The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON POWER SYSTEMS
Transactions ID Number: 89-890
Full Name: Gulden Kokturk
Position: Assistant Professor
Age: ON
Sex: Female
Address: Dokuz Eylul University, Dept. of Electrical&Electronics Eng., Campus of Kaynaklar, Buca, Izmir
Country: TURKEY
Tel: +90-232-4127165
Tel prefix:
Fax: +90-232-4531085
E-mail address: gulden.kokturk@deu.edu.tr
Other E-mails: ggkokturk@hotmail.com
Title of the Paper: Failure Analysis in Power System by the Discrete Wavelet Transform
Authors as they appear in the Paper: Ismail Yilmazlar, Gulden Kokturk
Email addresses of all the authors: gulden.kokturk@deu.edu.tr, yilmazlarismail@yahoo.com
Number of paper pages: 10
Abstract: Voltage variations are the most common power quality events that may result in corruption of different industrial processes. The electric power utility industry requires significant improvement in the quality of power provided to customers during faults or wide area system disturbance. Power system failure signals are monitored by using embedded systems. This paper presents an approach to provide the detection and location in time as well as the identification of power quality problems which are represented in both transient and fixed signals. The method was applied by using the discrete wavelet transform (DWT). The given signal is decomposed with wavelet transform and any change on the lower frequencies of the signal is detected at the finer wavelet transform resolution levels. The entropy contents of the signal are considered and a relationship between this entropy contents and the one of the corresponding component is accomplished. This paper shows wavelet trans!
form can be used to reduce data set while covering original information. Because of the reduced data set embedded systems can work within a wider time range. Paper helps power system analysis and classifies power system failures.
Keywords: discrete wavelet transform, wavelet entropy, power system failure, Daubechies wavelet, biorthogonal wavelet
EXTENSION of the file: .pdf
Special (Invited) Session: Power System Failure Analysis by Using The Discrete Wavelet Transform
Organizer of the Session: 633-333
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