977,16,187-204. (2) Flagan, R. C.; Friedlander, S. K. Particle Formation in Pulverized Coal Combustion-A Review. In Recent Deoelopments in Aerosol Science; Shaw, D. T., Ed.; New York Wiley-Interscience,1978;Chapter 2, pp 25-59. (3) Damle, A. S.;Ensor, D. S.; Ranade, M. B. Coal Combustion Aerosol Formation Mechanisms: A Review. Aerosol Sci. Tech. 1982,1,119-133.
Q887-0624/93/ 25Q7-Q746$Q4.QQ/Q 0 1993 American Chemical Society
Predicting Ash Behavior in Utility Boilers
proximately 25 76 of the oxygen in low-rank coals is in the form of carboxylic acid groups. These groups act as bonding sites for cations such as sodium, magnesium, calcium, potassium, strontium, and barium (other minor and trace elements may also be associated in the coal in this form). In addition, some elements may be in the form of coordination complexes with pairs of adjacent organic oxygen functional groups. The cations originate from the plant material from which the coal was formed and from groundwater filtering through the coal seam. In some lowrank coals,the organically associated inorganic components can constitute up to 60% of the total inorganic content of the coal? In higher-rank coals, bituminous and anthracite, the inorganic Components consist mainly of minerals. In order to predict the behavior of the inorganic constituents during combustion, detailed information must be obtained on the abundance, size, and association of mineral grains in the coal. In addition, the association of the mineral grains within the coal matrix must be determined and classified. A mineral associated with the organic part of a coal particle is said to be included. A mineral that is not associated with the organic material is referred to as excluded. An additional term that has been used to describe the association of minerals is juxtaposition,5 referring to the general association of minerals to coal and to other minerals. For example, a single coal particle may contain several minerals such as quartz, kaolinite, and pyrite. The methods used to determine the association of inorganic components in coals have evolved significantly over the past 80 years. The early methods involved concentrating the inorganic components for chemical analysis using ashing or gravity separation techniques. These methods are fraught with errors and do not provide quantitative information on the associationand abundance of inorganic components in coals. Recently, more advanced methods, such as computer-controlled scanning electron microscopy (CCSEM16 and chemical fractionation: are being used to more quantitatively determine the abundance, size, and association of inorganic components in coals. The CCSEM and chemical fractionation techniques are providing a quantitative determination of the inorganic composition of the coal that allows for more effective prediction of the behavior of the inorganic components during combustion. Formation of Ash Intermediates. Inorganic components in coal undergo complex chemical and physical transformations during combustion to produce intermediate ash specie^.^ In order to predict the effects of inorganic constituents on combustion systems, the mechanisms by which the size and composition of intermediate ash species are formed must be elucidated. The size and composition of the intermediate ash species directly influence slagging and fouling problems in combustion systems. (4)Beneon, S.A.; Holm,P. L. Comparison of Inorganic Constituents in Three Low-Rank Coals. 2nd. Eng. Chem. Rod. Res. Deu. 1986,24, 145. (5) Jones, M. L.; Kalmanovitch, D. P.; Steadman, E. N.; Zygarlicke, C. J.;Benson,S. A. ApplicationofSEMTechniquestotheCharacterization of Coal and Coal Ash Products. In Aduances in Coal Spectroscopy; Meuzelar, H. L. C., Ed.; New York Plenum Press, 1992. (6) Zygarlicke, C. J.; Steadman, E. N. Advanced SEM Techniques to Characterize Coal Minerals. ScanningElectronMicrosc. 1990,4(3),579590. (7)Benson, S. A.; Jones, M. L.; Harb, J. N. Ash Formation and Deposition. InFundamentalsof Coal Combustionfor CleanandEfficient Use; Smoot,D., Ed.; The Netherlande: Elsevier SciencePublishing, 1992; Chapter 4.
