Photovoltaic/thermal (PV/T) systems combine two collectors, which increase efficiency, reduce cost and space, and produce electricity and heat, simultaneously. Many factors affect PV/T current, voltage, power, efficiency, and heat energy production. For example, the location of the PV system, ambient temperature, irradiance, humidity, dust, and many other factors. Also, different modelling techniques are used to evaluate PV/T efficiency, for example, analytical, regression, numerical, artificial neural network (ANN). The current work aims to predict and assess a PV/T system using ANN models based on an experimental dataset in Oman. The PV/T system with weather station and data acquisition was installed in Sohar, Oman. The weather and electrical data has been recorded. A novel mathematical and ANN model for examining the performance of PV/T systems has been developed. The experimental results show improvement in PVT power production (68.6132 W) compared to the conventional PV (66.7827 W). The results demonstrate that the three proposed models (MLP, SOFM, and SVM) achieved excellent MSE results for generating the current values of the PV system (0.00043, 0.00030, 0.00041) and PV/T system (0.00719, 0.00683, 0.00763), respectively. Also, the proposed models delivered excellent MSE results for simulating the power values of the PV system (0.04457, 0.05006, 0.13816) and PV/T system (0.04457, 0.05006, 0.13816), respectively. The proposed models result validated with experimental data using descriptive statistics and Evaluation Metrics. Finally, the proposed neural models can generate future figures for any needed period that accurately fit the actual datasets.

光伏/热能 (PV/T) 系统结合了两个集热器，可提高效率、降低成本和空间，同时产生电力和热量。许多因素会影响 PV/T 电流、电压、功率、效率和热能生产。例如，光伏系统的位置、环境温度、辐照度、湿度、灰尘和许多其他因素。此外，还使用不同的建模技术来评估 PV/T 效率，例如，分析、回归、数值、人工神经网络 (ANN)。当前的工作旨在使用基于阿曼实验数据集的 ANN 模型来预测和评估 PV/T 系统。带有气象站和数据采集功能的 PV/T 系统安装在阿曼苏哈尔。天气和电气数据已被记录。已开发出一种用于检查 PV/T 系统性能的新型数学和 ANN 模型。实验结果表明，与传统 PV (66.7827 W) 相比，PVT 发电量 (68.6132 W) 有所提高。结果表明，提出的三个模型（MLP、SOFM 和 SVM）分别在生成 PV 系统（0.00043、0.00030、0.00041）和 PV/T 系统（0.00719、0.00683、0.00763）的电流值方面取得了优异的 MSE 结果. 此外，所提出的模型分别为模拟 PV 系统（0.04457、0.05006、0.13816）和 PV/T 系统（0.04457、0.05006、0.13816）的功率值提供了出色的 MSE 结果。所提出的模型结果使用描述性统计和评估指标通过实验数据进行验证。最后，