Monday, November 29, 2010

On-line Fault Detection of Transmission Line Using Artificial Neural Network

S. M. El Safty, H. A. Ashour, H.El Dessouki and M. El Sawaf
 Abstract:
As the voltage and current waveforms are deformed due to transient during faults, their pattern changes according to the type of fault, The Artificial Neural Network  (ANN) can then be used for fault detection due to its  distinguished behavior in pattern recognition. In order to  minimize the structure and timing of the ANN, preprocessing of  the voltage and current waveforms was done. The data delivered from a simulated power system using PSCAD (EMTP with cad  system) was used for training and testing the ANN. An  experimental setup, consists of a 3 phase power supply module and transmission line module, is utilized. A set of signal  conditioning circuits is designed and implemented in order to transfer data to a PC which is used as an on-line relay for fault  detection. This is done via a data acquisition card (CIODAS1602/   12). The Matlab program captures and processes real  data for training the ANN. Applying different types of faults for  testing the system, right tripping action was taken and the type  of fault was correctly identified. The suggested artificial neural  network algorithm has been found simple and effective hence  could be implemented in practical application.

Sunday, November 28, 2010

Murari Mohan Saha • Jan Izykowski Eugeniusz Rosolowski : Fault Location on Power Networks

Preface
Electric power systems, which are growing in size and complexity, will be always  exposed to failures of their components. In the case of a failure, the faulty element  should be disconnected from the rest of the sound system in order to minimize the damage of the faulty element and to remove the emergency situation for the entire system. This action should be taken fast and accurately and is accomplished by a set of automatic protective relaying devices. At the same time, when a fault occurs on a line (distribution or transmission), it is very important for the  utility to identify the fault location as quickly as possible for improving the  service   reliability.     If a fault location cannot be identified quickly and this produces prolonged line outage during a period of peak load, severe economic losses  may  occur    and   reliability

Saturday, November 27, 2010

JOURNAL FAULT LOCATION ON TRANSMISSION OVERHEAD LINE (ABSTRACT)

        1. Moghadas, A.A., Shadaram, M., 2010. Fiber Bragg Grating Sensor for Fault Detection in Radial and Network Transmission Lines. Sensors 10, 9407-9423.
Abstract: In this paper, a fiber optic based sensor capable of fault detection in both radial and network overhead transmission power line systems is investigated. Bragg wavelength shift is used to measure the fault current and detect fault in power systems. Magnetic fields generated by currents in the overhead transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). The Fiber Bragg interrogator senses the reflected FBG signals, and the Bragg wavelength shift is calculated and the signals are processed. A broadband light source in the control room scans the shift in the reflected signal. Any surge in the magnetic field relates to an increased fault current at a certain location. Also, fault location can be precisely defined with an artificial neural network (ANN) algorithm. This algorithm can be easily coordinated with other protective devices. It is shown that the faults in the overhead transmission line cause a detectable wavelength shift on the reflected signal of FBG and can be used to detect and classify different kind of faults. The proposed method has been extensively tested by simulation and results confirm that the proposed scheme is able to detect different kinds of fault in both radial and network system

JOURNAL FAULT DETECTION ON TRANSMISSION ( ABSTRACT )


      1.   Moghadas, A.A., Shadaram, M., 2010. Fiber Bragg Grating Sensor for Fault Detection in Radial and Network Transmission Lines. Sensors 10, 9407-9423.
Abstract: In this paper, a fiber optic based sensor capable of fault detection in both radial and network overhead transmission power line systems is investigated. Bragg wavelength shift is used to measure the fault current and detect fault in power systems. Magnetic fields generated by currents in the overhead transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). The Fiber Bragg interrogator senses the reflected FBG signals, and the Bragg wavelength shift is calculated and the signals are processed. A broadband light source in the control room scans the shift in the reflected signal. Any surge in the magnetic field relates to an increased fault current at a certain location. Also, fault location can be precisely defined with an artificial neural network (ANN) algorithm. This algorithm can be easily coordinated with other protective devices. It is shown that the faults in the overhead transmission line cause a detectable wavelength shift on the reflected signal of FBG and can be used to detect and classify different kind of faults. The proposed method has been extensively tested by simulation and results confirm that the proposed scheme is able to detect different kinds of fault in both radial and network system

JOURNAL EARLY DETECTION ON TRANSMISSION

.                           Mark, W. D., Lee, H., Patrick, R., and Coker, J. D., Mechanical Systems and Signal Processing 24(8), 2807 (2010).
Ref Type: Journal
Ref ID: 1
Abstract: Fixed transducers often are used to monitor meshing gear pairs in order to detect tooth damage A simple frequency-domain damage-detection algorithm is suggested for very early detection of such damage. Ratios of rotational-harmonic amplitudes computed from before and after potential damage are utilized to eliminate effects of transducer and structural-path-caused amplitude changes between tooth-meshing location and transducer output, to minimize attenuating effects of multiple-tooth contact, and thereby, to approximately equally weight rotational-harmonic amplitudes over a wide range of harmonics. Statistical averaging of absolute values of logarithmic ratios of rotational-harmonic amplitudes is used to minimize fluctuations caused by multiple-tooth contact and manufacturing errors on the subject gear. Synchronous averaging is employed to minimize effects of noise and manufacturing errors on the mating gear. Time-windowing tailored to contact ratios of mating gears is utilized to isolate individual tooth locations. Resultant windowing effects on availability of useful rotational harmonics are analyzed. Application of the algorithm to detection of seeded bending-fatigue faults on a planetary ring-gear tooth indicates that successful detections were achieved. (C) 2010 Elsevier Ltd. All rights reserved

Electrical Fault Detection in Power Systems by ANN structures

  MICHAŁ SZEWCZYK ADRIAN HALINKA Institute of Power Systems and Control  Silesian University of Technology ul. B. Krzywoustego 2 POLAND

Abstract: Nowadays used power system protections are worked out to get the properties of digital technology. This improves the reliability and functionality of protection devices by increasing the number of possible information received from protected object,  self testing, monitoring and logging the events. However the decision parts of such systems are still based on commonly used principles defined already for analog protection devices. The exceeding of threshold value cause the generation of respectively logical signals (mainly “0” and “1”) which are adequately interpreted as “normal” and “faulty” conditions of protected object. Such approach to making a decision, considerably narrow down the area of recognized states. One of the methods to define of decision system, not based on the above mentioned principle, is the use of artificial neural networks (ANN). In the paper a model of decision system based on ANN, will be shown. As protected object the generator-transformer unit has been taking into consideration. The range of detected faults are initially narrows to faults of electromagnetic character (three-phase, two-phase, two-phase to earth and one-phase faults) within the generator – unit transformer – high voltage transmission line configuration.

Keywords: Artificial neural network, power system protection, electrical fault detection, generator-transformer unit.