A Comparison Study of Learning Algorithms for Estimating Fault Location

2017 ◽  
Vol 6 (2) ◽  
pp. 464 ◽  
Author(s):  
Mimi Nurzilah Hashim ◽  
Muhammad Khusairi Osman ◽  
Mohammad Nizam Ibrahim ◽  
Ahmad Farid Abidin ◽  
Ahmad Asri Abd Samat
Keyword(s):  
Transmission Lines ◽  
Conjugate Gradient ◽  
Goodness Of Fit ◽  
Fault Location ◽  
Discrete Wavelet ◽  
Training Algorithm ◽  
System Protection ◽  
Fault Resistance ◽  
Quasi Newton ◽  
Selection Of

Fault location is one of the important scheme in power system protection to locate the exact location of disturbance. Nowadays, artificial neural networks (ANNs) are being used significantly to identify exact fault location on transmission lines. Selection of suitable training algorithm is important in analysis of ANN performance. This paper presents a comparative study of various ANN training algorithm to perform fault location scheme in transmission lines. The features selected into ANN is the time of first peak changes in discrete wavelet transform (DWT) signal by using faulted current signal acted as traveling wave fault location technique. Six types commonly used backpropagation training algorithm were selected including the Levenberg-Marquardt, Bayesian Regulation, Conjugate gradient backpropagation with Powell-Beale restarts, BFGS quasi-Newton, Conjugate gradient backpropagation with Polak-Ribiere updates and Conjugate gradient backpropagation with Fletcher-Reeves updates. The proposed fault location method is tested with varying fault location, fault types, fault resistance and inception angle. The performance of each training algorithm is evaluated by goodness-of-fit (R<sup>2</sup>), mean square error (MSE) and Percentage prediction error (PPE). Simulation results show that the best of training algorithm for estimating fault location is Bayesian Regulation (R<sup>2 </sup>= 1.0, MSE = 0.034557 and PPE = 0.014%).

scholarly journals A Novel Single-Terminal Fault Location Method for AC Transmission Lines in a MMC-HVDC-Based AC/DC Hybrid System

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2066 ◽  
Author(s):  
Shimin Xue ◽  
Junchi Lu ◽  
Chong Liu ◽  
Yabing Sun ◽  
Baibing Liu ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Fault Location ◽  
Control Strategies ◽  
Linear Regression Analysis ◽  
Location Method ◽  
Fault Resistance ◽  
Ac Networks ◽  
Minimum Residual ◽  
Ac Transmission ◽  
Location Methods

Accurate and reliable fault location method for alternating current (AC) transmission lines is essential to the fault recovery. MMC-based converter brings exclusive non-linear characteristics to AC networks under single-phase-to-ground faults, thus influencing the performance of the fault location method. Fault characteristics are related to the control strategies of the converter. However, the existing fault location methods do not take the control strategies into account, with further study being required to solve this problem. The influence of the control strategies to the fault compound sequence network is analyzed in this paper first. Then, a unique boundary condition that the fault voltage and negative-sequence fault current merely meet the direct proportion linear relationship at the fault point, is derived. Based on these, a unary linear regression analysis is performed, and the fault can be located according to the minimum residual sum function principle. The effectiveness of the proposed method is verified by PSCAD/EMTDC simulation platform. A large number of simulation results are used to verify the advantages on sampling frequency, fault resistance, and fault distance. More importantly, it provides a higher ranging precision and has extensive applicability.

scholarly journals Comparison of Various Mother Wavelets for Fault Classification in Electrical Systems

2020 ◽  
Vol 10 (4) ◽  
pp. 1203 ◽  
Author(s):  
Chaichan Pothisarn ◽  
Jittiphong Klomjit ◽  
Atthapol Ngaopitakkul ◽  
Chaiyan Jettanasen ◽  
Dimas Anton Asfani ◽  
...  
Keyword(s):  
Power System ◽  
Fault Location ◽  
Classification Algorithm ◽  
Fault Classification ◽  
Discrete Wavelet ◽  
Mother Wavelet ◽  
System Protection ◽  
Fault Type ◽  
Zero Sequence ◽  
Mother Wavelets

