Real-Time Detection and Classification of Bypass Diode-Related Faults in Photovoltaic Modules via Thermoelectric Devices

The accurate detection and classification of faults in photovoltaic (PV) systems contribute to enhancing their performance. Bypass diode (BD) heating is a common issue afflicting field-installed PV modules. Although different fault modes exist, they exhibit similar characteristics, which hinder their early detection and classification. Thus, a real-time fault detection and classification method for heated BDs in PV modules using thermoelectric devices (TEs) is proposed. When PV modules experience partial shading (PS) or exhibit bypass diode faults (BDFs), the temperature of the BD rises. By attaching a TE to the BD, the heat generated due to the PS or BDF can be converted into electrical energy. Additionally, the cause of bypass heating can be classified in real time by analyzing the TE's power-generation capacity, considering the inverter status and ambient conditions. For example, the power generated by the TE is in the ranges of 8.5-14.7 (PS) and 28-49.4 mW cm-2 (BDF) under operating conditions. Moreover, the power generated by the TE under the PS and BDF conditions is sufficiently high to drive a communication system, guaranteeing the reliability of the detection system. Therefore, the proposed bypass heating detection system can classify the fault modes of PV systems in real time without external power. The proposed method discussed in this paper aims to detect and classify fault modes of bypass diode in photovoltaic modules through the use of self-powered thermoelectric devices. By analyzing the heating patterns of the bypass diode, the method can effectively distinguish between bypass diode faults and partial shading without the need for any external power supply.image