IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v204y2017icp1124-1137.html
   My bibliography  Save this article

Development of high-temperature corrosion risk monitoring system in pulverized coal boilers based on reducing conditions identification and CFD simulations

Author

Listed:
  • Modlinski, Norbert
  • Hardy, Tomasz

Abstract

Low-emission combustion (for example the use of low-NOx burners and air staging) contributes to formation of a reducing atmosphere in the furnace, that is accompanied by oxygen depletion and excess of CO in the vicinity (boundary layer) of waterwalls. Corrosion of boiler tubes is often caused by reducing atmosphere. O2 and CO measurement in the boundary layer of evaporators can be a good indicator of corrosion risk assessment. System based on the on-line measurement of the O2 and CO concentration in the boundary layer of the industrial scale boiler walls was described. To improve the functionality of the monitoring system Computational Fluid Dynamics may appear helpful. A validated CFD model capable of properly predicting the CO and O2 concentration in the vicinity of the combustion chamber walls may help to adjust the monitoring system during variable boiler operating conditions or different fuel properties without the necessity to repeat the measurements for new conditions. The scientific part of the current research is concentrated on volatiles combustion simulation with the emphasis on CO burnout. Four popular global mechanisms have been implemented into CFD code and their CO and O2 predictive capabilities are demonstrated. Additionally global mechanisms have been compared to detailed one in Perfectly Stirred Reactor model. It appears that the choice of global mechanism has significant influence on CO and O2 prediction. The measurements of the CO and O2 in the waterwalls boundary layer have been extracted from the monitoring system and compared to simulation results. One of the tested mechanisms demonstrated acceptable qualitative agreement with the measurement in terms of O2 predictions. The quantitative accuracy of CFD-based oxygen prediction in the boundary layer was described as moderate. CFD-based CO prediction was less satisfactory.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:204:y:2017:i:c:p:1124-1137
    DOI: 10.1016/j.apenergy.2017.04.084
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917304877
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2017.04.084?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yin, Chungen & Yan, Jinyue, 2016. "Oxy-fuel combustion of pulverized fuels: Combustion fundamentals and modeling," Applied Energy, Elsevier, vol. 162(C), pages 742-762.
    2. Modliński, Norbert & Madejski, Pawel & Janda, Tomasz & Szczepanek, Krzysztof & Kordylewski, Wlodzimierz, 2015. "A validation of computational fluid dynamics temperature distribution prediction in a pulverized coal boiler with acoustic temperature measurement," Energy, Elsevier, vol. 92(P1), pages 77-86.
    3. Hu, Yukun & Li, Hailong & Yan, Jinyue, 2014. "Numerical investigation of heat transfer characteristics in utility boilers of oxy-coal combustion," Applied Energy, Elsevier, vol. 130(C), pages 543-551.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Maximilian von Bohnstein & Coskun Yildiz & Lorenz Frigge & Jochen Ströhle & Bernd Epple, 2020. "Simulation Study of the Formation of Corrosive Gases in Coal Combustion in an Entrained Flow Reactor," Energies, MDPI, vol. 13(17), pages 1-24, September.
    3. Wang, Zhimin & Huang, Qian & Liu, Guanqing & Wang, Kexuan & Lyu, Junfu & Li, Shuiqing, 2024. "Knowledge-inspired data-driven prediction of overheating risks in flexible thermal-power plants," Applied Energy, Elsevier, vol. 364(C).
    4. Jakub Mularski & Norbert Modliński, 2020. "Impact of Chemistry–Turbulence Interaction Modeling Approach on the CFD Simulations of Entrained Flow Coal Gasification," Energies, MDPI, vol. 13(23), pages 1-25, December.
    5. Tomasz Hardy & Amit Arora & Halina Pawlak-Kruczek & Wojciech Rafajłowicz & Jerzy Wietrzych & Łukasz Niedźwiecki & Vishwajeet & Krzysztof Mościcki, 2021. "Non-Destructive Diagnostic Methods for Fire-Side Corrosion Risk Assessment of Industrial Scale Boilers, Burning Low Quality Solid Biofuels—A Mini Review," Energies, MDPI, vol. 14(21), pages 1-15, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mansir, Ibrahim B. & Ben-Mansour, Rached & Habib, Mohamed A., 2018. "Oxy-fuel combustion in a two-pass oxygen transport reactor for fire tube boiler application," Applied Energy, Elsevier, vol. 229(C), pages 828-840.
    2. Ramadan, Islam A. & Ibrahim, Abdelmaged H. & Abou-Arab, Tharwat W. & Rashwan, Sherif S. & Nemitallah, Medhat A. & Habib, Mohamed A., 2016. "Effects of oxidizer flexibility and bluff-body blockage ratio on flammability limits of diffusion flames," Applied Energy, Elsevier, vol. 178(C), pages 19-28.
