Criteria selection for the assessment of Serbian lignites tendency to form deposits on power boilers heat transfer surfaces

Mladenović, Milica; Mladenovic, Rastko; Manović, Vasilije; Radovanović, Milan; Stojiljković, Dragoslava

doi:10.2298/tsci0904061m

Cited by 9 publications

(6 citation statements)

References 1 publication

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“…Based on measured gamma-ray spectrum of 82 Due to low concentration of natural radio nuclides in lignite samples (approximately 3 times lower compared to values for subbituminous and bituminous coals) and obtained low correlation coefficient, integral or specific natural gamma radiation method could not be used for on-line measurement of ash content in Kolubara lignite. [12,13]. Based on results of these research and experimental verification of transmission radiation method/activity concentrations of naturally occurring radionuclides in the representative lignite samples from Kolubara basin, it could be concluded that the best method for on-line detection of lignite quality is based on Prompt gamma neutron activation method combined with transmission radiation method for detection of coal bed high at the transport belt and microwave method for moisture detection.…”

Section: Physical-chemical Properties Of Coalmentioning

confidence: 92%

Review of the investigations of pulverized coal combustion processes in large power plants in laboratory for thermal engineering and energy: Part B

et al. 2019

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Paper presents short review of research problems, applied methods for solving problems and main results obtained by the researchers in Laboratory for Thermal Engineering and Energy (LTE) of the "Vinča" Institute of Nuclear Sciences, Belgrade, Serbia dealing with pulverized coal combustion processes and technologies for reduction of pollutions problems at thermal power plants in a period since 2000. The presented results were published in numerous studies realized for different users, Ph. D., Masters, and Specialist thesis, in international and domestic scientific journals and monographs, presented at numerous international and domestic scientific conferences, etc. Presented research projects and results of applied research projects realized at pulverized coal combustion thermal power plants clearly show that LTE team was involved in key activities of rehabilitation and modernization, including implementation of best available technologies for pollution reduction at thermal power plants, in the region of South East Europe.

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Section: Physical-chemical Properties Of Coalmentioning

confidence: 92%

Review of the investigations of pulverized coal combustion processes in large power plants in laboratory for thermal engineering and energy: Part B

et al. 2019

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“…Na osnovu obimne baze podataka sakupljene za domaće ugljeve i korelativne analize postojećih polu-empirijskih kriterijuma razvijeni su pokazatelji (indikatori) tendencije pepela goriva za stvaranje naslaga na grejnim površinama. Ključne empirijske korelacije razvijene kod nas su (Repić, 1979, Mladenović, 2005, Mladenović et al 2009): a) Interval između početne deformacije (t1) i temperature topljenja pepela (t4). Ako je interval mali, tanak, tečni sloj šljake biće formiran na zidovima ložišta i njega je izuzetno teško kontrolisati pomoću duvača čađi.…”

Section: Rezultati I Diskusijaunclassified

“…Ovi indikatori (Tabela 1) mogu se definisati kao (Repić, 1979, Pronobis, 2005 Indeks aglomeracije fluidizovanog sloja: BAI = Fe2O3)/(Na2O + K2O). Korelaciona analiza testiranih domaćih goriva dala je tačnu funkcionalnu zavisnost kriterijuma B, B/A, It i So (Repić, 1979, Mladenović et al 2009). Granice za primenu ovih kriterijuma su u skladu sa time i stoga se bilo koji od ovih četiri kriterijuma može koristiti za procenu tendencije lepljenja pepela domaćih lignita (Tabela 1).…”

Section: Rezultati I Diskusijaunclassified

Analysis criteria for the assessment of deposits formation on boilers heat surfaces during biomass combustion

