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Adaptive Overhead Transmission Lines Auto-Reclosing Based on Hilbert–Huang Transform

Author

Listed:
  • Arman Ghaderi Baayeh

    (Department of Electrical Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Kurdistan 66177-15175, Iran)

  • Navid Bayati

    (Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark)

Abstract

This paper presents a reliable and fast index to detect the instant of arc extinction for adaptive single-pole automatic reclosing (ASPAR). The proposed method is a simple technique for ASPAR on shunt compensated transmission lines using the Hilbert–Huang Transform (HHT). The HHT method is a combination of the empirical mode decomposition (EMD) and the Hilbert transform (HT). The first intrinsic mode function (IMF1) decomposed by EMD, which contains high frequencies of the faulty phase voltage, was used to calculate the proposed index. HT calculates the first IMF spectrum in the time-frequency domain. The presented index is the sum of all frequency contents below 55 Hz, which remains very low until the fault clearance. The proposed method uses a global threshold level and therefore no adjustment is needed for different transmission systems. This method is effective for various system configurations including different fault locations, line loading, and various shunt reactor configurations, designs, compensation rates, and placement. The performance of the method was verified using 324 test cases simulated in electromagnetic transient program (EMTP) related to a 345 kV transmission line. For all the test cases, the algorithm successfully operated with an average reclosing time delay of 32 ms.

Suggested Citation

  • Arman Ghaderi Baayeh & Navid Bayati, 2020. "Adaptive Overhead Transmission Lines Auto-Reclosing Based on Hilbert–Huang Transform," Energies, MDPI, vol. 13(20), pages 1-15, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5416-:d:429307
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    References listed on IDEAS

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    1. John Morales & Eduardo Muñoz & Eduardo Orduña & Gina Idarraga-Ospina, 2019. "A Novel Approach to Arcing Faults Characterization Using Multivariable Analysis and Support Vector Machine," Energies, MDPI, vol. 12(11), pages 1-21, June.
    2. Gyu-Jung Cho & Ji-Kyung Park & Seung-Hyun Sohn & Se-Jin Chung & Gi-Hyeon Gwon & Yun-Sik Oh & Chul-Hwan Kim, 2017. "Development of a Leader-End Reclosing Algorithm Considering Turbine-Generator Shaft Torque," Energies, MDPI, vol. 10(5), pages 1-14, May.
    3. Seung-Hyun Sohn & Gyu-Jung Cho & Chul-Hwan Kim, 2020. "A Study on Application of Recloser Operation Algorithm for Mixed Transmission System Based on Travelling Wave Method," Energies, MDPI, vol. 13(10), pages 1-15, May.
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    Cited by:

    1. Radu Plamanescu & Ana-Maria Dumitrescu & Mihaela Albu & Siddharth Suryanarayanan, 2021. "A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms," Energies, MDPI, vol. 14(7), pages 1-16, March.
    2. Liqiang Wei & Xianhai Pang & Jingang Su & Tao Han & Yufei Yao, 2022. "Improved Locating Method for Local Defects in XLPE Cable Based on Broadband Impedance Spectrum," Energies, MDPI, vol. 15(21), pages 1-14, November.
    3. Adam Dyśko & Dimitrios Tzelepis, 2022. "Protection of Future Electricity Systems," Energies, MDPI, vol. 15(3), pages 1-2, January.
    4. Zakarya Oubrahim & Yassine Amirat & Mohamed Benbouzid & Mohammed Ouassaid, 2023. "Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review," Energies, MDPI, vol. 16(6), pages 1-41, March.

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