New technology for monitoring fouling deposition in coal ......of tangential ring boiler in the Orot Rabin power plant (Hadera) and the second is a 550 MW unit of opposite red boiler

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VGB PowerTech 6 l 2016 Monitoring fouling in coal fired boilers

Authors

Kurzfassung

Eine neue Technologie zur Überwachung von Ablagerungen in mit Kohle gefeuerten KesselnEine neue Technologie wird vorgestellt, mit der Echtzeitdaten zu Schichtdicke und Reflektivität der Verschmutzungen auf der Wandberohrung von mit Kohle befeuerten Kesseln ermittelt wer-den können. Die Daten werden durch Direkt-messungen an unterschiedlichen Positionen des Kessels ermittelt und ermöglichen die Überwa-chung der lokalen Wärmeübertragung entlang der Kesselwand sowie die Auswirkungen auf die Feuerraumendtemperatur (FEGT) und den Sauberkeitsfaktor (CF) der Anlage. Mithilfe dieser Daten lassen sich die für die Reinigung des Kessels optimalen Verfahren ermitteln. Messbeispiele zeigen, dass die Verschmutzungs-dynamik innerhalb des Kessels signifikante Ab-weichungen aufweist. Es hat sich außerdem gezeigt, dass sich beim Betrieb zwei unterschiedliche Ablagerungs-mechanismen ausbilden: Ein Mechanismus mit geringer Schichtdicke und kontinuierlichem Wachstum und ein weiterer Mechanismus, bei dem große Konglomerate unverbrannten Mate-rials beim Auftreffen auf die Kesselwände an-setzen und dann nach relativ kurzer Zeit durch turbulente Gasströme im Innern des Ofens wieder entfernt werden. Für unterschiedliche Kohletypen wurde ein Vergleich der Verschmut-zungsdynamik durchgeführt. Dabei hat sich gezeigt, dass die Auswirkungen der Verschmut-zungsreflektivität auf die Feuerraumendtempe-ratur (FEGT) und den Sauberkeitsfaktor (CF) den entsprechenden Auswirkungen der Ver-schmutzungsdicke entsprechen bzw. dass die Verschmutzungsreflektivität sich unter Um-ständen sogar stärker als die Verschmutzungs-dicke entwickelt. l

New technology for monitoring fouling deposition in coal fired boilersNaftaly Menn and Boris Chudnovsky

Naftaly Menn, PhDAMS – Advanced Measurement Systems LtdHaifa, IsraelBoris Chudnovsky, PhDIEC-Israel Electric CompanyHaifa, Israel

IntroductionThe paper addresses the age-old problem of improving power plant and boiler effi-ciency and specifically in facilities where solid fuel, such as coal and biomass, is burnt and combustion energy is trans-ferred into electric power generated by the steam turbine.

Increased efficiency can still be achieved using new technologies allowing for a deeper understanding of the complex, dy-namic processes taking place in the com-bustion chamber (the furnace) and other major parts of the facility.

As is well known, there are different meth-ods for coal firing: pulverised combustion, fluidised bed combustion, moving bed etc. For pulverised combustion, the particles of coal are mixed with air. The pulverised coal-air mixture is fired by the furnace burners (located at several furnace levels). The fuel particles are ignited and create the flame consisting of very hot solid particles and combustion gases. The temperature in the flame achieves 1,700 °C to 1,800 °C. At such high temperatures the transfer of heat energy from the flame to the furnace wall (comprising the water tubes where water is converted into steam) is mainly due to radiation heat transfer (up to 90 %). In such conditions radiation properties of the furnace wall (spectral reflectivity R and spectral emissivity ε) play a significant role in the overall heat balance of the facility.

Furthermore, the fuel characteristics of coal and especially biomass are very differ-ent, including moisture content, ash con-tent, calorific value, and alkali/alkaline earth metal content. Ash-forming elements are present in biomass and coal as salts, bound in the carbon structure or as mineral particles introduced randomly even dur-ing transportation. Concentration of major ash forming elements (Si, Ca, Mg, K, Na, P) have an influence on ash melting behavior and corrosion/erosion mechanisms.