Energy & Fuels, Vol. 7, No. 6, 1993 747
The physical transformations involved in fly ash formation include coalescence of individual mineral grains within a char particle, shedding of the ash particles from the surface of the chars, incomplete coalescence due to disintegration of the char, convectivetransport of ash from the char surface during devolatilization, fragmentation of the inorganic mineral particles, formation of cenospheres, and vaporization and subsequent condensation of the inorganic components upon gas cooling. As a consequence of these interactions, the resulting ash has a bimodal size distribution. The submicron component is largely a result of the condensation of flame-volatilized inorganic components. The mass mean diameter of the larger particles is approximately 12-15 pm, depending upon the coal and combustion conditions. The larger-sizeparticles have been called the residual ash by some investigators1because these ash particles resemble, to a limited degree, the original minerals in the coal. Deposition Phenomena in Utility Boilers. The characteristics of a deposit depend upon the chemical and physical characteristics of the intermediate ash species, geometry of the system (gas flow patterns), gas temperature, gas composition, and gas ~ e l o c i t y .Deposits ~ that form in the radiant section are called slag deposits. Deposits that form in the convective pass on steam tubes are called fouling deposits. Slag deposits are usually associated with a high level of liquid-phase components and are exposed to radiation from the flame. Slag deposits are usually dominated by silicate liquid phases but may also contain moderate to high levels of reduced iron phases. In addition, the initiating layers of slag deposits may consist of very fine particulate and may produce a reflective ash layer. Fouling deposits form in the convective passes of utility boilers and, in most cases, do not contain the predominance of liquid usually associated with slaggingtype deposits. The minor amounts of liquid contained in fouling deposits usually consist of silicates and sulfates that bind the particles together. The formation of these deposits on heat-transfer surfaces can significantly reduce heat transfer. Heat transfer through a deposit is related to the temperature and the physical and chemical properties of the deposited material, since these factors affect the thermal conductivity, emissivity, and absorptivity of the deposit. Several different types of ash-fouling deposits form in the convective passes of coal-fired boilers, but they all fall into two main categories. The first is often called hightemperature or conventional fouling. It normally occurs on the upstream sides of steam tubes but can bridge tubes across the gas flow. This type of fouling only occurs near the front of the convective pass. The second is termed low-temperature fouling, which occurs on tubes toward the back of the pass, especially when high-calcium coals are fired. Low-temperature fouling can occur on upstream or downstream sides of tubes. The most-striking difference between the two categories of deposits is in their compositions. Figure 1 shows the concentrations of silicon, calcium, and sulfur in deposits as a function of local gas temperature. The deposits were collected from steam tubes in the convective pass of a midwestern boiler that was firing a high-calcium subbituminous coal. All deposits were taken from the upstream sides of tube surfaces except the one a t 1400 O F , which was collected from the downstream side of a steam tube. The values are listed as oxide weight percents on an SOs-free basis (SO3 is
748 Energy &Fuels, Vol. 7, No. 6, 1993
Benson et al. (a)
Si02
K lot
\ Temperature ('F)
Figure 1. Concentrationsof silicon, calcium, and sulfur in offline deposits @Os-freeoxide basis). included for comparison). The data show that the concentrations of silicon and calcium in the upstream deposits increase slightly with temperature in the pass, possibly because calcium silicate particles are stickier at higher temperatures and so are more likely to stick to the boiler surfaces they contact than other ash particles. The changes in sulfur concentration are much more dramatic. The deposita collected from positions that were at or below approximately 1900 O F contain much higher concentrations of sulfur than those collected from higher-temperature regions.* Through laboratory thermogravimetric analysis, it was found that the increase occurs not because the dew point of sulfate species has been reached but because below that temperature some of the alkali and alkaline elements (Na, K, and Ca) are more stable as condensed sulfates than as silicates. The ash collected from the downstream side of a tube has the highest sulfur content, most likely because it could not be eroded or soot-blown and so had the most time to sulfate. The CaO/ SO3 ratio indicates that the calcium was fully sulfated. Because it presents an easy demarcation parameter, the sulfur content of the deposits is used to define the zones of high-versuslow-temperature fouling. By this definition, low-temperature fouling occurs below approximately 1900 OF in a boiler firing a high-calcium subbituminous coal. Some viscous sintering of silicate glasses in the ash may continue below this temperature, but the deposits from these temperatures are typically dominated by the presence of sulfated ash. Advanced Methods of Coal Inorganics and Product Analysis. The application of new analytical techniques has resulted in data and mechanistic insights that have advanced our understanding of ash behavior in utility boilers. At the present time, accurate prediction of the fate of inorganic constituents during combustion as a function of coal composition and combustion conditions is not possible using standard, bulk ash chemistry methods of analysis. High-temperature ashing is currently used routinely to determine the abundance of inorganic constituent/s present in coal. This technique involves oxidizing the coal at 1023 K (750 "C) and chemical analysis of the resultant ash. There are several major errors involved in this type of analysis. First, significant transformations of the inorganic components occur during the ashing process. The loss of mass due to water loss from clay minerals, carbon dioxide loss from carbonates, and (8)Hurley, J. P.; Benson, S. A.; Mehta, A. Ash Deposition at Low Temperatures in Boilers Burning High-Calcium Coals. The Impact of Ash Deposition of Coal-FiredPZants;TheEngineeringFoundation: New York, 1993; in press.
Coo (b)
Si02
Figure 2. Composition of ASTM ash and fly ash for Eagle Butte subbituminous: (a) ASTM ash; (b) fly ash. sulfur loss from pyrite can significantly influence the determination of the inorganic content of the coal. The organicallyassociated inorganic elements such as the alkali and alkaline earth elements absorb oxygen and SO2 during the ashing processes, further complicating the determinations. In addition, these species (H20, C02,and SO21 are usually included as volatiles in the proximate analysis, leading to erroneous results. Several investigators have developed empirical methods based on the composition of the ash and losses due to decomposition of minerals to estimate the inorganic content of coals as summarized by Given and Y a r ~ a b Furthermore, .~ the analysis of the bulk ash provides only an average composition of the ash, while the fly ash composition varies on a particle-byparticle basis. Figure 2 compares the composition of the ASTM ash and the composition of individual fly ash particles in a ternary diagram for an Eagle Butte subbituminous coal. The fly ash was produced by combusting the coal in a laminar flow drop-tube furnace. Details of this work can be found in Steadman and others.'O Coal ash deposits in utility boilers are the result of very complex processes involving very complex materials. In order to understand the ash deposition process, one must first have knowledge of both the materials and system conditions involved. This necessitates a combined ma(9) Given, P. H.; Yarzab, R. F. Analysis of the Organic Substance of Coals: Problems Posed by the Presence of Mineral Matter. In Analytical Methods for Coal and Coal Products, 2nd ed.; Karr, C. J., Ed.; New York Academic Press, 1978; Chapter 20, pp 3-41. (10) Steadman, E.N.;Benson, S. A.; Zygarlicke,C. J. Digital Scanning Electron MicroscopyTechniquea for the Characterization of Coal Minerals and Coal Ash. Presented at the Low-Rank Fuels Symposium, Billings, MT, May 20-23, 1991,16 pp.
