PREDICTION OF ASH AND DEPOSIT FORMATION FOR BIOMASS PF CO-COMBUSTION

Contract JOR3-CT98-0198

FINAL REPORT (PUBLISHABLE)

Research funded in part by

THE EUROPEAN COMMISSION in the Framework of the

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Non Nuclear Energy Programme JOULE III

PREDICTION OF ASH AND DEPOSIT FORMATION FOR BIOMASS PF CO-COMBUSTION

JOR3-CT98-0198

KEY WORDS

pulverized fuel combustion, coal, biomass, co-combustion, slagging, fouling, corrosion, deposit, ash, slag, analysis, prediction, minerals.

1. ABSTRACT

The implementation of biomass as secondary fuel in existing pulverized fuel firings, for the reduction of net CO2 emissions, presents one main disadvantage. Due to the nature of the biogenic fuels, there is major concern about about ash deposition-related effects and excessive rates of corrosion in advanced plants.

The objective of the project was therefore to provide predictive tools for the specific operational problems slagging, fouling and corrosion in pulverized fuel co-combustion of biomass in advanced high temperature power utilities.

A total of eleven partners was involved in the investigations. For a better co-ordination of the activities, three groups were formed to work independently on basic understanding of relevant mechanisms and processes. The results were later correlated in common to take into account the synergetic effect between the different phenomena. The three groups concentrated on Slagging and Fouling Experiments, on Chemistry and Analysis and on Corrosion Measurements.

The investigations were mainly focused on analytical work on the feeding of the system, to establish the adequate analytical methods to be applied on the fuel for the prediction purpose. The information gained was correlated with the analytical work on the samples resulting from the experimental work.

Mechanisms for the formation of deposits and corrosion of materials in industrial boilers were in this way identified and schematized. Although no guidelines could be established for a complete and perfect prediction, due to the complexity of the problem, successful results were obtained in the overall comprehension of the phenomena and some prediction tools could be proposed.

Guidelines for the prediction of ash stickiness were drawn based on the chemistry of the ashes. Key numbers for prediction were defined based on the chemical composition of the fuel. A new rough method was developed to predict the sintering risk of a determined fuel by conductivity measurements. A test method for corrosion was defined, and guidelines for the analysis of corrosion samples were established. The synergy between deposition and corrosion was outlined. Kinetic data for the corrosion through ash exposure was obtained and kinetic modeling was carried out for

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corrosion during biomass co-combustion. A criterion for the selection of the most appropriate material regarding corrosion protection was established.

Finally, all the results were compiled in a database. The main purpose of the compilation was to allow a better comparison of the analytical data for the identification of trends.

2. INTRODUCTION

The implementation of biomass as a secondary fuel in existing pulverised coal utility boilers is a technically feasible and economical option for the realisation of a considerable reduction of net CO2 emissions originating from large-scale heat and power production. Besides high electricity conversion efficiencies, lower specific emissions and lower investment costs compared to dedicated biomass systems, operational problems, such as fouling, slagging and corrosion, or the utilisation of by-products can effect the co-utilisation of coal and renewable fuels in a negative way.

Especially, due to the nature of renewable solid fuels, such as straw or wood, there is a major concern about ash deposition-related effects within the furnace and the convective parts of a power plant as well as about increased rates of corrosion. Therefore, the objective of the project is to provide a fundamental understanding of the relevant mechanisms and processes in order to define predictive tools for the specific operational problems. The development of these tools will be based on standard and advanced fuel analysis and characterisation methods as well as on extensive experimental investigations in different lab-, bench- and pilot-scale test rigs and full-scale power plants for pulverized fuel co-combustion.

The specific objectives of the project were:

- A better comprehension of slagging, fouling and corrosion phenomena taking place within a furnace, during the combustion of coal and biomass fuels and during fouling, slagging and corrosion. The identification of relevant mechanisms that define these processes and the influence of them on operational parameters and fuel quality.

- The definition of guidelines, based on combined analytical and experimental work for the prevention of operational problems using new unknown secondary fuels.

The project strategy to achieve these goals is as follows:

- A thorough analytical work on the composition of the fuels, from standard analysis to the most advanced available techniques, provides the information necessary to identify the basics of slagging, fouling and corrosion. In this sense, a broad spectrum of analytical methods were tested for a latter identification of the necessary information. The analytical methods, accurately classified and assessed regarding the consistency of their results, turn into the most powerful prediction tool, with low costs and quick results.

- A broad and systematic experimental work and a latter correlation with the fuel data permits the identification of the processes really taking place. In this sense, the work was divided in three separate study fields. Slagging and fouling experiments were run in different facilities, scanning from full scale operation down to laboratory tests procedures. Chemical and analytical work was

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done on the samples for the identification and characterization of mechanisms. Corrosion work was carried out separately, including as well full and lab scale experiments. For all test runs, samples and information on the relevant operational parameters were collected. Based on the expected and verified synergy between deposit formation and corrosion phenomena, an extensive co-operation among the two was established and common work carried out.

- The trends identified by comparison of the complete picture of the process, form the feeding to the resulting ashes, deposits and corroded materials, would allow to define mechanisms, chemical reactions and eventual models to describe the phenomena.

- Prediction tools based on fuel information were mainly looked for, in the aim of defining the necessary information on the fuel for increasing the prediction accuracy but with reduced costs. Anyhow, complementary lab scale procedures were to be developed, that would provide the missing experimental information for the prediction and prevention of the operational problems.

The structure of the report is based on the goals and described strategy. The work carried out on the characterization of the fuels is therefore summarized in a first place, as main concern of the project and most powerful prediction tool to develop. The tested methods are discussed and evaluated concerning their prediction potential and feasibility.

After presenting an overview of the test facilities and the fuels used, the discussion on the experimental work is summarized. The different analytical methods applied to both ash and deposit samples from the slagging and fouling experiments are summarized, including the results attained regarding definition of mechanisms and establishing prediction guidelines.

The corrosion work is then presented separately, were the very good synergy of the partners permitted to attain successful common results. The analytical work is here once more discussed, presenting its results. Identified mechanisms are pointed out and prediction tools proposed. Remarkable results from this work are the establishing of a corrosion test procedure and a criterion for the selection of the appropriate construction materials to prevent corrosion problems.

The work for the compilation of the results in a common database, with information from the fuels, the different samples and operational parameters of the facilities used, is presented a the end of the report, including examples of the analysis and potential of the collected data.

Conclusions on the overall experience gained during the project are drawn in the closure.

An example was chosen for each of the described methods, result analysis, identified mechanisms and proposed tools. Although it was an aim on the hand of the co-ordinator to include examples from all partners and provide like that an overall picture of the project, the extensive and thorough work carried out during the three years by all eleven partners is here only summarized. This report intends to attract the attention on our common activities. Detailed information can be found in the single reports of each partner in the annexes.

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3. FUEL ANALYSIS

The selection of a fuel on the hand of an operator is usually made on very little analytical information. The main determining factor being its price, fuels are seldom extensively characterized before purchase and utilization. With increasing concern on operational and ash derived problems, a deeper knowledge on the fuels is demanded, being the main key for the prediction and prevention of fouling, slagging and corrosion effects within industrial combustion systems.

The work carried out as support for the comprehension of deposition and corrosion phenomena during pulverized coal and biomass co-combustion and the identification of the requested fuel information for a development of prediction tools is summarized in this section.

3.1 Standard Fuel Analysis (IVD)

Generally very few analytical techniques are commonly used for the characterization of a fuel before firing. The heating value is for example required for the basic calculation of the combustion process. But little further data, such as proximate (moisture, volatile matter and ash content) and ultimate (C/H/N and in some cases S) analysis is usually available. These commonly as standard understood analysis methods are run on all fuels used during the project by all partners, as the first step to their characterization.

The results of the standard analysis run at IVD are presented as an example, with the conclusions that are drawn from. Table 3.1 presents the type of sample required and the method used for the standard analytical work.

Table 3.1: Standard Analysis on Fuels

Determination of Sample Principle

Heat Value (LHV) Raw Fuel Calorimeter

C, H, N, S Raw Fuel Gas Chromatography

Moisture, volatile matter, fixed carbon, ash content Raw Fuel Thermogravimetry

The fuels analyzed are presented in Table 3.2, indicating the reference name used for the compilation in the database. Some trials were run with fuels used by the partner ALSTOM for the sake of comparison of experimental results from different test facilities. These two fuels are here included.

Table 3.2: Fuels analyzed at IVD

Fuel Ref. Fuel Ref.

Lignite Coal Coal-IVD1 Straw (chlorine rich) S-IVD3

Bituminous Coal Coal-IVD2 Straw (Ref. fuel) S-IVD4

Colombian Coal Coal-ALSTOM Sewage Sludge SS-IVD

Annual Crops AC-IVD Wood Pellets W-IVD1

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Straw S-IVD1 Wood Flakes W-ALSTOM

Straw Pellets S-IVD2

The lower heating values determined for each of the fuels used during the testsare presented in the Figure 3.1, for the raw fuel and as dry matter. The biogenic fuels presented between 25 and 30% lower energy values than the lignite and 40-45% less energy content than the selected bituminous coal. The biggest differences were given for the Sewage Sludge, with a 58% less than the lignite and even up to a 66% lower than the bituminous coal, being this fuel subjected to much broader variations on quality than other fuels.

The analytical results for the main elements Sulfur, Nitrogen and Chlorine are presented in Figure 3.2, and the contents of moisture, volatile matter, fixed carbon and ash are plotted in Figure 3.3.

0

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Coal-IVD1 Coal-IVD2 S-IVD1 S-IVD2 S-IVD3 W-IVD1 AC-IVD SS-IVD

LH

V [

MJ/

Kg

]

Dry Matter

Raw

Fig. 3.1: Lower Heating Values [MJ/kg] of All Fuels

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Several trends can already be observed at the simple information obtained from the ultimate analysis, which differences biomass from coals and foresees a different behavior during combustion.

On the one hand, some positive trends can be observed. The lower Nitrogen (N) and Sulfur (S) concentrations common for biomass fuels allow, by the use of this type of fuel, a reduction of the nitrogen and sulfur oxides emissions during solid fuel combustion.

On the other hand, several trends confirm biomass as problematic type fuels. A commonly higher Chlorine (Cl) content will drive to more severe corrosion problems on the metal surfaces within the boilers.

Especially the much higher volatile matter content in comparison with coals, should allow to predict a higher production of problematic species from the point of view of slagging and fouling. If this characteristic is combined with a high ash content, deposits of ashes melting at lower temperatures are to be expected, resulting in slagging problems. In the case, such as most types of woods, where the ash content is very low, the volatile fuel components with low melting points tend to leave the combustion in the flue gaseous phase.

The importance of the broad differences in the heating values gains here importance at the fact that, in spite of lower concentrations of problematic elements such as sulfur (S) and nitrogen (N), the higher fuel amounts needed to obtain the same energy levels make the firing of biomass reduce the good effect on the emissions, at the same time that the problematic aspects regarding operation are reinforced.

The information obtained by the standard analysis described in the former paragraph is certainly not sufficient for the characterization of a fuel, for a thorough comprehension of the combustion and

0,0

0,5

1,0

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2,0

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3,0

C-IVD1

C-IVD2

C-ALST

OMAC

-IVD

S-IVD

1

S-IVD

2S-I

VD3

W-IVD1

W-ALST

OMSS

-IVD

[% r

aw]

NSCl

Fig. 3.2: Nitrogen, Sulfur and Chlorine values in the raw fuels

010

2030

4050

6070

8090

C-IVD1

C-IVD2

C-ALST

OMAC

-IVD

S-IVD

1

S-IVD

2S-I

VD3

W-IVD1

W-ALST

OMSS

-IVD

[% r

aw]

moisture

volatiles

ash

fixed C

Fig. 3.3: Moisture, Volatile, Fixed Carbon and Ash contents in the raw fuels

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deposition processes, for the ash forming elements and the nature of their appearance in the fuel are not considered in these analytical methods. Further analytical techniques are presented in the following sections and evaluated according to their relevance as prediction tools.

3.2 Advanced Fuel Analysis (RWE)

A special effort was made on the characterization of the inorganic chemistry of the fuel. The contents of ash forming elements in the fuel were analyzed for the correlation with the data to be collected from the samples.

An example of inorganic chemistry characterization is given in the Table 3.3. The data corresponds to the values for the main known ash forming elements, Silicon (Si), Aluminum (Al), Iron (Fe), alkaline-earth (Mg and Ca) and alkali elements (Na and K), Titanium (Ti) and Sulfur (S). The element contents in an ash produced in the laboratory directly from the fuel blend used are here presented in an oxide basis. The example corresponds to the fuels used for the experiments carried out by the partner RWE.

Table 3.3: Inorganic chemistry of the blends fired during the co-combustion experiments by the partner RWE

SiO2 Al2O3 Fe2O3 MgO CaO Na2O K2O TiO2 SO3Ref. [kg/h] Ref. [%th]

C-RWE2 281 - - 14,83 2,35 12,57 10,57 25,27 4,42 0,52 0,28 17,28C-RWE2 241 S-RWE1 15 11,36 2,27 12,19 10,49 24,99 4,29 3,23 0,18 17,01C-RWE2 150 S-RWE1 30 13,95 2,42 10,90 9,81 23,28 3,94 6,29 0,18 14,28C-RWE2 211 S-RWE1 30 15,60 2,50 9,90 9,20 21,55 3,68 7,92 0,17 15,08C-RWE2 140 S-RWE1 30 17,68 3,04 9,45 8,77 20,04 3,47 9,23 0,20 11,90C-RWE2 161 S-RWE1 30 16,75 2,83 9,63 8,99 20,33 3,55 9,32 0,20 11,70C-RWE1 310 - - 21,08 1,40 7,70 6,16 31,73 0,45 0,18 0,25 -C-RWE1 270 S-RWE1 15 14,37 1,79 7,57 6,37 31,57 0,25 2,66 0,20 -C-RWE1 220 S-RWE1 30 16,13 4,94 7,04 5,53 26,53 0,16 6,69 0,21 -C-RWE1 240 S-RWE1 30 15,53 7,32 8,19 5,63 27,80 0,19 5,83 0,25 -C-RWE1 160 S-RWE1 30 18,43 6,55 7,72 5,61 26,37 0,25 8,06 0,25 -C-RWE1 140 S-RWE1 30 16,90 7,19 7,64 5,47 26,50 0,16 8,35 0,26 -C-RWE1 220 S-RWE1 30 16,70 6,27 7,45 5,36 26,20 0,16 7,44 0,25 -C-RWE2 150 W-RWE 30 9,37 2,95 14,58 11,33 28,95 4,37 0,90 0,29 -C-RWE2 300 W-RWE 30 8,05 2,63 15,98 12,20 29,90 4,80 0,88 0,20 19,33C-RWE2 180 W-RWE 30 8,00 8,81 10,87 7,38 36,10 0,81 0,38 0,20 21,70C-RWE2 200 W-RWE 30 7,50 9,03 10,73 7,11 36,23 0,64 0,35 0,21 21,17C-RWE2 280 W-RWE 30 7,48 8,95 10,25 6,80 36,85 0,41 0,34 0,20 20,85C-RWE2 200 S-RWE2 30 9,47 2,87 16,95 12,68 30,75 4,70 0,59 0,28 17,50C-RWE2 190 S-RWE2 30 15,60 3,00 14,30 11,50 26,50 4,50 4,60 0,27 15,10C-RWE3 170 S-RWE2 30 31,00 2,60 8,70 10,20 23,40 3,90 3,50 0,40 11,50C-RWE3 170 S-RWE2 30 34,80 2,70 7,50 9,40 20,70 3,80 5,40 0,50 8,00C-RWE3 180 W-RWE 30 31,10 2,60 8,70 10,20 23,60 3,70 3,40 0,50 9,80C-RWE1 145 - - 11,13 8,09 9,99 6,48 35,2 0,2 0,24 0,24 19,68

[% in fuel ash]Coal Biomass

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This simple method, commonly carried out by most laboratories, has proven to provide very valuable information on the species forming the ashes. Some mistakes were made in the past by analyzing ashen samples of the fuel. A fraction of some of the elements to be determined, e.g. silicon and aluminum, is set free during the ashing process, resulting in a determination error of their content. A direct analysis of the fuel is therefore required for an accurate fuel characterization. The dependency on the one hand on the nature of these elements in the fuel matrix, which depends strongly on the type of fuel (see discussions on advanced fuel analysis) and determines the behavior during combustion, and on the other hand the lack of models connecting the fuel and ash composition makes a development of a prediction tool from this method also very difficult.

