An Agglomeration Index for CaO Addition (as CaCO3) to Prevent

Aug 4, 2014 - Agglomeration of ash in fluidized bed combustors may result in defluidization and subsequent downtime of the installation. Previous rese...
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An Agglomeration Index for CaO Addition (as CaCO3) to Prevent Defluidization: Application to a Full-Scale Poultry Litter Fired FBC Pieter Billen,*,† José Costa,‡ Liza van der Aa,‡ Luc Westdorp,‡ Jo Van Caneghem,§ and Carlo Vandecasteele† †

Department of Chemical Engineering, KU Leuven (University of Leuven), Willem de Croylaan 46, 3001 Leuven, Belgium BMC Moerdijk, Middenweg 36a, 4782 PM Moerdijk, The Netherlands § Materials Technology Cluster, Group T, KU Leuven (University of Leuven), A. Vesaliusstraat 13, 3000 Leuven, Belgium ‡

ABSTRACT: Agglomeration of ash in fluidized bed combustors may result in defluidization and subsequent downtime of the installation. Previous research has shown that Ca-based additives can prevent agglomeration, but the added amount was determined arbitrarily and testing occurred only on lab scale or pilot scale. This paper presents a statistical approach, based on a newly developed agglomeration index, to calculate the amount of CaO that should be added (in the form of a Ca-based mineral, e.g., CaCO3) to the fluidized bed in order to prevent agglomeration. The agglomeration index is based on an understanding of the reactions occurring in the ash, for instance, the formation of potassium silicates with low melting points, and the formation of calcium phosphates and calcium silicates with high melting points. Full-scale testing of partial replacement of silica sand by calcite (CaCO3) as fresh bed material showed that the increased CaO concentration in the ash, with respect to normal operation, appears to reduce both wall and in-bed agglomeration problems. As a measure for agglomeration risk, differential bed pressure variations were statistically analyzed. In the test periods during which CaCO3 was added, the bed pressure variations were smaller and less frequent, and the severity of agglomeration was thus reduced. The proposed strategy can be applied for fuels that are commonly perceived as difficult or unsuited for fluidized bed combustion, and also for other additives than CaCO3, e.g., Al-based minerals.

1. INTRODUCTION Agglomeration of ash in fluidized bed combustors (FBCs) can cause defluidization of the bed and subsequent downtime of the installation. Research by Visser et al.1 showed that partial melting of ash coatings on bed particles is the cause of coatinginduced agglomeration. Indeed, e.g., alkali silicates (e.g., K2Si4O9) may melt at typical bed temperatures of 700−750 °C, causing multiple particles to stick together.2,3 In contrast, the formation of calcium silicates (e.g., CaSiO3, Ca3Si2O7, Ca2SiO4)4 in the bed ash can result in complex silicate compounds (e.g., K2CaSiO4, K4CaSi3O9)4,5 with higher melting points than the initial alkali silicates. For fuels with a high phosphorus concentration, e.g., manure, corn stover, and oat straw, the formation of calcium silicates is limited, as thermodynamically more stable calcium phosphates (e.g., Ca3(PO4)2) form preferentially. Billen et al.2 showed that, this way, the presence of phosphates reduces the amount of calcium silicates and, therefore, shifts the composition in the ternary CaO−K2O−SiO2 diagram toward low-melting potassium silicates. Assuming the reactions (formation of phosphate and silicate salts) are terminated, the influence of the formed calcium phosphates on the melting points of the formed silicates, and vice versa, is not documented adequately enough in the literature and is mostly neglected in order to obtain a manageable description of the agglomeration mechanisms. Figure 1 illustrates the above for a poultry litter fired FBC.6 In the present paper, it is not our intention to reinvestigate the exact agglomeration mechanisms. Instead, after shortly introducing earlier research results of Billen et al.2,6 as background, we will use these results of thermodynamic © 2014 American Chemical Society

Figure 1. Ternary CaO−K2O−SiO2 diagram with composition of normal bed ash (white dots) and of agglomerates (black dots) from a poultry litter fired FBC. The solid contour line delimits an area with solidus temperatures below 1000 °C, and the dashed contour line delimits an area with solidus temperatures below 800 °C.6

calculations and lab experiments as a basis to develop, test, and evaluate practical countermeasures, in the full-scale FBC. The concentrations of the main ash forming elements in the fuel and in the bed ash, i.e., silica sand bed particles coated with combustion ash, from the poultry litter fired FBC are shown in Table 1. Approximately 35 wt % of the bed ash consists of SiO2 Received: March 19, 2014 Revised: August 4, 2014 Published: August 4, 2014 5455

