Correction of capacitive voltage transformer distorted secondary voltages using artificial neural networks

This paper presents the use of artificial neural networks (ANN) to correct capacitive voltage transformer secondary waveform distortions. Voltage transformers provide instrument level voltage signals to protective relays. A capacitive voltage transformer transient can cause protective relay misoperation. The proposed module uses samples of voltage signals to achieve the inverse transfer function of the CVT. Simulation studies are performed on the influence of changing different parameters. Details of the design procedure and the results of performance studies with the proposed method are given in the paper. Performance studies results show that the proposed algorithm is accurate.