Line Loss Outlier Detection and Correlation Analysis Between Low-voltage Distributed PV Loads: An Empirical Study

The development of clean energy sources, such as distributed photovoltaic provides an essential means of achieving the ’double carbon’ target. In this paper, we investigate the detection of line loss anomalies based on automated machine learning and the relationship between distributed PV line loss and station area to study the impact of PV on the line loss of the station area. The report is based on data analysis from an empirical case of a constructed PV grid. Based on the example analysis and the anomaly detection model, the significant influencing factors of the impact of low-voltage distributed PV on the station area were obtained.