Predicting Ash Behavior in Utility Boilers
terials science and process engineering approach. Since the transformations in mineral matter that take place in coal utilization are so complex, detailed analyses of the coal, intermediates, and deposits are needed in order to completely understand the ash deposition process. New, more advanced methods allow for a more complete description of these components and mechanisms. As a result of these improvements in characterization techniques and our understanding of the critical mechanisms, better predictive indices and models are being developed. The formation of deposits in utility boilers is the result of the interaction of deposited ash intermediates. The intermediate species form the microscopicparticles which, in turn, can be deposited on a microscopic scale. Therefore, in order to understand the process associated with ash deposition, we must examine ash deposits microscopically. Because scanning electron microscope and electron microprobe analysis (SEM/EMPA) provides both morphologic and chemical information on a micrometer scale, the SEM/EMPA as well suited to the characterization of complex materials such as coal minerals and inorganic combustion products. Several automated SEM/EMPA and automated image analysis (AIA)techniques have been developed to quantify coal and ash minerals.616J@-16 The automated SEM/EMPA techniques rely on the analysis of statistically representative numbers of particles to produce quantitative data on their size and chemistry. Three SEM/EMPA techniques-computer-controlled scanning electron microscopy (CCSEM),scanning electron microscopy point count (SEMPC), and automated image analysis (AIAI-are presently used in ash behavior research of combustion and gasification systems at the Energy and Environmental Research Center (EERC). These techniques permit the study of transformations of inorganic constituents from the initial stages of coal conversion through the transformations that occur during ash deposition and slag formation. Their specific applications include (1)determination of the size, composition, and association of minerals in coals; (2) determination of the size and composition of intermediate ash components; (3) determination of the degree of interaction (sintering) in ash deposits; and (4) identification and quantification of the components of ash deposits and slags, including liquidphase composition, reactivity, and crystallinity. By using SEM/EMPA for coals, and throughout all stages of utilization, a continuity of data is achieved. CCSEM6 is used to characterize coal samples and (11) Steadman, E. N.; Zygarlicke, C. J. Benson, S. A.; Jones, M. L. A Microanalytical Approach to the Characterization of Coal, Ash, and Deposita. InProceedings ofthe SeminaronFirestoneFouling Problems; ASME Research Committee on Corrosion &Deposita from Combustion Gases: Washington, DC, 1990. (12)Huffman, G . P.; Shah, A.; Shah, N.; Zhao, J.; Huggins, F. E. Investigation of Ash by Microscopic and Spectroscopic Techniques. Presented at Engineering Foundation Conference, The Impact of Ash Deposition on Coal Fired Plants, Solihull, Birmingham, U.K., June 2025, 1993, 23 pp. (13) Huggins, F. E.; Huffman, G. P.; Lee, R. J. Scanning Electron Microsope-BasedAutomated Image Analysis (SEM-AIA) and Mbsbauer Spectroscopy-Quantitative Characterizationof Coal Minerals. In Coal and Coal Products: Analytical Characterization Techniques; Washington, DC: American Chemical Society, 1982; Chapter 12, pp 239-258. (14) Huggins, F. E.; Kosmack, D. A.; Huffman, G. P.; Lee, R. J. Coal Mineralogies by SEM Automatic Image Analysis. Scanning Electron Microsc. 1980,1, 531-540. (15) Lee, R. J.; Huggins, F. E.; Huffman, G. P.;CorrelatedMoeabauerSEM Studies of Coal Mineralogy. Scanning Electron Microsc. 1978,1, 561-568. (16) Shah, N.; Huffman, G. P.; Huggins, F. E.; Shah, A. Graphical Representation of CCSEM Data for Coal Minerals and Ash Particles. Prepr. Pap-Am. Chem. SOC.,Diu. Fuel Chem. 1991, 36(1), 165-172.
