Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review

The rapid development of photovoltaic (PV) technology and the growing number size PV power plants require increasingly efficient intelligent health monitoring strategies to ensure reliable operation high energy availability. Among various techniques, Artificial Neural Network (ANN) has exhibited functional capacity perform identification classification faults. In present review, a systematic study on application ANN hybridized models for fault detection diagnosis (FDD) is conducted. For each application, targeted faults, detectable type amount data used, model configuration FDD performance are extracted, analyzed. main trends, challenges prospects extracted presented.