Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform
The transmission lines of an electricity system are susceptible to a wide range of unusual fault conditions. The transmission line, the longest part of the electricity grid, sometimes passes through wooded areas. Storms, cyclones, and poor vegetation management (including tree cutting) increase the...
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MDPI AG
2023-01-01
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| author | Pampa Sinha Kaushik Paul Chidurala Saiprakash Almoataz Y. Abdelaziz Ahmed I. Omar Chun-Lien Su Mahmoud Elsisi |
| author_facet | Pampa Sinha Kaushik Paul Chidurala Saiprakash Almoataz Y. Abdelaziz Ahmed I. Omar Chun-Lien Su Mahmoud Elsisi |
| author_sort | Pampa Sinha |
| collection | DOAJ |
| description | The transmission lines of an electricity system are susceptible to a wide range of unusual fault conditions. The transmission line, the longest part of the electricity grid, sometimes passes through wooded areas. Storms, cyclones, and poor vegetation management (including tree cutting) increase the risk of cross-country faults (CCFs) and high-impedance fault (HIF) syndrome in these regions. Recognizing and classifying CCFs associated with HIF syndrome is the most challenging part of the project. This study extracted signal characteristics associated with CCF and HIF syndrome using the Tunable Q Wavelet Transform (TQWT). An adaptive tunable Q-factor wavelet transform (TQWT) based feature-extraction approach for CCHIF fault signals with high impact, short response period, and broad resonance frequency bandwidth was presented. In the first part, the time–frequency distribution of the vibration signal is used to determine the distinctive frequency range. Adaptive optimal matching of the impact characteristic components in the vibration signal was achieved by optimizing the number of decomposition layers, quality factor, and redundancy of TQWT based on the characteristic frequency band. In the last, the TQWT inverse transform was utilized to recreate the best sub-band to boost its weak impact characteristics. The effectiveness of the approach is confirmed by simulation and experimental findings in signal processing. The best decomposition level for signature features that can be extracted has been decided by Minimum Description length (MDL). The IEEE 39-bus system is used to test the suggested approach with reactor switching and the Ferranti effect. |
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| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T09:35:22Z |
| publishDate | 2023-01-01 |
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| series | Mathematics |
| spelling | doaj.art-3c38e95e7ffc46a4b36e74d04d6687912023-11-16T17:21:43ZengMDPI AGMathematics2227-73902023-01-0111358610.3390/math11030586Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet TransformPampa Sinha0Kaushik Paul1Chidurala Saiprakash2Almoataz Y. Abdelaziz3Ahmed I. Omar4Chun-Lien Su5Mahmoud Elsisi6School of Electrical Engineering, KIIT University, Bhubaneswar 751024, IndiaDepartment of Electrical Engineering, BIT Sindri, Dhanbad 828123, IndiaSchool of Electrical Engineering, KIIT University, Bhubaneswar 751024, IndiaFaculty of Engineering & Technology, Future University in Egypt, Cairo 11835, EgyptElectrical Power and Machines Engineering Department, The Higher Institute of Engineering at El-Shorouk City, El-Shorouk Academy, Cairo 11837, EgyptDepartment of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, TaiwanDepartment of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, TaiwanThe transmission lines of an electricity system are susceptible to a wide range of unusual fault conditions. The transmission line, the longest part of the electricity grid, sometimes passes through wooded areas. Storms, cyclones, and poor vegetation management (including tree cutting) increase the risk of cross-country faults (CCFs) and high-impedance fault (HIF) syndrome in these regions. Recognizing and classifying CCFs associated with HIF syndrome is the most challenging part of the project. This study extracted signal characteristics associated with CCF and HIF syndrome using the Tunable Q Wavelet Transform (TQWT). An adaptive tunable Q-factor wavelet transform (TQWT) based feature-extraction approach for CCHIF fault signals with high impact, short response period, and broad resonance frequency bandwidth was presented. In the first part, the time–frequency distribution of the vibration signal is used to determine the distinctive frequency range. Adaptive optimal matching of the impact characteristic components in the vibration signal was achieved by optimizing the number of decomposition layers, quality factor, and redundancy of TQWT based on the characteristic frequency band. In the last, the TQWT inverse transform was utilized to recreate the best sub-band to boost its weak impact characteristics. The effectiveness of the approach is confirmed by simulation and experimental findings in signal processing. The best decomposition level for signature features that can be extracted has been decided by Minimum Description length (MDL). The IEEE 39-bus system is used to test the suggested approach with reactor switching and the Ferranti effect.https://www.mdpi.com/2227-7390/11/3/586cross-country high impedance faultjellyfishfault detectionTunable Q Wavelet transformgraph theory |
| spellingShingle | Pampa Sinha Kaushik Paul Chidurala Saiprakash Almoataz Y. Abdelaziz Ahmed I. Omar Chun-Lien Su Mahmoud Elsisi Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform Mathematics cross-country high impedance fault jellyfish fault detection Tunable Q Wavelet transform graph theory |
| title | Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform |
| title_full | Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform |
| title_fullStr | Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform |
| title_full_unstemmed | Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform |
| title_short | Identification of Cross-Country Fault with High Impedance Syndrome in Transmission Line Using Tunable Q Wavelet Transform |
| title_sort | identification of cross country fault with high impedance syndrome in transmission line using tunable q wavelet transform |
| topic | cross-country high impedance fault jellyfish fault detection Tunable Q Wavelet transform graph theory |
| url | https://www.mdpi.com/2227-7390/11/3/586 |
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