Multi-objective design optimization of a solar based system for electricity, cooling, and hydrogen production.

Abstract In this research paper, a novel solar-based integrated energy system with a thermoelectric generator (TEG) is proposed to provide cooling and hydrogen production. The energy integration is performed by establishing a TEG unit instead of the condenser of the double effect LiBr-H 2 O absorption cooling system. The proposed system is comprehensively investigated and compared with the conventional cogeneration system from energy, exergy, and exergoeconomic point of view. To enhance the understanding of the effect of major design parameters on system exergy efficiency, net output work, total cost rate and hydrogen production, a comprehensive parametric study is carried out. In addition, using a developed MATLAB code, multi-objective optimization method based on genetic algorithm is applied to optimize the proposed model and determine the optimal design parameters. The results of exergy and exergoeconomic analysis show that PVT has the highest exergy destruction rate and the cooling set has the lowest exergoeconomic factor. Results of the parametric study indicate that the proposed system with TEG has higher exergy efficiency, higher hydrogen production rate, lower total cost rate, and lower pay back period. Multi-objective optimization results show that, at the optimum point, exergy efficiency and total cost rate of the proposed system are 12.01% and 0.1762 $/h, respectively. Examining scatter distribution, further shows that the high-pressure generator temperature and PV module area are the most sensitive parameters and should be kept at their lowest value. Higher performance indicators and lower economic indicants reveal that the proposed integration method is more suitable from the exergy/exergoeconomic standpoints. Highlights • Developing a new solar based integrated system with thermoelectric generator. • A newly proposed system to provide electricity, cooling and hydrogen. • Comparing performance of the newly proposed model to the condenser based model. • Applying a Multi-objective optimization to determine the optimal parameters. [ABSTRACT FROM AUTHOR]