Classification of Faults on Transmission lines using EMTP and Wavelet Multiresolution Analysis (original) (raw)
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Electric Power Systems Research, 2005
This paper proposes a technique that uses Wavelet Multiresolution Analysis (MRA) and Neural Networks for the detection and classification of transients in a power system. Daubechies eight (db 8) wavelet transforms of the phase current on a transmission line fed from both ends are used. The 5 th level output of MRA detail signal of phase current is used to train a perceptron neural network. After training, the perceptron neural network is able to classify all three types of power system transients correctly. All the work is carried out in MATLAB Power System Block set program. The simulation results show that the proposed method is simple, accurate and reliable to automate the procedure of classification of power system transients. This paper is focused on identification of transients but can also be easily extended to other power system solutions such as fault location and so forth.
Transmission Line Fault Classification and Identification using Wavelet Transform
Along with alternative electrical elements, the conductor suffers from the sudden failures thanks to varied faults. Protective of transmission lines is one in every of the vital tasks to safeguard wattage systems. For safe operation of EHVAC conductor systems, the protection system ought to ready to detected, classified, set accurately and cleared is quick as doable to take care of stability within the network. The protecting systems square measure needed to stop the propagation of those faults. The incidence of any conductor faults offers rise to transient condition. Optimal operation of an influence system depends on however a fault location is accurately and quickly set, in order that restoration and maintenance of power is accomplished. Fault detection, fault classification, must be performed employing a quick responsive formula at completely different levels of an influence system. result of things like fault electric resistance, fault origination angle (FIA), and fault distance, that cause disturbances in cable are often countered by ripple multi resolution analysis (MRA). The tactic of fault discrimination projected during this work is on the idea of the three-phase current and voltage waveforms measured throughout the incidence of fault within the power transmission-line. Further, a superior technique, viz. ripple Singular Entropy (WSE) is applied each at conductor and electrical device level that minimizes the noise within the fault transients and is unaffected by the transient magnitude. The projected formula is verified victimization MATLAB/Simulink package and also the obtained results prove that each MRA and WSE based mostly fault detection and classification ways square measure much possible and reliable.
WAVELET TRANSFORM BASED FAULT DETECTION AND CLASSIFICATION IN TRANSMISSION LINE
This paper presents a Wavelet Transform based approach to detect and classify different shunt faults that may occur in transmission lines. The algorithm is based mainly on calculating the RMS values of the wavelet coefficients of current signals at both the ends of the transmission line over a moving window length of half cycle.The current signals are analyzed with 'db4' wavelet to obtain detail coefficients and compared with threshold values to detect and classify the faults. To illustrate effectiveness of proposed technique extensive simulation studies using PSCAD/EMTDC and MATLAB have been carried out for different types of faults considering wide variations in fault resistances, inception angle and loading levels. Fault data generated by PSCAD/EMTDC have been used for fault detection and classification by a MATLAB program. Thus, the proposed technique is well suited for implementation in digital distance protection schemes. and 0.8L, where L is the length of the line. All these locations have proved the accuracy of the proposed technique.
Classification of Transmission Line Faults Using Wavelet Transformer.
International Journal of Engineering Sciences & Research Technology, 2014
In general fault analysis is carried out for a given system assuming various types of fault currents are estimated based on the configurations. It is proposed to implement Discrete Wavelet Transformer (DWT) approach for fault classification once the fault currents are known in a particular location. Daubechies eight (D-8) wavelet transforms of the three phase currents on a transmission line fed from both ends is used. An algorithm is implemented for the classification of faults in the transmission line using MATLAB-SIMULINK software. The advent of large generating stations and highly interconnected power systems makes early fault detection and rapid equipment isolation imperative to maintain system stability. In analyzing the fault are existing methods like Fourier analysis, Short Time Fourier Transforms and Fast Fourier Transforms have the limitations of fixed window and poor resolution. If wavelet transforms are opted, they overcome the above disadvantages, as wavelet transforms employ analysis functions that are localized both in time and frequency domain. It focuses on short-time intervals for high frequency components and long-time intervals for low frequency components. Wavelets have a window that automatically adapts to give appropriate resolution.