Energy & Fuels, Vol. 7, No. 6,1993 749
inorganic combustion products. The analysis is usually conducted on a polished cross section of coal-epoxy plug. A computer program is used to locate, size, and analyze particles. Because the analysis is automated, a large number of particles can be analyzed quickly and consistently. The heart of the CCSEM analysis system is an annular backscattered electron detector (BES). The BES system permits a high degree of resolution between sample components based on their atomic numbers, which allows coal minerals to be easily discerned from the coal matrix and fly ash particles to be easily discerned from epoxy in polished sections. Brightness and contrast controls are used to optimize threshold levels between the coal matrix and mineral grains or fly ash particles. When a video signal falls between these threshold values, a particle is discerned and the particle center located. A set of eight rotated diameters about the center of the particle are measured, and the particle area, perimeter, and shape are calculated. The beam is then repositioned to the center of the particle, and an X-ray spectrum is obtained. The information is then stored to an ASCII Print file for data reduction and manipulation. The CCSEM data provide quantitative information concerning not only the mineral types that are present but their size and shape characteristics as well. Since the same analysis can be performed on the initial coal and resultant fly ash, direct comparisons can be made and inorganic transformations inferred. The primary method used to characterize deposits is the scanning electron microscope/microprobe. The SEM is capable of imaging deposits and determining the chemical composition of areas within deposits down to 1 pm in size. The use of the SEM is extremely valuable in identifying materials responsible for deposit initiation, growth, and strength development, as well as the characterization of significant slag properties such as reactivity and viscosity. The SEM technique is used to characterize entrained ashes and deposits is SEMPC.6J7 This technique was developed to quantitatively determine the relative number of phases present in ashes and deposits. The method involves microprobe analysis, for chemical compositions, of a large number of random points in a polished cross section of a sample. This technique provides information on the degree of melting and interaction of the various deposited ash particles and provides quantitative information on the abundance of phases present in the ash. The chemical interactions and transformations ascertained by the SEMPC provide information on the degree of melting and interaction through the identification and classification of the relative abundance of phases based on chemical composition. By examining the phases present, the material responsible for the formation of the deposit can be identified. In addition, various regions in deposits and individual entrained ash particles can be examined to determine the changesthat occurred with time and changes in coal composition. In addition, X-ray diffraction is used to determine the crystalline phases present in the deposit as a support for the SEMPC analysis. Bulk chemical analysis of the deposit is also performed with x-ray fluorescence (XRF). XRD and XRF provide independent checks on the validity of the SEMPC analysis. (17)Kalmanovitch, D. P.; Montgomery, G. C.; Steadman, E. N. Computer-Controlled Scanning Electron Microscope Characterization of Coal Ash Deposita. 87-JPGC-Fact-4, 1987, 8 pp.
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The CCSEM and SEMPC techniques are supplemented with morphological and chemical analysis of the microstructural features of the deposit. This is performed either by manually scanning across the sample, elemental mapping, or AIA. Automated digital imaging allows for the rapid, objective collection of digital images. Once the digital images hvae been collected and saved to disk they can be manipulated in many constructive ways. Numerous applications for the digital images have been implemented at the EERC. Two methods, using AIA to enhance the utility of the CCSEM and SEMPC techniques, are described below. The CCSEM technique described above is used for the standard analysis of coal. However, more detailed analysis of the coal minerals may be necessary. During pulverization of the coal, some coal minerals are liberated from the coal matrix. The mineral grains liberated from the matrix will experience different conditions and undergo different transformations and reactions than the minerals present within the coal matrix. The present method used to determine the includedl excluded and juxtaposition of the coal mineral matter involves the standard CCSEM analysis of the coal. However, prior to the analysis of each frame examined, a digital backscattered image is obtained and saved to a TN8500 image analysis system. As the CCSEM analysis proceeds, each particle analyzed is identified on the image. The data can then be modified to include juxtapositional relationships. The SEMPC technique does not provide all the information needed to fully characterize a deposit or other material. I t is also important to examine the morphology and physical relationships of the microscopic components of the deposit. While the SEMPC technique quantifies the chemistry and phase distributions, the morphologic characterization of deposits reveals the size, crystallinity, and juxtaposition of the phases present. The morphologic investigation of the deposits provides insight into the sintering process, as evidenced by the growth of necks between particles and the formation of a captive surface. An analysis18 developed at the EERC combines the SEMPC analysis with the morphological investigation. This new technique is combined with the current SEMPC technique, automatically collecting digital images of each frame analyzed and saving them to disk. After the analysis is complete, the location of the analysis points can be plotted, allowingfor a detailed composition/morphological investigation. In addition, automated applications are being designed to quantify neck growth and porosity in deposits and liquid-phase determinations. Quantification of the type and abundance of organically associated inorganicelements in lower-ranksubbituminous and lignitic coals is currently performed by chemical fra~tionation.~ Chemical fractionation is used to selectively extract elements from the coal based on solubility, which reflects their association in the coal. Briefly, the technique involvesextracting the coal with water to remove water-soluble elements such as Na in sodium sulfate or those elements that were most likely associated with the groundwater in the coal. This is followed by extraction with 1M ammonium acetate to remove elements such as (18) Galbreath, K. C.; Brekke, D. B.; Folkedahl, B. C. Automated Analytical Scanning Electron Microscopy and Image Analysis Methods for Characterizing the Inorganic Phases in Coals and Coal Combustion Products. P r e p . Pap-Am. Chem. SOC.,Diu. Fuel Chem. 1992,37(3), 1170-1176.
Benson et al.
