Current Transformer Saturation Detection Using Gaussian Mixture Models
نویسندگان
چکیده
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 successfully detect CT saturation with high accuracy.
منابع مشابه
Modelling transformer core joints using Gaussian models for the magnetic flux density and permeability
Simple equivalent permeability and reluctance models are obtained for the transformer core joints from the analysis of the magnetic flux. It is shown that the flux variations in the joint zone can be fitted with simple Gaussian expressions suitable for transformer design purposes. These models are derived from 2D and 3D finite element simulations. The magnetic flux distribution in the transform...
متن کاملSpeech Enhancement Using Gaussian Mixture Models, Explicit Bayesian Estimation and Wiener Filtering
Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equatio...
متن کاملArtificial Intelligence Based Approach for Identification of Current Transformer Saturation from Faults in Power Transformers
Protection systems have vital role in network reliability in short circuit mode and proper operating for relays. Current transformer often in transient and saturation under short circuit mode causes mal-operation of relays which will have undesirable effects. Therefore, proper and quick identification of Current transformer saturation is so important. In this paper, an Artificial Neural Network...
متن کاملCurrent Transformer Saturation Detection By Wavelet Transform and Compensation By Newton’s Forward Interpolation
-Protective systems require a faithful reproduction of primary current on the Current Transformer (CT) secondary side. Saturation is a common problem in a steel core CT. Saturation problem causes dreadful effects in the protection systems. This paper presents a simple solution towards detection and compensation of current transformer saturation problems. This paper describes a method in which C...
متن کاملDesigning of a New Transformer Ground Differential Relay Based on Probabilistic Neural Network
Low- impedance transformer ground differential relay is a part of power transformer protection system that is employed for detecting the internal earth faults. This is a fast and sensitive relay, but during some external faults and inrush current conditions, may be exposed to maloperation due to current transformer (CT) saturation. In this paper, a new intelligent transformer ground differentia...
متن کامل