    3. Yin, Chungen, 2017. "Prediction of air-fuel and oxy-fuel combustion through a generic gas radiation property model," Applied Energy, Elsevier, vol. 189(C), pages 449-459.
    4. Bordbar, Hadi & Maximov, Alexander & Hyppänen, Timo, 2019. "Improved banded method for spectral thermal radiation in participating media with spectrally dependent wall emittance," Applied Energy, Elsevier, vol. 235(C), pages 1090-1105.
    5. Yang, Xin & Clements, Alastair & Szuhánszki, János & Huang, Xiaohong & Farias Moguel, Oscar & Li, Jia & Gibbins, Jon & Liu, Zhaohui & Zheng, Chuguang & Ingham, Derek & Ma, Lin & Nimmo, Bill & Pourkash, 2018. "Prediction of the radiative heat transfer in small and large scale oxy-coal furnaces," Applied Energy, Elsevier, vol. 211(C), pages 523-537.
    6. Hu, Yukun & Tan, CK & Broughton, Jonathan & Roach, Paul Alun, 2016. "Development of a first-principles hybrid model for large-scale reheating furnaces," Applied Energy, Elsevier, vol. 173(C), pages 555-566.
    7. Laubscher, Ryno & Rousseau, Pieter, 2020. "Numerical investigation on the impact of variable particle radiation properties on the heat transfer in high ash pulverized coal boiler through co-simulation," Energy, Elsevier, vol. 195(C).
    8. Guo, Junjun & Liu, Zhaohui & Hu, Fan & Li, Pengfei & Luo, Wei & Huang, Xiaohong, 2018. "A compatible configuration strategy for burner streams in a 200 MWe tangentially fired oxy-fuel combustion boiler," Applied Energy, Elsevier, vol. 220(C), pages 59-69.
    9. Wu, Hai-bo & Xu, Ming-xin & Li, Yan-bing & Wu, Jin-hua & Shen, Jian-chong & Liao, Haiyan, 2020. "Experimental research on the process of compression and purification of CO2 in oxy-fuel combustion," Applied Energy, Elsevier, vol. 259(C).
    10. Mikulčić, Hrvoje & von Berg, Eberhard & Vujanović, Milan & Wang, Xuebin & Tan, Houzhang & Duić, Neven, 2016. "Numerical evaluation of different pulverized coal and solid recovered fuel co-firing modes inside a large-scale cement calciner," Applied Energy, Elsevier, vol. 184(C), pages 1292-1305.
    11. Ma, Lun & Fang, Qingyan & Yin, Chungen & Wang, Huajian & Zhang, Cheng & Chen, Gang, 2019. "A novel corner-fired boiler system of improved efficiency and coal flexibility and reduced NOx emissions," Applied Energy, Elsevier, vol. 238(C), pages 453-465.
    12. Zhang, Xin & Chen, Zhichao & Hou, Jian & Liu, Zheng & Zeng, Lingyan & Li, Zhengqi, 2022. "Evaluation of wide-range coal combustion performance of a novel down-fired combustion technology based on gas–solid two-phase flow characteristics," Energy, Elsevier, vol. 248(C).
    13. Li, Xinli & Wang, Yingnan & Zhu, Yun & Yang, Guotian & Liu, He, 2021. "Temperature prediction of combustion level of ultra-supercritical unit through data mining and modelling," Energy, Elsevier, vol. 231(C).
    14. Zhou, Jing & Zhu, Meng & Su, Sheng & Chen, Lei & Xu, Jun & Hu, Song & Wang, Yi & Jiang, Long & Zhong, Wenqi & Xiang, Jun, 2020. "Numerical analysis and modified thermodynamic calculation methods for the furnace in the 1000 MW supercritical CO2 coal-fired boiler," Energy, Elsevier, vol. 212(C).
    15. Díez, Luis I. & García-Mariaca, Alexander & Canalís, Paula & Llera, Eva, 2023. "Oxy-combustion characteristics of torrefied biomass and blends under O2/N2, O2/CO2 and O2/CO2/H2O atmospheres," Energy, Elsevier, vol. 284(C).
    16. Li, Shiyuan & Xu, Mingxin & Jia, Lufei & Tan, Li & Lu, Qinggang, 2016. "Influence of operating parameters on N2O emission in O2/CO2 combustion with high oxygen concentration in circulating fluidized bed," Applied Energy, Elsevier, vol. 173(C), pages 197-209.
    17. Lupiáñez, Carlos & Carmen Mayoral, M. & Díez, Luis I. & Pueyo, Eloy & Espatolero, Sergio & Manuel Andrés, J., 2016. "The role of limestone during fluidized bed oxy-combustion of coal and biomass," Applied Energy, Elsevier, vol. 184(C), pages 670-680.
    18. Prabu, V., 2015. "Integration of in-situ CO2-oxy coal gasification with advanced power generating systems performing in a chemical looping approach of clean combustion," Applied Energy, Elsevier, vol. 140(C), pages 1-13.
    19. Bo Gao & Chunsheng Wang & Yukun Hu & C. K. Tan & Paul Alun Roach & Liz Varga, 2018. "Function Value-Based Multi-Objective Optimisation of Reheating Furnace Operations Using Hooke-Jeeves Algorithm," Energies, MDPI, vol. 11(9), pages 1-18, September.
    20. Wenshuai Wang & Mo Yang, 2024. "Numerical and Experimental Study on Nonlinear Phenomena and Thermal Deviation Control in a 1000 MW Tower-Type Boiler," Energies, MDPI, vol. 17(6), pages 1-32, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:204:y:2017:i:c:p:1124-1137. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.