This paper presents a comparative study on mother wavelets using a fault type classification algorithm in a power system. The study aims to evaluate the performance of the protection algorithm by implementing different mother wavelets for signal analysis and determines a suitable mother wavelet for power system protection applications. The factors that influence the fault signal, such as the fault location, fault type, and inception angle, have been considered during testing. The algorithm operates by applying the discrete wavelet transform (DWT) to the three-phase current and zero-sequence signal obtained from the experimental setup. The DWT extracts high-frequency components from the signals during both the normal and fault states. The coefficients at scales 1–3 have been decomposed using different mother wavelets, such as Daubechies (db), symlets (sym), biorthogonal (bior), and Coiflets (coif). The results reveal different coefficient values for the different mother wavelets even though the behaviors are similar. The coefficient for any mother wavelet has the same behavior but does not have the same value. Therefore, this finding has shown that the mother wavelet has a significant impact on the accuracy of the fault classification algorithm.

Fault Location of Transmission Line Based on Discrete Wavelet Transforms

2011 ◽  
Vol 121-126 ◽  
pp. 1269-1273
Author(s):  
Wen Xiu Tang ◽  
Mo Zhang ◽  
Ying Liu ◽  
Xu Fei Lang ◽  
Liang Kuan Zhu
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Wavelet Transforms ◽  
Fault Location ◽  
Short Circuit ◽  
Signal Transmission ◽  
Transient Signal ◽  
Discrete Wavelet ◽  
Novel Method ◽  
Non Stationary Signal

In this paper, a novel method is investigated to detect short-circuit fault signal transmission lines in strong noise environment based on discrete wavelet transform theory. Simulation results show that the method can accurately determine the fault position, can effectively analyze the non-stationary signal and be suitable for transmission line fault occurred after transient signal detection. Furthermore, it can effectively eliminate noise effects of fault signal so as to realize the transmission lines of accurate fault.

scholarly journals Short Circuit Faults Identification and Localization in IEEE 34 Nodes Distribution Feeder Based on the Theory of Wavelets

2018 ◽  
Vol 14 (1) ◽  
pp. 65-79
Author(s):  
Sara Authafa
Keyword(s):  
Fault Location ◽  
Short Circuit ◽  
Circuit Breaker ◽  
Discrete Wavelet ◽  
Detection Scheme ◽  
Protection Scheme ◽  
System Protection ◽  
Fault Type ◽  
Distribution Feeder ◽  
System States

In this paper a radial distribution feeder protection scheme against short circuit faults is introduced. It is based on utilizing the substation measured current signals in detecting faults and obtaining useful information about their types and locations. In order to facilitate important measurement signals features extraction such that better diagnosis of faults can be achieved, the discrete wavelet transform is exploited. The captured features are then utilized in detecting, identifying the faulted phases (fault type), and fault location. In case of a fault occurrence, the detection scheme will make a decision to trip out a circuit breaker residing at the feeder mains. This decision is made based on a criteria that is set to distinguish between the various system states in a reliable and accurate manner. After that, the fault type and location are predicted making use of the cascade forward neural networks learning and generalization capabilities. Useful information about the fault location can be obtained provided that the fault distance from source, as well as whether it resides on the main feeder or on one of the laterals can be predicted. By testing the functionality of the proposed scheme, it is found that the detection of faults is done fastly and reliably from the view point of power system protection relaying requirements. It also proves to overcome the complexities provided by the feeder structure to the accuracy of the identification process of fault types and locations. All the simulations and analysis are performed utilizing MATLAB R2016b version software package.

scholarly journals Parameter-Free Fault Location Algorithm for Distribution Network T-Type Transmission Lines