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melt-induced agglomeration1 (because it is initiated by molten HPO42− and H2PO4− salts in the fuel ash), mainly causes in-bed agglomeration,6 and can be seen as a concretization of earlier descriptions by, e.g., Grimm et al.11 Addition of Ca-based salts to the ash increases the melting temperatures of the formed silicate mixtures in the ash and, therefore, reduces the coating-induced agglomeration problems in an FBC. This was shown earlier by lab-scale and pilot-scale research,6,12−14 highlighting the beneficial effects of CaO addition (in the form of a Ca-based mineral) to ash. However, in all of these lab-scale and pilot-scale experiments, to our knowledge, the added amount of Ca-based salts was only determined arbitrarily. Moreover, to our knowledge, reported full-scale experiments or successful applications of this countermeasure are scarce, with only Hagman et al.15,16 showing limestone addition to a 50 MWth circulating fluidized bed combustor. The present paper discusses full-scale tests of addition of CaO, added as calcite (CaCO3), to the bed material of a 115 MWth bubbling FBC firing poultry litter. Two types of agglomeration, in-bed agglomeration and wall agglomeration, occur in the installation and are caused by different mechanisms, melt-induced agglomeration and coating-induced agglomeration, respectively.6 After addition to the fluidized bed, calcite decomposes to give CO2 and CaO, the latter reacting with unstable HPO42− and H2PO4− salts from the poultry litter to Ca(PO3)2 or Ca3(PO4)2. When all phosphate was thus consumed, calcium silicates are formed with the remaining CaO. On the basis of this understanding, a novel agglomeration index is presented for use as a criterion for CaO addition. Statistical analysis of the difference between this agglomeration index for formed agglomerates and for nonagglomerated bed ash resulted in a theoretically optimal amount of calcite addition to the FBC. The evaluation of a full-scale test, during which silica was partly replaced by calcite as fresh bed material, was performed via temporal analysis of the differential bed pressure. Calcite addition to the bed might influence fouling of, e.g., superheaters,17 though this effect is not studied in the present paper.

Table 1. Average Concentrations (with Standard Deviation) of the Main Ash Forming Elements in the Fuel (Poultry Litter), Sampled Several Times per Week, in the Bed Ash, Sampled Weekly during the Period of 24 months, and in Agglomerates, Sampled after Several Shutdowns, Analyzed after Acid Digestion6,18 [wt % of ash]

Ca Mg K Na P S Cl a

fuel

bed ash

agglomerates

(415 samples)

(105 samples)

(53 samples)

± ± ± ± ± ± ±

16.5 ± 5.3 2.0 ± 0.5 7.8 ± 2.2 1.6 ± 0.3 3.7 ± 1.0 2.0 ± 1.0 0.62a

21.0 3.7 14.0 2.2 6.7 0.7 0.5

4.9 0.9 3.2 0.3 1.2 0.1 0.1

15.3 2.8 9.0 2.2 7.3 0.4 0.1

± ± ± ± ± ± ±

2.8 1.0 4.1 0.8 1.5 0.3 0.3

Only 1 bed ash sample analyzed for Cl concentration.