Na, Ca, and Mg that may be bound as salts of organic acids. The residue of the ammonium acetate extraction is then extracted with 1 M HC1 to remove acid-soluble species such as Fe and Ca which may be in the form of hydroxides, oxides, carbonates, and organically coordinated species. The components remaining in the residue after all three extractions are assumed to be associated with the insoluble mineral species such as clays, quartz, and pyrite. Predicting Ash Behavior. A number of purely operational options are available to reduce ash-related problems in coal-fired boilers. Some examples are switching or blending coals, using additives, or changing the temperature profile of the boiler. Predicting the effects of a proposed operational change is difficult; even though a variety of empirical indices involving simple ASTM analyses have been used, the complex nature of coal requires that finding the most economicalsolution involves some experimentation. However, experimentation with a 500-MW boiler is a complicated proposition, and often times, the failures can be expensive or the solutions chosen may not be the most efficient. Therefore, computer simulations of key parameters affecting ash deposition are often used to reduce the size of the experimental matrix. There are several other research groups that are investigating improved methods to predict ash behavior.lSz6 Advanced Indices. The EERC has derived indices that rank low-rank coals according to their fouling propensity in utility boilers.26 The approach taken was to gain a very complete inorganic characterization of discrete minerals and organically associated inorganic components in selected coals and to compare the performance of the coals, if possible, at the utility scale. Full-scale boiler performances was based on the general degree of fouling and the ability of the unit to maintain load. An index was derived that correlates certain applicable parameters of the (19)Barta, L.E.; Beer, J. M.; Sarofim, A. F.; Teare, J. D.; Toqan, M. A. Coal Fouling Tendency Model. Presented at Engineering Foundation Conference, The Impact of Ash Deposition on CoalFired Plants, Solihull, Birmingham, U.K., June 20-25,1993,12p. (20) Beer, J. M.; Sarofim, A. F.; Barta, L. E. From Coal Mineral Matter Properties to Fly Ash Deposition Tendencies: A Modeling Route. In Inorganic Transformations and Ash Deposition During Combustion; Bemon,S. A.,Ed.; NewYork AmericanSocietyofMechanicalEngineers, 1992;pp 71-94. (21)Helble, J. J.; Srinivasachar, S.;Boni, A. A.; Bool, L. E.; Gallagher,
N.B.;Peterson,T.W.;Wendt,J.O.L.;Huggins,F.E.;Shah,N.;Huffman,
G. P.; Graham, K. A.; Sarofim, A. F.; Beer, J. M. Mechanisms of Ash Evolution-A Fundamental Study. Part I1 Bituminous Coals and the Role of Iron and Potassium. In Inorganic Transformations and Ash DepositionDuring Combustion; Benson, S. A., Ed.; New York American Society of Mechanical Engineers, 1992;pp 229-248. (22)Helble, J. J.; Srinivasachar, S.; Boni, A. A.; Kang, S. G.;Graham, K. A.; Sarofim, J. F.; Beer, J. M.; Gallagher, N. B.; Bool, L. E.; Peterson, T. W.; Wendt, J. 0. L.; Shah, N.; Huggins, F. E.; Huffman, G. P. Mechanisms of Ash Evolution-AFundamental Study. P a r t 1 Low Rank Coals and the Role of Calcium. In Inorganic Transformations and Ash Deposition Durirq Combustion; Benson, S. A,, Ed.; New York American Society of Mechanical Engineers, 1992; pp 209-228. (23)Loehden, D. 0.; Walsh, P. M.; Sayre, A. N.; Beer, J. M.; Sarofim, A. F. Generation and Deposition of Fly Ash in the Combustion of Pulverised Coal. J. Inst. Energy 1989,119-127. (24)Walsh, P. M.; Sayre, A. N.; Loehden, D. 0.;Monroe, L. S.; Beer, J. M.; Sarofii,A. F. Deposition of Bituminous Coal Ash on an Isolated Heat Exchanged Tube: Effects of Coal Properties on Deposit Growth. Bog. Energy Combust. Sci. 1990,, 16, 327-346. (25)Abbott, M. F.; D o u g h , R. E.; Fink, C. E.; Delullis, N. J.; Baxter, L. L. A Modeling Strategy for Correlating Coal Quality to Power Plant Performance and Power Costs. Presented a t Engineering Foundation Conference, The Impact of Ash Deposition on Coal Fired Plants, Solihull, Birmingham, U.K., June 20-25,1993, 13 pp. (26)Weisbecker, T.; Zygarlicke, C. J.; Jones, M. L. Correlation of Inorganics in Powder River Basin Coala in Full-Scale Combustion. In Inorganic Transformations and Ash Deposition During Combustion; Benson, S. A., Ed.; New York ASME for the Engineering Foundation, 1992;pp 699-711.
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Predicting Ash Behavior in Utility Boilers
inorganic composition and the general performance or experience at the full-scale utility boiler. These indices are in the development phase at this time; however, experience has provided evidence for certain trends in coal inorganic composition that lead to convective pass fouling in utility boilers. Because of the additional detail in the analyses used, the indices provide a much more reliable method for predicting the fouling behavior of coal compared to conventional indices, which are based on simplistic ASTM coal analysis data. The usefulness of these indices has been demonstrated by their repeated use by several utilities in the midwest United States that are screening Powder River Basin coals for use in their coal-fired boilers. A low-temperature index has been developed which pertains more to fouling that would occur in lower-temperature regions of a boiler, such as in the primary superheater or economizer. A high-temperature index has been formulated which pertains to fouling in higher-temperature zones, such as in the secondary superheater or reheater. The calculation of these indices is such that a higher value is indicative of greater fouling propensity in a boiler. The criteria used in developing the indices and their relation to combustion behavior can be summarized as follows: 1. Sodium content: organicallybound Na quickly enters the vapor phase as a hydroxide or sulfate and interacts with silica or aluminosilicates in deposits to potentially cause accelerated deposit growth and strength development, especially in higher-temperature zones of the convective pass where silicate-based deposition occurs. 2. Calcium content: organicallybound Ca quicklyreacts with aluminosili~ates~~ and quartz,28within coal particles, to form lower melting point phases which may enhance deposit formation. Calcium, dependent upon its association with other elements or compounds, will react with sulfur in lower-temperature zones to form calcium sulfatebased deposit^.^^^^^ 3. Total mineral content: this refers to discrete minerals which may have a diluting effect on deposit strength if their ratio to the organically bound content is greater than 1.0. 4. Organically bound content: the refers to inorganic constituents that are intimately associated with the organic structure of the coal. They usually have a greater potential for reaction with other minerals that are within coal particles. Also, their finely divided inorganics are more apt to be partitioned into the finer-sized fly ash, causing them to be more readily transported to deposition areas in the convective pass regions of a boiler. 5. Small quartz content: a general observation that has been made is that smaller-sized quartz grains provide a larger surface-area-to-volume ratio for reaction with organically bound Ca and Na within coal particles, which may create lower melting point phases on the surface of the quartz particles. 6. Juxtaposition of minerals: quartz and clay minerals have more of a tendency t o react with organicallyassociated cations for lower melting point phase production when (27) Hurley, J. P.; Erickson, T. A.; Benson, S.A,; Brobjorg, J. N. Ash Deposition at Low Temperatures in Boilers Firing Western U.S. Coals. Presented at the International Joint Power Generation Conference, San Diego, CA, 1991, 8 pp. (28) Zygarlicke, C. J.; McCollor, D. P.; Benson, S. A.; Holm,P. L. Ash Particle Size andcomposition EvolutionDuring Combustionof Synthetic Coal and Inorganic Mixtures. In Twenty-Fourth Symposium (International) on CombustionlThe Combustion Institute; Pittsburgh, PA, 1992; pp 1171-1177.
