Direct supercritical CO2 (sCO2) power cycles have received considerable attention in recent years as an efficient and potentially cost-effective method of capturing CO2 from fossil-fueled power plants. These cycles combust natural gas or syngas with oxygen in a high pressure (200–300 bar), heavily-diluted sCO2 environment, such that the fluid entering the turbine is 90–95% CO2, with the balance composed primarily of H2O, CO, O2, N2 and Ar. After recuperation of the turbine exhaust thermal energy, water is condensed from the cycle, and the remainder is recompressed for either return to the combustor or for enhanced oil recovery (EOR) or storage. The compression power requirements vary significantly, depending on the proximity of the operating conditions to the CO2 critical point (31 °C, 73.7 bar), as well as to the level of working fluid dilution by minor components. As this has a large impact on cycle and plant thermal efficiency, it is crucial to correctly capture the appropriate thermo-physical properties of these sCO2 mixtures when carrying out performance simulations of direct sCO2 power plants. These properties are also important to determining how water is removed from the cycle, and for accurate modeling of the heat exchange within the recuperator.

This paper presents a quantitative evaluation of ten different property methods that can be used for modeling direct sCO2 cycles in Aspen Plus®. REFPROP is used as the de facto standard for analyzing indirect sCO2 systems, where the closed nature of the cycle leads to a high purity CO2 working fluid. The addition of impurities due to the open nature of the direct-sCO2 cycle, however, introduces uncertainty to the REFPROP predictions. There is a limited set of mixtures available for which REFPROP can be reliably used and there are a number of species present in a coal-fired direct-fired sCO2 cycle that REFPROP cannot accommodate. Even with a relatively simplified system in which the trace components are eliminated, simulations made using REFPROP require computation times that often preclude its use in parametric studies of these cycles. Consequently, a series of comparative analyses were performed to identify the best physical property method for use in Aspen Plus® for direct-fired sCO2 cycles. These property methods are assessed against several mixture property measurements, and offer a relative comparison to the accuracy obtained with REFPROP. This study also underscores the necessity of accurate property modeling, where cycle performance predictions are shown to vary significantly with the selection of the physical property method.

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