3.3 Fuel Ash Fusion Behavior

The characterization of the fusion behavior of the ashes created in the laboratory directly from the fuel was tested as an assessment tool of the tendency of a fuel ash to form fused deposits on the heat exchanger and other surfaces in coal-fired boiler furnaces.

For this purpose, the ash fusion behavior of all pure fuels and a number of the blends was analyzed. An example of the method and the work carried out, in this case by the partner Mitsui Babcock, is presented in the following.

It should be said in advance that a closer evaluation of this analytical method drives to a definitely skeptic position regarding its prediction potential. There are technical concerns about the behavior of the mixed ashes generated by the direct co-firing of biomass and waste materials with coal in large coal-fired boilers. The heating paces found during industrial combustion processes can not be achieved, not even approximated, at lab rigs. Although the so-generated ashes allow a qualitative comparison of the behavior of different fuels, their quantitative prediction potential for new fuels and blends is therefore questionable.

However, the fusion behavior of the ashes and ash blends has been investigated by the partner Mitsui Babcock using two complementary techniques, viz:

- The Ash Fusion Test, performed according to the procedure described in BS 1016-Part 113 : 1995/ISO 540-1995, and

- A relatively novel technique, which involves the simultaneous measurement of the electrical resistivity and the linear shrinkage of small ash specimens as they are heated slowly up to a temperature of about 1400 °C. This technique has been developed at Mitsui Babcock Technology Center over the past ten years.

A suite of appropriate samples of coals, and biomass and waste materials, has been collected and utilized in this work, viz.:

- Longannet coal a deep-mined coal, delivered in large quantities to Longannet Power Station in Scotland. This coal has a very refractory ash, i.e. has high ash

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fusion temperatures and a low slagging propensity.

- Trinity coal an open-cast, power station coal from Nottinghamshire in England, which has an ash with relatively high Fe2O3 and CaO contents, and low ash fusion temperatures. This coal is known to have a high slagging propensity in power plant boilers.

- Wheat straw Collected from a farm in Lothian Region, Scotland.

- Oil seed rape straw Collected from a farm in Lothian Region,Scotland.

- Short rotation coppice wood Three year old stems of willow (Salix Vinimalis), chipped on site and supplied by the Long Ashton Crop Research Station, Bristol, England.

- Sewage sludge Collected from a sewage treatment works in the West of Scotland.

The experimental procedure involves mixing the coal with the biomass/waste material in the correct proportions, and co-ashing them at a maximum temperature of 815 °C. The principal technical interest is in relatively low biomass ash:coal ash ratios, and hence the following suite of blends was prepared for each blend pair, on an ash weight basis:

- 0%:100 % / 5 %:95 % / 10 %:90 % / 15 %:85 % / 20 %:80 % / 100 %:0%

The fusion temperatures of the ashes and ash blends are measured using the techniques listed above, and six characteristic temperatures are recorded. These are, starting with the lowest temperature:

- T10 % The temperature at which the ash specimen has shrunk by 10 % of its original height.

- TR The temperature at which the first significant change in the current- temperature plot occurs. This is evidence of the formation of a continuous molten phase within the specimen.

- T30 % The temperature at which the ash specimen has shrunk by 30 % of its original height.

- DT the temperature at which the first signs of rounding, due to melting, of the tip of the test piece occurs.

- HT The temperature at which the test piece forms a hemisphere, i.e. when the height becomes equal to half the width of the base.

- FT The temperature at which the ash is spread out over the supporting tile in layer, the height of which is one-third of the height of the test piece at the hemisphere temperature.

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The ash fusion temperatures are measured in both oxidizing and reducing atmospheres, and are presented graphically in a plot of the measured temperatures against the ash blend compositions by weight.

Fig. 3.3: Trinity Coal/Wheat Straw Ash Blends in Reducing Atmosphere

The data presented in Figure 3.3, illustrates the behavior of the Trinity coal-wheat straw ash blends. It is clear from the test data that the effect of increasing straw ash in the blends was minimal. The fusion temperature-blend composition curves are all very flat and, in the case of the FT (red.), the values actually increased with increasing straw ash content. These data imply that the effect of the co-firing of the wheat straw ash with a coal which has relatively low fusion temperatures will be minimal, i.e. no significant change in the extent or rate of formation of furnace slag deposits at straw ash contents up to 20 % of the mixed ash.

The implications of the results are clear. The impact of co-firing biomass materials with coal on the fusion behavior of the ash is dependent on the chemistry of the ashes. In the case of a relatively refractory coal ash, the effect of co-firing can be significant, whereas in the case of a coal ash with lower fusion temperatures and higher slagging propensity, the effect will be less marked.

3.4 Special Analysis

The analytical methods presented up to now provide a very complete information on the composition of a fuel. They can not, anyhow, clear the way in which the different elements are present in the fuel and therefore behave during the combustion and heat transfer process in the furnace and boiler. Whether an element is forming part of the fuel matrix, of the structure, or it is present in inclusions, will determine its availability and the consequent reactions that will take place during the combustion. It determines thus the elements that will be available for the ash formation and resulting deposit formation and corrosion phenomena. In order to attain information on the structure of the fuel, two

700

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0 5 10 15 20 25 30Biomass Ash, % in Blend

Te

mp

era

ture

, o C

IDT Red

HT Red

FT Red

T10%

T30%

TR

100% Wheat Straw

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different analytical methods were tested, which are presented below.

These two methods provide very valuable information for the identification and description of mechanisms. But they are, in spite of their relative simplicity, most probably not adequate as standard tools for fast fuel assessment. (Lab scale tests can possibly provide more valuable information for prediction purposes).

Nature and elementary presence (ECN)

The particular effort on fuel characterization concentrated on the nature and appearance of inorganic elements was mainly made by partner ECN. With the use of SEM-EDX analysis, differences between coal and biogenic type of fuels could be established concerning the structure of fuel matrix and the bindings of elements. The nature of the fuel and the availability of the ash forming elements found in it, have an determinant relevance on the mechanisms taking place during the combustion and latter deposit formation.

Example results from the studies for three biogenic fuels are summarized.

Based on SEM-EDX analysis of the biomass fuels the following results have been obtained:

Wood

The wood fuel is very clean and contains very little external mineral particles like clay and/or sand. The element calcium is predominantly found as crystalline calciumoxalate or carbonate particles in a typical size range of 1-10 µm. Other particulate compounds contain mixtures of Ca, Mg, Na as either silicates or sulfates, in a size range up to 40 µm. The majority of these inorganic species are biogenic and are found embedded within the organic wood matrix.

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Straw

The straw fuel is also very clean and contains very little external mineral particles like clay and/or sand. The element silicon is predominantly (est. 75%) found in quartz particles which either may be embedded in the organic straw matrix as up to around 25 µm particles or from a thin (few µm), continuous lining at the ouside of straw stems. Some clay minerals containing Mg and/or Ca have been found in the fuel as well.

Chemical Fractionation (ECN)

Another method for the characterization of a fuel that was investigated by partner ECN was the chemical fractionation. A scheme of the procedure can be found in Annex 1.

Chemical Fractionation (CF) is a method to discriminate inorganic classes in biomass fuels according to their solubility in a sequence of increasingly aggressive solvents [Baxter, 1996]. The parts of the fuel found as either water soluble, ion exchangeable, hydrochloric acid soluble or residual (non-soluble) are subsequently related to their alleged behaviour in a process like e.g. pulverised fuel combustion. Generally, the water soluble and ion exchangeable classes include various salts of potassium and sodium which are considered to be easily vaporised in a high temperature process. Carbonates and sulphates are expected in the hydrochloric acid soluble class [Baxter, 1996], while the oxides, silicates and sulfides are not extracted and classified as residual.

Both the hydrochloric acid soluble and residual matter are considered to be much less reactive in a thermal process.

The proportion of the elements of interest found in the first two classes is mostly interpreted as a measure for the release of reactive inorganic species to the gas phase. Their availability is subsequently related to enhanced deposition of ash on boiler and heat exchanging surfaces.

So far, ash deposition has been studied using fuels as a whole. In the current study, selective extraction has been applied to produce fuels lacking specific inorganic species. These fuels have been used in lab-scale deposition tests to verify the alleged relations with the currently used CF classes.

Experimental

Wood, straw and chicken manure with well-known inorganic compositions (threefold ICP-AES

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analysis per fuel) have been tested with respect to their ash deposition behavior in a lab-scale combustion simulator. In Figure 1, a schematic view of the installation is given. By means of a staged gas burner and electrical furnace, the gas temperature and gas phase concentrations of O2, CO, CO2, H2O, SO2 and N2 have been set to simulate typical combustion conditions in a pulverized fuel boiler. Fouling of superheater was simulated by means of a temperature-controlled metal deposition surface, with a surface temperature of 600 °C at a gas temperature of 1200 °C. The surface temperature was recorded during the deposition test. The deposits were analyzed off-line in 2D and 3D by means of SEM-EDX. The results serve as a reference for comparison with the deposition behavior of partly extracted fuels.

The same fuels were subjected to a sequence of three selective extractions using water, a 1 M NH4Ac solution and a 1M HCl solution. The procedure suggested by Baxter [1996], see Figure 2, was evaluated by a) comparing the composition of the extracted material with the extract concentrations, b) comparing parallel to sequential extraction, c) examining the effect of pH-control during the extraction and d) evaluating multiple extractions at a low L/S ratio versus a single extraction at a proportionally higher L/S ratio. From these tests, suggestions for improvement of the procedure are given. Extracted material has been taken from each extraction step to be used as a fuel in a deposition test in the facility described above. Again, SEM-EDX was used to examine the deposits and to compare the occurrence of specific species in these deposits with those obtained from burning the original fuels.

Results

Extraction at a L/S ratio of 3 is not feasible for biomass such as wood or straw due to a very high water uptake. An L/S ratio of 10 or more should be used in stead.

The determination of extracted elements is much easier and cheaper by analyzing the extract than by handling and opening up and analyzing the extracted solid residue.

The pH-value after equilibration of the solvent with the solid phase is influenced by and depends on the biomass used. Control of the pH-value at a pre-set constant value may be considered but care must be taken not to replace a pH-influence on the extraction process by an influence of increased ion concentrations in the solvent.

Partly extracted fuels have been used in lab-scale ash deposition tests under simulated pf firing conditions. The deposits are compared to those obtained from the original fuels by means of 2D and 3D SEM-EDX analysis, identifying the presence and role of relevant species in the deposit. Heat fluxes through the growing deposit layers have been determined as a function of time as a more quantitative measure of deposit development.

Discussions and Conclusions

§ Selective extraction schemes which are currently used for predicting fuel ash behavior have been designed - in the past - for the evaluation of leaching characteristics of soils. For a Chemical Fractionation analysis of biomass fuel inorganic matter, an adapted design should be aimed at the selective extraction of elements of interest applying specific pH-values and/or solvent ion concentrations. It may be necessary to control these conditions to eliminate effects of the fuel (biomass) matrix during the extraction. More work is needed to establish specific conditions for extracting key elements or species with a known behavior in thermal processes.

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§ Up till now, only a gross difference between water soluble / ion exchangeable, strong acid soluble and non soluble inorganic species can be made using three selective extractions. A definite relation between extraction results and fuel ash behavior can be obtained using fuels which have been partly extracted under well-controlled conditions in subsequent combustion tests aimed at ash deposition evaluation. From this, extraction schemes can be set up for the determination of specific, predefined inorganic species.

A scheme of the procedure for the chemical fractionation is presented in the Annex 1.

4. EXPERIMENTAL INVESTIGATIONS

Parallel to the characterization of the fuels, experimental trials are run with the purpose of collecting fly ash, deposit and corrosion samples. The correlation of the experimental data obtained through the sampling and the analytical work on the fuels helped to identify the processes taking place within the boilers, define mechanisms and establish tools for the prediction and prevention of the mentioned operational problems.

The facilities, testing and sampling methods and the fuels used all through the project by each of the partners are summarized in this chapter, before presenting the results of the project.

4.1 Facilities

Table 4.1 summarizes the facilities that were used during the project by each of the eleven partners. The laboratory equipment used for analytical measurements and lab scale experimentation is also included for a better overview of the work carried out.

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Table 4.1: Test Facilities

Facility Partner Tests * Facility Type

HTOET UC C Oxidation and Erosion Furnace

HTEC UC C Erosion / Corrosion Test Rig

ARDEA MBEL - Ash Resistivity/Dilatometry Exp. Apparatus

TCF MBEL C Tube Corrosion Furnaces

Lab Equip.

- DTU - High Temperature Rotational Viscometer

BTS IVD S&F pf drop tube furnace (30kW)

- TPS S&F - Lab Scale

- ECN S&F pf drop tube furnace

KSVA IVD S&F pf vertical furnace (500kWth)

VVA RWE S&F -

- TPS S&F - Pilot Scale

St. Gilla ENEL S&F -

CTR ALSTOM S&F -

- TPS S&F -

Jordbro VAB S&F – C -

Nyköping VAB S&F – C -

Full Scale

Fusina ENEL S&F -

(*) S&F: slagging and fouling C: corrosion

A complete description of the facilities as well as the testing and sampling methods can be found in the database of the results. Additional trials were run by partner TPS on other facilities, also described in the database, for the collection of validation data.

4.2 Fuels

A list of all fuels used for the different experiments carried out is presented in Table 4.2, separately for coals and biogenic fuels. These last were used as secondary fuel in most of the cases. Anyhow, several experiments were made with biomass as primary fuel and some pure biomass flames were investigated. The ranges for fuel blending are also roughly presented. The detailed configuration of the feeding of each trial can be found in the database of the results. The labeling used in the database for the fuels is given here under the category “Ref.”.

17

Table 4.2: Tested Fuels and blending rages

Fuel Ref. Partners Fuel Ref. Partners

Coal Lignite Coal-IVD1 IVD S-IVD3 IVD

Bituminous Coal-IVD2 IVD S-IVD4 IVD

Colombian IVD, ALSTOM,

S-RWE1 RWE

Lignite Coal-RWE1

RWE S-RWE2 RWE

Lignite Coal-RWE2

RWE S-MBEL1 MBEL

Lignite Coal-RWE3

RWE S-MBEL2 MBEL

Coal-MBEL1

MBEL S-ENEL8 ENEL

Coal-MBEL2

MBEL S-ENEL9 ENEL

Coal-ENEL1

ENEL S-ENEL12 ENEL

Coal-ENEL10

ENEL S-ECN1 ECN

Coal-ENEL13

ENEL S-ECN2 ECN

Biomass Alfa-Alfa AA-TPS TPS S-ECN3 ECN

Annual Crops

AC-IVD IVD S-ECN4 ECN

Annual Crop Pop-ENEL3

ENEL Sewage Sludge

SS-IVD IVD

Annual Crop Pop-ENEL5

ENEL SS-MBEL MBEL

Annual Crop Pop-ENEL7

ENEL

Bark B-TPS TPS Wood W-IVD IVD

Chicken Manure

CM-ECN ECN Wood Flakes

W-ALSTOM IVD, ALSTOM

Forest Residue

FR-TPS TPS W-RWE RWE

Peat P-TPS TPS W-MBEL MBEL

Peat-Coke Pet-ENEL14

ENEL Waste Wood

WW-TPS TPS

RDF RDF-ENEL

ENEL Wood W-ENEL6 ENEL

18

Robinia ROB-ENEL4

ENEL W-ENEL11 ENEL

Straw S-IVD1 IVD W-ECN ECN

S-IVD2 IVD

The experimental work was divided into two separate areas of investigation. On the one hand, tests were run to characterize the slagging and fouling phenomena. Corrosion tests and measurements took place separately. Combined experiments were run to determine the synergetic effect between the two phenomena, deposition and corrosion.

Accordingly, the experimental work is summarized in the following sections separately for slagging and fouling tests and corrosion measurements. An example of the results of each of the analytical tasks carried out on the different samples is presented, discussing the results and presenting the mechanisms identified. Conclusions are drawn on the prediction potential of the information obtained and some tools are proposed.

19

5. SLAGGING AND FOULING TESTS

The sampling programs during the slagging and fouling tests resulted in fly ash samples and deposits. The analytical work and its results are presented in the following section separately for the fly ash samples and the deposits. Correlated results follow, identified mechanisms are described and prediction tools are proposed at the end of this section.

5.1 Fly Ashes

The fly ashes collected during the slagging and fouling experiments underwent analytical work for the characterization of their chemical composition, their particle size distribution and its influence on the chemical distribution, their fusion behavior, their viscosity and their morphology. The results of these investigations are summarized in the following.

Chemical Composition (ALSTOM)

Samples of fly ash collected during the trials, at the end of the furnace by fly ash sampling and the bulk ash from the particle control devices, were analysed. A mnemonic coding system, xynn was used to identify the samples as follows:

x = A: small ash sample; x = B: bulk ash sample (see section 3.1)

y = L: low excess air; y = H: high excess air

with nn designating the biomass addition on a weight % basis.

