In this work, an automatic fault detection method for grid-connected photovoltaic (GCPV) plants is presented. The proposed method generates a diagnostic signal which indicates possible faults occurring in the GCPV plant. In order to determine the location of the fault, the ratio between DC and AC power is monitored. The software tool developed identifies different types of faults like: fault in a photovoltaic module, fault in a photovoltaic string, fault in an inverter, and a general fault that may include partial shading, PV ageing, or MPPT error. In addition to the diagnostic signal, other essential information about the system can be displayed each 10 min on the designed tool. The method has been validated using an experimental database of climatic and electrical parameters regarding a 20 kWp GCPV plant installed on the rooftop of the municipality of Trieste, Italy. The obtained results indicate that the proposed method can detect and locate correctly different type of faults in both DC and AC sides of the GCPV plant. The developed software can help users to check possible faults on their systems in real time.

Fault detection method for grid-connected photovoltaic plants

MASSI PAVAN, ALESSANDRO;
2014-01-01

Abstract

In this work, an automatic fault detection method for grid-connected photovoltaic (GCPV) plants is presented. The proposed method generates a diagnostic signal which indicates possible faults occurring in the GCPV plant. In order to determine the location of the fault, the ratio between DC and AC power is monitored. The software tool developed identifies different types of faults like: fault in a photovoltaic module, fault in a photovoltaic string, fault in an inverter, and a general fault that may include partial shading, PV ageing, or MPPT error. In addition to the diagnostic signal, other essential information about the system can be displayed each 10 min on the designed tool. The method has been validated using an experimental database of climatic and electrical parameters regarding a 20 kWp GCPV plant installed on the rooftop of the municipality of Trieste, Italy. The obtained results indicate that the proposed method can detect and locate correctly different type of faults in both DC and AC sides of the GCPV plant. The developed software can help users to check possible faults on their systems in real time.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2822524
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