An ANN based algorithm for correction of saturated CT secondary current

Current transformers (CT) provide instrument level current signals to meters and protective relays. Protective relays´ accuracy and performance are directly related to steady state and transient performance of current transformers. Current transformer saturation could lead to protective relay maloperation or even prevent tripping. This paper proposes use of artificial neural networks (ANN) scheme to correct current transformer secondary waveform distortions. The proposed module uses samples of current signals to achieve the inverse transfer function of CT. Simulation studies are performed and influence of changing different parameters are studied. 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 and reliable.