Modeling of organic Rankine cycle systems using Engineering Equation Solver: A review

The organic Rankine cycle (ORC) is widely applied to convert low-temperature heat sources into useful power. Engineering Equation Solver (EES) is one of the most frequently used tools for ORC thermodynamic modeling, parametric analysis, optimization, and energy, exergy, economic, and environmental (4E) assessment. While numerous reviews address ORC systems in general, a focused evaluation of how EES is implemented in ORC research remains lacking. This study reviews ORC studies conducted using EES to clarify its modeling capabilities, identify recurring methodological limitations, and synthesize best practices for future research. The recent literature is analyzed with respect to ORC thermodynamic modeling strategies, component modeling approaches, working fluid selection, operating-condition analysis, optimization methods, and application domains, including renewable energy systems, waste heat recovery, and multi-generation ORC configurations. The results indicate that most studies rely on steady-state energy and exergy analyses, particularly for working fluid selection and operating-condition optimization. However, recurring shortcomings include oversimplified component models, unrealistic assumptions, neglect of environmental and safety criteria in working fluid selection, treatment of heat sources as constant, limited environmental and economic assessments, and insufficient experimental validation, especially for advanced systems. The study concludes that future EES-based ORC research should incorporate practical design constraints, expand evaluation metrics beyond energy and exergy efficiencies, strengthen experimental validation and uncertainty analysis, integrate environmental and safety considerations, and link EES with external tools for transient modeling, optimization, prediction, and control. A simple ORC model implemented in EES is presented to demonstrate its application. The review also integrates cross-comparative, chronological, and economic analyses to clarify the evolution, methodological positioning, and practical relevance of EES-based ORC research. In addition, a standardized reporting framework is recommended to improve transparency, reproducibility, and comparability. • Reviews organic Rankine cycle (ORC) studies implemented in Engineering Equation Solver (EES) and maps research trends. • Identifies recurring EES modeling limitations in component fidelity, assumptions, and validation. • Synthesizes best practices for working fluids, operating conditions, optimization, and 4E evaluation. • Provides an EES demonstration ORC model to clarify cycle-level implementation and reporting. • Proposes a standardized reporting framework to improve transparency and reproducibility.