Article pubs.acs.org/EF
Measuring and Predicting the Slagging of Woody and Herbaceous Mediterranean Biomass Fuels on a Domestic Pellet Boiler Daniel Jose Vega-Nieva,*,† Luis Ortiz Torres,† Jose Luis Míguez Tabares,‡ and Jorge Morán‡ †
Forest Biomass Research Group, Faculty of Forest Engineering, University of Vigo, A Xunqueira Campus, 36005 Pontevedra, Spain Energy Technology Group, Faculty of Industrial Engineering, University of Vigo, Campus As Lagos Marcosende, 36310 Vigo, Spain
‡
ABSTRACT: One of the main barriers for the successful utilization of new biomass feedstocks in commercial pellet boilers is the lack of knowledge about the combustion behavior of such fuels, particularly in terms of ash slagging, which can potentially damage the boiler and limit combustion efficiency. The VI Framework European project Domoheat studied the combustion of 15 Mediterranean woody and herbaceous biomass fuels in commercial 60 kW domestic pellet boilers. The performance of several methods for the prediction of measured boiler slagging was tested, including ash composition-based slagging indices, standard ash initial deformation temperature (IDT), and a new slagging laboratory method, the BioSlag test, based on the sieving of the ash and slag obtained in the combustion of 250 g of fuel in a furnace at controlled temperature conditions. IDT values allowed us to identify slagging in fuels with high silica (e.g., rye straw pellet) or alkali contents (e.g., almond shell) but failed to discriminate medium slagging of fuels such as contaminated poplar chip. Slagging indices based on silica and alkali content of the ashes showed success for predicting boiler-observed slagging. The BioSlag test predicted observed slagging percentage in the boiler with R2 = 0.87. This test could discriminate both high slagging of fuels with high Si content (e.g., rye straw pellet, pinecone seed shell) and the medium slagging tendency caused by alkali elements (e.g., almond shell, olive stone) and by moderate Si contents (e.g., contaminated poplar chip).
1. INTRODUCTION
Ash fusion tests based on the norm ISO 540 (2008) or equivalent norms have been widely utilized for coal ashes.16 Their performance for the prediction of slagging risk in the combustion of biomass fuels, nevertheless, has been widely criticized in the literature in terms of lack of representativity of the small ash sample utilized, the low representativity of the ashing temperature utilized to generate the ash sample test and the temperature ramp and atmosphere conditions of the test, and the risk of boiler slag formation not being detected because of the changes in the shape of the small ash sample utilized in the test.31−35 Reports of low correlation of the ash fusion test results with the biomass slagging observed under the boiler combustion conditions are frequent, with many reported cases of underestimation by the test of the slagging observed in the boiler, resulting in a need for the development of more reliable new ash slagging methods.31−38 The VI Framework European project Domoheat, aimed at studying the combustion behavior of Mediterranean woody and herbaceous biomass fuels in medium- and large-scale domestic boilers, was conducted with a focus on the monitoring of biomass ash slagging in the boilers and its prediction based on ash analysis and laboratory methods. The objectives of the current study within the Domoheat project were (1) to quantify the slagging behavior of 15 Mediterranean fuels in the combustion in a 60 kW commercial domestic pellet boiler and (2) to test the performance of three laboratory and ash composition-based methods for quantifying and predicting the observed boiler slagging tendency of the fuels.
The potential of many new woody and herbaceous biomass fuels remains largely unexplored, particularly in Sothern European Mediterranean countries.1−5 One of the main barriers for the successful utilization of these new biomass feedstocks in domestic pellet boilers is the scarcity of studies on the combustion behavior of such biomass fuels,6−9 particularly in terms of ash melting and slagging, which can potentially damage the boiler and limit its combustion efficiency.10−14 Knowledge of biomass slagging is therefore important for an efficient and economically viable large-scale utilization of field crop residues and energy crops.15 Slagging occurs in the boiler sections that are directly exposed to flame irradiation.16 The mechanism of slagging formation involves stickiness, ash melting, and sintering.16,17 Fuels with large contents of silica and potassium can result in the formation of potassium silicates that can cause severe ash deposition problems at high or moderate combustion temperatures.18−21 Ash deposits deteriorate burning, retard heat transfer, cause hightemperature corrosion, and provoke mechanical failures.22,23 Therefore, the prediction of slag formation in biomass combustion is essential in order to establish the biofuel quality by the application of appropriate quality standards and to minimize the described effects in the combustion furnaces.10 Slagging indices, based on fuel ash composition, are one of the most promising tools for predicting operational slagging risk on the basis of the quantification of the chemical elements that result in the slag formation.19,24−27 Most of those indices have been derived for coal ashes, and their applicability needs to be validated for biomass ashes,16 which have different ash slagging mechanisms that are still not completely understood.28−30 © XXXX American Chemical Society
Received: November 5, 2015 Revised: December 30, 2015
A
DOI: 10.1021/acs.energyfuels.5b02495 Energy Fuels XXXX, XXX, XXX−XXX
Article
Energy & Fuels The procedure involved the use of (a) ash slagging indices, based on the composition of ash obtained at 550 and 850 °C, (b) ash initial deformation temperature (IDT) following the current standard ISO-540 (2008) method, and (c) a new ash slagging laboratory method, the BioSlag test,36 based on the sieving of the biomass ash and slag produced in the furnace combustion of 250 g of biomass fuel under controlled combustion temperature conditions.
