<![CDATA[The electrical power output and conversion efficiency of photovoltaic (PV) systems decrease significantly due to increased thermal losses at elevated module temperatures. Unlike conventional PV/T enhancement approaches, this study integrates recycled porous media, hybrid nanofluid PCM cooling, and data-driven optimization within a unified electro-thermal framework. This work experimentally investigates and optimizes the electro-thermal performance of a PV/T renewable energy system under real climat-ic conditions of Madinah, Saudi Arabia. An extreme gradient boosting (XGBoost) machine learning model was employed to pre-dict PV/T electrical and thermal performance and identify the dominant parameters affecting power generation and system effi-ciency. Four modified PV/T configurations were developed and compared with a conventional PV unit: Al₂O₃/water nanofluid cooling, recycled copper porous media, PCM containing recycled copper fillings, and Cu/water nanofluid integrated with PCM. These configurations significantly enhance heat transfer coefficients and thermal dissipation, leading to improved electrical per-formance. The results revealed that the mean surface temperatures of PV/T@Al2O3, PV/T@Al2O3+CP, PV/T@Al2O3+CPPCM, PV/T@Cu+CPPCM were reduced by 6.05 (3.16 oC), 10.30 (5.51 oC), 15.31 (8.17 oC), 17.38% (11.98 oC) compared to standard PV, respectively. Consequently, electrical energy production increased by 7.57%, 18.85%, 27.85%, and 31.49%, respectively, compared with the standard PV unit of 610 W. The PV/T@Cu+CPPCM configuration achieved the highest electrical and thermal efficiencies of 15.90% and 24.85%, respectively, with an electrical efficiency improvement of up to 22.39%. Techno-economic analysis indi-cates significant improvements in LCOE and payback period by 136 160% and 160 181%, respectively. The XGBoost model demonstrated high predictive accuracy and robustness, confirming its capability for real-time performance prediction and sys-tem-level optimization. The results demonstrate a strong coupling between thermal regulation and electrical output enhancement, confirming the effectiveness of the proposed electro-thermal optimization strategy. The improved thermal regulation enhances PV output stability and facilitates efficient integration with power electronic interfaces, including DC-DC converters, MPPT, and in-verter-based renewable systems. This work presents a novel integrated electro-thermal optimization approach that combines hy-brid cooling techniques with data-driven modeling to maximize PV/T system performance under real operating conditions. This work presents a novel integrated electro-thermal optimization approach that combines hybrid cooling techniques with da-ta-driven modeling to maximize PV/T system performance under real operating conditions for sustainable buildings in Saudi Arabia.]]>
