Fault diagnosis method based on an output prediction model of a photovoltaic array
A fault diagnosis method was proposed based on an output prediction model of a photovoltaic(PV)module array to identify four kinds of faults on the DC side.Key points on the I-V(current-voltage)and P-V(power-voltage)curves were selected as diagnostic features,and features without faults were used as reference features.A PV array output prediction model was setup by using double-diode model of a module to predict references under different operating conditions.The photovoltaic array simulation with no faults and different faults were conducted using MATLAB/Simulink platform,and the corresponding features were compared with predicted references.In the experiment without faults,the error rate between predicted and simulated measured reference features was less than 2％under three operating conditions,indicating a good prediction accuracy for reference features by the prediction model of a PV array.The predicted values were then used as references for subsequent fault experiments.By calculating relative error for simulated measured features to references in various fault experiments,changes in features were analyzed and diagnostic methods for different types of faults were summarized.
万方数据
维普
