Thermodynamic analysis of working fluids: What is the highest performance of the sub- and trans-critical organic Rankine cycles?

The thermodynamic performance limits of power cycles are governed not only by the first and second law of thermodynamics, but also by the cycle configuration and working fluid properties. The organic Rankine cycle (ORC) is a promising technology for low-and-medium temperature heat utilization. This work further develops the thermodynamic performance limits analysis framework of sub-and trans-critical ORCs under realistic heat source conditions, and investigates the impact mechanism of key property parameters on system performance. Working fluid thermodynamic properties are characterized using a corresponding state model with 5 property parameters that are usually available in the early stages of system design. The property and system parameters are optimized simultaneously using a multi-objective genetic algorithm. The thermodynamic performance limits, and the optimal working fluid properties and system operation conditions are identified. The obtained limits represent the highest performance of ORC. The obtained optimal property and system parameters represent the desired working fluid and system operation characteristics. The impact mechanism of key property parameters on system performance is discussed in detail in a sensitivity analysis. It is found that the critical tem-perature is the most important property parameter, and that it changes the preference over efficiency and compactness objectives. The obtained thermodynamic performance limits, optimal parameter sets, and impact mechanism provide insights for working fluid selection in ORC research and implementation. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This study further develops the analysis framework for thermodynamic performance limits of sub- and trans-critical ORCs, and determines the optimal working fluid and system operation conditions through parameter optimization. The results provide valuable insights for working fluid selection in ORC research and implementation.