Condition monitoring based on partial discharge diagnostics using machine learning methods: A comprehensive state-of-the-art review
This paper presents a state-of-the-art review on machine learning (ML) based intelligent
diagnostics that have been applied for partial discharge (PD) detection, localization, and …
diagnostics that have been applied for partial discharge (PD) detection, localization, and …
Advances in DGA based condition monitoring of transformers: A review
Abstract Dissolved Gas Analysis (DGA) is a standout diagnostic strategy to recognise
incipient faults and monitor the condition of oil-immersed transformers. It correlates the …
incipient faults and monitor the condition of oil-immersed transformers. It correlates the …
Effective IoT-based deep learning platform for online fault diagnosis of power transformers against cyberattacks and data uncertainties
The distribution of the power transformers at a far distance from the electrical plants
represents the main challenge against the diagnosis of the transformer status. This paper …
represents the main challenge against the diagnosis of the transformer status. This paper …
Big data analytics for future electricity grids
This paper provides a survey of big data analytics applications and associated
implementation issues. The emphasis is placed on applications that are novel and have …
implementation issues. The emphasis is placed on applications that are novel and have …
Enhancing diagnostic accuracy of transformer faults using teaching-learning-based optimization
The early detection of the transformer faults with high accuracy rates guarantees the
continuous operation of the power system networks. Dissolved gas analysis (DGA) is a …
continuous operation of the power system networks. Dissolved gas analysis (DGA) is a …
Reliable IoT paradigm with ensemble machine learning for faults diagnosis of power transformers considering adversarial attacks
Power transformer represents an important equipment in electric power systems.
Transformers are not only a source of power outages for electric utilities, but they also affect …
Transformers are not only a source of power outages for electric utilities, but they also affect …
A novel double-stacked autoencoder for power transformers DGA signals with an imbalanced data structure
D Yang, J Qin, Y Pang, T Huang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Artificial intelligence is the general trend in the field of power equipment fault diagnosis.
However, limited by operation characteristics and data defects, the application of the …
However, limited by operation characteristics and data defects, the application of the …
State-of-the-art review on asset management methodologies for oil-immersed power transformers
L **, D Kim, A Abu-Siada - Electric Power Systems Research, 2023 - Elsevier
Owing to their vital function and high cost, oil-immersed power transformers represent key
links in electricity grids. While extensive effort has been invested by industry in develo** …
links in electricity grids. While extensive effort has been invested by industry in develo** …
A review of power system protection and asset management with machine learning techniques
Power system protection and asset management have drawn the attention of researchers for
several decades; but they still suffer from unresolved and challenging technical issues. The …
several decades; but they still suffer from unresolved and challenging technical issues. The …
Hybrid grey wolf optimizer for transformer fault diagnosis using dissolved gases considering uncertainty in measurements
The transformer fault diagnosis based on dissolved gas analysis is greatly affected by the
uncertainties existing in measured data during oil sampling, handling and storage. This work …
uncertainties existing in measured data during oil sampling, handling and storage. This work …