Fault detection through discrete wavelet transform in overhead power transmission lines

Author:

Ahmed Nadeem1ORCID,Hashmani Ashfaq Ahmed2,Khokhar Sohail3,Tunio Mohsin Ali1,Faheem Muhammad4ORCID

Affiliation:

1. Department of Electrical Engineering Mehran University of Engineering & Technology Shaheed Zulfiqar Ali Bhutto Campus Khairpur Mir's Sindh Pakistan

2. Department of Electrical Engineering Mehran University of Engineering and Technology Jamshoro Sindh Pakistan

3. Department of Electrical Engineering Quaid‐e‐Awam University of Engineering Sindh Pakistan

4. School of Technology and Innovations University of Vaasa Vaasa Finland

Abstract

AbstractTransmission 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.

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

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