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Coordinated control approach for load following operation of SOFC-GT hybrid system

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  • Wang, Xusheng
  • Lv, Xiaojing
  • Mi, Xicong
  • Spataru, Catalina
  • Weng, Yiwu

Abstract

In order to achieve the fast load following and safe transient operation of Solid Oxide Fuel Cell-Gas Turbine hybrid system, a novel control approach by combining the multi control loops with the coordinated protection loops is proposed in this work. The coordinated protection loops can adjust the transient behavior of operation parameters on-line to avoid the undesired operation faults, such as compressor surge, reformer carbon deposition, fuel cell thermal crack and turbine blade overheat. Meanwhile, the fuzzy logic theory is introduced to self-tuning the control parameters to meet the control requirements of the nonlinear time varying system. The analysis in system transient behavior during load step changes operation indicates that the present work can realize parameters decoupling and eliminate the instability of SOFC-GT. The proposed control strategy can reduce the SOFC current overshoot by 10.8% during the load step-down operation, meanwhile, this reduces the transient maximum temperature changing rate by almost 47.7%. In addition, by changing the transient behavior of air and fuel flow, the proposed control strategy can reduce the temperature overshoot by 1.16% in load step-up operation. This leads to the transient maximum temperature gradient is decreased by 0.18K/cm.

Suggested Citation

  • Wang, Xusheng & Lv, Xiaojing & Mi, Xicong & Spataru, Catalina & Weng, Yiwu, 2022. "Coordinated control approach for load following operation of SOFC-GT hybrid system," Energy, Elsevier, vol. 248(C).
    • Handle: RePEc:eee:energy:v:248:y:2022:i:c:s0360544222004510
    DOI: 10.1016/j.energy.2022.123548
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    References listed on IDEAS

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    2. Martsinchyk, Aliaksandr & Milewski, Jaroslaw & Dybiński, Olaf & Szczęśniak, Arkadiusz & Siekierski, Maciej & Świrski, Konrad, 2023. "Experimental investigation of novel molten borate fuel cell supported by an artificial neural network for electrolyte composition selection," Energy, Elsevier, vol. 279(C).
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    5. Xu, Yuhao & Luo, Xiaobing & Tu, Zhengkai & Siew Hwa Chan,, 2022. "Multi-criteria assessment of solid oxide fuel cell–combined cooling, heating, and power system model for residential application," Energy, Elsevier, vol. 259(C).

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