The small fly ash samples were analysed by ICP (Alstom). Figures 5.1 and 5.2 show respectively the results obtained on the ash samples obtained from the firing trials conducted at low and high excess air with the different proportions of coal and biomass.

20

Samples of ash from the LH series were also submitted to ECN to complement the samples of deposit collected on the test coupons during the low excess air trials.

0.10

1.00

10.00

100.00

% (

as o

xide

)

AL00 AL10 AL20 AL30

AL00 0.5 0.7 22.0 63.9 0.8 0.5 1.4 1.4 1.0 8.1

AL10 0.4 0.5 18.6 67.1 0.6 0.6 1.1 1.3 0.8 7.1

AL20 0.4 0.6 19.3 66.7 0.7 0.4 1.3 1.1 0.8 7.9

AL30 0.4 0.7 18.8 67.3 0.6 0.4 1.3 1.2 0.8 7.5

Na Mg Al Si P S K Ca Ti Fe

Figure 5.1 Analytical Data on Small Ash Samples (Low Excess Air Firing)

21

Bulk samples of ash collected from the waste heat boiler were coarsely sieved to remove any debris originating from the plant. Batches of sample were sealed in tins and dispatched to DTU in Denmark and RWE in Germany. Results of the analysis are presented in Figures 5.3.and 5.4.

0.10

1.00

10.00

100.00

% (a

s ox

ide)

AH00 AH10 AH20 AH30

AH00 0.4 0.5 19.7 66.9 0.7 0.3 1.1 1.4 0.8 6.5

AH10 0.3 0.5 19.2 66.6 0.6 0.4 1.1 1.5 0.8 7.0

AH20 0.3 0.6 18.7 66.0 0.7 0.2 1.2 1.0 0.8 7.7

AH30 0.4 0.7 19.5 64.7 0.7 0.2 1.3 1.1 0.8 8.8

Na Mg Al Si P S K Ca Ti Fe

Figure 5.2: Analytical Data on Small Ash Samples (High Excess Air Firing)

0.10

1.00

10.00

100.00

% (

as o

xide

)

BL00 BL10 BL20 BL30

BL00 0.7 0.8 14.8 76.3 nd 0.8 1.2 1.4 0.8 3.2

BL10 0.4 0.5 12.3 78.6 nd 1.0 1.1 1.9 0.9 3.5

BL20 0.5 0.6 12.1 77.2 nd 0.7 1.1 1.5 0.9 5.5

BL30 0.5 0.8 11.6 78.7 nd 0.9 1.2 1.5 1.0 3.9

Na Mg Al Si P S K Ca Ti Fe

Figure 5.3: Analytical Data on Bulk Ash Samples (Low Excess Air Firing)

22

Particle Size vs. Composition (ABO)

A study of the effect of the particle size distribution on the chemical composition of the fly ash was made by the partner ABO. The results are summarized in the following section.

To get more information about the type of fly ash particles in the flue gas channel of the Jordbro-boiler, ABO performed in-situ fly ash sampling with a Berner-type low-pressure cascade impactor. The sampling was performed in the fluegas channel at a location where the fluegas temperature was approximately 400oC. Details about the sampling can be found in a separate result report presented to VUAB /Laurén T., Skrifvars, B-J: In-situ fly ash sampling at Drefviken-Jorbro pulverised fuel fired heat water boiler, Result report 2000, Åbo Akademi University, Process Chemistry Group, to be published/.

These results are here summarized. Figure 5.5 presents an overall analysis of one of the sampling cases, from the test run No 5, where 100 % wood chips were fired at a 75 MWth load.

As can be seen from the figure alkali chlorides and sulfates dominate the sub-micron sized particles while calcium is the dominating element in the super-micron size fractions. A commonly accepted understanding is that sub-micron sized particles usually are generated from vapors. This suggests that during pulverised wood chips firing alkali, sulfur and chlorine are released into the gas phase and then condenses as they enter colder regions in the fluegas channel. This well-know phenomenon is confirmed also here.

0.10

1.00

10.00

100.00%

(as

oxi

de)

BH00 BH10 BH20 BH30

BH00 0.5 0.5 10.9 82.5 nd 0.6 0.8 1.4 0.7 2.0

BH10 0.6 0.5 12.6 79.3 nd 0.8 0.8 2.1 0.8 2.6

BH20 0.5 0.6 13.0 76.7 nd 1.0 1.3 2.0 1.0 3.9

BH30 0.5 0.6 13.0 76.7 nd 1.0 1.3 2.0 1.0 3.9

Na Mg Al Si P S K Ca Ti Fe

Figure 5.4: Analytical Data on Bulk Ash Samples (High Excess Air Firing)

23

In Figure 5.6 similar results are presented from the test run No 3, during which the same wood chips as in test run No 5 were fired together with addition of elemental Sulfur. As can be seen from this figure the share of sulfur is increased in all the size fractions at the same time as chlorine is decreased in the sub micron sized particle fraction. It seems obvious that chlorine is replaced by sulfur in the sub-micron particles while calcium is reacting with sulfur in the super-micron sized particles. This replacement mechanism is also well known from earlier studies.

It is interesting to note the behaviour of calcium. Calcium is found mainly in the super-micron sized particles, which clearly indicates its presence in the fuel in another form than alkali sulfur or chlorine.

One could speculate that in woody typed biomass such as wood chips fired here, much of the inorganic ash forming matter would be tied up in the fuel as organically bound ions or as ions in the plant moisture. A further implication would be that this type of matter could be easily released from the fuel during a combustion process and would eventually form sub-micron sized ash particles. This is, however not the case.

0

10

20

30

40

50

60

Na2O MgO Al2O3 SiO2 P2O5 SO3 Cl K2O CaO MnO Fe2O3

wt-%

60 nm

100 nm

170 nm

260 nm

400 nm

650 nm

1,0 µm

1,6 µm

2,5 µm

> 10 µm

Figure 5.5: In-situ fly ash sampling from the test run No 5, 100 % wood chips. All analyses were performed with SEM/EDS. The size fractions 30 nm, 4.0 µm, 6.8 µm, 10.3 µm were not analysed.

24

In SEM/EDS analyses performed by ECN (partner 11) on the wood chip fuel, fired at Jordbro, they could clearly show the presence of micron sized calcium rich minerals, possibly calcium oxalate, in the fuel. It seems that these minerals form CaO particles of some 2-5 µm in size when they are released from the wood chip.

They are thereafter transported up through the fluegas channel and form one part of the fly ash. Part of the CaO may form CaCO3 as the particles pass the temperature region of some 780-880oC. These particles may also form deposits on heat exchanger surfaces if they impact on a surface at such conditions that they can recarbonate on the surface. Recarbonation of CaO has been shown to cause deposits /Skrifvars et al., J.Inst Energy, Vol 64, No 461, 1991/. In fact some of the deposits collected in Jordbro at the hotter sampling location (see ABO 1st Annual report Fig 1.), during firing of wood chips seem to suggest such behaviour.

The implication from these analyses towards ash behavior predictions is that careful fuel analysis gives information about what ash-forming elements and minerals enter with the fuel into the boiler. These can be tracked down in the boiler and their behavior can be estimated when their composition and size is known

0

10

20

30

40

50

60

Na2O MgO Al2O3 SiO2 P2O5 SO3 Cl K2O CaO MnO Fe2O3

wt-%

60 nm

100 nm

170 nm

260 nm

400 nm

650 nm

1,0 µm

1,6 µm

2,5 µm

> 10 µm

Figure 5.6: In-situ fly ash sampling from the test run No 3, 100 % wood chips + 0,1 % elemental Sulfur. All analyses were performed with SEM/EDS. The size fractions 30 nm, 4.0 µm, 6.8 µm, 10.3 µm were not analysed.

25

Ash Fusion Tests (IVD)

Ash fusion tests (AFT) were carried out for the fly ash samples from the pilot scale at IVD. The small amount of fly ash collected in the bench scale facility did not allow this type of analysis for all the samples.

Figures 5.7a through 5.7c. present the fusion curves of ash samples collected in the particle control devices of the pilot scale facility during co-combustion of straw. The height of the cone prepared with the sample is plotted against the initial height for increasing temperatures. A first slow but constant loss of height indicates a softening of the ash, corresponding to a sintering process. Once the melting temperature is reached, the sample looses height at a clearly higher pace, showing a marked inflexion point in the curve. After this point, the ash melts creating a slag.

The addition of biomass has a very clear influence on the fusion behavior of the fly ashes. In general, the ashes produced during biomass co-combustion present lower melting points than those corresponding to pure coal flames.

As the figures show, already a 12,5 % (thermal input) of straw lowers the melting temperature about 50°C for all of the fractions. The effect turns determinant by a 25% of straw, where the melting points sink about 100°C in the finer fractions (bag filter, < 10µm) and up to 200°C in the courser samples (bottom ash and air preheater), down to the 1000°C region, temperatures which can be very commonly found in superheater regions of industrial utilities.

Air Preheater

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

1,1

700 800 900 1000 1100 1200 1300 1400 1500

Temperature [°C]

rela

tive

heig

ht

0%

12,50%

25% Straw

50%

100%

Fig. 5.7a: Ash Fusion Curves for Fly Ash Samples from Straw (S-IVD3) Co-Combustion at the Pilot Scale Facility.

26

But the major effect of biomass turns relevant when comparing the sintering ranges of the ashes.

While the ashes originated during pure coal combustion do not tend to major sintering at

Cyclone

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

1,1

700 800 900 1000 1100 1200 1300 1400 1500

Temperature [°C]

rela

tive

heig

ht

0%

12,50%

25% Straw

50%

100%

Fig. 5.7b: Ash Fusion Curves for Fly Ash Samples from Straw (S-IVD3) Co-

Combustion at the Pilot Scale Facility.

Filter

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

1,1

700 800 900 1000 1100 1200 1300 1400 1500

Temperature [°C]

rela

tive

heig

ht

0%

12,50%

25% Straw

50%

100%

Fig. 5.7c: Ash Fusion Curves for Fly Ash Samples from Straw (S-IVD3) Co-Combustion at the

Pilot Scale Facility.

27

temperatures below 1150°C, the ashes created during co-combustion, e.g. in the case of straw, commonly present severe sintering processes already for temperatures as low as 900°C, or even 800°C for some of the cases. This behavior predicts the formation of highly sintered deposits all over within the furnaces and superheater regions, in some cases even in convective sections.

The combination of early sintering and high ash contents, e.g. in the case of sewage sludge and most of the straws, allows to predict the formation of bulky deposits, with a high sintering degree and therefore high porosity, which will be responsible for considerable reductions on the heat transfer to the tubes, and therefore on the efficiency of the utility.

Ash Viscosity (DTU)

The viscosity of the fly ashes was measured by the partner DTU. The results of some selected samples are presented here and compared with the existing models for ash viscosity calculation in an attempt of modeling the behavior of the ashes. A summary of the selected models and detailed information on the analyzed samples and results can be found in the report of DTU in the Annexes.

A pretreatment of the sample was necessary for the viscosity measurements, including ash washing with water (mainly water soluble contents in the ashes, alkali chlorides and sulfides), combustion of residual carbon and melting.

Viscosity measurements

Table 5.1 contains the technical data for the five test runs on a sample collected at the pilot scale rig at IVD’s facilities during the co-combustion of a 50%th blend of bituminous coal and chlorine rich straw.

Table 5.1: Technical data for ash viscosity measurements for OPTEB 19 ash hopper.

Measurement run # 1 2 3 4 5

Temperature (°C) 1468 - 1285 1297 - 1114 1106 - 1031 1466 - 1413 1359 - 1171

Rotational speed (rpm) 35 - 23 2.5 – 1.2 0.05 – 0.02 35 - 31 10 – 6

% Torque 7 – 42 4.6 - 77 5.2 - 94 7 - 11 7 - 97

The measured data is presented in a tabulated form in Table 5.2. The standard deviations on the viscosity estimate for each temperature lie in the range 0.7 % to 9.5% of the measured viscosity with the highest values at high viscosities, especially measurement series 3.

Table 5.2: Temperature vs. viscosity for OPTEB 19 ash hopper. By visual examination of the graphical representation.

28

Temperature (°C)

1050 1075 1100 1125 1150 1175 1200 1225 1250

Viscosity (Pa∀s) 700000 160000 57000 22000 12000 5600 3500 2300 1375

Temperature (°C)

1275 1300 1325 1350 1375 1400 1425 1450

Viscosity (Pa∀s) 900 620 435 310 229 172 130 98

Modeling

The eight models presented in the report have been tested on this ash. The models are applied to the studied ash by a re-calculation of the composition according to the results of the washing procedure. This has been achieved by assuming that one liter of water was used for each wash, and then the resulting ion-removal has been calculated. This result has been related to the ash compositions by assuming that all chlorine was removed by the washing.The resulting composition is listed in Table 5.3.

Table 5.3: Recalculated ash composition for OPTEB 19 ash hopper.

Oxide SiO2 Al2O3 Fe2O3 MgO CaO Na2O K2O TiO2 P2O5

Mole -% 76.43 0.70 1.19 4.54 10.23 0.63 5.28 0.08 0.92

Weight-% 73.08 1.14 3.01 2.91 9.13 0.63 7.92 0.10 2.08

The performance of the models is compared to the measured viscosity vs. temperature relationship

OPTEB19 Ash Hopper

1 E+1

1 E+2

1 E+3

1 E+4

1 E+5

1 E+6

1 E+7

1300 1400 1500 1600 1700 1800

Temperature (K)

Vis

cosi

ty (

Pa*

s)

Watt-Fereday

Measurements

Urbain

S2

Kalmanovitch

Shaw

Riboud

Lakatos

Botting-Weill

Figure 5.8: Performance of eight mathematical models for OPTEB 19 ash hopper.

29

for the OPTEB 19 ash hopper sample in Fig 5.8. No model is able to reproduce the curvature of the measured graph, this may be due to either a lack of accuracy in the models, but it may also be due to the onset of crystallization during cooling. The Urbain model [17] produces the best fit at the high-temperature range, but most models give fits that fall within an order of magnitude from the measured viscosities. However, the Bottinga-Weill model that is not able to cope with the composition of the ash and thus predicts a positive inclination of the viscosity-temperature graph.

Studies were made for increasing shares of the presented straw. An implication of the ash viscosity study is that apparently the addition of wheat straw to coal decreases the viscosity of the resulting ash and thus makes the ash more prone to deposit formation.

Furthermore, the study has shown that no single mathematical model is capable of predicting the viscosity of ash samples from the co-firing of coal and straw. The results of some selected samples are plotted in the Figure 5.9.

Morphology (IVD)

Some selected samples underwent specific advanced analytical work to identify the morphology of the fly ashes.

With the help of x-ray diffraction, the mineral phases in the ashes were determined and compared with the chemical composition determined by x-ray fluorescence or under the electronic microscope.

Comparison of Ash Viscosities

1E+1

1E+2

1E+3

1E+4

1E+5

1E+6

1E+7

1300 1400 1500 1600 1700 1800 1900

Temperature (K)

Vis

cosi

ty (

Pa*

s)

BH00OPTEB 20 air preheater

OPTEB 20 ash hopper

OPTEB 19 air preheater

OPTEB 19 ash hopper

Figure 5.9: Measured viscosity vs temperature relationship for the ashes that

have been studied in this report.

30

The finer ash particles, which were collected during the pilot scale tests carried out by the partner IVD in the bag filter, present e.g. some of the identified trends which explain common mechanisms between the flue gas and the deposits.

For the co-combustion of ash hard coal and a 25% of straw, a low crystalline content indicates a high share of amorphous silicates in the ash. The composition is clearly dominated by silicon (Si) and aluminum (Al) species. The silicates formed with alkali elements, in higher concentrations in the biogenic fuels, present lower fusing temperatures and will act therefore as the sticky matrix of the deposits.

