Fault Type Identification Method based on Wavelet Detail Coefficients of Modal Current Components

Myint, Shwe; Wichakool, Warit

doi:10.1109/icsima.2018.8688796

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…However, the arriving time of these components cannot give the accurate and correct fault information and significantly one of the difficulties in loop distribution network is that the sensor can get many reflected signals from the fault point to face the complexity of detection of actual faulted length. Therefore, the proposed algorithm can choose the correct faulted section in [25], the accurate faulted path and uses the arriving time of faulted phase-based modal component [26] that can give higher accuracy than that of conventional methods with the consideration of noise effects, such as white noise. The paper is organized as section: 2 presents traveling wave method and modal transformation, research methodology is explained in section 3.…”

Section: Introductionmentioning

confidence: 99%

A simple faulted phase-based fault distance estimation algorithm for a loop distribution system

Myint

Wichakool

2022

IJEECS

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This paper presents a single ended faulted phase-based traveling wave fault localization algorithm for loop distribution grids which is that the sensor can get many reflected signals from the fault point to face the complexity of localization. This localization algorithm uses a band pass filter to remove noise from the corrupted signal. The arriving times of the faulted phase-based filtered signals can be obtained by using phase-modal and discrete wavelet transformations. The estimated fault distance can be calculated using the traveling wave method. The proposed algorithm presents detail level analysis using three detail levels coefficients. The proposed algorithm is tested with MATLAB simulation single line to ground fault in a 10 kV grounded loop distribution system. The simulation result shows that the faulted phase time delay can give better accuracy than using conventional time delays. The proposed algorithm can give fault distance estimation accuracy up to 99.7% with 30 dB contaminated signal-to-noise ratio (SNR) for the nearest lines from the measured terminal.

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Section: Introductionmentioning

confidence: 99%

A simple faulted phase-based fault distance estimation algorithm for a loop distribution system

Myint

Wichakool

2022

IJEECS

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“…In previous work [26,27], the amplitude maxima of detail coefficients of modal current components are used to classify fault type and faulty phase by comparing the classification parameters each other according to basic power system fault principles. However, this method may identify wrongly when the magnitude and frequency of the original signals are very small because the detail coefficients represent the high frequency content of the signals.…”

Section: Introductionmentioning

confidence: 99%

A high frequency reflected current signals-based fault type identification method

Myint

Wichakool

2020

IJEECS

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The main objective of this paper is to identify fault type and faulted phase focus on the time delay values of reflected phase and modal current signals. The proposed method identifies fault type with the help of amplitude maxima of detail wavelet coefficient of residual current. The time delay values of phase and modal current reflected signals are used to detect faulty phase instead of using threshold values. Using time delay as a fault type identification parameter is achieved to save the overall protection system operating time because time delay is also the main feature of traveling wave fault location method. Moreover, to ensure the applied wavelet filter, the proposed algorithm is tested with the detail information of the three mother wavelets, such as db4, db6 and db8 and chosen the highest classification accuracy. Various disturbance events were tested with changing different possible fault types, faulted-feeders, fault resistances, fault locations and fault inception times on a loop distribution system. The robustness of the proposed faulted phase selection algorithm is performed through MATLAB Simulation.

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Fault Type Identification Method based on Wavelet Detail Coefficients of Modal Current Components

Cited by 2 publications

References 9 publications

A simple faulted phase-based fault distance estimation algorithm for a loop distribution system

A simple faulted phase-based fault distance estimation algorithm for a loop distribution system

A high frequency reflected current signals-based fault type identification method

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