Electrical and thermal analyses of solar PV module by considering realistic working conditions

Photovoltaic (PV) cells are used as clean energy technologies for generating electricity from solar irradiance. In designing and modeling of PV-based energy systems, it is crucial to consider their efficiency and the factors influencing it. Among the effective factors on the cell efficiency, temperature is very crucial. Ambient temperature, speed of wind and solar irradiance are among the most significant parameters which influence the cell temperature and its electrical output. In this regard, computation fluid dynamics is employed in the current study for determining cell temperature under different operating conditions. In order to achieve more realistic and accurate solution, the cell efficiency in the model is considered as a temperature-dependent variable. On the basis of determined temperatures by the model at high wind speed, ambient temperature impact on the cell performance becomes more remarkable. Finally, the outputs of numerical simulation are applied in an artificial neural network (GMDH type) to propose a predictive and simple-to-use model. The proposed model has reliable performance, and its maximum relative deviation does not exceed 0.04%. Employing the proposed model instead of computational fluid dynamic for predicting the PV performance will result in saving time. Moreover, using the ANN-based model is more cost-effective compared with experimental evaluation of PV efficiency.