Title of article :
Internal Fault Detection, Location, and Classification in Stator Winding of the Synchronous Generators Based on the Terminal Voltage Waveform.
Author/Authors :
Fayazi, M Dept. of Electrical Engineering - Shahid Beheshti University, Tehran , Haghjoo, F Dept. of Electrical Engineering - Shahid Beheshti University, Tehran
Abstract :
In this paper, a novel method is presented for detection and classification of the faulty
phase/region in the stator winding of synchronous generators on the basis of the resulting harmonic
components that appear in the terminal voltage waveforms. Analytical results obtained through Decision
Tree (DT) show that the internal faults are not only detectable but also they can be classified and
the related region can be estimated. Therefore, this scheme can be used to protect the synchronous
generators against the various internal faults. Fuji technical documents and data sheets for an actual
salient pole synchronous generator (one unit of an Iran’s hydroelectric power plants) are used for the
modeling. Simulations in Maxwell software environment are presented. All the related parameters, such
as B-H curve, unsymmetrical air gap and pole saliency, slot-teeth effect, and other actual parameters, are
considered to obtain a comprehensive model to generate acceptable terminal voltage waveforms without
any simplification.
Keywords :
Synchronous Generator , Internal Faults , Turn-Turn Faults , Phase To Ground Faults , Detection , Classification , Location , Harmonic Components , Decision Tree
Journal title :
AUT Journal of Electrical Engineering