Data driven transformer thermal model for condition monitoring

A Doolgindachbaporn, G Callender… - … on Power Delivery, 2021 - ieeexplore.ieee.org
Condition monitoring of power transformers, which are key components of electrical power
systems, is essential to identify incipient faults and avoid catastrophic failures. In this paper …

Prediction of the degree of polymerization in transformer cellulose insulation using the feedforward backpropagation artificial neural network

BA Thango, PN Bokoro - Energies, 2022 - mdpi.com
The life expectancy of power transformers is primarily determined by the integrity of the
insulating oil and cellulose paper between the conductor turns, phases and phase to earth …

On-line monitoring of maximum temperature and loss distribution of a medium frequency transformer using artificial neural networks

D Santamargarita, D Molinero, E Bueno… - … on Power Electronics, 2023 - ieeexplore.ieee.org
Losses and maximum temperature are important indicators of the health status of the
medium-frequency magnetic components. Both the losses and the maximum temperature …

A temperature calculation method of oil immersed transformer considering delay effects and multiple environmental factors

R Ni, J Chen, C Yang, C Li, R Qiu, Z Liu, R Li… - Electric Power Systems …, 2022 - Elsevier
In the traditional transformer temperature calculation methods, the hot spot temperature
(HST) is obtained by calculating the oil temperature rise, winding temperature rise, and then …

Forecasting thermal parameters for ultra‐high voltage transformers using long‐and short‐term time‐series network with conditional mutual information

W Lin, X Miao, J Chen, S Xiao, Y Lu… - IET Electric Power …, 2022 - Wiley Online Library
Precise forecasting of the thermal parameters is a critical factor for the safe operation and
fault incipient warning of the ultra‐high voltage (UHV) transformers. In this work, a novel …

[HTML][HTML] Grey-box modeling for hot-spot temperature prediction of oil-immersed transformers in power distribution networks

EMV Blomgren, F D'Ettorre, O Samuelsson… - … Energy, Grids and …, 2023 - Elsevier
Power transformers are one of the most costly assets in power grids. Due to increasing
electricity demand and levels of distributed generation, they are more and more often loaded …

Inversion detection of transformer transient hot spot temperature

J Ruan, Y Deng, YU Quan, R Gong - IEEE Access, 2021 - ieeexplore.ieee.org
This paper proposes an inversion method to estimate a 10 kV oil-immersed transformer
transient hot spot temperature (HST). A set of transient feature quantities which can reflect …

Novel and Simplified Procedure to Test Immunity of Low-Power Voltage Transformers

A Mingotti, L Peretto, R Tinarelli - Sensors, 2022 - mdpi.com
International technical committees put considerable efforts into the writing process of
standards. They always try to find a tradeoff between the rigorous scientific requirements …

Artificial neural network-based cooling capacity estimation of various radiator configurations for power transformers operated in ONAN mode

A Koca, O Senturk, AB Çolak, A Bacak… - Thermal Science and …, 2024 - Elsevier
Power transformers submerged in oil are universally acknowledged as very useful elements
in electrical power networks. A fraction of the electrical energy involved in the conversion …

Transformer hot spot temperature estimation through adaptive neuro fuzzy inference system approach

ET Mharakurwa, DW Gicheru - Heliyon, 2024 - cell.com
Transformer performance and efficiency can be enhanced by effectively address the
properties of its insulation system. The power transformer insulation system weakens as a …