added as fresh bed material (calculated by mass balance).6 For clarity, the present paper focuses, similarly to Billen et al.,2 only on the four main ash forming elements, mostly expressed as their oxides: CaO, K2O, P2O5, and SiO2. The speciation, indicating which salts are formed by the ash elements, of agglomerates (of which the average element concentration of the main ash forming elements is shown in Table 1), sampled during several shutdowns of the FBC, and of bed ash samples was thermodynamically calculated by Billen et al.,6 using data from the FactSage7 databases, Sandström et al.,8 and Jung and Hudon.9 The concentrations of the formed calcium and potassium silicates were plotted in a ternary CaO−K2O−SiO2 diagram (Figure 1) by Billen et al.6 The plotted Ca concentration equals the total Ca concentration of the ash minus the fraction that reacted to the more stable calcium phosphates. The solid contour line delimits an area with solidus temperatures below 1000 °C (typically, the temperature of the freeboard above the fluidized bed), and the dashed contour line delimits an area with solidus temperatures below 800 °C (slightly above the average bed temperature of 760 °C). These solidus contour lines were deduced from the well-known CaO− K2O−SiO2 phase diagram of Morey et al.,10 where the liquidus and solidus temperatures can be consulted in detail. In the remaining part of the diagram, the solidus temperatures exceed 1000 °C, meaning that melt formation cannot occur at typical operational temperatures of an FBC. The agglomerates (black dots in Figure 1) have a significantly higher P concentration than the bed ash, resulting in lower calcium silicate concentrations, which leads to lower melting temperatures. This is apparent in the lower part of the phase diagram, near the K2O−SiO2 axis. Besides coating-induced agglomeration due to the formation of low-melting silicates, Billen et al.6 described a second agglomeration mechanism, according to which unstable HPO42− and H2PO4− salts present in the fuel directly melt at the bed temperature and cause multiple particles to stick together by liquid interparticle bridges. By reaction of these molten salts with Ca salts from the bed ash particles, in the liquid interparticle bridges, solid Ca3(PO4)2 is formed, the most stable phosphate salt among the alkaline earth phosphates in the ash.6 This way, the interparticle bridges are solidified, creating agglomerates in an irreversible way. This mechanism, identified by Billen et al.6 in lab experiments, can be classified as

2. MATERIALS AND METHODS The installation of BMC in Moerdijk, The Netherlands, a 37 MWe (115 MWth) FBC biomass power plant, was described in detail by Billen et al.6,18 The combustor is fed with 1100 t/day of poultry litter (with a lower heating value of 7.0 ± 0.6 MJ/kg and an ash concentration of 11.8% of the wet fuel), together with 25 t/day of silica sand (approximately 80% between 0.55 and 0.90 mm) as fresh bed material. The bed temperature is 750−765 °C, whereas the temperature in the freeboard sometimes exceeds 1000 °C. Seventy tonnes per day of bed ash is extracted at the bottom of the fluidized bed. The residence time of the bed ash is approximately 26 h. Agglomeration occurs mainly to the wall, according to the mechanism of coating-induced agglomeration, but also in the bed, according to the mechanism of melt-induced agglomeration,6 as illustrated in Figure 2. Visual observations of the FBC indicated that defluidization mostly occurs when large agglomerates, adhered to the wall, break loose, fall into the bed, and disturb the air distribution. The fuel (from the bunker) and the nonagglomerated bed ash (i.e., sand particles coated with ash, sampled at the conveyor screw below the ash extraction hoppers, located below the fluidized bed) were, during normal operation, sampled on a weekly basis by BMC. Agglomerates were sampled in the bed after several shutdowns. Element analysis of the fuel, bed ash, and agglomerates was done by Laboratorium Zeeuws-Vlaanderen in The Netherlands. Element concentrations were measured after dissolution in aqua regia. K, Mg, 5456

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the routine weekly analyses. The bed ash samples were directly dissolved in aqua regia and then analyzed. On a daily basis, a representative sample of the fuel was ashed in the laboratory at 550 °C, and the ash was dissolved and then analyzed.

3. RESULTS AND DISCUSSION 3.1. Tracking the Bed Ash Composition to Explain Agglomeration. In an attempt to understand agglomeration problems leading to defluidization, the bed ash was analyzed on a regular basis (at least once per week) for the most important elements with respect to agglomeration, expressed as the oxides K2O, CaO, and P2O5. The aim of these ash analyses was to quantify the agglomeration risk, in order to allow countermeasures, such as CaO addition, to be taken timely. The K2O, CaO, and P2O5 concentrations (in stoichiometric sense) in the bed ash samples are plotted in Figure 3. The analyses started in February 2010 and covered a period of more than 2 years. During this period, several shutdowns due to bed agglomeration problems occurred, indicated by the vertical lines in Figure 3. As the shutdowns generally lasted less than 2 days, for reasons of clarity, only one vertical line at the start date is shown. The K2O, CaO, and P2O5 concentrations in the bed ash varied strongly, with relative standard deviations (as % of the average value) of ca. 30%. The concentrations of K2O and P2O5 seem to be correlated, indicating the presence of potassium phosphates in the poultry manure. The strong variation of the CaO concentration is probably caused by different ratios of manure from broiler and layer hens being supplied. The manure from layer hens contains more Ca (ca. 26 wt % of the ash) than that of broiler hens (ca. 13 wt % of the ash).19 This hypothesis is sustained by the fact that the composition of the fuel, which is a varying mixture of manure of broiler and layer hens, also showed significant week-to-week variations (shown later in Figure 6). As the composition of the last sampled bed ash before a defluidization related shutdown was different for every shutdown, the occurrence of agglomeration cannot be predicted accurately based only on the composition. Moreover, the most important problem in the BMC FBC is wall agglomeration (shown in Figure 2). Because of the buildup of material adhered to the wall throughout time, it is inherent

