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Optimal Operation of MEA-Based Post-Combustion Carbon Capture Process for Natural Gas Combined Cycle Power Plants

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Exergy for A Better Environment and Improved Sustainability 1

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Abstract

Carbon capture for fossil fuel power generation draws an increasing attention because of significant challenges of global climate change. This paper aims to explore the optimal operation of MEA-based post-combustion carbon capture (PCC) process for natural gas combined cycle (NGCC) power plant. Levelized cost of electricity (LCOE) is formulated as the objective function to be minimized in optimization. The rate-based steady-state process model including the absorber, stripper and compression train and other auxiliary equipment was developed in Aspen Plus® to give accurate prediction of process performance. The techno-economic estimate was carried out for the base case for whole chain of NGCC integrated with PCC, CO2 transport and storage (T&S). The optimal operations were investigated for the carbon capture level under different carbon price, fuel price and CO2 T&S price. The study shows carbon price needs to be more than 100 EUR/ton CO2 to justify the total cost of carbon capture from the NGCC power plant and needs to be around 150 EUR/ton CO2 to drive carbon capture level to 90–95%. Higher NG price and CO2 T&S price would cause a greater operating cost of running carbon capture process; thus a higher carbon price is needed to rejustify the cost of high carbon capture level of PCC process.

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Acknowledgements

The authors would like to acknowledge the financial support from EU FP7 Marie Curie International Research Staff Exchange Scheme (Ref: PIRSES-GA-2013-612230) and 2013 China-Europe small- and medium-sized enterprises energy saving and carbon reduction research project (No.SQ2013ZOA100002).

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Correspondence to Meihong Wang .

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Luo, X., Wang, M. (2018). Optimal Operation of MEA-Based Post-Combustion Carbon Capture Process for Natural Gas Combined Cycle Power Plants. In: Aloui, F., Dincer, I. (eds) Exergy for A Better Environment and Improved Sustainability 1. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-62572-0_88

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  • DOI: https://doi.org/10.1007/978-3-319-62572-0_88

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