Comparative Analysis of Wavelet Based Algorithms for Protection of Power Transformer

  • Authors

    • S. Poornima
    • K. Ravindra
    https://doi.org/10.14419/ijet.v7i4.22.28697
  • inrush current, internal fault current, wavelet, Artificial Neural Network, Multi layer perceptron and Particle swarm optimization
  • The main theme of this paper is to protect the transformer from unnecessary tripping due to inrush current and to overcome drawbacks in traditional frequency transform based protection schemes. In this method, Inrush and Internal fault currents are simulated and Protection of power transformer is presented using a time-frequency transform. Pre-processing is done using Continuous Wavelet Transform for decomposition of signals. Preprocessed signals are used to train Artificial Neural Network architecture using Multi Layer Perceptron, Particle Swarm Optimization Techniques. Results are compared and better classification combination is chosen.

     

  • References

    1. [1] S.Poornima; K.Ravindra; “Comparison of CWT&DWT based Algorithms In Combination With ANN For Protection of Power Transformer†International Conference On Signal Processing, Communication, Power And Embedded System (SCOPES),pp.1781-1785,Jan.2016.

      [2] Reena Moon;R.K.Dhatrak;“A Study of Effect ofMagnetizing Inrush Current On Different Ratings of Transformers “International Journal of Advanced Research In Electrical, Electronics And Instrumentation Engineering (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 4,pp.9022-9027,April.2014.

      [3] Sagar Devidas Bole;â€Mitigation Of Inrush Current In Transformer†International Journal of Innovative Technology And Exploring Engineering(IJITEE) ISSN: 2278-3075, Volume-3, Issue-7, pp.117-119, Dec.2013.

      [4] G,Mokryani ;P,Siano; A,Piccolo â€Inrush Current Detection Based on Wavelet Transform and Probabilistic Neural Networkâ€, International Symposiumon Power Electronics, Electrical Drives, Automation And Motion ,SPEEDAM,pp.62-67,Oct.2010.

      [5] Atthapol Ngaopitakku; Anantawat Kunakorn; “Internal Fault Classification In Transformer Windings Using Combination of Discrete Wavelet Transforms†International Journal of Control, Automation, And Systems, Vol. 4, No. 3, pp. 365-371, June.2006.

      [6] Kleber Mariano Ribeiro; Roberto Alves BragaJúnior; Thelma Sáfadi; GrahamHorgan;â€Comparison Between Fourier And Wavelets Transforms In Biospeckle Signalsâ€. Applied Mathematics,pp.11-22.Nov.2013.

      [7] Y,NajafiSarem;E,Hashemzadeh,M.A.,Layegh;“TransformersFaultDetection Using Wavelet Transform†International Journal On “Technical And Physical Problems of Engineering†(IJTPE) Published By International Organization ofIOTPE,vol-4,pp.17-26,March .2012.

      [8] Yang Long; Ning Jing dong “A Wavelet Transform Based Discrimination Between Internal Faults And Inrush currents in Power Transformers†School of Computer And Information Engineering, Harbin University ofCommerce.May.2011.

      [9] I,El-Gallad,M. El-Ha Wary; A. A,Sallam,A. Kalas;“Swarm-Intelligence Trained Neural Network For Power Transformer Protectionâ€,pp.0265-0269,Jan.2001.

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  • How to Cite

    Poornima, S., & Ravindra, K. (2018). Comparative Analysis of Wavelet Based Algorithms for Protection of Power Transformer. International Journal of Engineering & Technology, 7(4.22), 202-206. https://doi.org/10.14419/ijet.v7i4.22.28697