Fault diagnosis in distribution power systems using stationary wavelet transform and artificial neural network
- 1 December 2017
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2017 7th International Conference on Power Systems (ICPS)
Abstract
Short-circuit faults are the most commonly occurred transient events in a distribution system. Therefore, it is necessary to analyze fault transients to detect and localize. Detection and localization of faults in a distribution power system are very difficult due to the complex structure of the system. This paper presents an efficient time-frequency based detection and localization algorithm for distribution system faults. The proposed algorithm suggests a feature extraction from the transient signal using Stationary Wavelet Transform and machine-learning using Artificial Neural Network to detect and localize fault transients. The result obtained in this study proves the reliability of the proposed algorithm by achieving better accuracy in fault detection and localization.Keywords
This publication has 14 references indexed in Scilit:
- Continuous wavelet transform and artificial neural network based fault diagnosis in 52 bus hybrid distributed generation systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approachInternational Journal of Electrical Power & Energy Systems, 2015
- Adaptive Threshold Neural Spike Detector Using Stationary Wavelet Transform in CMOSIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2015
- A novel wavelet transform aided neural network based transmission line fault analysis methodInternational Journal of Electrical Power & Energy Systems, 2009
- Wavelet and neuro-fuzzy based fault location for combined transmission systemsInternational Journal of Electrical Power & Energy Systems, 2007
- A novel distance protection scheme using time-frequency analysis and pattern recognition approachInternational Journal of Electrical Power & Energy Systems, 2006
- Fault classification and location using HS-transform and radial basis function neural networkElectric Power Systems Research, 2006
- Artificial Neural Network and Support Vector Machine Approach for Locating Faults in Radial Distribution SystemsIEEE Transactions on Power Delivery, 2005
- Wavelet transform-based impulse fault pattern recognition in distribution transformersIEEE Transactions on Power Delivery, 2003
- A new approach to fault section estimation in power systems using Ant systemElectric Power Systems Research, 1999