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

Area of Science:

• Renewable Energy Systems
• Nanofluids
• Heat Transfer

Background:

• Photovoltaic/thermal (PV/T) systems offer combined electricity and heat generation.
• MXene/water nanofluids show promise as advanced heat transfer fluids (HTFs) for PV/T systems.
• Optimizing operating parameters is crucial for maximizing PV/T system efficiency.

Purpose of the Study:

• To numerically investigate the performance of a PV/T system using MXene/water nanofluid.
• To analyze the impact of operating parameters on thermal, electrical, and exergy efficiencies.
• To optimize the system for maximum energy and exergy efficiency using response surface methodology.

Main Methods:

• Numerical simulation using ANSYS Fluent^®.
• Development of a predictive model using response surface methodology (RSM).
• Analysis of Variance (ANOVA) to determine parameter significance.

Main Results:

• Nanofluid mass flow rate significantly impacts thermal efficiency.
• Incident solar radiation greatly influences electrical efficiency and exergy efficiencies.
• Optimized parameters include mass flow rate (71.84 kgh^-1), mass fraction (0.2 wt%), incident radiation (581 Wm^-2), and inlet temperature (20 °C).

Conclusions:

• The study successfully optimized a PV/T system with MXene/water nanofluid.
• Maximum predicted overall energy efficiency reached 81.67%, and exergy efficiency reached 18.6%.
• The developed model provides a valuable tool for designing and enhancing similar PV/T systems.