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Mathematical model of a power boiler operation under rapid thermal load changes

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  • Zima, Wiesław
  • Grądziel, Sławomir
  • Cebula, Artur
  • Rerak, Monika
  • Kozak-Jagieła, Ewa
  • Pilarczyk, Marcin

Abstract

Due to the current need for coal-fired power units to cooperate with renewable energy sources, they should be characterized by a high flexibility of operation. An in-house mathematical model of a natural circulation power boiler was developed to analyse whether such cooperation is possible. A new method to simulate the heating of several surfaces located parallel in one flue gas duct is proposed. The correctness of the results obtained using the developed model was verified experimentally. A test was performed in a fossil fuel-fired power plant involving a rapid increase in the steam mass flow rate at the boiler outlet. The model verification consisted of comparing the measured and computed temperature and mass flow rates of the fluids at several boiler locations. To estimate the accuracy of the results obtained using the developed model, relative errors and root-mean-square errors were calculated. The small values of these errors indicate the correctness of the results obtained with in-house developed computation methods. The mathematical models presented in this study can be used in power unit simulators. In particular, they can be applied to create in-house models of other power boilers intended for cooperation with renewable energy sources under fast-changing loads.

Suggested Citation

  • Zima, Wiesław & Grądziel, Sławomir & Cebula, Artur & Rerak, Monika & Kozak-Jagieła, Ewa & Pilarczyk, Marcin, 2023. "Mathematical model of a power boiler operation under rapid thermal load changes," Energy, Elsevier, vol. 263(PC).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pc:s0360544222027220
    DOI: 10.1016/j.energy.2022.125836
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    Cited by:

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    2. Li, Guolong & Li, Yanjun & Fang, Chengyue & Su, Jian & Wang, Haotong & Sun, Shengdi & Zhang, Guolei & Shi, Jianxin, 2023. "Research on fault diagnosis of supercharged boiler with limited data based on few-shot learning," Energy, Elsevier, vol. 281(C).

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