The fine filter ash of brown coal and 50% straw is clearly dominated by the elements K, Na, Cl and S. Here the low ash amount and high sodium contents in the coal and high potassium and chlorine content in biomass result in gaseous alkali species that condense on the high specific surface particles, and are expected to be found on the deposits as condensed particles.

mpa - Labor für Materialprüfung und -analyse GmbH

20-0928 (I) - Aphthitalite, syn - K3Na(SO4)2 - Y: 50.00 % - d x by: 1.000 - WL: 1.5405641-1476 (*) - Sylvite, syn - KCl - Y: 100.00 % - d x by: 1.000 - WL: 1.5405605-0628 (*) - Halite, syn - NaCl - Y: 34.02 % - d x by: 1.000 - WL: 1.5405637-1496 (*) - Anhydrite, syn - CaSO4 - Y: 18.14 % - d x by: 1.000 - WL: 1.5405646-1045 (*) - Quartz, syn - SiO2 - Y: 8.27 % - d x by: 1.000 - WL: 1.5405645-0946 (*) - Periclase, syn - MgO - Y: 18.61 % - d x by: 1.000 - WL: 1.54056C:\DIFFDAT1\Uni Stuttgart Filter 19.RAW - Type: 2Th/Th locked - Step: 0.040 ° - Step time: 1.0 s - WL1: 1.54056 - Company: mpa GmbH LeipzigD5005 - Creation: 05/12/99 11:57:40

Lin

(Cou

nts)

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

180

190

200

210

220

230

240

250

260

270

280

290

300

2-Theta - Scale

8.5 9 10 11 12 13 14 15 16 17 18 19 2 0 2 1 22 23 24 25 26 27 28 2 9 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Peri

klas

Qua

rz

Anh

ydrit

Hal

it

Hal

it

Sylv

it

Sylv

it

Aph

thita

lit

Aph

thita

lit

Aph

thita

lit

Aph

thita

lit

Aph

thita

lit

Aph

thita

lit

Aph

thita

lit

Filter 19

Fig. 5.10b: X-ray diffraction analysis of filter ash produced during co-combustion of lignite

(Coal-IVD1) and a 50%th of straw (S-IVD3)

31

This condensation effect was even observed for the pure biomass flames, where the low sulfur and very high potassium and chlorine contents resulted in very high concentrations of KCl in the filter ashes.

5.2 Deposits

The results of the analytical work on the deposit samples to determine their chemical compostion, morphology, ash fusion behavior and the measurements made in situ on the coupons, such as the deposition rate and the degree of fusion of the samples are discussed in the following section and an example for each is presented.

Chemical Composition

- Water Soluble (ENEL)

On the S. Gilla Simulator 5 tests were performed using coal and two different biomasses, wood and straw at two different biomass fraction. For each test two samplings were performed in order to measure the total deposition rate and to take the amount of deposit to analyse. The results are summarised in the table 3. For each test the distance from the wall, the gas and probe temperature, the TDR and the water soluble part of the deposit are reported. (the soluble part is analysed in order to measure pH, Al, Si, Na, K, Mg, Ca, Cl, NO3, SO4).

mpa - Labor für Materialprüfung und -analyse GmbH

10-0360 (D) - Anorthite, sodian, disordered, syn - (Ca,Na)(Si,Al)4O8 - Y: 20.83 % - d x by: 1.000 - WL: 1.54056

01-0613 (D) - Mullite - Al6Si2O13 - Y: 50.00 % - d x by: 1.000 - WL: 1.5405639-1346 (*) - Maghemite-C, syn - Fe2O3 - Y: 50.00 % - d x by: 1.000 - WL: 1.5405609-0216 (D) - Gehlenite - Ca2Al2SiO7 - Y: 29.17 % - d x by: 1.000 - WL: 1.5405601-0993 (D) - Halite - NaCl - Y: 29.17 % - d x by: 1.000 - WL: 1.5405633-0664 (*) - Hematite, syn - Fe2O3 - Y: 50.00 % - d x by: 1.000 - WL: 1.5405637-1496 (*) - Anhydrite, syn - CaSO4 - Y: 55.30 % - d x by: 1.000 - WL: 1.5405646-1045 (*) - Quartz, syn - SiO2 - Y: 100.48 % - d x by: 1.000 - WL: 1.54056C:\DIFFDAT1\Uni Stuttgart Filter 20.RAW - Type: 2Th/Th locked - Step: 0.040 ° - Step time: 1.0 s - WL1: 1.54056 - Company: mpa GmbH LeipzigD5005 - Creation: 05/14/99 09:07:57

Lin (Counts)

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

2-Theta - Scale

8.5 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Quarz

Anhydrit

Filter 20

Mullit

Mullit

Mullit

Mullit

HalitHalit

MaghemitHämatit

Gehlenit

Anorthit

Fig. 5.10a: X-ray diffraction analysis of filter ash produced during co-combustion of

bituminous coal (Coal-IVD2) and a 25%th straw (S-IVD3)

32

From the analysis of data it appears evident the effect of co-combustion on TDR <10 mg/cm2h with coal, between 10 and 25 mg/cm2h with coal/wood as fuel and between 30 and 300 mg/cm2h with coal/straw as fuel.

The elements contained in the soluble part of the deposit are mainly calcium which is predominant with coal, sodium and potassium with increasing amount moving from wood to straw and increasing the biomass/coal ratio.

The gas and probe temperature were measured during the sampling and it was possible to understand the influence of these parameters on the deposition.

All the results of the field measurements and the lab analysis are showed in Table 5.4. Some of the salts deposited onto the particles are not soluble in water but are soluble in acid. It is the case of the calcium and magnesium sulfate and calcium phosphate. These salts can be also responsible of the deposition, they can increase the stickiness of the particles or decrease the overall particles fusion temperature or viscosity. The insoluble part of the deposit was extracted with HCl 1N. A table summarizing the results of this investigation can be found in the final report of the partner ENEL. The composition of the solution can be mainly related to TDR and to other deposition parameters such as gas and probe temperature.

33

The data was treated with the PCA in order to find the clusters of parameters. It appeared, from the application of PCA to the data matrices of the water soluble deposit and HCl soluble deposit composition, that this technique can discriminate between tests carried out in different experimental conditions and allows to find the chemical associations which can favor the deposition tendency of a fuel or a fuel mixture.

Table 5.4: Composition of the soluble deposit in water Fuel Coal Dist Tp Tgas pH AL SI NA K MG CA CL SO4 SOL TDRtype % cm °C °C % % % % % % % % % mgcm

-2h

-1

coal 100 115 651 1522 6,7 0,2 0,0 4,7 0,5 4,1 22,5 2,2 65,7 5,4 4,0coal 100 80 633 1390 7,7 0,6 0,0 3,1 0,8 4,5 20,1 0,2 70,3 2,9 9,6coal 100 40 613 1268 9,1 0,8 0,0 3,9 1,3 5,6 17,3 0,0 71,0 7,0 5,0coal 100 105 637 1319 7,4 0,6 0,0 4,4 1,2 3,7 23,0 3,6 63,2 4,8 3,2coal 100 75 623 1330 8,7 1,2 0,0 2,5 0,9 4,3 21,8 0,6 68,5 4,9 4,2coal 100 45 609 1338 8,7 1,2 0,0 3,5 1,4 4,9 19,8 0,4 68,7 5,5 4,4coal/wood 80 105 637 1461 7,6 0,0 0,0 3,5 2,4 3,2 19,2 0,7 70,7 3,0 8,9coal/wood 80 75 621 1375 9,0 0,6 0,0 4,3 4,8 2,8 17,2 0,2 70,1 9,1 5,3coal/wood 80 45 605 1303 9,4 0,4 0,0 5,8 7,2 2,6 15,2 1,0 67,7 9,7 5,4coal/wood 80 105 647 1461 8,2 0,2 0,0 3,6 3,0 2,8 20,1 0,7 69,4 9,3 3,0coal/wood 80 75 632 1375 9,1 0,4 0,0 4,8 4,6 2,5 17,4 1,1 69,1 10,0 4,8coal/wood 80 45 618 1303 9,4 0,4 0,0 5,5 6,8 2,7 14,5 0,5 69,5 10,4 4,9coal/wood 50 105 661 1470 9,6 0,4 0,0 4,4 14,5 1,3 13,0 0,4 65,9 23,4 4,6coal/wood 50 75 647 1370 10,6 0,4 0,6 4,0 16,0 0,2 16,0 0,2 62,6 14,6 10,1coal/wood 50 45 632 1285 10,7 0,4 0,6 4,5 19,0 0,2 15,1 0,2 60,0 13,8 10,8coal/wood 50 105 696 1470 10,8 0,5 0,8 4,2 16,0 0,2 20,9 0,2 56,9 12,5 11,1coal/wood 50 75 686 1370 11,2 0,5 1,0 4,0 17,4 0,0 22,7 0,0 54,3 7,5 24,3coal/wood 50 45 675 1285 11,3 0,6 1,0 4,2 20,7 0,0 22,4 0,0 51,1 7,0 25,8coal/straw 80 105 679 1306 10,2 0,1 0,0 4,6 36,7 0,1 3,0 0,0 55,3 35,3 28,5coal/straw 80 75 662 1294 11,0 0,2 0,2 4,2 35,9 0,0 5,5 0,0 53,7 15,5 80,3coal/straw 80 45 645 1283 10,9 0,2 0,1 4,2 37,0 0,0 4,9 0,0 53,3 19,2 62,2coal/straw 80 105 692 1306 9,2 0,1 0,0 4,6 37,6 0,2 2,2 0,1 55,1 41,5 23,7coal/straw 80 75 682 1294 10,5 0,1 0,0 4,6 37,6 0,1 3,4 0,1 53,9 25,0 51,5coal/straw 80 45 671 1283 10,6 0,2 0,0 4,5 37,7 0,1 3,9 0,1 53,5 22,1 60,3coal/straw 50 100 666 1312 11,0 0,1 0,1 6,0 32,2 0,0 6,4 1,2 53,9 12,3 145,1coal/straw 50 75 656 1313 11,3 0,1 0,2 5,8 32,7 0,0 7,4 3,6 50,1 7,6 294,1coal/straw 50 45 644 1314 11,3 0,1 0,3 5,6 34,3 0,0 6,6 7,1 45,8 10,7 224,9coal/straw 50 100 670 1312 11,0 0,1 0,1 4,1 36,4 0,0 5,6 1,0 52,7 12,9 123,6coal/straw 50 75 659 1313 11,4 0,1 0,3 3,8 35,3 0,0 7,3 2,8 50,3 7,1 262,2coal/straw 50 45 647 1314 11,4 0,1 0,2 3,8 36,4 0,0 6,9 6,7 45,9 8,3 259,7

34

- XRF / ICP / SEM-EDX (ALSTOM)

The main effort of the analytical work was made to determine the inorganic composition of the deposits. Several analytical methods were used by the different partners, from XRF and IPC to SEM-EDX. An example is given here, corresponding to samples collected by the partner ALSTOM Combustion Services Ltd. and analyzed by the partner ECN. The samples were collected on X22 coupons during the co-combustion of Colombian coal and wood flakes with a 5% air excess.

Following the instructions of partner ECN, the deposits were “fixed” to the coupon by embedding in resin (Figure 5.11). The choice of a resin (Epofix) with a low curing temperature, and the limiting of the embedding layer to 5 mm avoided any heat-related problems that might damage or modify the deposit.

Figures 5.12 and 5.13 contrast the composition of the deposits analysed by partner ECN, on the windside (WS) and leeside (LS) of the coupons for low excess air firing on the coal as the stand-alone fuel and the coal with additions of 10 % and 30 % wood flakes. Details of the coupon sectioning and sample preparation together with the analytical technique are given in the report of ECN. The analysis and comparison represents part of Task 4 of the project.

0.10

1.00

10.00

100.00

% (

norm

alis

ed)

DL00_WS DL10_WS DL30_WS

DL00_WS 0.3 3.9 8.0 19.7 0.4 0.7 0.5 0.5 8.1 57.8

DL10_WS 0.2 2.8 21.1 26.8 0.4 0.3 1.0 0.6 4.7 54.1

DL30_WS 0.4 0.8 21.3 18.4 0.3 0.5 0.5 0.6 2.3 65.6

Na Mg Al Si P S Cl K Ca Fe

Figure 5.12: Analytical Data on Windside Deposit Samples (Low Excess Air Firing)

Figure 5.11: Test coupons with deposit embedded in resin

35

0.10

1.00

10.00

100.00%

(no

rmal

ised

)DL00_LS DL10_LS DL30_LS

DL00_LS 0.7 1.0 18.9 57.8 0.6 0.5 1.9 2.9 2.0 13.8

DL10_LS 1.0 0.6 18.0 56.5 1.0 0.6 2.8 2.4 2.8 14.3

DL30_LS 0.7 0.8 21.1 52.1 1.2 0.3 2.7 3.6 1.6 15.9

Na Mg Al Si P S Cl K Ca Fe

Figure 5.13: Analytical Data on Leeside Deposit Samples (Low Excess Air Firing)

Results demonstrate a clear difference between the compositions of the windside and leeside deposits. The windside deposit is notable for the predominance of iron, as well as inflated contents of calcium and magnesium. The leeside deposit composition is much closer to that predicted from the laboratory ash analysis, but shows some inflation of the potassium content, and possibly, the sodium and phosphorus contents. There are no obvious trends obtained in the composition, with biomass addition.

36

Figure 5.14: SEM photographs of windside (left) and leeside (right) deposits for 0 % (top), 10 % (middle) and 30 % (bottom) biomass additions. Note different magnifications.

Photographs by courtesy of ECN.

Deposition Rate (ENEL)

Modelling TDR as a function of the fuel composition The mechanism of deposition is very complex. A physical model that should be able to predict the fouling tendency of a fuel must be take into account all the thermodynamic properties of the mineral inclusions in order to be able to describe the properties of the generated ash. These data together with a fluid-dynamic description of the motion field in the exchanger zone can provide such prediction tool. Another approach can be to make an empirical model using the fuel composition and the deposition descriptive parameters as gas temperature probe temperature and total deposition rate measured

37

during the co-combustion tests at the S. Gilla Simulator. These data were analyzed using . It is assumed that deposition depends only on the gas temperature, the tube temperature and on the fuel composition. The regressive technique used in order to predict TDR is PLS (Partial Least Squares) which is able to treat block of variables even if they are

correlated each other in order to build a multivariate model. Figure 5.15 shows the results of the application of this technique to the simulator experimental data-set in terms of evaluated Total Deposition Rate (standardized) against the experimental one. In the fig. 27 a group of points in the bottom left are relative to the lowest TDR and refer to the baseline tests with coal and with coal and wood while on the bottom right there are the tests with coal and straw. The built model is not applicable to all the plants, it represents in terms of trend which can be the behavior of the tested fuels even on another plant but the coefficients of the found relationship must be evaluated for every plant. The used empirical approach produces a correlation between the input parameters and the response (TDR) but the some calibration tests must be made before adopt it on other plants or in another plant set-up. More over it must be noted that all the measurements used for the TDR evaluation were made with a clean SS tube but the exchanger tubes are not clean during the normal run and a kinetic factor dependent on the time could be introduced after tests designed for this purpose.

Fig. 5.15: TDR evaluated by PLS vs. Experimental

38

Morphology (ECN)

Figures 5.16a to 5.16e represent an example of the studies on the morphology of the deposits carried out by the partner ECN. In the pictures the deposits collected during straw co-combustion.

5.16a / 5.16b

Deposit with molten (spehrical) K-Ca-silicate particles covered by potassium sulphate; the details show sticky inorganic material (potassium sulphate) directly attached to metal surface

5.16c/ 5.16d

Deposit with molten (spherical) silicate particles from original straw (left) and non-molten (angular) silica particles from straw that was extracted with H2O, NH4Ac and HCl (right)

39

5.16e Deposit from straw-coal co-firing showing mainly aluminosilicate particles with K and S enrichment

Ash Fusion Tests (RWE)

Brown coal

As expected showed the pure coals, depending on the temperature at the end of the furnace chamber, a varying S&F-behaviour:

• The coal from Garzweiler led to sulphatic deposits at temperatures up to 1150°C and to sulphurfree, silicatic deposits at 1250 °C with a soft consistency.

• The ash-poorer coal from Hambach (Ha 42) produced sulphatic deposits up to 1150 °C. Remarkable, that the consistency of the deposit at 1050 was stated harder than that at 1150 °C.

• The ash fusion behaviour of the deposit from the end of the furnace chamber at 1150 °C is characterized by a hemisphere point at 1380 °C.

• The coal from Hambach with a higher ash-, that means Quarz content (Ha 45) led to sulphur poor deposits at 1050 °C and sulphur free deposits at 1150 °C and 1250 °C with comparable soft consistency.

• In comparision with the results of Ha 42 it seems, that small ash content variations of 1 % vary the character of the deposits produced at 1150 °C.

40

In general the sulphatic character of deposits increases with a decreasing building temperature, that means more sulphur in the samples from the colder part of the furnace chamber.

