Institut for Forretningsudvikling og Teknologi

Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line

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  • Bhuvnesh Rathore, MBM Engineering College
  • ,
  • Om Prakash Mahela, Rajasthan Rajya Vidyut Prasaran Nigam Ltd.
  • ,
  • Baseem Khan, Hawassa University
  • ,
  • Sanjeevikumar Padmanaban

Fault analysis (detection, classification and location) of transmission network is of great importance in power system. A Wavelet-Alienation-Neural (WAN) technique has been developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network. The detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals. The precise location of faults is carried out by an Artificial Neural Network fed from estimated approximate coefficients computed from voltage and current signals of the same quarter cycle. The robustness of the algorithm is proved with the case studies of varying fault locations, sampling frequency, system parameters, effects of noise, fault incipient angle, different control strategies and fault path impedances.

OriginalsprogEngelsk
TidsskriftIEEE Access
Vol/bind9
Sider (fra-til)13737-13753
Antal sider17
ISSN2169-3536
DOI
StatusUdgivet - jan. 2021
Eksternt udgivetJa

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Publisher Copyright:
© 2013 IEEE.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

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