Machine learning driven smart electric power systems: Current trends and new perspectives
MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
A review of machine learning approaches to power system security and stability
Increasing use of renewable energy sources, liberalized energy markets and most
importantly, the integrations of various monitoring, measuring and communication …
importantly, the integrations of various monitoring, measuring and communication …
Detection and classification of multiple power quality disturbances in Microgrid network using probabilistic based intelligent classifier
Microgrid (MG) networks have evolved as reliable power source for providing secure,
reliable, and low carbon emission of energy supply to the remote communities. Power …
reliable, and low carbon emission of energy supply to the remote communities. Power …
Distributed generation hybrid AC/DC microgrid protection: A critical review on issues, strategies, and future directions
The integration of distributed energy resources (DERs) with conventional systems emerges
as an intelligent solution for providing uninterrupted and secure power even at times of high …
as an intelligent solution for providing uninterrupted and secure power even at times of high …
Hybrid convolutional neural network-multilayer perceptron model for solar radiation prediction
Urgent transition from the dependence on fossil fuels towards renewable energies requires
more solar photovoltaic power to be connected to the electricity grids, with reliable supply …
more solar photovoltaic power to be connected to the electricity grids, with reliable supply …
Affinity based fuzzy kernel ridge regression classifier for binary class imbalance learning
BB Hazarika, D Gupta - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The class imbalance learning (CIL) problem indicates when one class have very low
proportions of samples (minority class) compared to the other class (majority class). Even …
proportions of samples (minority class) compared to the other class (majority class). Even …
Major challenges towards energy management and power sharing in a hybrid AC/DC microgrid: a review
A fundamental strategy for utilizing green energy from renewable sources to tackle global
warming is the microgrid (MG). Due to the predominance of AC microgrids in the existing …
warming is the microgrid (MG). Due to the predominance of AC microgrids in the existing …
A stacking ensemble classification model for detection and classification of power quality disturbances in PV integrated power network
P Radhakrishnan, K Ramaiyan, A Vinayagam… - Measurement, 2021 - Elsevier
This paper proposes a stacking ensemble classification model to classify the different Power
Quality Disturbances (PQDs) in Photovoltaic (PV) integrated power network. For this study …
Quality Disturbances (PQDs) in Photovoltaic (PV) integrated power network. For this study …
Review of distributed generator integrated AC microgrid protection: issues, strategies, and future trends
In the recent power system scenario, the concept of microgrid is evolving rapidly. The
architecture should be robust enough to cater the complexity of integration of distributed …
architecture should be robust enough to cater the complexity of integration of distributed …
Computational approach to clinical diagnosis of diabetes disease: a comparative study
Diabetes is one of the most prevalent non-communicable diseases and is the 6th leading
cause of death worldwide. It'sa chronic metabolic disorder which has no cure, however, it is …
cause of death worldwide. It'sa chronic metabolic disorder which has no cure, however, it is …