ANN Stabilization of Negative-Sequence Integral Protection of Power Transformers for Turn-to-Turn Winding Faults

被引：0

作者：

Solak, Krzysztof ^{[1
]}

Rebizant, Waldemar ^{[1
]}

Mieske, Frank ^{[2
]}

Boehme, Klaus ^{[2
]}

机构：

[1] Wroclaw Univ Sci & Technol, Fac Elect Engn, Wroclaw, Poland

[2] Siemens AG, Berlin, Germany

来源：

2024 24TH INTERNATIONAL SCIENTIFIC CONFERENCE ON ELECTRIC POWER ENGINEERING, EPE 2024 | 2024年

关键词：

transformer protection; turn-to-turn faults (TTFs); artificial neural network (ANN); transient analysis; stabilization;

D O I：

10.1109/EPE61521.2024.10559578

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The negative-sequence differential current integral principle supplemented with appropriate asymmetry indices is a very sensitive technique for detecting turn-to-turn faults (TTFs) in transformer windings. In this paper, an ANN-based stabilization function for such a protection scheme is introduced. The developed technique offers effective stabilization during transformer energization and recovery inrush after fault clearing, preserving the required sensitivity for TTFs.

引用

页码：300 / 305

页数：6

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