Degree of Fusion (IVD)

Table 5.5: Parameter of fusion behaviour for deposit samples

Sample-parameter

Deposit; position door 10 (Temperature fluegas: 1150 °C)

Sintering[ °C ]

Deformation[ °C ]

Hemisphere[ °C ]

Flow[ °C ]

Ash fusion behaviour (DIN 51730)

1390

1230

12101160

1020 1340 1380

1010 1080

1080

1130

Flame 1-43 (Ha 42 / 30% straw, λB = 0,8)

Flame 2-07 (Ha 45 / 30% straw, λB = 0,8)

Flame 1-46 (Ha 42 / 30% straw, λB = 1,1)

Temperature point ( Oxidizing atmoshere )

Flame 2-02 (Ha 42 / pure, λB = 0,8)

1130 1180 1230890

930

41

Fusion Behavior

The deposit samples collected at IVD’s test facilities were as well classified according to their degree of fusion observed with bare eye. The main concern by the specification of the classification criterion was the bonding strength of the particles and the estimated success of cleaning devices at utility boilers. The different structural stages are presented in the Table 5.6. An example of the influence of the flue gas temperature on the degree of fusion of the deposits is shown on the Figure 16 for the co-combustion of a 10%th of straw with lignite at the bench scale rig. The same effect is plotted on the Figure 17a through 17c for the combustion tests at the pilot scale facility with different shares of straw.

Table 5.6: Classification criterion for the deposit samples

Degree of Fusion Deposit Structure (bare eye observation)

1 Powdery, not bonded

2 Powdery with slight sintering

3 Slightly sintered

4 Sintered

5 Hardly sintered

6 Sinter with partial slag

7 Slag with partial sintering

8 Slagged

Fig. 5.17: Influence of the temperature on the degree of

fusion observed on the deposit coupons collected at the bench scale rig.

42

The degree of fusion of a deposit was introduced as a simple method for classification of the deposits in order to analyze the influence of parameters, such as biomass type and share, flue gas temperature, etc., on the slagging and fouling processes.

Figure 5.18 shows the influence of the biomass type on the degree of fusion of the coupons The samples compared correspond to blends of 25% thermal share in the case of sewage sludge and wood and 20% for the straw. The type of secondary fuel has a clear influence on the degree of

fusion; the differences in the sintering points go here up to 300°C.

These results could unfortunately not be directly predicted from the fusion behavior of the lab ashes of the corresponding fuels. According to the data from the fuel analysis for S-IVD3, SS-IVD and W-IVD, the fuels used for the trials plotted, the sewage sludge should have presented the lower degrees of fusion of all three fuels.

An effect to take into account is the different ash contents of the fuels. The blends were made on energetic basis, considering the heating values of each fuel. With this point of view, the ash apportionment results in values that vary from a 2% in weight for the wood, through a 56%wt for the straw, to a 92% in weight for the sewage sludge.

The ash content, which makes of the wood clearly the best candidate to avoid slagging and fouling, is anyhow clearly not the only parameter to take into account. The composition of the fuel, in this case the high concentration of chlorine in the straw, can not be excluded of the prediction chain.

The ashes produced during the co-combustion of wood show the highest softening and fusion points. The very low ash contents of wood are its main favorable characteristic, allowing shares up to 50% of the thermal input, not expecting sintering problems until well over 1150°C.

0

1

2

3

4

5

6

7

8

9

900 1000 1100 1200 1300 1400

Flue Gas Temperature [°C]

Deg

ree

of fu

sion

[1-8

]

Straw

Sew. Sludge

Wood

Slagging

Sintering

Lignite

Fig. 5.18: Influence of the secondary (approx. a 25%th share) fuel type on the degree of

fusion of lab scale deposition coupons.

43

The worst case corresponded to the straw ashes (S-IVD3), with sintering point clearly below 950°C and melting points down to 1100°C.

The melting points for straw ashes are reached at a lower pace as for the other biomass types, predicting porous deposits, not easy to clean, and that can grow considerably in height, resulting in an important reduction of the heat transfer.

The sewage sludge ashes present an intermediate behavior, with sintering beginning around the 1050°C. Anyhow, the high ash content and very low heating values of this type of biomass makes the region between the sintering and melting points a very dangerous one regarding the deposit formation. The sludge ashes reach then rapidly their melting point. Many of the deposit samples were therefore completely molten, showing a continuos glassy surface over the ceramic.

5.3 Correlation

The analytical data from the fly ashes and the deposits were correlated for the identification of the deposition mechanisms. The results from the impactor measurements made by partner ABO are presented, pointing out the trends identified.

Fly Ash vs. Deposit Composition (ABO)

As a separate part during the 1st measurement campaign additionally to the deposit probe sampling, ABO performed in-situ fly ash sampling with a Berner-type low-pressure cascade impactor. The wind side (side against the fluegas stream) and lee side (side turned away from the fluegas stream) were analysed separately..

A number of interesting trends can bee seen in these deposit analyses.

• Firstly it is clear that the deposit analyses vary fairly significantly compared to any of the fuel ash analyses, done on the laboratory ash during the fuel analysis stage. Nor is the fly ash sample, grabbed from the particle separator in the fluegas (in this case an ESP), comparable to the collected deposits.

• Secondly it is clear that the deposit analyses vary fairly significantly depending on which side of the tube they are situated on, and from where in the fluegas channel they are collected.

The obvious implication from these results towards ash behavior or corrosion prediction is that one should be very careful in making too far going direct conclusions made on the behavior of an ash sample received in a lab furnace, since the difference in the behavior may be significant.

• The deposit analyses also showed that high amount of chlorine and alkali could be found in the deposits occasionally even if the input amount of chlorine into the boiler together with the fuel was low or very low. The amount of chlorine increased significantly in the deposit only when the surface temperature of the sampling probe was decreased below some 500-550oC or when we moved the sampling location to a colder region in the flue gas channel (further out).

• Chlorine together with sulfur and alkalis were also enriched in the first layers of deposits found on the tubes. This showed up in the analyses mainly on the back side of the sampling rings, since the

44

front side also collected other material, which then covered the initial deposit layer.

• The amount of chlorine in the collected deposits could be decreased by adding sulfur to the boiler input, either as a more sulfur rich fuel, such as peat, or as elemental sulfur. In both cases it was shown that the chlorine amount in the deposits decreased.

The obvious implication from these results towards deposit formation or corrosion is that alkali chlorides and sulfates seem to deposit very effectively on heat exchanger tubes when firing biomass, even if the input amounts are low (mainly chlorine)

If sulfur is present in the flue gas it seems to prevent the formation of chlorides and chlorine seems to be driven of the system as HCl.

This is shown in Figures 5.19 and 5.20, where we compare the in-situ fly ash samples with short-term wind side deposit samples collected simultaneously.

0

10

20

30

40

50

60

Na2O MgO Al2O3 SiO2 P2O5 SO3 Cl K2O CaO MnO Fe2O3

Fly ash size: 2.5 µmWindside deposit Tsurf: 400 °C

wt-%

Figure 5.20: A comparison between the size fraction 2.5 µm of the in-situ fly ash sample and the wind side short term deposit. Samples collected during test run No 3 in Jordbro, pulverised firing of 100 % wood chips + 0,1 % elemental Sulfur.

45

0

10

20

30

40

50

60

Na2O MgO Al2O3 SiO2 P2O5 SO3 Cl K2O CaO MnO Fe2O3

Fly ash size: 2.5 µmWind side deposit Tsurf: 400°C

wt-

%

Figure 5.19: A comparison between the size fraction 2.5 µm of the in-situ fly ash sample and the wind side short term deposit. Samples collected during test run No 5 in Jordbro, pulverized firing of 100 % wood chips.

46

As can be seen from the figures the composition of the size fraction around 2.5 µm corresponds well with that of the wind side deposits. Since no major difference in compositions could b efound in the fly ash size fractions above 2.5 µm we can most likely conclude that particles larger than 2.5 µm have impacted on the wind side of the probe. This is well in line with common knowledge about particle behaviour in gases. The sticking mechanism has possibly been the recarbonation of the calcium rich particles since no other clear option is available.

We also compare separately the in-situ fly ash samples with short-term lee side deposit samples collected simultaneously and found the well established fact that sub-micron sized particles do not impact on surfaces but are transported by other mechanisms to tube surfaces. This is shown in

Figures 5.21 and 5.22.

0

10

20

30

40

50

60

Na2O MgO Al2O3 SiO2 P2O5 SO3 Cl K2O CaO MnO Fe2O3

Fly ash size: 150 nmLeeside deposit, Tsurf: 400 °C

wt-%

Figure 5.21: A comparison between the size fraction 150 nm of the in-situ fly ash sample and the lee side short term deposit. Samples collected during test run No 5 in Jordbro, pulverised firing of 100 % wood chips.

0

10

20

30

40

50

60

Na2O MgO Al2O3 SiO2 P2O5 SO3 Cl K2O CaO MnO Fe2O3

Fly ash size:150 nmLee side deposit, Tsurf: 400°C

wt-%

Figure 5.22: A comparison between the size fraction 150 nm of the in-situ fly ash sample and the lee side short term deposit. Samples collected during test run No 3 in Jordbro, pulverised firing of 100 % wood chips + 0,1% elemental Sulfur.

47

As can be seen the composition of sub-micron sized particles compare well with the lee side deposits collected simultaneously.

The impactor analyses show the following things.

• Alkali sulfates and chlorides seem to form sub micron sized particles in PF firing of wood. These particles reach heat exchanger surfaces mainly through different diffusion mechanisms such as termophoresis. Direct condensation of tubes may also be possible.

• It seems that chlorine almost quantitatively forms alkali chloride when firing wood type biomass and the alkali is found in a very reactive form in the fuel (not clay like in coal or selected peats). This explains why so high amounts of alkali chlorides are found in the deposits even if the in-going amount of chlorine to the boiler is very low. This also explains why the severe corrosion effects are seen in boilers firing wood type fuels. Chlorine is known to promote corrosion.

• The impactor analyses show also very clearly that calcium is found in a separate particle size-fraction that is transported to the tube surfaces by impaction. Most likely the primary form of the calcium particles in the fluegas channel is calcium oxide. Calcium has earlier been shown to be able to attach on surface by reaction with SO2 to calcium sulfate or by reaction with CO2 to calcium carbonate.

• Calcium rich mineral particles were found readily in the fuel with SEM/EDS analyses (see report of partner 11, ECN). These calcium rich mineral particles have most likely during the firing process formed calcium oxide particles of the size of a few microns, which then were detected both on the front side of the deposit rings as well as with the impactor.

The implication from these analyses towards ash behavior predictions is that careful fuel analysis gives information about what ash-forming elements and minerals enter with the fuel into the boiler. These can be tracked down in the boiler and their behavior can be estimated when their composition and size is known.

5.4 Prediction

Identified mechanisms for deposition are roughly described. A model for the deposit formation resulting from the lab scale investigations in then described. A procedure for estimating the stickiness of an ash through its chemical composition is given. Based on identified problematic species present in the fuels, key numbers for the prediction of deposition problems are listed. A very simple method for determining the risk of ash sintering using biofuel in commercial boilers was developed bay the partner TPS. The method relates the amount of mobile salts in a particular fuel to the ash sintering temperature by measuring the conductivity in water. This method is presented at the end of the section.

48

Mechanisms of Deposit Formation (ALSTOM)

The ash analyses from the co-firing trials are primarily a function of the coal ash composition, given the disproportionate ash contents of the two fuels. The small ash samples collected from the furnace exit show closest correlation with the composition predicted from the laboratory ash analysis. The bulk samples collected from the waste-heat boiler are unrepresentatively low in iron probably evidencing fall-out of heavier particles.

Figure 5.23 illustrates the aspects of deposit formation that will be influential to the composition and characteristics of the coupon deposit.

The manner in which the deposit accumulates on the heat transfer surface, here represented by the boiler tube, is strongly related to the particle size range of the ash, the geometry of the target and the dynamics of the gas stream.

The larger and heavier particles will impact the windside surface if they have sufficient inertia to leave

the gas streamlines around the tube. There is thus usually a preponderance of iron-rich particles, e.g. pyrites, found in the windside deposit. Rebounding of particles back into the gas stream may occur in cases of excessive kinetic energy and/or less receptive surfaces for capture.

Smaller particles will have a tendency to follow the gas streamlines because the drag forces on the particles are sufficient to keep them in the flow stream. Thus, these particles are less likely to impact on the windside of the tube, but have sufficient inertia to impact on the leeside; as a result of turbulent eddies in this region. Eddy impaction acts on particles of a size, e.g. 10 µm, between those that leave the gas streamline and impact on the windside of the tube, and those susceptible to the diffusion and thermophoresis mechanisms referred to below.

Small particles entrained in the gas flow, in the temperature gradient region around the tube, are also subjected to thermophoretic forces attracting them to the relatively low temperature surface. The thermophoresis mechanism is most apparent in the initial stages of deposit formation and for particles of less than 10 µm in size, the smaller the size, the greater the influence of the force. Thermophoresis is important at high temperatures such as those observed in the radiant section of a utility boiler.

BoilerTube

WS = Windside Deposit

Inertial Impaction

Diffusion /Thermophoresis

Gas Flow Streamline

EddyImpaction

ReboundSolids

Liquids

Vapour /Small Particles

WS LS

LS = Leeside DepositGas Flow Streamline

Figure 5.23: Deposit Formation Mechanisms

49

Vapour phase and small particles (<1 µm) are primarily transported to surfaces by diffusion mechanisms. These particles are usually enriched in species that have been volatilised in the flame. This is important as far as biomass is concerned, given that the ash may be relatively rich in alkali metals and phosphates in forms that are readily available for release into the gas phase by volatilisation. The vapour phase materials may condense in the stagnant boundary layer next to the heat transfer surface. The deposits formed by condensation are likely to be sticky and evenly distributed around the perimeter of a heat transfer tube, thereby increasing the surface capture ability.

The composition of the deposit will be determined to some extent by chemical reactions accompanying the ash transportation and deposition. The reactions include processes of both oxidation and reduction. Important also from the standpoint of biomass combustion, are the processes involving alkali metals. These include absorption into silica, thereby forming lower melting point silicates, and for co-firing regimes, sulphation through uptake of sulphur from the coal. The first effect is generally undesirable in that sintering will occur at lower gas temperatures, whilst the second effect is positive in limiting the amount of corrosive alkali chlorides in the deposit.

The results of deposit characterisation carried out by partners IVD and ECN on samples from the co-firing trials, show consistency with the above mechanisms of deposit formation. Inertial impaction explains the relatively large-size particle population of the windside deposit, represented by the iron-rich particles and probably, but to a lesser extent, dolomite particles. The smaller quartz and clay particles, predominant on the leeside of the tube may have been deposited by eddy impaction. Diffusion and thermophoretic processes may be attributed to the leeside deposition of alkali metals either as salts or in organically bound form.

Although the thermal properties, in terms of the conductivity and emissivity, of the deposit will be essentially dependent on the physical characteristics, these may be determined indirectly by the chemical composition, e.g. through colour modification. There is no evidence of significant change in the nature of the deposits with biomass addition that would be likely to influence the thermal properties. The thin and powdery characteristics obtained from four hours exposure of the heat transfer surface should not however, be taken as an indication that the thermal properties would not be seriously impaired.

Initial Deposition Mechanisms (ECN)

The initial formation of ash deposits in the convective section of biomass and biomass-coal fired systems has been studied in detail on several scales. Major mechanisms are discussed below.

Biomass Deposits

In lab-scale deposits from wood, straw and chicken manure, three typical deposits were distinguished (see Figure 5.24):

i) micron-sized sticky (molten) particles, ii) dense layers of deposit and iii) individual fly ash particles.

50

Figure 5.24 Biomass deposit types observed from lab-scale experiments

Type I is a sticky deposit that was found when sufficient sulphur was brought into the system. It was identified as micron-size “glassy” patches attached directly to the metal coupon surface. For all three biomass fuels, the main compound of this type of deposit was K2SO4, with smaller amounts of Si (straw), Ca (wood, straw, chicken manure) or Mg (wood). Some Na2SO4 was also found in the wood and chicken manure deposits.

Without sulphur addition no (wood) or very little (straw, chicken manure) sulphates were found, which is in agreement with literature and the full-scale tests with sulphur addition carried out by partner Vattenfall. Instead, a more uniform layer consisting of alkali chlorides and probably oxides or carbonates is observed. This is called type II. A new mechanism for the formation of type I (and II) is proposed and shown in Figure 5.25 based on the following arguments:

1) the fact that the sulphate deposits were always found as distinct patches can only be explained as particle deposition and not by heterogeneous condensation mechanisms that would otherwise have resulted in a more uniform deposit layer,

2) since no comparable patches containing e.g. KCl have been found when no sulphur was added, it is not likely that the sulphate deposits have been mainly formed by a mechanism that involves sulphating of already deposited material; ergo, sulphating prior to deposition is the more likely route,

3) K2SO4 has a 1072 °C melting point whereas KCl melts around 772 °C, which explains why K2SO4 (at least below this temperature) condenses onto fly ash particles while KCl may still remain gaseous; the superheater metal surface is cold enough (600 °C) for the KCl to condense on which explains the different deposit mechanism observed for this compound; direct condensation of sulphates onto the superheater surface could take place as well, but was effectively prevented by the large available fly ash surface,

4) K2SO4 condenses onto (sub)micron nuclei and may form completely molten eutectic mixtures such as K-S-silicates which then deposit as the observed sulphate patches; the availability of such nuclei has been shown by means of SEM-EDX fuel analysis of wood (calcium oxalate and phytoliths) and straw (silica)

5) larger fly ash particle are (partly) covered by K2SO4 either by similar heterogeneous condensation or by deposition of the described micron-size sulphate particles; as a result the fly ash particles become more sticky and, depending on their composition, obtain a lower melting point as has been shown by the extracted straw experiments.

