Saber M. Saleh

Unsynchronized Fault-Location Scheme for Nonlinear HIF in Transmission Lines

The general aim of this paper is to develop an accurate fault-location scheme that can solve the problems affecting the accuracy of the existing conventional fault locators achieving easier maintenance and restoration time reduction as well as economical aims. This consequently helps to fit the new deregulation policies and competitive marketing. This investigation successfully applies zero-sequence current (3I 0) from the two terminals for earth high impedance fault (HIF) location, or negative-sequence currents from the two terminals of one faulted phase for line-to-line fault location. The HIF location is determined within only a maximum time of one cycle. The proposed scheme is insensitive to variations of different parameters, such as fault type, HIF behavior, wide-range transmission-line parameters variation, and fault inception angle. Staged fault testing results demonstrate that the proposed algorithm has feasible performance.

High Impedance Faults Detection in EHV Transmission Lines Using the Wavelet Transforms

High impedance faults (HIFs) are difficult to detect by overcurrent protection relays. This paper presents an ATP/EMTP fault simulations studies based algorithm for high impedance fault detection in extra high voltage transmission line. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIF. The discrete wavelet transform (DWT) based analysis, yields three phase voltage in the high frequency range which are fed to a classifier for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of the high frequency signal generated over one cycle and shifting one sample. A HIF model of distribution is modified for EHV transmission lines. Characteristics of the proposed fault detection scheme are analyzed by extensive simulation studies that clearly reveal that the proposed method can accurately detect HIFs in the EHV transmission lines.

High impedance fault detection in EHV series compensated lines using the wavelet transform

Coupling capacitive voltage transformers behave as low pass filters which reject the high frequencies associated with voltage signals, so the effect of HIF on voltage signals is neglected. In addition, using series capacitors (SCs) equipped with metal oxide varistors (MOVs) increases the protection relaying problems and complicates the trip decision. This paper presents a high impedance fault detection algorithm for maximum trip time required of 3/4 cycle. The proposed scheme implemented on two different models of HIF in extra high voltage double-ended transmission lines with series capacitors at the middle of the line. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIFs. The discrete wavelet transform (DWT) based analysis, yields three phase voltages in high frequency range which are fed to Clarkes transformation to produce ground and aerial modes voltage components for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of high frequency signals generated over one cycle and shifts one sample. Characteristics of the proposed scheme are fully analyzed by extensive ATP/EMTP simulation studies that clearly reveal that the proposed method can accurately detect HIFs in EHV transmission lines and does not affected by different fault conditions such as fault distance and fault inception angle.

High impedance fault detection in mutually coupled double-ended transmission lines using high frequency disturbances

Coupling Capacitor Voltage Transformer (CCVT) secondary voltages, normally applied to conventional schemes, do not comprise appropriate information for schemes that operate on high frequency fault generated transients. However it is possible to capture the required travelling wave information contained in fault transients using a high frequency tap from a CCVT. This paper presents an ATP/EMTP fault simulations studies based algorithm for half cycle high impedance fault detection. The proposed scheme implemented on two different models of HIF in extra high voltage mutually coupled double- ended transmission lines. The scheme recognizes the distortion of the voltage waveforms caused by the arcs usually associated with HIFs. The high pass filter tap yields three phase voltage in the high frequency range which are fed to Clarkes transformation to decouple the traveling waves of the mutually coupled lines and produces ground mode and aerial modes voltage components to the classifier for pattern recognition. The classifier is based on an algorithm that uses recursive method to sum the absolute values of the high frequency signal generated over one cycle and shifting one sample. Characteristics of the proposed fault detection scheme are analyzed by extensive simulation studies that clearly reveal that the proposed method can accurately detect HIFs in the EHV transmission lines within only half a cycle from the instant of fault occurrence. The reliability of the proposed scheme does not affected by different fault conditions such as fault distance and fault inception angle.

