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On-line simulation and optimization of a commercial-scale shell entrained-flow gasifier using a novel dynamic reduced order model

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  • Zhou, Hua
  • Xie, Taili
  • You, Fengqi

Abstract

The development of computationally efficient, accurate, and stable dynamic reduced order models of Shell Entrained-flow gasifiers would help to better understand the influence of design variables, feedstocks, and processing conditions on the operating performance of the reactors. This work presents a novel dynamic model of a commercial-scale Shell entrained-flow gasifier for on-line process simulation and soft-measurement of relevant process variables. A dynamic mathematical model of the reactor is developed to obtain real-time performance data of some unmeasurable variables and assess dynamic performance of the reactor under different operating conditions. The model consists of several sub-models for devolatilization and combustion, gasification, slagging, and heat transfer. To validate the model, the simulation results are compared with the literature data. Sensitivity analysis is further performed for process optimization. Furthermore, dynamic characteristics is analyzed and optimal operational strategies for industrial Shell entrained-flow gasifier is obtained by optimizing the ratio of oxygen with carbon and the ratio of coal with carrier CO2.

Suggested Citation

  • Zhou, Hua & Xie, Taili & You, Fengqi, 2018. "On-line simulation and optimization of a commercial-scale shell entrained-flow gasifier using a novel dynamic reduced order model," Energy, Elsevier, vol. 149(C), pages 516-534.
    • Handle: RePEc:eee:energy:v:149:y:2018:i:c:p:516-534
    DOI: 10.1016/j.energy.2018.02.031
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    Cited by:

    1. Cao, Zhikai & Wu, Qi & Zhou, Hua & Chen, Pingping & You, Fengqi, 2020. "Dynamic modeling, systematic analysis, and operation optimization for shell entrained-flow heavy residue gasifier," Energy, Elsevier, vol. 197(C).
    2. Fang, Neng & Li, Zhengqi & Liu, Shuxuan & Xie, Cheng & Zeng, Lingyan & Chen, Zhichao, 2021. "Experimental air/particle flow characteristics of an 80,000 Nm3/h fly ash entrained-flow gasifier with different multi-burner arrangements," Energy, Elsevier, vol. 215(PB).
    3. Fang, Neng & Li, Zhengqi & Xie, Cheng & Liu, Shuxuan & Lu, Yue & Zeng, Lingyan & Chen, Zhichao, 2021. "Influence of the multi-burner bias angle on the air/particle flow characteristics in an improved fly ash entrained-flow gasifier," Energy, Elsevier, vol. 234(C).
    4. Fang, Neng & Li, Zhengqi & Xie, Cheng & Liu, Shuxuan & Zeng, Lingyan & Chen, Zhichao & Zhang, Bin, 2020. "The application of fly ash gasification for purifying the raw syngas in an industrial-scale entrained flow gasifier," Energy, Elsevier, vol. 195(C).
    5. Fang, Neng & Li, Zhengqi & Wang, Jiaquan & Zhang, Bin & Zeng, Lingyan & Chen, Zhichao & Wang, Haopeng & Liu, Xiaoying & Zhang, Xiaoyan, 2018. "Experimental investigations on air/particle flow characteristics in a 2000 t/d GSP pulverized coal gasifier with an improved burner," Energy, Elsevier, vol. 165(PB), pages 432-441.
    6. Kim, Mukyeong & Ye, Insoo & Jo, Hyunbin & Ryu, Changkook & Kim, Bongkeun & Lee, Jeongsoo, 2020. "New reduced-order model optimized for online dynamic simulation of a Shell coal gasifier," Applied Energy, Elsevier, vol. 263(C).
    7. Wang, Kangcheng & Zhang, Jie & Shang, Chao & Huang, Dexian, 2021. "Operation optimization of Shell coal gasification process based on convolutional neural network models," Applied Energy, Elsevier, vol. 292(C).

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