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;
i 0
Dietz
Wyodak
Figure3. High-temperature and low-temperaturefouling indices (high-temperature index, 0-10 low, 10-20 medium, 20+ high; low-temperatureindex, 0-50 low, 50-200 medium, 200+ high).
they are included within coal particles rather than excluded from coal particles. 7. Calcite content: large excluded mineral grains of calcite may act as a diluting agent for deposit strength and also may increase viscosityof liquid phases in a deposit which would decrease the sintering and deposit strength. Finer-sized included calcite, however, reacts with silicates to depress silicate liquid viscosities29which can enhance ash stickiness and deposit formation. 8. Clay content: this includes all of the aluminosilicate minerals that may facilitate production of lower melting point liquid phases if combined with organically bound cations such as K, Na, and Ca. This actual algorithm for calculating the indices is not available for publication at this time because of proprietary constraints. Figure 3 displays the low- and high-temperature indices for four ACERC coals and two Powder River Basin (PRB) coals. The index valves are interpreted as follows: for the high-temperature index 0-10 implies low fouling tendencies, 10-20 implies medium fouling with definite losses in efficiency, and 20+ implies high fouling. For the lowtemperature index, 0-50 indicates low fouling, 50-200 indicates medium fouling, and 200+ indicates high fouling. The Dietz and Wyodak coals are subbituminous coals from Montana and Wyoming, respectively, the Beulah coal is a North Dakota lignite, the Utah Blind Canyon coal is a Utah bituminous coal, and the PRB coals are from southern and middle parts of the Powder River Basin. The unnamed PRB coals, Beulah lignite, and Wyodak have known utility boiler experience. The Beulah is notorious for high-temperature fouling, and the Wyodak seam has produced intermediate to serious front end fouling in some utility boilers. The index agrees with these observations (Figure 3). The other coals are low fouling coals, according to the index and utility boiler experience. According to the low-temperature index, Beulah may experience moderate deposition and the southern PRB serious deposition in lower temperature regions of the boiler. The other coals are predicted to have no appreciable low-temperature deposition. This type of index works well in a relative sense for specific boilers, and to optimize the utility of the index, modifications are being made to add boiler type and (29) Zygarlicke, C. J.;Ramanathan,M.;Erickson,T.A. FlyAshParticleSize Diatributionand Composition: Experimentaland Phenomenological Approach. In Inorganic Transformations and Ash Deposition During Combustion; Benson, S . A., Ed.; ASME, 1992; pp 469-471.
752 Energy & Fuels, Vol. 7,No. 6,1993
Benson et al.
