Fault Diagnosis Method for Photovoltaic Arrays Considering Low Irradiation Samples

This article introduces a fault diagnosis method for photovoltaic (PV) arrays operating under low irradiation conditions. First, we construct feature vectors by analyzing the differences in the steady-state electrical signal characteristics of PV arrays in normal and abnormal scenarios. Then, we present a data processing method for these feature vectors to mitigate the impact of environmental changes on the array’s actual operating characteristics. Additionally, we propose a regularization logistic regression approach tailored for fault diagnosis in PV arrays under low irradiation conditions. The regularization logistic regression method effectively addresses the overfitting issues often encountered in traditional logistic regression methods. Experimental results validate the exceptional accuracy of the proposed fault diagnosis method.