Sensitivity analysis and optimization of modified CO2CPU process using response surface methodology

Today, the CO2 emission from the combustion of fossil fuels is recognized as one of the main causes of global warming and its consequent problems. Oxy-fuel combustion (OFC) is an effective way to separate CO2 from combustion flue gas. CO2 Compression and Purification Unit (CO2CPU) is a relatively new industrial unit for the separation of CO2 from the combustion gas produced by OFC process. However, the high energy required for the compression and refrigeration process is one of the main challenges of this unit. Therefore, identification and sensitivity analysis of the parameters affecting the process are needed for appropriate optimization and control of these parameters. The present study, while introducing this unit, aimed at sensitivity analysis, optimization and improvement of the process. The process was simulated in the Aspen Plus environment. In addition, Peng-Robinson thermodynamic equation of state was applied to estimate the thermodynamic properties and it was improved using the data ​​in the literatures to increase the accuracy of the thermodynamic coefficients. Given that the interaction of operational parameters is effective on the optimization results, the response surface methodology (RSM) was employed for optimization. The results of this study show that the process can be performed at 25 bar pressure by improving the operating conditions, while the operating pressure of this process was previously reported to be 30 bar. Obviously, reducing operating pressure decreases not only the operating costs but also the investment costs and thus, the total costs.