Deposit type III is the result of inertial impaction and is general for all solid fuels containing inorganic

51

matter with a particle size larger than a few microns. There may or may not be a clear bonding with the metal surface on which the particles impact. It was generally observed that K2SO4 (type I) served as an effective bonding agent once it covered fly ash particles as described above.

The amount and overall composition of this type of deposit varies with the fuel but generally bear a good resemblance with the fuel inorganic bulk composition. With wood, mainly calcium sulphate particles are found in the deposit, with straw silicates and with chicken manure calcium phosphates

form the basis of this type of deposit.

Biomass-Coal Deposits

Co-firing biomass with coal changes the observed mechanisms in a number of ways. First of all, the coal ash will exhibit a diluting effect, by which any phenomenon that would occur when a pure biomass is fired, will be less pronounced. This effect is primarily determined by the ratio of the biomass to coal ash load. Secondly, most coals should be able to provide enough sulphur to form sulphate-based in stead of chlorine-rich deposits. Again, the actual biomass to coal ash ratio, but also actual boiler conditions will determine how effective coal can be in this respect. A third change relates to the interaction between biomass and coal-derived ash species. The coal fly ash offers a large surface area for the volatile biomass species to condense on and react with. In the case of wood co-firing up to 30% on a mass basis (lab-scale and full-scale, Alstom), no individual sulphate deposits were found. Only a very slight overall increase of alkalis could be observed, while at lower co-firing ratios no effects were observed at all. Also for the straw and the chicken manure, no sulphate deposits were found directly on the metal surface when 25% of the fuel was co-fired with

KCl (g)

KOH (g)

SO2 (g)

K2SO4 (g)

condensation impaction

thermophoresis

KCl (g)

KOH (g)

condensation

600°C

600°C

low T melt

K2SO4 (g)

nucleussubmicron Si or Ca

K2SO4, CaSO4,silicates

low T melt

evaporation

biomassparticle

KCl (g), KOH (g) (?),CaO/CO3

biomassparticle

1500°C 1200°C

evaporation

gas phase temperature

Type I

Type II

with S

without S

Figure 5.25 Proposed formation mechanism of sticky sulphate deposits (type I) and chloride

deposits (type II) on superheater tube surface

52

coal. However, significantly increased concentrations of biomass-derived species were found on the outer surface of clay minerals. In case of straw this was mainly K2SO4, while in case of chicken manure co-firing complete mergers between aluminosilicate particles and K2SO4-covered calcium phosphate particles were observed.

Ash Stickiness (ABO)

The analytsis and calculations show that the input knowledge i.e. what minerals and elements enter the boiler is very important to know if the thermodynamic calculations are to be used. When this is known the melting behavior estimation is a very powerful tool in assessing ash behavior predictions. If one knows roughly in what form an ash particle arrives to a deposit a simplified scheme can be used for estimating its stickiness according to the following procedure (the calculations must be done on a molar base):

1. Estimate all Cl and S to form alkali salts, rest alkali to form oxides. If there is rest S, then estimate this to form CaSO4. If there is still rest S, then estimate this to MgSO4.

2. Estimate all P to Ca3(PO4)2. If there is rest P, then estimate instead Ca2P4O7 to form.

3. Estimate all analysed (if analysed) loss of CO3 to CaCO3. If there is rest Ca, estimate that to CaO. If there is rest CO3, then estimate that to alkali, i.e. K2CO3 in first hand, Na2CO3 in second hand or depending on which (if any) there is left of.

4. Estimate all rest elements as oxides, indicating that these may be part of silicates (K2O, Na2O, CaO, MgO, Al2O3, Fe2O3, SiO2)

This gives now the folowing possibility to evaluate the stickiness of these compounds:

1. Alkali salts, (Na, K)2 (SO4, CO3, Cl2), reactive, partly molten 515 - 900oC, melting behaviour can be calculated

2. Earth alkali salts, (Ca, Mg) (SO4, CO3, O), reactive, solid < 1000oC, partly molten together with alkali > 650oC, uncertain calculations, phase diagram evaluations necessary. If CaO is found as such (mineral), it can also be problematic due to its reactions with CO2 to CaCO3 at som 800oC or SO2 to CaSO4 at temperatures > 800oC,

3. Phosphates, Ca3(PO4)2, inert, stable, solid < 1000oC, combinating with K, unknown, may form low melting compounds.

4. Silicates, oxides, K2O, Na2O, CaO, MgO, Al2O3, Fe2O3, SiO2, troublesome together with alkali and reduced form of iron, lowers the T0 and the viscosity, K2O-Al2O3-SiO2, partly molten > 695oC, Na2O-SiO2, partly molten > 790oC

Key Numbers for Prediction (TPS)

The key numbers for elements problematic in a combustion facility can either be used as a tool for predicting possible deposit problems but also for the evaluating possible reasons for observed deposition in a boiler. The different key numbers and the procedure for using in prediction is

53

described in section 2.3.2 below.

Description of Key numbers

Key numbers can briefly be described as a semi-empirical tool for rough prediction which elements that may be problematic in a combustion facility, i.e. elements possibly causing for instance formation of deposit in essential parts. The key numbers method has for a long time been used in the prediction of slagging/fouling and deposit formation in combustion of coal. Table 6 below shows a list of Key numbers that could be useful in case of biomass.

The Key numbers are a construction of quotas of direct comparison between different elements present in for example fuels, ashes or other substances present in the combustion process. For a correct stochiometric comparison is the Key numbers calculated using relative molar numbers for the elements. The Key numbers, based on relative molar numbers, offer the possibility to “wash” critical quotas between different elements directly related to risky components or blends of components.

The Key numbers in Table 6 are determined by using so-called relative molar number, mr, for the particular element on atomic basis. Since the ash chemistry mainly concerns the transfer of oxide ions is also the weight of each individual ash components considered and included in the equations. The ability to release or react with other oxide ions, i.e. the ash components either function as a Lewis-acid or a Lewis-base, varies for the different ash components. Also, other so-called anions, such as chloride and hydroxide should be considered. Readers not familiar with fundamental theory of chemistry are referred to standard chemistry literature. The relative molar number, R, is calculated using the relation,

elementelementC

r nRnM

m ∗=∗=ash in C of %

, Eq. 5.1

where C is an oxide component, MC is the molecule weight (g/mole) of the oxide component and nelement is the number of atoms of the element of interest in the oxide (for Fe2O3 is nelement = 2).

The weighting of the components are not always straightforward and in many ways based on experiences especially in case of the acidic ash components. Table 7 exemplifies the weighting of common acid and base ash components. These weightings are included in the equations in Table 5.

The most important Key numbers is 1-8 in Table 6. The general roles for these Key numbers can be described as follows:

Key number 1: Indicates if there is excess of basic oxides (>1). The excess cannot be bound in mineral form but in reactive and easily released oxide form or in other acidic form such as chlorides or sulphates.

Key number 2: The value for this number is more as for evaluating deposit samples. In a sample is in some cases iron oxide from corrosion of the tube material present. A large difference between numbers 1 and 2 indicates large amount of corrosion products in the sample.

Key number 3: A quotient >1 implies a not negligible risk for evaporation of alkali metal content in excess in salt or oxide form. Should be considered as a strong warning sign.

Key number 4: The fraction of the mobile alkali metals, potassium and sodium, in relation to total

54

amount of light metals. The number is always <1 and a number >0.5 should be treated as alarming, especially when key numbers 1 and 3 are high.

Key number 5: The number describes the maximum amount of alkali metals that could be bound in chloride and sulphate form. A number >1 implies that also other alkaline metals, such as calcium and magnesium, easily can be present in mixtures with the alkali metals.

Key number 6: Similar to 5 but includes also the possibility forming salts with phosphate.

Key number 7: The quotient gives an indication of the extent of sulfating that can take place related to amount of chlorine and sulfur available in the combustion system. This number should be considered with caution since there is many factors, such as transport phenomena and combustion temperature, that influence the amount available at different points in the system.

Key number 8: Indicates the maximal fraction of alkali metal that can evaporate in chloride form. A Key number around 1 or >1 probably implies that a large fraction of the alkali metal is converted to and also evaporated as chlorides. However, in case of biofuels the Key number rarely is larger than 1 but a number >0.5 is already a clear warning for chloride induced deposit formation.

The outline of important selected Key numbers gives only a hint of the possible use and evaluation using Key numbers generally requires a good knowledge in combustion systems as well as in inorganic chemistry (or chemistry of ashes).

A complete listing of the key numbers and their denomination can be found in the final report of partner TPS.

Conductivity measurement (TPS)

TPS has recently developed a very simple method for determining the risk of ash sintering using biofuel in commercial boilers [1]. The method relates the amount of mobile salts in a particular fuel to the ash sintering temperature [2-3] by measuring the conductivity in water containing water-soluble ions soaked from biofuel. At present, the report [1] is in Swedish and so far confidential but will soon be published.

Experiences from experimental test’s [4] have shown that around 80% and over 90% of the alkali metal and chlorine can be soaked from a biomass fuel prior to combustion. This forms the basis for the study and the first step was to determine how different ash composition correlate to the conductivity. By comparing the measured conductivity (taking into account amount of fuel used) and the electrochemical equivalent, i.e. amount of ions multiplied with the ion charge, the most important ions contributing to the conductivity could be determined, i.e. sodium, potassium and chlorine. The elements most readily released in the combustion process. The next step was to correlate the conductivity to the ash sintering temperatures and a linear relation was obtained using the equation,

)(exp

maB

CCabs −∗∗

=1

, Eq. 5.2

where Cabs is the absolute conductivity, Cexp is the measured conductivity, B is the amount of biofuel in gram, a is the fuel ash content and m is the fuel moisture.

55

0,00 0,25 0,50 0,75 1,00600

650

700

750

800

850

900

950

1000

Low risk for sintering

Large risk for sinteringS

inte

ring

tem

pera

ture

[°C

]

Cabs [mS/(g/l)]

Figure 5.26: Diagram for determining the risk for ash sintering for a particular biofuel by soaking.

An experimentally established relation between absolute conductivity and the temperature for ash sintering (broken-line).

By using experience and the results from the study a diagram, shown in Figure 5.26, has been established that can be used for determining the possible risks for ash sintering. From the figure is it possible to read that a measured absolute conductivity of 0.3-0.5 mS/(g/l) or above indicates risks for ash sintering problems. The grey area indicates an ash sintering temperature of around 900ºC where normally large ash sintering risks exist.

The practical procedure for determining the conductivity can roughly be described as follows:

1. Grind 25-50 g the particular biofuel and mix it in 1000 ml of distilled water and stir for ca 30 min.

2. Measure the conductivity

3. Determine the ash and the moisture content in the fuel

4. Calculate the absolute conductivity using the equation and determine the risk for sintering problem using the diagram in Figure 15.

The diagram and a simple conductivity measurement could be used as a simple predictive tool determining the ash sintering risks. Of course, is further work needed to relate these methods more to the different deposit formation processes taking place in a commercial boiler.

56

5.5 Conclusions

The work on the basic assessment of slagging and fouling potentials of ashes produced from fuels during pulverized co-combustion has given good results.

The development of testing and sampling methods suitable for co-combustion was successfully fulfilled, as well as the identification of the appropriate rig scale for representative experimental work on slagging and fouling. Deposition sampling methods consistent with the slagging and the fouling mechanisms on furnace walls and boiler tubes have been successfully tested, developed and applied.

A large amount of information was compiled from different fuels to ash and deposit samples for a broad range of fuels and blends, as well as from different test facilities and full scale power plants.

The main problem encountered during the comparison of the different results is the establishment of an objective evaluation criterion for the deposits. In spite of the several deposition mechanisms which have been identified and successfully verified, although an estimation of the slagging and fouling potential of a blend can be driven from its analytical data, no definite predictive tool could be developed due to the lack of an evaluation criterion taking into account related operational data, conditions and limits. A missing modeling of the phenomena drove to a lack of basic information.

There remains the problem of obtaining reliable measurements of the thermal properties on deposits, as a major concern for the evaluation of ash deposition on boiler tubes. The impact of deposition problems on the heat transfer efficiency would be the only reliable and measurable evaluation criterion. A possible approach to future investigation is to measure changes in the heat transfer in-situ using a small rig.

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6. CORROSION TESTS

Lab scale studies were made on the influence of the composition of the ashes on different materials for the construction of boiler tubes. The materials were tested as well in full scale facility, for the sake of the comparison with the results from the lab scale investigations.

In the following section, the results from the corrosion work are summarized. The corrosion results are the results of a good synergetic work of all partners involved in the corrosion group and the collaboration of partners of the slagging and fouling experimental group. A test method for corrosion experiments, developed by the industrial partner Mitsui Babcock, is firstly presented. Thorough guidelines for the corrosion measurements on the collected samples, established by the partner University of Cambridge, are outlined. The proposal of an identified corrosion mechanism follows, as well as the synergetic effect of deposition and corrosion phenomena. The results of kinetic studies and modeling are presented at the end of the section.

6.1 Corrosion Test Method (MBEL)

A test method has been developed by the partner Mitsui Babcock for the corrosion tests and further evaluation of the results, which is described in the following.

The corrosion test procedure has been developed to permit estimation of the metal wastage rates to a level of precision relevant to the industrial application i.e. the projected service life of the boiler tubes. It is widely accepted within the power industry that an acceptable rate of metal wastage is of the order of 25 nm h-1, which is equivalent to an annual wastage rate of around 0.2 mm, assuming linear wastage. The requirement, therefore, is to have the capability of measuring the metal wastage rates to a level of precision of around ± 10 nm h-1 or ± 10 microns after an exposure time of 1000 hours.

In order to achieve this level of precision, very careful machining of the metal coupons and accurate thickness measurements are required. The procedure adopted is as follows:

• A number of small coupons (10x10x4 mm) are manufactured from each of the test materials. The ferritic steel coupons have been manufactured to a thickness tolerance of ± 0.02 mm and the austenitic steel coupons have been manufactured to a thickness tolerance of ± 0.05 – 0.1 mm.

• The individual coupons are then subject to 9-point thickness measurements using a Carl Zeiss microscope. It has been found that individual coupons have thickness tolerances of ± 0.004 mm or better.

• The coupons are then coated on one side with the selected chemical treatment and placed on one of eight ceramic tile platforms on a metal frame, which fits inside the tube furnace. The frame has been fitted with eight thermocouples to provide a continuous measurement of the temperature on each stage. The furnace has three wire-wound sections, which are adjusted to provide a reasonably linear temperature gradient. The positions of the ceramic tile platforms are adjusted to provide eight exposure temperatures over the range 460-655 °C.

58

• On completion of the 1000 hour exposure, the coupons are removed from the frame and mounted vertically in cold-setting resin. The thicknesses of the metal coupons are then measured in polished section using an optical microscopic technique.

• The metal wastage rates are calculated from the pre and post-exposure coupon thicknesses by difference. This technique permits measurement of the metal wastage rates to a precision of around ± 0.010 mm (10 microns).

