SavedAdd your journal

Journals / Turkish Journal of Electrical Engineering and Computer Science / 2005 / Cilt: 13 - Sayı: 1

Transformer Protection Using the Wavelet Transform

Okan ÖZGÖNENEL
Güven ÖNBİLGİN
Çağrı KOCAMAN
Pages
119–136
Publication Date
2005-01-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The simulated results presented clearly show that the proposed technique for power transformer protection facilitates the accurate discrimination between magnetizing inrush and fault currents in transformer protection.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper introduces a novel approach for power transformer protection algorithm.
📊
Key Findings & Data:Power system signals such as current and voltage have traditionally been analysed by the Fast Fourier Transform.
💡
Conclusion & Impact:The simulated results presented clearly show that the proposed technique for power transformer protection facilitates the accurate discrimination between magnetizing inrush and fault currents in transformer protection.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Differential Protection · Power Transformer · Discrete Wavelet Transform (DWT)

Abstract

This paper introduces a novel approach for power transformer protection algorithm. Power system signals such as current and voltage have traditionally been analysed by the Fast Fourier Transform. This paper aims to prove that the Wavelet Transform is a reliable and computationally efficient tool for distinguishing between the inrush currents and fault currents. The simulated results presented clearly show that the proposed technique for power transformer protection facilitates the accurate discrimination between magnetizing inrush and fault currents in transformer protection.

Özet

This paper introduces a novel approach for power transformer protection algorithm. Power system signals such as current and voltage have traditionally been analysed by the Fast Fourier Transform. This paper aims to prove that the Wavelet Transform is a reliable and computationally efficient tool for distinguishing between the inrush currents and fault currents. The simulated results presented clearly show that the proposed technique for power transformer protection facilitates the accurate discrimination between magnetizing inrush and fault currents in transformer protection.

🔖

Cite This Article

ÖZGÖNENEL, O., ÖNBİLGİN, G., KOCAMAN, Ç. (2005). Transformer Protection Using the Wavelet Transform. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 13 - Sayı: 1, 119–136. https://ajindex.com/articles/179329

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (13)

  1. M.A. Rahman, B. Jeyasurya”, A State-of-The-Art Review of Transformer Protection Algorithms, IEEE Trans- actions on Power Delivery, Vol. 3, No. 2, April 1988.
  2. M.A. Rahman, B. So, M. R. Zaman, M.A. Hoque”, Testing of Algorithms for A Stand-Alone Digital Relay for Power Transformers, IEEE Transactions on Power Delivery, Vol. 13, No. 2, April 1998.
  3. M. Habib, M.A. Marin”, A Comparative Analysis of Digital Relaying Algorithms for Differential Protection of Three Phase Transformers, IEEE Transactions on Power Systems, Vol. 3. No. 3, August 1988.
  4. M. Fancisco, A.A. Jose, Wavelet Based ANN Approach For Transmission Line Protection, IEEE Power Engi- neering Review, 2003.
  5. G.-M. Moises, W.N. Denise, A Wavelet-Based Differential Transformer Protection, IEEE Transactions on Power Delivery, Vol. 14, No. 4, October 1999.
  6. O. Ozgonenel, G. Onbilgin, C. Kocaman, Wavelets and Its Applications of Power System Protection, Gazi University Technical Education Faculty, Journal of Politechnic, 17:2, P:75-88, 2004, ISSN: 1003:9709. M. Fedi, et al., Joint Application of Continuous and Discrete Wavelet Transform on Gravity Data to Identify Shallow and Deep Sources, International Journal of Geophys, 156, 7-21, 2004.
  7. Y.W. Seng, Q. Wang, A. Wavelet Based Method to Discriminate Between Inrush Current and Internal Fault, Power System Technology, 2000. Proceedings. PowerCon 2000.
  8. International Conference on, Volume: 2, 4-7
  9. Dec., Page(s): 927 -931 vol. 2. L. M. Peilin, R.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.
  10. M. Vannucci, P.J. Brown, T. Fearn, A Decision Theoretical Approach to Wavelet Regression on Curves With a High Number of Regressors. Journal of Statistical Planning and Inference, 112(1-2), 195-212, 2003.
  11. M. Vannucci, F. Corradi, Model Shrinking of Wavelet Coefficients and Applications. Proceedings of the Section on Bayesian Statistical Science, 1996
  12. Joint Statistical Meetings, American Statistical Association. August 4-8,
  13. Chicago, Illinois, USA, pp. 117-123, 1996. C¸. Kocaman, Wavelet Based Transformer Protection Algorithm, Ondokuz Mayis University, Institute of Basic and Applied Sciences, MSc Thesis, 2003.