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Direct conversion of syngas to alpha olefins via Fischer–Tropsch synthesis: Process development and comparative techno-economic-environmental analysis

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  • Wang, Danfeng
  • Gu, Yu
  • Chen, Qianqian
  • Tang, Zhiyong

Abstract

Under the pressure of carbon peak and carbon neutrality, coal chemical industry urgently needs to transform to high energy efficiency, low carbon emissions, and high-added value. A coal-based Fischer-Tropsch to olefins route using a new cobalt carbide nanoprisms catalyst for directly converting syngas into olefins was proposed in this study. To evaluate the feasibility and competitiveness of this route, we designed an products separation process and conducted a process simulation via Aspen plus based on laboratory data. On top of that, the energy consumption, energy efficiency, carbon emission, and economic performance of the coal-based Fischer–Tropsch to olefins route were analyzed, in comparison with coal-based methanol to olefins route. The energy consumption of the proposed route is 10.1% lower than that of coal-based methanol to olefins, and its carbon emissions factor is 14.8% lower than that of coal-based methanol to olefins. When the mass weighted product price is 1504 US $/ton, the project's financial internal rate of return of 17.39% is significantly greater than the industry's benchmark internal rate of return of 12%, indicating that the proposed route has strong economic competitiveness. Finally, several suggestions are proposed to improve the comprehensive performance of the proposed route for its sustainable development.

Suggested Citation

  • Wang, Danfeng & Gu, Yu & Chen, Qianqian & Tang, Zhiyong, 2023. "Direct conversion of syngas to alpha olefins via Fischer–Tropsch synthesis: Process development and comparative techno-economic-environmental analysis," Energy, Elsevier, vol. 263(PE).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pe:s0360544222028778
    DOI: 10.1016/j.energy.2022.125991
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    References listed on IDEAS

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    Cited by:

    1. Teimouri, Zahra & Abatzoglou, Nicolas & Dalai, Ajay K., 2024. "A novel machine learning framework for designing high-performance catalysts for production of clean liquid fuels through Fischer-Tropsch synthesis," Energy, Elsevier, vol. 289(C).
    2. Chen, Xiangxiang & Sun, Zhuang & Kuo, Po-Chih & Aziz, Muhammad, 2024. "Carbon-negative olefins production from biomass and solar energy via direct chemical looping," Energy, Elsevier, vol. 289(C).

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