Search

The increase in the PV cell temperature ultimately causes a reduction in its effectiveness. One of the new methods used to retain that efficiency is to establish a hybrid photovoltaic thermal PV/T system. In this study, PCM has been employed with a cooling nanofluid circulation system in order to the control heat capacitance of the system to maintain electrical efficiency on the one hand, and to raise the overall efficiency on the other. Nano-SiC particles were used in paraffin-PCM and nanofluid to establish higher thermal conductivities and therefore higher efficiency. The design is tested outdoors in Selangor, Malaysia. The tests were conducted using a fluid flow rate of 0.17 kg/s. The proposed system reduced the cell temperature (30 °C) at the peak solar radiation period (12:30 AM to 1:30 PM), which was reflected positively on the PV/T system performance. The proposed PV/T-nano PCM-nanofluid system increased the open circuit voltage from 11–13 V to 20–21 V, the power from 61.1 W to 120.7 W, and the electrical efficiency from 7.1% to 13.7%. Besides, the system made use of the thermal energy gained as its thermal efficiency reached 72%. These results ensure the adequate use of the new design. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • An artificial neural network model for PV/T is presented. • Discretization of parameters and equation was made. • An experiment has been conducted to validate the proposed ANN models results. • Systems using water, nanofluid and nano-PCM moving through the cooling pipes are tested. • The comparison between different models results showed a good consistent and agreement. Abstract A Photovoltaic/Thermal (PV/T) system combines PV and thermal collector, which is considered promising technology especially for building integrated PV/T system. The PV/T cooling systems using water, water-PCM and nanofluid/nano-PCM moves through the cooling pipes were investigated, in this study. However, this paper focuses on testing different PV/T systems (conventional PV, water-based PVT, water-nanofluid PVT, and nanofluid/nano-PCM) under the same conditions and environment using one artificial neural network (ANN) based Multi-Layer Perceptron (MLP) system. Also, investigate the differences in the efficiency of these systems on both thermal and electrical when using only one simulation system (MLP). The proposed ANN approach proved that using of nanofluid/nano-PCM was enhanced the electrical efficiency from 8.07% to 13.32% and its thermal efficiency reached 72%. Also, the voltage was improved significantly. Many measurement methods were used for validating the results of the proposed ANN model like the Mean Absolute Error (MAE), Mean Square Error (MSE), Correlation (R), and coefficient of determination (R2). The proposed ANN model achieved a final MSE of 0.0229 in the training phase and 0.0282 in the cross-validation phase. The sensitivity analysis showed that the influence of solar irradiation and Amb-temp almost has a constant effect on electrical efficiency. However, the Ambient temperature had a significant impact on thermal efficiency. The results of the network were consistent with the experimental results of the current study and published works. [ABSTRACT FROM AUTHOR]