Multi-objective optimization of parameters affecting Organic Rankine cycle performance characteristics with Taguchi-grey relational analysis

Abstract

In the literature, energetic and exergetic performance of Organic Rankine Cycle (ORC) were investigated by various researchers. The working parameters affecting the cycle's performance were determined but the impact weights and the order of importance of these parameters were not discussed with a statistical approach. In this context, nine fundamental process parameters such as working fluid type, pinch point temperature differences in the evaporator and condenser, superheating temperature, evaporation and condensation temperatures, heat exchanger effectiveness, turbine and pump efficiencies have been selected for the statistical evaluation. A comprehensive statistical analysis has been carried out to observe the effect of the parameters on the first and second law efficiencies of the ORC. The impact ratios and order of importance of these parameters on the system's performance indicators have been determined. While Taguchi method is performed to determine the optimum levels of each parameter, ANOVA method is used to obtain the impact weights of the parameters on objective functions. In addition to these methods, Grey Relational Analysis (GRA) method is used to optimize the multi-objective function. Evaporator temperature, turbine efficiency, effectiveness of heat exchanger, condenser temperature are obtained as main process parameters on the multiple performance characteristics of ORC and the impact ratios of these parameters are calculated as 31.37%, 19.53%, 16.64%, and 16.61%, respectively. The best condition for the multiple performance characteristics is determined as A(1)B(1)C(3)D(3)E(3)F(3)G(1)H(3)I(3) and under these operating conditions, the first and second law efficiencies of the system are found as 18.1% and 65.52%, respectively.