NDLI: A new approach to digital protection of power transformer using support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Shah, A.M. Bhalja, B.R.
Copyright Year	2011
Description	Author affiliation: Department of Electrical Engineering, A. D. Patel Institute of Technology (ADIT), New V. V. Nagar, Anand, India (Shah, A.M.; Bhalja, B.R.)
Abstract	This paper presents a new classification scheme for power transformer which effectively discriminates between internal faults (phase to ground, phase to phase & phase to phase to ground) and non-internal faults (magnetising inrush, external fault & normal condition). The proposed scheme utilizes CT secondary current signals from both sides (LV and HV) of transformer windings as an input. Various signals during internal and external faults, different types of inrush (initial inrush, residual inrush, recovery inrush and sympathetic inrush) and normal/healthy operating states have been generated by modeling the existing 315 MVA power transformer using PSCAD / EMTDC software package. The simulated data set of more than 4600 operating states of transformer has been used in MATLAB for implementation and validation of the proposed scheme. To illustrate the effectiveness of the proposed scheme in terms of classification accuracy, two types of kernel functions of Support Vector Machine (SVM) classifier have been used by the authors. Using optimum kernel function of SVM, the overall fault classification accuracy has been obtained in which only 33% of total data (4650) has been used for training, whereas the remaining data (67%) has been applied for testing.
Starting Page	000011
Ending Page	000014
File Size	522194
Page Count	4
File Format	PDF
ISBN	9781424497881
ISSN	08407789
e-ISBN	9781424497898
e-ISBN	9781424497874
DOI	10.1109/CCECE.2011.6030399
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-08
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Surges Kernel Surge protection Power transformers Support vector machines Polynomials Accuracy waveform identification Power transformer protection support vector machine
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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