Commenced in January 2007
Paper Count: 30076
Wavelet based ANN Approach for Transformer Protection
Authors: Okan Özgönenel
Abstract:This paper presents the development of a wavelet based algorithm, for distinguishing between magnetizing inrush currents and power system fault currents, which is quite adequate, reliable, fast and computationally efficient tool. The proposed technique consists of a preprocessing unit based on discrete wavelet transform (DWT) in combination with an artificial neural network (ANN) for detecting and classifying fault currents. The DWT acts as an extractor of distinctive features in the input signals at the relay location. This information is then fed into an ANN for classifying fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz laboratory transformer connected to a 380 V power system were simulated using ATP-EMTP. The DWT was implemented by using Matlab and Coiflet mother wavelet was used to analyze primary currents and generate training data. The simulated results presented clearly show that the proposed technique can accurately discriminate between magnetizing inrush and fault currents in transformer protection.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084232Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1473
 Zhonghao Yang and et all, "A New Technique For Power Transformer Protection Using Discrete Dyadic Wavelet Transform", Development in Power System Protection, Conference Publication No. 479, IEE, 2001.
 F. Jiang and et all, "Power Transformer Protection Based On Transient Detection Using Discrete Wavelet Transform (WT)", Power Engineering Society Winter Meeting, 2000. IEEE , Volume:3,23-27Jan.2000 Page(s): 1856 -1861 Vol.. 3.
 Xiangning Lin, Pei Liu, Shijie Cheng, "A Wavelet Based Scheme For Power Transformer Inrush Identification", Power Engineering Society Winter Meeting, 2000. IEEE , Volume: 3 , 23-27 Jan. 2000 Page(s): 1862 -1867 Vol.. 3
 Shaohua Jiao, Wanshun Liu, Peipu Su, Qixun Yang, Zhenhua Zhang; Jianfei Liu; "A New Principle of Discriminating Between Inrush Current and Internal Short Circuit of Transformer Based on Fuzzy Sets", Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on , Volume: 2 , 18-21 Aug. 1998 Page(s): 1086 -1090 vol. 2.
 Saleh, S.A., Rahman, M.A., "Off-line Testing of a Aavelet Packet-based Algorithm for Discriminating Inrush Current in Three-phase Power Transformers", Power Engineering, 2003 Large Engineering Systems Conference on , 7-9 May 2003, Page(s): 38 -42.
 Saleh A. Saleh and M.A. Rahman, "Transient Model of Power Transformer Using Wavelet Fitler Bank", Proceedings of The 2002 Large Engineering Systems Conference on Power Engineering, 2002 IEEE, 0-7803-7520-3.
 Qi Li, David, Chan Tat Wai, "Investigation of Transformer Inrush Current Using A Dyadic Wavelet", IEEE Catalogue No: 98EX137, 0- 7803-4495-2/98.
 Harumi Kamada, Nobuharu Aoshima, "Analog Gabor Transform Fitler with Complex First Order System", SICE, 97, July 29-31, Tokushima.
 Yong Sheng, Steven M. Rovnyak, "Decision Trees and Wavelet Analysis for Power Transformer Protection", Power Delivery, IEEE Transactions on , Volume: 17 Issue: 2 , April 2002, Page(s): 429 -433.
 Omar A.S. Youssef, "A Wavelet-Based Technique for Discrimination Between Faults and Magnetizing Inrush Currents in Transformer", IEEE Transactions on Power Delivery, Vol. 18, No. 1, January, 2003.
 Karen L. Buttler-Purry, Mustafa Bagriyanik, "Characterization of Transients in Transformers Using Discrete Wavelet Transforms", IEEE Transactions on Power Delivery, Vol. 18, No. 2, May, 2003.
 Moises Gomez-Morante, Denise W. Nicoletti, "A Wavelet Based Differential Transformer Protection", IEEE Transactions on Power Delivery, Vol. 14, No. 4, October, 1999.
 Sng Yeow Hong, Wang Qin, "A Wavelet Based Method to Discriminate Between Inrush Current and Internal Fault", Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on , Volume: 2 , 4-7 Dec. 2000, Page(s): 927 -931 vol. 2
 Peilin L. Mao, Raj K. Aggarwal, "A Novel Approach to the Classification of the Transient Phenomena in Power Transformers Using Combined Wavelet Transform and Neural Network", IEEE Transactions on Power Delivery, Vol. 16, No. 4, October, 2002.