Failure Diagnosis Method of Photovoltaic Generator Using Support Vector Machine

The capacity of photovoltaic (PV) generators can increase owing to the 4030 policy of the Government of South Korea.. In addition, there has been significant interest in developing a technology for the maintenance of PV generators owing to an increase in the number of outdated PV generators. This paper describes a failure diagnosis method that uses operational data for power generation and solar radiation of PV generators. The measured data stored since four years in an operational 50-kW PV generator that was installed in 2014, were analyzed. The proposed failure diagnosis logic uses support vector machine classification as a failure diagnosis method that can classify normal and failure data. The failure data were processed to be used as the fault diagnosis logic for solar power generators. A new 50-kW PV generator, which contained no fault data, was used for a case study in this paper. Fault data were generated and the operation data of the PV generators were diagnosed by applying the proposed method. In addition, the accuracy was calculated and the results were analyzed.