6.2 Analytical method and mechanisms (UC/VAB)

Test Procedures for Laboratory Corrosion Tests

The purpose of laboratory corrosion tests is to provide initial evaluation and/or ranking of material’s performances (usually among those commercially available), fuel chemistry and/or combustion conditions. It is also useful for investigating corrosion mechanisms. Such studies are fast and low cost but suffer from difficulties in reproducing real conditions that exist in industrial boilers. Pilot- and full-scale tests provide additional data to ensure the accuracy of laboratory tests. The basic sample preparation for the laboratory scale tests involved:

• Sample selection - prepared samples were ensured to be representative, e.g. cut from cross sections of real tubes;

• Accurate measurement of thickness - for evaluation of ash deposit induced corrosion, data from weight loss or weight gain are not applicable, due to possible internal corrosion and vaporisation of corrosion products. Thus, accurate thickness measurement by means of a microscope or SEM was essential. The higher the corrosion resistance the material under testing, the more accurate the method used;

• Identifiable and multiple - significant corrosion damage occurred when using both synthetic ashes and industrial fly ashes. Thus, special care was taken to ensure that samples buried in the ashes could be identified after testing;

• Uniform composition for ashes - this was important when mixing individual chemicals together to simulate particular ash compositions (synthetic ashes). From the literature, low-temperature pre-melting followed by ball milling is recommended and was used. For industrial ashes, care was taken to achieve uniform composition;

• Corrosion testing methods – studies were carried out at the University of Cambridge using the widely used “conventional crucible” method, whereby samples are buried in alumina crucibles filled with the relevant ash, which are then placed into the hot-zone of a tube furnace. Collaborative experiments using a small-scale combustion simulator were employed by ECN. The conventional crucible method is low-cost and suitable for long-term evaluation, but care was needed to cover samples with ashes of sufficient depth. This was to reduce the loss of volatile species within the furnace over a long period of time. The accuracy of this method can be improved significantly (with an increase in cost) by using controlled gas atmosphere for the test period. Combustion simulators are suitable for short-term, mechanistic studies;

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• Preparation of samples after test - it was important and useful to examine corrosion samples as soon as tests were completed. Additional handling and sample ageing can often lead to damage or distortion. It is also important to examine both the top surface and the cross section of the same sample, using as many available techniques (XRD, SEM/EDX, optical microscope, etc.) as possible to gain a complete picture of the corrosion process;

• Mounting and cross sectioning - most corrosion products are soluble in water and therefore during cutting and subsequent preparation for microscopic examinations, the use of water was avoided wherever possible. Alternatives, including oil-based liquids and/or pressured air were used instead.

When measuring corrosion depth or penetration depth, it is the remaining, unaffected wall thickness (as a function of exposure time) that gives the most accurate kinetic information. This has been well documented in the literature (Figure 41). The total corrosion can be divided into the contribution from the internal corrosion (pitting, grain-boundary attack and internal element depletion zone) that can be measured directly, and the contribution from the scale development that usually cannot be measured directly (because of spalling and volume expansion). To take an accurate account of internal corrosion, suitably etched samples were used, because polishing and grinding can distort true microstructural features and the internal element depletion zone is usually revealed only under etching (Figure 6.1).

Figure 6.1: A schematic drawing for measuring the remaining unaffected wall thickness after corrosion ((left)), (t0-tm)/2, and the internal element depletion zone (right)

A number of etchants were used in the present work for the accurate examination of alloy’s corrosion, post-testing. Table 6.1 lists the etchants recommended for future studies of the corrosion of the candidate alloys.

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Corrosion Mechanism

The combination of general corrosion morphologies from four alloys tested during full scale tests by Vattenfall, extensive SEM/EDX analysis and laboratory tests permitted to propose a corrosion mechanism (Figure 6.2) linking alloy composition with the corrosion environment under the ash deposit. The key feature of this mechanism recognizes that alloys with different alloying contents may now react differently towards reactive ash ingredients, particularly with respect to their tendency to pit.

Figure 6.3: Proposed corrosion mechanism with respect to alloying element concentration

The initial scale growth (composed of mixed oxides) is similar to oxidation (Stage 1). Subsequent

Table 6.1: Recommended etchants for candidate alloys

Etchant Alloy Information

Oxalic Acid Electrolitic Etchant

2ml H2SO4, 48 ml HCl, 50 ml H2O

2g CuCl 2 + 40 ml HCl + 80 ml ethanol

Suitable for Esshete 1250 (4-6 seconds etching time)

Suitable for 347H FG (5-8 seconds)Suitable for X20CrMoV121 (2-3 seconds)

Suitable for HR3C (10-14 seconds)Suitable for Ni-base alloy (Haynes 230)

Suitable for Fe-base high Cr and Ni alloy (Sanicro 28)Severly aggressive- not advised (expect for X20 (1-2 seconds))

Figure 6.2: Three characteristic corrosion morphologies with increasing corrosion damage

Fe-rich Scale

Cr (Ni)-rich Scale

Stage2: Growth Stress Induced Scale Cracking & Initial Ash Deposition

Outer Scale Cracking by Merging Scale Patches

Thin Ash LayerO2, Cl2/HCl SO2/SO3, etc.

Cr(Ni)-rich Corrosion Products

Fe-rich Corrrosion Products

Ash Deposit

High Iron Diffusion

Thick Iron Oxides

Stage3 (Low Cr/Ni Alloys): Pitting via Enhanced Gas Phase Reactions & Scale Growth

Ash and Corrrosion Products

Internal Penetration: Grain Boundary Attack

Stage3 (High Cr/Ni Alloys): Pitting via Molten Salt Fluxing

Ash DepositThinner Iron Oxides

Stage1: Nucleation & Lateral Growth of Oxide PatchesMixed oxides

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thickening of the scale results in iron oxide becoming the outer scale layer and the lateral growth of these oxide patches generates growth stresses which may lead to cracking of the outer scale layer (Stage 2). The difference between the four alloys in their growth up to Stage 2 is probably small and will be mainly with respect to scale thickness. Significant ash is expected to be deposited on the scale after this stage through condensation of the volatile species such as alkalis, which combine with chlorine containing species and/or SO2/SO3 to form chloride and sulphate mixtures. It is possible for a mixture of chlorides and sulphates to be molten below 600oC in the form of a low melting point eutectic (an equi-molar mixture of NaCl, KCl and Na2SO4 melts at 518oC[Kawahara 1996]). Direct impact of ash particles, rich in alkali salts and other compounds such as calcium and alumino-silicates, add to the deposit volume. Alloys with different alloying contents may react differently (Stage 3). For alloys with low chromium (high iron) content (i.e. X20CrMoV121), a more rapid diffusion of iron through the thin chromia scale means that thick iron oxides form the outer scale layer in shorter periods of time. Therefore, growth stresses cause the outer scale to crack relatively earlier in the process, possibly before a significant build-up of the deposit occurs and this is also assisted by micro-porosity within the scale. However, either due to the fact that the scale is much thicker and hence restricting the flow of bulk molten ash, or that the rapid diffusion of iron provides better self-repairing ability, these cracks mainly appear to serve as faster diffusion channels for gaseous reactants (oxygen, chlorine and/or sulphur-related gases) than the rest of the scale. Oxy-chlorination/oxy-sulphidisation works in the "active" oxidation mode at these localised cracks, causing the extensive scale development seen around the pits. For alloys with high chromium (low iron) content (i.e. HR3C), the thin outer scale layer takes longer to reach the same stress level and to crack. Higher amounts of molten, reactive ash ingredients are deposited on the scale and are available when the scale cracks. The cracks can therefore be filled with molten ash ingredients and hence pitting is accompanied by deeper intergranular penetration, and occurs via typical fluxing mechanisms involving molten salts. Another fundamental difference between pitting on the two alloys may be suggested by this mechanism: pitting on HR3C may be self-sustaining although this may be more difficult to achieve on X20CrMoV121. This is because pitting on X20CrMoV121 relies on the transport of gaseous reactants as described earlier, which may be slowed down or even stopped when a thicker, denser deposit layer covers the scale surface. However, the ash deposition supplies molten species and the pockets of occluded molten salt may continue to create the necessary environment for pitting on HR3C. Therefore, pitting on HR3C is potentially more catastrophic than on X20CrMoV121. Scale cracking, and the locations where the deposit is molten are both localised, and thus pitting on X20CrMoV121 and HR3C can only occur at isolated places. The occluded environment created by the pit cover, common for both types of pitting, may assist the corrosion reactions as the oxygen activity within the pit cavity may be lower than the rest of the scale surface, hence diminishing the possibility for protective oxide to form. This mechanism suggests that Esshete1250 and TP347H FG maintain better corrosion resistance by forming a less stressed outer scale layer. This minimises the chance of cracking and thus localised pitting.

Ash Deposition and Corrosion

Ash deposition occurs through a series of physical and chemical processes that begin at the substrate interface and develop into voluminous deposits which seriously hinder boiler operation. In order to understand the mechanisms of fouling, slagging and corrosion, it is helpful to distinguish two stages of ash deposition: 1) the initial stage; 2) the bulk deposition stage. In the first of these two stages (initial ash deposition), chemical interactions between the substrate (an alloy, a ceramic or a refractory surface) and the reactive ash ingredients cause an initial ash layer to form. The composition of this

62

thin ash layer and its evolution has a major influence on fouling tendency and the corrosiveness towards the underlying substrate, while it has relatively less effect on heat transfer efficiency. This stage is followed by bulk ash deposition, where the build-up of a temperature gradient across the deposit is such that its outer layer becomes sticky and substantial amounts of ash particles are captured. As a consequence, the heat transfer efficiency is severely reduced and slags form quickly. The effect of this bulk deposit on the corrosion of the underlying substrates (especially heat transfer tubes) is expected to be less. In collaboration with Vattenfall, ECN and Alstom (UK), investigations on the difference and the link between the two stages of ash deposition have been carried out[Liu et al, 2000d].

The need to identify and understand the initial interaction between ash deposition and alloy substrates arises as illustrated by the three examples in Figures 6.4 to 6.6. Figure 6.4 shows that, for the same ash, the amount of the ash sticking to the three alloys is different; the more corrosion resistant an alloy is, the less the amount of ash that sticks to its surface. Figure 6.5 further shows that for the same alloy, the amount of the ash sticking rises as the concentration of the reactive ingredient (in this case, K2O content) increases. The three IVD ashes give the same trend (Figure 6.6). The results suggest that the initial ash deposition is predominantly chemical in nature, with help from other

mechanisms such as condensation, adsorption and thermophoresis.

Figure 6.5: Scale and deposit morphologies on X20CrMoV121 after reactions with three different synthetic ashes at 600oC for 15 hours: (a) Ash A (K2O 20 wt%); (b) Ash B ( K2O 15 wt%); (c) Ash C ( K2O 7 wt%); balance (wt%): SiO 2 37, Fe2O3 1, Al2O3 3, CaO 5 and Na2O 5

Figure 6.4: Scale and deposit morphologies after reacting with a synthetic ash (wt%: SiO2 37, Fe2O3 1, Al2O3 3, CaO 5, Na2O 5 and K2O 20) at 600oC for 15 hours: (a) X20CrMoV121; (b) Esshete1250; and (c) Sanicro28

63

Figure 6.6: Deposit and scale morphologies on X20CrMoV121 after reactions with the three IVD ashes at 600oC for 5 hours: (a) and (a') OBTEB 17; (b) and (b') OBTEB 18; (c) and (c') OBTEB 19, with both top and cross-sectional views

Detailed analysis on those ash particles sticking, showed that there are predominantly three modes by which ash particles can stick to the scale surface: i) entrapment (some ash particles are seen deeply buried within the scale and some are partially trapped between cracks or crevices formed on the scale); ii) simple attachment (this may be the result of inertial impaction and/or chemical reactions that bond the molten ash particles to the surface, no matter how small the contacting area is); iii) chemical interaction. (this mode is expected for reactive ash ingredients such as volatile alkali salts, often causing the outer scale layer to be porous and mixed with ash ingredients). The first two modes appear to operate mainly for inert ash particles, but may be supplemented by thin layers of reactive ingredients that cannot be seen, for example, by SEM. Reactive ash particles may also be involved in these two modes, but they are probably consumed by the reactions.

Laboratory scale, initial ash deposition experiments were supplemented with industrial scale tests.

A sequential account of the possible interaction between ash deposition and corrosion is given in Figure 6.7, involving the following major steps: -

• Stage 1 - initial formation of a transient layer due to the oxidation, forming a thin, mixed scale layer. No significant effects of the ash ingredients are expected at this stage, although a flue gas with higher concentrations of chlorine and/or SO2/SO3 would significantly increase the rate of transient oxide formation and its porosity;

• Stage 2 - a relatively thick iron oxide layer begins to grow on top of the transient oxidation layer, because of the higher diffusion rate of iron compared to chromium or nickel. This leads to the observed outer and more porous scale layer. Alkali vapours released from the fly ash, or carried by flue gases begin to condense on the scale layer and react with it via oxy-chlorination, oxy-sulphidisation and/or fluxing. The result is a more porous scale layer with a faster growth rate. The porosity may be generated by the release of volatile corrosion products (metal chlorides, for example);

• Stage 3 - as the outer scale layer becomes more porous, it becomes easier for alkali vapour to condense within these often sub-micron-size, gaps or cracks. This applies mainly to the volatile and reactive ash ingredients and is responsible for the first "sticking mode" identified. Large cracks may also form within the thickening scale, possibly as a result of growth-stresses. This

64

will also encourage ash particles to be trapped, thus promoting ash sticking. This applies to reactive and also inert ash ingredients. Alkali vapours, when further condensed on the inert ash particles, may cause them to become more “sticky” by reaction with the scale, particularly iron oxides that could lower viscosity;

• Stage 4 - The growth of the scale will be further enhanced by the presence of alkali salts, whether condensed or entrapped.

This mechanism implies a synergistic effect between corrosion and ash deposition. It explains the trends in corrosion and deposition observed. Corrosion of tube metals by initial contact with alkali vapour and ash ingredients affects further ash deposition. For an entirely inert substrate or inert ash particles, deposition might occur simply by condensation on to a cooler surface or by viscous impact. However, without chemical bonding at the interface between the deposit and the substrate, subsequent fly ash particles might remove the existing deposits by erosive wear. Experimental work

by ECN using a combustion simulator also qualitatively confirm these findings

6.3 Kinetic Data & Modeling (UC/VAB)

Kinetic measurements under laboratory conditions have been carried out using both Vattenfall SCA fly ash (to 3770 hours in 1000-hour increments) and IVD series ashes (to 3000 hours in 1000-hour increments), all at 600°C. Coupons were cut to specified thickness, with an accuracy of ± 1 µm, using an Accutom-5 (Struers) and then buried under ca. 10 mm of the relevant ash for a specified

Metal Substrate

Initial Metal Surface

Simple Oxidation

Corrosion & Ash Deposition

Stage1: Nucleation & Growth of Transient Oxide Patches

Stage3: Scale Thickening via Diffusion

Stage3 & 4: Synergistic Effects at Initial Scale/Deposit Interface

Enhanced Scale Growth and Ash Deposition

Outer Fe-rich Scale

Inner Cr (Ni)-rich Scale

Stage2: Formation of Different Oxide Layers

Stage2: Enhanced and Roughened Scale Retains Ash Particles

Deposition of Volatile Alkali: Vaporisation & Condensation

Solid Particles: Non-viscous Impaction Entrappment Molten Particles: Viscous Impact

Enhanced Condensation & Entrappment

Oxychlorination/Oxysulphidation

Micro/Macro-roughening of Scale Surface

Condensed Volatile Species Rich in KCl

Biomass Combustion

Volatile Alkali Vapour, Cl, S, etc.

Hot Corrosion by Molten Ash

Bulk Ash Deposition by Viscous Impact, etc.

Figure 6.7: Schematic illustrating the synergistic effect between ash deposition and corrosion

Table 6.2: Results of kinetic measurements in SCA fly ash

Scale Thickness (ST in microns) Internal Corrosion (IC in microns) Total Corrosion (TC in microns)

Alloy Cr (wt%) 1000 h 2000 h 3000 h 3770 h 1000 h 2000 h 3000 h 3770 h 1000 h 2000 h 3000 h 3770 hX20CrMoV121 10.3 72 142 177 395 8 8 8 10 80 150 185 405

347H FG 18.5 19 30 64 142 6 15 20 30 25 45 84 172

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time. Due to economic and practical limitations long-term kinetic tests were conducted in an air atmosphere. After testing, the coupons were mounted in resin and examined in cross-section. The remaining unaffected thickness (half of this if both sides were tested) was taken as the total corrosion (TC) depth. This was measured using a high-resolution optical microscope fitted with a XY-stage allowing accurate thickness to be taken to within ± 2 µm. The total corrosion is a combination of both; scale thickness (ST) and internal corrosion (IC). Candidate alloys suffered extensive alloying element depletion beyond visible scale development, pitting or intergranular corrosion. This meant that etching was needed to reveal the true corrosion depth. The results of testing in the SCA (100% biomass) ash for three of the iron-base, candidate alloys studied are shown in Table 6.2.

The data in Table 6.2 has been both linearly and curve-fitted (using polynomial equations), an example of which, for the total corrosion depth, is shown in Figure 6.8.

The linear trend-lines are the least squares fit for a line represented by the equation: -

D = Mt Eq.6.1

Where D is the corrosion depth in microns

t is the time in hours

M is the gradient of the trend-line and is a constant

The values of the gradients (M) for the different alloys were determined.

