Fault detection through discrete wavelet transform in overhead power transmission lines
Ahmed, Nadeem; Hashmani, Ashfaq Ahmed; Khokhar, Sohail; Tunio, Mohsin Ali; Faheem, Muhammad (2023-09-28)
Ahmed, Nadeem
Hashmani, Ashfaq Ahmed
Khokhar, Sohail
Tunio, Mohsin Ali
Faheem, Muhammad
John Wiley & Sons
28.09.2023
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe20231010139439
https://urn.fi/URN:NBN:fi-fe20231010139439
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vertaisarvioitu
© 2023 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
© 2023 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Tiivistelmä
Transmission lines are a very important and vulnerable part of the power system. Power supply to the consumers depends on the fault-free status of transmission lines. If the normal working condition of the power system is disturbed due to faults, the persisting fault of long duration results in financial and economic losses. The fault analysis has an important association with the selection of protective devices and reliability assessment of high-voltage transmission lines. It is imperative to devise a suitable feature extraction tool for accurate fault detection and classification in transmission lines. Several feature extraction techniques have been used in the past but due to their limitations, that is, for use in stationary signals, limited space in localizing nonstationary signals, and less robustness in case of variations in normal operation conditions. Not suitable for real-time applications and large calculation time and memory requirements. This research presents a discrete wavelet transform (DWT)-based novel fault detection technique at different parameters, that is, fault inception and fault resistance with proper selection of mother wavelet. In this study, the feasibility of DWT using MATLAB software has been investigated. It has been concluded from the simulated data that wavelet transform together with an effective classification algorithm can be implemented as an effective tool for real-time monitoring and accurate fault detection and classification in the transmission lines.
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