Enhancement of auxiliary overcurrent protection in transformers using novel feature extraction algorithms

Shyh-Jier Huang, Hsing Ho Wan

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, a feature extraction approach embedded with wavelet computation is applied to enhance the auxiliary overcurrent protection, by which the transformer inrush current discriminating from internal fault can be achieved. This proposed method starts with a feature extraction of acquired differential current waveform following the execution of wavelet computation. Then, the extracted features are expressed as a group of quantitative turning points to serve as indicators for overcurrent recognition. It is found that by this way of design, the inrush current can be effectively discriminated from the fault current. To validate the effectiveness of the method, it was applied to various simulated scenarios as well as employed to inspect a 60âMVA, 161/23.9âkV transformer connected to a 161âkV power system in Taiwan. Test results help support the feasibility of the method for the application considered.

Original languageEnglish
Pages (from-to)1153-1162
Number of pages10
JournalEuropean Transactions on Electrical Power
Volume20
Issue number8
DOIs
Publication statusPublished - 2010 Nov 1

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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