Photovoltaic Faults Prediction by Neural Networks

Solar energy is one of the most important forms of renewable energy. The most significant method of converting solar energy is photovoltaic (PV) systems. Fault diagnosis is crucial for the dependable and efficient operation of PV systems. Early fault detection and diagnosis can save maintenance costs, avoid or minimise system downtime, and generally improve system performance. Artificial neural networks, a key artificial intelligence methodology, have been developed and applied in a variety of fields, including the fault diagnosis of PV systems, because of their robust self-learning capability, outstanding generalisation performance, and high fault tolerance. This study shows how artificial neural networks (ANN) can be used to predict solar panel problems.