Short-memory non-Fourier heat conduction PV model: stability analysis and cooling techniques

A short-memory non-Fourier model (SMNFM) is proposed to simulate the performance of a photovoltaic (PV) panel coupled with two different heat spreader (HS) designs. The proposed model employs a physically justified short-memory fractional formulation to capture transient heat transfer while overcoming the high computational cost associated with conventional long-memory fractional models. To further enhance PV thermal management, the model is integrated with a hybrid cooling strategy combining passive cooling using rectangular and trapezoidal heat spreaders with active water cooling. A finite difference numerical scheme is developed, and its stability is rigorously analyzed using the Von Neumann method for both explicit and implicit formulations. The proposed SMNFM is validated against published experimental data obtained under the hot climatic conditions of Egypt, demonstrating excellent agreement with the measured results. Compared with the classical model, the proposed approach improves prediction accuracy while reducing computational time and memory requirements. The fractional model achieves prediction errors as low as 0.175% for cell temperature and 4.7% for output power. Furthermore, the trapezoidal heat spreader combined with turbulent water cooling provides the best thermal and electrical performance, increasing the PV electrical efficiency to 11.9%. These findings demonstrate that the proposed short-memory fractional framework provides an efficient, accurate, and physically realistic approach for the thermal analysis and optimization of advanced photovoltaic cooling systems.