This paper presents an artificial neural network (ANN) based scheme for fault identification in power transformer protection. The proposed scheme is featured by the application of ANN to identifying system patterns, the unique choice of harmonics of positive sequence differential currents as ANN inputs, the effective handling of current transformer (CT) saturation with an ANN based approach, an...

Transformer inrush currents are high-magnitude, harmonic-rich currents generated when transformer cores are driven into saturation during energization. These currents have undesirable effects, including potential damage or loss-of-life to the transformer, protective relay misoperation, and reduced power quality on the system. Controlled transformer switching can potentially eliminate these tran...

This paper presents a novel current transformer (CT) saturation detection approach based on Gaussian Mixture Models (GMMs). High accuracy is the advantage of this method. GMMs are trained with secondary current of CT. The appropriate performance of the proposed method is tested by simulation of different fault conditions in PSCAD/EMTDC software. The results show that the trained GMMs can succes...

The development of power electrical systems causes attention to accuracy of protection elements and measurement values. So we need some new measuring devices with high accuracy for power transmission lines. One of these devices is Optical Current Transformer (OCT). Optical current transformers are suitable for power system protection and can replace the magnetic current transformers. In this pa...

When current transformer is saturated, mainly due to the presence of an exponentially decaying DC component in fault current, its secondary has a distinctive distorted waveform which significantly differs from primary (true) waveform. It leads underestimation value calculated by relay protection compared true value. Thus, turn, results trip time delay or even devices operation failure, since se...

Malfunctions in relay protection devices are predominantly caused by current transformer (CT) saturation which produces distortion measurements and disturbances power system protection. The development of deep learning is on the rise recently because its robustness. This study presents a CT detection where secondary becomes distorted. proposed scheme offers wide range consists moving-window tec...

A bond graph model of an electrical transformer including the nonlinear saturation is presented. A nonlinear observer for the transformer based on multivariable circle criterion in the physical domain is proposed. In order to show the saturation and hysteresis effects on the electrical transformer, simulation results are obtained. Finally, the paper describes that convergence of the estimates t...