Detecting anomalous electricity consumption with transformer and synthesized anomalies.

ABSTRACT: Non-technical losses are consistently a troubling issue for power suppliers. With the application and popularization of smart grid and advanced measurement systems, it has become possible to use data-driven methods to detect anomalous electricity consumption to reduce non-technical losses. A range of machine learning models have been utilized for detecting anomalous electricity consumption and have achieved promising results. However, with the evolution of techniques like electricity theft, coupled with the exponential increase in electricity consumption data, new challenges are constantly being posed for anomalous electricity consumption detection. We propose a Transformer-based method for detecting anomalous electricity consumption. The Transformer is composed of multi-head attention, la

SUBMITTER: Mu T 

PROVIDER: S-EPMC10702936 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature