Skip to main content

Advertisement

Log in

Detection of Ash Fouling in Thermal Power Plant

  • Short Communication
  • Published:
National Academy Science Letters Aims and scope Submit manuscript

Abstract

Ash fouling is one of the significant problems in thermal power plant. It degrades the thermal performance of heat transfer surfaces; hence, soot blowers are initiated in a pre-defined sequence and scheduled to clean the surfaces. Frequent soot blow operation leads to waste of steam, increased maintenance cost and tube erosion. This study aims in developing a simplified method to detect economizer fouling based on the assessment of cleanliness factor. Economizer model that includes the heat capacity of metal between flue gas and feed water is simulated and validated using power plant data. The decrease in efficiency and cleanliness factor with effect of fouling is analyzed. It is observed that a 3% decrease in cleanliness factor in the economizer leads to a 2% loss in its efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

References

  1. Teruel E, Cortes C, Diez LI, Arauzo I (2005) Monitoring and prediction of fouling in coal fired utility boilers using neural network. Chem Eng Sci 60:5035–5048

    Article  CAS  Google Scholar 

  2. Johnson R, Subasavage B, Breeding CH (2004) Superheater fouling monitor system. Electric Power, Baltimore, Maryland, March 30–April 1, pp 3–10

  3. Simon FM, Jochum B, Lang A (2006) Increase of steam generator output firing coal qualities through new intelligent on-load cleaning technology. VGB Power Tech 86(11):40–45

    Google Scholar 

  4. Zhang S, Shen G, An L, Niu Y, Jiang G (2015) Monitoring ash fouling in power station boiler furnaces using acoustic pyrometry. Chem Eng Sci 126:216–223

    Article  CAS  Google Scholar 

  5. Wallhauber E, Hussein WB, Hussein MA, Hinrichs J, Becker TM (2011) On the usage of acoustic properties combined with an artificial neural network—a new approach of determining presence of dairy fouling. J Food Eng 103(4):449–456

    Article  Google Scholar 

  6. Radhakrishnan VR, Ramasamy M, Zabiri H, DoThanh V, Tahir NM, Mukhtar H, Hamdi MR, Ramli N (2007) Heat exchanger fouling model and preventive maintenance scheduling tool. Appl Therm Eng 27:2791–2802

    Article  Google Scholar 

  7. Mohanty DK, Singru PM (2014) Fouling analysis of a shell and tube heat exchanger using local linear wavelet neural network. Int J Heat Mass Transf 77:946–955

    Article  Google Scholar 

  8. Jonsson GR, Lalot S, Palsson OP, Desmet B (2007) Use of extended Kalman filtering in detecting fouling in heat exchangers. Int J Heat Mass Transf 50:2643–2655

    Article  Google Scholar 

  9. Delmotte F, Dambrine M, Delrot S, Lalot S (2013) Fouling detection in a heat exchanger: a polynomial fuzzy observer approach. Control Eng Pract 21(10):1386–1395

    Article  Google Scholar 

  10. Delrot S, Guerra TM, Dambrine M, Delmotte F (2012) Fouling detection in a heat exchanger by observer of Takagi–Sugeno type for systems with unknown polynomial inputs. Eng Appl Artif Intell 25(8):1558–1566

    Article  Google Scholar 

  11. Shi Y, Wang J, Liu Z (2015) Online monitoring of ash fouling and soot-blowing optimization for convective heat exchanger in coal fired power plant boiler. Appl Therm Eng 78:39–50

    Article  Google Scholar 

  12. Shi Y, Wang J (2015) Ash fouling monitoring and key variables analysis for coal fired power plant boiler. J Therm Sci 19(1):253–265

    Article  Google Scholar 

  13. Lalot S, Palsson H (2010) Detection of fouling in a cross-flow heat exchanger using a neural network based technique. Int J Therm Sci 49(4):675–679

    Article  Google Scholar 

  14. Taler J, Taler D (2009) Slag monitoring system of combustion chambers of steam boilers. Heat Transf Eng 30(11):903–911

    Article  ADS  CAS  Google Scholar 

  15. Trojan M, Taler D (2015) Thermal simulation of superheaters taking into account the processes occurring on the side of steam and flue gas. Fuel 150:75–87

    Article  CAS  Google Scholar 

  16. Ordys AW, Pike AW, Johnson MA, Katebi RM, Grimble MJ (1994) Modelling and simulation of power generation plants. Springer, London

    Book  Google Scholar 

Download references

Acknowledgements

This work is supported by Department of Science and Technology under DST-PURSE phase II programme-5. Manpower (Proc. No. 9500/PD2/2014, M.H.No.7.1.3.69).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anitha Kumari Sivathanu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sivathanu, A., Subramanian, S. & Ramalingam, P. Detection of Ash Fouling in Thermal Power Plant. Natl. Acad. Sci. Lett. 41, 369–373 (2018). https://doi.org/10.1007/s40009-018-0734-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40009-018-0734-y

Keywords

Navigation