Table I. Chemical Composition of ACERC and Other Coals Dietz
Wyodak
Beulah
Utah Blind Canyon
middle PRB
eouthem PRB
30.8 0.9 0.5 35.4 0.5 11.7
14.1 1.6 0.3 15.9 17.9 37.5
18.0 1.4 0.1 41.7 0.8 25.0
14.9 2.6 7.4 16.2 7.8 11.5
45.2 0.1 0.0 12.3 0.4 26.1
44.5 0.5 0.3 24.1 1.5 3.5
12.5 4.5 2.2 0.3
11.3 2.9 1.5 0.2
10.6 4.7 10.3 0.2
3.8 1.0 2.3 0.1
21.5 7.0 0.5 0.2
18.3 7.3 0.7 0.0
36.0 20.8 4.9 2.2 0.7 13.3 4.5 2.2 0.3 1.49 4.1 3.2
28.7 15.5 10.2 1.2 1.2 15.1 3.6 1.5 0.8 22.0 9.1 6.6 1.9 5.9 26.7
21.5 13.5 10.8 1.0 0.9 16.1 4.0 6.2 0.2 25.7 6.9 5.6 1.9 3.0 33.0
45.9 16.6 10.0 1.2 0.3 9.9 1.5 3.6 1.2 9.8 6.0 4.8 1.3 3.9 9.1
27.5 13.1 6.8 0.9 0.8 22.4 7.2 0.6 0.4 20.4 6.0 2.4 2.9 16.0 18.8
27.2 18.4 5.6 1.3 1.4 21.1 8.0 0.9 0.3 15.8 4.4 1.5 2.1 9.8 30.9
CCSEM mineralogy, wt % quartz iron oxide calcite kaolinite K Al-silicate pyrite organically bound, wt % ash SO3-free CaO
CiO Me0 N&O KzO SO3 % ash % minerals % organically bound small incl. quartz, wt % large incl. minerals, wt %
1.0 2.4 23.3
operating conditions to the index calculations. For example, the Southern PRB sometimes produces troublesome front-end or higher-temperature fouling deposits in a particular pc-fired utility boiler located in the midwestern U.S. In the same boiler, the middle PRB does not cause high-temperature fouling but does produce lower-temperature calcium sulfate-based deposition in the primary superheater and economizer sections of the convective pass. Table I lists some of the coal inorganic content that was used to derive the indices in Figure 3. The coals that have higher high-temperature fouling indices generally show more available aluminosilicate materials, sodium, and larger-sized minerals, whereas the coals with greater potential for low-temperature ash fouling are generally more enriched in calcium, magnesium, organically bound inorganics, and smaller-size available quartz (Table I). Again, these indices are in the development stage at this time, and research is ongoing. The algorithms are proprietary information at this time. Other factors need to be considered in the future. Factors involved in boiler design and combustion parameters, which have not been included, may, in some cases, far outweigh the influences of the inorganic composition. For now, the indices are only based on interactions that may occur between coal inorganic constituents during combustion and provide a more reliable screening tool for selecting coals compared to current methods that use ASTM coal data. Ash Particle Size and Composition Distribution. A computer model entitled ATRAN (ash transformations) was developed to predict the particle-size and composition distribution (PSCD) of ash produced during the combustion of coal.29330This technique used advanced analytical characterization data, boiler parameters, and a detailed knowledge of the chemical and physical trans~~
(30) Benson, S. A.; Hurley, J. P.; Zygarlicke, C. J.; Steadman, E. N.;
Erickson, T. A. Predicting Ash Behavior in Utility Boilers: Assessment of Current Status. In Proceedings of the Third International Conference on the Effects of Coal Quality on Power Plants; La Jolla, CA, Aug 25-27, 1992.
I Advanced Coal Characferization I
I
Submicron Minerals
Supermicron Minerals
1
1
I
1 Fragmentation
Fragmenfation
I
Coalescence
1
i Homogeneous Condensation
1
Heterogeneous Condensation
1
I
1
Heferogeneous Condensation
I
4
Submicron Fly Ash
Supermicron Fly Ash
I
Ash Partitioning and Mass Balance
Entrained Ash Size and Composition
Figure 4. Schematic diagram of the particlesize and composition evolution model, ATRAN.
formations of inorganic components during combustion to predict the PSCD of the resulting ash. The PSCD of the ash directly impacts deposit growth, deposit strength development, and ash collectability. A schematic diagram of the ATRAN model is shown in Figure 4. The PSCD of the ash is predicted from the abundance and distribution of the inorganic components in the coal. XRF (bulk ash composition), CCSEM, and ultimate analysis are used to characterize the coal. The CCSEM analysis is also coupled with a locked/liberated particle
Predicting Ash Behavior in Utility Boilers
analysis (todetermine if the individual mineral grains are located within a coal matrix or free mineral grains) and ZAF data reduction of the compositions. The ZAF data reduction produces compositions that are corrected for the effects of atomic number (Z), X-ray absorption (A), and X-ray fluorescence (F). A mass balance is compiled on the coal by comparing the CCSEM and XRF data. The resultant balance provides the compositions of the minerals with their associations to the coal, organically associated constituents, and submicron particles. The discrete minerals are represented by a database (size and composition) of individual particles as determined from the CCSEM analysis, while the organically associated and submicron constituents are represented by a bulk composition only. Chemical fractionation data can provide additional information on the quantity of submicron material. The discrete minerals are further divided into locked and liberated species. The discrete mineral compositions, for both locked and liberated minerals, are characterized to determine their mineralogical form. Those mineral forms which will undergo the release of vapor species and/or fragmentation will be corrected for composition changes, size reduction, and density changes (i.e., pyrite will release sulfur, fragment, and oxidizeto Fe203). The ATRAN code allows for the fragmentation of pyrite, pyrrhotite, oxidized pyrrhotite, Ca-A1-P, kaolinite, montmorillonite,gypsum, barite, calcite, dolomite, and iron carbonate. Each phase contains a different range of fragmentation values as determined experimentally. The organicallyassociated inorganicsare separated into two groupings (long-term and short-term volatile species) through a set of empirically and theoretically derived factors. The long-term volatile species will be released from the coal matrix, form oxides, and pass into the bulk gas stream as vapor species. The short-term volatile species will initially volatilize from the coal matrix but will quickly oxidize and form solid/liquid particles which will primarily remain on the receding surface of the char particles. A small amount of the short-term volatile species are released into the bulk gas stream as submicron particles. The locked minerals are randomly coalesced on a frequency basis with other minerals, submicronparticles, and those short-term volatile organicallyassociated species that remain with the receding char surface. The coalescence step produces intermediate, locked fly ash particles. The liberated particles do not undergo a coalescence step. Both the intermediate locked particles and the liberated minerals are allowed to interact with those long-term volatile organically associated species through heterogeneous condensation. Some of these organicallyassociated species are assumed to homogeneously condense as determined through empirical correlations. The three resultant data sets-locked fly ash, liberated fly ash, and submicron fly ash particles-are combined on a mass basis, producing the resultant particle-size and composition distribution of the ash. Entrained ash was sampled from the convective passes of full-scale utility boilers as part of a research program entitled “Project Calcium: Calcium-Based Deposition in Utility Boilers.” The size and composition distribution of the entrained ash produced by combusting of a Powder River Basin subbituminous coal were compared to the predictions made with ATRAN. The particle size and
Energy & Fuels, Vol. 7, No. 6, 1993 753
-
/
Actual
-o- Predicted
0 ‘
‘
I
3-10
1-3
41
>10
Particle Diameter, Microns
Figure 5. Particle-size distribution of fly ash predicted and measured in the convective pass of a tangentially fired boiler. 3 1 Microns 60
L
n J MgO I L L -K20 Na20
Oxides
Figure 6. Compositioncomparison of predicted and measured 1-to 3-pm fly ash in the convective pass of a tangentially fired boiler.