the treatment of olive plantations in S Spain (F15). Table 1 summarizes moisture content upon receipt of the 15 fuels and observations such as the presence of high and moderate soil contamination for poplar and olive pruning chips, respectively. For the wood chips with moisture contents upon receipt above 20%, 3−4 weeks of air drying was applied to reduce the moisture contents to the values detailed in the second column of Table 1. The standards utilized for analysis are summarized in Table 2. Fuels were ground to 1 mm using a Retsch mill, and representative samples
2. EXPERIMENTAL SECTION
Table 2. Properties Analyzed for the Investigated Fuels, Units, and Standards Utilized for the Analysis
2.1. Fuel and Ash Analysis. A total of 15 fuels from northwestern (NW), central, and southern (S) Spain were selected, covering both woody fuels from plantation harvests, silvicultural treatments, and woody energy crops and representative agricultural pellets and residues from herbaceous processing industry that represent large current or potential biomass feedstock markets in Spain (Table 1). Studied fuels
Table 1. Moisture Content upon Receipt and after Drying, Origin, and Observations of the Investigated Fuels moisture content (% w.b.)a fuel sample
upon receipt
F01, pine chips
53.9
18.6
F02, eucalyptus chips F03, oak chips
35.6
17.9
24.6
16.7
24.6
15.8
31.6
16.3
F04, poplar chips F05, paulownia chips F06, rye straw pellets F07, pine (sawdust) pellets F08, oak (sawdust) pellets F09, pine with bark chips F10, pinecone chips F11, pinecone seed shell F12, almond shell F13, hazelnut shell F14, olive stone F15, olive pruning chips
after drying
origin
8.9
no drying
6.6
no drying
forest plantation (NW Spain) forest plantation (NW Spain) forest plantation (NW Spain) energy crops (central Spain) energy crops (central Spain) agricultural pellets factory (central Spain) wood pellets company (NW Spain)
7.3
no drying
wood pellets company (NW Spain)
13.9
no drying no drying no drying no drying no drying no drying 18.3
silvicultural treatments (NW Spain) silvicultural treatments (NW Spain) food company residue (S Spain) food company residue (S Spain) food company residue (S Spain) food company residue (S Spain) silvicultural treatments (S Spain)
9.1 14.2 16.4 15.1 13.6 40.5
unitsa
standard
moisture content
% w.b.
granulometric distribution higher heating value ash content initial ash deformation temperature Si, Al, Ti, Ca, Mg, Na, K, Fe, and P content of biomass ash (550 °C) and of boiler ash and slag Mn, Zn, Cu, Ni, and Cr content of biomass ash (550 °C) and of boiler ash and slag biomass and ash C, H, N content biomass and ash Cl, S content
% d.b. MJ/kg % d.b. °C % d.b.
UNE-EN 14774-1:2010, UNE-EN 14774-3:2010 UNE-EN 15149-1:2011 UNE-EN 14918:2011 UNE-EN 14775:2010 ISO 540:2008 UNE-EN 15290:2011
% d.b.
UNE-EN 15297:2011
% d.b. % d.b.