Unsymmetrical High-impedance Earth Fault Central Relay for Transmission Networks

Abstract This article presents a central relay based on wavelet transform for high-impedance earth fault detection, zone identification, location, and classification in part of the Egyptian 500-kV transmission network. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with high-impedance earth faults for unsymmetrical faults, whether single line to ground fault The proposed discrete wavelet transform based analysis yields three phase voltages in the high-frequency range and zero-sequence root mean square current in the low-frequency range that are fed to fault detection and location algorithms, respectively, while phase currents in the high-frequency range are fed to the classification algorithm. The fault detection algorithm is based on the recursive method to sum the absolute values of the high-frequency signal generated over one voltage cycle, while the zone identification and fault location algorithms use unsynchronized zero-sequence root mean square currents. On the other hand, the fault classification algorithm is based on the currents in the high-frequency range for one-side data of the faulted line at the local relay after the detection and location process. Characteristics of the proposed central relay are analyzed by extensive simulation studies that clearly reveal that the proposed relay can accurately determine the network faulted line and can calculate fault distance with an acceptable error that does not exceed 5%. All simulation studies are carried out using a high-impedance earth fault model of a distribution system that is modified for transmission systems. An available real high-impedance earth fault case study is used to check the performance of the fault classification algorithm to classify phase and earth faults.

High-impedance fault detection in EHV transmission lines

The automatic detection of high impedance faults (HIFs) on transmission systems has been one of the most persistent and difficult problems facing utilities as a major safety concern. The paper presents two approaches to HIF detection in extra high voltage transmission lines. Both schemes analyze the nature and dynamics of the arc phenomenon related to HIFs using voltage waveforms at the relaying point. The first scheme is based on discrete wavelet transform (DWT) analysis while the second analyzes the three phase voltages using high frequency tap of the coupling capacitor voltage transformers. To ensure development of reliable algorithms, an accurate modeling of HIF is utilized with its complex characteristics such as buildup, shoulder as well as nonlinearity and asymmetry. Results of computer simulation using ATP/EMTP on 345 kV transmission line system clearly reveal that each of the proposed methods can accurately detect HIFs in the EHV transmission lines as well as their ability to discriminate clearly between HIFs and various switching conditions.

Diagnostic techniques used in power transformer turn to turn faults identification based on Sweep Frequency Response Analysis (SFRA)

Sweep Frequency Response Analysis (SFRA) is a technique which is recently used to detect the malfunction operation of electrical power transformers. This paper suggested three diagnostic techniques used to interpret SFRA for power transformer fault turn to turn identification. Namely they are Chinese standard DL-911/2004, Cross-Correlation Coefficient Factor technique (CCF) and R2 relative factor technique. The diagnostic techniques are used to identify the transformer turn to turn short circuit faults at high voltage and low voltage sides. The results of diagnostic techniques used in power transformer fault identification; indicate that the used method can accurately identify the transformer faults.

Study of genetic algorithm performance through design of multi-step LC compensator for time-varying nonlinear loads

Display OmittedProposed GA based techniques for multi-step LC compensator Performance of GA is related to processing time and number of generations required for convergence and the convergence itself.GA is affected by choosing its parameters and implementation techniques through designing the multi-step LC.The performance of GA is widely affected by choosing its parameters and implementation techniques. Genetic algorithm (GA) is a search mechanism simulating the natural selection and population genetics. The performance of GA is related to processing time and the number of generations required for convergence and the convergence itself. This article studies how the performance of GA is affected by choosing its parameters and implementation techniques through designing the multi-step LC based on performance criteria; maximizing the power factor ( P F ), minimizing the transmission loss ( T L ), or minimizing the voltage total harmonic distortion ( V T H D ). The multi-step LC compensator consists of switchable units thus assuming that a single unit is not sufficient to ensure satisfactory results. GA is used to estimate that steps while holding the performance quantities at the corresponding desired values and constraining the compensator values which would create resonance. The contribution of the proposed procedure is demonstrated in examples taken from previous publications. Finally, simulated results show the performance of GA is widely affected by choosing its parameters and implementation techniques and hence it could be improved.

Neural network-based technique used for recovery the CCVT primary signal

The coupling capacitor voltage transformers transient response during faults can cause protective relay mal-operation or even prevent tripping. This paper presents the CCVT transient response errors and the use of artificial neural network (ANN) to correct the CCVT secondary waveform distortion. In this paper, an ANN program is developed to recover the primary voltage from the distorted secondary voltage. The ANN is trained to achieve the inverse transfer function of the coupling capacitor voltage transformer (CCVT), which provides a good estimate of the true primary voltage from the distorted secondary voltage. The neural network is developed and trained using MATLAB simulations. The accuracy of the simulation program is confirmed by comparison of its response with that of the target value from the simulation data.