Module-Level Fault Diagnosis of Photovoltaic Array based on Wireless Sensor Networks and Inverter Activated I-V Scanning

Abstract

Photovoltaic (PV) technology has become a promising renewable energy in the recent decade. The intelligent operation and maintenance of PV system is one of the hottest research issues in PV industry. In this paper, the module-level fault diagnosis is proposed based on the developed wireless sensor networks and inverter activated current-voltage (I-V) scanning. The voltage waveform of PV module is measured during the scanning of I-V characteristic curve activated by the inverter. Then, the open-circuit voltage and voltage at maximum power point are obtained and used to diagnose the pattern of partial shading, short-circuit of bypass diodes of PV module, and open-circuit faults. Using the real-time monitoring in the developed virtual reality (VR) environment, the efficiency of fault localization and diagnosis of PV array is enhanced. The experimental results show that the proposed module-level fault diagnosis of PV array based on wireless sensor networks and inverter activated I-V scanning is effective and feasible, especially suitable for the PV string that few PV modules are slightly shaded or one of its bypass diodes is short-circuited.