A Robust Method for Diagnosis and Localization of Faults in Photovoltaic Panel Strings and Bypass Diodes

This paper proposes a novel approach for systematically diagnosing and locating faulty strings and bypass diodes within PV panels. It is essential to address this issue to ensure the efficient operation of PV panels and promptly diagnose defective strings under various faults. This is achieved through the detection and pinpointing of subjected defects in PV strings(s) and bypass diodes within the PV panel. Therefore, this paper demonstrates a real-time detection and localization methodology using an Internet of Things (IoT) infrastructure using microcontroller and sensor technologies to successfully locate subjected faults on individual string(s) and faulty diodes. This is achieved through the analysis of I-V and P-V characteristics of given PV panels, along with the individual current of the bypass diodes. This methodology enables the detection of the given diode state, which enables locating the faulty string and diode. In this notion, the proposed methodology observed a PV panel efficiency of 10.71% and 4.6% under non-faulty and large-fault conditions, respectively. Moreover, the IoT infrastructure rapidly responds to fault detection in an average of <5 seconds, leading to a 100% accuracy in locating the faulty diode or string. Therefore, this methodology paves the way for implementation in large PV power plants to maintain possible faults subjected to PV panels regularly.