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 …

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 presents a comprehensive study of winter temperatures in Norway and northern
Sweden, covering a period of 50 to 70 years. The analysis utilizes Singular Spectrum …

The classification of voltage sags source location as downstream (DS) or upstream (US) of a
monitor is a significant issue that should be taken into account when establishing mitigation …

The paper investigates the application of machine learning (ML) for voltage sag source
localization (VSSL) in electrical power systems. To overcome feature-selection challenges …

Recognition and analysis of voltage sags (dips) allow network operators to predict and
prevent problems in real-life applications. Clearing the voltage sag source by direction …

Voltage sags are the most frequent and impactful disturbances in industrial power grids,
leading to high financial losses for industrial clients. The identification of the cause and its …

Real-time detection of the voltage sag sources' relative location requires fast and accurate
methods. Therefore, in this paper, the transient period of voltage sags is used with useful …

The growing penetration of distributed energy resources (DERs) in form of inverter-based
distributed generations (IBDGs) in distribution systems has a high impact on fault location …

It is of great significance to extract the voltage sag disturbances with high signal-to-noise
ratio (SNR) for safety, environmental and economic interests, which can be applied to locate …