Techno-economic, techno-environmental assessments, and deep learning optimization of an integrated system for CO2 capturing from a gas turbine: Tehran case study

Abstract

This study investigates methods to reduce heat losses, CO2 emissions, and improve the overall efficiency of micro gas turbine power plants, considering economic viability as gas turbines are a major component of the global energy supply chain. Heat recovery and carbon capture techniques were employed to achieve these goals. First, a steam Rankine cycle and a greenhouse were designed to integrate with an existing micro gas turbine. Second, the entire system was simulated using thermodynamic, economic, and environmental models. Finally, an optimization process was conducted through a machine learning model using the integrated model. By adding a Rankine cycle, 80% of the heat losses in a traditional power plant were recovered, converted into electricity and cooling, and resulted in a 3% efficiency improvement. Additionally, implementing a CO2 separation and capture unit with utilization in a nearby greenhouse not only enhanced greenhouse profitability but also significantly reduced CO2 emissions into the atmosphere. While the system's cost rate increased by $40/hour, the investment payback period is only 0.97 years. Furthermore, CO2 emission rate was reduced by 15%.