This article studies robust event classification using imperfect real-world phasor
measurement unit (PMU) data. By analyzing the real-world PMU data, we find that it is …

This paper studies distributed learning of real-world phasor measurement unit (PMU) data to
enable privacy-preserving data sharing and analytics among different entities (ie, PMU data …

As the penetration of inverter-based renewable energy resources increases in the power
grid, especially at the distribution and microgrid levels, the need to accurately represent …

Timely detection of power system events is a crucial task, which can facilitate the
implementation of remedial actions to improve reliability, resiliency, and security of the …

Event classification is a critical task to ensure the reliability of the power system. Recent
developments in event classification methods leverage data-driven techniques with fine …

Phasor measurement units (PMU) are integral to the modernization and automation plan of
the electric power industry. PMU data signatures contain system-level events (eg, faults …

This paper studies event classification using imperfect real-world phasor measurement unit
(PMU) data with scarce event types (labels). By investigating the real-world PMU data, it is …

This dissertation presents and evaluates model-free methodologies to process Phasor
Measurement Unit (PMU) data. Model-based PMU applications require knowledge of the …

The increasing penetration of renewable energy sources (such as solar and wind) and
incoming widespread electric vehicles charging introduce new challenges in the power …