An empirical correlation of ambient temperature impact on PV module considering natural convection

Abstract

<p><span>In this paper, the effect of the ambient temperature on the PV modules for different angles of inclinations and different intensities of the solar radiation on the surface of the PV module is considered by using empirical correlations for natural convection. An analytical model based on the energy balance equilibrium between the PV module and the environment conditions has been used. Also an expression for calculating the electric power of silicon PV modules in a function of the ambient temperature, the intensity of the solar radiation, the incident angle of the solar radiation to the surface of the PV module and the efficiency of the PV modules at STC conditions have been used. By comparing the obtained both results, it can be seen that the largest deviation between the power values obtained by the analytical model and expression is about (5 %). The results obtained indicates that in the case of a small number of PV modules corresponding to the required number for an average household, it is more economical to invest additional resources in increasing the PV module's surface area than in case of the PV module with sun tracking system. </span></p>

Fault classification and detection for photovoltaic plants using machine learning algorithms

“…Some of the measures are discussed in [20], [24] which are utilized in detecting and classifying faults in the grid-connected PV systems such as wind speed, output voltage, total irradiance, wind direction, current of every PV array, ambient temperature, energy, and output power of every PV array [25]. These variables provide the foundation for evaluating the performance of the plant in real-time and improving system dependability, as described in [24].…”