Multi-parameter study and two-step optimization of the nanofluid-filtered photovoltaic/thermal systems

Abstract

Optimizing nanofluid filters and operational parameters is instrumental in enhancing the performance of nanofluid-filtered photovoltaic/thermal (PV/T) systems. However, studies on optimization of nanofluid-filtered PV/T systems have not yet been thoroughly explored. This work aims to optimize performance of nanofluid-filtered PV/T systems through a two-step procedure. Various scenarios of nanofluids tailored for specific solar cells were considered, and optimization was conducted based on the merit function (MF) to identify the most effective nanofluid filters parameters. The results showed that the optimization program tends to achieve satisfactory photovoltaic efficiency by combing a low nanoparticle concentration with a high optical path. A numerical model of the PV/T system was then developed to obtain the constraints of the operating parameters, which are used to optimize the system energy efficiency and exergy efficiency by genetic algorithm. The results demonstrated all systems present the satisfactory energy efficiency (>84 %) and exergy efficiency (>23 %). Specifically, the blended nanofluid-filtered PVSC-system achieved the highest energy efficiency of 89.45 %, while the GaAs-system with a single nanofluid filter attained the highest exergy efficiency of 27.90 %. This work contributes to advancing solar-to-PV/T efficiency, confirming the viability of blended nanofluid filters, and offering valuable insights for the development of nanofluid optical filters.