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

Research output: Contribution to journalArticlepeer-review

5 Downloads (Pure)

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.
Original languageEnglish
Article number774
Pages (from-to)1-26
Number of pages26
JournalNanomaterials
Volume14
Issue number9
DOIs
Publication statusPublished (in print/issue) - 28 Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Data Access Statement

All data is available in the manuscript.

Keywords

  • nanofluid
  • CFD
  • response surface method
  • ANOVA
  • optimization

Fingerprint

Dive into the research topics of 'Performance Prediction and Optimization of Nanofluid-Based PV/T Using Numerical Simulation and Response Surface Methodology'. Together they form a unique fingerprint.

Cite this