During combustion, a fraction of the ash-forming compounds in the fuel is volatil-ised and released into the gas phase. An-other fraction creates the solid particles which cannot be completely burnt. These unburnt residuals, primarily consisting of oxides of the aforementioned metals and other elements presented in different pro-portions in different kinds of coal and bio-mass, appear in the combustion chamber

as separate ash particles and sometimes also create the aggregates of slag. Com-plex fluid dynamics existing in the furnace is responsible for multi-phase flow with 3D velocity distribution which moves ash particles towards the walls where they are deposited on the water tubes. The deposi-tion layer (fouling) created in such a way is usually characterised by very low thermal conductivity and causes significant ther-mal resistance, which reduces heat transfer from the flame and hot gases to the water and steam. The larger the thickness (T) of the deposition layer the greater amount of heat energy originated in the combustion is going not to the heated water, but to the furnace exit and increases the Flue Gas Exit Temperature (FEGT). Therefore, increases of T and R reduce the overall heat absorp-tion of the combustion chamber and as a result reduces boiler and unit efficiency.To improve the heat transfer inside the fur-nace the fouling deposits obviously should be removed. This is usually carried out by activating numerous soot blowers distrib-uted all along the furnace walls and oper-ated in some predefined manner in order to clean the heat transfer surfaces. However, activation of the cleaning blowers causes additional energy wastage and, what is more critical, results in growing erosion of the water tubes. Therefore the cleaning should be optimised taking into considera-tion different factors which influence the heat transfer, fouling dynamics and main-tenance issues.

Several approaches addressing the clean-ing procedure have been suggested over the years.

In advanced boiler systems the activation of soot blowers is based on the Cleanliness Factor (CF) defined as the ratio of overall heat transfer coefficient at actual opera-tion condition to its value at clean condi-tion. However, usage of CF is still problem-atic because real heat transfer depends on many factors, such as the utility load, tilt position of the burners, spatial distribu-tion of different fraction of solid particles inside the furnace, situation in convection pass and other conditions varying in the course of normal operation of the utility. Most of them can hardly be measured or even quantified. In addition, CF is defined as an integral parameter which depends on local heat transfer in different zones of the furnace water tube walls: it may happen that in some places the fouling deposits


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Monitoring fouling in coal fired boilers VGB PowerTech 6 l 2016

achieves the critical thickness while in oth-ers deposition is still very low. Moreover, reflectivity of the fouling surface varies in a completely different way to deposi-tion growth and sometimes in a manner opposite to the impact of the thickness of fouling. In other words, implementation of CF as a target parameter for cleaning opti-misation requires measurement of fouling data collected in real time and from differ-ent areas of the furnace.

Method and technology An approach presented here is based on non-contact direct measurement of Foul-ing Thickness and Reflectivity (FTR) in real time. For this purpose a special electro-op-tical device attached to the furnace wall is used which enables the simultaneous and continuous measurement of the T and R of the fouling (see detailed description in [1 to 3]). This device is located in the vi-cinity of a soot blower and therefore col-lects information from the adjacent zone. It comprises the extended part (moving head) which moves in and out of the fur-nace – while inside the furnace the system measures the fouling thickness and reflec-tivity and, as it leaves the furnace, the sys-tem collects data on reflection from a refer-

ence surface located inside the device. The

light beam originating in the light source

(a laser diode) is focused on the fouling

surface growing on the water tube. The

image of the light spot is transferred by the

system optics to the video sensor interfaced

with the system processor. Movement of the image spot is translated into meas-

ured thickness T. The measurement is fast

(about one second) so there is no need for

intensive cooling, in spite of the fact that

the extended part is introduced to a very

hot zone of the furnace.

Comparing intensity of light reflected from the fouling surface with intensity of

light reflected from the standard specimen makes it possible to calculate spectral re-

flectivity of the fouling in the wavelength of the laser. Special measures undertaken

in order to get high contrast of the spot im-

age with regard to the background of the

high intensity radiation originated in the

furnace flame.

Reflectivity measurement is performed in each cycle of thickness measurement, so

both values, T and R, characterise the dy-

namic of fouling (and, finally, of local heat transfer) in the vicinity of the FTR device.

Several FTR devices installed on the fur-

nace wall are connected in one complete

system interfaced to the system local serv-

er. From the server results of measurement

and calculation of T and R from all zones equipped by FTR devices are transferred to the PI (data acquisition system) of the sta-

tion. A special software package provides

real time processing of all data in PI fol-lowed by recommending how the cleaning

procedure should be carried out.

Experimental resultsFTR systems have been successfully operat-

ed over the last 2.5 years on two Israel Elec-

tric Company plants – one is a 575 MW unit of tangential firing boiler in the Orot Rabin power plant (Hadera) and the second is

a 550 MW unit of opposite fired boiler in the Rutenberg power plant (Ashkelon). A great volume of data was collected during

this period at both stations. Analysing the

results measured makes it possible to find new features of the process of fouling and

to gain a better understanding of relations

between the dynamics of fouling, parame-

ters of heat transfer and characteristics and

sequence of cleaning. Some typical results

are presented below.