Figure 2. Schematic side view of the BMC fluidized bed, with indication of the zone where wall agglomeration occurs.6 and Na were determined using atomic absorption spectrophotometry according to NEN 7436, Ca was determined with ICP-MS, and P was determined spectrophotometrically according to NEN 7435. Chloride and sulfate were measured spectrophotometrically according to NENEN-ISO 15682 and NEN-ISO 22743, respectively. During two separate test periods, instead of pure silica sand, mixtures of silica sand (approximately 80% between 0.55 and 0.90 mm) and calcite (approximately 80% between 0.70 and 1.25 mm) were added as fresh bed material, with two different ratios (80/20 and 60/40 silica/calcite w/w). As a reference, the periods before, in between, and after the test periods were included in the analysis. The five considered time periods, all in 2013, are described in Table 2. To

Table 2. Description of the Calcite Addition Test Periods period period period period period

1 2 3 4 5

07/03 21/03 31/03 11/04 18/04

to to to to to

20/03 30/03 10/04 17/04 28/04

reference 80/20 test reference 60/40 test reference

take the effect of the residence time of the bed ash (26 h) into account, the indicated time periods were shifted 1 day further in time, starting from the beginning of calcite addition; for instance, calcite was added from 20/03 on, whereas the start of period 2 was set at 21/03. The differential pressure over the fluidized bed was measured every minute, by two pressure probes (Siemens SITRANS P-DSIII/PT6), one below the fluidized bed and one above. During the test, the bed ash and fuel were sampled and analyzed daily (i.e., more frequently than during normal operation), in the same way as described earlier for

Figure 3. Weekly variations of the concentrations of K2O, CaO, and P2O5 in the bed ash during 2010−2012. The vertical lines mark shutdowns related to agglomeration. 5457

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Figure 4. Distribution of the agglomeration index for the analyzed agglomerates and the bed ash samples (a). The arrow indicates the shift of the bed ash composition needed for reduction of the agglomeration risk, shown in (b).

to a (geometrical) locus of a composition in a CaO−K2O−SiO2 phase diagram for a varying SiO2 concentration, was calculated. The oxides between brackets in eq 1 are the concentrations in the ash (w/w). The AI gives the ratio of the CaO concentration in the ash available for calcium silicate formation, i.e., after subtraction of the concentration (stoichiometrically) reacting to Ca3(PO4)2, to the concentration of K2O, which results in potassium silicate formation. As 3 mol of CaO (molar mass approximately 56) reacts with 1 mol of P2O5 (molar mass approximately 142), the amount of CaO that reacts to Ca3(PO4)2 corresponds to 168/142 times the concentration of P2O5 in the ash (w/w). A high AI means that the silicate mixture contains a high amount of calcium silicates and has, therefore, a high melting point. This corresponds to a location high in the ternary CaO−K2O−SiO2 diagram (Figure 1 or the phase diagram of Morey et al.10).

