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The supercritical CO 2 (SC-CO 2 ) Brayton cycle has recently been gaining a lot of attention for fossil fuel power plants, nuclear reactors, and concentrated solar power applications. The current emphasis on such an innovative cycle is directed toward its economic evaluation and equipment sizing requiring process simulation and optimization. However, the rationale for choosing an appropriate thermodynamic model for supercritical CO 2 does not receive much attention. Despite the important and fundamental role played by the thermodynamic model in the process simulation and optimization, its exactness as well as its impact on machinery sizing is not yet well studied. This paper intends to present a rigorous selection procedure of an equation of state for SC-CO 2 as well as to investigate its influence on the performance and design of a SC-CO 2 Brayton cycle.

Improving the efficiency and flexibility of fossil-fired power plants remains a current and challenging issue. In that regard, supercritical CO2 Brayton cycles offer promising potential. This paper aims to apply a process synthesis approach to the design of a closed Brayton cycle using supercritical CO2 as a working fluid with a coal furnace as a heat source. The general methodology presented here for designing closed power cycles includes the construction of a superstructure containing all relevant possible cycle layouts, the formulation of the cycle-synthesis problem as a mathematical optimization problem, and its solution using an appropriate algorithm. This study was conducted with the help of a process simulation commercial software (PROSIM) and using the Mixed-Integer Distributed Ant Colony Optimization (MIDACO) as a commercial optimization algorithm. This work highlights the limits of a purely technical optimization approach that would ignore the economical layer. The optimal structure obtained regarding Levelized Cost Of Electricity (LCOE) minimization is a configuration with one reheat of the supercritical CO2 in the boiler, two recuperators, and one recompression loop around the low-temperature recuperator; it is associated with a cycle efficiency of 49.35 % and a 10% reduction in the LCOE in comparison to the optimal case found through energy optimization under typical design heuristics constraints.