Internal Protection of Transformer Windings Against Transeint Surges Using ZnO Varistors

Authors

  • J Gholinezhad University of Birjand, Iran
  • Z Ejtemaee University of Birjand, Iran
Abstract:

Power system overvoltages due to switching, lightning and other disturbances are the main problem for designers of the power transformers. Once some frequencies of the incoming surges match with some of the natural frequencies of transformer winding, the resonance phenomenon is expected in transformer winding. The resonant overvoltages may destroy the insulation between turns and cause to insulation failure or transmformer damage. In this paper, the transformer winding is modeled based on the lattice diagram concept with variable parameters and the IEEE model of surge arresters has been utilized in order to perform the simulations.  For internal protection of transformer windings, it is assumed that ZnO varistors are installed in parallel to the winding turns. Also the effect of ZnO varistors in reducing the voltage stress across the transformer winding has been investigated for the case of grounded and insolated nutral winding.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

internal protection of transformer windings against transeint surges using zno varistors

power system overvoltages due to switching, lightning and other disturbances are the main problem for designers of the power transformers. once some frequencies of the incoming surges match with some of the natural frequencies of transformer winding, the resonance phenomenon is expected in transformer winding. the resonant overvoltages may destroy the insulation between turns and cause to insul...

full text

Analysis of the Voltage Stresses on Transformer Windings under Different Type of Surges

Standard high voltage lightning and switching impulse tests are performed on Extra High Voltage (EHV) transformers during manufacture to ascertain the breakdown strength of insulation used. But during their service, transformers encounter numerous voltage transients of complex and varying wave shapes which do not necessarily resemble these standard surge type voltages. This paper reports the re...

full text

Internal Fault Classification in Transformer Windings using Combination of Discrete Wavelet Transforms and Back-propagation Neural Networks

This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and neural networks for detection and classification of internal faults in a twowinding three-phase transformer. Fault conditions of the transformer are simulated using ATP/EMTP in order to obtain current signals. The training process for the neural network and fault diagnosis decision are implemented using t...

full text

Transformer protection using MLE approach

This paper proposed a new wavelet based method to identify inrush currents and to distinguish it from power system faults. The proposed algorithm extracts fault and inrush generated transient signals using DWT. Transient current signals at both sides of a transformer are firstly captured. The wavelet transform is a relatively new and powerful tool in the analysis of power transformer transient ...

full text

Quality assessment of ZnO-based varistors by 1/f noise

Noise has been used as a diagnostic tool of surge arrester varistor structures comprising of ZnO grains of various type and size. The physical and electrical properties of the measured samples have been described. In the experimental study, the applied measurement system and the results of noise measurements for the selected structures of varistors designed for the continuous working voltage 28...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 1  issue 2

pages  73- 82

publication date 2016-05-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023