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Modelling and control of pulverizing system considering coal moisture

Author

Listed:
  • Zeng, De-Liang
  • Hu, Yong
  • Gao, Shan
  • Liu, Ji-Zhen

Abstract

The pulverizing system serves an important function in the safe and efficient operation of thermal power units. The effect of coal moisture and pulverized coal moisture on the pulverizing system was considered in establishing a mass and energy balance-based dynamic mathematical model of a coal mill. The parameters of the model were identified by using the genetic algorithm and later validated with measurements. An extended Kalman filter was designed to estimate and verify the internal states of the coal mill. Based on the dynamic mathematical model of coal mill, pulverized coal moisture was used as a feed-forward signal, and a feed-forward compensation controller was designed to optimize the coal mill outlet temperature. Simulation results showed that the dynamic characteristic of the mill can be forecasted effectively with the established model. Moreover, pulverized coal moisture was reduced with feed-forward compensation, thereby improving the efficiency of the boiler.

Suggested Citation

  • Zeng, De-Liang & Hu, Yong & Gao, Shan & Liu, Ji-Zhen, 2015. "Modelling and control of pulverizing system considering coal moisture," Energy, Elsevier, vol. 80(C), pages 55-63.
    • Handle: RePEc:eee:energy:v:80:y:2015:i:c:p:55-63
    DOI: 10.1016/j.energy.2014.11.042
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    References listed on IDEAS

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    1. Kortela, J. & Jämsä-Jounela, S-L., 2013. "Fuel moisture soft-sensor and its validation for the industrial BioPower 5 CHP plant," Applied Energy, Elsevier, vol. 105(C), pages 66-74.
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    Cited by:

    1. Xiufan Liang & Yiguo Li & Xiao Wu & Jiong Shen, 2018. "Nonlinear Modeling and Inferential Multi-Model Predictive Control of a Pulverizing System in a Coal-Fired Power Plant Based on Moving Horizon Estimation," Energies, MDPI, vol. 11(3), pages 1-27, March.
    2. Li, Zixiang & Miao, Zhengqing & Zhou, Yan & Wen, Shurong & Li, Jiangtao, 2018. "Influence of increased primary air ratio on boiler performance in a 660 MW brown coal boiler," Energy, Elsevier, vol. 152(C), pages 804-817.
    3. Li, Zixiang & Miao, Zhengqing & Shen, Xusheng & Li, Jiangtao, 2018. "Effects of momentum ratio and velocity difference on combustion performance in lignite-fired pulverized boiler," Energy, Elsevier, vol. 165(PA), pages 825-839.
    4. Li, Zixiang & Miao, Zhengqing & Shen, Xusheng & Li, Jiangtao, 2018. "Prevention of boiler performance degradation under large primary air ratio scenario in a 660 MW brown coal boiler," Energy, Elsevier, vol. 155(C), pages 474-483.
    5. Yong Hu & Boyu Ping & Deliang Zeng & Yuguang Niu & Yaokui Gao, 2020. "Modeling of Coal Mill System Used for Fault Simulation," Energies, MDPI, vol. 13(7), pages 1-14, April.

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    1. Kortela, J. & Jämsä-Jounela, S.-L., 2014. "Model predictive control utilizing fuel and moisture soft-sensors for the BioPower 5 combined heat and power (CHP) plant," Applied Energy, Elsevier, vol. 131(C), pages 189-200.

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