Supervised Optimum Path Forest Algorithm for Fault Diagnosis of Photovoltaic Array

Abstract

When the photovoltaic (PV) system fails, the power generation efficiency is greatly reduced or even leads to incidents, that is why the fault diagnosis of the PV system is very necessary. This paper proposed an optimum-path forest (OPF) photovoltaic arrays fault diagnosis method. According to the characteristics of the photovoltaic panel, seven factors were selected as the characteristic parameters for studying the fault diagnosis of PV system. Then, combined with the actual measurement data and the simulated measurement data, the complete graphs and the minimum spanning trees were obtained in turn, and finally the OPF classifier was obtained which was used for fault diagnosis and classification. At the same time, this paper also compared the OPF algorithm with other algorithms such as Linear SVM, Fine KNN, Linear discriminant and Boosted Trees that showed the OPF algorithm has very high speed and accuracy and is more suitable for fault diagnosis of PV system in practical application. In addition, this paper also optimized the traditional OPF method which improves the speed of classification. Finally, the actual fault detection of PV system was built and achieved good fault diagnosis effect.