to this wall agglomeration that the effect of low-melting species in the ash is delayed. Through inspection of the FBC, it is observed that defluidization typically occurs after a large wall agglomerate breaks loose and falls into the fluidized bed, which is a nearly unpredictable event, depending on the surface properties, viscosity, density, etc. of the agglomerates. The presence of low-melting ash species is thus responsible for buildup of the wall agglomerates, but the defluidization potentially occurs when a large piece of agglomerate falls in the bed and blocks a part of the nozzle bed. The buildup of wall agglomerates and the potentially resulting defluidization can thus only be avoided by minimizing the presence of lowmelting bed ash compositions at all times. 3.2. Toward a Predictive Agglomeration Index. At a bed temperature of about 750 °C, K 2 O with SiO 2 thermodynamically gives stable potassium silicates.2 According to Billen et al.,6 CaO preferably forms stable Ca(PO3)2, Ca2P2O7, or Ca3(PO4)2, depending on the stoichiometric ratio of CaO to P2O5, rather than forming calcium silicates. Indeed, Ca3(PO4)2 is commonly found in X-ray diffraction spectra of bed ash, sometimes in combination with CaSiO3,20,21 Only the CaO remaining after reaction to Ca3(PO4)2 reacts to form CaSiO3, if any SiO2 is left forming potassium silicates and is available for reaction.2 For this reason, CaO (in the form of CaCO3) addition might not reduce the agglomeration risk when the phosphate concentration of the bed ash is high. In other words, enough CaO should be added first to form Ca3(PO4)2 and second to form calcium silicates, increasing the melting point of the silicate mixture. In this study, the amount of CaO to be added to the FBC (in a stoichiometric sense, by addition of a Ca-salt) as a preventive measure was calculated using statistical data on the composition of bed ash samples and agglomerates. The aim was to develop a strategy to reduce the risk of agglomeration at all times of operation, given the variation of the fuel composition. Therefore, an “agglomeration index” (AI, eq 1), corresponding

AI =

[CaO] −

168 ·[P2O5] 142

[K 2O]

(1)

The SiO2 concentration does not occur in the AI, as the addition of fresh bed material (silica) at a high rate causes mostly an excess of SiO2 compared to K2O and CaO. Indeed, Lynch et al.22 showed that, for bed ash from fluidized bed combustion of poultry litter, based on SEM images, only a fraction of the total amount of SiO2 (a combination of SiO2 from the poultry litter and from the fresh bed particles) reacts. This may correspond to the thermodynamic equilibrium, where K2O and the CaO, remaining after reaction with phosphate, have reacted with a stoichiometric excess of SiO2. The distribution of the AI, calculated for 54 agglomerated samples and 105 nonagglomerated bed ash samples, is given in Figure 4a. The average AI for the agglomerates is 0.25 with a standard deviation of 0.77. The normal distribution for the agglomerates is shown as the bell-shaped curve in black. The agglomerates can be both wall agglomerates and in-bed 5458

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To prevent wall agglomeration, the AI of the bed ash must increase to enhance formation of calcium rich silicate mixtures with high melting points. This can be achieved by lowering the (in stoichiometric sense) P2O5 concentration (resulting in less Ca3(PO4)2 and hence more calcium silicate formation), lowering the K2O concentration, or increasing the CaO concentration. Lowering the P2O5 and K2O concentrations is only possible by dilution or washing of the fuel, because phosphate and potassium salts are naturally present in the poultry litter. The CaO concentration in the bed ash can be increased by adding Ca containing minerals, e.g., calcite (CaCO3), to the fluidized bed. To minimize the risk of wall agglomeration of the bed ash, its AI should significantly exceed the AI of the agglomerates. The cutoff value (lowest acceptable AI) is, e.g., set (arbitrarily) at 2 standard deviations above the average AI of the agglomerates, corresponding to a value of 1.79, so that all AIs higher than this value correspond to only 2.3% of the agglomerates. If, in order to prevent agglomeration, the distribution of bed ash AIs should significantly exceed 1.79, it should be shifted so that the average is 2 standard deviations (σBA = 0.88) above this cutoff value, corresponding to an average AI of 3.55. This shift of the AI distribution of the bed ash is represented in Figure 4a by the horizontal arrow, leading to the distribution represented by the right bell-shaped curve in Figure 4b. As mentioned previously, the AI can only be increased by addition of CaO. The amount of CaO to be added (ZCaO) can be calculated from eqs 2−4, where the subscript “BA” indicates nonagglomerated bed ash, “aggl” indicates agglomerated samples, and overlines represent average values. By adding a fixed amount of CaO to the bed ash, the shape of the distributions, and hence their standard deviation, remains unchanged.

