| Summary: | Population and economic growth, industrial activities, development of technology, and depletion of fossil fuels have all led to increasing energy demand. As a result, there is an increasing ambition towards implementation of sustainable energy sources. In this study, first, a review of the literature is conducted to learn about various methods and objectives for optimization of photovoltaic and thermal (PV/T) systems. Then, a case study is considered, and the seasonal and hourly solar radiation are studied. Further, two methods of multiobjective evolutionary algorithm based on decomposition (MOEA/D) and multiobjective particle swarm optimization (MOPSO) are compared. On this basis, the energy and exergy efficiencies are analyzed for a proposed PV/T system. The outcomes are validated by taking into account the previous studies, and a sufficient agreement is found indicating the validity and accuracy of the results. It is also found that the efficiency rates for both energy and exergy soar with a rise in the ambient temperature. Additionally, a growth in the warm water flow rate from 0.4 to 1 kg/s increases the exergy efficiency by 0.6%. It is concluded that the MOEA/D method outperforms the MOPSO in terms of the optimization of the proposed PV/T system.
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