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Journal ArticleDOI

An artificial neural network based digital differential protection scheme for synchronous generator stator winding protection

A.I. Megahed, +1 more
- 01 Jan 1999 - 
- Vol. 14, Iss: 1, pp 86-93
TLDR
In this article, a new artificial neural network (ANN) based digital differential protection scheme for generator stator winding protection is described. But the scheme only uses two ANNs, one for fault detection and the other for internal fault classification.
Abstract
This paper describes a new artificial neural network (ANN) based digital differential protection scheme for generator stator winding protection. The scheme includes two feedforward neural networks (FNNs). One ANN is used for fault detection and the other is used for internal fault classification. This design uses current samples from the line-side and the neutral-end in addition to samples from the field current. Fundamental and/or second harmonic present in the field current during a fault help the ANN, used for fault detection, to differentiate between generator states (normal, external fault and internal fault states). Results showing the performance of the protection scheme are presented and indicate that it is fast and reliable.

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Citations
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Journal ArticleDOI

Condition Monitoring of Brushless Three-Phase Synchronous Generators With Stator Winding or Rotor Circuit Deterioration

TL;DR: In this article, the authors present experimental and theoretical analyses used to establish electrical features that can be utilized as indicators of armature winding, field winding or rectifier diode deterioration in brushless three-phase synchronous generators before the imperfection progresses to become a ground fault.
Journal Article

Fault location in EHV transmission lines using artificial neural networks

TL;DR: In this paper, a fault detector and locator were trained using various sets of data available from a selected power network model and simulating different fault scenarios (fault types, fault locations, fault resistances and fault inception angles) and different power system data.
Journal ArticleDOI

Development and implementation of an ANN-based fault diagnosis scheme for generator winding protection

TL;DR: In this paper, the authors developed and implemented a new fault diagnosis scheme for generator winding protection using artificial neural networks (ANN) which performs internal fault detection, fault type classifications and faulted phases identification.
Journal ArticleDOI

A New Internal Fault Detection and Classification Technique for Synchronous Generator

TL;DR: Comparative assessment of the proposed scheme in terms of detection time and incorporation of different types of faults with the existing techniques proves its superiority.

Overview and literature survey of artificial neural networks applications to power systems (1992 - 2004)

TL;DR: An extended bibliography of ANN application to power systems is presented, which discusses the ability of ANN to learn complex non-linear relations, and their modular structure, which allows parallel processing.
References
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Journal ArticleDOI

Neural network approach to fault classification for high speed protective relaying

TL;DR: A new approach to fault classification for high speed protective relaying based on the use of neural network architecture and implementation of digital signal processing concepts is presented and its effectiveness in computer simulations on parallel transmission lines is shown.
Journal ArticleDOI

Design, implementation and testing of an artificial neural network based fault direction discriminator for protecting transmission lines

TL;DR: A fault direction discriminator that uses an artificial neural network (ANN) for protecting transmission lines and is suitable for realizing an ultrafast directional comparison protection of transmission lines is described.
Journal ArticleDOI

Improved operation of power transformer protection using artificial neural network

TL;DR: In this paper, an artificial neural network (ANN) was applied to inrush detection and reconstruction of distorted secondary CT currents due to saturation, which improved the reliability of the protection operation.
Journal ArticleDOI

Neural-network based adaptive single-pole autoreclosure technique for EHV transmission systems

TL;DR: The outcome of the study indicates that the neural network approach can be used as an attractive and effective means of realising an adaptive autoreclosure scheme.
Journal ArticleDOI

Digital simulation of a synchronous generator in direct-phase quantities

TL;DR: The paper describes a mathematical model for the simulation of a 3-phase synchronous machine using direct-phase quantities, thus obviating the need for any transformation, and enables a unified approach to be adopted in the study of both symmetrical and asymmetrical conditions.
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