Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the …

T Ahmad, R Madonski, D Zhang, C Huang… - … and Sustainable Energy …, 2022 - Elsevier
The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …

Comprehensive review on detection and classification of power quality disturbances in utility grid with renewable energy penetration

GS Chawda, AG Shaik, M Shaik, S Padmanaban… - IEEE …, 2020 - ieeexplore.ieee.org
The global concern with power quality is increasing due to the penetration of renewable
energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power …

A parallel random forest algorithm for big data in a spark cloud computing environment

J Chen, K Li, Z Tang, K Bilal, S Yu… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
With the emergence of the big data age, the issue of how to obtain valuable knowledge from
a dataset efficiently and accurately has attracted increasingly attention from both academia …

Power quality in microgrids including supraharmonics: Issues, standards, and mitigations

AA Alkahtani, STY Alfalahi, AA Athamneh… - IEEE …, 2020 - ieeexplore.ieee.org
A microgrid (MG) is a small-scale power system with a cluster of loads and distributed
generators operating together through energy management software and devices that act as …

Power quality assessment and event detection in distribution network with wind energy penetration using stockwell transform and fuzzy clustering

OP Mahela, B Khan, HH Alhelou… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Power quality (PQ) is a vital issue in the present power systems integrated with large
renewable energy sources since more power electronics devices are incorporated in the …

The impact of intelligent cyber-physical systems on the decarbonization of energy

O Inderwildi, C Zhang, X Wang, M Kraft - Energy & Environmental …, 2020 - pubs.rsc.org
The decarbonisation of energy provision is key to managing global greenhouse gas
emissions and hence mitigating climate change. Digital technologies such as big data …

A new optimal feature selection algorithm for classification of power quality disturbances using discrete wavelet transform and probabilistic neural network

S Khokhar, AAM Zin, AP Memon, AS Mokhtar - Measurement, 2017 - Elsevier
Abstract Automatic classification of Power Quality Disturbances (PQDs) is a challenging
concern for both the utility and industry. In this paper, a novel technique of automatic …

Variational mode decomposition and decision tree based detection and classification of power quality disturbances in grid-connected distributed generation system

PD Achlerkar, SR Samantaray… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
This paper presents a variational mode decomposition (VMD) and decision tree based
detection and classification method of single and mixed power quality (PQ) disturbances in …

A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances

S Khokhar, AABM Zin, ASB Mokhtar… - … and Sustainable Energy …, 2015 - Elsevier
The increasing trend towards renewable energy sources requires higher power quality (PQ)
at the generation, transmission and distribution systems. The PQ disturbances are produced …

Power quality disturbance detection and classification using signal processing and soft computing techniques: A comprehensive review

M Mishra - International transactions on electrical energy …, 2019 - Wiley Online Library
Power quality (PQ) studies have gained huge attention from the academics and the industry
over the past three decades. The main objective of this article is to provide a comprehensive …