[HTML][HTML] Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality
The deployment of energy storage systems (ESSs) is a significant avenue for maximising the
energy efficiency of a distribution network, and overall network performance can be …
energy efficiency of a distribution network, and overall network performance can be …
Fault detection, classification and location for transmission lines and distribution systems: a review on the methods
A comprehensive review on the methods used for fault detection, classification and location
in transmission lines and distribution systems is presented in this study. Though the three …
in transmission lines and distribution systems is presented in this study. Though the three …
Self attention convolutional neural network with time series imaging based feature extraction for transmission line fault detection and classification
This paper introduces a novel self-attention convolutional neural network (SAT-CNN) model
for detection and classification (FDC) of transmission line faults. The transmission lines …
for detection and classification (FDC) of transmission line faults. The transmission lines …
Situational awareness in distribution grid using micro-PMU data: A machine learning approach
The recent development of distribution-level phasor measurement units, also known as
micro-PMUs, has been an important step toward achieving situational awareness in power …
micro-PMUs, has been an important step toward achieving situational awareness in power …
Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems
Quantum computing (QC) and deep learning have shown promise of supporting
transformative advances and have recently gained popularity in a wide range of areas. This …
transformative advances and have recently gained popularity in a wide range of areas. This …
A critical assessment of imbalanced class distribution problem: The case of predicting freshmen student attrition
Predicting student attrition is an intriguing yet challenging problem for any academic
institution. Class-imbalanced data is a common in the field of student retention, mainly …
institution. Class-imbalanced data is a common in the field of student retention, mainly …
Deep power: Deep learning architectures for power quality disturbances classification
The transformation of the conventional electric power grid to modern smart grid are
subjected to power system quality and reliability problems. In order to ensure reliable …
subjected to power system quality and reliability problems. In order to ensure reliable …
Time-series classification methods: Review and applications to power systems data
Chapter Overview The diffusion in power systems of distributed renewable energy
resources, electric vehicles, and controllable loads has made advanced monitoring systems …
resources, electric vehicles, and controllable loads has made advanced monitoring systems …
Classification of power quality events–a review
Power quality (PQ) interest has increasingly evolved over the past decade. The paper
surveys the application of signal processing, intelligent techniques and optimization …
surveys the application of signal processing, intelligent techniques and optimization …
A fast fault detection and identification approach in power distribution systems
In this paper, a Modified Multi-Class Support Vector Machines (MMC-SVM) technique is
developed to simultaneously detect and classify different types of open-circuit faults in power …
developed to simultaneously detect and classify different types of open-circuit faults in power …