An insight into the similarity approach to predict the maximum efficiency of organic Rankine cycle turbines
2020
Masi, Massimo | Da Lio, Luca | Lazzaretto, Andrea
This work deals with the prediction of the maximum efficiency achievable by turbines for Organic Rankine Cycle (ORC) systems by means of similarity principles. At present, this is a key topic in the preliminary design optimization procedures of these systems. The dimensional analysis applied to the most general ORC turbines scenario helps obtain the functional relationship between maximum turbine efficiency and the most relevant design variables within the general framework of the flow similarity.Aim of the work is to search for the less wide and more convenient set of independent similarity parameters to increase the accuracy of turbine efficiency data in the optimization of ORC systems.Results show that the strict flow similarity does not hold if the same design is used for different working fluids, because real gas compressibility effects cannot be disregarded for most of the fluids usually adopted in ORC systems.On the other hand, a “quasi-similarity” approach can be applied to the design of low volume expansion ratios ORC turbines using the size parameter (SP), volume expansion ratio (VR) and the compressibility factor (Z) as predictors of turbine efficiency. Accordingly, two original correlations for the SP-VR-Z map of optimized axial turbine stages are suggested.
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