A fault diagnosis method of distributed photovoltaic power generation equipment based on big data mining

Aiming at the massive operation and monitoring data of distributed photovoltaic equipment, this paper builds a real-time database and a relational database platform. Based on big data mining technology, the distributed photovoltaic power generation equipment status data and the related data are preprocessed and cleaned. Then the failure mode of distributed photovoltaic power generation equipment is counted and analyzed with the data mining algorithm, and the failure severity, probability level, severity level and failure rate of each faulty subsystem is calculated to find out the failure rule and corresponding treatment measures. At the same time, a new energy remote expert fault diagnosis software system has been developed to realize early warning, fault cause analysis and fault trend analysis of distributed photovoltaic equipment faults.