A theoretical expression on performances of transcritical power cycle with the pseudocritical temperature prediction of working fluid

Abstract

As a representative energy conversion technology of medium and low grade heat source, organic Rankine cycle (ORC) has attracted much attention. Compared with the cycle performance calculation from REFPROP, a theoretical expression can conveniently and quickly predict the cycle performance. Although there exist various theoretical equations to predict the performances of subcritical ORC, few expressions have been proposed for the transcritical cycle. Thus, in this study, based on the pseudocritical temperature of working fluid, a theoretical equation is proposed to predict the performance of the transcritical power cycle. For the required pseudocritical temperature, an artificial neural network (ANN) model is developed to obtain the reduced value (Tpr) from the reduced pressure (Pr), molar mass (M) and critical compressibility factor (Zc), based on the generated 30,670 data of 93 working fluids. From the obtained results, it can be concluded that the developed ANN has the absolute average relative deviation (AARD) 0.44% for the prediction of pseudocritical temperature. For the cycle performance prediction of the proposed expression, when the cycle condition is closer to the critical region of working fluids, the prediction accuracy is lower. Compared with the dry and wet fluids, the isentropic fluid generally has lower deviations of thermal efficiency and net work. Furthermore, for any working fluid, deviations of cycle performances are lower than 10% in the typical ranges of cycle conditions. Meanwhile, the average AARDs of cycle efficiency and net work are 4.93% and 6.36%, respectively. Based on the developed theoretical expression, cycle performance of transcritical cycle can be accurately and quickly predicted for any working fluid.