UNE-EN 15104:2011 UNE-EN 15289, EN-ISO 11885
property
observations wet chip wet chip
a
wet chip wet chip, high soil contamination wet chip
w.b. = wet basis; d.b. = dry basis
were taken for analysis following UNE-EN 14780:2012. Three replicates per sample were measured. Moisture content was determined by ovendrying samples at 105 °C for 24 h following UNE-EN 14774-1:2010 and UNE-EN 14774-3:2010. Higher heating value (HHV) was determined using a bomb calorimeter following UNE-EN 14918:2011. Following this standard, 1 g of ground sample was placed in a metal crucible of 30 mm diameter and 20 mm depth. The crucible with the sample was introduced into the bomb calorimeter, capable of measuring temperatures with a precision of 0.001 K. The HHV on a dry basis was calculated by eq 1 following UNE-EN 14918:2011: qv,gr,d = qv,gr ×
100 (100 − Maadd)
(1)
where qv,gr,d is the HHV at constant volume of the dry (moisture-free) fuel, in joules per gram, qv,gr is the HHV at constant volume of the fuel as analyzed, in joules per gram, and Mad is the moisture in the analysis sample, in percentage by mass. Ash content was determined following UNE-EN 14775:2010. A sample of 1 g of fuel ground to 2 mm was determined. 2.3. Slagging Indices. The indices listed in Table 3 were calculated on the basis of the ash composition obtained at 550 °C. 2.4. Combustion Tests and Boiler Slagging Measurement. Combustion tests were conducted in a 60 kW commercial underfed pellet burner. Every test run lasted for 24 h, resulting in fuel consumptions of up to 90 kg per test. Combustion temperatures recorded in the furnace were in the range 800−1000 °C.
The amount of deposited ash and slag in the boiler was measured after every test, and the products were collected for slag percentage determination by sieving. Boiler ash and slag samples were sieved using the same protocol described for the BioSlag test. 2.5. Models for Predicting Slagging Tendency of the Fuels from Ash Composition and from Laboratory Tests. Linear models were constructed for predicting IDT, slag percentage of BioSlag test and of the boiler from the slagging indices (3.3), and slag percentage from IDT values and from the slag percentage of the BioSlag test. Models were evaluated by RMSE and R2corr: R2corr =
slagging index
RMSE =
NaK/B
Na 2O + K 2O CaO + MgO + Fe2O3 + Na 2O + K 2O
alkali index24
(Na 2O + K 2O)A (%) HHV SiO2 + P2O5 CaO + MgO
SiP/CaMg SiPNaK/CaMg
∑ (yi − yi ̂ )2 n
where, as above, yi is the observed data, ŷi is the estimated data, and n is the number of observations.
3. RESULTS Moisture content upon receipt of fuels is shown in Table 1. Whereas pellets and agricultural shells showed appropriate values for combustion, some of the wood chips were at values above 20% and required air-drying to moistures below 20% prior to combustion. High-moisture chips are common in the NW of Spain, where high precipitation, in the range of 1500−2000 mm, occurs during all of the year. High moisture content values for wood chips have also been reported for central Spain. For example, Fernández-Llorente et al.43 reported moisture content values of 52.8% for poplar chips in central Spain. Granulometric distribution results are shown in Table 4, and fuel heating value, ash content, and elemental analysis results are shown in Table 5. The highest heating values were observed for pine and pinecone chips, whereas lower values were observed for herbaceous fuels and hardwood chips. Conifer fuels typically have higher calorific values because of their higher resin and carbon contents.42 Lower HHV values were found for contaminated olive pruning, similar to the value of 17.3 MJ reported by Fernández-Llorente et al.,10 very possibly because of the effect of increased ash content in decreasing HHV (e.g., Lousada et al.42). Clean wood chips were characterized by low ash contents, as commonly found for clean woody fuels (e.g., Werther et al.,44 Vassilev et al.45,46). As expected, chips with soil contamination showed higher ash content values, similar to the high ash values reported by other authors for soil-contaminated poplar chips (e.g., Fernández-Llorente et al.10,11,43) or contaminated olive pruning (e.g., Fernández-Llorente et al.10). Low N, S, and Cl contents were found for woody chips, with values within the ranges of 0.1−0.7, 0.01−0.4, and 0.01−0.05 reported by Vassilev et al.45 for those elements, respectively, in clean woody biomass. The largest ash content was found for straw pellet, similar to reports of values of 6−8% by other authors for this problematic fuel (e.g., Werther et al.,44 Vassilev et al.,45,46 Fernández-Llorente et al.,10 and Arvelakis et al.47). In addition, rye straw pellet biomass analysis showed high chlorine contents, similar to the values of 0.4−0.5% Cl contents reported for several straw fuels in the literature (e.g., Vassilev et al.45 and Fernández-Llorente et al.10,11,43). Almond and hazelnut shells showed ash contents of approximately 1%, similar to the range of 0.9−1.3% reported
index formulation
CaO + MgO + Fe2O3 + Na 2O + K 2O
(n − p) ∑ (yi − yi ̅ )2
where yi is the observed data, yi̅ is the mean of the observed data, ŷi is the estimated data, n is the number of observations, and p is the number of model parameters.
