Composite Index for Identifying Anomalies in Low Voltage Systems Using Smart Meter Measurement Data

Abstract

Smart meters are essential for distribution utilities as they provide valuable data that enable efficient management of distribution systems and informed decision-making processes. A critical application of this data is identifying abnormal system operations, such as non-technical losses and high impedance faults, which can affect power quality, safety, and utility revenue. However, there is currently no consensus on how to address these issues. This study proposes a composite index that uses smart meter data, and statistical concepts to simultaneously detect and locate anomalous system operations. This index is called the “Anomaly Intensity Index” and relies on tests that evaluate local and system-wide measurements, ranking customers according to the expected anomaly intensity. The proposed approach successfully identified abnormal demand as low as 0.2 kW per phase in test cases and estimated deviated energy with less than 1% error.