F i g u r e 1 and F i g u r e 2 demonstrate two different types of fouling existing in

Reflectivity (hemispherical)(Vertical lines designate soot-blowing process)

Time in hours

Refle

ctivi

ty

230 235 240 245 250 255 260 265 270 275 280

0.6

0.5

0.4

0.3

0.2

0.1

0

South Africa coal Russian coal

Low load

Fig. 3. Fouling rflectivity variation versus time.

Fouling thickness in mm(Vertical lines designate soot-blowing process)

Time in hours

Thik

ness

in m

m

21.81.61.4

10.80.60.40.2

0204 205 206 207 208 209 210 211 212

Fig. 1. Measurement of fouling thickness versus time. Type I of fouling deposition.

Fouling thickness in mm(Vertical lines designate soot-blowing process)

Time in hours

Thik

ness

in m

m

290 291 292 293 294 295 296 297 298 299 300

6

5

4

3

2

1

0

Fig. 2. Measurement of fouling thickness versus time. Type II of fouling deposition.


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such big lumps of material of course reduce the radiation heat transfer from the flame to the wall, but may be even more essential that when they are “sitting” on the tubes these lumps significantly increase the ther-mal resistance of the fouling layer.

FTR01 Device data FTR05 Device data




Sootblowing SQ. 5

Sootblowing SQ. 6

Sootblowing SQ. 5

Sootblowing SQ. 6

Sootblowing SQ. 3

Fig. 5. PI data for thickness and reflectivity of FTR system with 8 devices.

the furnace. Each point on those figures represents one cycle of measurement of thickness of contamination on the water wall tubes and vertical lines indicate the soot blowing activation. The first type of fouling (Figure 1) is characterised by slow, almost monotonic change of fouling

thickness. The situation shown in Figure 2 is completely different: it is seen that big lumps of material are approaching the wa-ter wall, attaching to the tubes for some pe-riod of time after which they are removed by the main flow of the air and combustion products away from the wall. The cloud of

Water wall tube contamination thickness trendLevel 9, SA Anglo MAF coal

Water wall tube contamination thickness trendLevel 9, SA Billiton coal

Time

Thick

ness

in m

m

Time

a)

b)

Thick

ness

in m

m

6.0

5.0

4.0

3.0

2.0

1.0

0.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0

280 281 282 283 284 285 286 287 288 289 290

30 32 34 36 38 40 42 44 46

Fig. 4. Contamination thickness variation for Anglo MAF and Billiton coal.

Water wall tube contamination thickness trendLevel 9, SA Anglo MAF coal

Water wall tube contamination thickness trendLevel 9, SA Billiton coal

Time

Thick

ness

in m

m

Time

a)

b)

Thick

ness

in m

m

6.0

5.0

4.0

3.0

2.0

1.0

0.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0

280 281 282 283 284 285 286 287 288 289 290

30 32 34 36 38 40 42 44 46


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F i g u r e 3 shows reflectivity measure-

ment. It is clearly seen that reflectivity depends not only on the type of coal, but

also on the loading of the boiler, which

can be explained by different dynamics of

combustion at different loads (caused by

changing of the burner blades’ tilt, for in-

stance). Cleaning activation in most cases results in an immediate decrease of reflec-

tivity, but then, after a short period of time,

it goes back to the higher values.

The measurements presented on the F i g -

u r e s 4 a , b have been performed during

standard operation of the 550 MW unit with two types of coal, Anglo MAF and Billiton. The unit was fully loaded and the furnace exit temperature was high (about 1,450 °C in both cases). Therefore some actions were definitely needed. But what actions? FTR data allows one to ascertain the reason for high FEGT in both cases and indicate what action should be taken. Figure 4 demonstrates the thickness of contamination and moments of cleaning (activation of soot blowers, red lines on the graphs). We see that the DYNAMICS of fouling is completely different in these two

cases. Indeed, in the case of Anglo MAF (Figure 4a) deposition achieves significant thickness, then it is removed by cleaning, but it grows again very fast before subse-quent cleaning. In the case of Billiton (Fig-ure 4b) contamination rate is much lower, but it is not removed by cleaning. Reflectiv-ity of both coals was also different - reflec-tivity of Billiton is almost two times higher than that of Anglo MAF. Therefore, in the case of Anglo MAF, more frequent cleaning is desirable whereas in the case of Billiton it is reflectivity which is responsible for high FEGT and changing the cleaning procedure