Table 3. Slagging Indices Calculated on the Basis of Ash Composition at 550 °C B16
(n − 1) ∑ (yi − yi ̂ )2
SiO2 + P2O5 + Na 2O + K 2O CaO + MgO C
DOI: 10.1021/acs.energyfuels.5b02495 Energy Fuels XXXX, XXX, XXX−XXX
Article
Energy & Fuels Table 4. Granulometric Distribution (Expressed in Percentage, Dry Basis) of the Investigated Fuelsa granulometric distribution (% d.b.) of fuel sample sieve size (mm)
F01
F02
F03
F04
F05
F06
F07
F08
F09
F10
F11
F12
F13
F14
F15
63 53 40 32 25 20 16 12.5 8 3.15 2 1 0.5 0.25 0.125 0.063 2 mm) from the BioSlag test and from the boiler, are shown in Table 8. The highest slagging percentage in the boiler and in the BioSlag tests was found for fuels F06 (wheat straw) and F11 (pinecone seed shell). These two silica-rich fuels showed the lowest B index values, the highest SiP/CaMg and SiPNaK/CaMg values, and IDT values of 2 mm from the BioSlag test and measured in the sieving of the boiler ash and slag.
Figure 1. Initial deformation temperature (IDT, °C) plotted against SiO2 content (left) and NaK/B index (right) of the investigated fuels. Right panel shows the predictions and confidence interval from eq [2] of Table 9.
Table 9. Equations for the Prediction of Initial Deformation Temperature and of Slag Percentage from the BioSlag Test and from the Boiler Slag Samplesa dependent variable
R2corr
RMSE
IDT = 1318.552 − 9.571*K2O IDT = 1415.136 − 877.506*NaK/B
0.552 0.657
147.636 125.418
[3] [4]
slag % (BioSlag) = 11.706 + 11.529*SiP/CaMg slag % (BioSlag) = 20.669 + 13.950*SiPNaK/CaMg
0.679 0.767
16.778 14.283
[5] [6] [7] [8]
slag % (boiler) = 12.164 + 11.738*SiP/CaMg slag % (boiler) = 6.337 + 8.869*SiPNaK/CaMg slag % (boiler) = 73.589 − 0.047*IDT slag % (boiler) = −0.556 + 0.710*slag % (BioSlag)
0.860 0.797 0.142 0.872
8.385 10.073 20.733 7.996
independent variable
eqn no.
IDT (°C)
ash composition at 550 °C
[1] [2]
slag % (BioSlag)
ash composition at 550 °C
slag % (boiler)
ash composition at 550 °C IDT (°C) slag % (BioSlag)
expression
a
IDT is the initial deformation temperature, determined following ISO-540-2008; slag % (BioSlag) is the percentage of slag >2 mm measured by the BioSlag test; slag % (boiler) is the percentage of slag >2 mm from the boiler ash deposits; and NaK/B, SiPCaMg, and SiPNaK/CaMg are slagging indices based on ash composition, as defined in Table 3.
F09), soil-contaminated wood chips (F04), clean wood pellets (F07, F08), high-Si agricultural fuels (F06, F11), and high-alkali shells (F11−F14)against SiO2 content and against NaK/B
index. It can be seen in the right-hand panel that IDT values showed a good correlation with the alkali content of the fuels measured by NaK/B, whereas no clear relationship with SiO2 G
DOI: 10.1021/acs.energyfuels.5b02495 Energy Fuels XXXX, XXX, XXX−XXX
Article
Energy & Fuels
Figure 2. Percentage of slag >2 mm measured in the boiler ash and slag (top) and in the BioSlag test (bottom) for the investigated fuels, plotted against SiP/CaMg and SiPNaK/CaMg slagging indices calculated from the ash compostion at 550 °C. Dotted lines correspond to eqs [3]−[6] of Table 9 for the prediction of slag percentage in the respective sample. Gray lines represent the confidence intervals of the equations.
