Few-Shot Metering Anomaly Diagnosis with Variable Relation Mining
Jianqiao Sun,
Wei Zhang,
Peng Guo
et al.
Abstract:Metering anomalies not only mean huge economic losses but also indicate the faults of equipment and power lines, especially within the substation. As a result, metering anomaly diagnosis is becoming one of the most important missions in smart grids. However, due to the insufficient and imbalanced anomaly cases, identifying the anomalies in smart meter data accurately and efficiently remains challenging. Existing methods usually employ few-shot learning models in computer vision directly, which requires the ric… Show more
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