Parametric and nonparametric machine learning techniques for increasing power system reliability: a review
F Imam, P Musilek, MZ Reformat - Information, 2024 - mdpi.com
Due to aging infrastructure, technical issues, increased demand, and environmental
developments, the reliability of power systems is of paramount importance. Utility companies …
developments, the reliability of power systems is of paramount importance. Utility companies …
Application of machine learning methods for asset management on power distribution networks
GLL Rajora, MÁ Sanz Bobi, C Mateo Domingo - 2022 - repositorio.comillas.edu
This study aims to study the different kinds of Machine Learning (ML) models and their
working principles for asset management in power networks. Also, it investigates the …
working principles for asset management in power networks. Also, it investigates the …
Gas-Sensing Properties of Dissolved Gases in Insulating Material Adsorbed on SnO2–GeSe Monolayer
LY Guo, S Liang, Z Yang, L Jin, Y Tan, Z Huang - Chemosensors, 2022 - mdpi.com
In a transformer, the insulation materials will produce different dissolved gases due to
various faults in the operation of the transformer, in which C2H2, CH4, and H2 are the main …
various faults in the operation of the transformer, in which C2H2, CH4, and H2 are the main …
A holistic integration of conventional and machine learning techniques to enhance the analysis of power transformer health index considering data unavailability
Health index is an essential tool to evaluate the condition of power transformers. Generally,
there are two methodologies to evaluate the health index of power transformers …
there are two methodologies to evaluate the health index of power transformers …
A review of asset management using artificial intelligence‐based machine learning models: Applications for the electric power and energy system
Power system protection and asset management present persistent technical challenges,
particularly in the context of the smart grid and renewable energy sectors. This paper aims to …
particularly in the context of the smart grid and renewable energy sectors. This paper aims to …
Hybrid fuzzy and gated recurrent network based artificial intelligence approach for fault diagnosis and prognosis of transformers using dissolved gas analysis
KS Krishna Veni, N Senthil Kumar… - Journal of Intelligent & …, 2023 - content.iospress.com
In the electrical energy transmission and distribution sector, power transformers play an
important role. Early fault diagnosis and prognosis are essential to ensure continuous …
important role. Early fault diagnosis and prognosis are essential to ensure continuous …
[HTML][HTML] Propuesta de metodología para el diagnóstico de fallos basado en árboles de decisión y lógica difusa
AM Coll, AM Rodríguez, DM Gutiérrez… - Ingeniería Electrónica …, 2022 - scielo.sld.cu
La presente investigación tiene como objetivo presentar una propuesta de metodología
para el diagnóstico de fallos en la industria basado en árboles de decisión y lógica difusa …
para el diagnóstico de fallos en la industria basado en árboles de decisión y lógica difusa …
A review about Zig Zag and Double Zig Zag connections in Transformer
G Peter, AA Stonier, A Sherine… - 2022 2nd International …, 2022 - ieeexplore.ieee.org
Whenever we think of three-phase transformer connections, we think straightaway of either
star-connected transformers or delta-connected transformers. A great majority of polyphase …
star-connected transformers or delta-connected transformers. A great majority of polyphase …