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Prediction of tube temperature distribution of boiler platen superheater by a coupled combustion and hydrodynamic model

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  • Jin, Donghao
  • Yan, Jingwen
  • Liu, Xin
  • Zhang, Chaoqun
  • Wang, Heyang

Abstract

The platen superheater of boiler is prone to tube overheating in comparison to other boiler heating surfaces. The resultant tube failures seriously affect the safe operation of boilers. The tube temperature of boiler is determined by the “heating” of the gas flow in the furnace and the “cooling” of the steam flow in the tubes. In order to incorporate the effects of both the gas and steam flows of boiler on tube temperature, this paper presented a coupled combustion and hydrodynamic model in which the gas flow in the furnace is simulated by a three-dimensional CFD model while the steam flow in the tubes is simulated by a one-dimensional hydrodynamic model. The two models are coupled by iteratively exchanging the data of boiler gas heat flux and steam temperature. This coupled model was applied to predict the tube temperature distributions of the platen superheater of a 600 MW boiler and investigate the effects of boiler load and superheater design on the tube temperature and overheated tube areas. The results showed close agreement with the measured values and incorporated the critical effects of both the gas thermal deviation and steam flow maldistribution on the tube overheating of the platen superheater.

Suggested Citation

  • Jin, Donghao & Yan, Jingwen & Liu, Xin & Zhang, Chaoqun & Wang, Heyang, 2023. "Prediction of tube temperature distribution of boiler platen superheater by a coupled combustion and hydrodynamic model," Energy, Elsevier, vol. 279(C).
    • Handle: RePEc:eee:energy:v:279:y:2023:i:c:s0360544223015104
    DOI: 10.1016/j.energy.2023.128116
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    References listed on IDEAS

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    Cited by:

    1. Yin, Linfei & Zhou, Hang, 2024. "Modal decomposition integrated model for ultra-supercritical coal-fired power plant reheater tube temperature multi-step prediction," Energy, Elsevier, vol. 292(C).
    2. 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).

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