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

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  • 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)

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.

Suggested Citation

  • Tomasz Hardy & Sławomir Kakietek & Krzysztof Halawa & Krzysztof Mościcki & Tomasz Janda, 2020. "Determination of High Temperature Corrosion Rates of Steam Boiler Evaporators Using Continuous Measurements of Flue Gas Composition and Neural Networks," Energies, MDPI, vol. 13(12), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3134-:d:372637
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    References listed on IDEAS

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    1. Bartłomiej Hernik, 2020. "Numerical Research of the Modification of the Combustion System in the OP 650 Boiler," Energies, MDPI, vol. 13(3), pages 1-22, February.
    2. Modlinski, Norbert & Hardy, Tomasz, 2017. "Development of high-temperature corrosion risk monitoring system in pulverized coal boilers based on reducing conditions identification and CFD simulations," Applied Energy, Elsevier, vol. 204(C), pages 1124-1137.
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    Cited by:

    1. Tadeáš Ochodek & Emmanouil Karampinis & Artur Pozarlik, 2022. "Contemporary Problems in Combustion—Fuels, Their Valorisation, Emissions, Flexibility and Auxiliary Systems," Energies, MDPI, vol. 15(5), pages 1-4, February.
    2. Martyna Tomala & Andrzej Rusin, 2022. "Risk-Based Operation and Maintenance Planning of Steam Turbine with the Long In-Service Time," Energies, MDPI, vol. 15(14), pages 1-17, July.
    3. Pronobis, Marek & Wejkowski, Robert & Kalisz, Sylwester & Ciukaj, Szymon, 2023. "Conversion of a pulverized coal boiler into a torrefied biomass boiler," Energy, Elsevier, vol. 262(PB).

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