agglomerates, as these cannot be differentiated when sampled in the bed during a shutdown. The average AI for the bed ash samples is 1.52, with a standard deviation of 0.88. The corresponding normal distribution for the bed ash samples is shown in gray in Figure 4a. The average AI from the agglomerates thus differs significantly from that of the bed ash (a t test with both averages equal as null hypothesis resulted in p < 0.001). The distribution of the agglomerates is rather wide, as they may be formed by the coating-induced or the melt-induced mechanism. The AI has only a predictive/ explanatory value for coating-induced agglomeration, as this mechanism is strongly dependent on the ash composition or, more specifically, the concentration of potassium silicates and calcium silicates in the ash. On the other hand, many bed ash samples should have given rise to wall agglomeration problems, also resulting in a wide distribution of the AI. We assume that bed ash compositions with low AI potentially caused wall agglomeration, as their AI is similar to that of agglomerates. Recall that the effect of wall agglomeration on the bed operation is always delayed. Given the wide distributions of the AI for both the agglomerates and the bed ash, it is our goal to reduce the overlap, by increasing the AI of the bed ash during normal operation. A low AI means that the formed potassium and calcium silicate mixture has a low melting temperature, corresponding to a composition near the K2O−SiO2 axis in the CaO−K2O− SiO2 phase diagram. The locus of the average AI of the agglomerated samples, for a variable SiO2 concentration, is shown in Figure 5 as the solid line near the K2O−SiO2 axis.

AIBA,new = AIaggl + 2·σaggl + 2·σBA (CaO + ZCaO) − K 2O ZCaO = 20 wt %

168 ·P O 142 2 5

= 3.55

(2)

(3) (4)

In the case where the added CaO replaces part of the silica sand that is used as fresh bed material, the total mass of the bed ash is unchanged. Therefore, increasing the CaO concentration to 43.5 wt % (the initial 23.5 wt %, being the Ca concentration of 16.5 wt % in the bed ash (Table 1) expressed as CaO, with addition of ZCaO) by replacing silica sand does not alter the concentrations of P2O5 and K2O. With 70 t/day of extracted bed ash, 14 t/day of CaO should be added, replacing 56 wt % of the 25 t/day of silica sand fresh bed material. The corresponding amount of CaCO3 to be added should, therefore, be 35 t/day, which is more than the amount of fresh bed material that is currently used. In that case, during normal operation, only 2.3% of the bed ash throughout time is expected to have an AI below the threshold value of 1.79 (Figure 4b), meaning that only this fraction has a composition that resembles the agglomerates, and hence might cause wall agglomeration. This is a large improvement compared to the situation without the addition of CaCO3 to the bed ash, where 73% of the bed ash samples had a composition similar to the agglomerates and, therefore, potentially caused wall agglomeration. The partial replacement of silica sand with CaCO3 shifts the locus of the average bed composition in the silicate ternary

Figure 5. Locus of the average composition with variable SiO2 concentration of the agglomerates (straight line), the bed ash (dashed line), and the bed ash with added CaO (dashed-dotted line) in the ternary CaO−K2O−SiO2 diagram.

The locus of the average AI of the bed ash samples (dashed line in Figure 5) is located much higher in the diagram. Despite the fact that the averages apparently differ, Figure 4 shows that many bed ash samples have an AI within the distribution of the agglomerated samples. Bed ash with these AIs, and, therefore, a similar composition to that of agglomerates, may, therefore, cause wall agglomeration, without being directly detected as problematic because defluidization does not occur immediately. 5459

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Figure 6. Daily variations of (a) the CaO concentration in the bed ash and the ashed fuel and (b) the AI of the bed ash, during the five test periods.

Table 3. Results of the Calcite Addition Test CaOBA / CaOfuel , with standard error period period period period period

1 2 3 4 5

0.88 1.16 1.04 1.21 0.79

± ± ± ± ±

0.08 0.13 0.07 0.12 0.13

average AI, with standard deviation 2.15 1.81 2.24 4.16 1.93

± ± ± ± ±

1.24 0.85 0.74 1.36 1.44

average bed pressure, with standard deviation [mbar] 127.4 127.4 127.0 126.3 126.5

± ± ± ± ±

2.6 2.7 2.9 2.7 3.0

average squared difference between subsequent pressure measurements, with standard deviation [mbar2] 0.16 0.05 0.10 0.07 0.08

± ± ± ± ±

0.68 0.19 0.64 0.23 0.32

illustrates that the CaO concentration in the bed ash and ashed fuel samples varies strongly from day to day. Unfortunately, the measured CaO concentrations in the bed ash did not increase strongly during the test periods 2 (80/20) and 4 (60/40). Especially in period 2, the CaO concentration in the bed ash drops below 20 wt %, caused by a low CaO concentration of the fuel. The low CaO concentration in this period has its effect on the AI of Figure 6b, which is, on average, the lowest in period 2 (Table 3). On the contrary, despite the suboptimal amount of calcite added to the bed, for the aforementioned reasons of precaution, the AI of the bed ash in period 4 was higher than that in any other period, even higher than the minimal AI of 3.55 as calculated in section 3.2, enabling a test evaluation. This high AI in period 4 is partly caused by the composition of the poultry litter (a low P2O5 concentration in combination with a high CaO concentration), due to deviations thereof throughout time. The difference between the bed ash compositions (expressed by the AI) between period 2 and period 4, due to variations of the incoming fuel, allows a comparison and may explain the underlying agglomeration mechanisms, although this was not the main aim of the full-scale test.

