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Performance analysis and carbon reduction assessment of an integrated syngas purification process for the co-production of hydrogen and power in an integrated gasification combined cycle plant

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  • Lee, Woo-Sung
  • Oh, Hyun-Taek
  • Lee, Jae-Cheol
  • Oh, Min
  • Lee, Chang-Ha

Abstract

The integrated gasification combined cycle (IGCC) is prominent in coal-based power plants because of its high efficiency and environmental benefit. Because of global warming, the integration of a carbon capture process (CCP) into the IGCC is exigent. In this study, performance analysis of an integrated syngas purification process was performed for a 500 MW-class IGCC. First, various carbon capture efficiencies were investigated to elucidate the most economical carbon capture efficiency, and a carbon capture efficiency of 90% was recommended. This value includes sour gas (H2S) removal cost, and it is essential for coal-power plants regardless of carbon capture. Thus, the net carbon capture cost was calculated from the difference in the operating costs of the integrated syngas purification process with/without a CCP. The net carbon capture cost per ton of CO2 was determined as approximately 21 USD. In addition, the exergy analysis and H2 co-production from the integrated syngas purification process with pressure swing adsorption (PSA) were presented to suggest the direction of the potential process improvement and carbon reduction assessment. The study can contribute towards decision-making related to investment in near-future candidate technologies for increasing efficiency and carbon emissions.

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  • Lee, Woo-Sung & Oh, Hyun-Taek & Lee, Jae-Cheol & Oh, Min & Lee, Chang-Ha, 2019. "Performance analysis and carbon reduction assessment of an integrated syngas purification process for the co-production of hydrogen and power in an integrated gasification combined cycle plant," Energy, Elsevier, vol. 171(C), pages 910-927.
    • Handle: RePEc:eee:energy:v:171:y:2019:i:c:p:910-927
    DOI: 10.1016/j.energy.2019.01.069
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    3. Vo, Nguyen Dat & Oh, Dong Hoon & Kang, Jun-Ho & Oh, Min & Lee, Chang-Ha, 2020. "Dynamic-model-based artificial neural network for H2 recovery and CO2 capture from hydrogen tail gas," Applied Energy, Elsevier, vol. 273(C).
    4. Zhang, Chao & Shen, Yuanhui & Zhang, Donghui & Tang, Zhongli & Li, Wenbin, 2022. "Vacuum pressure swing adsorption for producing fuel cell grade hydrogen from IGCC," Energy, Elsevier, vol. 257(C).
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    6. Oh, Hyun-Taek & Lee, Woo-Sung & Ju, Youngsan & Lee, Chang-Ha, 2019. "Performance evaluation and carbon assessment of IGCC power plant with coal quality," Energy, Elsevier, vol. 188(C).

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