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Parametrization Study for Optimal Pre-Combustion Integration of Membrane Processes in BIGCC

Author

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  • Maytham Alabid

    (Faculty of Energy, University Politehnica of Bucharest, Splaiul Independenței, 060042 Bucharest, Romania)

  • Cristian Dinca

    (Faculty of Energy, University Politehnica of Bucharest, Splaiul Independenței, 060042 Bucharest, Romania
    Academy of Romanian Scientists, Ilfov 3, 050044 Bucharest, Romania)

Abstract

Presently, the utilization of biomass as an energy source has gained significant attention globally due to its capacity to provide constant feedstock. In 2020, biomass combustion generated 19 Mt of CO 2 , representing an increase of 16% from the previous year. The increase in CO 2 emissions is fundamentally due to biomass gasification in power plants. Due to the growing demand to reduce greenhouse gas emissions, this paper aims to improve CO 2 capture technologies to face this challenge. In this context, the utilization of three stages of the polymer membrane process, using different compressor pressure values, has been technically and economically analyzed. The proposed solution was combined pre-combustion in a BIGCC process equipped with a Siemens gas turbine with an installed power capacity of 50 MW. The article simulated energy operations by using membranes of polymer and CHEMCAD software improved in the CO 2 integration research project. Consequently, polymeric membranes with CO 2 permeability of 1000 GPU were examined while CO 2 selectivity towards nitrogen was investigated to be 50. It was observed that by increasing the surface area of the polymer membrane (400,000–1,200,000 m 2 ) an increase of 37% occurs in CO 2 capture efficiency. On the other hand, LCOE increased from 97 to 141 EUR/MWh. The avoided cost of CO 2 captured was 52.9 EUR/ton.

Suggested Citation

  • Maytham Alabid & Cristian Dinca, 2022. "Parametrization Study for Optimal Pre-Combustion Integration of Membrane Processes in BIGCC," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16604-:d:1000476
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    References listed on IDEAS

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