Determination of High Temperature Corrosion Rates of Steam Boiler Evaporators Using Continuous Measurements of Flue Gas Composition and Neural Networks

Tomasz Hardy, Sławomir Kakietek, Krzysztof Halawa, Krzysztof Mościcki and Tomasz Janda
Additional contact information
Tomasz Hardy: Department of Mechanics, Machines, Devices and Energy Processes, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
Sławomir Kakietek: Thermal Processes Department, Institute of Power Engineering, Augustówka 36 Street, 02-981 Warsaw, Poland
Krzysztof Halawa: Department of Computer Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
Krzysztof Mościcki: Department of Mechanics, Machines, Devices and Energy Processes, Wroclaw University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
Tomasz Janda: PGE Energia Ciepła S.A., Ciepłownicza 1 Street, 31-587 Kraków, Poland

Energies, 2020, vol. 13, issue 12, 1-17

Abstract: The use of low-emission combustion techniques in pulverized coal-fired (PC) boilers are usually associated with the formation of a reduced-gas atmosphere near evaporator walls. This increases the risk of high temperature (low oxygen) corrosion processes in coal-fired boilers. The identification of the dynamics and the locations of these processes, and minimizing negative consequences are essential for power plant operation. This paper presents the diagnostic system for determining corrosion risks, based on continuous measurements of flue gas composition in the boundary layer of the combustion chamber, and artificial intelligence techniques. Experience from the implementation of these measurements on the OP-230 hard coal-fired boiler, to identify the corrosion hazard of one of the evaporator walls, has been thoroughly described. The results obtained indicate that the continuous controlling of the concentrations of O 2 and CO near the water wall, in combination with the use of neural networks, allows for the forecasting of the corrosion rate of the evaporator. The correlation between flue gas composition and corrosion rate has been demonstrated. At the same time, the analysis of the possibilities of significantly simplifying the measurement system by using neural networks was carried out.

Keywords: steam boiler; high-temperature corrosion; online monitoring; neural networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/12/3134/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/12/3134/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:12:p:3134-:d:372637

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().