Distributed photovoltaic (PV) power generation systems are widely spread. Moreover, due to the randomness of meteorological conditions and the complexity of installation environments, it is difficult to eliminate the interference of factors such as meteorological fluctuations in the monitoring of abnormal states of PV equipment. Based on this, this paper proposes a PV power generation anomaly detection method based on Quantile Regression Recurrent Neural Network (QRRNN). First, the characteristics of solar irradiance on clear days are analyzed, and the clear day masking method is used to elimi...
