Performance Prediction and Optimization of Nanofluid-Based PV/T Using Numerical Simulation and Response Surface Methodology

Sreehari Sreekumar; Supriya Chakrabarti; Neil Hewitt; Jayanta Deb Mondol; Nikhilkumar Shah

doi:10.3390/nano14090774

Performance Prediction and Optimization of Nanofluid-Based PV/T Using Numerical Simulation and Response Surface Methodology

Nanomaterials (Basel). 2024 Apr 28;14(9):774. doi: 10.3390/nano14090774.

Authors

Sreehari Sreekumar¹, Supriya Chakrabarti², Neil Hewitt¹, Jayanta Deb Mondol¹, Nikhilkumar Shah¹

Affiliations

¹ Centre for Sustainable Technologies (CST), Belfast School of Architecture and the Built Environment, Ulster University, Belfast BT15 1ED, Northern Ireland, UK.
² Nanotechnology and Integrated Bio-Engineering Centre (NIBEC), Ulster University, Belfast BT15 1ED, Northern Ireland, UK.

Abstract

A numerical investigation was carried out in ANSYS Fluent^® on a photovoltaic/thermal (PV/T) system with MXene/water nanofluid as heat transfer fluid (HTF). The interaction of different operating parameters (nanofluid mass fraction, mass flow rate, inlet temperature and incident radiation) on the output response of the system (thermal efficiency, electrical efficiency, thermal exergy efficiency, and electrical exergy efficiency) was studied using a predictive model generated using response surface methodology (RSM). The analysis of variance (ANOVA) method was used to evaluate the significance of input parameters affecting the energy and exergy efficiencies of the nanofluid-based PV/T system. The nanofluid mass flow rate was discovered to be having an impact on the thermal efficiency of the system. Electrical efficiency, thermal exergy efficiency, and electrical exergy efficiency were found to be greatly influenced by incident solar radiation. The percentage contribution of each factor on the output response was calculated. Input variables were optimized using the desirability function to maximize energy and exergy efficiency. The developed statistical model generated an optimum value for the mass flow rate (71.84 kgh^-1), the mass fraction (0.2 wt%), incident radiation (581 Wm^-2), and inlet temperature (20 °C). The highest overall energy and exergy efficiency predicted by the model were 81.67% and 18.6%, respectively.

Keywords: ANOVA; CFD; nanofluid; optimization; response surface method.

Grants and funding

The authors would like to thank the support provided by Ulster University through PhD studentship funding from the Northern Ireland Department for the Economy. The financial support for this research by the Built Environment Research Institute (BERI), Ulster University, is deeply acknowledged. This research received no external funding.