In addition, the data has been curve-fitted using second or third order polynomial equations of the form: -

D = At3 + Bt2 + Ct Eq.6.2

or

0

100

200

300

400

500

0 500 1000 1500 2000 2500 3000 3500 4000

Time (t in hours)

Tot

al C

orro

sion

(TC

in M

icro

ns)

n X20CrMoV121 (TC = 2E-08t 3 - 0.0001 t 2 + 0.18 t (R 2 = 0.9824))

u Sanicro 28 (TC = 3E-08 t 3 - 0.0001 t 2 + 0.1132 t (R 2 = 0.9666))

s 347H FG ( TC = 7E-09t 3 - 3E-05 t 2 + 0.0488t (R 2 = 0.9985))

0

100

200

300

400

500

0 500 1000 1500 2000 2500 3000 3500 4000Time (t in hours)

Tot

al C

orro

sion

(TC

in M

icro

ns)

n X20CrMoV121 (TC = 0.0873 t (R 2 = 0.8670))

u Sanicro 28 (TC = 0.0639 t (R 2 = 0.6155))

s 347H FG (TC = 0.036 t (R2 = 0.8479))

a b

Figure 6.8: Total alloy corrosion in SCA ash: (a) Data linearly fitted; (b) Data curve-fitted

66

D = Bt2 + Ct Eq.6.3

Where A, B and C are constants.

The values of the constants A, B and C for the different alloys were as well determined.

The values are the kinetic rate constants for alloys, i.e. they are an indication of how an iron-base alloy with a given chromium content will perform in a 100% biomass fuel application. Given the non-linear nature of the corrosion of some of the alloys, it is believed that the polynomial rate constants are more representative. This is confirmed by the R-squared (R2) values; these give an indication of the validity of a given trend-line (R2 has a potential maximum of unity and the closer the value to 1 the closer the fit of the trend-line to the data).

The data in Table 6.2 has also been plotted as a function of the alloy’s chromium content and this is

shown in Figure 6.9.

Figure 6.9 shows that for both X20CrMoV121 (lowest chromium content) and Sanicro28 (highest chromium content), the total corrosion rate is higher than that of TP347H FG (medium chromium content). Furthermore, the contribution of the internal corrosion to the total corrosion depth is different among the three alloys; an increased chromium content leads to enhanced internal corrosion with an associated decrease in scale thickness. This is consistent with the corrosion mechanism

0

100

200

300

400

500

10 15 20 25Cr wt%

Tot

al C

orro

sion

(TC

in M

icro

ns)

a l 3770 hoursn 3000 hourss 2000 hoursu 1000 hours

Cr wt%

0

100

200

300

400

500

10 15 20 25Cr wt%

Scal

e T

hick

ness

(ST

in M

icro

ns)

b

0

100

200

300

400

500

10 15 20 25

Inte

rnal

Cor

rosi

on (I

C in

Mic

rons

)

c

Figure 6.9: Corrosion as a function of chromium content in SCA ash: (a) Total corrosion(TC); (b) Scale thickness (ST); (c) Internal corrosion (IC)

67

described earlier from the Vattenfall corrosion probes.

The kinetic data of all five, iron-base, candidate alloys has been determined in the IVD ash series, and once again linaerly- and curve-fitted, determining the relevant constants.

The identified kinetics can be summarized in a model shown in Figure 6.10. Coal combustion alone will produce the least corrosive situation and the corrosion rate is found to decrease monotonically for alloys with increasing chromium content. The introduction of biomass in the fuel blend for up to 50% significantly aggravates the internal corrosion and its contribution to the overall corrosion becomes larger for alloys with increasing chromium content, hence the benefit of higher chromium content starts to disappear with increasing biomass blend in the fuel. For the 100% biomass fuel investigated in this work, the higher the chromium content in the alloy, the severer the extent of the internal corrosion, leading to a rise in the corrosion rate. These results are comparable to those reported in literature and reported by other partners involved in establishing corrosion kinetics in this project. Some of their data can be found in previous annual project reports.

6.4 Conclusions

The work on the assessment of corrosion potential of biomass deposits formed during pulverized co-combustion has given very positive results.

The work covered the whole spectrum, from the development of a test method for corrosion

10 15 20 25 30Cr in steel (wt%)

Tota

l Cor

rosi

on R

ate

Contribution fromscale growth

Contribution frominternal corrosion

Sani

cro

28

347H

FG

HR

3C

X20

CrM

oV12

1

Ess

hete

125

0

No biomass

Low biomass/coalratio

High biomass/coalratio

Figure 6.10: Schematic model illustrating the relationship between the overall corrosion rate and biomass/coal ratio as well as alloy composition

68

experiments to the establishment of a selection criterion for appropriate materials.

Detailed corrosion mechanisms under biomass ashes have been identified, which have been verified by evaluating field corrosion probes of a range of candidate alloys from Vattenfall (Sweden). Extensive corrosion tests using synthetic ashes also confirm the same systematic trend and corrosion mechanisms.

Two major modes of corrosion damage have been identified: accelerated scale growth; and excessive internal corrosion (pitting and intergranular corrosion). It is possible to achieve an optimal balance between the resistance to scale growth and that to internal corrosion by having adequate and often medium level of chromium content, which offers good resistance to overall corrosion damage, in general.

Good collaborative work with other partners allowed to demonstrate that there is a close relationship between the initial ash deposition and corrosion of the alloy substrates. The initial ash deposition is also closely linked to fouling of boiler components. The bulk ash deposition mainly influences the heat transfer characteristics and slag formation. The ash viscosity and temperature gradient across the deposits are expected to play dominant role at this stage.

A kinetic model is established, based on extensive laboratory tests, and tested in the synergetic collaboration among the partners under pilot-scale conditions. This model will be useful in predicting and preventing biomass-induced fireside corrosion of boiler tubes.

7. DATABASE

The experimental data as well as the results of the analytical work on collected samples from all partners was compiled in a database. The experimental data includes operational parameters relevant for the problems under study and for an appropriate description of the facilities for the sake of the comparison. The work on the samples comprises analytical data from the tested fuels, from the fuel lab ashes, from the fly ashes and deposit samples collected during the slagging and fouling trials as well as the corrosion coupons generated in lab scal facilities and full scale power plants.. For a better mathematical analysis of the results, a worksheet was chosen as the appropriate technical support. The work sheet presents the following structure:

- Table 1: Overview

An overview is given of all trials run within the three years of the project, ordered per facilities. The numeration for the facilities can be found in the last table, Table 4 “List of Facilities”. The main and secondary fuels are listed for each experiment, as well as any tested additives. A mnemonic coding system was used for the fuels as follows:

X-YYY, were

- X: corresponds to the type of fuel (Coal / AA: Alfa-alfa / AC: Annual Crop / B: Bark / CM: Chicken Manure / FM: Fuel Mixture / FR: Forest Residue / O: Oil / P: Peat / Pet: Petcoke / RDF: residue derived fuel / S: Straw / SS: Sew. Sludge / W:

69

Wood / WW: Waste Wood).

- YYY: is the acronym of the partner in the project (IVD / ALSTOM / RWE / TPS / UC / MBEL / VAB / ABO / DTU / ENEL / ECN).

Each trial is provided with an identification number (T-Number), which is used as the base for the sample identification. The designations follow the structure:

Trials

T-Number: XX-0- Label1, were

- XX: is a correlative number for the partner in the project (01:IVD / 02:ALSTOM / 03: RWE / 04:TPS / 05: UC / 06:MBEL / 07: VAB / 08:ABO / 09:DTU / 10:ENEL / 11:ECN)

- 0: is a number corresponding to the scale of the experimental facility

- 1: Full scale

- 2: Pilot scale

- 3: Lab scale

- 4: Others (e.g.: laboratory equipment for viscosity measurements)

- Label1: is the designation given by the partner for internal management

Samples

ID-Number: XX-0-Label1-0Y-Label2, were

- XX-0-Label1: corresponds to the trials in which the sample was produced / collected

- 0Y: identifies the type of sample and any eventual corresponding experimental characteristic needed for the characterization

- 1: Fuel sample (for fuel analysis)

- 2: Corrosion sample

- 3: Deposit sample (C for cooled surface / U for non cooled surface)

- 4: Ash sample (F for fly ashes / B for bottom ashes)

- Label2: is the designation given by the partner for internal management

70

- Table 2: Available Data

The characteristics of the fuel feeding of each experiment are given, including fuel types and blending shares, as well as type and amount for the additives.

Facility parameters relevant for the operational problems studied are included here, including: combustion intensity (CI); different residence times to characterize each of the facilities, for the sake of the comparison; residence times for the sampling; and characteristic temperatures for the facility.

The samples available for each facility are here listed in five different groups:

- Lab ashes: produced directly from the fuels and used for their characterization

- Corrosion samples

- Deposit samples

- Ash samples from slagging and fouling tests

- SOAM results

The diversity in facilities, test techniques and sampling methods introduces a too great uncertainty in the comparison of the obtained data. The results need therefore to be sorted according to similarity criteria, in order to ensure a sustainable comparison. The analysis of the data contained in this table enables a first filter procedure, determining groups of comparable results.

- Table 3.1: Fuel Analysis

The results of the different analytical work carried out on the tested fuels, from the standard analysis summarized in Table 3.1 to the special analysis mentioned in paragraph 3.4, are compiled in this table.

The fuels are ordered from left to right according to the order of the partners given in the contract (IVD / ALSTOM / RWE / TPS / UC / MBEL / VAB / ABO / DTU / ENEL / ECN), used as well for the labeling. The fuels are here labeled according to the structure used in Table 1

Facility Main Secondary Aditive Trials SamplesNumber Fuel Fuel [T-Number] [ID-Number]

01-A Coal-IVD1 - - 01-2-1L100 Program 2Coal-IVD1 S-IVD3 - 01-2-1LBa12,5 Program 1Coal-IVD1 S-IVD3 - 01-2-1LBa25 Program 1Coal-IVD1 S-IVD3 - 01-2-1LBa50 Program 1Coal-IVD1 W-IVD1 - 01-2-1LCa25 Program 1Coal-IVD1 W-IVD1 - 01-2-1LCa50 Program 1

- W-IVD1 - 01-2-1LCa100 Program 2

Fig. 7.1: Example of Table 1 of the Database

71

and the other tables of the database.

Although a big effort was made at the beginning of the project to standardize the analysis of fuels, several differences can be observed during the analysis of the compiled data. One main encountered problem represents the heterogeneous format of the results from different analytical devices. Like that, the inorganic chemistry for example can be commonly found in two different formats, viz. as “% in ash” or as “mg/kg raw”. The results are certainly comparable, but they need to be transformed into an homogeneous format to enable the comparison.

- Table 3.2: Samples

Finally the complete information on the collected samples is compiled in this table.

A first block on the left hand side of the table includes all experimental parameters which have an influence on the operational problems under study. Here information is compiled regarding the experimental environment in which the sample was produced (e.g. local temperature, residence time, radiation or convective zone, distance to burner, etc.) as well as of the complete facility and from the feeding.

A second block of data includes the results of the analytical work on the samples. Starting with information on the main components (C / H / N) and S and Cl, a main effort was concentrated on the ash forming minerals. The results from other studies are also included, such as LOI and burnout, sintering and melting ranges, the degree of fusion, the deposition rate and ash fusion behavior. The information on corrosive attack is attached at the end, as well as particular analytical work carried out by single partners.

- Table 4: List of Facilities

All facilities used during the project are listed here per partner, including information concerning the type, the scale and any relevant main characteristics or comments.

The facilities are here numbered, according to the system 00-X (00 for the partner’s number and X a correlative letter), for an easier classification in the former tables.

In spite of the long work in common with all partners in the aim of obtaining a suitable structure for the database, the analysis of the data later to its compilation has highlighted several possible improvements. These go from the mere structure of the database for a better compilation and easier comparison (e.g. a more homogeneous format for the presentation of specific detailed results), to even more detailed specifications at the beginning of the project.

The database contributed as well to the evaluation of single partner results by giving n overview of totally available data and experiments.

8. CONCLUSIONS

Within the present project extensive analytical and experimental work has been carried out for a basic and fundamental understanding on processes during the combustion of pulverised fuel mixtures

72

of coal and bio-fuels leading to increased operational problems such as fouling, slagging and corrosion. Three work groups were formed focussing on "Chemistry and Analysis", "Fouling and Slagging Experimental Tests", and "Corrosion Measurements".

The work consisted of detailed analytical characterisation of a broad variety of used pure fuels by either available standard laboratory analysis methods or newly or further developed advanced fuel characterisation procedures. The results from these investigations formed the basis of a better understanding of ongoing mineral matter transformation as well as fly ash and fine particle formation processes during pulverised fuel co-combustion which was investigated extensively in a large number of different test facilities from lab- to full-scale. By knowing the content and chemical bonding of the major ash forming elements in the different types of fuel mechanisms for initial deposit formation and deposit growth could be developed and determined. Further on, the detailed knowledge for predicting the combustion and ash forming processes facilitated the development of primary measures, such as fuel mixing, additive addition, etc. for lower risks of operational problems. The experimental combustion and deposit forming investigations enabled the partners defining several suitable and cost effective laboratory scale test methods for the characterisation of different fuel mixtures on their behaviour during the combustion course referring to fouling and slagging. The experimental work on full-scale power plants resulted in valuable information and procedures for sampling either deposits or material samples for corrosion investigations.

The work focussing on corrosion effects started from detailed and extensive experimental investigations in two different laboratory test facilities using synthetic gas mixtures and fly ash compositions. By combining the thereby obtained data with results from the experimental investigations on deposit formation a clear interaction between initial deposition formation and corrosion processes could be demonstrated. This work was supported by corrosion investigations using real fly ashes from combustion tests of different partners in the project. The available corrosion data were summarised and evaluated for the establishment of a kinetic model facilitating a performance prediction of a candidate material on given co-combustion conditions.

The lack of overall applicable and general guidelines and tools, mainly for the prediction of fouling and slagging, is on the one hand due to the fact that the originally proposed establishment of an overall comprehensive model on fouling and slagging phenomena was cut-off the project. A suitable model correlating combustion, ash formation and geometric boundary conditions would supported a better understanding of the complex and inter-linked phenomena occurring in combustion systems and therefore would be able to act as an ideal tool for the prediction of fouling and slagging and thereby for the development of predictive guidelines and tools. On the other hand, during the course of the project it became obvious that a lack of quantifiable, objectively measurable criteria and parameters describing and characterising ash deposits on heat exchanger tubes from an operational point of view are not yet available.

Summarizing the total effort and work accomplished during the project it could be said that considerable progress have been achieved in a more basic and fundamental understanding of process during the co-combustion of coal and renewable solid fuels leading to operational such as fouling, slagging and corrosion. Especially outstanding results could be obtained for the understanding of corrosion phenomena as well as for the performance prediction of different candidate materials for heat exchanger tubes under co-combustion conditions. But also for the indication of possible counter measures and procedures against fouling and slagging effects during the utilisation of biomass fuels in coal fired boilers fundamental and very important results could be deduced from an extensive database formed by the available experimental data.

73

Acknowledgements

The R&D programm reported was supported in part by the Europeans Commission, Directorate General XII, under the Joule III Program. The authors would like to thank the European Commission for the funding.

Research funded in part by THE EUROPEAN COMMISSION in the framework of the NON NUCLEAR PROGRAM – JOULE III

74

ANNEX 4: CHEMICAL FRACTIONATION

100 g dry sample(<74 µm or < 200 mesh)

3 ml/g H 2O

3 ml/g NH 4Ac(1M)

3 ml/g HCl(1M)

20 g dry sample

1/3 of wet sample(>=20 g)

1/2 of wet sample(>=20 g)

remaining wetsample (>=20 g)

water leaching 10 hr(stirred, room temp.)

filtering +rinsing (distilled)

weighing totalwet sample

NH4Ac leach. 10 hr(stirred, room temp.)

filtering +rinsing (distilled)

weighing totalwet sample

3 timesin total

HCl leaching 10 hr(stirred, 70 °C)

filtering +rinsing (distilled)

weighing totalwet sample

2 timesin total

ICP-AES

proximate-ash

moisture(immediate)

Chemical fractionation procedureaccording to L.L. Baxter

ICP-AES

proximate-ash

moisture(immediate)

ICP-AES

proximate-ash

moisture(immediate)

ICP-AES

proximate-ash

moisture(immediate)

expressed in mg/kg Me xOy(Si, Al, Fe, Ti, Ca, Mg, Na, K, S, P,

and residual)

"residual" = ash - Σ (Me xOy)

optionalICP-AES

optionalICP-AES

optionalICP-AES

Figure A1: Procedure for Chemical Fractionation of a Fuel.

75