Determination of sensitivity and contribution ratios of parameters affecting organic Rankine cycle efficiency with multivariant optimization

In this study, the sensitivity levels and contribution rates of the performance parameters that have an effect on the Organic Rankine Cycle (ORC) were determined. Performance parameters were chosen as evaporator-condenser pinch point temperature difference (Delta T-pp,T-e,Delta T-pp,T-k), cooling water inlet temperature (T-c,T-l), superheating temperature (T-ak), turbine-pump isentropic efficiencies (eta(t) ve eta(p)). The effects of these parameters on the ORC system were evaluated under different objective functions. Examined objective functions; thermal efficiency, net power, and exergy efficiency maximization; total irreversibility, volumetric flow rate (VFR) and environmental impact factor (EEF) minimization. Thus, thermodynamic performance with energy-exergy analysis; VFR, which has a significant impact on turbine economy; thermodynamic sustainability indices and environmental factor were examined. It has been determined that the effect of performance parameters varies greatly with the change of objective functions. While the effect of Delta T-pp,T-e was 20.59% effective in obtaining maximum thermal efficiency, it was determined that it was 71.9% effective in obtaining maximum turbine power. Taguchi-ANOVA was used in the study. By using the L25 orthogonal array, the optimum orthogonal arrays and the sensitivity level order of the parameters have been determined to reach the objective functions. By defining a weight function that affects all objective functions equally, it was determined that 42.85% Delta T-pp,T-e and 25.71% T-c,T-t had an effect on ORC performance. Finally; with regression analysis, equations are derived for each objective function depending on the performance parameters. The error rates between the results estimated by the empirical equation and the numerical analysis results were extracted. Considering these ratios, it has been determined that empirical equations can be used successfully in determining ORC performance..