Mladenović¹,

Repić²,

Paprika³

et al. 2018

Savr poljopriv tehnika

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Sagorevanje goriva u kotlovskim ložištima dovodi do stvaranja naslaga na ozračenim i konvektivnim kotlovskim grejnim površinama. Ovo nije nov problem, ali je postao jedan od glavnih operativnih problema u kotlovima koji koriste ugljeve lošeg kvaliteta i neke vrste biomasa, posebno poljoprivredne. U radu su prikazani rezultati analize kriterijuma za procenu formiranja naslaga na kotlovskim grejnim površinama u slučaju sagorevanja biomase. Takođe, razmatrani su problemi uzrokovani pepelom tokom sagorevanja biomase u kotlovskom ložištu. Testirane su ključne empirijske korelacije za lepljenje i zaprljanje u slučaju sagorevanja uglja ili biomase dobijene na osnovu ispitivanja različitih vrsta goriva u laboratorijskim i realnim ložišnim uslovima. Analiza je pokazala da mnoge vrste agro biomase kao i Kosovski lignit imaju veliku sklonost ka lepljenju i zaprljanju što potvrđuju indikatori bazirani na hemijskom sastavu pepela goriva i temperaturama topivosti pepela.

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“…It has been estimated to be an important source of losses of availability and energy efficiency in thermal power plants, that may amount to 1% under normal operating conditions [1]. A large number of case studies can be found in recent decades [3][4][5], indicating a continuous worldwide interest in this problem. The collected data showed 7% of units suffering from frequent fouling and 40% reporting occasional problems, out of a total of 91 pulverized-coal utility boilers in the USA.…”

Section: Introductionmentioning

confidence: 99%

Ash fouling monitoring and key variables analysis for coal fired power plant boiler

Shi

Wang

2015

THERM SCI

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Ash deposition on heat transfer surfaces is still a significant problem in coalfired power plant utility boilers. The effective ways to deal with this problem are accurate on-line monitoring of ash fouling and soot-blowing. In this paper, an online ash fouling monitoring model based on dynamic mass and energy balance method is developed and key variables analysis technique is introduced to study the internal behavior of soot-blowing system. In this process, artificial neural networks are used to optimize the boiler soot-blowing model and mean impact values method is utilized to determine a set of key variables. The validity of the models has been illustrated in a real case-study boiler, a 300 MW Chinese power station. The results on same real plant data show that both models have good prediction accuracy, while the artificial neural networks model II has less input parameters. This work will be the basis of a future development in order to control and optimize the soot-blowing of the coal-fired power plant utility boilers.tion. Therefore, optimization for soot blowing system according to the actual cleaning need becomes more and more important. At first, an appropriate assessment for the ash fouling level of each heat transfer surface of the boiler is needed. Monitoring techniques become more and more important for the study of boiler behaviors and ash fouling influence in coal-fired power plant boilers and have attracted extensive research effort recently [6][7][8].Ash fouling monitoring can be accomplished by means of on-line calculations and special power plant instrumentation or a combination of both techniques. On-line calculations always need to calculate the heat absorption of heat transfer surfaces. The conventional method of calculating the heat absorption rate is the log-mean-temperature-difference approach [6]. However, it is a static balance method which cannot show the dynamic behaviors of heat transfer surfaces. While special power plant instrumentation (i. e. heat fluxes meters [7]) can well reflect the status of heat absorption of heat transfer surfaces by providing a continuous signal, they induce significant increase of cost on sensors, installation, and maintenance. There are some commercial (ash fouling) boiler monitoring tools [8], but the internal behaviors of these applications are unclear.Key variables analysis is a tool that is often used to study the behavior of a system, or a model, and to attain the dependency of outputs on each or some of input parameters [9]. Artificial neural network (ANN) has recently proved its availability to tackle with thermal engineering problems [10,11]. ANN has also been used in system modeling, identification, control, forecasting, power systems and optimization [12][13][14]. ANN has also been proposed to deal with ash fouling [15], but it is not completely used for tackle the problem of variables influence. Some examples are important revisions of the ANN applications and references made in the field of energy [16].In this paper, the cleanliness factors (C...

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Criteria selection for the assessment of Serbian lignites tendency to form deposits on power boilers heat transfer surfaces

Cited by 9 publications

References 1 publication

Review of the investigations of pulverized coal combustion processes in large power plants in laboratory for thermal engineering and energy: Part B

Review of the investigations of pulverized coal combustion processes in large power plants in laboratory for thermal engineering and energy: Part B

Analysis criteria for the assessment of deposits formation on boilers heat surfaces during biomass combustion

Ash fouling monitoring and key variables analysis for coal fired power plant boiler

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