A fast MPPT-based anomaly detection and accurate fault diagnosis technique for PV arrays

Catastrophic faults in photovoltaic (PV) arrays, if not detected timely, will significantly reduce the output power and even cause fire risks. Thus, fast and accurate fault detection and diagnosis techniques are of importance to enhance the efficiency, reliability, and safety of PV systems. However, conventional methods fail to detect faults at low mismatch levels and low irradiance levels. In this paper, a sensorless detection technique is thus proposed based on the instantaneous current reduction between two maximum power point tracking (MPPT) sampling instants. Simulations have been conducted to validate its availability to identify anomalies under varying environments, irrespective of the mismatch and irradiance levels. The results clearly demonstrate that the proposed method is less time-consuming but more accurate than the existing techniques. However, due to the presence of blocking diodes, the similarity between faults and certain partial shading (PS) conditions will make them more difficult to be classified. Hence, a unique point on the current–voltage (I-V) curve, namely inflection point, is exploited to accurately distinguish PS conditions, and further determine the mismatch level. More simulation tests under different conditions reveal that the proposed method is effective to quantitatively evaluate the faults. Accordingly, different voltages can be set to differentiate the currents in the faulty string and normal ones as much as possible for efficient fault location.