Multi-objective optimization of solar powered ericsson cycle using genetic algorithm and fuzzy decision making

Solar driven Ericsson heat engine has been considered for multi-objective thermodynamic optimization. Multi-objective genetic algorithm (MOGA) and finite time thermodynamic (FTT) approaches are implemented for optimization of power output and thermal efficiency which are considered as objectives in the study. Simultaneous optimization of power output and thermal efficiency are achieved using evolutionary algorithm based on MOGA. Various effectiveness of heat exchangers and temperatures of source and sink side working fluid are considered as decision variables. Pareto front between dual objectives is found in MATLAB 7.8. Further, Fuzzy Bellman-Zadeh decision making method is used to extract best optimal values of dual objective. Simultaneous optimization of power output and thermal efficiency of proposed model is obtained at optimal values of source side heat exchanger effectiveness, sink side heat exchanger effectiveness, regenerator side heat exchanger effectiveness, and source side working fluid and sink side working fluid as 0.79, 0.79, 0.88, 901 K and 436 K respectively.