| description abstract | The successful penetration of supercritical carbon dioxide (sCO2) power systems in the energy market largely depends on the achievable turbomachinery efficiencies. The present study illustrates a systematic framework where both the compressor and the turbine are designed via validated (within ±2% pts against experiments) mean-line tools, and the subsequent impact on cycle performance estimates is quantitatively and qualitatively assessed. A significant effort is devoted to the analysis of centrifugal compressors that operate close to the thermodynamic critical point, where sharp variations in the thermodynamic properties may make the compression process critical. The analysis is performed for different compressor sizes and pressure ratios, showing a comparatively small contribution of the compressor-intake fluid conditions to the machine efficiency, which may achieve competitive values (82–85%) for representative full-scale sizes. Two polynomial correlations for both the turbomachinery efficiencies are devised as a function of proper similarity parameters accounting for machine sizes and loading. Such correlations can be easily embedded in power cycle optimizations, which are usually carried out assuming constant turbomachinery efficiencies, thus ignoring the effects of plant size and cycle operating parameters. Efficiency correlations are finally exploited to perform several optimizations of a representative recompression sCO2 cycle, by varying multiple cycle parameters, namely maximum and minimum temperature, pressure ratio, and net power output. The results highlight that the replacement of the constant-efficiency assumption with the proposed correlations leads to more accurate performance predictions (e.g., cycle efficiency can differ by more than 4% pts), besides demonstrating that an optimal pressure ratio exists in the range 2–5 for all the investigated configurations. | |
