Systematic analysis of additives on the performance parameters of sCO2 cycles and their individual effects on the cycle characteristics. (1st August 2022)

• Record Type: Journal Article
• Authors: Rath, Sebastian; Mickoleit, Erik; Gampe, Uwe; Breitkopf, Cornelia; Jäger, Andreas
• Is Part Of: Energy. Volume 252(2022)
• Publication Date: 2022-08-01
• Subjects: sCO2 mixtures -- Mixture modeling -- Power cycles -- Predictive fluid screening -- Supercritical CO2 -- Critical point calculations; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.123957
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Compared to existing technologies, thermodynamic cycles based on supercritical carbon dioxide (sCO2 ) are leading to higher efficiencies and reduced component sizes. However, it is possible to further improve the performance of sCO2 power cycles by using mixtures of CO2 with suitable additives, as also discussed in the literature for different applications. This work investigates the potential to optimize the characteristics of sCO2 power cycles by selectively adding different substances in varying amounts to CO2 . A new methodology is proposed: By using the reference equation of state for CO2 in combination with a multi-fluid mixture model, a theoretical screening of suitable additives was done. In the literature, studies were mainly limited to mixtures for which adjusted mixture models are available. By contrast, in this work the use of a predictive mixture model, which was recently developed at our institute, also allows to include fluids, for which no adjusted models are available. Applied to two thermodynamic cycles, changes in efficiency compared to the use of pure CO2 have been evaluated. Several promising mixture candidates have been identified. Additionally, individual effects on the cycle characteristics as well as shifts of the critical points have been investigated and are discussed. Highlights: Application of a recently developed predictive mixture model to sCO2 . Screening of 135 potential additives for two different sCO2 -cycle architectures. Potential increases in efficiency of more than 0.04 compared to the use of pure CO2 . The critical point can be shifted to higher or lower temperatures and pressures. Simple mixture models may not represent the real mixture behavior correctly.