Electrical power grid insulators installed outdoors are exposed to environmental conditions,
such as the accumulation of contaminants on their surface. The contaminants increase the …

The improvement of photovoltaic (PV) power prediction precision plays a crucial role in the
new energy consumption. This paper proposes a composite prediction framework (DC (DWT …

Photovoltaic (PV) technology plays a crucial role in the transition towards a low-carbon
energy system, but the potential-induced degradation (PID) phenomenon can significantly …

This paper proposes a robust diagnosis method of photovoltaic (PV) array faults considering
label errors in training data. First, the online data of PV systems, including the sequences of …

A novel intelligent scheme using the wavelet packet transform (WPT) and extreme learning
machine (ELM) is proposed for fault event classification in the grid-connected photovoltaic …

Conventional overcurrent protective relay is unable to detect high impedance faults (HIFs) in
the micro-grid system owing to the reduced levels of fault magnitude. In this paper …

With the rapid expansion and installation of Photovoltaic (PV) power plants, developing a
proper Fault Detection and Diagnosis (FDD) strategy has become a significant issue within …

We proposed a pattern recognition strategy based on the long short-term memory network
(LSTM) and convolutional neural network (CNN), with phase-sensitive optical time domain …

The dependence of high-impedance faults (HIFs) detection methods on a large amount of
training data has always been a fundamental problem in electrical distribution systems. This …

Monitoring the status of rotating components is important in modern machinery. The goal of
this study is to evaluate the feasibility of using a k-Nearest Neighbors (kNN) classifier …