The digitalization of production in smart grids entails challenges related to data collection,
coordination, privacy protection, and anomaly detection. Machine learning techniques offer …

In smart electric grid systems, various sensors and Internet of Things (IoT) devices are used
to collect electrical data at substations. In a traditional system, a multitude of energy-related …

Smart Grids (SG) have emerged as one of the complex cyber-physical systems integrating
information and communication technologies to existing power system infrastructure for …

The industrial internet of things (IIoT) is a flexible and scalable manufacturing system that
can collect and analyse data from sensors based on machine learning, cloud, and edge …

Aiming at the problem of untimely fault detection caused by the large number and wide
distribution of power grid equipment, this paper designs a cloud computing platform-based …

Anomaly detection is critical in industrial systems such as smart grid systems to guarantee
their safe and effective operation. The smart grid stations contain sensitive data, and they …

The smart grid integrates Information and Communication Technologies (ICT) into the
traditional power grid to manage the generation, distribution, and consumption of electrical …

This paper tries to solve anomaly detection, a very important issue in ensuring the safe and
stable operation of power system. As the proportion of abnormal data in the operation of …

The smart grid accessibility over the Internet of Things (IoT) is becoming attractive to
electrical grid operators as it brings considerable operational and cost efficiencies. However …

Accurate state estimation is critical to wide-area situational awareness of smart grid.
However, recent research found that power system state estimators are vulnerable to a new …