Thermodynamic and exergoeconomic analysis of a novel solar-assisted multigenerational system utilizing high temperature phase change material and hybrid nanofluid

[Display omitted] •Development & exergoeconomic analysis of hybrid nanofluid multigeneration system.•Electricity, hydrogen, fresh water and cooling effect are the desired outputs.•Utilization of PCM (Li2CO3-Na2CO3) to meet energy demands at nighttime.•LEC of system is 0.1387 $/kWh with PCM, while 0.354 $/kWh without PCM.•System-integrated energy & exergy efficiencies are 31.59% and 30.02%, respectively. The goal of this article is to propose and analyze a novel solar driven multigenerational system producing electricity, cooling, hydrogen and fresh water. The system consists of parabolic dish collector with hybrid nanofluids, re-compression sCO2 Brayton cycle, proton exchange membrane (PEM) electrolyzer, desalination unit and double effect lithium-bromide/water absorption cycle. To achieve high system performance and to meet the energy demand in the absence of solar flux, a thermal energy storage system has been used having high temperature phase change material (PCM). This system is able to continue system operation after the sunset and also ensure the stable fluid temperature at the turbine inlet. The performance of the proposed system is assessed by varying the different input parameters such as; inlet temperature, mass flow rate, direct normal irradiation (DNI), wind speed and turbine inlet temperature (TIT). In addition to the energy and exergy analysis, exergoeconomic approach is used to calculate the cost rate and exergo-economic factor of all the components of the integrated system. The results indicate that the overall energy and exergy efficiencies of the proposed system are 31.59% and 30.02%, respectively; while production of fresh water and cooling load are 1.564 kg/s and 196.1 kW, respectively. The exergoeconomic results show that Levelised cost of electricity and total cost rate of exergy destruction are 0.1387 $/kWh and 530 $/hr., respectively with payback period of 9.5 years. Moreover, single- and multi-objective optimizations are carried out to determine the optimal design using a genetic algorithm method in EES (engineering equation solver). Total cost rate and overall exergy efficiency are the two desired objectives to be optimized.