A detailed mathematical model and experimental validation for coupled thermal and electrical performance of a photovoltaic (PV) module

Abstract

Photovoltaic (PV) performance fluctuates greatly due to varying meteorological, physical, and operational conditions. Therefore, there is a need to develop accurate predictions without unjust simplification of how it will perform in real conditions. In this paper, a detailed mathematical model was developed to determine the thermal and electrical parameters of a PV module under transient conditions. The model simultaneously solved a thermal model based on thermal resistance circuit and an electrical model based on an equivalent electrical circuit. In order to evaluate the proposed model in a wider way, the experimental validation was made by taking into account different meteorological conditions. The root mean square error (RMSE) and mean bias error (MBE) values of the solar cell temperature for a winter day were 1.341 ℃ and 1.916%, respectively. For a summer day, these values were 1.296 ℃ and 0.855%, respectively. The RMSE and MBE values of the power output for a winter day were 5.094 W and −0.022%, respectively. For a summer day, these values were 3.913 W and −2.499%, respectively. Experimental validation showed that the errors in the proposed model were within an acceptable level. The model was then implemented to investigate the distribution of thermal resistance in the PV module. The results show that the radiative thermal resistance for the winter and summer days is 80.3% and 70.7% of the total thermal resistance, which includes conduction, convection, and radiation, respectively, while the conductive thermal resistance has a negligible effect on the total resistance. A long-term evaluation of the model was used to examine the highest temperatures and electrical power output that the PV module can reach in various weather conditions. According to the findings, the wind speed was not dominant in effecting the cell temperature compared to the solar radiation and ambient temperature. As the intensity of solar radiation got higher, less electrical power was produced than its capacity due to an increased cell temperature. Finally, it was compared with previous models in the relevant literature to investigate the effect of different approaches. Accordingly, it is revealed that the proposed model provides a significant improvement in both the cell temperature and power output prediction.