[Objective

]

Oxy-fuel combustion technology is a critical pathway for achieving near-zero emission from coal-fired power generation

yet its high energy consumption from auxiliary systems constrains economic viability. Integrating an S-CO

2

Brayton cycle can improve efficiency

but existing optimization studies predominantly rely on single-factor analyses

failing to capture complex parameter interactions. This study addresses this gap by developing a thermodynamic model and employing a multi-factor optimization framework to quantitatively analyze the individual and interactive effects of key parameters

thereby optimizing system performance. [Methods

]

A detailed thermodynamic model of an S-CO

2

Brayton cycle integrated with an

oxy-fuel coal-fired power plant was developed. To systematically investigate the multi-parameter design space

response surface methodology(RSM) was employed. Using a central composite design(CCD) within the Design-Expert software platform

a structured simulation plan was executed. Four key operational parameters were selected as independent variables: the economizer bypass ratio

the primary dry cycle flue gas proportion

the high-pressure turbine inlet pressure

and the cold primary air temperature. The system's net electrical efficiency and exergy efficiency were defined as the primary performance responses. Based on the simulation data

multi-factor quadratic regression models were constructed. These explicit mathematical models enabled a rigorous quantitative analysis to determine the main effect(individual influence) of each parameter and

crucially

to evaluate the significance and nature of the twofactor interaction effects between them. [Results

]

The analysis yielded clear quantitative insights. The hierarchy of influence for the four parameters on both net electrical efficiency and exergy efficiency was definitively established as: primary dry cycle flue gas proportion cold primary air temperature economizer bypass ratio high-pressure turbine inlet pressure. More importantly

the interaction effect analysis revealed significant coupling between parameters. For optimizing net electrical efficiency

the most pronounced interactions were between the economizer bypass ratio and the primary dry cycle flue gas proportion

and between the high-pressure turbine inlet pressure and the cold primary air temperature. For exergy efficiency

the interaction between the high-pressure turbine inlet pressure and the cold primary air temperature was identified as the most significant. [Conclusion

]

This research confirms that the S-CO

2

Brayton cycle can effectively mitigate the efficiency penalty associated with oxy-fuel carbon capture. By moving beyond conventional single-factor analysis

the application of R

esponse Surface Methodology successfully quantified the complex interdependencies governing system performance. The study thus delivers a clear

multi-stage optimization pathway and robust theoretical support for the design of high-efficiency S-CO

2

Brayton cycle oxy-fuel power generation systems.