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Waveshape recognition technique to detect current transformer saturation
Author(s) -
Hooshyar Ali,
SanayePasand Majid
Publication year - 2015
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2014.1147
Subject(s) - current transformer , computer science , transformer , pattern recognition (psychology) , electrical engineering , artificial intelligence , voltage , engineering
This study presents a technique to identify current transformer (CT) saturation based on waveshape properties of the CT secondary current. First, a variable‐length window, designated as the symmetry assessment window (SAW), is defined. Certain distinctive features of the distorted and undistorted currents inside the SAW are extracted by defining two variance functions. Using the extracted features, a new criterion is introduced to detect CT saturation. The proposed method is unaffected by fault current characteristics and CT variable parameters, such as CT burden, core remanence and its magnetising curve. One major contribution of this method is allowing cheaper measurement systems for busbar protection by easing the relay CT requirements. Analysis of real power system fault currents in a real‐time manner using a hardware setup is accompanied by PSCAD/EMTDC simulation results to verify the accuracy and high speed of the proposed technique in various conditions.

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