Thermo-economic multi-objective optimization for a solar-dish Brayton system using NSGA-II and decision making

摘要: Abstract A 100 kW regenerative Brayton heat engine driven by the hybrid of fossil fuel and solar energy was considered for optimization based on multiple criteria. thermodynamic model such system developed so that power output, thermal efficiency dimensionless thermo-economic performance with imperfect parabolic dish collector, external irreversibility conductive bridging loss could be obtained. Evolutionary algorithm NSGA-II (Elitist Non-dominated Sorting Genetic Algorithm) employed to optimize triple-objective dual-objective functions, where temperatures hot reservoir, cold reservoir working fluid, effectiveness hot-side exchanger, cold-side exchanger regenerator were as design variables. Using decision makings, including Shannon Entropy, LINMAP TOPSIS methods, final optimal solutions selected from Pareto frontier obtained NSGA-II. The results show there exists an appropriate fluid temperature cause solution under each given condition. comparisons single-objective indicate multi-objective can yield more suitable due lower deviation index ideal solution. In analysis optimization, expected result is values out, solar-dish (68.65 kW, 0.2331 0.3077) are 22.6%, 34.9% 18.4% respectively less than convectional engine. Finally, a range functional relationship between optimized objectives in fitted provide detailed insight into system.