Time

Thick

ness

in m

m

Time

Time

Thick

ness

in m

mTh

ickne

ss in

mm

SootblowSQ. 3

11:55-12:05

SootblowSQ. 5

12:18-12:35

SootblowSQ. 6

12:50-13:15

Indirect effect on FTR07

Indirect effect on FTR08

FTR01 - THCKNS

FTR02 - THCKNS

FTR03 - THCKNS

FTR04 - THCKNS

FTR05 - THCKNS

FTR06 - THCKNS

FTR07 - THCKNS

FTR08 - THCKNS

FTR01 - THCKNS

FTR02 - THCKNS

FTR03 - THCKNS

FTR04 - THCKNS

FTR05 - THCKNS

FTR06 - THCKNS

FTR07 - THCKNS

FTR08 - THCKNS

FTR01 - RFLKT

FTR02 - RFLKT

FTR03 - RFLKT

FTR04 - RFLKT

FTR05 - RFLKT

FTR06 - RFLKT

FTR07 - RFLKT

FTR08 - RFLKT

0

1

2

3

4

5

6

7

8

9

10.90.80.70.60.50.40.30.20.1

0

10.90.80.70.60.50.40.30.20.1

0

04-03-16 11:31 04-03-16 12:00 04-03-16 12:28 04-03-16 12:57 04-03-16 13:26

04-03-16 11:31 04-03-16 12:00 04-03-16 12:28 04-03-16 12:57 04-03-16 13:26

04-03-16 11:31 04-03-16 12:00 04-03-16 12:28 04-03-16 12:57 04-03-16 13:26

Fig. 6. Three sequences of cleaning versus T and R data of FTR devices.


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cannot improve the situation significantly (in this case only using the mix or different coals might be useful).

The next three figures represent results from the 550 MW unit with opposite fired burners where 8 FTR devices are installed. All devices are connected in a single net-work interfaced to the PI of the station. A pair of devices is located on floor 7 at the top burners level, an additional two devices are on the floor 8 (at SOFA level) and another 4 devices are positioned on floors 9 and 10, two devices on each floor. The measurements have been performed and processed every four minutes at each device. F i g u r e 5 shows the results re-corded by PI during about three hours of continuous operation. As it can be seen, there is a significant difference between the dynamics of fouling in different zones of the furnace: namely, FTR 1 and 2 (from the tenth floor) recorded the first type of fouling with a low rate of contamination growth. In all other locations, and espe-cially on the seventh floor the second type of fouling definitely exists. The lumps of material achieving about 10mm size and which are sometimes attached to the tube

for a relatively long period of time cannot be successfully removed by the overall flow existing in the furnace. It was decided to activate cleaning of three sequences of the soot blowers – in the vicinity of FTR devices number three, five and six where contamination was most significant. Three sequences of cleaning were performed and the results were clearly seen on the PI re-cord. Immediately after activation of the soot blowers the thickness was reduced to a very low level. Reflectivity in loca-tions of FTR three and five also decreased significantly whereas in location FTR six it returned to a higher value after several minutes.

DiscussionIn order to check whether the fouling cleaning chosen according to FTR data is relevant and correlates with dynamics of the main parameters of the boiler perfor-mance, the following values have been es-timated on unit 4 of the Rutenberg power plant: CF factor, boiler efficiency and FEGT. All values were calculated and recorded in the same period of time when three se-quences of cleaning mentioned above were

performed. Results are depicted in F i g -u r e 6 and F i g u r e 7. The first of these two figures demonstrates changing of FTR measured parameters as a result of clean-ing. Just after the cleaning, the fouling thickness decreased in all three locations of the activated soot blowers. In addition to cleaning operated in locations five and six also caused a reduction of fouling thick-ness at locations seven and eight because these zones are close to the activated soot blowers (indicated in Figure 6 as an indi-rect effect of FTR).

As it is clearly demonstrated in Figure 7 each soot blowing sequence is accompa-nied by a corresponding increase in CF val-ues, increased boiler efficiency and reduc-tion of FEGT.

Due to actual dynamics of heat transfer in the boiler, there exists a delay in variation of efficiency, CF and FEGT compared to the cleaning action.

It should be noted that all results presented in Figures 5 to 7 have been obtained at the unit partial load. As it can be seen, efficien-cy measured as a result of these sequences of soot blowing improved by 0.2 %.