diagram from the dashed to the dashed-dotted line (Figure 5), corresponding to silicate mixtures with high melting points. 3.3. Increase of CaO Concentration during Full-Scale Test. To validate the proposed CaO addition (as CaCO3) as a means of preventing agglomeration and resulting bed defluidization, a full-scale test was performed in the poultry litter fired FBC described in section 2. As it was the first test in this full-scale installation, the added calcite amounts (80/20 and 60/40 silica/calcite; see Table 2) were kept lower than the value theoretically calculated in the previous section. Indeed, changing the bed material composition can cause unwanted side effects on, e.g., the hydrodynamics of the fluidized bed, which are beyond the scope of this study. The CaO concentration in the bed ash sampled on a daily basis throughout the full-scale test is shown in Figure 6a. As a measure for what the CaO concentration in the bed ash would be without CaCO3 addition, the CaO concentration of laboratory ashed fuel samples is given. It should be kept in mind that the ashed fuel CaO concentration is higher than the bed ash concentration without addition of CaCO3, mainly because of dissolution by silica sand bed material. Figure 6 5460

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Figure 7. Measured differential bed pressures during the five test periods, 1 measurement every minute.

deviations of the pressure measurements in the five periods are similar, as shown in Table 3. Although the standard deviation is a common measure for variations, it does not describe the difference between slowly fluctuating measurements, due to, e.g., increasing or decreasing bed mass, and short, sudden variations. Therefore, also the difference between two subsequent bed pressure measurements was calculated for the entire time span of the test. These differences are squared, to enlarge the relative weight of sudden, large fluctuations in differential bed pressure. The distribution of this parameter (the squared difference) is described by the average and the standard deviation, given in the fifth column of Table 3, and serves as a measure for the pressure fluctuations and hence the severity of agglomeration in each period. In contrast with the expectations, based on the low AI for period 2, the behavior of the bed pressure was indeed more stable in both periods 2 and 4. This might be observed in Figure 7 but is quantitatively shown in Table 3. For these periods, where silica/calcite mixtures were used as fresh bed material, both the average and the standard deviation of the squared differences between pressure measurements are lower than in the control periods (1, 3, and 5) (Table 3, column 5). The average values of the squared difference between pressure measurements differ significantly, as each period corresponds to approximately 10 000 measurements, and therefore, the error of the mean is very small. The lower this average is, the less sudden pressure changes, which possibly indicate agglomeration, occur. In the control periods, the average is higher (Table 3, column 5), meaning that short, sudden pressure changes are more likely to occur, and the larger standard deviation means that larger peaks (i.e., peaks with a higher amplitude) occurred in these periods. Because the pressure variations in the periods where a 60/40 and 80/20 silica/calcite mixture is used as a fresh bed material were smaller and slower, it appears that the calcite effectively reduced agglomeration problems, assuming that large sudden pressure fluctuations are related to agglomeration, as mentioned earlier. However, the AI of the bed ash during period 2 (Figure 6b, Table 3) did not predict a reduction of coating-induced agglomeration problems, i.e., wall agglomeration. Given the fact that, during this period, the amount of sudden pressure variations is significantly reduced, we conclude that the addition of CaCO3 not only counteracts wall