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1534 ◽  
Author(s):  
Wang ◽  
Yun
Keyword(s):  
Distributed Generation ◽  
Transmission Lines ◽  
Fault Location ◽  
Trust Region ◽  
Distribution Networks ◽  
Trust Region Algorithm ◽  
Fault Resistance ◽  
Fault Type ◽  
Location Algorithm ◽  
Data Error

T-type transmission lines have been increasingly used in distribution networks because of the distributed generation integration, but inaccurate line parameters will cause significant error in the results of most existing fault location algorithms for this kind of line. In order to improve the precision, this paper proposes a new fault location algorithm taking line parameters as unknowns. The fault is assumed to occur on each section, and corresponding ranging equations can be built based on one set of three-terminal post-fault synchronous measurements, without using line parameters as inputs. Then, more sets of measurements are utilized to increase the redundancy of equations to resist the influence of data error. The reliable trust-region algorithm is used to solve each group of equations, but only equations of the assumed faulty section with the actual fault point can give the reasonable solutions, accordingly identifying the fault point. The performance of the proposed method is thoroughly investigated with MATLAB/Simulink. The results indicate that the algorithm has a high accuracy and is basically unaffected by fault position, fault resistance, unbalanced fault type, line parameter, and data error.

scholarly journals Application of wavelet transforms to fault location of teed branch transmission lines

2013 ◽  
Vol 16 (4) ◽  
pp. 92-103
Author(s):  
Binh Xuan Nguyen ◽  
Tu Phan Vu
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Wavelet Transforms ◽  
Wavelet Transformation ◽  
Fault Location ◽  
Discrete Wavelet ◽  
System Operation ◽  
Transient Wave ◽  
New Approach ◽  
High Voltage Transmission Line

Fault location identification of highvoltage transmission line, especially threeterminal lines, is an important issue in power system operation. In this paper, we investigate the application of wavelet transform to locate the fault position of teed circuits high-voltage transmission line. The components of the transient wave at terminals of the faulted line are simulated by MATLAB Simulink. These components will be decomposed into wavelet coefficients by using discrete wavelet transformation. The proposed approach has the advantages that gives the exact time of transient wave for traveling from fault position to the terminals of the lines. To evaluate the applicability and effectiveness of this new approach, we have applied the proposed method to a threeterminal transmission line in reference [9] and the actual transmission line 110kV O Mon – Sa Dec – Binh Minh.

scholarly journals Fault Location in the Transmission Network Based on Extraction of Fault Components Using Wavelet Transform

2019 ◽  
Vol 19 (2) ◽  
pp. 1-9 ◽  
Author(s):  
Majid Dashtdar ◽  
Masoud Dashtdar
Keyword(s):  
Wavelet Transform ◽  
Transmission Line ◽  
Fault Location ◽  
Current Data ◽  
Signal Decomposition ◽  
Discrete Wavelet ◽  
Transmission Network ◽  
Fault Resistance ◽  
Before And After ◽  
Design Characteristics

AbstractIn this paper, a Discrete Wavelet Transform (DWT) has been utilized for processing the current signal in order to fault-location evaluation in network transmission using pre-fault and post-fault current data of both the terminals of a transmission line. In fact, the basis of the work is based on the information recorded before the fault at the end of the line and after the fault at the beginning of the line received by the relay. Obviously, high-frequency components are created at the time of the fault, which is a way of extracting these components using a wavelet transform. In this design, characteristics extorted from synchronous recording of three-phase current signals at the two terminals using DWT. In the following, can accurately estimate the exact location of the fault in the transmission network by extraction and subtracting of the minimum and maximum components of the DWT approximate and detail components of the signal before and after the fault (pre-fault and post-fault). The simulation results reveal that the minimum and maximum extracted components are highly dependent on the fault resistance. Hence, due to increase the fault resistance, the level of signal decomposition has to be increased so that the algorithm is not compromised. Eventually, the proposed method is tested on the transmission network of 735 kV at different distances of the transmission line, which indicates that the proposed algorithm can accurately estimate the fault distance, depending on the type of fault (including low-impedance and high-impedance fault) by changing the signal decomposition level.

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