Electricity ranks among the world's most plundered commodities. The fraudulent act of
acquiring electrical power without paying for it is termed electricity theft. Electricity theft is …

Electricity theft (ET) is an utmost problem for power utilities because it threatens public
safety, disturbs the normal working of grid infrastructure and increases revenue losses. In …

This paper presents a novel supervised machine learning-based electric theft detection
approach using the feature engineered-CatBoost algorithm in conjunction with the …

Electricity theft is one of the most significant factors among non-technical losses. Because of
electricity theft, genuine users have to pay more, supply quality decreases, and generation …

In this paper, a hybrid deep learning model is presented to detect electricity theft in the
power grids, which happens due to the Non-Technical Losses (NTLs). The NTLs emerge …

Electricity theft damages power grid infrastructure and is also responsible for huge revenue
losses for electric utilities. Integrating smart meters in traditional power grids enables real …

As the use of deep learning models is increased in smart grid systems, especially in load
forecasting, supply-demand response, vulnerability detection, and finding abnormal …

Electricity theft (ET), which endangers public safety, interferes with the regular operation of
grid infrastructure, and increases revenue losses, is a significant issue for power companies …

Obtaining outstanding electricity theft detection (ETD) performance in the realm of advanced
metering infrastructure (AMI) and smart grids (SGs) is quite difficult due to various issues …

The problem of electricity theft is exponentially increasing around the globe, which is harmful
to the power sectors and consumers. The recent development in the advanced metering …