Fault Location and Fault Type Recognition of Power System Based on Wavelet Transform

2019 ◽  
Author(s):  
Xiaotian Tang ◽  
Zhenyuan Zhang ◽  
Qi Huang ◽  
Yan Gong
Keyword(s):  
Wavelet Transform ◽  
Power System ◽  
Fault Location ◽  
Fault Type

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.

scholarly journals Fault Location Based on Synchronized Measurements: A Comprehensive Survey

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
A. H. Al-Mohammed ◽  
M. A. Abido
Keyword(s):  
Wavelet Transform ◽  
Metal Oxide ◽  
Power System ◽  
Transmission Line ◽  
High Frequency ◽  
Fault Location ◽  
Future Research ◽  
Comprehensive Survey ◽  
Synchronized Measurements ◽  
Transmission And Distribution

This paper presents a comprehensive survey on transmission and distribution fault location algorithms that utilize synchronized measurements. Algorithms based on two-end synchronized measurements and fault location algorithms on three-terminal and multiterminal lines are reviewed. Series capacitors equipped with metal oxide varistors (MOVs), when set on a transmission line, create certain problems for line fault locators and, therefore, fault location on series-compensated lines is discussed. The paper reports the work carried out on adaptive fault location algorithms aiming at achieving better fault location accuracy. Work associated with fault location on power system networks, although limited, is also summarized. Additionally, the nonstandard high-frequency-related fault location techniques based on wavelet transform are discussed. Finally, the paper highlights the area for future research.

scholarly journals Fault Detection of the Power System Based on the Chaotic Neural Network and Wavelet Transform

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Zuoxun Wang ◽  
Liqiang Xu
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Fault Detection ◽  
Power System ◽  
Fault Location ◽  
Detection Algorithm ◽  
Travelling Wave ◽  
Discrete Wavelet ◽  
Chaotic Neural Network ◽  
Transition Resistance

The safety and stability of the power supply system are affected by some faults that often occur in power system. To solve this problem, a criterion algorithm based on the chaotic neural network (CNN) and a fault detection algorithm based on discrete wavelet transform (DWT) are proposed in this paper. MATLAB/Simulink is used to establish the system model to output fault signals and travelling wave signals. Db4 wavelet decomposes the travelling wave signals into detail signals and approximate signals, and these signals are combined with the two-terminal travelling wave location method to achieve fault location. And the wavelet detail coefficients are extracted to input to the proposed chaotic neural network. The results show that the criterion algorithm can effectively determine whether there are faults in the power system, the fault detection algorithm has the capabilities of locating the system faults accurately, and both algorithms are not affected by fault type, fault location, fault initial angle, and transition resistance.

Fault Location for Transmission Lines with Voltage and Current Measurements at One Bus

2014 ◽  
Vol 15 (5) ◽  
pp. 449-456
Author(s):  
Wanjing Xiu ◽  
Yuan Liao
Keyword(s):  
Power System ◽  
Transmission Lines ◽  
Fault Location ◽  
Positive Sequence ◽  
Distributed Parameter ◽  
Impedance Matrix ◽  
Simulation Studies ◽  
Location Method ◽  
Fault Resistance ◽  
Fault Type

Abstract This paper presents a novel fault location method for transmission lines. The proposed method extends an existing method to locate faults by employing voltage and current measurements at one bus, which can be the bus of the faulted line or be far away from the faulted line. The method is applicable if a loop exists that encloses the faulted line, and the bus, of which the voltage is used, and the branch, of which the current is used. The during-fault positive-sequence bus impedance matrix is derived. Then superimposed voltages and currents due to the fault are expressed as a function of fault location and related transfer and driving point impedances. Consequently, the fault location can be evaluated using the obtained measurements. The distributed parameter line model is adopted to consider the shunt capacitances of the line. The proposed method is independent of fault resistance and fault type. Simulation studies have been carried out based on a 27-bus power system, and promising results have been achieved.

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

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