Cooling PV cells is an important requirement to prevent any loss performance of PV cell and any reduction of their lifespan. Therefore, using nanofluid as working fluid in a PVT collector has become attractive due to the significant improvement in heat transfer properties as compared to conventional fluids. For the first time, this work introduces a novel statistical model by applying the response surface methodology (RSM) method to examine the electrical and thermal efficiencies of behavior of a nanofluid photovoltaic thermal (PVT) collector. The developed statistical model correlates the efficiencies of the solar collector with the operational parameters, including the heat transfer coefficient by conduction between the PV module and the absorber plate, the mass flow rate, the concentration of Zinc oxide (ZnO) nanoparticles and the tubes number. An excellent correlation is achieved between the foretold results derived from the statistical model and numerical simulation of the heat transfer model. The coefficient of determination (R²) for thermal and electrical efficiencies are 0.9888 and 0.9908, respectively. The outcomes show that the heat transfer coefficient by conduction between the PV and the absorber, the mass flow rate are notable factors compared to concentration of ZnO nanoparticles and the tube number.

冷却PV电池是防止PV电池性能下降和寿命缩短的重​​要要求。因此，与常规流体相比，由于传热性能的显着改善，在PVT收集器中使用纳米流体作为工作流体已变得具有吸引力。这项工作首次通过应用响应表面方法（RSM）方法来检查纳米流体光伏热（PVT）收集器的行为的电效率和热效率，引入了一种新颖的统计模型。开发的统计模型将太阳能集热器的效率与运行参数相关联，这些参数包括PV模块与吸收板之间的热传导系数，质量流量，氧化锌（ZnO）纳米颗粒的浓度以及管数。从统计模型得出的预测结果与传热模型的数值模拟之间实现了极好的相关性。测定系数（R²）的热效率和电效率分别为0.9888和0.9908。结果表明，与ZnO纳米颗粒的浓度和管数相比，PV和吸收器之间的热传导系数，质量流量是显着的因素。