The article describes the experience of a successful online implementation of the
Dissipating Energy Flow method for locating the source of oscillations in the Oscillation …

Online power system event identification and classification are crucial to enhancing the
reliability of transmission systems. In this paper, we develop a deep neural network (DNN) …

These days, endless streams of data are generated by various sources such as sensors,
applications, users, etc. Due to possible issues in sources, such as malfunctions in sensors …

Data quality issues exist in practical phasor measurement units (PMUs) due to
communication errors or signal interferences. As a result, the performances of existing data …

While the quality of the synchronized measurements is of paramount importance for real-
time monitoring and protection of the power grids, collected measurements often contain …

The paper proposes a new approach for the recovery of missing data from phasor
measurement units (PMUs). The approach is based on the application of tensor …

Data integrity of power system states is critical to modern power grid operation and control
due to communication latency, state measurements are not immediately available at the …

A high penetration of renewable energies into the modern grid creates randomness and
uncertainties which require advanced real-time monitoring and control. Phasor …

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power
systems. We propose a novel data-driven online event detection algorithm with …

Real-time identification of successive events in power systems is crucial to avoid cascading
failures. Existing identification methods are mainly designed for single events and may not …