Jinjin Li
ABSTRACT
Metering anomaly is one of the main causes of abnormal line loss, and it has always been an important problem that power grid enterprises expect to solve. With the popularization of smart meters in the power grid, more and more measurement data are collected, and the diagnosis of metering anomalies has also been greatly improved. Aiming at the problems of low accuracy and poor real-time performance of metering anomaly detection methods in power grids, a metering anomaly detection method based on intelligent algorithm is proposed. Firstly, the user's original electricity consumption data collected under the intelligent measurement system is preprocessed, the periodic electricity consumption characteristics are extracted to establish the feature fusion layer network, and then the extracted feature vectors are spliced horizontally to obtain a new fusion vector, so as to realize the intelligent diagnosis of various metering anomalies.
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