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Neural network-based technique used for recovery the CCVT primary signal

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5 Author(s)
S. M. Saleh ; Saber Mohamed Saleh Salem is with Ministry of Electricity and Energy, Egypt ; E. M Aboul-Zahab ; E. Tag Eldin ; D. K. Ibrahim
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The coupling capacitor voltage transformers transient response during faults can cause protective relay mal-operation or even prevent tripping. This paper presents the CCVT transient response errors and the use of artificial neural network (ANN) to correct the CCVT secondary waveform distortion. In this paper, an ANN program is developed to recover the primary voltage from the distorted secondary voltage. The ANN is trained to achieve the inverse transfer function of the coupling capacitor voltage transformer (CCVT), which provides a good estimate of the true primary voltage from the distorted secondary voltage. The neural network is developed and trained using MATLAB simulations. The accuracy of the simulation program is confirmed by comparison of its response with that of the target value from the simulation data.

Published in:

2009 IEEE Power & Energy Society General Meeting

Date of Conference:

26-30 July 2009