This paper presents a research work which focuses on generating synthetic data to enrich
the training‐set of a deep learning (DL) based classification system to classify power system …

In this work, we present a Real-Time, Multi-layer cybEr-power TestbEd for the Resiliency
analysis (RT-METER) to support power grid operation and planning. Developed cyber …

The automated classification of grid disturbances based on phasor measurements is a key
technology for the reliable operation of power transmission systems. The predominant use of …

Monitoring, protection, and control processes are becoming more complex as distributed
energy resources (DERs) penetrate distribution networks (DNs). This is due to the inherent …

The significance of Smart Grid can be realized by the bidirectional communication channel
between consumers and utility providers which gives accurate energy use data and demand …

Increased real-time monitoring of the electric grid is vital to meet the burgeoning challenges
posed by load growth and diversification, renewable generation integration, extreme …

Timely and precise identification of anomalies and events in cyber-power distribution
systems is critical. This work introduces d-SyncAED, a real-time bad data anomaly and event …

The automated classification of grid disturbances based on phasor measurement units
(PMU) is a key application for a fast and reliable monitoring and control of future power …

Objectives: To decrease the model parameters in Reinforcement learning with Compressed
Improved DeepRT (RC-IDeepRT) for Cyber-Physical System (CPS) data analysis, a method …