Due to the increase in world population and more energy consumption, Greenhouse Gas (GHG) emissions are increasing. The most important GHG emissions sources are Coal-Fired power plants and Natural Gas Combined-Cycle (NGCC) power plants. One way to help reduce GHG emissions, especially CO2 emissions, is to use CO2 Capture and Storage (CCS) technologies. This paper investigates CO2 Capture methods from combined cycle power plants using bibliometric analysis and data mining. According to the main keywords in the studies by VOSViewer software, a word cloud is obtained from all related topics, classified into 7 clusters. The number of articles published in each of the methods in different years are obtained and each of these cluster’s placement in each Cooperative Patent Classification (CPC) is examined by Google Patent and International Patent Classification (IPC). Finally, the gaps in energy production are examined by word cloud to improve the total net power plant's efficiency using the Post-Combustion CO2 Capture (PCC) technology. By analyzing CPCs and IPCs in patent analysis, the power plants and CO2 Captures technologies are classified. The use of exergy and pinch analysis can be possible to optimize the energy consumption of the PCC unit, and by using the Organic Rankine Cycle (ORC), the total net power output can be optimized. For using different types of CCS technologies, the gaps between them were studied in gaps analysis. Market failures are identified and from a policy perspective, solutions to improve those failures are proposed. By Gap analysis, the potential of using renewable systems and exergy and pinch analysis to improve the energy consumption of this process is identified. It is concluded that the best CCS technology at the NGCC power plant is PCC with tertiary amine absorbent due to lower regeneration energy.

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