Sequential feature selection for power system event classification utilizing wide-area PMU data

Sequential feature selection for power system event classification utilizing wide-area PMU data

The increasing penetration of intermittent, non-synchronous generation has led to a reduction in total power system inertia. Low inertia systems are more sensitive to sudden changes and more susceptible to secondary issues that can result in large-scale events. Due to the short time frames involved,...

Full description

Bibliographic Details
Main Authors: Mark Rafferty, Xueqin Liu, John Rafferty, Lei Xie, David Laverty, Seán McLoone
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Energy Research
Subjects:
event classification
dimensionality reduction
PMU data
machine learning
power system monitoring
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2022.957955/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2022.957955/full

Similar Items