Multi-objective thermo-economic optimization of solar parabolic dish Stirling heat engine with regenerative losses using NSGA-II and decision making

The proposed work investigates optimal values of various decision variables that simultaneously optimize power output, overall thermal efficiency and thermo-economic function of solar driven Stirling heat engine with regenerative heat losses, conducting thermal bridging losses using evolutionary algorithm based on second version of non-dominated sorting genetic algorithm (NSGA-II) in matrix laboratory (MATLAB) simulink environment. Effects of design parameters as absorber temperature, concentrating ratio, radiative and convective heat transfers are considered for the investigation. Pareto frontier is obtained for triple and dual objectives and the best optimal value is selected through four different decision making techniques viz. Fuzzy Bellman-Zadeh, Shannon's entropy, LINMAP and TOPSIS. The optimum values of average absorber temperature and concentrating ratio are found to be 1168 K and 1300, respectively. Triple objective evolutionary approach applied to the proposed model gives power output, overall thermal efficiency and thermo-economic function as (38.96 kW, 0.2392, 0.3124) which are 17.09%, 35.09% and 10.74%, respectively lower in comparison with reversible system. With the objective of error investigation, the average and maximum error of the obtained results are reckoned at last.