Fault detection through discrete wavelet transform in overhead power transmission lines
Copyright policy )Fault detection through discrete wavelet transform in overhead power transmission lines
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.
- University of Sindh Pakistan
- University of Vassa Finland
- Mehran University of Engineering and Technology Pakistan
- Quaid-e-Awam University of Engineering, Science and Technology Pakistan
- University of Vaasa Finland
Technology, Artificial intelligence, Robustness (evolution), fi=Tietotekniikka|en=Computer Science|, Biochemistry, Gene, Electric power system, Engineering, Electric power transmission, Actuator, Materials Chemistry, fault simulation, Seismology, ta213, T, Physics, Q, Geology, fault diagnosis, Power (physics), Chemistry, Physical Sciences, Telecommunications, Fault detection and isolation, Transformer Fault Diagnosis, Wavelet, Science, Nanocomposite Dielectric Materials and Insulation, Materials Science, power system interconnection, Quantum mechanics, Real-time computing, Fault (geology), Condition Assessment of Power Transformers, Transmission line, FOS: Electrical engineering, electronic engineering, information engineering, fault location, Electrical and Electronic Engineering, ta113, Fault indicator, transmission lines, Electronic engineering, FOS: Earth and related environmental sciences, Fault Detection, Computer science, Adaptive Protection Schemes for Microgrids, Overhead (engineering), Operating system, Control and Systems Engineering, Electrical engineering, Discrete wavelet transform, Wavelet transform
Technology, Artificial intelligence, Robustness (evolution), fi=Tietotekniikka|en=Computer Science|, Biochemistry, Gene, Electric power system, Engineering, Electric power transmission, Actuator, Materials Chemistry, fault simulation, Seismology, ta213, T, Physics, Q, Geology, fault diagnosis, Power (physics), Chemistry, Physical Sciences, Telecommunications, Fault detection and isolation, Transformer Fault Diagnosis, Wavelet, Science, Nanocomposite Dielectric Materials and Insulation, Materials Science, power system interconnection, Quantum mechanics, Real-time computing, Fault (geology), Condition Assessment of Power Transformers, Transmission line, FOS: Electrical engineering, electronic engineering, information engineering, fault location, Electrical and Electronic Engineering, ta113, Fault indicator, transmission lines, Electronic engineering, FOS: Earth and related environmental sciences, Fault Detection, Computer science, Adaptive Protection Schemes for Microgrids, Overhead (engineering), Operating system, Control and Systems Engineering, Electrical engineering, Discrete wavelet transform, Wavelet transform
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