Time

Load

in M

W

Time

FEGT

in °C

SootblowSQ. 3

11:55-12:05

SootblowSQ. 5

12:18-12:35

SootblowSQ. 6

12:50-13:15

Boiler load (MW) Boiler Eff (%)

FEGT (C) Furnace cleanliness factor

450435420405390375360345330

1,350

1,300

1,250

1,200

1,150

1,10004-03-16 11:31 04-03-16 12:00 04-03-16 12:28 04-03-16 12:57 04-03-16 13:26

04-03-16 11:31 04-03-16 12:00 04-03-16 12:28 04-03-16 12:57 04-03-16 13:26

Effic

ienc

y in

%Fu

rnac

e cle

anlin

ess f

acto

r

93.80093.72593.65093.57593.50093.42593.35093.27593.200

10.90.80.70.60.50.40.30.20.10

Fig. 7. Variation of efficiency, cleanliness factor, FEGT and boiler load versus time, with indication of three cleaning sequences.


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It is interesting to indicate that the correct choice of cleaning location, based on direct measurement of FTR devices, provides for a marketable change of heat transfer ex-pressed in efficiency, FEGT and CF, in spite of the fact that in each cleaning sequence of our experiments, only a small amount of blowers (three-four per sequence) have been activated, while all other blowers of the furnace were in the OFF position. This fact demonstrates once again the benefits of the FTR approach compared to other procedures of cleaning optimisation based on measurements of integral boiler opera-tion parameters – such as the amount of su-perheater spray flow, the position of burner tilts, boiler exit temperatures etc. (see, for example [4, 5]).

Summary – Usage of the FTR approach results in re-

liable information on dynamics of heat transfer in an operating furnace of a coal-fired boiler. Information is collected in real time and addresses the directly measured thickness and reflectivity of fouling deposited on the water wall.

– It was revealed that parameters of foul-ing in different zones of the furnace can differ significantly one from to the other. Two major types of fouling deposition, one with low rate of thickness growth and the second with big lumps of mate-rial attaching to the wall for a relatively short period of time, were experienced at the same time inside the furnace.

– It was demonstrated that the situation might occur when reflectivity variation and not the thickness play the major role in heat balance of the furnace. In such a case the cleaning cannot be effective at all. It depends on the type of fuel (type of coal) and chosen procedure of clean-ing activation.

– It was shown that data collected by the FTR system and interfaced to PI data acquisition system of the plant can be successfully exploited in order to define location and time of cleaning activation

– If cleaning procedure is based on direct measurement data collected by the FTR system, it is possible to improve overall efficiency by up to 0.2 %, even at unit partial load.

References[1] N.Menn, B.Chudnovsky: Measurement of

thickness and reflectivity of fouling deposits on the wall tubes in a pulverised-coal furnace. Proceedings of ASME Conference Power, Aug1, 2013, Boston, MA, USA.

[2] B. Chudnovsky, N.Menn: Long term experi-ence of the real time fouling deposits thick-ness measurements for on-line soot blowing optimisation. Proceedings of the ASME 2015 Power Conference, June 28 – July 2, 2015, San Diego Convention Center, Cali-fornia, USA.

[3] N Menn, B. Chudnovsky: Boiler performance optimisation for pulverised coal and biomass co-firing due to utilising novel method of real time of fouling deposits thickness and its re-flectivity measurements. Proceeding of COAL GEN 2015 conference, August 2015, Nash-ville, USA.

[4] S.J. Plboontum, S.M. Smith and R.S. Con-rad: Boiler Performance Improvement Due to Intelligent Soot blowing Utilising Real-Time Boiler Modelling on UP Boilers. Proceeding of Electric Power, April 5-7, 2005, Chicago, IL, USA.

[5] C. Clark, C. Breeding, S. Shah: Intelligent Soot Blowing Installation Experience at Hom-er City. Clyde Bergemann Inc. White Paper, March 3, 2007. l

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Jahres-CD 2014

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Fachzeitschrift: 1990 bis 2014

Diese DVD und ihre Inhalte sind urheberrechtlich geschützt.© VGB PowerTech Service GmbH

Essen | Deutschland | 2015

· 1990 bis 2014 · · 1990 bis 2014 ·

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VGB PowerTech DVD 1990 bis 2014: 25 Jahrgänge geballtes Wissen rund um die Strom- und Wärmeerzeugung Mehr als 25.000 Seiten Daten, Fakten und Kompetenz

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