composition distributions were calculated for 20 000 particles and then were binned by size and composition for comparison with ash collected during field testing. Figure 5 shows the particle-size distribution of fly ash sampled from the convective pass of a tangentially fired boiler compared to that predicted by ATRAN. Figure 6 illustrates the composition distribution of the 1-to 3-pm particles sampled in a tangentially fired boiler to those prediced in that size range from the ATRAN code. In all, ash sampleswere compared for four different coals in both tangentially fired and cyclone-fired boilers for a total of six sampled ashes. In all six cases, the ATRAN code compared favorably in both particle size and composition. Additional case comparisons can be found elsewhere.% Ash Deposition. LEADER (low-temperature engineering algorithm of deposition risk) is a computer code designed to predict low-temperature fouling potential of a coal based on analysis of the inorganic components of the coal, boiler design, and firing rate.27 The code requires specific inputs about the amount and associations of the inorganic components in the coal. The CCSEM and chemical fractionation, along with the standard ash composition and proximate-ultimate data, are used as inputs. The code first determines the ash size and composition distributions using the ATRAN code. These distributions are then used to determine the deposition rate of the upstream inner layer and downstream deposits, strength development in these deposits, and the loss of heat exchange efficiency due to the deposits. The deposition rates are a function of the particle-size distribution of the
Benson et al.
754 Energy & Fuels, Vot. 7, No. 6, 1993
Figure 7. Output of fouling behavior for the convective pass as predicted by LEADER.
-
A simplified. advanced index to predict fouling propensity of coals has been developed. The index is based on advanced method of analysis, detailed understanding of key processes that influence fouling, and full-scale performance data. Work is continuing on further verification of the index for more coals and a wider range of combustion systems.
300
8
A
B
C
D
E
F
G
H
I
J
Coal
Coal Blended 50-50 by Ash Weight with ND Lignite
- Wscosityof Lignite Ash Figure 8.
ash and of the gas velocity and temperature. The strength development rate is a function of the composition of the deposited ash. The heat exchange efficiency loss is a function of the deposit depth and thermoconductivity. The deposit growth and strength development rates are also expressed as a shedding index (SI)equal to the ratio of the deposition rate and strength development rate. Figure 7 illustrates an output screen for various sections of the convective pass.
Summary and Conclusions The advances made over the past several years in predicting ash behavior have been made possible as a result of more detailed and better analysis of coal and ash materials. These advanced techniques, such as CCSEM, are able to quantitatively determine the chemical and physical characteristics of the inorganic components in coal and ash (fly ash and deposits) on a microscopic scale. Many of the mechanismsof ash formation, ash deposition, and ash collection in combustion systems are more clearly understood as a result of these new data. This understanding is leading to the development of better methods of prediction which include advanced indices and phenomenological models.
Phenomenological or mechanistic models have been developed and are being used to predict the effects of ash-formingconstituentsas a function of coal composition, combustion conditions, systems geometry, and operating conditions. ATRAN has been developed to predict particle-size composition distributions of ash produced in utility boilers. The results of this model have been verified with full-scale experience for both pulverized coal and cyclone-fired boilers with favorable results. ATRAN is a vital part of other methods used to predict the effects of ash species, since the particle-sizecompositiondistribution is needed to predict ash deposition. LEADER is used to predict low-temperatureconvectivepass fouling behavior. This code was developed through testing of five full-scale utility boilers that fire subbituminous coals. Future efforts will be focused on a more comprehensive model that includes waterwall slagging and convective pass fouling.
Acknowledgment. The authors thank the U.S.Department of Energy for its support, under the Combustion Inorganic Transformations project, for the development of ATRAN. The authors also thank the sponsorsof Project Calcium, who supported the field testing that led to the development of LEADER. Project Calcium sponsors include Northern States Power Co., Otter Tail Power Co., Northern Indiana Public Service Co., Wisconsin Power and Light Co., Ontario Hydro, AMAX Coal Sales Co., Cyprus Coal Co., Peabody Development Co., Babcock and Wilcox Co., The Electric Power Research Institute, and the U.S.Department of Energy.
