A generalized log-linear poisson-modeled correlation to predict the optimal heat rejection pressure of transcritical CO2 systems

Abstract

In this study, a comprehensive literature survey of all the experimental data available in literature regarding optimal heat rejection pressure on transcritical carbon dioxide systems is carried out. Based on the phenomenological analysis and quantitative assessment of the data, a Poisson regression analysis is performed and a new dimensionless correlation to predict the optimal heat rejection pressure is developed. The influences of relevant parameters on heat rejection pressure, such as ambient temperature and temperature at the gas cooler are taken into account in the correlation development. The proposed correlation is tested against experimental measurements and is further validated by comparison to all existing experimental data collected from literature. Additionally, the predictive ability of the newly proposed correlation is discussed, tested against experimental data found in literature and compared with existing correlations. Upon comparison with existing correlations, the new generalized dimensionless correlation proposed in this study predicts the optimal heat rejection pressure with an average deviation of 1.31% and a standard deviation of 4.26 bar. Thus, becoming the most accurate correlation up to date, yet providing a much wider range of temperature applicability than the correlations currently available in literature.