A real-time DWT and traveling waves-based multi-functional scheme for transmission line protection reinforcement

Jnaneswar, Kolli; Mallikarjuna, Balimidi; Saravanakumar, D.; Roy, Diptendu Sinha; Reddy, M. Jaya Bharata; Mohanta, Dusmanta Kumar

doi:10.1007/s00202-020-01117-0

Cited by 15 publications

(10 citation statements)

References 21 publications

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“…With the help of loss detection, many tests and diagnostics have been completed of the digital signal, including fault lines and similarities, displaying this information with LEDs, and making sound and seeing the alarm. safety warning [8,9]. Figure 1 shows the structure of the electrical protection circuit breaker.…”

Section: Literature Reviewmentioning

confidence: 99%

Electrical Line Fault Detection and Line Cut-Off Equipment and Control

Fu¹

2022

Journal of Control Science and Engineering

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In order to locate the leakage fault location of low-voltage electrical lines, cut off the power supply of electrical lines, and ensure the safety and reliability of the power supply network, this paper proposes an electrical line leakage fault detection system based on a signal trigger. Based on the research on the current leakage protection system of low-voltage electrical lines, the author puts forward that the leakage current of the selected test analog trigger signal is not less than twice the maximum value of the normal leakage current of electrical lines and equipment with STC15F2K60S2 single-chip microcomputer as the control core. The experimental results show that 30 mA is preferred for the sensitivity of the leakage fault test signal. When the rated leakage action current is equal to or less than 30 mA, the protection action time is required to be less than 0.1 s, and when the rated leakage action current is greater than 30 mA, it is required to be less than 0.2 S. The device is a supplement to the traditional leakage protection device. According to the comparison between the indirect leakage detection and direct leakage detection results and the actual leakage position distance, the error is within 10%. It is proved that the system meets the actual needs and improves the protection performance of the leakage protection system of low-voltage electrical lines.

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Section: Literature Reviewmentioning

confidence: 99%

Electrical Line Fault Detection and Line Cut-Off Equipment and Control

Fu¹

2022

Journal of Control Science and Engineering

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“…In DWT, the wavelet decomposition layer is set to 3, and the wavelet basis function db4 is used here as recommended in Ref. [5].…”

Section: Simulation Resultsmentioning

confidence: 99%

Adaptive Morphological Filter for Extracting Features of Fault on Transmission Line

Luo

Zhang

2022

IEEJ Transactions Elec Engng

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This letter proposes an adaptive feature extraction method based on mathematical morphology for fault detection and location on transmission line. Multi‐scale morphological operation is designed where triangular structural elements are employed with the heights adjusted adaptively according to the input signal. Extensive simulation studies were carried out under different fault conditions, and the results demonstrated the effectiveness of the proposed method. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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“…Data used is PMU measurements from two ends of a transmission line. Researchers in [13] propose a Discrete Wavelet transform-based scheme for transmission line protection. Features extracted are the energy values of the wavelet decomposition.…”

Section: A Related Workmentioning

confidence: 99%

“…Features extracted are the energy values of the wavelet decomposition. In [30] and [13], the data sets considered are from PMUs placed on both transmission line ends. PMU deployment on a transmission line necessitates installing the sensing devices (current and potential transformers) and the communication infrastructure with the measurement unit.…”

Section: A Related Workmentioning

confidence: 99%

“…Signal processing techniques, Wavelet transform, Wavelet multivariate analysis, and Wavelet entropy analysis are the most applied feature extraction methods [9], [10], [11], [12] for FD&C in transmission lines. In [13] and [14], faults are classified using the energy values of the wavelet approximation coefficients. Reference [15] proposes an ensemble feature extraction method using wavelet transform.…”

Section: Introductionmentioning

confidence: 99%

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Fault Detection and Classification for Wide Area Backup Protection of Power Transmission Lines Using Weighted Extreme Learning Machine

2022

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The changing landscape of power grids with distributed energy sources and power electronic devices has led to increasing relay maloperations. Wide area backup protection is necessary for the resolution of faults and for a reliable power grid. This paper presents detecting and classifying faults in transmission lines for wide-area backup protection using phasor measurement units (PMU) data. The faults are detected and classified using a Weighted Extreme Learning Machine (WELM) algorithm, which considers the variable distribution of data among the different classes using a weighted approach. The PMU signal data used were generated by the simulation of an IEEE 39 bus test system in the PowerWorld/OpenPDC/MATLAB environment. For classification, the input features data were derived using a wavelet transform-based ensemble feature extraction technique, and the WELM classifier was optimized using Particle Swarm Optimization (PSO). The PSO optimized WELM (PSO-WELM) model trained on PMU data detected faults with 100% accuracy and classified them into different types with an accuracy of 99.85%. It is validated that the PSO-WELM outperforms other known classifiers on performance comparison. The model also classified noisy data with a signal-to-noise ratio (SNR) as low as 10 dB and with an accuracy of 97%.

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A real-time DWT and traveling waves-based multi-functional scheme for transmission line protection reinforcement

Cited by 15 publications

References 21 publications

Electrical Line Fault Detection and Line Cut-Off Equipment and Control

Electrical Line Fault Detection and Line Cut-Off Equipment and Control

Adaptive Morphological Filter for Extracting Features of Fault on Transmission Line

Fault Detection and Classification for Wide Area Backup Protection of Power Transmission Lines Using Weighted Extreme Learning Machine

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