A Fault Locator for Three-Terminal Lines Based on Wavelet Transform Applied to Synchronized Current and Voltage Signals

This paper presents a new method of fault location in transmission lines. The method is based on analysis of reflected traveling waves from fault point. Regarding weak frequency response of conventional output of capacitive voltage transformers (CVT), the proposed method receives the travelling waves from PLC output of CVTs, which has a good frequency response for high frequency travelling waves. Received signal is processed by wavelet transform, and signal characteristics are used as input for neural network. After training a neural network, the algorithm estimates the location of fault with reasonable accuracy. The algorithm is independent of the network configuration or length of the line, and is trained once for each voltage level. Numerical studies show the efficacy and accuracy of the algorithm for different configurations.

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“…While reference [7] and [18] use voltage travelling waves, reference [20] proposes to use both current and voltage waves to increase accuracy.…”

Section: A Travel Time Calculation Methodsmentioning

confidence: 99%

Fault location in transmission lines using neural network and wavelet transform

Raoofat

Mahmoodian

Abunasri

2015

2015 International Congress on Electric Industry Automation (ICEIA 2015)

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“…Fault location for three-terminal transmission lines is addressed in [ 103 , 105 ] where WT is used to analyze high and low frequency components generated by a fault. The proposed fault location scheme is based on travelling waves and on calculation of the fundamental frequency component.…”

Section: Fault Location Using Wavelet Transformmentioning

confidence: 99%

Fault Location Based on Synchronized Measurements: A Comprehensive Survey

Al-Mohammed¹,

Abido

2014

The Scientific World Journal

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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.

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“…The main problems of the traveling wave method is that it requires high sampling rates and has a difficulty in distinguishing between traveling waves from the fault and the remote end of the line. The wavelet transform analysis [3,4] is based on the highfrequency components of the fault generated signals on each terminal of the system. The limitation stated is that at low signal-noise ratio (SNR), the method becomes inefficient.…”

Section: Introductionmentioning

confidence: 99%

Fault Classification, Distance Location and Faulty Section Identification in Teed Transmission Circuits using Artificial Neural Network

Yadav¹,

Walayani²,

Thoke³

2012

IJCA

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An accurate fault classification and distance location algorithm for Teed transmission Circuit based on application of artificial neural networks (ANN) is presented in this paper. The proposed algorithm uses the fundamental component of voltage and current signals of each section measured at one end of teed circuit to detect, classify and locate the faults. ANN has the ability to classify the nonlinear relationship between measured signals by identifying different patterns of the associated signals. The adaptive protection scheme based on application of ANN is tested for shunt faults, varying fault location, fault resistance and fault inception angle. An improved performance is experienced once the neural network is trained adequately, which gives accurate results when faced with different system parameters and conditions. The entire test results clearly show that the fault is detected, classified and located within one cycle; thus the proposed adaptive protection technique is well suited for teed transmission circuit fault classification, distance location and faulty section identification. Results of performance studies show that the proposed neural network-based module can improve the performance of conventional fault selection algorithms.

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A Fault Locator for Three-Terminal Lines Based on Wavelet Transform Applied to Synchronized Current and Voltage Signals

Cited by 13 publications

References 13 publications

Fault location in transmission lines using neural network and wavelet transform

Fault location in transmission lines using neural network and wavelet transform

Fault Location Based on Synchronized Measurements: A Comprehensive Survey

Fault Classification, Distance Location and Faulty Section Identification in Teed Transmission Circuits using Artificial Neural Network

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