The actual increase of the CaO concentration in the bed ash with respect to normal operation is described by the ratio of average CaO in the bed ash to average CaO in the ashed fuel ( CaOBA / CaOfuel ). The relative error for this ratio is calculated by the sum of squared standard errors for both averages (the CaO concentration of the bed ash and of the ashed fuel). The added CaCO3 was effectively retained in the fluidized bed and resulted in an increase of the CaO concentration of the bed ash, as indicated by the results in Table 3. 3.4. Quantitative Evaluation of Full-Scale Test. Although the CaO concentration in period 2 was lower than expected, the first qualitative experience showed that the bed operation appeared more stable (smaller temperature and pressure variations) to plant operators during periods 2 and 4. During full-scale tests, a defluidization would have large consequences and can, therefore, not be provoked for the purpose of test evaluation, contrary to pilot-scale and lab-scale tests. This hampers straightforward evaluation of the test. Statistically sound conclusions could only be drawn after multiple defluidization related shutdowns, causing large expenses, which may exceed the potential benefits related to the test. This calcite addition test was, therefore, besides the quantitative evaluation of the CaO concentration in bed ash samples discussed in section 3.3, evaluated by analyses of online pressure measurements. In the case of a positive evaluation of the test in this paper, prolonged addition of CaO during normal operation could show the effect on the defluidizations in the long run. Fluctuations of the differential bed pressure in FBCs are common, due to superficial gas velocity variations, bubbling behavior, and agglomeration. This makes prediction of agglomeration problems not straightforward, requiring highfrequency pressure measurements and statistical techniques as described in Bartels et al. 23 However, the fact that agglomeration increases the frequency and amplitude of pressure fluctuations24 gives the opportunity to use them also for test evaluation, i.e., retrospectively. Figure 7 shows the differential bed pressures, measured once every minute, for the five periods of the test, as described in Table 2. The gap of the pressure measurements in the beginning of period 3 is due to failing pressure measurement equipment. It seems from Figure 7 that the bed pressure fluctuates more frequently in periods 1 and 3, but the standard 5461

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ACKNOWLEDGMENTS Grateful acknowledgement is made for providing measurement data and for financial support to BMC Moerdijk (The Netherlands).

agglomeration but is also effective against in-bed (meltinduced) agglomeration. In-bed agglomeration occurs when HPO32− salts, which are present in the poultry manure ash, melt and form liquid bridges between multiple bed ash particles. The contact of liquid HPO32− salts with CaO from the bed ash results in the formation of solid Ca3(PO4)2. Hence, a solid permanent bridge is formed between the bed ash particles, resulting in an agglomerate. Instead of reacting with multiple bed ash particles and forming solid interparticle bridges, as described by Billen et al.,6 the molten HPO32− salts react during test periods 2 and 4 with separate, added CaO/CaCO3 particles, reducing the extent of agglomeration.

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REFERENCES

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4. CONCLUSIONS A strategy was developed to determine the amount of CaO to be added to an operating, full-scale fluidized bed combustor, combusting poultry litter, a fuel with a high P concentration. The main problem leading to defluidization in this installation is wall agglomeration, caused by low-melting potassium silicates. The strategy was based on a newly developed agglomeration index, taking into account the thermodynamically viable reactions for the most important oxides (in this case, CaO, SiO2, P2O5, and K2O) of the ash. The distance between the distributions of the agglomeration index of the bed ash and the agglomerates was considered a measure for agglomeration propensity. Reducing wall agglomeration problems can be achieved by shifting the bed ash AI distribution, e.g., by adding 20 wt % of CaO (e.g., as CaCO3) to the bed ash. This results in only 2.3% of the bed ash having a composition similar to that of agglomerates, potentially causing agglomeration. Without addition of CaO, 72.9% of the bed ash compositions were similar to the composition of agglomerates. The newly developed agglomeration index can thus provide a set point for the addition rate of Ca-based salts to fluidized bed combustors, as a countermeasure against agglomeration. The agglomeration behavior during a full-scale test using two different silica/calcite mixtures (80/20 and 60/40, w/w) as fresh bed material was evaluated based on the differential bed pressure variations. Large, sudden bed pressure variations occurred more frequently during the control periods, where only silica sand was used as fresh bed material, indicating more agglomeration problems. When calcite was used, the pressure variations were smaller, so less agglomeration occurred. Analysis of the relation between the agglomeration index and the bed pressure variations showed that addition of calcite to the fluidized bed combustor counteracted both wall agglomeration and in-bed agglomeration. The results from this paper illustrate that calcite addition is a promising countermeasure for the agglomeration problems in the poultry litter fired fluidized bed combustor. Prolonged calcite addition during normal operation should show whether the number of defluidizations can effectively be reduced.

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*E-mail: [email protected]. Tel: +32 16 322353. Fax: +32 16 322991. Notes

The authors declare no competing financial interest. 5462

dx.doi.org/10.1021/ef500621w | Energy Fuels 2014, 28, 5455−5462