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Using multi-objective optimisation in the design of CO2 capture systems for retrofit to coal power stations

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  • Harkin, Trent
  • Hoadley, Andrew
  • Hooper, Barry

Abstract

An Aspen Plus® simulation of an existing power station with a potassium carbonate based carbon capture (CCS) plant including CO2 compression is combined with an Excel based genetic algorithm to optimise the net power output of the power station and amount of CO2 captured for a range of solvent flowrates, lean loading and stripper pressures. The net power output was compared for a CCS plant that is added to the power station without any heat integration to a system where heat integration is maximised by the use of pinch analysis and linear optimisation to calculate the amount of steam required to be extracted from the turbine to meet the additional heating requirements of the CCS plant. The multi-objective optimisation of the process identified that lean solvent loading and stripper pressure will have a large impact on the net power output and amount of CO2 captured. The curves developed in the multi-objective optimisation can provide not only the ability to determine the CO2 capture rate to maximise the profit at a given time due to fluctuating electricity prices, but will also provide the optimum solvent flowrate and lean loading to achieve that maximum capture rate for a given net power. The paper shows that the design of the optimum carbon capture plant will depend not only on the specific capture process but also on the conditions of the power station and the importance in optimising the whole process at the same time. The minimum energy penalty for the potassium carbonate system combined with the reference power station modeled in this paper is 1.02 MJe/kgCO2 with a reboiler regeneration energy of 5.3 MJth/kgCO2. In this example optimisation and heat integration was able to reduce the energy penalty by 0.4 MJe/kgCO2.

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  • Harkin, Trent & Hoadley, Andrew & Hooper, Barry, 2012. "Using multi-objective optimisation in the design of CO2 capture systems for retrofit to coal power stations," Energy, Elsevier, vol. 41(1), pages 228-235.
    • Handle: RePEc:eee:energy:v:41:y:2012:i:1:p:228-235
    DOI: 10.1016/j.energy.2011.06.031
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    References listed on IDEAS

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    1. Page, S.C. & Williamson, A.G. & Mason, I.G., 2009. "Carbon capture and storage: Fundamental thermodynamics and current technology," Energy Policy, Elsevier, vol. 37(9), pages 3314-3324, September.
    2. Pellegrini, G. & Strube, R. & Manfrida, G., 2010. "Comparative study of chemical absorbents in postcombustion CO2 capture," Energy, Elsevier, vol. 35(2), pages 851-857.
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    3. Valiani, Saba & Tahouni, Nassim & Panjeshahi, M. Hassan, 2017. "Optimization of pre-combustion capture for thermal power plants using Pinch Analysis," Energy, Elsevier, vol. 119(C), pages 950-960.
    4. Mardan, Nawzad & Klahr, Roger, 2012. "Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry," Energy, Elsevier, vol. 44(1), pages 410-419.
    5. Mores, Patricia & Scenna, Nicolás & Mussati, Sergio, 2012. "CO2 capture using monoethanolamine (MEA) aqueous solution: Modeling and optimization of the solvent regeneration and CO2 desorption process," Energy, Elsevier, vol. 45(1), pages 1042-1058.
    6. Khalilpour, Rajab, 2014. "Multi-level investment planning and scheduling under electricity and carbon market dynamics: Retrofit of a power plant with PCC (post-combustion carbon capture) processes," Energy, Elsevier, vol. 64(C), pages 172-186.
    7. Ligang Wang & Zhiping Yang & Shivom Sharma & Alberto Mian & Tzu-En Lin & George Tsatsaronis & François Maréchal & Yongping Yang, 2018. "A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants," Energies, MDPI, vol. 12(1), pages 1-53, December.
    8. Jordán, Pérez Sánchez & Javier Eduardo, Aguillón Martínez & Zdzislaw, Mazur Czerwiec & Alan Martín, Zavala Guzmán & Liborio, Huante Pérez & Jesús Antonio, Flores Zamudio & Mario Román, Díaz Guillén, 2019. "Techno-economic analysis of solar-assisted post-combustion carbon capture to a pilot cogeneration system in Mexico," Energy, Elsevier, vol. 167(C), pages 1107-1119.
    9. Pérez Sánchez, Jordán & Aguillón Martínez, Javier Eduardo & Mazur Czerwiec, Zdzislaw & Zavala Guzmán, Alan Martín, 2019. "Theoretical assessment of integration of CCS in the Mexican electrical sector," Energy, Elsevier, vol. 167(C), pages 828-840.
    10. Li, Long & Liu, Weizao & Qin, Zhifeng & Zhang, Guoquan & Yue, Hairong & Liang, Bin & Tang, Shengwei & Luo, Dongmei, 2021. "Research on integrated CO2 absorption-mineralization and regeneration of absorbent process," Energy, Elsevier, vol. 222(C).
    11. Rohlfs, Wilko & Madlener, Reinhard, 2013. "Assessment of clean-coal strategies: The questionable merits of carbon capture-readiness," Energy, Elsevier, vol. 52(C), pages 27-36.
    12. Krishna Priya, G.S. & Bandyopadhyay, Santanu, 2017. "Multi-objective pinch analysis for power system planning," Applied Energy, Elsevier, vol. 202(C), pages 335-347.
    13. Lara, Y. & Martínez, A. & Lisbona, P. & Romeo, L.M., 2016. "Heat integration of alternative Ca-looping configurations for CO2 capture," Energy, Elsevier, vol. 116(P1), pages 956-962.
    14. Van Wagener, David H. & Liebenthal, Ulrich & Plaza, Jorge M. & Kather, Alfons & Rochelle, Gary T., 2014. "Maximizing coal-fired power plant efficiency with integration of amine-based CO2 capture in greenfield and retrofit scenarios," Energy, Elsevier, vol. 72(C), pages 824-831.

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