Detection of the faults in the photovoltaic array under normal and partial shading conditions

This paper propounds a novel technique for detection of the faults in photovoltaic array by using Artificial Neural Network. By using a simulation model, the power variation under different faulty conditions such as open circuit fault, short circuit fault, and bridging fault are measured under normal and partial shading conditions. The simulated attributes are given to the Artificial Neural Network to predict the type of fault occurred in or between photovoltaic modules. Finally, three different training algorithms of Artificial Neural Network are compared for fault detection with help of mean square error as the performance parameter.