Energetic, exergetic, and entropy generation prediction and optimization of photovoltaic thermal system integrated hexagonal boron nitride-water nanofluid - Nurhanis Sofiah, Abd Ghafar; Kumar Pandey, Adarsh Kumar; Rajamony, Reji Kumar; Samykano, Mahendran; Pasupuleti, Jagadeesh; Nur Fatin, Sulaiman; Saidur, Rahman Md (Elsevier Ltd, 2025)
This study investigates the performance and optimization of a photovoltaic thermal (PVT) system integrated with hexagonal boron nitride-water (hBN-water) nanofluid using a central composite design (CCD) of the response surface method (RSM). The research focuses on optimizing mass flow rate and irradiance to enhance electrical efficiency, thermal efficiency, electrical exergy efficiency, thermal exergy efficiency, and minimize entropy generation. ANOVA tables demonstrate the statistical significance of variables and their interactions, with high R-squared values of 98.27 %, 99.51 %, 99.86 %, 97.34 %, and 100 %, respectively, confirming the model's robustness. The actual vs. predicted graph aligns closely along the 45° line, and the residual vs. predicted plot shows a random distribution of residuals, indicating reliable predictive performance and model resilience. The optimization results estimate an electrical efficiency of 7.72 % at a mass flow rate of 1.18 L/m and irradiance of 444.44 W/m2. Single-objective optimizations predict maximum thermal efficiency of 73.84 % at 0.63 L/m and 481.94 W/m2, maximum electrical exergy efficiency of 8.92 % at 0.62 L/m and 444.44 W/m2, maximum thermal exergy efficiency of 1.83 % at 0.84 L/m and 682.23 W/m2, and minimized entropy generation of 1.6 at 1.18 L/m and 444.44 W/m2. The ramp function plot for multi-objective optimization reveals the best overall performance at a mass flow rate of 0.62 L/m and irradiance of 492.22 W/m2, achieving electrical efficiency of 7.43 %, thermal efficiency of 73.82 %, electrical exergy efficiency of 8.56 %, thermal exergy efficiency of 1.21 %, and minimized entropy generation of 1.57. These research study aim to enhance the understanding, efficiency, and broader adoption of PVT technologies integrated with nanofluids, contributing to more sustainable renewable energy solutions.