A Novel Fault Diagnosis Scheme for PV Plants Based on Real-Time System State Identification
Xuan Jiao, Xingshuo Li, Tangwu Yang, Yongheng Yang, Weidong Xiao
Abstract
A large-scale photovoltaic (PV) power plant is composed of hundreds or thousands of solar panels, which makes fault diagnosis a challenging problem due to its complexity. It is known that the PV power output characteristics dramatically change with environmental conditions. Thus, it is difficult to distinguish a short-circuit line fault from mismatching conditions induced by partial shading or unbalanced generation. The article proposes a novel fault diagnosis scheme that is based on real-time system identification to determine normal or abnormal operations. It does not require any additional hardware or measurement support. The identification and analysis include both short- and long-term characteristics of the generation system to mitigate disturbances and improve the robustness. The effectiveness of the proposed scheme is validated by simulations and experiments under a wide range of test conditions.