This paper aims to introduce deep learning to the power quality community by reviewing the
latest applications and discussing the open challenges of this technology. Publications …

Harmonics and waveform distortion is a significant power quality problem in modern power
systems with high penetration of Renewable Energy Sources (RES). This problem has …

Power quality (PQ) monitoring and detection has emerged as an essential requirement due
to the proliferation of sensitive power electronic interfacing devices, electric vehicle charging …

This work aims to cover the measurement, modeling, and analysis of waveform distortions in
railway power systems. It is focused on waveform distortion as a phenomenon that includes …

Waveform distortion in general represents a widespread problem in electrified transports
due to interference, service disruption, increased losses, and aging of components. Given …

Implementing a proper clustering algorithm and a high accuracy classifier for applying on
electricity smart meter data is the first stage in analyzing and managing electricity …

This paper proposes an unsupervised learning schema for seeking the patterns in rms
voltage variations at the time scale between 1 s and 10 min, a rarely considered time scale …

Energy consumption has increased over the years, and, due to the dependency on fossil
energy, alternative and renewable energy sources have been integrated to address …

This paper addresses the issue of seeking sub-10-min patterns in fast rms voltage variations
from time-limited measurement data at multiple locations worldwide. This is a rarely …

This paper proposes a deep learning (DL) method for the identification of spectral patterns of
time-varying waveform distortion in photovoltaic (PV) installations. The PQ big data with …