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Graph theory-based heat current analysis method for supercritical CO2 power generation system

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  • Li, Xia
  • Chen, Qun
  • Chen, Xi
  • He, Ke-Lun
  • Hao, Jun-Hong

Abstract

Supercritical carbon dioxide (sCO2) power generation system holds tremendous potential in energy utilization fields featuring with its high efficiency, compactness, and security. However, dramatic variations in sCO2 thermophysical properties make the existing constant property analysis methods imprecise. In this contribution, inlet temperature difference-based thermal resistance transforms the nonlinear governing equations of heat transfer process into linear forms, and applying the graph theory builds the heat current model of a sCO2 recompression cycle with consideration of fluid property variation, which is analogous to electric circuit. Therefore, utilizing the electric circuit principle offers the overall heat transport and conversion laws in the whole system and gives the integral mathematical relations of all independent variables, which are solved by the newly proposed iterative divide-and-conquer solution algorithm. Finally, optimization of a typical sCO2 recompression system under different boundary conditions shows the applicability and conciseness of the heat current method compared to the existing analysis methods.

Suggested Citation

  • Li, Xia & Chen, Qun & Chen, Xi & He, Ke-Lun & Hao, Jun-Hong, 2020. "Graph theory-based heat current analysis method for supercritical CO2 power generation system," Energy, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:energy:v:194:y:2020:i:c:s0360544220300189
    DOI: 10.1016/j.energy.2020.116911
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    Cited by:

    1. Sun, Lei & Liu, Tianyuan & Wang, Ding & Huang, Chengming & Xie, Yonghui, 2022. "Deep learning method based on graph neural network for performance prediction of supercritical CO2 power systems," Applied Energy, Elsevier, vol. 324(C).
    2. Zhang, Ruiyuan & Su, Wen & Lin, Xinxing & Zhou, Naijun & Zhao, Li, 2020. "Thermodynamic analysis and parametric optimization of a novel S–CO2 power cycle for the waste heat recovery of internal combustion engines," Energy, Elsevier, vol. 209(C).
    3. Zhao, Tian & Chen, Xi & He, Ke-Lun & Chen, Qun, 2021. "A standardized modeling strategy for heat current method-based analysis and simulation of thermal systems," Energy, Elsevier, vol. 217(C).
    4. Xin, Yong-Lin & Sun, Qing-Han & Zhao, Tian & Li, Xia & Chen, Qun, 2023. "A categorized and decomposed algorithm for thermal system simulation based on generalized benders decomposition," Energy, Elsevier, vol. 282(C).

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