showed B index values of 30−40%, similar to the 35−55% peak for B for maximum slagging stated by Pronobis.25 Clean wood chip fuels (F01−F03) and clean wood sawdust pellets (F07 and F08) presented both low silica content (Table 6) and low slagging content in the boiler and in the BioSlag test and high ash fusion temperatures (Table 8). Clean wood chips and pellets are characterized by low inherent silica content in the absence of soil contamination and are generally low slagging fuels.29,30,35,41 The lowest slagging risk of these samples corresponded to B values of 75−80%, which imply a sum of silica and acid compounds of 20−25%, similar to the critical value of silica of 25% proposed by Ö hman et al.41 On the other hand, high silica contents of close to 30% SiO2, above the 25% SiO2 threshold proposed by Ö hman et al.,41 were measured for the soil-contaminated poplar chip (Table 5), which showed moderate slagging both in the boiler combustion and in the BioSlag test (Table 8). Regarding potassium, the highest contents were found for the agricultural fuels, with the highest values for almond shell (F12) and olive stone (F14), having K contents of more than 40% measured at 550 °C ash analysis (Table 6), corresponding to a moderate slagging observed both in the boiler and in the BioSlag test, together with low ash fusion temperatures (Table 6). These two fuels, together with all the high-alkali shells with IDT values below 800 °C, could be discriminated at NaK/B values above 0.4−0.5 (Table 8). Several authors, such as Ferrnández-Llorente et al.,10,11 Vega-Nieva et al.,13,14 Vamvuvka et al.,19 Arvelakis et al.,47 and Abreu et al.,49 have reported boiler slagging and alkali melting of these potassium-rich fuels. Alkali metals react with
content was observed. The best models for the prediction of IDT from slagging indices are shown in Table 9. Alkali-based indices NaK/B and K2O content were the best indices for explaining IDT values (eqs [1] and [2] in Table 9), whereas silica-based indices showed R2 < 0.5 for the prediction of the IDT values of the investigated fuels (models not shown). The best slagging indices for explaining slag percentage both of BioSlag test and of boiler slag were the silica-based indices SiP/CaMg and SiPNaK/ CaMg, as shown in Table 9 (eqs [3]−[6]) and Figure 2, whereas alkali-based indices had R2 < 0.5 for the prediction of the slag percentage of the fuels of study. IDT values and BioSlag test percentage of slag were explored as predictors of the measured boiler slag percentage (Figure 3 and Table 9). Whereas no significant relationship was found for the IDT as a predictive value of slag percentage measured in the boiler (Figure 3, left, and eq [7] in Table 9), with R2 = 0.1, a strong linear relationship was found between BioSlag test slag percentage and boiler slag percentage of the studied fuels, with R2 = 0.87 and RMSE = 8% (eq [8] in Table 9).
4. DISCUSSION 4.1. Ash Composition and Ash Slagging Indices. The samples with the highest silica content, rye straw pellet (F06) and pinecone seed (F11) (Table 6), showed the highest slagging behavior in the boiler and in the BioSlag test, together with low ash fusion temperatures of 2 mm of the BioSlag test (top left) and of the boiler (top right), plotted against initial deformation temperature (IDT, °C). (Bottom) Percentage of slag >2 mm of the BioSlag test versus percentage of slag >2 mm of the boiler, showing the predictions and confidence interval of eq [2] in Table 9.
some reports, such as those of Osman60 and Li et al.,56 suggest some influence of silica content on increasing or decreasing ash fusion temperature, other works, such as that of Reisinguer,57,58 found no clear effect of silica, contrasting with a clear effect of potassium on IDT and ash fusion temperatures. 4.3. BioSlag Test, IDT Test, and Boiler Slag Percentage. The best slagging indices based on ash composition at 550 °C for predicting the amount of slag, both in the boiler slag and in the BioSlag test, were silica-based indices SiP/CaMg and SiPNaK/ CaMg (eqs [3]−[6] in Table 9 and Figure 2), suggesting a higher sensitivity to silica for both boiler and BioSlag test slag content than found in the IDT test. No statistical relationship was found between IDT test values and boiler slag percentage, with R2 = 0.14 between the two variables (eq [7] in Table 9). IDT test predicted extreme slagging risk for the high-alkali fuels (F10, F12−F14), which showed moderate slagging levels on the boiler (Table 8 and Figure 3, top right) and failed to identify the slagging observed for the highsilica soil-contaminated woody fuel (F04), which showed an IDT value of >1100 °C (Table 8 and Figure 3, top right). This latter limitation may be caused by a low sensitivity of this fusion test to silica content, as discussed above. In addition, the small ash sample utilized in the ash fusion test may not be representative enough for capturing soil contamination, compared to tests such as the BioSlag test that utilize a more representative amount of fuel. The standard ash fusion test has been extensively criticized in the literature for not providing conservative estimates of slag behavior observed in the boilers (e.g., refs 28, 32−35). The microscopic variations observed in the ash sample caused by ash
silica contained in the ash, forming silicates with very low melting point (
