With recent advances in information and communication technology (ICT), the bleeding
edge concept of digital twin (DT) has enticed the attention of many researchers to …

Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

Among an electricity provider's non-technical losses, electricity theft has the most severe and
dangerous effects. Fraudulent electricity consumption decreases the supply quality …

As one of the major factors of the nontechnical losses (NTLs) in distribution networks, the
electricity theft causes significant harm to power grids, which influences power supply quality …

The big data sources in smart grid (SG) enable utilities to monitor, control, and manage the
energy system effectively, which is also promising to advance the efficiency, reliability, and …

Energy theft poses a significant challenge for all parties involved in energy distribution, and
its detection is crucial for maintaining stable and financially sustainable energy grids. One …

Electricity theft has been a growing concern for the smart grid. It can be defined as follows:
illegal customers use energy from electric utilities without a contract or manipulate their …

Non-technical losses (NTL) in electricity utilities are responsible for major revenue losses. In
this paper, we propose a novel end-to-end solution to self-learn the features for detecting …

In smart grids, homes are equipped with smart meters (SMs) to monitor electricity
consumption and report fine-grained readings to electric utility companies for billing and …

The theft of electricity affects power supply quality and safety of grid operation, and non-
technical losses (NTL) have become the major reason of unfair power supply and economic …