Wavelet Feature Based Fault Detection and Classification Technique for Transmission line Protection
In the present scenario, the efficiency of a power system depends on how a fault is accurately detected and classified, so that quick restoration and maintenance of power is accomplished. Fault detection, fault classification, needs to be performed using a fast and responsive algorithm at different levels of a power system. Effect of factors such as fault impedance, fault inception angle (FIA), and fault distance, which cause disturbances in power line can be analyzed by Wavelet based multi resolution analysis (MRA). This paper proposed, a fault detection and classification technique using MRA based on wavelet transform. The present paper also deals with the exploration of advantages and problems related with the proposed fault detection and classification technique. The method of fault detection and classification proposed in this work is based on the three-phase current and voltage waveforms measured during the occurrence of fault in the power transmission-line. The technique proposed in this paper, is verified using MATLAB/Simulink software and the obtained results shows that the wavelet based MRA is a good tool for detection and classification of faults. However it is also shown that the most critical problem related to this technique is the selection of appropriate threshold values for all the three phases. It has been also shown that this technique requires expert hands and knowledge of the system for the selection of proper threshold value.
Asian journal of managerial science/Asian Journal of Managerial Science, 2018
This work proposes a wavelet transform based fault detection and classification technique for the protection of double circuit transmission line. The three phase current signals of both circuits recorded at Bus-1 of the double circuit transmission line power system are used to evaluate the approximate and high frequency detail coefficients at level-1. The proposed scheme is extensively tested using the test system of a 400 kV, 50 Hz double circuit transmission line simulated in MATLAB. The probability of wavelet transform based proposed technique is tested under a extensive deviation of fault parameters, such as fault location, fault type, fault inception time, fault resistance and ground resistance. The test results exemplifies that all types of faults are appropriately detected/ classified.
Identification and Classification of Transmission Line Faults Using Wavelet Analysis
An accurate fault detection and classification is required to transmit power from generating station to various load centers reliably. Transmission line protection is mainly based on circuit breaker active tripping's. This tripping action depends on the voltage and current waveforms during the fault. Wavelet analysis which is a signal processing tool to detect and analyze the fault occurring in transmission line. Discrete wavelet transform (DWT) is used for the analysis of the current waveform during the fault. An approach for transmission line classification also described in this paper. MATLAB/Simulink software is used to illustrate the effectiveness of the proposed approach, an extensive simulation studies have been carried out for different types of faults.
DETECTION OF HIGH-IMPEDANCE FAULTS IN TRANSMISSION LINES USING WAVELET TRANSFORM
A novel approach for detection of High Impedance Faults (HIF) using wavelet transforms is presented in this work. Wavelet functions have been proposed in connection with the analysis of signals, primarily transients in a wide range of applications. The technique used here, is based on using the absolute sum value of coefficients in Multi resolution Signal Decomposition (MSD) based on the Discrete Wavelet Transform (DWT). A fault indicator and a fault criterion are then used to detect the HIF in the transmission line. The technique developed is robust to fault type, fault inception angle, fault resistance, and fault location. A new concept and methodology for HIF in transmission lines is presented. The performance of the proposed technique is tested under a variety of fault conditions on a typical 400KV transmission-line system.
A NOVEL METHOD FOR DETECTION OF ELECTRIC TRANSMISSION LINE FAULTS USING DISCRETE WAVELET TRANSFORM
The power utility companies have been trying to identify and locate three-phase transmission line faults in the minimum possible time in order to prevent economic losses. In the last few decades technology used for power system protection has evolved and shifted from electromechanical devices to solid state and micro-processor based intelligent devices, which require fast and accurate detection of faults in the transmission lines. This paper presents a novel discrete wavelet transform (DWT) based mult i-resolution analysis technique for detection of transmission line faults including and without including ground. A comparative study of all types of faults is presented. A test system having generation, load and transmission line in two parts is modeled in MATLAB/ Simulink environment. The MATLAB programming is used for DWT analysis of the faults.
Identification of Faults on Transmission Lines using Wavelet Technique
2017
The aim of this paper is to understand wavelet technique and identification of fault using wavelet transform. This paper presents high speed fault identification and protection of power system lines based on wavelet transform technique. It is a unique method which is used to detect the location and identification of fault in power system. Faults in power system are single line to ground, double line to ground and three phase faults. In this paper the conventional timeamplitude response is presented and the result shows that wavelet leads to identify the type of fault and its location. The results indicate that wavelet technique is fast compared to time amplitude technique. Keywords—Wavelet, Single Line to Ground fault, Double Line to Ground fault, Three phase fault.