The deviation of the I-V parameters predicts the type of failure of PV modules

Long-term photovoltaic (PV) modules are installed in the fields. Data processing is essential for analyzing and predicting PV module failure. The measurement current-voltage (I-V) characteristics parameters of PV modules are interesting to predict their failure that the measuring I-V data versus the nameplate data was studied, and their shows the ratio of parameters such as short circuit current (I_sc), open circuit voltage (V_oc), maximum power (P_max), current at maximum power (I_mp), voltage at maximum power (V_mp), and fill factor (FF). The I-V results were measured at the standard test condition. The ratios of each parameter show a deviation that depends on the type of failure, as shown in Figure 1. Figure 1 shows the three I-V curves compared with Electroluminescence (EL) images to confirm the I-V parameter deviation. Then, the I-V distortion data set was used to verify. Therefore, the I-V curve results can predict the failure type by reporting parameter deviation from the datasheet or first normal measurement data of each module. The decrease in the deviation ratio of Isc and shunt resistance (R_sh) is mainly caused by cell impurity/degradation. Low ratios of V_oc, I_mp, P_max, and FF are caused by potential induced degradation (PID).  The example increased the V_mp ratio of about 1.011, as shown in the figure, compared with the datasheet parameters, but the V_oc also shows fit to the datasheet as well, which is caused by cell crack in the module, as shown in the middle of Figure 1. In addition, the highly decreased ratio of P_max, I_mp, and FF indicates cells in the module failure, including failure interconnections in the module and shorting bypass diode. Thus, the PV module failure types can be predicted preliminary using this method and using only the I-V measurement parameter and datasheet.