An intelligent Fault Diagnosis Method Based on Neural Networks for Photovoltaic System

In this paper we propose an intelligent method to detect fault diagnosis in the photovoltaic (PV) systems by applied the artificial neural network (ANN). Firstly, the temperature of the PV module is used to locate the fault in the PV system, and usually there is an obvious temperature difference between the fault and normal PV module. The current and voltage of the maximum power point tracking (MPPT) and the temperature of the PV modules are the input parameters of the ANN, and the output is the result of the fault detection. The simulation result under both normal and fault conditions show that the outputs of the ANN are almost consistent with the expected value, and the proposed fault diagnosis method can not only detect and find the location of the fault and determine the type of the fault rapidly and accurately.