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Study of a new method for power system transients classification based on wavelet entropy and neural network
- Source :
- International Journal of Electrical Power & Energy Systems. 33:402-410
- Publication Year :
- 2011
- Publisher :
- Elsevier BV, 2011.
-
Abstract
- The detection and classification of transient signals are widely applied in many fields of power system. The study of transient signal detection and classification is a sustaining focus of researchers as well as a difficult issue. There are still many problems needed to be solved in this area. Based on the wavelet transform (WT), the idea of entropy and weight coefficient is introduced, and the wavelet energy entropy (WEE) and wavelet entropy weight (WEW) are defined in this paper. The distribution picture of WEE and WEW along with scales are presented for the first time. PSCAD/EMTDC models for six types of transients, namely breaker switching, capacitor switching, short circuit fault, primary arc, lightning disturbance and lightning strike fault, are constructed. With WEE and WEW, the eigenvectors for the six transients are established and a model which uses the eigenvectors as the input of the BP (back-propagation) neural network is set up to realize the classification of these transients. The simulation has been executed based on a 500 kV transmission line model in China and the results show that feature extraction based on WEE and WEW can effectively discover the useful local features. With the help of neural network classifier, it has effective classifying result. This method is applicable in the power system.
- Subjects :
- Engineering
Signal processing
Artificial neural network
business.industry
Energy Engineering and Power Technology
Wavelet transform
Backpropagation
law.invention
Electric power system
Wavelet
law
Electrical network
Electronic engineering
Electrical and Electronic Engineering
Entropy (energy dispersal)
business
Algorithm
Subjects
Details
- ISSN :
- 01420615
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- International Journal of Electrical Power & Energy Systems
- Accession number :
- edsair.doi...........e1057277cbbad6ace54979173795ed63